Parameter sensitivity ranking and category of the most sensitive parameters.
\\n\\n
IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\\n\\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
\\n\\nBiomedical Engineering, ISSN 2631-5343
\\n\\nInfectious Diseases, ISSN 2631-6188
\\n\\nPhysiology (Coming Soon)
\\n\\nDentistry (Coming Soon)
\\n\\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\\n\\nNote: Edited in October 2021
\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/132"}},components:[{type:"htmlEditorComponent",content:'With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\n\nLaunching 2021
\n\nArtificial Intelligence, ISSN 2633-1403
\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
\n\nPhysiology (Coming Soon)
\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"6011",leadTitle:null,fullTitle:"Advances in Shoulder Surgery",title:"Advances in Shoulder Surgery",subtitle:null,reviewType:"peer-reviewed",abstract:"The goal of this book is to provide readers with an update on recent developments in surgical treatment of some shoulder disorders. The perspective of this book involves highlighting management of complex shoulder conditions in better ways. This book is divided into four main sections: 'Repair' involves chapters related to primary repair; 'Replacement' section provides detailed perspective on shoulder replacement procedures for different conditions; 'Reconstruction' includes a chapter on reconstructive procedures where primary repair is not possible; and lastly 'Rehab and Miscellaneous' section includes chapters on surgical management of rheumatoid arthritis and rehab. Individual chapters provide a base for a wide range of readers including students, professors, physiotherapists and orthopaedic surgeons, who will find in this book simply explained basics as well as advanced techniques of shoulder surgeries. The book consists of ten chapeters, compiled by experts from institutes across the globe.",isbn:"978-1-78923-017-8",printIsbn:"978-1-78923-016-1",pdfIsbn:"978-1-83881-269-0",doi:"10.5772/66683",price:119,priceEur:129,priceUsd:155,slug:"advances-in-shoulder-surgery",numberOfPages:244,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"fd8f22eb088d93f5043ab53516e494f7",bookSignature:"Satish B. Sonar",publishedDate:"May 2nd 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6011.jpg",numberOfDownloads:10540,numberOfWosCitations:1,numberOfCrossrefCitations:0,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:0,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:1,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"December 8th 2016",dateEndSecondStepPublish:"December 22nd 2016",dateEndThirdStepPublish:"September 17th 2017",dateEndFourthStepPublish:"October 17th 2017",dateEndFifthStepPublish:"December 17th 2017",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"173251",title:"Dr.",name:"Satish",middleName:null,surname:"Sonar",slug:"satish-sonar",fullName:"Satish Sonar",profilePictureURL:"https://mts.intechopen.com/storage/users/173251/images/system/173251.png",biography:"Dr. Satish B. Sonar, MS in Orthopaedics, practises sports medicine and shoulder surgery in Nagpur, India. He is an associate professor in the Department of Orthopaedics at the Dr. PDM Medical College, Amravati, Maharashtra, India. Dr. Sonar is an executive committee member of the Shoulder and Elbow Society of India and serves as a team physician for various local, collegiate and professional sports teams. Dr. Satish B. Sonar is the secretary of Nagpur Arthroscopy Society, and every year he organizes ‘Nagpur Arthroscopy Meet’, a 2-day conference covering recent advances in arthroscopy and sports medicine with lectures, debates, discussions, video demonstrations and live surgeries. He is the founder and director of ‘Sports Med Joint Care Centre’ in Nagpur, exclusively managing sports injuries, shoulder surgeries and arthroscopy. Dr. Sonar has participated in many national conferences and courses over the years. He has many presentations and publications to his name.",institutionString:"Mumbai University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Mumbai",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1150",title:"Orthopedics",slug:"orthopedics"}],chapters:[{id:"60043",title:"Introductory Chapter: Shoulder Joint",doi:"10.5772/intechopen.76187",slug:"introductory-chapter-shoulder-joint",totalDownloads:1031,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Satish B. Sonar and Omkar P. Kulkarni",downloadPdfUrl:"/chapter/pdf-download/60043",previewPdfUrl:"/chapter/pdf-preview/60043",authors:[{id:"173251",title:"Dr.",name:"Satish",surname:"Sonar",slug:"satish-sonar",fullName:"Satish Sonar"}],corrections:null},{id:"56618",title:"Complete Rotator Cuff Tear: An Evidence-Based Conservative Management Approach",doi:"10.5772/intechopen.70270",slug:"complete-rotator-cuff-tear-an-evidence-based-conservative-management-approach",totalDownloads:1235,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"Rotator cuff disease accounts for 10% of all shoulder pain and major shoulder disability, with limited information concerning the natural history and treatment approaches for the disorder. Our objective is to assess the available evidence for the efficacy and morbidity of commonly used systemic medications, physiotherapy, and injections alongside evaluating any negative long-term effects. Although there is conflicting literature, there appears to be some consensus on the best indicators for choosing to treat a full-thickness tears (FTT) non-operatively to reduce pain and improve function. The risks associated with these tears include the potential of the progression of the tear, a diminished healing potential due to age or longer symptom duration, muscle atrophy, and fatty infiltration. The indications for surgery following conservative treatment are becoming more defined, and an outline regarding what scenarios warrant a transition from an initial conservative treatment plan has been developed. The developing benefits of using mesenchymal stem cells (MSCs) and other biologics have the potential to be disruptive to current treatment protocols in the approaches to healing rotator cuff tears (RCTs). With improved imaging modalities, diagnostic accuracy, and sensitivity, practitioners of the future will hopefully be able to intervene earlier in the disease pathogenesis cycle.",signatures:"Taiceer A. Abdulwahab, William D. Murrell, Frank Z. Jenio, Navneet\nBhangra, Gerard A. Malanga, Michael Stafford, Nitin B. Jain and\nOlivier Verborgt",downloadPdfUrl:"/chapter/pdf-download/56618",previewPdfUrl:"/chapter/pdf-preview/56618",authors:[{id:"204153",title:"Dr.",name:"Taiceer",surname:"Abdulwahab",slug:"taiceer-abdulwahab",fullName:"Taiceer Abdulwahab"},{id:"211079",title:"Dr.",name:"William",surname:"Murrell",slug:"william-murrell",fullName:"William Murrell"},{id:"211080",title:"Mr.",name:"Frank Z.",surname:"Jenio",slug:"frank-z.-jenio",fullName:"Frank Z. Jenio"},{id:"211081",title:"BSc.",name:"Navneet",surname:"Bhangra",slug:"navneet-bhangra",fullName:"Navneet Bhangra"},{id:"211082",title:"Prof.",name:"Gerard",surname:"Malanga",slug:"gerard-malanga",fullName:"Gerard Malanga"},{id:"211083",title:"Prof.",name:"Nitin",surname:"Jain",slug:"nitin-jain",fullName:"Nitin Jain"},{id:"211084",title:"Dr.",name:"Olivier",surname:"Verborgt",slug:"olivier-verborgt",fullName:"Olivier Verborgt"},{id:"211203",title:"Mr.",name:"Michael",surname:"Stafford",slug:"michael-stafford",fullName:"Michael Stafford"}],corrections:null},{id:"59690",title:"Subscapularis Repair",doi:"10.5772/intechopen.74734",slug:"subscapularis-repair",totalDownloads:964,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Subscapularis is largest muscle of the rotator cuff. It is important component of shoulder joint for necessary of unimpaired shoulder movements. Since past decade subscapularis tears are recognized as source of pain and dysfunction of shoulder joint. New diagnostic techniques and arthroscopic repair surgeries help to treat subscapularis tears. This article provides an overview of types of tear, diagnostic methods and treatment options.",signatures:"Omkar P. Kulkarni and Satish B. Sonar",downloadPdfUrl:"/chapter/pdf-download/59690",previewPdfUrl:"/chapter/pdf-preview/59690",authors:[{id:"173251",title:"Dr.",name:"Satish",surname:"Sonar",slug:"satish-sonar",fullName:"Satish Sonar"}],corrections:null},{id:"56682",title:"Surgical Approaches in Shoulder Arthroplasty",doi:"10.5772/intechopen.70363",slug:"surgical-approaches-in-shoulder-arthroplasty",totalDownloads:1066,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Shoulder arthroplasty is a complex procedure that is becoming increasingly more utilized throughout the world. Due to the numerous static and dynamic stabilizers of the glenohumeral joint, along with the relative proximity to vital neurovascular structures, great care must be taken to access the joint in a safe and effective manner. To