\r\n\tThe aim of this book is to provide the reader with a comprehensive state-of-the-art in artificial neural networks, collecting many of the core concepts and cutting-edge application behind neural networks and deep learning.
",isbn:"978-1-83962-375-2",printIsbn:"978-1-83962-374-5",pdfIsbn:"978-1-83962-376-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"5cc6cd7972551be6cfc4d3c87bf8fb5c",bookSignature:"Dr. Pier Luigi Mazzeo and Dr. Paolo Spagnolo",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10390.jpg",keywords:"Recurrent, Recursive Nets, Face Recognition, Crowd Analysis, Different Applications, Object Detection, Classification, Visual Tracking, Speech Recognition, Grams, Reinforcement Learning, 3-D Map",numberOfDownloads:382,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 25th 2020",dateEndSecondStepPublish:"October 23rd 2020",dateEndThirdStepPublish:"December 22nd 2020",dateEndFourthStepPublish:"March 12th 2021",dateEndFifthStepPublish:"May 11th 2021",remainingDaysToSecondStep:"6 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Author and co-author of more than 80 works in national and international journals, conference proceedings, and book chapters, with Ph.D. in Computer Science Engineering.",coeditorOneBiosketch:"Dr. Spagnolo received the engineering degree in computer science from the University of Lecce, Italy. Since 2002 he has been with the Italian National Research Council. His work includes more than 80 publications on AI.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"17191",title:"Dr.",name:"Pier Luigi",middleName:null,surname:"Mazzeo",slug:"pier-luigi-mazzeo",fullName:"Pier Luigi Mazzeo",profilePictureURL:"https://mts.intechopen.com/storage/users/17191/images/system/17191.jpeg",biography:"Pier Luigi Mazzeo received the engineering degree in computer science from the University of Lecce, Lecce, Italy, in 2001. \nSince 2015 he has been with Institute of Applied Sciences and Intelligent Systems of the Italian National Research Council, Lecce, Italy. The most relevant topics, in which he is currently involved, include algorithms for video object tracking , face detection and recognition, facial expression recognition, deep neural network (CNN) and machine learning.\nHe has taken part in several national and international projects and he acts as a reviewer for several international journals and for some book publishers. He has been regularly invited to take part in the Scientific Committees of national and international conferences. \nDr. Mazzeo is author and co-author of more then 80 works in national and international journals, conference proceedings and book chapters.",institutionString:"Institute of Applied Sciences and Intelligent Systems (CNR)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Institute of Applied Science and Intelligent Systems",institutionURL:null,country:{name:"Italy"}}}],coeditorOne:{id:"20192",title:"Dr.",name:"Paolo",middleName:null,surname:"Spagnolo",slug:"paolo-spagnolo",fullName:"Paolo Spagnolo",profilePictureURL:"https://mts.intechopen.com/storage/users/20192/images/system/20192.jpg",biography:"Paolo Spagnolo received the engineering degree in computer science from the University of Lecce, Lecce, Italy, in 2002.\nSince then he has been with the Italian National Research Council.\nHe has been working on several research topics regarding Artificial Intelligence and Computer Vision studying techniques and methodologies for multidimensional digital signal processing; linear and non-linear signal characterization; signal features extraction; supervised and unsupervised classification of signals; deep neural network (CNN).\nDr. Spagnolo is an author of over 80 papers on Artificial Intelligence. He also acts as a reviewer for several international journals.\nHe has also participated in a number of international projects in the area of image and video analysis and has been regularly invited to take part in the Scientific Committees of national and international conferences.",institutionString:"Institute of Applied Sciences and Intelligent Systems (CNR)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Institute of Applied Science and Intelligent Systems",institutionURL:null,country:{name:"Italy"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"9",title:"Computer and Information Science",slug:"computer-and-information-science"}],chapters:[{id:"75352",title:"Speech Enhancement Based on LWT and Artificial Neural Network and Using MMSE Estimate of Spectral Amplitude",slug:"speech-enhancement-based-on-lwt-and-artificial-neural-network-and-using-mmse-estimate-of-spectral-am",totalDownloads:17,totalCrossrefCites:0,authors:[null]},{id:"75265",title:"Deep Learning for Subtyping and Prediction of Diseases: Long-Short Term Memory",slug:"deep-learning-for-subtyping-and-prediction-of-diseases-long-short-term-memory",totalDownloads:62,totalCrossrefCites:0,authors:[{id:"179217",title:"Prof.",name:"Hayrettin",surname:"Okut",slug:"hayrettin-okut",fullName:"Hayrettin Okut"}]},{id:"75193",title:"The Digital Twin of an Organization by Utilizing Reinforcing Deep Learning",slug:"the-digital-twin-of-an-organization-by-utilizing-reinforcing-deep-learning",totalDownloads:68,totalCrossrefCites:0,authors:[null]},{id:"75690",title:"Application of Artificial Neural Networks to Chemical and Process Engineering",slug:"application-of-artificial-neural-networks-to-chemical-and-process-engineering",totalDownloads:52,totalCrossrefCites:0,authors:[null]},{id:"75628",title:"Material Classification via Machine Learning Techniques: Construction Projects Progress Monitoring",slug:"material-classification-via-machine-learning-techniques-construction-projects-progress-monitoring",totalDownloads:29,totalCrossrefCites:0,authors:[null]},{id:"75329",title:"Risk Assessment and Automated Anomaly Detection Using a Deep Learning Architecture",slug:"risk-assessment-and-automated-anomaly-detection-using-a-deep-learning-architecture",totalDownloads:41,totalCrossrefCites:0,authors:[null]},{id:"75342",title:"Application of Deep Learning Methods for Detection and Tracking of Players",slug:"application-of-deep-learning-methods-for-detection-and-tracking-of-players",totalDownloads:53,totalCrossrefCites:0,authors:[null]},{id:"74861",title:"Modeling the Behavior of Amphiphilic Aqueous Solutions",slug:"modeling-the-behavior-of-amphiphilic-aqueous-solutions",totalDownloads:7,totalCrossrefCites:0,authors:[null]},{id:"75196",title:"The Application of Artificial Neural Network to Predicting the Drainage from Waste Rock Storages",slug:"the-application-of-artificial-neural-network-to-predicting-the-drainage-from-waste-rock-storages",totalDownloads:53,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"297737",firstName:"Mateo",lastName:"Pulko",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/297737/images/8492_n.png",email:"mateo.p@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"8725",title:"Visual Object Tracking with Deep Neural Networks",subtitle:null,isOpenForSubmission:!1,hash:"e0ba384ed4b4e61f042d5147c97ab168",slug:"visual-object-tracking-with-deep-neural-networks",bookSignature:"Pier Luigi Mazzeo, Srinivasan Ramakrishnan and Paolo Spagnolo",coverURL:"https://cdn.intechopen.com/books/images_new/8725.jpg",editedByType:"Edited by",editors:[{id:"17191",title:"Dr.",name:"Pier Luigi",surname:"Mazzeo",slug:"pier-luigi-mazzeo",fullName:"Pier Luigi Mazzeo"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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1. Introduction
\n
Block copolymer (BCP) composed of two (more) immiscible polymers form variety structures with the periodicity of several tens nanometer both in bulk and thin films. BCP thin film has attracted great attention as an applicable material to various fields, e.g., solar cell [1–3], nanolithography [4–6], and size-selective separation [7, 8]. In bulk state, microphase-separated structure is predicted by the Flory-Huggins interaction parameter, the degree of polymerization, and the volume fraction of blocks [9], whereas in thin film, film thickness [10, 11] and substrate-polymer interaction and/or also polymer-air interaction[12] must be taken into consideration. Controlling morphology, orientation and size of the structures are necessary for practical use although phase-separation behavior of BCP in thin film becomes more complicated. This has motivated numerous orientation control methodology studies that have examined the influence of film thickness [10, 11, 13, 14], surface/or interfacial free energy [14–17], surface topology [15, 18, 19], external applied fields (shear-induced [4, 20], electric field [21], magnetic field [22], and light-driven [23, 24]), solvent vapor or thermal annealing[25–30], and directional solidification [31–33]. Since functionality and physical property are also strongly related to the structure and the mobility in the vicinity of interface, revealing structure in detail is required. Suitable characterization techniques are required to monitor the structures of BCP both laterally and in-depth. Several approaches have been used to find BCP structures. Atomic force microscopy (AFM), electron microscopy, dynamic secondary ion mass spectrometry (DSIMS), X-ray photoelectron spectroscopy (XPS), grazing incidence small angle X-ray or neutron scattering (GISAXS, GISANS), X-ray or neutron reflectivity (XRR, NR), etc. have been used to study the structure of BCP thin films. AFM can enable an access of the information only near the surface although the surface structure can be directly observed and easily understandable. Electron microscopy is a powerful tool for visually examining a cross-sectional view of polymeric thin films in two-and three-dimensional real space [34]. DSIMS can elucidate the BCP morphology and the self-diffusion of polymer chains in thin films along a depth direction [35]. Time-of-flight (ToF) SIMS using ion cluster beam was reported to be a particularly well-suited technique that enables the in-depth profiling of polymers [36, 37]. X-ray photoelectron spectroscopy depth profiling with C60+ sputtering revealed the ion distribution in lithium salt-doped BCP thin films [38, 39].Electron microscopy, DSIMS, and XPS techniques are essentially accompanied by the destruction of specimen because of processing such as sectioning or etching for analysis. In particular, it is important to take into account the deformation and losing of a precise original spatial coordinate induced by sectioning and chemical reactions induced by etching in the analysis of results obtained by these techniques. In contrast, neutron reflectivity (NRR) measurements enable a practically nondestructive analysis of depth profiles and ordering of microphase-separated structure in BCP thin films [40, 41]. However, the NRR provides structural information (density profile) only in the vertical direction to the sample surface and lateral information of the structure is inaccessible. In addition, accuracy of the density profile (depth-resolved information) perpendicular to the surface becomes worse when the film thickness is large for analyzing periodicity of microphase-separated structure. Generally, NRR depth profiling is suited for very thin film (less than 100 nm) as in the above case. GISAXS is another very powerful tool for understanding the nanostructure in both vertical and lateral directions of organic thin film (BCP thin film). And GISAXS is essentially nondestructive method under the condition of the no radiation damage of X-rays [42–47]. Commonly, SAXS and GISAXS methods have been conducted using hard X-rays with energy range of 6–14 keV. However, under these conditions, the penetration depth of X-rays rapidly reaches the thickness scale of the organic materials in the vicinity of the critical angle αC of total reflection at the polymeric surface, which is making depth-resolved GISAXS measurements with hard X-rays totally impractical. A depth-sensitive GISAXS method using tender X-ray (1.77 keV) was first reported for the BCP thin film by Okuda et al. [48] and Wernecke et al. [49]. They investigated the structural relaxation near the surface and the dynamic heterogeneity of polymer chains in thin films. At even lower X-ray photon energies, near the adsorption K edges of the polymeric materials (the oxygen, nitrogen, and carbon K edges), the fine structure of the adsorption edge can be utilized in GISAXS as reported by Ruderer et al. [50]. The grazing-incidence resonant soft X-ray (GI-RSoXS) has been applied for polymer blend thin films with low contrast in the real part of the refractive index for the hard X-rays but with significant differences in the soft X-ray regime. Furthermore, the X-ray penetration depth is drastically affected by the changes in the X-ray photon energy across the K-edge. The surface-and volume-sensitive structure of polymer blend films had been analyzed using this technique [50]. Similar to the GISAXS, GISANS has been developed by Müller-Buschbaum and co-workers. GISANS is a perfectly nondestructive approach for structure analysis and has essentially the same capability for surface-sensitive [51], interface-sensitive (structural information near the polymer-substrate interface enabled by the ability of the neutrons to go through the substrate) [52, 53], and depth-sensitive analysis [54]. Moreover, in time-of-flight mode GISANS (ToF-GISANS) [52, 55] a broad wavelength band is used instead of a single neutron wavelength, i.e., a range of different scattering vectors is directly probed by the measurement under a fixed angle of incidence. At an appropriate incident angle, it is possible to simultaneously conduct surface- and bulk-sensitive measurements. While GISANS possesses advantages as compared with the GISAXS, GISANS experiments still remain very rare because GISANS requires very high-flux sources to measure the much weaker signals in grazing-incidence geometry and the need for deuterium labeling (in some cases, of course, this is beneficial for structure analysis by tuning the contrast). These GISANS techniques have been well summarized in the reviews [56].
