Data on the buildings studied.
\r\n\tRisk management aims to develop an efficient organizational development environment through risk planning, assessment, analysis, and control. This process will apply in all areas of activity, and the evaluation framework is the same regardless of the field. This volume will aim to appeal to chapters that address methods, models, evaluation frameworks, benefits, barriers, and other dimensions of risk management.
\r\n\tSustainability and the circular economy are approaches approached by many companies and have become activities of global interest. Protecting the environment, streamlining the consumption of organizational resources, reducing the amount of waste generated, and other activities are objectives of these efforts. The circular economy contributes to the sustainable development of the company or country and the achievement of the global objectives of sustainable development. This book will aim to collect various studies for organizational and global sustainability.
\r\n\tLeadership has become a globally desirable approach that can help improve organizational competitiveness and reduce organizational risks. Risks and barriers in risk-free management can be well managed through effective organizational leadership. This book will aim to bring together chapters that explore different areas of leadership.
Masonry is a material composed of natural or manually manufactured units joined with fresh mortar, which constitute an important inventory of existing buildings in the world from the Egyptian civilization to the present day. The most widely studied and investigated construction techniques correspond to the masonry of the Greek and Roman constructions that have remained to this day. In Africa and Asia, the oldest masonry was made of stone or earth. In America, ceramics were used as masonry in the late nineteenth century that are now part of the local cultural heritage.
The preservation of heritage buildings requires knowledge to guide technical and economic maintenance strategies [1]. Building materials degrade over time when in contact with the environment, and this is a natural and inevitable process. From the perspective of use, the main unknown behaviour is the rate of deterioration, necessary data to raise the estimated construction service life in relation to safety and/or functionality [2].
The use of masonry has significant advantages in cost, installation speed, aesthetics, durability, sound insulation, thermal insulation, fire resistance and accidental damage, energy consumption, maintenance and repair, availability of materials and local workmanship and potential recyclability. Regarding the disadvantages, we have detected the need for greater resistant area compared to reinforced concrete, the need of better foundations, problems in the insulation, the size of the openings, in the arrangement of the joints, considerations of safety and health, durability problems by presence of water and salts and currently lack of skilled labour.
The architectural function of the masonry is the envelope of the building to protect its inhabitants and their belongings from environmental agents, for example, the effect of rain. They can be constituted as walls of barriers or drainage.
Structural masonry can be classified as bearing or nonbearing. The bearing masonry resists the own weight and wind loads or earthquake and gravitational loads generated by the floors or ceilings supported on it [3].
The presence of moisture, whose origin may be the wet soil, rainfall or faulty drainage services, causes damage to old masonry. Although moisture can be measured by different techniques, the results are not repeatable. In other cases, new interventions with new materials have increased moisture problems [2].
The application of the finite element method using nonlinear constitutive models is a tool to verify the observed damages and stress states of historic masonry. But nevertheless, laboratory and field tests are necessary in order to characterise masonry materials and provide reliable data on the design parameters needed for building modelling although the number of samples to be extracted should be minimal.
The methodology used in the study of cases evaluates at the beginning whether the historical works have heritage values or not (Figure 1), defining the responsibilities before specifying the procedure [2]. All the activities involved in this task involve the interaction of different disciplines and an important responsibility of the maintenance management of the heritage.
Basic criteria for recovery of historical works.
Figure 2 presents the different steps of the procedures followed for the rehabilitation of historic buildings, applying safety criteria stated in the regulations and conservation criteria of the International Council on Monuments and Sites (ICOMOS) charts [4]. In this evaluation, the impact of the durability of the materials and the environmental sustainability with the built environment must be incorporated in addition to the safety in the structure.
Procedures of study of heritage construction.
Stone has been used from earliest times. Stone as a material is geographically widespread. Its use in structures is often confined to local materials from a nearby quarry. Load bearing stonework was used up to about the late nineteenth century, but many earlier structures were built of rubble or brick faced with stone ashlar. Since about the year 1900, stone has been mostly used as facade to cheaper masonry or as cladding for other materials.
Stone masonry construction may be of ashlar, squared/coursed rubble, random rubble, etc. Composite rubble/ashlar walls have often been used. It cannot be assumed that a pier or wall with ashlar facing is of solid construction through its entire section; often the core will be of very weak material [5].
Bricks are the oldest man-made building material. Examples of sun-dried clay bricks (adobe) date back to 8000 BC, and fire bricks were used by 2500 BC. Clay bricks were traditionally made locally. Urban buildings of the late nineteenth century and early twentieth century were made of masonry of fired ceramic bricks [5]. In the transition to the use of steel, concrete constructions appear, which employ hybrid metal profiles for supporting floor slabs or as bridges and columns within the masonry to withstand earthquakes known as sidero-brick [6]. Since 1930 the use of reinforced concrete in the world is widespread, leaving the brick masonry walls for minors or cladding in reinforced concrete structures or termination of facades.
Although features may be more reliable as a dating aid, brickwork may sometimes be approximately dated by the brick size. However, there are regional variations which may be greater than those relating to age [5]. Bricks can be fired clay, calcium-silicate or concrete.
Figure 3 shows different placement patterns of solid bricks: stretcher bond, header bond, English bond and Flemish bond, which have different applications in construction (walls, landscaping, pavements).
Common solid brickwork bonds: stretcher (up, left), header (up, right), English (down, left) and Flemish (down, right) bonds [
These patterns allow to identify the time of construction but not the elements of metallic union that were placed from the middle of the nineteenth century in the form of flat strips every four or six courses. Its presence is detected by the slight but regular cracking in these joints due to the increase in volume due to iron corrosion.
The walls with inner cavities are later than 1850 for thicknesses close to 0.40 m and preponderance from 1930 to thicknesses of 0.45 m. These walls generally have a common brick course, an air layer of 0.05 m and a course of decorative purposes or tightness control.