date, there are two well-described approaches utilized in shoulder arthroplasty: the deltopectoral approach and the anterosuperior approach. Both of these approaches are effective in accessing the glenohumeral joint; however, due to their anatomic location, they both have distinct advantages and disadvantages. The aim of this book chapter is to describe the methodology for approaching the glenohumeral joint through each of these approaches, as well as to discuss the advantages and disadvantages of utilizing each. In addition, we aim to discuss the various methodologies for closing these wounds and, briefly, to discuss the other approaches described in the orthopedic literature.",signatures:"Brian W. Sager and Michael Khazzam",downloadPdfUrl:"/chapter/pdf-download/56682",previewPdfUrl:"/chapter/pdf-preview/56682",authors:[{id:"203792",title:"Dr.",name:"Michael",surname:"Khazzam",slug:"michael-khazzam",fullName:"Michael Khazzam"},{id:"203836",title:"Dr.",name:"Brian",surname:"Sager",slug:"brian-sager",fullName:"Brian Sager"}],corrections:null},{id:"58204",title:"Current Outcomes Following Reverse Total Shoulder Arthroplasty: A Composite",doi:"10.5772/intechopen.72545",slug:"current-outcomes-following-reverse-total-shoulder-arthroplasty-a-composite",totalDownloads:1192,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Reverse Total Shoulder Arthroplasty (RTSA) is a popular treatment for patients with rotator cuff damage, glenohumeral arthritis, complex fractures, and previously failed total shoulder arthroplasty given its ability to alleviate pain and increase range of motion and function. Although RTSA significantly improves functionality, pain, and satisfaction, patients need to be given realistic expectations for when to expect improvements, peak performance, and plateaus as well as potential risks for negative outcomes. As with any surgical procedure, patients are at risk for intraoperative, perioperative, short-term, and long-term complications. Thus, the purpose of this review is to discuss the short-term and long-term complications, metrics, and length of follow-up for patients who have undergone RTSA. In addition, we provide recommendations for a cut-off point between short-term and long-term outcomes for RTSA.",signatures:"Sydney C. Cryder, Samuel E. Perry and Elizabeth A. Beverly",downloadPdfUrl:"/chapter/pdf-download/58204",previewPdfUrl:"/chapter/pdf-preview/58204",authors:[{id:"220198",title:"Mrs.",name:"Sydney",surname:"Cryder",slug:"sydney-cryder",fullName:"Sydney Cryder"},{id:"223845",title:"Dr.",name:"Samuel",surname:"Perry",slug:"samuel-perry",fullName:"Samuel Perry"},{id:"223846",title:"Dr.",name:"Elizabeth",surname:"Beverly",slug:"elizabeth-beverly",fullName:"Elizabeth Beverly"}],corrections:null},{id:"57220",title:"Options Before Reverse Total Shoulder Replacement",doi:"10.5772/intechopen.70795",slug:"options-before-reverse-total-shoulder-replacement",totalDownloads:1105,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Management of massive tears of the rotator cuff tears is one of the most difficult problems an upper limb surgeon encounters. Patients with similar tears can present with minimal discomfort through to a flail shoulder. There are a bewildering number of options available, many with published outcomes not always borne out in clinical practise. These range from rehabilitation, simple arthroscopic surgery, attempts at repair, complex tendon transfers and ultimately a reverse total shoulder replacement. More recently further options of patch augmentation and balloon arthroplasty have been added. This paper attempts to provide a critical assessment of the evidence available.",signatures:"Roger Hackney, Piotr Lesniewski and Paul Cowling",downloadPdfUrl:"/chapter/pdf-download/57220",previewPdfUrl:"/chapter/pdf-preview/57220",authors:[{id:"204122",title:"Mr.",name:"Roger",surname:"Hackney",slug:"roger-hackney",fullName:"Roger Hackney"},{id:"212188",title:"Dr.",name:"Piotr",surname:"Lesniewski",slug:"piotr-lesniewski",fullName:"Piotr Lesniewski"},{id:"212189",title:"Mr.",name:"Paul",surname:"Cowling",slug:"paul-cowling",fullName:"Paul Cowling"}],corrections:null},{id:"56431",title:"Superior Capsule Reconstruction: Review of a Novel Operative Technique for Management of Irreparable Rotator Cuff Tears",doi:"10.5772/intechopen.70049",slug:"superior-capsule-reconstruction-review-of-a-novel-operative-technique-for-management-of-irreparable-",totalDownloads:1027,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Rotator cuff tear is a common yet functionally debilitating shoulder condition. Risk factors for failure of repair or inability to repair include advancing age of the patient, chronicity of the tear, and larger tear size. Current operative management options for tears that are considered irreparable include debridement, partial repair, biceps tenotomy, interpositional grafting, tendon transfers, and reverse shoulder arthroplasty. Recently, superior capsular reconstruction has been introduced as an alternative surgical option for these tears and has demonstrated favorable short-term outcomes. However, the literature lacks studies with large numbers of patients, consistency of results, and long-term outcomes. This article reviews the anatomy and function of the rotator cuff and shoulder capsule; patho-etiology of rotator cuff tears, particularly the irreparable ones; and rationale, techniques, outcomes, and future direction of superior capsular reconstruction in the context of this clinical indication.",signatures:"Alexander Golant, Daiji Kano, Tony Quach, Kevin Jiang and Jeffrey\nE. Rosen",downloadPdfUrl:"/chapter/pdf-download/56431",previewPdfUrl:"/chapter/pdf-preview/56431",authors:[{id:"157699",title:"Dr.",name:"Alexander",surname:"Golant",slug:"alexander-golant",fullName:"Alexander Golant"},{id:"202398",title:"Dr.",name:"Tony",surname:"Quach",slug:"tony-quach",fullName:"Tony Quach"},{id:"202399",title:"Dr.",name:"Jeffrey",surname:"Rosen",slug:"jeffrey-rosen",fullName:"Jeffrey Rosen"},{id:"202400",title:"Dr.",name:"Kevin",surname:"Jiang",slug:"kevin-jiang",fullName:"Kevin Jiang"},{id:"202401",title:"Dr.",name:"Daiji",surname:"Kano",slug:"daiji-kano",fullName:"Daiji Kano"}],corrections:null},{id:"56245",title:"Integral Management in Painful Shoulder Treatment: Anesthesiologist’s Point of View",doi:"10.5772/intechopen.69914",slug:"integral-management-in-painful-shoulder-treatment-anesthesiologist-s-point-of-view",totalDownloads:858,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Shoulder pain is a common complaint in clinical practice. The usual form of treatment is based on nonsteroidal anti-inflammatory drugs (NSAIDs), rest, rehabilitation and, as an alternative, a local injection into the joint. Due to the lack of oral medication and the lack of evidence, it is necessary to use different nonsurgical therapeutic alternatives. Pulsed radiofrequency produces a temporary nondestructive blockage being the most common technique in the management of shoulder pain. The application of pulsed radiofrequency on the suprascapular nerve has proven to be an effective method in the treatment of shoulder pain, with a decrease in pain that allows the rehabilitation of patients. The axillary or circumflex nerve provides motor innervation mainly to deltoids with branches to the teres minor, provides sensitive innervation to the lower, lateral, and anterior articular capsule, and innervates the humeral head and upper humeral neck. It has a cutaneous branch, which contributes sensitivity of the skin on the deltoids. Combined pulsed radiofrequency on the suprascapular nerve and on the circumflex nerve has been scarcely studied with very few references in the literature. The joint treatment by pulsed radiofrequency technique on suprascapular nerve and circumflex nerve can provide a complete and lasting relief of this pathology.",signatures:"José Miguel Esparza Miñana",downloadPdfUrl:"/chapter/pdf-download/56245",previewPdfUrl:"/chapter/pdf-preview/56245",authors:[{id:"203612",title:"Dr.",name:"Jose-Miguel",surname:"Esparza-Miñana",slug:"jose-miguel-esparza-minana",fullName:"Jose-Miguel Esparza-Miñana"}],corrections:null},{id:"57602",title:"The Rheumatoid Shoulder: Current Surgical Treatments",doi:"10.5772/intechopen.71452",slug:"the-rheumatoid-shoulder-current-surgical-treatments",totalDownloads:1007,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Background: Rheumatoid arthritis (RA) is an inflammatory disease resulting in pain and decreased functional outcome. Even though most of large joints are widely discussed in literature, shoulder’s surgical treatment options, indications and superiorities to each other were not compared entirely.",signatures:"Nuri Aydin, Lercan Aslan, Janne Lehtinen and Vedat Hamuryudan",downloadPdfUrl:"/chapter/pdf-download/57602",previewPdfUrl:"/chapter/pdf-preview/57602",authors:[{id:"218615",title:"Prof.",name:"Nuri",surname:"Aydin",slug:"nuri-aydin",fullName:"Nuri