\n
In this chapter, recent advanced GISAXS experiment utilizing low-energy X-rays will be introduced. GISAXS probes the complex nano- and microphase-separated structure in polymer thin films. Especially, tuning the energy of GISAXS in the tender and soft X-ray regime allows to the tailoring of X-ray penetration depth and contrast and thereby the probing of more complex morphologies in polymer thin films. GI-RSoXS has been applied for polymer blend thin films with low contrast in the real part of the refractive index for the hard X-rays but with significant differences in the soft X-ray regime. Furthermore, the X-ray penetration depth is drastically affected by the changes in the X-ray photon energy across the K-edge. The surface- and volume-sensitive structure of polymer blend films had been analyzed using this technique.
\n
\n
2. Grazing-incidence small angle X-ray scattering
\n
Incident X-ray beam goes into the sample surface at a very shallow angle αi (normally less than 1°). Scattering is measured with a two-dimensional detector as a function of the exit angle αf (out-of-plane angle) and the in-plane angle 2Θ. The magnitude of the scattering vector is given by q = 4πsinθ/λ(λ: wavelength of X-ray, 2θ: scattering angle). The scattering vector qz means the component vertical to the film surface. The qx and qy are the components of scattering vectors in the sample surface, perpendicular to and directed to the X-ray beam, respectively. For each data set I(y, z), pixels of the detector were converted into exit angle αf normal to the sample surface and a scattering angle 2Θ parallel to the surface by simple geometrical consideration. The amplitude of scattering vector q is composed of qx, qy, and qz related to the experimental angles by
As shown in Figure 1, typical sample-to-detector distances (SSD) for GISAXS are of the order of 1–2 m. In the case of small angle scattering, the two-dimensional detector probes mainly the qy and qz information because qx is very small and the curvature of the Ewald sphere is negligible. The calculation of the out-of-plane scattering vector is considerably complex. Above critical angle αC of polymeric materials, the theoretical penetration depth is much larger than the film thickness (order of micro-meter) (when hard X-ray is normally used) as shown in Figure 2. The transmitted wave can therefore be reflected at the polymer-substrate interface in combination with diffraction from the structures in the thin film. Under the assumption that each X-ray scatters no more than once from the objects and there is no transmission through the substrate, there are four possible scattering events to happen, additionally refraction at the sample surface (air-polymer interface) (Figure 3).
\n\n
Figure 1.
Schematic illustration of the scattering geometry used in GISAXS. The sample surface is inclined by incident angle with respect to the horizon. The exit and in-plane angles are denoted αi and 2Θ, reepectively.
\n
Figure 2.
Penetration depth calculated for a block copolymer (S2VP) film for different X-ray energies, 12.397, 8.265, 3.60, and 2.40 keV.
\n\n
Figure 3.
Four scattering events, demonstrating different combinations of reflection from the substrate with diffraction from the objects.
\n
\n
3. Depth-resolved structure analysis of microphase-separated structures in block copolymer thin film by grazing-incidence small angle X-ray scattering utilizing tender X-ray
\n
3.1. Cylindrical microdomain in block copolymer thin film [57]
\n
In this section, GISAXS measurement with low energy (tender) X-ray (2.40 keV) is introduced in order to precisely elucidate the depth profile of a microphase-separated structure (hexagonally packed cylinders) of a polystyrene-b-poly (2-vinylpyridine (S2VP) thin film on a silicon wafer with the cylindrical microdomains (poly (2-vinylpyridine): P2VP) oriented parallel to the substrate after the appropriate thermal annealing in vacuum. The cylindrical domains in the S2VP thin film were preferentially oriented parallel to the surface of the substrate induced by the surface free energies and/or an interfacial interaction between S2VP and the substrate. In GISAXS, the structural parameters of the cylindrical domains in both the lateral and vertical directions are accessible because the diffraction spots appear with the offset in the qy direction.
\n
S2VP thin film (number average molecular weight Mn = 26,400, molecular weight polydispersity index = 1.24, and ϕPS = 76.3 vol%) was prepared by spin casting from toluene solution (10 wt%) of S2VP onto a silicon wafer substrate at 3000 rpm for 30 s. Subsequently, the S2VP thin film was thermally annealed under vacuum at 170 °C for 48 h. The sample surface was composed of PS component (X-ray photoelectron spectroscopy and water contact angle [58], predicted by surface free energies of components [59]) was a very flat and smooth examined by atomic force microscopy and optical white-light interferometer microscopy measurements.
\n
Tender X-ray GISAXS measurement (room temperature) was performed at BL15A2 [60] at the Photon Factory, KEK, Tsukuba in Japan. The BL15A2 is an undulator beamline where X-rays in a wide energy range from 2.1 to 15 keV (energy resolution is 2 × 10−4) is available. In this study, the energy of X-ray was set at 2.40 keV (the wavelength of 5.16 Å) and the sample-to-detector distance (SDD) was 830 ± 5 mm. The accuracy of the camera lengths arises from the scattering vector calibration on a detector with a standard specimen and a footprint of the incident beam on the sample surface (sample size of c.a.1 cm). The X-ray incident angle was varied between 0.290° and 0.620° and PILATUS 2M designed for usage in vacuum was used as a detector for the 2D scattering pattern. X-ray exposure time of 300 s was sufficient to obtain a clear scattering pattern. Hard X-ray (wavelength 1.0 Å) GISAXS measurements were performed at BL10C in Photon Factory and BL03XU57 in SPring-8, Harima, Japan using PILATUS 2M and CCD (Hamamatsu Photonics) detectors with SDD of 2.3 m. All detectors were calibrated using lead stearate prepared in-house (d = 5.01 nm, calibrated).
\n
The X-ray penetration depth Λ is defined as the depth at which the X-ray intensity is attenuated by 1/e. The value of Λ depends on X-ray energy (wavelength λ), the critical angle, αC, of total reflection, and the incident angle αi. Surface roughness influences practically the penetration depth of X-rays because various αi are provided. The roughness of the surface used here is regarded as sufficiently small to estimate the penetration depth as evidenced by the clear observation of the critical angle in XRR. Under experimental conditions with the ideally flat surface, Λ is given by
\n
Λ=λ4π2(αi2−αc2)2+4β2−(αi2−αc2),E2
\n
where β is the imaginary part of the complex refractive index. The critical angle αC is specified as αc~2δ where δ is deviation from the real part of the refractive index, δ and β are given by
\n
δ=(reλ2NA/2π)ρM∑ZwZ(f0Z+fZ\'(E))/∑ZwiAZ,E3
\n
β=(reλ2NA/2π)ρM∑ZwZfZ\'\'(E)/∑ZwZAZ,E4
\n
where re is the classical electron radius (2.82 × 10−5 Å), NA is Avogadro’s number, ρM is the mass density, wZ is the fraction of element Z, AZ, is the relative atomic mass,f0Z is the nonresonant term of the atomic scattering factor corresponding to the atomic number, and fZ\'(E) and fZ\'\'(E) are the real and imaginary parts of the anomalous dispersion for the incident X-ray energy E, respectively. For example, here we used 4.1468 × 10−5 for δ and 7.0239 × 10−7 for β of PS at 2.40 keV. The αc value of S2VP thin film using GISAXS and XRR measurements was obtained. The calculated S2VP penetration depth is shown in Figure 2. It is hard to precisely control the penetration depth Λ at the nanometer scale for GISAXS experiment conducted using hard X-rays (8–12.4 keV) because the value of Λ rises steeply at αC. On the other hand, as the X-ray energy decreases, Λ changes more gradually near the critical angle and shows decreased depth values at angles even greater thanαC. Hence, better control ofΛ is expected for depth-resolved GISAXS measurements using tender X-ray (2.40 keV) because of the critical angle and attenuation coefficient values that are much greater than those for the hard X-rays.
\n\n
GISAXS measurements of the S2VP thin film (thickness of 420 nm) using tender X-ray were performed at various incident angles and many Bragg spots were measured as shown for large αi in Figure 4. All spots were assigned to parallel oriented hexagonally packed cylinders. GISAXS patterns at approximately qy of 0.26 nm−1 are presented in Figure 4(c) and (d) and show a remarkable elongation of the Bragg spots in the qz direction for smallerαi. One-dimensional scattering profiles vertically cut at qy = 0.26 nm−1 with various incident angles are shown in Figure 5. Bragg peaks were assigned to the scattering from transmitted (denoted by T) and reflected (denoted by R) beams by the substrate. These two scattering events are typically noticeable in GISAXS measurements [45, 46]. The second-order peaks derived from (11) reflection at qz approximately 0.6 and 0.7 nm−1 were used for structure analysis because the primary peak from the (10) plans was partially invisible due to the detector gap. The magnitudes of the Bragg spot full widths at half maximum (FWHM) varied in the vicinity of theαC, with larger FWHM values observed at smaller incident angles.
\n
Figure 4.
2D-GISAXS (with λ of 5.166Å) patterns of S2VP-25k thin film annealed for 48 h at 170°C. (a) αi was set at 0.62° (αi>αC), (b) 0.54°(αi>αC), (c) 0.52°(αi<αC), and (d) 0.49° (αi > αC). Schematic illustration represents the cross section of cylindrical microdomains in the thin film forming HEX aligned parallel to the substrate.
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Figure 5.
One-dimensional GISAXS profiles along qz direction obtained by vertical cut at qy = 0.26 mn−1. Reprinted with permission from Saito et al. [57]. Copyright 2015 American Chemical Society.
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The observed peak broadening can be interpreted by the change in the penetration depth. While generally such broadening can be understood by either the grain size effect and/or disordering of the crystal lattice, the FWHM in the qy indicated no change irrespective of the incident angles as shown in Figure 6, eliminating the influence of the lattice disordering because the broadening was mainly seen in the qz direction and the size effect was dominantly considered. Rather, the broadening in this case is because of the reduction in the size of the observed region. The FWHM of a scattering peak depends on the grain size of a crystal, as expressed by the Laue function, L(q)
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Figure 6.
FWHM values of (11) Bragg spots obtained experimentally and calculated using Eq. (6). Reprinted with permission from Saito et al. [57]. Copyright 2015 American Chemical Society.
where N is the number of the reflection plane and b is the unit lattice vector related to z-direction normal to the surface. Here, the X-ray wave decays exponentially, and considering attenuation decay, the Laue function can be re-expressed as
where D01 is the periodicity of the (01) plane. Since the scattering intensity is proportional to the square of the Laue function, the FWHM can be calculated simply. The FWHM of the Bragg spots of the T (11) plane in qz direction experimentally obtained is shown in Figure 6. The calculated values for FWHM in the qz direction for the penetration depth Λ given by Eq. (2) are also plotted in Figure 6. The change in the calculated width shows the same trend as the experimental results, indicating that the broadening of the Bragg spots can be explained by the size effect determined by the depth Λ. Thus, the observed region of GISAXS measurement can be controlled with the incident angle, enabling depth-resolved GISAXS.