The first uses of concrete blocks are at the beginning of the twentieth century with an important growth due to the demand of houses before World War II. Since World War II, the use of concrete blockwork increased dramatically because of the promotion of cavity walls and the need for improved thermal insulation, which was achieved by the use of lightweight concrete blocks for the inner skin.
Block sizes vary from 390 × 190 × 60 mm to 590 × 215 × 250 mm. The blocks may be solid, cellular or hollow. Densities vary in the range 475 kg/m3 (autoclaved aerated) to 2000 kg/m3 (normal aggregate).
The mortars present in the historic masonry of buildings are typically composed by simple or hydraulic limes. There are two kinds of binders, aerial or hydraulic, depending on the mechanism of hardening [7].
They can be subdivided into simple mortars, hydraulic mortars and composite mortars. The binder can be cement, lime or mix of both. In the past, same mortars contained ash to give a dark colour.
The function of the mortar is to hold together the masonry units and compensate its dimensional tolerances. Also the purpose of mortar is to transfer the gravitational force uniformly through the brickwork, the tying effect being achieved by friction and the staggered pattern of the bricks.
Pure lime mortars, containing no clay or silt, are hardened by carbonation of calcium hydroxide. This can take many years, depending on the porosity of the stone or brick and on the thickness of the wall.
In the case of mortars made from hydraulic lime, where the limestone is ground and fired with some clay or silt, the lime reacts with water for initial strength gain, supplemented subsequently by carbonation of any free lime.
Pure lime mortars (lime-sand) are relatively weak and flexible. Pure cement mortars (cement-sand) may be stronger and stiffer than the stone or brick. If the mortar is too strong, any cracks in the masonry from whatever cause may therefore go through the stones or bricks rather than follow the joints.
Cement-lime mortars (cement-lime-sand) have intermediate strengths; the greater the proportion of cement, the stronger the mortar. Small additions of cement to lime mortars increase the strength marginally but reduce the permeability significantly. This can result in frost damage in porous stone or brick.
Mortar joints are eroded by rain running down faces of walls. This effect is aggravated by chemical breakdown of the binder, because of the acidity of the rainwater. The resistance to this weathering increases with the total proportion of binder to sand. Sulphates, from whatever source, can cause the expansion and disintegration of mortar. Some bricks contain sulphates which may be leached out into the mortar.
The strength of the mortar influences the strength of the masonry in compression, tension and flexure but not to a great degree.
Lime-sand mortars were traditionally used. They were able to accommodate movement, both from the bricks themselves and from the structure as a whole. It was considered a good practice that the mortar should never be stronger than the brick. This must be taken into account when specifying the repair mortar.
Strong cement-rich mortars tend to shrink, which can lead to poor bonding and water ingress into the wall.
The compressive strength of mortar in existing joints cannot be measured directly. The ratios of cement/lime/sand can be established by chemical analysis of mortar samples taken from the joints.
The basic method of construction has barely changed in several thousand years: the units are placed one above the other in such a way that they form an intertwined assembly in at least two horizontal directions. Sometimes order is achieved in the third dimension. Most of the time, an intermediate layer of mortar is used to save small to large inaccuracies between units and make the walls waterproof, airtight and soundproof.
There are four main techniques for achieving stable masonry [8]:
Irregularly shaped and sized but generally laminar pieces are selected and placed by hand in an interlocking mass (e.g. dry stone walls, see Figure 4).
Medium to large blocks are made or cut very precisely to one or a small range of interlocking sizes and assembled to a basic grid pattern either without mortar or with very thin joints (e.g. ashlars or thin-joint).
Small-to-medium units are made to normal precision in few sizes and assembled to a basic grid pattern, and the inaccuracies are taken up by use of a packing material such as mortar (e.g. normal brickwork, see Figure 5).
Irregularly shaped and sized pieces are both packed apart and bonded together with adherent mortar (e.g. random rubble walls).
Photographs of Mendoza, Argentina: (a) prehispanic stone walls (Uspallata), (b) stone bridge (Luján de Cuyo), (c) Jesús Nazareno church (Guaymallén).
Photographs of historical masonry heritage of Mendoza, Argentina: (a) provincial Museum of Fine Arts (Luján de Cuyo), (b) Caro wine vault (Godoy Cruz), (c) Arizu winery (Godoy Cruz).
The behaviour of historical masonry to permanent vertical loads has been satisfactory. A different approach to heritage building occurs when there is a seismic-risk region. The way in which a structure is damaged during an earthquake is strongly influenced by its proximity to the area of fault rupture.
Under the great demands on acceleration and displacement of the seismic events studied, only the conjunction updated with new design procedure regulations, a regular good structural design, static redundancy and proper implementation will allow structures to survive strong earthquakes [2].
By definition, “repair” refers to the post-earthquake repair of damage, caused by seismic ground motion that does not increase the seismic resistance of a structure beyond its pre-earthquake state.
“Strengthening”, “seismic strengthening”, or “seismic upgrading”, however, comprises technical interventions in the structural system of a building that improve its seismic resistance by increasing strength and ductility. According to the proposed terminology, strengthening a building before an earthquake is called “rehabilitation”, whereas strengthening after the earthquake is called “retrofit” [9].
The law procedure and how to decide the appropriate methods are different in each country. However, the practice between safety and historical preservation is almost the same in all countries that have some preservation regulations, but the problems are exacerbated when the effect of seismic actions is added. The California Historical Construction Code [10] has joined the vision regarding heritage aspects and safety. It includes the subject of use and occupation; protection against fire; escape routes and accessibility; structural requirements, materials and old methods of construction; requirements of mechanical and electrical installations; and drains, whenever the building merits the identification of heritage value.
In the United States, the bearing walls of unreinforced masonry (URM) correspond to before 1933 with two courses of bricks joined at their upper end. When the interior was filled with rubble, it was stiffened elastically and modified the behaviour of the frames where the masonry is inserted.