Aydin"},{id:"218616",title:"Dr.",name:"Lercan",surname:"Aslan",slug:"lercan-aslan",fullName:"Lercan Aslan"},{id:"218618",title:"Prof.",name:"Vedat",surname:"Hamuryudan",slug:"vedat-hamuryudan",fullName:"Vedat Hamuryudan"},{id:"221423",title:"Prof.",name:"Janne",surname:"Lehtinen",slug:"janne-lehtinen",fullName:"Janne Lehtinen"}],corrections:null},{id:"56650",title:"The Role of Physical Medicine and Rehabilitation in Shoulder Disorders",doi:"10.5772/intechopen.70344",slug:"the-role-of-physical-medicine-and-rehabilitation-in-shoulder-disorders",totalDownloads:1063,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Shoulder pain is a common problem and it is responsible for a high proportion of patients presenting to general practice, causing work absenteeism and claims for sickness. A lot of factors and conditions can contribute to shoulder pain. The most prevalent cause is rotator cuff tendinitis; its relevance is correlated not only to its high prevalence rate but also to the fact that is disabling, causing high direct and indirect cost in industrialized country. Other causes of shoulder pain are shoulder impingement syndrome, calcific tendonitis, frozen shoulder, etc. In this context, physical medicine and rehabilitation plays a fundamental role. The conservative approach consists of several interventions. The aim is to decrease shoulder pain and to regain shoulder function, with the goal to reduce the degree of impingement, decreasing swelling and inflammation, and to minimize the risk of further injuries. The purpose of this chapter is to give an overview about shoulder disorders and their conservative treatment by means of physical therapy.",signatures:"Raoul Saggini, Simona Maria Carmignano, Lucia Cosenza, Tommaso\nPalermo and Rosa Grazia Bellomo",downloadPdfUrl:"/chapter/pdf-download/56650",previewPdfUrl:"/chapter/pdf-preview/56650",authors:[{id:"60231",title:"Prof.",name:"Raoul",surname:"Saggini",slug:"raoul-saggini",fullName:"Raoul Saggini"},{id:"174446",title:"Prof.",name:"Rosa Grazia",surname:"Bellomo",slug:"rosa-grazia-bellomo",fullName:"Rosa Grazia Bellomo"},{id:"206445",title:"Dr.",name:"Simona Maria",surname:"Carmignano",slug:"simona-maria-carmignano",fullName:"Simona Maria Carmignano"},{id:"206446",title:"Dr.",name:"Tommaso",surname:"Palermo",slug:"tommaso-palermo",fullName:"Tommaso Palermo"},{id:"211116",title:"Dr.",name:"Lucia",surname:"Cosenza",slug:"lucia-cosenza",fullName:"Lucia Cosenza"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"938",title:"Recent Advances in Arthroplasty",subtitle:null,isOpenForSubmission:!1,hash:"617e868a5450ec0c9d233121177ca61e",slug:"recent-advances-in-arthroplasty",bookSignature:"Samo K. 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",isbn:"978-1-80355-883-7",printIsbn:"978-1-80355-882-0",pdfIsbn:"978-1-80355-884-4",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"093f9e26bb829b8d414d13626aea1086",bookSignature:"Dr. Hassan Ibrahim",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11124.jpg",keywords:"Next-Generation Textile, Intelligent Textile, Smart Textile, Technical Textile, Next-Generation Material, Medical Textile, Sustainable Textile, Nanofiber, Fabric, Smart Material, Biodegradable Fiber, Technological Innovation",numberOfDownloads:27,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 5th 2021",dateEndSecondStepPublish:"February 24th 2022",dateEndThirdStepPublish:"April 25th 2022",dateEndFourthStepPublish:"July 14th 2022",dateEndFifthStepPublish:"September 12th 2022",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Hassan Ibrahim was the Egyptian National Representative of the Chemistry and Human Health Division Committee (VII) at the International Union of Pure and Applied Chemistry (IUPAC) in 2018-2019 and is currently a member of several national committees of pure and applied chemistry. 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He supervised 8 PhD and M.Sc. thesis, and participated in 14 national and international projects dealing with organic and environmental chemistry, hazardous wastes, medical textiles, nanotechnology, and electrospun nanofibers formation. He has expertise in applied chemistry and technology of organic chemistry, especially in carbohydrates, polymers, pollution prevention, preparation, and applications of nanoparticles (polymer chemistry, chemistry of chitosan, chitosan modification, nanoparticles preparation, and electrospinning technique). He built this model after years of research and teaching at university and research centers. He was the Egyptian National Representative of the Chemistry and Human Health Division Committee (VII) at the International Union of Pure and Applied Chemistry (IUPAC) in 2018-2019, and is currently a member of several national committees of pure and applied chemistry. 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This could be attributed to the free online spatial dataset (elevation, soil, land cover) necessary for setting up SWAT. However, the ease of setting up SWAT using the available information does not mean that the model will give behavioral results. The calibration of hydrological models for water resources assessments is often difficult due to the large numbers of model parameters, and the difficulty increases with the model complexity. Similarly, calibration and uncertainty analysis are a pre-requisite of any hydrological modeling study. Despite, the claimed wide use of SWAT in Tanzania, the whole issue of uncertainty has been ignored, where the uncertainty framework within SWAT is used for the optimization of objective functions only [1]. In this study, SWAT2009 was used to explore the implementation of the uncertainty analysis framework for the meaningful application of the results.
\nSUFI 2 framework is used for the implementation of uncertainty analysis in this study. The framework was selected because it takes fewer runs in comparison to other calibration procedures tailored for SWAT. According to [2, 3, 4, 5] SUFI-2 parameter uncertainty accounts for all sources of uncertainties such as uncertainty in input data, model structure, and parameters. All uncertainties are quantified by a measure referred to as the P-factor, which is the percentage of measured data bracketed by the 95% prediction uncertainty (95PPU) and R-factor which is the measure of the width of the uncertainty band.
\nThe concept behind the uncertainty analysis of the SUFI-2 algorithm is illustrated graphically in Figure 1. The diagram illustrates that a single parameter value (black dot) leads to a single model response (Figure 1a), while the propagation of the uncertainty in a parameter (shown by a line) leads to the 95PPU illustrated by the shaded region in Figure 1b. As parameter uncertainty increases, the output uncertainty also increases (Figure 1c). SUFI-2 normally begin with a large parameter uncertainty (within a physically meaningful range) to make sure that the observed data falls within the 95PPU, then decreases this uncertainty in steps while monitoring the P-factor and the R-factor. If the initial parameter ranges are equal to the maximum physically meaningful ranges and still cannot find a 95PPU that brackets any or most of the data (Figure 1d), then the conceptual model needs to be re-examined [4]. In each step, initial parameter ranges are updated by calculating the sensitivity matrix, an equivalent of a Hessian matrix, followed by the calculation of the covariance matrix, 95% confidence intervals of the parameters, and correlation matrix. Parameters are then updated in such a way that the new ranges are smaller than the previous ranges and are centered on the best simulation. More details on SUFI-2 and its algorithm can be found in Abbaspour et al. [3, 4]. The uncertainty analysis in this study was implemented in the two stages;
Assigning initial parameter ranges: the complete physical range of each parameter was used to explore the surface response using Latin Hypercube sampling and to select the initial range for each parameter.
Derivation of a reduced parameter range and predictive uncertainty: the procedure identifies a range for each parameter in such a way that upon propagation:
A conceptual illustration of the relationship between parameter uncertainty and prediction uncertainty.
The model performance was assessed based on the two conditions being fulfilled and a good agreement between the simulated and the observed data for a calibration and validation period. In theory, the P factor values range between 0 and 100%, while the R-factor ranges between 0 and infinity [4]. A P-factor of 1 and R-factor of zero is a simulation that exactly corresponds to measured data. The degree of departure from these numbers is used to judge the strength of calibration. It is possible to achieve a good P-factor at the expense of a larger R-factor; therefore, there should be a balance between the two factors [4]. Other performance measures used are the R2 and Nash-Sutcliffe (CE) coefficient.