\n
When αi<αC, X-rays travel on the surface of the film and cannot propagate in the film. Only the evanescent wave can penetrate from the sample surface into the film. In this situation, the scattering peak αz along the qz direction is observed at the position given by the sum of the incident angle and the true scattering angle αS derived from the period of the observed structure. Thus, αs can be given as follows:
\n
αS=αZ−αiE7
\n
Using above relation, the true qz value of the (11) spot can be estimated from the experimental peaks. On the other hand, in the case of αi<αC, an X-ray wave can travel into the film. The X-ray first refracts at the sample surface, goes through the film, is reflected by the interface between the sample and substrate, and finally exits out of the film surface with refraction as shown in Figure 3. Normally, some scattering events in GISAXS experiments occur because of the refracted X-rays at the polymer surface and reflected X-ray on the substrate surface, resulted in appearance of a number of scattering peaks. The scattering cross-section for GISAXS of the block copolymer thin film has been calculated within the framework of the distorted wave Born approximation (DWBA) [61]. Lee et al. [44], Yoon et al. [44, 45], and Busch et al. [46, 47] introduced the DWBA (or a combination of Bragg’s and Snell’s laws, refraction and reflection) to estimate the scattering peak positions. Scattering intensity due to the incident X-ray (transmission) and reflected X-ray (reflection) were pronounced. Debye-Scherrer rings of the block copolymer films with powder-like orientation of lamellar domains. The scattering peaks arising from transmitted and reflected X-rays at the substrate can be calculated following [53]
where m represents the peak order, which is 31/2 for the (11) plane in hexagonally packed cylindrical microdomains. The upper (−) and lower (+) branches in the equation indicate the Bragg diffraction of the transmitted and reflected X-rays, respectively. D is the characteristic length of the given plane. As for the (11) plane, Eq. (9) can be derived from Eq. (8) as follows:
where D corresponds to the D01 in this case. When the D01 was set to 18.8 nm, the DWBA calculation Eqs. ( 8) and ( 9) gave the best representation for all Bragg spots as shown by crosses in Figure 7.
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Figure 7.
GISAXS patterns measured with tender X-ray (2.40 keV) at the angle of incidence 0.620. The dotted lines of the calculated Debye-Scherrer like rings from transmitted (red) and reflected (black) beams obtained using Eq. (8) as assuming the characteristic length D⊥ (perpendicular to the surface) is smaller than the D∥ (virtual parallel component). The D⊥ corresponds to D01. The crosses were obtained using Eqs. (8) and (9).
\n\n
For GISAXS experiment in the soft X-ray region, the large curvature of the Ewald sphere may give rise to an apparent distortion of the GISAXS pattern when the measurements are conducted with a fixed angle of incidence and using the area 2D plane detector. Yamamoto et al. [62] discussed the effect of the Ewald sphere curvature and performed model calculations using DWBA [61]. At the lower energy of 1.77 keV, while the interparticle interference peaks extended and bent inward at large qz, (approximately 2.0 nm−1), no bending of the extended peaks was observed using hard X-rays. In the presence of the Ewald sphere curvature, the unmodified equation is no longer valid. In this study, Eq. (9) that had been developed for the hard X-ray regime to explain the experimental GISAXS pattern is confirmed to be valid for this observed q-range with tender X-ray regime 2.40 keV [57].
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The lattice constant b associated with the direction perpendicular to the surface was slightly smaller than the lateral lattice constant a. The hexagonal lattice was slightly deformed, in particular, the nanocylinders were packed into distorted hexagonal lattice that was laterally elongated and/or vertically collapsed. The distorted hexagonal lattice in polymeric films has been often observed during the drying of solvents [63]. The lattice constant remained almost constant with respect to the depth. In contrast, the constant b and the angle φ between the lattice vectors increased with decreasing depth, i.e., approaching the surface, the lattice deformation was relaxed to a normal hexagonal lattice (Figure 8).
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Figure 8.
Lattice parameters plotted against the penetration depth (left). Right illustration indicates parallel-aligned cylindrical domains in thin film and the unit cell. The spacing Dn corresponds to the vertical distance neighboring planes (1). |an| and |bn| represents the distance between neighboring cylindrical domains. The following relations were obtained by analysis; D1 > D2 > D3 > ⋯ > Dc = ⋯ = Dn. |a0|=|a1|= ⋯ =|an|. |an|>|bn|. Here, Dc means Dn reached constant value. Reprinted with permission from Saito et al. [57]. Copyright 2015 American Chemical Society.
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3.2. Orientation and relaxation behaviors of lamellar microdomains of poly(methyl methacrylate)-b-poly(n-butyl acrylate) thin film [64]
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In this section, we investigated the phase-separation behavior of poly (methyl methacrylate-b-n-butyl acrylate) (PMMA-PnBA) forming a lamellar structure aligned parallel to the substrate after appropriate thermal annealing with GISAXS measurement. The structure development through such as degree of the lamellar orientation and relaxation of the lamellar domain spacing was inquired. Also, the GISAXS with tender X-ray for depth-sensitive analysis was conducted to reveal that the difference of the lamellar domain spacing near the surface from the bulk.
\n
To obtain a thin film of the block copolymer PMMA-b-PnBA (Mn = 32,000, Mw/Mn = 1.17, fPMMA = 0.44), PMMA-b-PnBA in toluene (5 wt% polymer solution) was prepared. The thin film was obtained by spin cast on silicon wafer at 3000 rpm for 30 s. The thin films (thickness was 280±30 nm) were dried at room temperature, subsequently thermal annealing was performed at 160° for given time. GISAXS measurement utilizing hard X-ray and tender (soft) X-ray was performed. Hard X-ray GISAXS measurement was conducted at beamlines BL6A and BL10C in Photon Factory of KEK, Tsukuba in Japan and BL03XU in SPring-8, Hyogo in Japan [65, 66] with wavelength of 0.15 (BL6A), 0.1488 (BL10C), and 0.1 nm (BL03XU), respectively. Tender X-ray GISAXS measurement was performed at BL15A2 in Photon Factory.
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2D GISAXS (hard X-ray) patterns with various annealing times were shown in Figure 9. The pattern of as-spun sample (Figure 9a) was shaped like an ellipse, which might arise from kinetically frozen or poorly ordered structure. Partially intense scattering was observed at qz of 0.25–0.28 nm−1 where was emphasized due to the so-called Yoneda peak, i.e., it did not indicate specific orientation, suggesting that no orientation of phase-separated structure of PMMA-b-PnBA appeared without thermal annealing. After the sample was thermally annealed for even 1 min, the scattering intensity around qy = 0 (near the beam stop) grew. In addition, two clear ring-shaped scattering patterns like Debye-Scherrer rings were observed. Each scattering ring was arising from transmitted (denoted by T) and reflected (denoted by R) beams as described in previous section. The scattering intensity near beam stop became strong with annealing time. This change in GISAXS pattern indicates the growth of the parallel orientation of the lamellar microdomain. The development of the normalized scattering intensity [64] from parallel lamellar structure is shown in Figure 10. Orientation is nearly complete after annealing for 60 min. The GISAXS measurement gave structure information about domain spacing of the lamellar morphology. The domain spacing (D) of the lamellar structures aligned parallel to the surface was estimated. To determine the accurate domain spacing, the distorted wave Born approximation (DWBA) was applied for analysis of the GISAXS patterns. The experimentally estimated D values are also plotted as a function of the annealing time in Figure 10. The value of the D approached to the D0 of the bulk sample (independently obtained to be 21.6 nm) with an increase in annealing time. The D of the parallel orientated structure was slightly smaller than D0 even after 4 h thermal annealing, i.e., the spacing collapsed vertically. Consequently, the lamellar structure was deformed along the depth direction (similar phenomena as the previous section). Thermal annealing induced the relaxation of the domain spacing and it seems taking approximately more than 2 h to complete the relaxation of D (equals to the value of the bulk)
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Figure 9.
GISAXS patterns (hard X-ray, 1.488 Å) of PMMA-b-PnBA thin film (a) as cast and (b–e) as annealed at 160°C with given annealing time; (b) 1, (c) 3, (d) 5, and (e) 10 min. R and T denoted the scatterings from reflected and transmitted X-rays, respectively. Reprinted from Saito et al. [64]. Copyright Nature Publishing Group.
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Figure 10.
Time evolution of the orientation of the lamellar domain (open circles) and the relaxation of the lamellar D (filled circles). The solid lines were drawn as a guide to eyes. Dotted line shows the D0 value of the bulk. Open square indicates the D value near the surface. Reprinted from Saito et al. [64]. Copyright Nature Publishing Group.
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As is well known, preferential wetting of surface and substrate interfaces plays an important role of orientation in thin film [12, 17]. In this case, surface energies of PMMA, PnBA, and Si substrate are 41.1, 33.7, and 77.4 ± 0.5 mJ/m2, respectively [16]. According to the surface free energies, it will be predicted that PMMA segregates to the surface of the silicon substrate, whereas PnBA segregates to air surface. As a result of preferential wetting, the parallel orientation of lamellar structure is induced at the surface and/or the polymer/substrate interfaces and the oriented lamellae propagate into the entire film [67]. In fact, XPS measurement proved that surface molar fractions of PnBA (within a few nanometers) were 80 mol% (repeat unit) in as-cast film and the PnBA component perfectly covered on the surface after thermal annealing with only 60 s. The segregation of each component, orientation of the lamellae, and relaxation of the domain spacing occurred in different time scale. It can be concluded that the PnBA first segregated at air surface within a minute after annealing (PMMA may segregated at the interface), second the microphase-separated structure aligned parallel to the surface, followed by relaxation of the domain spacing.
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The polymer thin films have reported to have different mobility dependent on the local region, i.e., near the surface, inside, or near the polymer/substrate interface. It is quite intriguing to investigate that the depth dependence of structure difference exists, in other words, whether there are difference between the structure (orientation, morphology, d-spacing, etc.) in the vicinity of the surface and inside of the film, or not. The GISAXS measurements of PMMA-b-PnBA thin film thermally annealed for 2 h with tender X-ray was performed with various incident angles. As shown in Figure 11(a) and (b), in the case of αi < αc, the scattering (marked arrows) of the lamellar structure oriented parallel to the substrate was considerably diffuse and broaden, while in the case of αi > αc, the scattering became clear and sharp. The FWHM values of scattering peak (parallel lamellar domains) in the one-dimensional GISAXS profile obtained vertically cut at various incident angles can be simulated as the same manner of the size effect of measured region as discussed in the previous section (modified the Laue function). Thus, the penetration depth was controlled by changing the incident angle. At near the critical angle, the surface-sensitive measurement is possible as predicted from Eq. (2). The true qz value of the oriented lamellar structure parallel to the substrate is estimated using the experimentally observed peaks, i.e. D near the surface can be estimated. At αi of 0.525° (penetration depth Λ of 32.4 nm), D was obtained to be 21.6 nm which is equal to the D0 value (21.6 nm) of the bulk sample. The value of D near the surface is slightly larger than the value 21.4 nm obtained from DWBA calculation (inside the whole film). This means that relaxation of the domain spacing near the film surface preceded that of the inside. According to previous reports, polymer chain near the surface indicates higher mobility (lower glass transition temperature or viscosity) [68–70]. Moreover, the lamellar structure started to orient from both the air/polymer and polymer/substrate interfaces, which was induced by segregation of one component in the BCP. Therefore, that the faster relaxation of the D of the lamellar structure near the surface was caused by the faster orientation and higher mobility in the vicinity of the surface.
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Figure 11.
Tender X-ray (2.40 keV) GISAXS patterns of PMMA-b-PnBA thin films annealed at 160 °C for 2 hours at incident angles (a) 0.525° and (b) 0.625°. Reprinted from Saito et al. [64]. Copyright Nature Publishing Group.