The behaviour of horizontal diaphragms in historic masonry is often deficient because they are not sufficiently connected to transfer the horizontal seismic forces to the resistant side walls. They are usually made of wood, supported by beams anchored in wall inserts, which are affected by deformations outside the plane of the loaded wall, which can lead to the overturning of the wall and the collapse of the building [3].
The Long Beach earthquake (California, 1933) showed the bad behaviour of this masonry, causing the prohibition to use it in school buildings. The UBC of 1943 established that the masonry had to meet the same criteria of design of the reinforced concrete of that time, appearing the armed masonry.
The Santiago (Chile) and City of México (1985); Izmit, Turkey, and Quindío, Colombia (1999); Pisco, Perú (2007); L’Aquila, Italy (2009); Lorca, Spain (2011); Kathmandú, Nepal (2015); and Manabí, Ecuador (2016) earthquakes have shown that nonengineering masonry buildings have suffered significant damage, especially the masonry constructions in adobe and in stone [3, 11, 12].
The tests of historic masonry specimens obtained from existing structures are scarce. However, there are several investigations carried out in small-scale replicas of URM or in different scales carried out in the United States, Italy and Yugoslavia in the last 25 years [3, 9].
There are in situ testing techniques to measure the compressive strength of the masonry, which produce some damage and require special equipment. The experimental static tests can be applied: flat-jack test and pull out. Ultrasonic, geo-radar, acoustic emission, static monitoring, thermography, X-ray diffraction can be used as non-destructive tests; which sometimes are not justified for masonry routine evaluations that have less thickness than the historic masonry.
The dynamic tests can be ambient vibration testing, even to register a long-term dynamic monitoring.
From the point of view of durability, the walls as an open system are in contact with other contiguous structures that take part in the dynamics of the overall behaviour. Even when any infiltration can be successfully eliminated, contact with the ground or with adjacent walls provides moisture sources by capillarity. Virtually all walls contain soluble salts, either dispersed within porous materials or locally concentrated. They can be present as efflorescence that form different aggregates of crystals with various shapes and located on the surface, such as sub-springs that form crystalline aggregates below the surface, and as solutes in aqueous solutions on and inside the walls.
The main known salts produced in the walls are carbonates, sulphates, chlorides, nitrates, oxalates and sodium, potassium, calcium, magnesium and ammonia. The different salt species, precipitated from multicomponent systems, vary considerably depending on the materials present, but the type of salt found can, therefore, very often give indications of their origin.
Both the plasters and the paint layer of the walls are typically open structures with high porosity (their pores can easily be intercommunicated). This means that there is a large surface exposed to the degradation agents and there is easy permeability to fluids in contact with it both liquids (solutions of salts diluted in the wall) and gases (atmospheric pollutants and water vapour) [13].
In masonry it is required that the chemical compatibility between the mortar of replacement and the old mortar, the physical compatibility in relation to the process of solubility of salts and water of transport and the structural compatibility where the resistance of the new mortar must be similar to that of the masonry historical in order to avoid damages by the use of mortars with Portland cement.
As far as mortars are complex systems, different approaches can be used for their characterisation. Nowadays, the reconstruction of the original composition is quite complex and requires the application of various and complementary techniques. In addition, the technological culture of making lime mortars has been lost, although from the economic point of view they would be of lower cost [7]. The need for mortar compatibility has led to the design of specific products to avoid damage by chemical reactions as shown in Figure 6 [2].
Evolution of the mortar compatibility process during rehabilitation of school building [
The directed behaviour of the geomaterials (shear as a function of compressive strength) requires computational models that allow capturing the different failure modes and, without losing precision, represent them in a simple way. In accordance with this, there are several modelling techniques; the micro-models consist of the modelling of the masonry units and the mortar as continuous elements, while the masonry-mortar interface is represented by means of discontinuous elements. As the macro-models, these are phenomenological models in which masonry units, mortar and interface are represented as a composite by means of a continuous element. The technique to be used is based on the level of accuracy and simplicity desired [14].
Phenomenological models allow focusing on the overall response of the structure at a lower computational cost. For this to happen, it is necessary to establish a constitutive model whose response is representative of the behaviour of the composites. The constitutive model of Drucker-Prager [15, 16] allows to represent the behaviour of the masonry as an elasto-plastic material with a strong dependence on the acting pressure. The low number of variables to define makes this model attractive. In turn, the characterisation of these variables can be carried out in a simple way through a diagonal compression test in laboratory or application of flat-jack in situ.
To obtain the modelling parameters of the masonry, laboratory tests are carried out in a 1:1 scale on specimens of different thickness [15]. With the experimental results achieved, a finite element model is formulated using the Abaqus software [16] whose parameters allow to obtain a behaviour similar to that observed during the tests.
Based on the model generated and calibrated, the building geometry and the state of applicants loads are simulated, the results of which are compared with the real damage evidenced in the structures analysed. The analysis of the results from the structural simulation allows a better understanding of the causes of the deterioration as well as the cracking patterns. These results have allowed us to make a proposal for its repair and subsequent rehabilitation.
Figure 7 shows the general structural model and the state of stresses of the masonry of an educational building [17]. It shows the concentration of stress associated with the wall encounters and points of application of loads, points that must be reinforced locally, while the rest of the masonry is subjected to a normal tension level below the stress maximum. In Figure 8 we can see the result of the modelling for the damage in archs, and Figure 9 shows the detachment of the main facade.
Comparison of stress state modelling and building damage status [
Comparison between stress state modelling and building damage status [
Simulation of facade damage due to inefficient foundation [
In the case of the museum in Figure 10, the stress concentration in the walls of the central nave is observed as a result of the differential settlement between this sector and the lateral ones [18].
Damage due settlements of different sectors [
Table 1 shows the cadastral characteristics of historic masonry buildings studied in Mendoza, Argentina, from 1999 to 2015 [2].