\nThe Little Ruaha basin (Figure 2) falls within the African land surface where the infiltration of the topsoil is good, and interflow is an important component of the River discharge. The soils in the upper part are deeply weathered and have a good soil structure. The total area for this sub-catchment is approximately 5200 km2. The headwaters of the Little Ruaha River (gauging station 1 ka31) originate from a permanent swamp covering an area of approximately 30–50 km2. The seasonal variation of the runoff is less apparent for the Little Ruaha River, due to a considerable infiltration and ground water recharge during the wet season which is favored by relatively high and often less intensive rainfall [6]. The maximum and minimum recorded flows of the River are 775.0 and 2.8 m3 s−1 during March and October, respectively. Estimates of groundwater recharge are discussed in the Water Master Plan for Iringa, Ruvuma, and Mbeya regions [7]. Based on the CCKK report, the base flow component constituted about 80% of the total annual stream flow, which is consistent with the fact that the catchment is characterized by swamps in the headwaters but also, has highly permeable soils. This implies that there is high recharge.
\nThe Great Ruaha River Basin with Little Ruaha River sub-basin (presented in green).
The geology of the Little Ruaha basin is mainly covered by the Usagarans System. The system covers the Great Ruaha and Kilombero catchments, in Great Ruaha, the system mostly covers Iringa region where Little Ruaha flows. These are rocks extending N-NE and S-SW of the Archean Tanzania Craton. The rocks formed between (2.1–1.8) Ga striking W-E to SW. Geologists have used different abbreviations for ages (time before present) and duration (amount of time elapsing between two different events). Ages are abbreviated from Latin: Ga (giga-annum) is a billion years, Ma (mega-annum) is a million years, ka (kilo-annum) is a thousand years. Major rock types in the system are crystalline limestone, graphite schists, and gneiss metamorphosed under amphibolites facies condition due to granitization and migmatization which took place during Pan African tectonothermal event 0.5 Ga which affected the Mozambique mobile belt. The system also contains granulites and granitic intrusions (1.8–1.85) in some parts of Iringa region, volcanic rhyolite lavas, granite gneiss, eclogite, and agglomerates are found in some areas of Kilombero in the Udzungwa Mountains and the Kilombero basins. The volcanic behavior in lower Kilombero is witnessed with high-temperature ground water recorded at monitoring borehole located at Ikule primary school in Ifakara and the volcanic soil. The rock types in the Usagaran system are dominant in Iringa, Mufindi, Njombe, Kilolo, Kilosa and Kilombero districts, which are in Great Ruaha and Kilombero catchments. The rocks are found in a part of Makete district though other parts are affected and dominated by Rungwe volcanic (anorthosites, basalts, peridotites, pyroxenites).
\nThe soils in the upper parts are deeply weathered and have good soil structure, but the relatively high rainfall has resulted in heavily leached soils with low fertility. The soils in the lower part Agro-ecological zone 8 are moderately fertile red clays and loams although sandy soils with low fertility are quite common.
\nThe basin is characterized by flat to undulating topography and inselbergs are common. While humid forest remnant covers the upper part of the zone, Acacia scrubland is more typical in the lower drier areas. The characteristic features of the basin, apart from the Rift Valley system, are the surrounding uplifted and warped plateaus. Covering nearly 90% of the total Iringa and Mbeya regions, the plateaus represent by far the most common land form. Fault-lines and erosion scarps separate them and are the result of steady erosion that has taken place since the Late Jurassic period.
\nRainfall is highest in the south–eastern part of the basin about 1200–1400 mm in the steep upper catchments areas, decreasing with altitude to 800–1000 mm in the middle part of the catchment which has undulating topography, whereas the lower parts of the catchments south-west of Iringa only receive about 700 mm. The rainfall is unimodal. Rain normally starts in November/December and ends in April/May. In the upper catchment areas rainy season often continues into the beginning of June for example in 1994 the rainy season finished in Iringa by mid-April whereas it was still raining in the upper part of the basin until the beginning of June.
\nMost of the population in this catchment depends on agricultural production, and the farming systems which evolved in this zone are predominantly smallholder with the average cultivated area varying from 1 to 2 ha per household. Large-scale farming is limited a few numbers of individuals and companies (often parastatals). Maize is the dominant crop in most of the smallholder farming systems. Maize is grown in mixtures most often beans but intercropping with sunflower and cowpeas are also common. Peas are very important crop and are often grown at the beginning of the dry season and are most often grown on broad ridges. Sorghum and millet are also grown, but the production is very minor compared to maize even in the drier areas where, the more drought resistant sorghum would be more appropriate than maize which is much more water demanding. In the area potatoes are an important crop where transport facilities are good they are often grown as a cash crop. The area under cultivation varies considerably within the zone approximately 25–75% with the highest land use pressure in the area around Iringa, where there has been severe overutilization of the land resources which has led to severe erosion.
\nThe gauging station 1 ka31 (Little Ruaha at Mawande) was used for SWAT2009 model calibration for the period 1971–1979. Daily stream flow data from this station were checked for quality, and this involved the identification of errors from suspicious extreme values. Figure 3 illustrates the percentage of available data points, missing data points, and removed data points. Six percent (6%) of the data was deleted from the time series, and 2% of the data was missing. Therefore only 92% of the record was used for the calibration method. Both manual and automatic calibration approaches were used for this study. The pre-calibration parameter sensitivity analysis was performed to identify parameters that are expected to have a strong influence on the model simulation results.
\nSummary of the screened daily stream flow data used in this study.
In this study, the Sequential uncertainty fitting (SUFI-2) approach was combined with SWAT to quantify parameter uncertainty of the stream flow simulations for the Little Ruaha River (5195 km2). The SWAT2009 model was setup for the whole GRR basin but the analysis presented here is based on one major tributary only. The hydrological response units (HRU) were characterized using the dominant land use, soil, and slope to keep the complexity of the analysis to a practical limit for the uncertainty propagation. Daily stream flow data from this station were checked for quality, and this involved the identification of errors from unexplained extreme value.
\nSensitivity analysis allows for the identification of model parameters that exert a strong influence on the model output, thus largely controlling the behavior of the simulation process. In this study, a sensitivity analysis was carried out using the Latin Hypercube One-factor At a Time (LH-OAT) algorithm [8, 14]. The Sensitivity analysis minimizes the number of parameters to be used in the calibration step. The Latin Hypercube simulation is based on a Monte Carlo approach with stratified sampling. The results of the sensitivity analysis are parameters arranged in ranks, where the parameter with a maximum effect obtains rank 1, and parameter with a minimum effect obtains the rank which corresponds to the number of all analyzed parameters. The parameter that has a global rank 1 is categorized as “very important,” rank 2–7 as “important,” rank 8–27 “slightly important” and rank 28 as “not important” [14].
\nThe sensitivity analysis in this study was done using (i) automatic global sensitivity analysis in SUFI-2, (ii) manual analysis of the sensitive parameters based on the output of the global sensitivity analysis. The global sensitivity analysis in SUFI-2 is not able to analyze all the parameters in SWAT; it analyses the sensitivity of the pre-defined 27 parameters (Table 1). In this approach, parameter sensitivity is determined using the multiple regression equations, which regresses the Latin Hypercube generated parameters against objective function values. The
Sensitivity analysis
Manual calibration
SUFI-2 set up (automatic calibration)
Assigning initial parameter ranges
Latin Hypercube sampling is used to sample the parameter distributions
Model simulations are performed, and objective functions are calculated for each of the n (n = 2000 for this study) simulations.