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3.3. Evaluation of mesogen orientation in thin films of polyacrylate with cyanobiphenyl side chain [71]
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Understanding the orientation behavior of polymer chain in the vicinity of interfaces (both substrate and free surfaces) is of practical importance in organic thin film technologies such as coating and photoresisting processes. Thus, a large amount of fundamental knowledge has been ever accumulated. It has been broadly recognized that diverse physical properties of polymeric materials in ultrathin film state are very different from those in the bulk state. Compared with the vast amount of studies for amorphous and crystalline (LC) polymers, studies on the anomaly in structure and orientation of side chain liquid crystalline polymers in ultrathin film states are rather unexplored. A large number of data related to mesogen orientation have been reported [72–78]. Accordingly, the side chain LC polymers are mostly aligned homeotropically [23, 79–81] The significant effect of the sample surface is apparent from the fact that the mesogen orientation changes to a planer orientation as the sample surface is covered by another layer or material [23, 82–84]. A cyanobiphenyl(CB)-containing polymethacrylate (PCBMA) exceptionally indicated the planar orientation regardless of the fact that the homologous polyacrylate (PCBA) oriented homeotropically [33]. This unexpected orientation behavior is responsible for the difference in the main chain rigidity (but still no rational explanation). In these contexts, the investigation to reveal in detail the orientation of PCBA is proceeded by the GISAXS measurements by systematically changing the film thickness. Additionally, GISAXS with hard (8.05 keV) and tender (2.30 keV) X-rays were carried out.
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The side chain LC polymer PCBA (chemical structure shown in Figure 12, Mn = 12,000, Mw/Mn = 1.83, glassy state – 13°C (Tg: glass-transition temperature)–smectic A - 95°C (Ti: isotropization temperature)) films on quartz plates were prepared by spin-casting from 0.12–3.0 wt % chloroform solutions to make different thickness samples. The spin-cast film samples were annealed at 135 °C, cooled to a target temperature, kept for 10 min, and then subjected to the measurements. The layer spacing of the smectic A of LC polymers in the bulk was estimated to be 4.6 nm (SAXS). GI-SAXS experiments with hard X-rays (Cu Kα radiation (λ = 0.154 nm)) were conducted with a FR-E X-ray diffractometer equipped with two-dimensional imaging plate R-AXIS IV detector (Rigaku). GI-SAXS experiments using low-energy X-rays were performed at BL-15A2 [60] at the Photon Factory, KEK, Tsukuba, Japan. Experimental details of the GI-SAXS measurements were described in previous sections.
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Figure 12.
Chemical structure of the side chain LC polymer.
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Figure 13 indicates GI-SAXS data measured with hard X-rays (λ = 0.154 nm) for 30 nm thick at 80 °C. For 140 nm thick film, the scattering peaks corresponding to d (smectic layer) = 4.6 nm (100) and 2.3 nm (200) were clearly seen in both out-of-plane and in-plane directions. The intensity of the peaks in the out-of-plane direction was significantly small in 30 nm thick film (as peaks was weakly shown in 1D profile), and no peaks were essentially recognized for 15 nm thick film, although those in the in-plane direction were clearly seen. These results evidently indicate the coexistent of planarly and homeotropically oriented CB in the films with film thickness greater than 30 nm, and that the CB mesogens were oriented only planarly at 15 nm thickness.
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Figure 13.
2D GI-SAXS (Cu Kα) patterns (a) of PCBA films with a thickness of 30 nm at 80 °C. Lower figure (b) indicates 1D intensity profiles (black: in-plane; red: out-of-plane directions). Reprinted with permission from Tanaka et al. [71]. Copyright 2016 American Chemical Society.
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GI-SAXS measurements with synchrotron tender X-rays (λ = 0.539 nm, 2.30 keV) were achieved at various αi. Figure 14 shows the 2D GI-SAXS images for 30 nm thick film at room temperature. The CB mesogens at this thickness as mentioned before are oriented both in the homeotropic and planar directions (coexistence). The αc in this sample was estimated at about 0.54° for this X-ray energy. Under conditions of αi < αc (αc is about 0.54° for 2.30 keV), the scattering signals in the thin film was observed only the out-of-plane direction as shown in Figure 14a and b, where Λ is estimated as in the range less than 10–20 nm in these experimental conditions. It is apparently indicated that the CB mesogens adopt homeotropic orientation in the free surface region. When αi > αc, the out-of-plane scatterings were split into double peaks in the qz direction as shown in Figure 14c–e. The split double peaks originate from the transmitted X-ray through the film and then reflected on the substrate [44]. Hence, the high qz peak of the double peaks can be assigned to the scattering from the reflection path on the film surface. The split spots means that the X-ray beam actually travelled through the overall film thickness and reached the sample/substrate interface. When αi > αc (Λ > 100 nm), the peaks appeared in-plane direction due to the planar orientation were clearly observed as shown in Figure 14d–f with arrows. These signals undoubtedly originate from the mesogens near the polymer/substrate interface.
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Figure 14.
Two-dimensional GI-SAXS patterns for PCBA thin film with 30 nm thickness using tender X-rays (0.539 nm). Measurements were conducted at αi = 0.48 (Λ = 11 nm) (a), 0.50 (Λ = 16 nm) (b), 0.56 (Λ = 167 nm) (c), 0.74 (Λ = 453 nm), and (d). Note that αc (0.54°) is positioned between (b) and (c). Reprinted with permission from Tanaka et al. [71]. Copyright 2016 American Chemical Society.
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From the overall data of UV-vis absorption spectroscopic [71] and the GISAXS measurements utilizing hard and tender X-rays, the orientation structural models of CB mesogens in PCBA thin films are schematically illustrated in Figure 15. In thick films with 140 nm, the CB mesogens are almost aligned homeotropically. However, a considerable number of the CB mesogens planarly anchored exist near the substrate (polymer/substrate interface) as revealed by GI-SAXS measurements with hard X-rays (Figure 13). At a thickness of 30 nm, the amounts of homeotropically and planarly oriented CB mesogens is comparable, where depth-resolved information is obtained by GI-SAXS with tender X-ray experiments (Figure 14). In the film thickness of 10–15 nm, the CB mesogens adopt almost planar alignment. When the film becomes further thinner from the critical level of 7 nm, the planar alignment near the surface disappears where the liquid crystal structuring (antiparallel packing of the CB mesogens) is lost.
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Figure 15.
Schematic illustration of orientation of the CB mesogens in films with film thickness 30 nm. Purple circles indicate the cyano group at the terminal of mesogen. Note that the antiparallel interactions (LC structuring) are kept among the CB mesogens at thickness above 10–15 nm. Such LC structuring is lost at thickness of 7 nm. Reprinted with permission from Tanaka et al. [71]. Copyright 2016 American Chemical Society.
The GI-RSoXS is a novel technique, which is in particular suited for more complex system such as multicomponent block copolymer and polymer blend films. Resonant soft X-ray scattering has already been successful for probing morphology and spatial structure in organic photovoltaic (OPV) systems [85, 86] and triblock copolymer system [87]. GI-RSoXS allows for detecting near surface and inner structure separately at fixed incident angle by tuning X-ray photon energy because the penetration depth of the X-ray beam is drastically affected by the change in X-ray photon energy across the adsorption edge. Adsorption K edge for organic materials composed of mainly carbon, nitrogen, and oxygen are 284, 409, and 543 eV. The fine structure of the adsorption edge can be utilized in GISAXS measurements. Near edge X-ray adsorption fine structure (NEXAFS) spectrum needs to be probed for the polymeric materials in order to estimate the complex refractive index of X-ray that becomes important for depth-sensitive and component sensitive analyses. Typically, the NEXAFS spectra of polymers, which have low contrast in the real part of the refractive index in the hard photon energy regime, indicate considerable differences in the soft X-ray regime. In this section, investigation of nanostructure in the polymer blend thin film, poly(3-hexylthiophene) (P3HT) and poly[5-(2-ethylhexyloxy)-2-methoxycyanoterephtalylidene] (MEH-CN-PPV), is introduced as an example of GI-RSoXS experiment carried out by Ruderer et al. [50].
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GI-RSoXS measurements with soft X-ray were conducted at the synchrotron beamline 11.0.1.2 of the advanced light source (ALS) at the LBNL in Berkeley (USA) [88, 89]. Due to the high adsorption of soft X-ray in air, full setup (sample and X-ray detector) was kept in high vacuum. The energy of X-ray was used in the range of 280–320 eV (λ: 4.4–3.9 nm). Sample-to-detector was 18.5 cm that was sufficient for detecting length scale in the range from 21 nm to a few micron meters. An incident angle αi = 2°, which is near the critical angle αC of 2.3° for 280eV and 1.5° for 283 eV. The both polymers (P3HT and MEH-CN-PPV) were dissolved in chloroform. The thin film of polymer blend was prepared by spin coating from the solution; the thickness was controlled to be about 70 nm. The films were annealed at 200 °C for 10 min in air without degradation. The NEXAFS spectroscopy measurement was conducted for taking the wavelength dependent refractive index (n = 1 − δ + iβ) of polymers used here for electromagnetic radiation near the adsorption edge. NEAXFS spectra were also obtained at the same beam line of the ALS. The sample environment is identical to the GI-RSoXS setup. The polymer thin films were prepared on silicon nitride membranes and measured in transmission geometry. The adsorption part β of the refractive index was obtained through Beer’s law. The real part δ of the refractive index was calculated from the β using Kramers-Krongis relation.
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Figure 16a shows the X-ray energy dependence of the dispersion δ and the adsorption β of P3HT and MEH-CN-PPV homopolymer. The spectra of respective homo polymers are different. NEXAFS spectra of the blend system with different blend ratio can be obtained by a linear superposition of the spectra of P3HT and MEH-CN-PPV homopolymer weighted with the corresponding blend ratio. The dispersion δ spectra of P3HT and MEH-CN-PPV reveal positive and negative values and differ strongly depending X-ray energy. Therefore, the scattering contrast depends on the X-ray energy. Using the adsorption β spectra, the penetration depth Λ of the soft X-rays into the blend film is calculated as shown in Figure 16b. Figure 17 indicates the GI-RSoXS patterns of as spun P3HT/MEH-CN-PPV bulk heterojunction films with a P3HT content of 70 wt% for different energies from 280 to 289 eV (wavelength of X-rays from 4.43 to 4.29 nm). Although the wavelength is varied by only 3%, the scattering patterns significantly change. For energy below 284 eV, an intensity oscillation in vertical direction is observed, which comes from the correlated roughness originating from the interference of scattered X-rays from different interfaces. The correlated roughness vanishes with increasing energies of the X-rays. It indicates no scattering signal from the substrate interface is detected and X-ray penetrates near the surface as shown in Figure 17. The low scattering intensity of GI-RSoXS at 284 eV (Figure 17c) is due to the very low incident intensity at this energy. The reduction of the intensity at 286 eV (Figure 17e) can be ascribed to the significant low contrast between P3HT and MEH-CN-PPV at this energy. Thus, the surface structure is accessible at 286 eV. The change in the total scattered intensity was attributed to the changed contrast conditions from the contrast variation.
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Figure 16.
(a)Dispersion δ and the absorption β of P3HT (red solid lines) and MEH-CN-PPV (blue solid lines) as a function of the X-ray energy. For comparison, the calibrated P3HT spectra (dashed lines) from the database [90] are drawn. (b) Penetration depth of X-ray of P3HT (red) and MEH-CN-PPV (blue) as a function of X-ray energy. Reprinted with permission from Ruderer et al. [50]. Copyright 2016 American Chemical Society.
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Figure 17.
Two-dimensional GI-RSoXS patterns of as-spun P3HT: MEH-CN-PPV film with a P3HT content of 70 wt% with different X-ray energies. The X-ray energy: (a) 282, (b) 283, (c) 284, (d) 285, (e) 286, (f) 287, (g) 288, and (h) 289 eV. Copyright American Chemical Society, Ruderer et al. [50].