Evaluated | Saint Francis Ruins, Capital | Mitre School, Capital | Giol Chalet, Maipú | Fader House, Luján de Cuyo |
---|---|---|---|---|
Date of building | XVIII century | Late nineteenth century−1906 | 1910 | 1892 house 1905–6 paints |
Date of study | 1999 | 1999 and 2010 | 2012 | 2013 |
Charge heritage | National Direction Architecture Municipality of Capital | Direction of Heritage Government of Mendoza | Municipality of Maipú National Direction Architecture | Direction of Heritage National Direction Architecture |
Intended use | Outdoor museum | Educational museum | Vintage museum | Fine arts museum |
Archaeological and historical background | Historical and archaeological studies | Few historical and archaeological studies | Few historical studies. No archaeological studies | Few historical studies. No archaeological studies |
Data on the buildings studied.
Table 2 shows the data obtained in the evaluation of the condition of the historic masonry buildings prior to the value enhancement [2].
Characteristics of previous interventions, masonry and existing pathologies.
Table 3 shows the soil criteria and masonry modelling for different buildings studied. It is taken as a criterion modelling by finite elements for walls using the type plate element of four or eight nodes. Drucker-Prager model has been used for the simulation of material failure [15]. The foundation is modelled by elastic springs, or the soil is modelled directly, considering its rigidity (elastic), since in this type of structure soil stiffness plays a fundamental role. For the roof structure, which is generally flexible, main resistance elements such as trusses or girders (ridges, etc.) are modelled, distributing loads to these elements. The seismic action is determined by applying the methods established by the regulations as proportional forces to the mass of each node of the finite element mesh [17].
Evaluated | Saint Francis Ruins, Capital | Mitre School, Capital | Giol Chalet, Maipú | Fader House, Luján de Cuyo |
---|---|---|---|---|
Modelling soil | Triangle 15 nodes Mohr-Coulomb elastic theory Plaxis Bv | Triangle 15 nodes Mohr-Coulomb elastic theory Plaxis Bv | Elastic theory | Elastic theory Interaction with Abaqus |
Modelling structure | Elastic Midlin theory Plaxis Bv | Eight nodes isoparametric nonlinear Abaqus SAP2000 linear retrofit | Linear masonry plates SAP2000 linear retrofit | Nonlinear model Drucker-Prager masonry Abaqus SAP2000 linear retrofit |
Estimate safety | It supports earthquake IV MM | >80% of the original | >80% of the original | >80% of the original |
Type of proposed intervention | Reversible (temporary propping) until the final consolidation project | Reversible (outer metal reinforcement chained) Irreversible in foundation | Irreversible (removal of corroded profiles) Without intervention foundation | Reversible (outer metal reinforcement chained) Irreversible in foundation |
Present status | Executed | Executed | Proposed | Executed |
Modelling and type of intervention.
A large number of historical structures do not meet safety requirements because today’s requirements are more demanding than those at the time of construction and because many years have passed by since their construction and structural safety has deteriorated due to use and time. To bring these historic buildings to a level of safety standards today, it is necessary to adapt its structure. However, historical value may be lost due to intervention; therefore, new approaches are needed to achieve sufficient safety.
The San Fernando, California, earthquake of 1971 demonstrated that the adaptation of the parapets to avoid their fall was effective. The 1994 Northridge, California, earthquake showed little damage to historic reinforced masonry with respect to URM that suffered damage and collapse [3].
The structural rehabilitation of historical buildings could be done by hiding those new structural elements or exposing them. Sometimes, the exhibition of new structural elements is preferred because alterations of this type may be reversible; in the future they can be changed without losing the historical character of the building [17].
The decision to hide or expose structural elements is complex, and there is to be a consensus with the preservation professionals who are participants of the project. In high seismic-risk area, it is difficult to strictly follow the principles of the different restoration charts (Venice, Athens, etc.), and the task is a challenge of structural engineering [17, 18].
The strengthening techniques depend on the building response to the earthquake. Different response leads to different strengthening methods. Three main groups could be:
Interventions to obtain better global response of the building (in case of building box type behaviour and a prevailing in-plane response, Figure 11)
Interventions for the local mechanisms (in case of a prevailing out-of-plane response, Figure 12)
Interventions on blocky structures (where the kinematic mechanisms must be prevented: obelisks, towers and also arches and vaults, Figure 13) [19]
Reinforcement of foundations and reversible metallic structures in columns and lattice, Mitre school, 2012.
Bidirectional tensors for bracing of historic masonry walls, Fader House, 2013.
Support structure of masonry blocks, Saint Francis Ruins, 2011.
In the PERPETUATE project [18], both traditional and innovative intervention techniques have been evaluated. Some of the methods that are widely used in URM structures are insertion of horizontal tie rods; insertion of anchors between structural elements; adding new walls, buttresses and foundations; changing of weak mortar in joints of existing masonry (repointing); repair of cracks; jacketing of walls with reinforced concrete; grout injections of stone masonry walls; injections of cement or epoxy-based grout into cracks; and insertion of reinforced concrete “ring” beams or moment frames and reinforced concrete slabs. Each of these mentioned methods has its own advantages and disadvantages.
Some innovative methods are strengthening brick masonry with attaching FRP fabric to the surface, restoration of stone masonry with compatible cement grouting, insertion of transversal connection in stone masonry walls, installing seismic isolation for single assets scale and installation of energy dissipation devices [18].
The choice of rehabilitation technique depends on the condition of the masonry, the availability of local workmanship and the safety requirements [4, 9, 11].
The effectiveness of a rehabilitation can be evaluated by system identification techniques. They measure the dynamic properties of the structure through environmental vibration before, during and after the structural reinforcement. The vibrations of low amplitude come from different sources, among them, the vehicular traffic, the micro-tremors, the wind, etc.
In the case of masonry, the parameter used to measure the efficiency of the structural reinforcement is the period of the walls measured at the top of them. Before starting the reinforcement work, the environmental vibration in the structure is measured in order to know the periods of the same with the existing level of damage. Once the foundations are consolidated and the walls reinforced, new measurements are taken, and in this way we can know the degree of recovery that the structure has had up to that stage as indicated in Figure 14 [20].