Parameter | \nDescription | \nRank | \nProcess | \n||
---|---|---|---|---|---|
ALPHA_BF | \nBase flow alpha factor for recession constant (days) | \n−34.23 | \n0.00 | \n1 | \nGround water | \n
CN2 | \nSCS runoff curve number for moisture condition II | \n−12.90 | \n0.00 | \n2 | \nRunoff | \n
SURLAG | \nSurface runoff lag time (days) | \n−1.54 | \n0.12 | \n3 | \nRunoff | \n
REVAPMN | \nThreshold water depth in the shallow aquifer for revap (mm) | \n−1.51 | \n0.13 | \n4 | \nGroundwater | \n
SOL_K(2) | \nSaturated hydraulic conductivity soil layer 2 (mm h−1) | \n−1.39 | \n0.16 | \n5 | \nSoil | \n
GWQMN | \nThreshold water depth in the shallow aquifer for flow (mm) | \n−1.28 | \n0.19 | \n6 | \nGroundwater | \n
SLSUBBSN | \nAverage slope length (mm−1) | \n1.17 | \n0.19 | \n7 | \nTopography | \n
BLAI | \nLeaf area index for crop | \n1.05 | \n0.29 | \n8 | \nCrop | \n
CANMX | \nMaximum canopy storage (mm) | \n0.60 | \n0.54 | \n9 | \nRunoff | \n
CH_N2 | \nManning’s “n” value for the main channel | \n0.58 | \n0.55 | \n10 | \nChannel | \n
HRU_SLP | \nAverage slope steepness of the HRU | \n−0.56 | \n0.57 | \n11 | \nTopography | \n
GW_REVAP | \nGroundwater “revap” coefficient | \n−0.46 | \n0.63 | \n12 | \nGroundwater | \n
BIOMIX | \nBiological mixing efficiency | \n−0.39 | \n0.69 | \n13 | \nSoil | \n
EPCO | \nPlant evaporation compensation factor | \n0.24 | \n0.80 | \n14 | \nEvaporation | \n
SOL_AWC | \nAvailable soil water capacity (mm H2O/mm soil) | \n0.21 | \n0.82 | \n15 | \nSoil | \n
RCHRG_DP | \nDeep aquifer percolation fraction | \n−0.21 | \n0.83 | \n16 | \nGroundwater | \n
ESCO | \nSoil evaporation compensation factor | \n−0.10 | \n0.91 | \n17 | \nEvapotranspiration | \n
GW_DELAY | \nMovement of water from shallow aquifer to the root zone | \n0.09 | \n0.92 | \n18 | \nGroundwater | \n
CH_K2 | \nChannel effective hydraulic conductivity (mm h−1) | \n0.07 | \n0.94 | \n19 | \nChannel | \n
Parameter sensitivity ranking and category of the most sensitive parameters.
The results of the sensitivity analysis indicated the sensitive parameters and helped in guiding the setup of the initial parameter ranges. It was important to consider the physical meaning of each parameter and its effects on the sub-basin behavior. Therefore, the initial parameter sets were guided by the understanding of the physical basin characteristics and the default upper and lower limits established in SWAT. In SWAT default parameters can be modified for the whole sub-basin (lumped), or in a distributed way for individual sub-basins or hydrological response units. Table 2 shows the initial parameter ranges of the sensitive 20 parameters, where the most sensitive parameters are presented in row 2–10.
\nParameter | \nLower limit | \nUpper limit | \nChange option | \n
---|---|---|---|
v__ALPHA_BF.gw | \n0.00 | \n1.00 | \nReplacement | \n
r__CN2.mgt | \n−50 | \n50 | \nRelative | \n
v__SURLAG.bsn | \n0.00 | \n24.00 | \nReplacement | \n
v__REVAPMN.gw | \n0.11 | \n0.80 | \nReplacement | \n
r__SOL_K (2).sol | \n0.39 | \n4.28 | \nRelative | \n
a__GWQMN.gw | \n1983 | \n2889 | \nAbsolute | \n
r__SLSUBBSN.hru | \n0.13 | \n0.33 | \nRelative | \n
v__BLAI{120}.CROP.DAT | \n3.63 | \n6.95 | \nReplacement | \n
v__CANMX.hru | \n2.87 | \n8.51 | \nReplacement | \n
v__CH_N2.rte | \n0 | \n0.3 | \nReplacement | \n
r__HRU_SLP.hru | \n0 | \n10 | \nRelative | \n
a__GW_REVAP.gw | \n0.02 | \n0.12 | \nAbsolute | \n
r__BIOMIX.mgt | \n0.11 | \n0.69 | \nRelative | \n
v__EPCO.hru | \n0 | \n0.4 | \nReplacement | \n
r__SOL_AWC (2).sol | \n0 | \n0.9 | \nRelative | \n
v__RCHRG_DP.gw | \n0 | \n1 | \nReplacement | \n
v__ESCO.hru | \n0 | \n1 | \nReplacement | \n
a__GW_DELAY.gw | \n0 | \n129 | \nAbsolute | \n
v__CH_K2.rte | \n24.27 | \n94.18 | \nReplacement | \n
r__SOL_K (1).sol | \n0.66 | \n5.55 | \nRelative | \n
Defined upper and lower limits of initial parameter ranges, the extension of the files in which they are located, and the option used for carrying out changes.
The identifiability of parameters was examined visually using scatter plots of model parameter values versus CE. Figure 4 shows scatter plots with the values of each parameter defined versus their corresponding Nash-Sutcliffe efficiency (CE), where the parameter values were obtained from Latin Hypercube sampling of the initial range defined using 2000 simulations. Scatter plots of the parameter values versus objective function were used to examine the identifiability of individual parameters. Based on the scatter plots the identifiable parameters are expected to show a distinct maximum, and lack of a distinct maximum indicates the difficulty in getting the optimal values that give a good model performance, therefore, the parameter becomes poorly identifiable. It is evident that none of the parameters are identifiable. However, it should be noted that in-identifiability of a parameter does not indicate that the model was not sensitive to these parameters. The sensitivity analysis results identify the most sensitive parameters to be considered for calibration but do not consider the interactions between parameters, therefore having the most sensitive parameters does not mean that the parameter will be identifiable. Estimation of an-identifiable parameters is difficult because there may be many combinations of these parameters that would result in similar model performance (equifinality). Many factors might have led to the non-identifiability of parameters in this study. The interactions between parameters may have contributed to the equifinality which might be associated with the simplified representation of the sub-basin (dominant HRU). Interactions between soil parameters (soil depth and available water capacity) and ground water parameters (Groundwater delay) is expected in SWAT. It is hard to explain these interactions since SWAT considers two soil layers (root zone and unsaturated zone) and ground water (conceptual shallow and deep aquifer stores) and there is not enough information regarding sub-surface water processes to will enable a better explanation of the parameter interactions.
\nScatter plots of the calibrated parameters of Little Ruaha River basin (Gauging station 1 ka31) versus Nash-Sutcliffe efficiency, obtained from Latin Hypercube sampling of the large initial range using 2000 simulations.
Latin Hypercube sampling was used to sample parameters within the initial ranges using 2000 ensembles and a uniform distribution. The CE was used to get optimum parameter values and to separate behavioral from non-behavioral parameter sets, where a cutoff limit of CE = 0.45 was used. Table 3 shows the parameter range and optimal value for the best simulation. ALFA_BF is the most sensitive parameter followed by CN.
Parameter name | \nLower limit | \nUpper limit | \nOptimal SUFI-2 | \n
---|---|---|---|
v__ALPHA_BF.gw | \n0.00 | \n1.00 | \n0.25 | \n
r__CN2.mgt | \n−50 | \n50 | \n−1.69 | \n
v__SURLAG.bsn | \n0.00 | \n24.00 | \n3.5 | \n
v__REVAPMN.gw | \n0.11 | \n0.80 | \n0.57 | \n
r__SOL_K (2).sol | \n0.39 | \n4.28 | \n1.36 | \n
a__GWQMN.gw | \n1983 | \n2887.18 | \n2071.38 | \n
r__SLSUBBSN.hru | \n0.13 | \n0.33 | \n0.32 | \n
v__BLAI{120}.CROP.DAT | \n3.63 | \n6.95 | \n4.82 | \n
v__CANMX.hru | \n2.87 | \n8.51 | \n5.95 | \n
v__CH_N2.rte | \n0 | \n0.3 | \n0.06 | \n
r__HRU_SLP.hru | \n0 | \n10 | \n0.75 | \n
a__GW_REVAP.gw | \n0.02 | \n0.12 | \n0.10 | \n
r__BIOMIX.mgt | \n0.11 | \n0.69 | \n0.40 | \n
v__EPCO.hru | \n0 | \n0.4 | \n0.004 | \n
r__SOL_AWC (2).sol | \n0 | \n0.9 | \n1.10 | \n
v__RCHRG_DP.gw | \n0 | \n1 | \n1.94 | \n
v__ESCO.hru | \n0 | \n1 | \n0.02 | \n
a__GW_DELAY.gw | \n0 | \n129 | \n−31.05 | \n
v__CH_K2.rte | \n24.27 | \n94.18 | \n59.94 | \n
r__SOL_K (1).sol | \n0.66 | \n5.55 | \n0.66 | \n
Final parameter ranges calibrated using SUFI-2.