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\n\n',keywords:"grazing-incidence X-ray scattering, organic thin film, block copolymer, tender X-rays, depth profiling",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/52323.pdf",chapterXML:"https://mts.intechopen.com/source/xml/52323.xml",downloadPdfUrl:"/chapter/pdf-download/52323",previewPdfUrl:"/chapter/pdf-preview/52323",totalDownloads:1867,totalViews:579,totalCrossrefCites:3,totalDimensionsCites:4,hasAltmetrics:0,dateSubmitted:"March 23rd 2016",dateReviewed:"August 3rd 2016",datePrePublished:null,datePublished:"January 25th 2017",dateFinished:"September 4th 2016",readingETA:"0",abstract:"The intricate nanoscopic morphology of soft materials such as block copolymer and polymer blend system successfully analyzed by small angle X-ray scatterings (SAXS). In thin films, those soft material systems have attracted great attention because of a potential for practical use of functional materials. The morphology has been revealed by grazing-incidence (GI) methods. Recently, advanced grazing-incidence technique for analysis for surface-, volume-, and material-sensitive method (high time, spatial, and/or material resolution) has been reported. Using low X-ray photon energy, tender X-ray (1–4 eV) and soft X-ray near K-edge carbon, allows probing a complex nanomorphology with those sensitivity. In this chapter, recent GI-SAXS with tender X-ray and resonant soft X-ray (GI-RSoX) will be picked up to open for discussion on new possibility of structural analyses.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/52323",risUrl:"/chapter/ris/52323",book:{slug:"x-ray-scattering"},signatures:"Katsuhiro Yamamoto",authors:[{id:"187032",title:"Prof.",name:"Katsuhiro",middleName:null,surname:"Yamamoto",fullName:"Katsuhiro Yamamoto",slug:"katsuhiro-yamamoto",email:"yamamoto.katsuhiro@nitech.ac.jp",position:null,institution:{name:"Nagoya Institute of Technology",institutionURL:null,country:{name:"Japan"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Grazing-incidence small angle X-ray scattering",level:"1"},{id:"sec_3",title:"3. Depth-resolved structure analysis of microphase-separated structures in block copolymer thin film by grazing-incidence small angle X-ray scattering utilizing tender X-ray",level:"1"},{id:"sec_3_2",title:"3.1. Cylindrical microdomain in block copolymer thin film [57]",level:"2"},{id:"sec_4_2",title:"3.2. Orientation and relaxation behaviors of lamellar microdomains of poly(methyl methacrylate)-b-poly(n-butyl acrylate) thin film [64]",level:"2"},{id:"sec_5_2",title:"3.3. Evaluation of mesogen orientation in thin films of polyacrylate with cyanobiphenyl side chain [71]",level:"2"},{id:"sec_7",title:"4. Grazing-incidence resonant soft X-ray scattering [50]",level:"1"}],chapterReferences:[{id:"B1",body:'Zhang, Q.; Cirpan, A.; Russell, T. P.; Emrick, T. Donor-acceptor poly (thiophene-block-perylene diimide) copolymers: synthesis and solar cell fabrication. 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Department of Life Science and Applied Chemistry, Frontier Research Institute for Materials Science, Field of Soft Materials, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan
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\n
1. Introduction
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It has been several decades since an unknown fever dramatically emerged, close to the Ebola river, a small tributary of the great Ubangi river in the heart of the Congolese tropical forest of Africa. Since that time, even though the virus responsible for this new hemorrhagic fever has been identified and characterized, the natural history of the eponymic Ebolavirus remains largely unknown. The cradle of the virus remains enigmatic and the emergence of the Ebola fever unsolved. Indeed, the arcane of Ebolavirus natural history is still hypothesized, thanks to an elusive virus that always risen where it was not expected, violent and devastating, and surprising local populations and health systems, as well as the international scientific community. This Ebolavirus eco-epidemiology remains complex while the Ebola fever (alias Ebolavirus Disease) can be considered as an exemplary disease that can be eventually comprehended only with a transdisciplinary approach that has recently been promoted as a One Health concept. Indeed, it is only when we take into account all disease and virus drivers, including biotic and abiotic factors of the natural and human environments, that some mechanisms of the Ebolavirus disease emergence, such as spread and circulation, can be ultimately unveiled. For that, we have collected all information available, often estimated, from the time and place of the virus emergence long before the emerging event was identified as it and the epidemic phase was brought to public attention. Moreover, when available we also collect all data on potential natural and accidental hosts, weather and environment chorology, among other multiple factors potentially involved.
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Historically, Ebolavirus emerged in Central Africa in the late 1970s, and has re-emerged most recently with the active epidemic (April 2019) in the eastern Democratic Republic of Congo (DRC), by encompassing more than 24 epidemic events from Central to West Africa, to imported infected monkey from Asia to Virginia, and the emerging new Ebola species of the Philippines archipelago [1].
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Among the negative sense RNA viruses of the Filoviridae family five genera are known, including Cuevavirus, Ebolavirus, Marburgvirus, Thamnovirus. Among the Ebolavirus genus, five Ebolavirus (EBOV) species have been identified [2].
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Ebolavirus’ (EBOV) first emergence occurred in 1976, as two different EBOV species in two different places in sub Saharan Africa. The Zaire Ebolavirus (ZEBOV) species and the Sudan Ebolavirus (SUDV) were detected concomitantly, a few weeks apart, respectively in the Northeastern Equator province of the Democratic Republic of Congo, DRC (alias Zaire), and in the Bahr el Ghazal province of South Sudan. On the 26th of August 1976 ZEBOV was isolated from missionaries and local villagers of the Yambuku, in the rain forest close to the Ebola river. However, earlier in June 1976, the SUDV had broken out among cotton factory workers in Nzara, Sudan (now in South Sudan) [3].
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Then, in 1989, the Reston Ebolavirus species surprisingly (RESTV) emerged in the US (!) and was identified during an outbreak of simian hemorrhagic fever virus in crab-eating macaques from Hazleton Laboratories (now Covance) of Reston county, Virginia. Such primate specimens were found to be recently imported from the Philippines. Then, in 1994 a fourth new species of Ebolavirus was isolated from chimpanzee leaving in the Tai Forest of Côte d’Ivoire and named Côte d’Ivoire ebolavirus (CIEBOV). Finally, in November 2007, a fifth Ebolavirus species, was detected from infected patients in Uganda in the Bundibugyo District and was subsequently identified by the eponymic name of Bundibugyo Ebolavirus [4].
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Briefly and extraordinarily among the world of the viruses, the filovirus virion presents a bacilliform (filamentous) shape, like a Rhabdovirus, but presents unique pleomorphic figures with branches and other tortuous shapes. Ebolaviruses have also an unusual and variable long length - up to 805 nanometers (only some plant virus can compete to this filamentous extensive length). However, the internal structure is more classical with a ribonucleoprotein nucleocapsid, a lipid envelope and seven nanometers size spikes. The genome is non-segmented, single stranded RNA of negative polarity with lengths of about 18.9 kb that code for seven proteins, each one having a specific function [5].
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Ebolaviruses are known for their high case-fatality rate (CFR) with always less than 2/3 of survivors among the identified cases. ZEBOV, the most frequently isolated Ebolavirus species during the outbreaks, has the highest CFR, up to 90% in some instances, with an average of 83% for the past 37 years. The Uganda BDBV outbreak had a mortality rate of 34%. RESTV imported to the US did not cause disease in exposed human laboratory workers. The scientist performing the necropsies on CIEBOV infected chimpanzees got infected and developed a Dengue-like fever, fully recovered 6 weeks after the infection while treated in Switzerland.
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\n
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2. When Ebolavirus raised his head in the heart of darkness
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Dates and time make History. Indeed, the various reports on the emergence of Ebolavirus in Africa show discrepancies and lack accuracy, for multiple reasons (remote event, reports by different person or team, at different time…) but the only way to forge the history is to label the events with date, time and the environmental factors observed. On July 27, 1976, the first (known) victim to contract Ebolavirus was a cotton factory worker from Nzara, Sudan. Then, in Zaire (DRC) on September 1, 1976, the first Ebolavirus (Zaire ebolavirus, ZEBOV) victim was a teacher who had just returned from a family visit to northern Zaire (6 Jennifer Rosenberg Internet). These two events were the very beginning of the boundless journey of a deadly Ebolavirus outbreaks.
\n
\n
2.1 The Ebolavirus species emerging events
\n
When the virus becomes epidemic in a human population, it does so weeks or months after the emergent event of the virus switching from its silent transmission in a natural cycle to a zoonotic/epidemic manifestation, revealed to the local health system. Let us see in more detail such emerging events of Ebolavirus species (ICTV, 2018) as there were reported or sometime interpreted, in time and place.
\n
Sudan ebolavirus (SEBOV) occurred when the first recorded SUDV broke out among cotton factory workers in Nzara, South Sudan in June 271,976. This was indeed, the first case of Ebolavirus infection recorded and confirmed and also reported as potentially exposed to chiropteran. Indeed, at the Nzara Cotton Manufacturing Factory this first patient was a cloth room worker where bats (mostly Tadarida - mops - trevori) have a large population in the roof space of their premises. He died in the Nzara hospital on July 6, 1976. Local animals and insects were tested for Ebolavirus without success [6, 7].
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Zaire ebolavirus (ZEBOV) was reported in the Mongala district of the Democratic Republic of Congo (DRC; alias Zaire) in August 1976, when a 44-year-old schoolteacher of the Yambuku village, became the first recorded case of Ebolavirus infection in DRC. Also, the schoolteacher travel earlier in August 1976 near the Central African Republic border and along the Ebola River, estimated 90 km NW from the village [6].
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Reston ebolavirus (REBOV) had its first emerging event as an imported infected cynomolgus monkey (Macaca fascicularis) in October 1989 imported from a facility in the Philippines (Mindanao Island) to Reston, Virginia, USA, where the primate got sick and the virus isolated [8]. In the Philippines, in several instances, the virus was found to infect pigs, in June and September 2008 ill pigs were confirmed to be infested by REBOV (Ecija and Bulacan, Manila island), as well during 2008–2009 epizootics in the island of Luzon (Philippines) [9].
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Cote d’Ivoire ebolavirus (CIEBOV) was isolated for the first time, and as an only known appearance, in November 1994, from wild chimpanzees presenting severe internal bleeding of the Taï Forest in Côte d’Ivoire, Africa. A researcher became infected when practicing a necropsy on one of these primates, he developed a dengue syndrome and survived. At that time, many dead chimpanzees were discovered and tested positive for Ebolavirus. However, the source of the virus was believed to be of infected western red colobus monkeys (Piliocolobus badius) upon which the chimpanzees preyed [10].
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Bundibugyo ebolavirus (BDBV) was then discovered during an outbreak of Ebolavirus in the Bundibugyo District (Bundibugyo and Kikyo townships), on August 1st, 2007, in Western Uganda (Towner et al. [11]). BDBV second emerging event was observed in the DRC in August 17, 2012 in Isiro, Pawa and Dungu, districts of the Province Orientale [11].
\n
With the exception of REBOV in Philippines and CIEBOV in West Africa, all other EBOVs species emerged in the Central African region. Also, all EBOVs are known to emerged in the tropical rain forest during the inter-season between dry and rainy seasons. Also, REBOV appears to actively circulate in the tropical rain or moist deciduous forest of the Philippines [12].
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\n
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2.2 From Central Africa to West Africa
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2.2.1 Concurrent emergences of Ebolaviruses
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On several occasions, concurrent emerging events of Ebolavirus have been observed. Indeed, such events occurred in places geographically distant, independent, and unconnected. The Ebolavirus was isolated and the strains different, even they belonged to the same species of Ebolavirus, altogether in favor of a different origin from an elusive natural reservoir, thus eliminating the notion of leaping from one site to the other. In that matter, the following observations are a paradigm: From its inceptive emergence the Ebolavirus was identified in Sudan at the cotton factory and a few days later at Yambuku, Zaire. The Ebola Sudan and Ebola Zaire viruses emerged concurrently in 1976 in the Congo basin of Central Africa; More than 20 years later the virus emerged and reemergence from 1994 to 1996 in a different places in Gabon, in a successive and timely overlapping events but in unconnected areas from where different strains of the same EBOVZ were isolated [13]; More recently, during the 2014–2016 dramatic Ebolavirus disease (EVD) emergence of in West Africa where the virus emerged in late December 2013 of a 18-month-old boy from the small village of Meliandou (Guéckédou district, South-Eastern Guinea) believed to have been infected by bats [14], concurrently, in August 2013, the Ebolavirus reemerged in the Equator province of DRC - different places and different strain of ZEBOV [15].