Evaluation of the change of the dynamic properties of the masonry building in the different stages of the rehabilitation [
The study of rehabilitation of masonry involves a team of specialists from historians, architects, structural engineers, geotechnical and chemical technicians, etc. That is, it cannot be considered only as a structural problem.
The seismicity of the site and the abandonment of the old buildings have caused the collapse of most of the old buildings, leading to the loss of cultural values that have been part of the local history. Therefore, the rehabilitation of old buildings should be considered a state policy, in order to preserve the few buildings that remain for the future.
It is emphasised that in the region with near-source earthquake, historic buildings that have been standing are made up of ceramic solid bricks; only very few of adobe and stone have managed to survive due to the high demand for ductility of earthquakes near-fault.
Modelling by MEF applying nonlinear constitutive models provides an effective tool for the simulation and verification of historic masonry heritage buildings, so it is necessary to research the formulation of efficient constituent models for thick masonry.
The monitoring through environmental vibration measurement has been a useful tool to evaluate the level of recovery of construction, allowing in the future to evaluate the state of conservation of the same. Model calibration is possible from frequency identification.
This work has been part of programme PICT 2015-761 supported by the Technological National University of Argentina and National Agency for Promotion of Science and Technology of Argentina. The authors want to thank the university staff and the professionals of preservation of Heritage Bureau of Province of Mendoza and CONICET because they had made the development of the research programme possible.
Respiratory allergic diseases are among the most prevalent chronic disease, affecting 20–25% of the general population. Allergy reactions at large encompass several mechanisms, but allergy reactions to pollen are considered as a “ type-1 ” or “ immediate-type ” or “ IgE-dependent ” hypersensitivity reaction involving mast cells and basophiles as effectors cells. Those cells are responsible for releasing inflammatory and immune mediators leading to ocular, nasal, and bronchial symptoms. Pathophysiology of these reactions allows the use of skin tests and/or measurement of serum specific IgE as powerful diagnostic tools.
The prevalence of allergy is increasing whatever is the allergenic source, pollen, food, animals. Pollen grains are the main inducers of respiratory allergies, and conifers play a major role around the Mediterranean basin, in North America, or in Japan. According to a phylogenetical classification, the conifers consist of one class, Pinopsida, and seven families have been described: Araucariaceae, Podocarpaceae, Sciadopityaceae, Cupressaceae/Cephalotaxaceae/Taxaceae, and Pinaceae. No extensive studies were reported on the allergenicity of the pollen grains from Araucariaceae and Sciadopityaceae, but a huge amount of data are published for Cupressaceae/Taxaceae (also reviewed in [1]) and Pinaceae pollen (see below). Cephalotaxaceae are sometimes included in Taxaceae and Araucariaceae and might be assimilated to pine because of the Wollemi pine discovered in Australia. A few data are available on the allergenicity of Podocarpaceae pollen [2, 3].
This review provides an update on various aspects of the highly allergenic family of conifer, i.e., Cupressaceae (Chapter 2) with, first, a botanical and palynological presentation of cypress followed by the various cypress pollen allergens involved; second, data on epidemiology; and third, the clinical aspects together with the management of cypress pollen allergy. Chapter 3 is devoted to the poorly allergenic conifer family, Pinaceae.
Cupressaceae corresponds to a family of the order Pinales. According to a phylogenetical classification, the family includes about 140–160 species with 27–30 genera. Cupressaceae is the most widely distributed conifer worldwide, except Antarctica devoid of any trees (Figure 1). Cupressaceae, commonly named cypress, is the most well-known gymnosperm family that produces allergenic pollen. Two main contributors to cypress pollen allergies belong to Cupressoideae by species from the
Worldwide distribution of reported Cupressaceae pollen allergy (orange dots).
Besides botanical and phylogenetical classification, a classification was proposed based on the functional and structural aspects of allergens (Table 1) [4, 5]. These allergens in different species exhibit a high degree of homology, up to 97% between
Groups | Proteins | Cupressus sempervirens | Hesperocyparis arizonica | Cryptomeria japonica | Juniperus | Chamaecyparis obtusa | Taxodium disticum | Thuja | |
---|---|---|---|---|---|---|---|---|---|
Italian cypress | Arizona cypress | Japanese cedar | Mountain cedar | Japanese cypress | Bald cypress | cedar | |||
Group 1 | Pectate lyase (40-45 kDa) | Cup s 1* | Cup a 1* | Cry j 1* | Jun a 1* | Jun c 1, o 1, v 1* | Cha o 1* | Thu p 1 | |
Group 2 | Polygalacturonase (43-60 kDa) | Cup s 2* | Cup a 2 | Cry j 2* | Jun a 2* | Cha o 2* | Tax d 2 | ||
Group 3 | Thaumatin-like protein PR-5 (24-34 kDa) | Cup s 3* | Cup a 3 | Cry j 3 | Jun a 3* | Jun r 3, v 3* | Thu oc 3 | ||
Group 4 | Ca-Binding protein (17-29 kDa) | Cup a 4 | Cry j 4 | Jun o 4*, v 4 | |||||
Group 5 | Gibberellin-regulated protein (8kDa) | Cup s 7* | Cup a 7 | Cry j 7* | Jun a 7* | ||||
OTHER | ß-galactosidase 46-50 kDa | ß-galactosidase 46-50 kDa | Chitinase 27 kDa | Cha o 3* 63 kDa | |||||
Profilin (Cup s 8) 14 kDa | LTP 14 kDa | CJP8 (LTP) 17 kDa | |||||||
Phenylcoumaran reductase 33 kDa | Isoflavone reductase 35 kDa | ||||||||
Rab-like protein 18 kDa | Aspartic protease 42 kDa | ||||||||
Sigma factor regulation protein 29 kDa | Serine protease subtilisin-like 79 kDa | ||||||||
Cytochrome c 12 kDa | |||||||||
SOD 15 kDa | |||||||||
Lactoyl glutathione lyase 32 kDa | |||||||||
Malate dehydrogenase 31 kDa | |||||||||
Triosephosphate isomerase 33 kDa | |||||||||
Glucanase 37 kDa | |||||||||
HSP104 104 kDa |
Cupressaceae allergens. Name, protein function, and molecular masses (kDa) are indicated.