The
Spatial variations in leaf area index within the Little Ruaha basin.
SWAT was calibrated against observed data for gauging station 1 ka31 for the period 1970–1971. Calibration results yielded satisfactory results given the data scarcity. CE and R2 values of 0.54 and 0.62 were achieved for the calibrated period. The P-factor (% of measured data bracketed by 95% prediction uncertainty) was 0.58 and 0.21 for the full range and behavioral simulations, respectively. The R factors for the full range and behavioral parameters were 1.91 and 0.36, respectively. These results confirm quite large uncertainty of the simulated discharge due to the large equifinality in parameters and reliability of input data (precipitation and daily evaporation data). Table 4 shows a summary of model performance for the calibrations and a comparison between all parameter sets (full range) and behavioral parameter sets. In presenting results, the following performance measures were used;
The relative distance between the observed data and the 95PPU (R-factor)
The percentage of observations covered by the 95PPU (P-factor)
Nash-Sutcliffe efficiency (CE)
Coefficient of correlation (R2)
Station | \nSimulations | \nP-factor | \nR-factor | \nCE | \nR2 | \n
---|---|---|---|---|---|
1ka31 | \nFull range | \n0.58 | \n1.91 | \n54% | \n62% | \n
Behavioral | \n0.21 | \n0.36 | \n54% | \n62% | \n
Summary of performance statistics for the best simulation.
Uncertainty analysis was implemented using the SUFI-2 algorithm. Figures 6 and 7 show the results of the daily flow uncertainty analysis carried out in the sub-basin for the full range and behavioral parameter sets respectively. The shaded area represents the 95% predictive uncertainty (95PPU), whereas the blue lines correspond to the observed discharges and the red lines correspond to the simulated flow at the sub-basin outlet. For the full range simulations (Figure 6) it was found that the observations fall within the lower and upper 95% prediction uncertainty in high and moderate flow but with large uncertainty. Figure 6 shows that the 95% prediction uncertainty of behavioral simulations (CE ≥ 45%) does not bracket the observed flow, only 15% of the data were bracketed, indicating that some processes are not well represented in the model. The prediction limits obtained with SUFI-2 are highly dependent on the threshold selected to separate behavioral from non-behavioral parameter sets. It is also important to note that in SUFI-2 parameter uncertainty is presented as a uniform distribution in the final parameter range, while parameter interactions are ignored and contribute to the large equifinality observed in these results.
\nCalibration at 1 ka31-Mawande (95PPU for full range simulations).
Calibration at 1 ka31-Mawande (95PPU for behavioral simulations).
Final calibration parameters for the Little Ruaha Drainage System with a Coefficient of Evaluation (CE) of 0.54 and R2 of 0.62 for the best simulation regardless of the parameter set. The results show reasonable performance in the hydrologic simulations but with large uncertainties. The model performance statistics achieved in this study are like the ones achieved in other studies in Tanzania [10], but one point that should be noted is that, after calibration, parameters should have physical meaning. With the large equifinality in the parameter sets, it was not possible to get identifiable parameter sets, and it is hard to say that behavioral parameters sets are representatives of the basin’s behavior. This observation highlights the challenges associated with implementing SWAT for water resources use in Tanzania and other developing countries.
\nThe SWAT2009 was applied to the Little Ruaha sub-basin. The model was set up using a coarse spatial dataset, interpolated rainfall data, and a single dominant HRU. Sensitivity analysis results showed that ALPHA_BF, CN2, SURLAG, REVAPMN, CH_K2, GWQMN, SLSUBBSN, BLAI, and CANMX are the most sensitive parameters in the basin. The Little Ruaha drainage system falls within the African land surface where the infiltration of the topsoil is good, and interflow is an important part of the total River discharge. The soils in the upper part are deeply weathered and have a good soil structure. This explains the sensitivity of the surface and subsurface parameters. The drainage is dominated by steep topography, and this explains the sensitivity of the mean slope length of the basin. Sensitivity analyses enabled the most sensitive model parameters to be identified for further calibration, but this does not mean that sensitive parameters will also be identifiable. Out of the 27 parameters, 20 were identified as sensitive, but the interactions between these parameters were not considered during the sensitivity analysis.
\nFinal calibration parameters for the Little Ruaha Drainage System are presented in Table 4, with a CE of 0.54 and R2 of 0.62 for the best simulation regardless of the parameter set. This is since the behavioral parameter sets are within the non-behavioral parameter sets. The results show reasonable performance in the hydrologic simulations but with large uncertainties. The model performance statistics achieved in this study are like the ones achieved in other studies in Tanzania [10], but one point that should be noted is that, after calibration, parameters should have physical meaning. With the large equifinality in the parameter sets, it was not possible to get identifiable parameter sets, and it is hard to say that behavioral parameters sets are representatives of the basin’s behavior. Ref. [13] reviewed the use of the SWAT model in the Nile Basin countries, including Tanzania, and found that the model produced satisfactory or good results, but almost all the case studies reviewed gave results based on the wrong process representation. These results were problematic because when different studies in the same or similar sub-basins are compared, they give different results. In peer-reviewed papers [9, 10] some documented parameter values were not realistic, but this information was not reported in those papers [11]. This observation highlights the challenges associated with implementing SWAT for water resources use in Tanzania and other developing countries.
\nEven though the model gave satisfactory results based on the performance measures, a critical analysis of Figures 6 and 7 suggests a different picture. Figure 6 showed that there is good agreement between observed and simulated flow but associated with very large uncertainty in high to moderate flows, and the uncertainty band does not bracket the low flows. Running the model with the behavioral parameter sets shows a reduction in P-factor and R-factor values (Table 4). Figure 7 shows that while the uncertainty band has been reduced, the model is under-simulating both high and low flows, and does not bracket the moderate to low flows. This could be associated with input data uncertainties, or some processes are not well represented in the model. ALPHA_BF was the most sensitive parameter identified through the sensitivity analysis, and apart from a lack of observed ground water information, difficulties of SWAT in simulating ground water flow [12] might have contributed to the negative aspects of these results.
\nThis study assessed model uncertainty using a combined uncertainty approach that assumes all sources of uncertainty have been considered within the model. In such an approach it is hard to separate the sources of uncertainty, and therefore a follow-up analysis of uncertainty should be undertaken by determining how erroneous input data influence model results. Although not assessed within the research questions of this study, the results highlight potential uncertainties in the input rainfall and evaporation data. The use of these data was justified and used in the simulations but could potentially have influenced the overall model performance and uncertainties that cannot be explained.
\nThe uncertainty analysis was carried out using 20 sensitive parameters, which is a large number considering the interactions between them. Therefore, some less sensitive parameters should be fixed and allow only the most sensitive parameters to vary. This will reduce the effect of parameter interactions and hence the none-uniqueness problem. Although this model has been shown to generate reasonable results, it is worthwhile to consider the challenges associated with setting up a distributed model. In this research, large-scale spatial datasets have been used, and a homogenous model was assumed because the spatial data resolution was insufficient to represent large numbers of hydrological response units. However, even when the resolution was sufficient, attribute values for most of the parameters are lacking. Because of difficulties associated with parameter representation across spatial scales, it is better to use a homogenous set up because biases and uncertainty can be added by the modeler when trying to parameterize values within the hydrological response unit at a size larger than its coverage. The overall conclusions from this assessment include;
The SUFI-2 approach has capabilities of identifying behavioral parameter. However, the results are influenced by large equifinality.
The scatter plots of the parameter values against objective functions obtained after simulation provided an initial qualitative overview of the uncertainties involved in the representation of basin’s behavior.
The 95% of the predictive uncertainty (95 PPU) for stream flow computed using SUFI-2 using the Latin Hypercube sampling with 2000 runs, did not bracket all simulations, indicating that some processes are not represented in the model. Hence additional information is needed to improve the results.
It is also important to emphasize that the prediction limits obtained with SUFI-2 are highly dependent on the threshold selected to separate behavioral from non-behavioral parameter sets and that the subjective choice of the threshold value and objective function can lead to additional uncertainty in the simulation results.