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It is remarkable that most of these emerging events occurred during or close to the end of the rainy season which generally stretches from August to October in the domain of the Congo basin tropical rain forest.
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Altogether, these observations are in favor of environmental factors of emergence favoring, when they occur synchronously in the same place, the spillover of the virus from its hidden natural cycle to an accidental and susceptible host. Therefore, these plural and concomitant emerging events play against the theory of Ebola virus diffusing in oil spot in Central Africa [16]. This original pattern of concurrent emergences could explain also the relative stability of the virus strains which remain for years in the same environment, and the interepidemic silences which require several fundamentals (i.e. concurrent risk factors) to be broken.
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2.2.2 An unexpected broader domain of Ebolavirus circulation
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The first evidence that showed that Ebola virus had previously circulated in areas without any known cases of disease came in 1977, near the Ebola outbreak in Tandala, DRC, just 200 miles west of the first known cases in 1976 [17]. Blood samples obtained from individuals in areas with no previous symptoms of Ebola were found to contain antibodies for Ebolavirus, indicating a previous or ongoing infection with that virus. Because subclinical illness is always a possibility with viral infections, the presence of these Ebolavirus-specific antibodies could only be explained by exposure to the virus, which is somewhat reasonable in an area that is endemic to the disease. But how do we know the true endemic zone of a virus such as Ebolavirus?
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Endemic zones are primarily based on where disease can most likely be expected, and are determined by historical accounts of disease, as well as supplemental information such as where animals or insects that might transmit the disease are located. With respect to the Ebola virus, outbreaks that occur in Central Africa, in or near the Congo River Basin, are expected; outbreaks that take place elsewhere are unexpected and can be problematic, as was the case for the 2014–2016 West African outbreak. And yet, scientists have highlighted the presence of Ebola antibodies well outside the endemic zone for disease for decades.
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In the early 1980’s, research based at the Pasteur Institute in Bangui, Central African Republic, demonstrated for the first time that the population of central Africa presented natural antibodies against the Ebolavirus strains of Zaire and Sudan [3, 4]. Research also showed for the first time that several mammal species had Ebolavirus-reacting antibodies, including rodents, dogs, and others. Initially, the scientific community was skeptical of the findings, due to the type of antibody tests used, and because the prevalence of these antibodies was unbelievably dispersed and at a high level of prevalence. However, a 1989 follow-up study confirmed methodology and preliminary observations, and expanded the results to include similar observations in Cameroon, Chad, Gabon, and Republic of Congo (the latter two of these countries would have their first Ebola outbreaks in 1994 and 2001, respectively) [5]. Moreover, such Ebolavirus antibody prevalence was found in West Africa (e.g. Senegal, Chad, Sierra Leone), preceding the catastrophic 2014–2016 Ebolavirus outbreak [18]. Subsequent studies have determined that 20–25% of persons living in or near the Congolese rain forest are seropositive for Ebola, despite never exhibiting symptoms [19].
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Today, Ebola antibody prevalence is widely distributed across the African continent in the absence of severe clinical presentation and/or outbreak manifestation. A 1989 study even found Ebola Zaire antibodies among people living in Madagascar, an island country that has never had a single known case of Ebola, and which has been geographically separated from continental Africa for 100 million years [20].
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Risk mapping, including ecological and geographical distribution <10-13 cm/s first hour, and extended, highly sensitive and specific environmental and biogeographical models based on EBOVs susceptible mammalian biogeography in Africa, show a robust and precise potential distribution of EBOVs in Africa that clearly overlap the African tropical rain forest biome of the Guinea-Congo forests (including the Congo basin rain forest, and the Occidental relic of the Congolese rain forest spreading from Guinea to Ghana) and the southern band of the Sudan-Guinea Savanna [21].
\n
Also, as a result of potential Ebolavirus (or Ebolavirus antigen) exposure, serological markers have been found in vertebrates outside of Africa. With the exception of Philippines, where REBOV is known to circulate in monkeys and pigs, thus showing its ability to infect multiple animal species, in several instances serological evidence of Ebolavirus exposure has been detected in many vertebrates, particularly chiropterans [9]. Definitely, bat populations in Bangladesh and China present antibodies against ZEBOV and REBOV proteins [22, 23]. Ultimately, it appears that EBOVs are widely distributed throughout Africa, West and Central, and Asia. Moreover, risk mapping of filovirus ecologic niches suggests potential areas of EBOVs distribution in Southeast Asia [24].
\n
The unexpected detection of REBOV first in Virginia, for the reason we know, and then the astonishing discovery of its circulation and natural cycle in the Philippines gave a rethinking of the entire family of Ebola viruses previously known mainly on the African continent [25].
\n
From these observation and facts, the potential circulation of EBOVs in its natural cycle appears much wider than expected, while the emerging events we can witness appears to be only a tip of the iceberg in the wide Congolese tropical rain forest.
\n
\n
\n
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2.3 From the index case to the epidemic chain, outbreak, and pandemic
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The fundamentals of emergence are changing in the heart of the rainforest and elsewhere: changing times, when the means of transmission switch from foot to motorbike, when knowledge conveyance has switched from paper reporting to the internet.
\n
Let us examine the risk of expansion for Ebolavirus. Indeed, the factors of transmission of the virus to man and man to man are essential to take into account in this context. Moreover, it is extremely important to note that these factors are subject to permanent changes in societies whose trade and means of communication are drastically changing as a result of health systems, responses and preparedness for epidemics at national and international levels, policies, and the economy.
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So, with the experience gained for more than 40 years, the strategies of struggle are clearly defined, but the societal changes that are taking place make their application difficult and sometimes impossible (e.g., the 2019 outbreak in the DRC, where political institutions have prevented an adapted response). Situation and the epidemic are perpetuated.
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There is also a growing means of communication, both smartphones and motorized transport, to travel more quickly as ever, between the epidemic zone of EVD and the family [26].
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Thus, during the emergence of the Ebola virus in West Africa, all of this means of communication played a fundamental role in the regional spread of the epidemic, until it became a pandemic risk when the virus was exported to other countries of the African continent and, outside Africa in Europe and North America [27].
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3. A strange iteration of epidemic events with unexplained virus disappearance
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It is known for several other transmitted viruses that during the inter-epidemic silences several factors can be responsible. In general mass herd immunity (natural of due to acquired immunization i.e. vaccine) of the permissive hosts force the virus in its natural cycle without apparent clinical manifestation in the hosts (e.g. Most by the arbovirus classically yellow fever, Dengue, Japanese encephalitis, West Nile, Zika etc.).
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The Paramyxoviridae and Rhabdoviridae are the two other viral families in the order Mononegavirales, genetically closely related to the Filoviridae and having chiropteran as reservoir and/or vector [28]. Indeed, it is interesting to note that megachiropteran fruit bats are reservoirs of Hendra and Nipah viruses of the Paramyxoviridae family [29]. When, Microchiroptera bats are the probable ancestors of all rabies virus variants of the Lyssavirus genus in the family Rhabdoviridae and infecting presently terrestrial mammals [30]. Both also present this cryptic interepidemic silences that has not been yet clearly understood. The Nipah emerged one time in Malaysia (1999), thought to have its original cycle in PNG, and ultimately reemerged more than 3500 km away in Bangladesh in 2001. From its inception, again the Marburgvirus (the closest to EBOVs in the family of Filovirus), emerging events from an expected natural foci occurred within the path of time including 4 to 11 years of inter-epidemic silences occurring mostly in distant sites of Eastern and South Africa (Uganda, Zimbabwe, Angola, Kenya).
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If one were to describe the history of Ebola outbreaks, one could simply construct a timeline, with a point on the line for each outbreak. You could create this timeline with a varying number of points, depending on your methodology, but regardless of how you built your timeline, there would be spaces between these points. This is due to the nature of Ebola; it appears, it disappears, and it appears again. To the Ebola virus, these gaps are periods of convalescence. To us, they are periods of absence and mystery, and one of these gaps stands out as the most mysterious (Figure 1).
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Figure 1.
Timeline of Ebolavirus emergence. Emerging events (bars) red = EBOV; blue = SEBOV; green = BDBV; horizontal axis = years 1972–2018; vertical axis = no value. Numbers above brackets = years of silent inter-emerging event.
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The CDC lists five Ebola outbreaks in the late 1970’s. The “first” Ebola outbreak took place in 1976, though we now recognize the event as two simultaneous and separate outbreaks. Between June and November 1976, 284 cases (151 deaths) of Ebola Sudan occurred near what is now Nzara, South Sudan; between September and October 1976, 318 cases (280 deaths) of Ebola Zaire occurred near what is now Yambuku, Democratic Republic of Congo (DRC). In November 1976, a researcher in England that was working with samples from the Nzara outbreak accidentally infected himself; CDC lists this accident as the third Ebola outbreak (the individual recovered). In June 1977, a child became sick and died from Ebola Zaire in Tandala, DRC though there was only one confirmed case, subsequent epidemiological investigations of the area uncovered several other historical, probable cases. Finally, between July and October 1979, 34 cases (22 deaths) of Ebola Sudan occurred, unbelievably, in Nzara, Sudan – the same community where the first cases of Ebola emerged just 3 years prior. In the span of just 39 months, the terror of Ebola had introduced itself to the world five times (638 cases, 454 deaths) and then… silence.
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Ebola would not reappear for 10 whole years, and even then, the subtype was Ebola Reston, which we now know does not affect humans. Though CDC lists four Ebola Reston outbreaks between 1989 and 1992, the world would not see another case of Ebola virus disease in humans until late-1994, in Gabon. Even then, the outbreak (52 cases, 31 deaths) was mischaracterized as yellow fever for several months. Perhaps the virus’s long absence from the spotlight had removed it from the collective consciousness in 1994, certainly in the presence of those pathogens that had been circulating and consuming our attention in the meantime.
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This fifteen-year disappearance of Ebola, particularly in light of its frequent and severe outbreaks in the late 1970’s, has perplexed researchers for decades. The mystery lay, to some extent, within the lack of complete knowledge of the virus reservoir, though scientists are now having their long-held suspicions in bats confirmed. It’s hard to detect disease when you cannot pinpoint the source. Surveillance and reporting have been another confounding element. How many times in that fifteen-year period was an illness misdiagnosed as yellow fever, dengue hemorrhagic fever, or some other similar illness, because of lack of knowledge or diagnostic capabilities, or simply because there was no health care around? We will probably never be able to answer this question. Finally, our perceived zone of endemicity at the time was limited to northern DRC and southern Sudan. Was the virus appearing elsewhere, unbeknownst to us? We certainly were not expecting it to emerge in Gabon in 1994, and Uganda in 2000, and West Africa in 2014 [31].
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Scientists today continue to be perplexed by the emergence of the virus. What brings Ebola out from its hiding place? Is its emergence/re-emergence tied to climate change? globalization? the changing interface between humans and wildlife? If it has to do with any of these increasingly significant factors, how do they explain the fifteen-year disappearance?
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These days, the virus comes and goes with some predictability—since 2000, outbreaks have approached a near-annual incidence, sometimes skipping a year, sometimes lasting more than a year. The periods between outbreaks are growing shorter. Is this because our capability to detect Ebola outbreaks is improving, or is the virus able to infect humans more frequently? One thing is for sure: the world knows that when one outbreak ends, another will eventually follow, and we need not wait 15 years.