*referenced in IUIS/WHO database; Jun c: Juniperus communis (Common juniper) ; Jun o: Juniperus oxycedrus (Prickly juniper); Jun r: Juniperus rigida (Temple juniper); Jun v: Juniperus virginiana (Eastern red cedar); Thu p: Thuja plicata (Western red cedar); Thu oc: Thuja occidentalis (Eastern white cedar); SOD: Superoxide dismutase; LTP: Lipid transfer protein; HSP: Heat shock protein.
Within a species, the pollination period is usually short. However, because of the different species in Cupressaceae, the pollination periods do not overlap, and this contributes to extend the exposition duration to Cupressaceae pollen from autumn to spring. In Mediterranean regions, pollen from early pollinating species (e.g.,
All Cupressaceae species produce spherical pollen grains very similar in appearance (Figure 2A) [14]. In the
A:
Cupressaceae trees are anemophilous, and pollen grains can be wind-transported over long distances because of their small size. Cupressaceae species generally produce huge quantities of pollen. The number of pollen grains per male inflorescence average 400,000, and production by individual trees has been estimated to be 276,000 million [18, 19]. Cupressaceae pollen predominates in the winter period, but can also be present all year long (Figure 3). In Mediterranean regions
Cupressaceae pollen dynamics over the course of the year in the Mediterranean area: Barcelona (Spain); Aix-En-Provence (France); Vielha, (Spain); Mornag (Tunisia); Thessaloniki (Greece); Madrid (Spain) and outside Mediterranean area: Paris (France); and Gümüshane (Turkey). Mean daily (thick black line) and maximum daily (thin black line) pollen concentrations are indicated for the period.
Comparative sampling methods developed during the last decades of the twentieth century showed that concentrations of airborne pollen diversity have steadily progressed [36, 37, 38, 39].
At least four indices exist to characterize the dynamics and patterns of airborne pollen:
In the case of cypress pollen, the pollination period (except in mountainous and in very cold sites) begins in autumn and lasts until the end of the following spring. However, in the Mediterranean area, days without any cypress pollen are rare. Therefore a percentage method was proposed. The season is considered to begin when 2.5% of the API has been reached and finished when 97.5% was reached. This method is not totally satisfactory because of substantial year-to-year variations of API.
Using pollen collectors mainly located in urban areas, the Cupressaceae API showed increasing trends in Mediterranean countries. This was shown in Southern France with an early pollination onset [40], in Greece [41] or in Catalonia (NE Iberian Peninsula). Two of these API trends, for Barcelona and Vielha, are shown in Figure 4 together with the trends in other localities around the Mediterranean. These trends were confirmed for 23 taxa from 13 European countries (97 sites) [42]. Authors did not find any correlation with variation of temperature and rather proposed, as an explanation, the extensive use of Cupressaceae as ornamental plants in the cities. Ariano
Cupressaceae annual pollen index (API) and trends at the localities with the longest continuous data series. Madrid (Spain), Barcelona (Spain), Vielha, (Spain), Aix-En-Provence (France), Paris (France), Thessaloniki (Greece), and Ankara (Turkey).
The daily pollen concentration threshold levels required to elicit allergic symptoms in patients remain a crucial question, and no general agreement has been reached. For instance, in Israel, the threshold is considered to be between 10 and 50 pollen grains/m3, whereas in France, different thresholds of symptom risk have been established for the Mediterranean area (designated as low, when 7–13 pollen grains/m3, moderate when 14–141 pollen grains/m3, and high >141 pollen grains/m3, respectively), and for the north and center of France (designated as low when 70–141 pollen grains/m3 and moderate when >141 pollen grains/m3 [44]). The Catalan Network of Aerobiology defined the risk of allergy as being low when concentrations are <20 pollen grains/m3, moderate for 20–50 pollen grains/m3, high for 50–100 pollen grains/m3, and very high when >100 pollen grains/m3. Furthermore the risk to develop allergy symptoms was shown to be increased by airborne pollutants, especially PM2.5 and suspended particulate matter [45].
The cypress pollen is considered to be highly allergenic (see, for instance, the website of the French National Network of Aerobiological Surveillance, RNSA,“Réseau National de Surveillance Aérobiologique”, www.pollens.fr). The allergenic potential of specific pollen depends on the following:
the degree of exposure, related to the total pollen amount released in the atmosphere (from intact or fragmented grains);
the phenological conditions in the considered area;
temperature, hygrometry, photoperiod, …;
air pollution.
The exposure to cypress pollen is high because of an abundant production of pollen (see pollen chapter), making of this pollen the most represented in the atmosphere (up to 40% of total pollen counts around Marseille in the south of France). Not only is the load high but also the spreading, since rather small pollen, can be wind-transported. Moreover, the pollen grain carries sub-micronic particles named orbicules on its surface (Figure 2A). These orbicules were shown to contain allergens from the groups 1 and 2 [46, 47, 48, 49, 50] (see below for the definition of groups of allergens) and to be easily released upon rainfall and an experimental
Up to now, five groups of allergens have been described in cypress pollen, although all allergen members for each species have yet to be referenced in the International Union of Immunological Societies (IUIS) allergen data bank (www.allergen.org): group 1: pectase lyase, group 2: polygalacturonase, group 3: thaumatin-like protein, group 4: Ca-binding protein, group 5: Gibberellin-regulated protein. Furthermore, about 20 additional allergens have been reported in the three most studied pollens,
Pollen/pollen
Cross-reactivities between pollen are common because proteins may belong to families of panallergens, such as Ca++-binding proteins or profilins. Some cross-reactivities were observed with
Pollen/food
Like for pollen from birch, mugwort, grass, ragweed, olive, plane, cypress pollen sensitization was shown to be associated to food allergies. In general, up to 60% of food allergies are associated with an inhalant allergy [73]. A pollen food allergy syndrome (PFAS) has been described, including mainly an oral allergy syndrome. As soon as 2000, Ishida
Cypress pollen allergy was reported for the first time in 1929 in the United States (Texas and New Mexico) [82] and in the early 1960s in Europe [83]. Cypress pollinosis is also reported in several locations worldwide: Japan [84], Australia [85], Iran [86], South Africa [87], the United States, and with special emphasis around the Mediterranean basin [88, 89, 90, 91, 92, 93, 94] (Figure 1).