Developing an understanding of the hydrological processes that occur in a system is critical for the effective assessment and management of water resources. However, the lack of observational data represents a serious challenge to understanding that is difficult to resolve, especially when there are so many factors that contribute to hydrological variation and change. Scientists and practitioners within the southern African region are attempting to develop the most effective methods for water resources assessment that will contribute to effective water resources management. This study has employed the uncertainty approach for setting up the rainfall-runoff model for the Little Ruaha River basin and the assessment of uncertainties associated with simulations of naturally hydrological responses. The aim was to explore uncertainties in modeling hydrological responses and to establish a behavioral model that can be used for water resources management and future decision making. This approach has addressed a range of key issues in hydrological modeling; these include the uncertainties associated with input data, parameter equifinality and the importance of realistic uncertainty representation using constraints.
\nAlzheimer’s disease (AD) is a chronic and progressive neurodegenerative disorder, with multiple pathophysiological mechanisms. It currently affects more than 5 million individuals in the United States, and this number is growing daily. It is a whole-body disease, manifested by brain and body function changes during its progression. Clinically, people progressing through dementia demonstrate different manifestations of brain and body functions, including psychiatric manifestations, sensory-motor system disabilities, digestion insufficiency, and multiple bodily system involvement. A diverse combination of symptoms reflects the complexity of vascular, biochemical, physiological, and morphological changes in the brain and body during the development and progression of dementia. The amyloid cascade hypothesis has dominated the field of AD for many years. The intensive research concerning amelioration of the protein abnormalities in AD, based on the amyloid hypothesis, does not have practical value yet despite a very controversial, accelerated FDA approval of Aducanumab, an amyloid monoclonal antibody [1]. Conventional therapies—monotherapy or combinations of multiple medications—are not able to stop the progression of the disease and have very limited modifying effects. Our present understanding of the pathogenesis of AD goes far beyond brain dysfunction and pathology. Clinical and epidemiological studies have helped to identify modifiable factors in the onset and treatment of AD. Among these, hemodynamics, muscle health, and nutritional factors have been researched in animal and clinical studies for many years. The hemodynamic factor is related to vasculature, cerebral blood flow (CBF), and structural changes in the brain. A decrease in CBF is well documented during the progression of dementia. Sensory muscle status, changes in gait, balance, and fine dexterous motor skills are all strongly connected to the initiation and progression of dementia [2].
Nutritional deficiencies begin in the early stages of AD with a loss of taste and smell, which interferes with normal digestive processes. This disruption progresses to digestive disorders, malnutrition, and weight loss in advanced stages of dementia [3].
Rehabilitation is an important part of any treatment and has gained attention from the World Health Organization (WHO). In February 2017, there was a meeting hosted by the WHO, “Rehabilitation 2030: A Call for Action.” At the event, WHO issued a call for action towards “concerted and coordinated global action to scale up rehabilitation.” Rehabilitation is very important for people living on the wide spectrum of our world’s economies and should thus be available for all medical conditions that require it, including dementia [4].
The rehabilitation of patients with dementia is an emerging concept aimed at achieving the optimum level of physical and psychological functioning in the progression of aging, neurodegenerative processes, and chronic medical illnesses. The general hypothesis for this combined therapy is based on the suggestion that every modality has a unique influence on brain functions in AD, and a combination of these modalities could have a synergistic effect, significantly slowing the rate of cognitive decline, improving quality of life, and delaying institutionalization. Nutrition and other non-pharmacological interventions, especially physical and cognitive activities, have shown promising results in delaying the onset of dementia and could potentially improve the outcome of dementia treatment. Research related to simultaneous implementation of medication and multiple non-pharmacological interventions is very limited [5, 6].
Studies relating to cognitive rehabilitation, physical exercises, and nutrition alone have shown a positive effect on cognition in animals and humans in time frames ranging from several months to several years [7, 8, 9, 10].
Since 2000, we have developed a working rehabilitation model, utilizing all available resources, most of which are accessible to the average individual in the hopes of delaying the progression of dementia and possibly improving function in certain cognitive and physical domains. The objectives of this rehabilitation model are the activation of brain functions through the alteration of neurotransmitter activities and the increase of muscle activity, sensory input to the brain, CBF, and nutrients and oxygen supply.
To the best of our knowledge, there is no rehabilitation model related to the simultaneous implementation of multiple available modalities (medications, physical and cognitive exercises, nutrition, and sensory stimulations) for AD patients living at home. We hypothesize that the simultaneous implementation of all possible rehabilitation modalities could delay the progression of dementia significantly, when compared to the utilization of a single modality. Here, we present the key elements of this working rehabilitation model for patients living at home.
Our understanding of pathophysiology in dementia has shifted in focus from amyloid accumulation to hemodynamic and energetic metabolism changes in the brain. It is a chronic, progressive disorder that affects the entire body [11]. Amyloid accumulation in the brain is a dynamic process in response to different etiological factors: stress, hypoxia, loss of subcortical nuclei (the nucleus basalis of Meynert, the locus coeruleus, and the raphe nucleous) [12, 13, 14].
The hemodynamic factor is related to the development of hypoxia- and hypoxia-related metabolic and structural changes in the brain. Hypoperfusion affects white matter, subcortical nuclei, and the cortex of the brain in people with dementia. Chronic hypoxia decreases energy production in the brain, affecting protein synthesis pathways, which cause the development of reversible and irreversible morphological changes in the brain structure. During dementia progression, there are cerebral cortex and cortical corpus callosum atrophy, white matter damage, and dysfunction of subcortical nuclei. Alzheimer’s dementia often begins as a disease of small blood vessels that are damaged by oxidation-induced inflammation and dysregulated amyloid metabolism, which may be seen as implications for early detection and therapy [15]. Today, there is an overlap between Alzheimer’s disease and cerebral vascular dementia. Vast evidence from epidemiological, neural, physiological, clinical, and pharmacological studies suggests common pathogenic pathways between these two types of dementia and highlights the vital roles of vascular pathways in dementia development and pathology. The deficiency of cerebral blood flow could be a reason for neuronal dysfunction, white matter damage, and death of brain cells in both types of dementia.
The course of dementia is associated with progressive changes in cardiovascular pathology in the brain, increased numbers of micro and lacunar infarcts, cerebral atrophy, white matter changes, and signs of demyelination [16, 17]. CBF changes have been well documented in normal aging, MCI, and dementia by using different imaging techniques, such as single-photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), positron emission tomography (PET), among others. On an rCBF—SPECT test, people with mild AD showed a significant reduction in rCBF in the left parietal cortex during an episodic memory task [18]. The conversion from MCI to AD, as well as the progression of AD, is associated with CBF changes. The lower the patient’s CBF, the faster and more drastic is their decline of Mini-Mental Status Exam (MMSE) scores [19].
The first notable changes in CBF start in the entorhinal and hippocampal areas of the brain, eventually expanding into the temporal and parietal lobes until finally reaching the frontal lobes [20]. In some places of the brain such as the sensory-motor strip areas and the cerebellum, CBF is relatively well-preserved in dementia [21]. This fact helps our understanding and explanation of the preservation of procedural memory in dementia, which is initiated in sensory-motor areas of the brain [22].
Moreover, judging from the same studies, it is quite possible to suggest that regulation of CBF is preserved as well, at least in the sensory-motor strip and cerebellum in moderate stages of the disease. Another example of preserved CBF in dementia is the report concerning increased CBF in frontal-occipital cortex in mild–moderate AD patients (7 affected people), compared to the control group (8 healthy individuals) during a visual face-matching task [23].
Energetic crises include mitochondrial failure and a decrease in the flow of substrate in brain neurons. A decrease in energy production in the central nervous system is one of the key factors in pathogenesis of dementia, which profoundly changes neuron function.
On the peripheral level, there are well-documented changes in sensory-motor system; decrease in feelings of taste, smell, and number of proprioceptive receptors; changes in mobility of joints and spine; increase in muscle spasticity; and decrease in muscles blood flow. Chronic muscles hypoxia is associated with muscle atrophy and sarcopenia. The decreased number of receptors and their functions result in diminished sensory input to the brain, and compromised CBF and neurotransmitters activities.
Dementia has a progressive course of cognitive decline and physical disability, negatively affecting the quality of life, the capacity to socialize, and the ability to perform everyday activities. From a practical point of view, we developed the 3M’s dementia assessment model™ for dementia evaluation, which includes assessing memory, mood, and movements. It is displayed in Figure 1.
3M’s dementia assessment model™ for dementia.
Dementia can start from any of them, alone or in combination with each other. All factors could be affected at different speeds, and all of them have to be taken into consideration during dementia evaluation [24, 25]. Movements, general slowness, and fine motor skills could start before the development of the cognitive problems in dementia [26].
Each of these modifiable factors could affect disease progression and treatment.