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4. Toward the discovery of the natural cycle of the Ebolaviruses
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4.1 The discovery of a putative natural reservoir of Ebolavirus
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Since the ZEBOV and SEBOV emergence, extended field studies have been conducted to discover the reservoir of EBOVs [32] including the 1976 first recorded DRC outbreaks and Sudan, the 1979 outbreak in DRC in 1979 and 1995 following the Kikwit outbreak, the same year in the Tai Forest and in 1999 in the Central African Republic [33, 34, 35, 36, 37, 38] . A total of more than 7000 vertebrates and 30,000 invertebrates were sampled and tested for the presence of EBOVs. Limited finding was inconclusive for an potential EBOVs reservoir status among all these animals. Moreover, while several animal species (Bats, birds, reptiles, mollusks, arthropods, and plants) were experimentally infected with ZEBOV, only two fruit bat species (Epomophorus spp. and Tadarida spp.) developed a subclinical transient viremia [39]. If these results were not confirmed in the natural settings, they indicated the potential for chiropteran to be natural for EBOVs [40].
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Also, historically, the first documented case of EVD in Sudan in 1976, the index case was located (by the World Health Organization) in a cotton factory far from the forest block, where the only wild significantly abundant species was an insectivorous bat species [21].
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Since the discovery of EBOV in 1976, more than half of the epidemic outbreaks caused by EBOVs have broken down between Gabon and the DRC. Following the successive EBOV outbreaks in Gabon from 1995 to 2001 affecting several animal species non-human primates, and wild ungulates and responsible of the dramatic decline of great apes (gorilla and chimpanzee) populations in the region (Leroy et al. [16]), researchers engaged several missions of captures of wild animals in the forest areas affected by the recent past epidemics. Also, 1030 animals were captured and analyzed, only three species of fruit bats were found infected with the ZEBOV by PCR including: Hypsignathus monstrosus; Epomops franqueti; and Myonycteris torquata. Moreover, antibody reacting anti-Ebola were detected in these species as well as for the genus Myonycteris spp. leading ultimately to design Chiropteran as a potential reservoir of EBOVs [41].
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Since then, many studies have converged in favor of the role of chiropters in maintaining EBOV in the wild (Caron et al. [42], Leendertz). In addition, a recent study of bats in Sierra Leone showed the association of an EBOV like with several species of bats (Mops condylurus and Chaerephon pumilus) from the Molossus family [43]. Moreover, a potential direct exposure to Ebola infected fruit bats was also reported as a putative index case of large epidemics [44, 45]. Moreover, further studies reported on direct infection of natural hosts (primates) by EBOV infected bats as highly plausible, given that bats, especially fruit bats, are frequently hunted and consumed as bushmeat by human when Cercopithecus species hunt roosting bats for consumption [46] also preying on bats has been reported in Cercopithecus ascanius and C. mitis (East Africa) as well as bonobos (DRC) [47]. It is also possible that different modes of exposure to Ebola virus could lead to different antibody profiles, that is, contaminated fruit vs. contact with infected bats during hunting [44, 47, 48].
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Altogether, several fruit bats (Epomophorus wahlbergi) and insectivorous bats (Chaerephon pumilus, Mops condylurus) experimentally survive to EBOV infections [39], EBOV RNA and/or anti EBOV reacting antibodies were detected also in several other fruit bat species (Epomops franqueti, Hypsignathus monstrosus, Myonycteris torquata, Eidolon helvum, Epomophorus gambianus, Micropteropus pusillus, Mops condylurus, Rousettus aegyptiacus, Rousettus leschenaultia) giving more insight of the potential for chiropteran to be a potential host or reservoir host of EBOVs [22, 49, 50].
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Interestingly, REBOV was also found associated with the bats in its natural habitat of the Philippines [51]. Also, again in this same Filoviridae family, Marburg viruses in Africa are clearly associated with bats [32, 52] as well as the Cueva virus in Europe [53]. While REBOV has been find associated with fruit bats, Roussetus spp. (Pteropodid family), each filovirus genus is associated with a specific chiropteran group including: Marburgvirus with a specific fruit bat, Roussetus aegyptiacus (Pteropodid family); and Cuevavirus with insectivorous bat, Miniopterus schreibersii (Miniopterid family); except for Thamnovirus isolated form fresh water fish.
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Moreover, several virus groups are known to hold bat-borne viruses including the coronaviruses, hantaviruses, lyssaviruses, lassa virus, Henipavirus, filovirus which are among the most severe of the emerging viruses [54, 55].
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Conclusively, this was the first evidence of chiropteran as a potential reservoir and/or vector of EBOV, while several wild animals, in particular great apes were find highly sensitive to EBOV infection. Also, if several species of chiropteran have been identified as a potential virus reservoir,
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4.2 The most complete figure of a putative Ebolavirus natural cycle in the central African raining forest
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From all above observations, records and historical events of EBOVs emerging events, several fundamentals of emergence have been identified as well putative time and space of such events where, that is when the virus jump from the cryptic natural cycle of the reservoir-vector to manifest itself clearly as an open index case of infection in a susceptible host and the potential opening epizootic or epidemic chain.
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4.2.1 The actors
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Again, from the literature numerous vertebrates appears to be permissive to infection by EBOVs, however, due to their ethology, including environmental habits, societal structure, density and their ability of intra and interspecies to mingle. Altogether primates appear highly susceptible to EBOVs infection including non-human primate apes, gorilla and chimpanzee, but also cercopithecids (e.g. colobus) but also small wild ungulates (e.g. forest duikers) and eventually domestic animals (e.g. dogs) [32, 56, 57, 58].
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One can summarize that EBOVs natural hosts belongs to chiropteran as a potential host reservoir represented mostly by Pteropodidae in Africa (REBOV and Roussetus; Bombali virus and Molossidae), and as secondary natural or accidental wild and domestic hosts including several other mammals: primates (Colobus, Cercopithecus), non-human primates (Gorilla, chimpanzee), wild ungulates (duikers) and, human primates. Also this needs to be taken into account with respect to other permissive species to EBOVs, indeed, as an example, if Roussetus spp. was shown to carry EBOVs reacting antibodies more recently R. aegyptiacus bats were demonstrated to unlikely able to maintain and perpetuate EBOV in nature while the natural transmission of filovirus in R. aegyptiacus, resulting viral replication and shedding are unknown [59].
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4.2.2 The stages
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The African Rain forest of the Congolese basin appears to be the epicenter of EBOVs emerging events. More than 80% of the emerging events of EBOVs occurred in the Tropical zone under the influence of the (Intertropical converging zone, ITCZ) from five degree North to 5 degrees south and oscillating as much as 40 to 45° of latitude north or south of the equator based on the pattern of land and ocean beneath it [28] (Figure 2).
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Figure 2.
Emerging events of Ebolavirus and climate since the Ebola fever inception in Africa. Left = annual rainfall; right = annual temperature. To illustrate the association temperature/rainfall and emergence, the month of May was chosen because it is at this time of the year that we observe the most emergent events of the Ebola virus. Temperature and rainfall are expressed as an annual average for the period under consideration. The precise location of 32 Ebola emergent events are here integrated into the global climatic map of Africa. Only 30-year average values per month of rainfall are available for the study period (ref.: WorldClim world databases) as well for the average monthly temperature.
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Temperature and precipitation data for Africa (average data computed from 1960 to 1990, 300 m resolution [HIJ 05]) were integrated with the distribution map of the emergent events of the Ebola virus and the values calculated for each of the emergence points [60].
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On all emergence points, the temperature at the time of emergence is not significantly different from the average annual temperature over 30 years. The difference in temperature between the moment of emergence and the average temperature (of 30 years monthly average) of the hottest month does not show any difference either. Emergence would not be directly related to temperature.
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When we compare Ebolavirus emerging events time and the rainfall, there is strict quantitative correlation between rainfall and emergence: Most of the emergent events (93.8%) occurred during the rainy season (Figure 2). For precipitation values, there is a slightly statistically significant (p = 0.02) positive difference between the average precipitation of the month of emergence and the average of the monthly average precipitation (over 30 years), indicating that precipitations are higher when emergences occur. There is an even more statistically significant (p = 0.003) positive difference when considering precipitation of the month preceding the emergence. Emergence is therefore likely to be associated with rainfall intensity and the rainy season. 10/32 emergences occur at the beginning of the rainy season, 9/32 in the middle, and 11/32 at the end. Only 2/32 emergences occurred in the dry season.
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When referring to land use (Figure 3) the temperature at the 6 emergence points in “Cropland” is highly significantly less (p = 0.005) than 15% (21.6°C) at temperature (24.4°C) to the 9 points in “Tree cover, broadleaved, evergreen, closed to open”, however the average temperature of the Cropland (21.6°) is to a degree less, significantly lower (p = 0.01) than that of the “Tree cover” (24.5°C).
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Figure 3.
Environmental factors surrounding Ebolavirus emerging event: Land use and places of Ebola virus emergence in Africa from 1976 to 2014. Land use from ESA 2015, 300 m resolution; red circle = putative place of the Ebola virus emergence (index case). Estimated Ebola emergence places are superimposed on the land use layer. The identification of the land use types were 32 points (red circle) representing the putative places of Ebolavirus emergence are superimposed and are distributed as follows: (1) cropland: 6, (2) herbaceous cover: 5, (3) cropland mosaic: 5 (> 50% natural vegetation vs. <50% tree, shrub, herbaceous cover), (4) tree cover with: (a) 15% of broadleaved, evergreen, closed to open: 9, (b) 15–40% of broadleaved, deciduous, open: 2, (5) flooded, fresh or brackish water: 1, (6) urban areas: 3, and (7) water bodies: 1. The limitations of this interpretation are linked to the accuracy of the location of Ebolavirus emergence sites (from literature and reports) and, to the evolution of vegetation cover over the past decades since the first emergence of the Ebolavirus occurred in Africa.
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Ultimately, taking into account these environmental factors, when we look for an association between the emergent events of the Ebola virus and the characteristics of the places of these emergences (i.e. land use, temperature, rainfall) it turns out that the emergences are always in the zone of heavy rainfall, but nevertheless do not follow the moving of the rainy season. Moreover, these emergences remain always and remarkably close enough to the Equator, therefore in the equatorial forest area with a high hygrometry, and a moderate annual temperature. However, the temperature at the time of emergence is not significantly different from the average annual temperature (at the points of emergence) which does not allow to distinguish seasonal effect in the emergence-temperature relationship. Conclusively, we did not identify a seasonality associated with the time of emergence, however the emerging events occur in specific geographic zone characterized by several environmental factors. Finally, the emergence zones are in areas of Land Use with specific temperatures not related to seasonality. Ultimately, it is also remarkable that all these emerging events occurred in an area with a highly potential presence of apes, virus-sensitive hosts.
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4.2.3 Fundamentals and domains of emergence: a theory for a natural cycle of EBOVs in Africa
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Also, the EBOVs species are closely genetically related, their seems to occur by foci in nature. The host appears to be the same, natural or accidental, and the transmission done by direct contact with infected hosts or its biological products [50, 61]. Altogether, in the early 2000s, before the identification of chiropteran as a potential host-reservoir of the EBOVs, a hypothetic natural cycle was described empirically based on seasonal environmental climatic factors [55]. Then, taking into account bats as a potential reservoir-host, the question of virus transmission was central to consider while environmental factors appears to play a major role to the host and their natural cycle (Chiropteran physiology) (climate/fructification, chorology, bats physiology). Several factors of emergence were then listed including: Chronic infection, infected organs, virus shedding, close encounters between reservoir and susceptible hosts, food and water resource, seasonality, chorology (i.e. causal effect between geographical phenomena – season) in the tropical rain forest and the spatial distribution of chiropteran (i.e. index site of Ebola emerging events).