There are consistent correlations between exposure to Cupressaceae/Taxaceae pollen and the presence of sensitization and allergy [95]. Studies performed in the general population are scare. In southern France and in Italy, two studies performed in children [96, 97] and one study in young adults [98] concluded that around 2–4% might suffer from cypress pollen allergy. A study performed in Japan led to a number of
In surveys performed in Mediterranean countries, 14–32% of patients attending an allergy clinic had an allergy to cypress pollen [1]. In a larger Italian study from Rome, 23,077 outpatient sera were studied. The presence of specific IgEs against 75 allergens was investigated, and 42.7% of the subjects exhibited specific IgEs against cypress pollen. In this survey, cypress allergy was the leading cause of sensitization in adults over 35 years of age (in children, house-dust mite allergy was the leading cause) [100]. In Montpellier, a cross-sectional study performed in 400 outpatients concluded that cypress pollen sensitization (20.7%) ranked third, after sensitization to
Several cross-sectional surveys carried out repeatedly over time showed an increase in the proportion of cypress allergy among outpatients consulting for allergic rhinitis: rising from 9.9% in 1991 to 24.5% in 1993, then to 35.4% in 1994 in central Italy [102], from 9.3 to 30.4% between 1994 and 1999 in the area around Rome [103], and from 7.2 to 22.0% between 1995 and 1998 in Italy’s Latium area [104]. A recent study in the southern region of Italy showed that cypress pollen sensitization almost doubled from 2005 (17%) to 2010 (29%) [105]. Eighteen were sensitized to cypress or Taxodiaceae pollen in an Italian survey of 3057 outpatients selected in 12 study centers [106]. The sensitization rate was higher in southern Italy (20.1%) and central Italy (28.2%) than in northern Italy (9.2%). In a more recent survey, the geographical hierarchy was unchanged, but the prevalence figures went up to 32.7%, 62.9%, and 16.1%, respectively [107]. A study performed in western Liguria demonstrated an upward trend, whereas pollen counts remained unchanged [108, 109]. This study, like the one by Mari
The rationale for such a rapid increase in prevalence mainly lies with the fact that:
millions of cypresses were planted in the 1970s and 1980s in the suburbs and around private houses and blocks of flats to offer a degree of privacy. Therefore the proximity of pollen sources has drastically changed: whereas Cupressaceae were traditionally planted in agricultural zones, away from dwellings, nowadays they are planted as hedges to as visual barriers.
at the same time, a decrease in farming allowed for the extensive proliferation of
lastly, in urban areas, air pollution interacts with pollen to increase the allergenicity [51] (see below).
In contrast to other respiratory allergic diseases, part of cypress pollen allergic patients have no personal or familial history of allergic diseases, and in this subgroup, the onset of symptoms occurs at an older age [111, 112]. Therefore, even non-atopic individuals repeatedly and heavily exposed during many years to cypress pollens can develop this allergic condition. In high exposure areas, the general population may become allergic to this pollen.
Ishizaki et al. first noticed in the 1980s the association between Cupressaceae pollen allergy and air pollutants [84]. They found that living near Japanese cedar trees in urban areas tended to increase the allergy risk compared with living near these trees in rural areas. Concomitantly in Japan, Muranaka
Since then, Cupressaceae pollen grains have frequently been used as a model to study the interrelationship between air pollutants and pollen allergies [51, 118]. The effects of pollution on the molecular and developmental biology of Cupressaceae pollen has been exemplified by several studies. In polluted areas, the accumulation of numerous inorganic elements such as sulfur, copper, aluminum, and iron on pollen grains and the acidification of pollen surfaces by the adsorption of acid gases such as nitric and citric acids were demonstrated. The natural exposure of Arizona cypress pollen to air pollutants in Barcelona and Madrid promotes the production and release of an allergenic protein (
According to the Japanese survey [99], and a subsequent study from Europe, rhinitis is more common than conjunctivitis. The latter is, however, the most disabling symptom, occurring in 72% of patients allergic to cypress pollen, versus 26% of patients allergic to grass pollen [111]. In this study, the occurrence of a chronic cough was much more frequent with cypress pollen allergy, whereas asthma symptoms during the pollen season were equally prevalent in patients allergic to grass and cypress pollens. Besides, allergy to cypress pollen was more disabling than other pollen allergies, according to a visual analog scale used by 4025 patients visiting their general practitioner for allergic rhinitis [121].
The diagnosis of cypress pollen allergy mostly relies on the clinical history, which is usually highly suggestive because most cypresses pollinate in wintertime when no other airborne pollens are present. The diagnosis is supported by skin tests, using either a mixture of
Compared with other allergic diseases, no specific pharmacologic treatments are given for this condition.
Although they only included a limited number of patients, several clinical trials have addressed this issue [1]. A benefit in terms of symptoms, quality of life, on-demand medications, late cutaneous response to allergen, and specific nasal hyperactivity was demonstrated in all trials. Clearly, larger clinical trials including longer treatments and longer follow-up periods are required.
While all of these procedures are based on common sense, they have not been clinically validated [124]. This paper demonstrated that four recommendations are provided by most scientific committees and organizations: avoiding outdoor activities, consulting pollen forecasts, avoiding drying laundry outdoors, and wearing pollen protective glasses and mask when outdoors. All these pieces of advice are applicable when the taxon to which an individual is sensitized is present.
Integrated strategies have to be developed to prevent cypress pollen allergy, in addition to medical care and desensitization. The reduction in individual exposure to pollen is the upstream component of this strategy. Pollinosis is more frequent in urban areas, although airborne pollen concentrations should be lower than in rural areas [125]. Therefore, the allergenic features of ornamental plants that are used in urban green spaces, parks, and gardens should be taken into account in future urban planning [126]. Should be chosen over allergenic wind-pollinated species non-allergenic species and/or insect-pollinated species the use of the latter species should be reduced in order not to aggravate their impact on allergy sufferers, even if cultural and historical reasons often make this a difficult choice.
A “Database of Urban Tree Potential Allergenic Values,” integrating the different components of the allergenicity risk (e.g., tree size, type of pollen dispersal type, flowering period, etc.), has been generated for all of the individual trees producing an estimate of the allergenicity of Urban Green Zones [127, 128].
People with pollen allergies could limit their exposure to pollen through consulting forecast of pollen emissions based on phenological modeling of pollination. They should avoid spending time in areas with high densities of Cupressaceae taxa. Because pollen penetration in summer was estimated to be one hundred times higher than in winter and although pollen is much more abundant in winter, the penetration of pollen into dwellings must also be minimized by avoiding the opening of doors and windows in the summer time [129]. This is all the more true that cypress pollen allergenic potency was shown to last over at least a 10-month period in an indoor environment [130].
Trimming of isolated trees or hedges before pollination represent a complementary strategy to reduce the amount of pollen produced by Cupressaceae trees. It can significantly reduce pollen production [131]. An efficient medium- to long-term way to reduce atmospheric pollen loads without the need to eradicate the Cupressaceae species in urban areas could be to select low pollen producing varieties. Female cultivars are preferable for the few monoecious species. Low pollen cultivars should be selected for other species, either in natural populations or breeding populations, as for
As stated in the introduction, Cupressaceae/Taxaceae and Pinaceae are the three families of conifers studied at an allergy point of view. Pinaceae is mentioned as poorly allergenic in the RNSA data bank despite a huge amount of pollen produced. Eleven genera were described distributed in four subfamilies and 220–240 species. Two genera are presented below,
From the family Pinaceae, the genus
Pine trees are evergreen, conifer trees with leaves as needles bundled in clusters called fascicles. Pines are mostly with male and female cones on the same tree. The male cones are mainly present in spring, falling after pollen shedding. The female cones have numerous spirally arranged scales, with two seeds per scale. Some pine seeds (pine nuts) are edible and have been reported to induce allergies. Pine pollen grains are 40–80 μm diameter, are heavy, and harbor a waxy hydrophobic coat. They are easily distinguishable under microscope observation because of two balloons filled with air. This particularity does not help the pollen to float in the air but rather to float on a water surface. The tree is anemophilous, and pollination is abundant generating the so-called “sulfur rain” during pollinating season [135, 136].
Despite the sometimes widespread pine forest and the abundance of pollen grains, the allergenicity of pine pollen was considered very poor if not nonexistent by some authors [137, 138, 139, 140, 141, 142, 143, 144]. The involvement of pine pollen in seasonal allergic reactions has been evaluated in some studies and has generally been considered of little clinical significance. For example, Harris and German, in 1985, evaluated 200 patients during the pine pollen season [145]. Among them, only five had a positive skin test to pine pollen (
There are several hypotheses to account for this low apparent clinical significance, which is at variance with the heavy pollen exposure in areas densely covered with pines. Firstly, there might be an underestimation of the sensitization rate because protein extraction from pine pollen is difficult [156]. In comparison to classical extraction protocols such as soft incubation in aqueous solution, grinding of the pollen grains together with 1 mm silica beads results in 20–50 times more extracted proteins amount (Figure 5) [157]. The improvement of the extraction is not only quantitative but also qualitative. Interestingly Pasaribu
Pine pollen (
From the family Pinaceae, the genus
Fir is present in many homes during Christmas time, and there are a few reports of rhinitis and conjunctivitis occurring during and following Christmas tree exposure [163]. However, authors concluded that these symptoms were not pollen-dependent but rather caused by volatile organic compounds emitted by the tree since fir pollen grains have disappeared at Christmas time. One of these compounds was identified as colophonium shown to be able to sensitize allergic patient to induce dermatitis [164]. Another confounding and misleading factor could be mold spores contaminating the Christmas tree [165]. Mold spores such as
Out of the seven families described in conifers, obviously the Cupressaceae/Taxaceae was the most studied precisely because its wide distribution and the powerful allergenic potential of its pollen giving rise to a high prevalence where Cupressaceae/Taxaceae is implanted. Furthermore numerous associations with food allergy were reported inducing not only respiratory but also food allergy symptoms from the oral syndrome to more severe outputs such as systemic anaphylaxis or urticaria. Sensitization can occur lately, in non-atopic individuals and thus, represents a public health threat. However, compared with ragweed or grass pollen allergy, Cupressaceae trees rarely spontaneously reproduce, and their expansion could then be controlled by policymakers.
Pinaceae pollen allergy was also studied, though to a lower extent, because pollination is huge despite a very low prevalence. Therefore it does not represent an important health issue. The question of food cross-reactivity was also addressed, especially with the edible pine seeds, but no convincing data were published.
However, the climatic change and polluted environment might result in a general trend to increase allergenicity of airborne allergenic sources, including pollen. Therefore an immunosurveillance and health monitoring should be maintained for all pollen species.
The authors declare that they have no conflict of interest concerning this article.
A part of the work on aerobiology was funded by the ICTA “Unit of Excellence” (MinECo, MDM2015-0552).
A part of the work on allergen identification was supported by the program Hubert Curien-Barrande 2015-2016 (France and Czech Republic scientific exchanges).
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He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}}]}},subseries:{item:{id:"26",type:"subseries",title:"Machine Learning and Data Mining",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence",scope:"The scope of machine learning and data mining is immense and is growing every day. 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