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Epidemiological field surveys indicate that mass mortalities of apes and monkey species due to Ebola virus often appear at the end of the dry season, a period when food resources are scarce. Restricted access to a limited number of fruit-bearing trees can lead to spatiotemporal clustering of diverse species of frugivorous animals, such as bats, nonhuman primates, and other terrestrial species foraging on fallen partially eaten (by bats) fruits. These aggregates of wild animal species favor the contact between infected and susceptible individuals and promote virus transmission. The dry season aggregation of reservoir host species involved in natural maintenance cycles, augmented by incidentally infected secondary hosts serving as sources for intra- and interspecific transmission chains independent of repeated spillover from the reservoir host, provides an ecological setting for amplifying enzootic transmission of Ebola virus when a vertebrate hosts are concentrated around a scarce number of water sources [62].
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In addition to this dietary impoverishment, there are behavioral and physiological events occurring among bats during the tropical dry favor the contact frequency and intimacy between bats, which can promote transmission of Ebola virus to others and increase R0. As an example, megachiropteran fruit bats breeding activities and intraspecific competitions between males and grouped kidding of females favor the contact between individuals. Moreover, pregnancy can involve physiological changes among female bats that alter immune functions and eventually favor virus shedding. Parturition among the African megachiropteran bats occurs throughout the year, although seasonal peaks provide birthing fluids, blood, and placental tissues, potentially Ebolavirus infected, falling on the ground as a medium highly attractive and readily available to scavenging terrestrial mammals [50, 56, 63] (Figure 4A and B).
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Figure 4.
(A) Understanding Ebolavirus enzootic and epidemics. Red arrows = cycles of transmission; dashed square = a putative natural cycle of Ebolavirus in Central Africa (see B). Fruit bats are considered to be a putative reservoir of Ebola virus in Central Africa after 2004; In 2009, several non-human primate epizootic are reported; 1976 was the first emerging events and subsequent epidemic chains in remote area of the rain forest and close by; 2012 showed a dramatic spread of the virus associated with motorized transportation and ground network; In 2014 urban epidemics are reported as well as a pandemic risk and become an international public health emergency. (B) Putative natural cycle of Ebolavirus in Central Africa. Red arrow indicates Ebolavirus transmission. Numbered red circle of transmission: (1) sylvatic inter- and intra-species transmission; (2) chiropteran migration; (3) chiropter to primate (close contact of dejection); (4) primate inter species (Cercopithecus/chimpanzee); (5) primate to primate (non-human primates); (6) non-human primate epizootic (gorillas); (7) chiropter to duikers; and (8) consumption of chiropteran infected food by shrew or wild pig.
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5. If we had to conclude
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Based on historical data and observations, the presented hypothesis of the natural cycle of Ebolavirus emergence prevail an inter-species spillover as the complex natural cycle involving several hosts (reservoir, vector, amplifier), as well as biotic and abiotic factors in a changing environment among other original features.
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Although the natural cycle of EBOVs remains in the darkness of the rain forest, strong findings and comparative analysis of close parents of the filovirus throw some light to a potential natural cycle of EBOVs in Africa. EBOVs clearly appear linked to chiropteran and dependent for merging events in the environmental factors. Indeed, it appears that filoviridae are often associated with chiropteran while the emergence of the virus strains occurs as a sparse focus with a silent period of cryptic virus circulation. When virus transmission, i.e. spillover, from a hidden natural cycle, to accidental hosts occurs, it happened in a specific time-frame often linked to the season.
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One can retain is that the EBOVs complex natural cycle is yet not on entirely elucidated and certainly dependent on environmental factors – associated with a specific environment of the chiropteran species incriminated (i.e. Different territories, different cycle) - leading to multiple, sometime concurrent, temporally and timely emergence in focus.
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Although, other hypothesis has been suggested elsewhere including the Ebola virus Disease as an arthropod borne disease among others [42], there is important fundamental matters to consider as well before providing more.
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However, beyond these hypotheses, fundamental questions subsist in order to go further learn. We can cite in particular the mystery of kin between the Reston virus of Asia and the Ebola viruses of Africa, would there not be a missing link in a geographic area yet to discover. Do the filovirus exist in the Americas hidden in the darkness of the tropical forest? Also, the Ebolavirus seems genetically stable, related to particular species of chiropter, was it to think about a co-evolution of the host and the virus in this closed environment of the forest of the tropical? Today, with the endless epidemic unfolding in the DRC, should we revisit our tools and strategy of struggle in an ever-changing world? [64].
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Acknowledgments
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We sincerely thank for their supports, brings to all the authors of this deep and never-ending research and scientific thought around an outstanding and fascinating subject: Georgetown University, Centaurus Biotech LLC., The DHS Emeritus Center for Emerging Zoonotic and Animal Diseases at Kansas State University.
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Conflict of interest
All authors do not have any conflict of interest whatsoever with this published manuscript.
\n',keywords:"Ebolavirus, bats, chorology, natural cycle, host, one health",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/69342.pdf",chapterXML:"https://mts.intechopen.com/source/xml/69342.xml",downloadPdfUrl:"/chapter/pdf-download/69342",previewPdfUrl:"/chapter/pdf-preview/69342",totalDownloads:436,totalViews:0,totalCrossrefCites:0,dateSubmitted:"April 15th 2019",dateReviewed:"July 29th 2019",datePrePublished:"October 1st 2019",datePublished:"February 12th 2020",dateFinished:"October 1st 2019",readingETA:"0",abstract:"This chapter presents a review of what is known about the natural history of the Ebolaviruses in Central and West Africa as well as in the Philippines. All the previous hypotheses on the natural cycle of Ebolavirus are revisited. Also, the main factors driving the virus natural cycle are summarized for the different ecosystems where the Ebolavirus is known to have emerged, including the virus species, the date of emergence, the seasonality, the environmental features, as well as the potential risk and associated factors of emergence. The proposed hypothesis of the Ebolavirus natural cycle prevails an inter-species spillover involving several vertebrate hosts, as well as biotic and abiotic changing environmental factors among other original features of a complex natural cycle. It is also compared with other virus having such type of cycle involving chiropteran as potential reservoir and vector and presenting such original inter-outbreak epidemiological silences. Ultimately, these observations and hypotheses on Ebolavirus natural cycles give some insight into the potential drivers of virus emergence, host co-evolution, and a spatiotemporal dimension of risk leading to identify high risk areas for preventing emerging events and be prepared for an early response.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/69342",risUrl:"/chapter/ris/69342",signatures:"Jean-Paul Gonzalez, Marc Souris, Massamba Sylla, Francisco Veas and Tom Vincent",book:{id:"7900",title:"Emerging Challenges in Filovirus Infections",subtitle:null,fullTitle:"Emerging Challenges in Filovirus Infections",slug:"emerging-challenges-in-filovirus-infections",publishedDate:"February 12th 2020",bookSignature:"Samuel Ikwaras Okware",coverURL:"https://cdn.intechopen.com/books/images_new/7900.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"178641",title:"Dr.",name:"Samuel Ikwaras",middleName:null,surname:"Okware",slug:"samuel-ikwaras-okware",fullName:"Samuel Ikwaras Okware"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"190955",title:"Dr.",name:"Jean-Paul",middleName:null,surname:"Gonzalez",fullName:"Jean-Paul Gonzalez",slug:"jean-paul-gonzalez",email:"jpgonzalez2808@gmail.com",position:null,institution:null},{id:"300443",title:"Dr.",name:"Massamba",middleName:null,surname:"Sylla",fullName:"Massamba Sylla",slug:"massamba-sylla",email:"massylla19@gmail.com",position:null,institution:null},{id:"309773",title:"Dr.",name:"Tom",middleName:null,surname:"Vincent",fullName:"Tom Vincent",slug:"tom-vincent",email:"tjvincen@yahoo.com",position:null,institution:{name:"CRDF Global",institutionURL:null,country:{name:"United States of America"}}},{id:"309774",title:"Dr.",name:"Marc",middleName:null,surname:"Souris",fullName:"Marc Souris",slug:"marc-souris",email:"souris@ird.fr",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. When Ebolavirus raised his head in the heart of darkness",level:"1"},{id:"sec_2_2",title:"2.1 The Ebolavirus species emerging events",level:"2"},{id:"sec_3_2",title:"2.2 From Central Africa to West Africa",level:"2"},{id:"sec_3_3",title:"2.2.1 Concurrent emergences of Ebolaviruses",level:"3"},{id:"sec_4_3",title:"2.2.2 An unexpected broader domain of Ebolavirus circulation",level:"3"},{id:"sec_6_2",title:"2.3 From the index case to the epidemic chain, outbreak, and pandemic",level:"2"},{id:"sec_8",title:"3. A strange iteration of epidemic events with unexplained virus disappearance",level:"1"},{id:"sec_9",title:"4. Toward the discovery of the natural cycle of the Ebolaviruses",level:"1"},{id:"sec_9_2",title:"4.1 The discovery of a putative natural reservoir of Ebolavirus",level:"2"},{id:"sec_10_2",title:"4.2 The most complete figure of a putative Ebolavirus natural cycle in the central African raining forest",level:"2"},{id:"sec_10_3",title:"4.2.1 The actors",level:"3"},{id:"sec_11_3",title:"4.2.2 The stages",level:"3"},{id:"sec_12_3",title:"4.2.3 Fundamentals and domains of emergence: a theory for a natural cycle of EBOVs in Africa",level:"3"},{id:"sec_15",title:"5. If we had to conclude",level:"1"},{id:"sec_16",title:"Acknowledgments",level:"1"},{id:"sec_19",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'CDC. Page last reviewed. Content source: Centers for Disease Control and Prevention, National Center for Emerging and Zoonotic Infectious Diseases (NCEZID), Division of High-Consequence Pathogens and Pathology (DHCPP), Viral Special Pathogens Branch (VSPB). 2019. Available from: https://www.cdc.gov/vhf/ebola/history/2014-2016-outbreak/index.html\n\n'},{id:"B2",body:'ICTV. Filoviridae. 2019. Available from: https://talk.ictvonline.org/ictv-reports/ictv_online_report/negative-sense-rna-viruses/mononegavirales/w/filoviridae\n\n'},{id:"B3",body:'Kuhn JH, Andersen KG, Baize S, Bào Y, Bavari S, Berthet N, et al. Nomenclature- and database-compatible names for the two Ebola virus variants that emerged in Guinea and the Democratic Republic of the Congo in 2014. Viruses. 2014;6(11):4760-4799. DOI: 10.3390/v6114760\n'},{id:"B4",body:'MacNeil A, Farnon EC, Morgan OW, et al. Filovirus outbreak detection and surveillance: Lessons from Bundibugyo. The Journal of Infectious Diseases. 2011;204:S761-S767\n'},{id:"B5",body:'Kiley MP, Bowen ET, Eddy GA, Isaäcson M, Johnson KM, McCormick JB, et al. Filoviridae: A taxonomic home for Marburg and Ebola viruses? Intervirology. 1982;18(1-2):24-32\n'},{id:"B6",body:'Anonymous. WHO/INTERNATIONAL STUDY TEAM. Ebola haemorrhagic fever in Zaire, 1976. Bulletin of the World Health Organization. 1978;56(2):271-293\n'},{id:"B7",body:'Anonymous. WHO/INTERNATIONAL STUDY TEAM. Ebola haemorrhagic fever in Sudan, 1976. Bulletin of the World Health Organization. 1978;56(2):247-270\n'},{id:"B8",body:'Centers for Disease Control. Ebola-Reston virus infection among quarantined nonhuman primates–Texas, 1996. Morbidity and Mortality Weekly Report. 1996;45:314-316\n'},{id:"B9",body:'Miranda MEG, Lee N, Miranda J. Reston ebolavirus in humans and animals in the Philippines: A review. The Journal of Infectious Diseases. 2011;204(suppl_3):S757-S760. DOI: 10.1093/infdis/jir296\n'},{id:"B10",body:'Le Guenno B, Formenty P, Wyers M, Gounon P, Walker F, Boesch C. Isolation and partial characterisation of a new strain of Ebola virus. The Lancet. 1995;345(8960):1271-1274\n'},{id:"B11",body:'Towner JS, Sealy TK, Khristova ML, Albariño CG, Conlan S, Reeder SA, et al. 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