Acute and chronic stresses can affect brain and bodily functions by mobilization of sympathetic nervous system and activation of hypothalamic–pituitary–adrenal (HPA) axis on different stages of stress. Since Hans Selye’s discovery of the general adaptation syndrome, countless publications demonstrate relationships between stressors, stress response, and diseases in animal and clinical studies [27]. Stress affects physiological and biochemical processes in every organ in the body during dementia initiation and progression [28]. Sensitivity to stress events increases with aging and may accelerate cognitive and physical decline in dementia [29]. Acute stress affects attention and memory [30]. Chronic stress could play a role in development and progression of dementia by persistent activation of fundamental surviving pathophysiological, mechanisms [31, 32]. There are links between chronic stress and level of memory loss in MCI and dementia [33]. Stress-related hormones mobilization is manifested in failures of homeostasis, thus leading to various diseases, including dementia [34]. Stress affects physiological and biochemical processes in every organ and system in the body during dementia initiation and progression [28].
They may be bidirectional relationships between stress and dementia. Stress is associated with CBF redistribution, mitochondrial and multiple neural pathways changes, and decreased attention and memory [35]. However, during dementia progression, loss of memory, behavior, and social communications could be stressors and evoke stress response by themselves.
There is related data utilization of different interventions aimed at modulation of stress response; the practical recommendations are in the early stages of research [36]. Effective stress management activities could be helpful for patients with dementia and their caregivers and need to be included in dementia treatment strategy [36, 37].
Depression like dementia is a whole-body disease, affecting brain metabolism, sensory systems, muscle health, and nutrition. Depression could share common pathophysiological mechanisms with dementia, such as hypoperfusion, hypoxia, oxidative stress, and energetic and neurotransmitters failure and stress. Depression is one of the risk factors for developing dementia [24].
Depression could precede dementia and accompany dementia progression. The “vascular depression” hypothesis has been proposed, based on clinical, physiological, and morphological changes in seniors, suffering from persistent depression [38]. Clinical and radiology data and epidemiological studies demonstrate the changes in brain structure in dementia in old-old patients [39]. Treatment of late-life depression with vascular pathology is a challenging task for clinicians.
Apathy and anxiety may be seen in depression and dementia affecting the course of these diseases and associated with detrimental effects on activities of daily living [40, 41, 42, 43].
The fact that cardiovascular pathology occurs in multiple neurodegenerative processes in dementia is well documented. However, it remains necessary to investigate the interconnections and order of occurrence of these two factors [44, 45]. The course of dementia is associated with progressive changes in cardiovascular pathology, increased numbers of microbleeds and lacunar infarcts, cerebral atrophy, white matter changes, and signs of demyelination [17].
Vascular pathology and decrease of CBF contribute to progression of clinical manifestations, improving cognitive and physical functions, and developing morphological changes in dementia. Changes in CBF, cerebral ischemia, and hypoxia negatively affect substrate delivery, necessary for energy production and protein synthesis and essential neuronal activities [46].
In epidemiological studies, nutrition has been under investigation for many years as an important factor contributing to healthy aging and prevention of dementia and multiple chronic diseases.
For the purposes of this discussion, the nutritional aspect in the treatment of dementia can be separated into four components.
The first component is related to the diet. There is currently no consensus regarding a diet geared towards at least partially normalizing brain metabolism in dementia. Along with the well-known Mediterranean diet, calorie-restrictive diets, as well as ketogenic diets, may have a beneficial neuroprotective effect in aging and multiple neurodegenerative diseases [47]. The diet close to that used for cardiovascular pathology and diabetes with some modification geared towards very low carbohydrate products is probably the most suitable diet to be offered for dementia patients.
The second component is a number of vitamins and nutriceuticals, which have been known to affect critical biochemical pathways involved in the pathophysiology of dementia. Among them are vitamins and nutrients that are a part of the normal metabolic processes and become deficient during stress, lack of exercises, hypoxia, and many other clinical conditions. In a controlled study on institutionalized, moderate-to-severe dementia patients taking a vitamin/nutriceutical combination for 9 months demonstrated a significant delay in decline on the Dementia Rating Scale and clock-drawing test, compared to those receiving placebo. The vitamin-nutriceutical combination in this study was designed to support antioxidant activities, energy production, and protein synthesis. This small study supports the notion that even in severe dementia, there is still room for stabilization of disease progression [48]. The specific research data related to different nutritional substances and vitamins is out of scope of this chapter.
General recommendations include products that are rich in antioxidants and include dietary precursors for mitochondria function, protein metabolism, and membrane phosphatide synthesis [6, 49].
The third component is associated with changes in gastrointestinal functions in every part of the GI system. These begin in the early stages of dementia and worsen with disease progression, frequently manifested as nutritional disorders such as anorexia, poor digestion, malnutrition, and weight loss. The loss of taste and smell develops in the early stages of dementia, results in the loss of appetite, and negatively impacts all stages of digestion. Even in the early stages of AD, community-dwelling patients display poor nutritional consumption [50]. Patients with dementia often forget to eat or drink on time. In the advanced stages of dementia, progressive GI malfunctions occur simultaneously with chewing and swallowing problems, dysphagia, and a decreased feeling of thirst, all of which are connected to poor food digestion and absorption, vitamin deficiencies, decreased immunity, loss of muscle mass, increased frequency of infection, poor balance, and falls [3]. Weight loss is associated with severity and mortality in AD and is an indicator of protein, energy, vitamin, and nutrient deficiency [51]. According to these authors, in the middle stage of AD (MMSE—16.6 ± 4.9), significant weight loss is observed in more than 40% of patients living at home.
The presence of malnutrition in dementia could be a result of GI system dysregulation: changes in appetite, weight, and GI motility, and the probable development of exocrine pancreatic insufficiency.
An indicator of pancreatic exocrine insufficiency is the level of fecal elastase-1 in stool, the concentration of which decreases progressively with age. Pancreatic exocrine insufficiency was seen in 21.7% of people over 65 years without gastrointestinal disorders, surgery, or diabetes [52]. Pancreatic exocrine insufficiency is more prominent in patients with insulin-dependent diabetes [53].
The existence of pancreatic insufficiency during the aging process and in diabetes, as well as changes in glucose metabolism in dementia, makes it quite possible that exocrine pancreatic insufficiency plays an important role in the digestive malfunctions in dementia.
The fourth component is the microbiome. Imbalance in gut flora can negatively affect general health. The first connection between intestinal microbiome and longevity was described over a century ago by Elie Metchnikoff [54]. Research about the gut-brain axis demonstrates the strong bidirectional connections between gut–body health. Gut flora participates in production of serotonin, dopamine, and GABA—neurotransmitters, actively affected in many neurodegenerative illnesses and medical diseases as well. Stress, depression, and dementia negatively influence the health of the gut. A practical recommendation about using probiotics, prebiotics, and postbiotics for depression and dementia is on the horizon [55, 56, 57].
Medical illnesses (cardiac problems, diabetes, etc.) are risk factors for dementia development and progression. In recent years, accumulating evidence of research has suggested that cardiovascular pathology, especially irregular pulse, could be associated with dementia progression. In diabetes mellitus (type 2), there are metabolic changes, which affect vasculature and cell functions in every organ in the body. The cognitive and physical decline in dementia became worse with progression of diabetes.
The treatment and stabilization of these medical illnesses and disorders have a positive effect on people with dementia. The same approach could be applied to diseases related to the transport of oxygen to the organs (anemia, pulmonary pathology, and renal problems).
Mental activities have a positive effect on CBF in healthy individuals and have been shown to delay the onset of dementia [58]. Research related to improving CBF in AD patients through the use of cognitive activities is slowly growing. Recently a program of mental exercises for nursing home residents with mild AD showed an improvement in cognitive function after being implemented for 6 months. This program was based on extensive previous research done by the same research team relating to increased CBF during various mental tasks [59].
The connections between physical activities and rCBF are well established and done on healthy seniors, patients with MCI, and animal dementia models [60]. Physical exercise is considered a preventative or disease-modifying intervention, as it has shown a neuroprotective effect in brain aging [61]. Physical activities increase level of BDNF, which is responsible for brain health [62].
The effects of resistance training and aerobic exercises are connected to increased activity of the entire cardiovascular system and CBF simultaneously. These physical activities increase level of BDNF, which actively participate in learning, memory, and mood [63].
Hand exercises are more suitable and safer for fragile medically ill patients with all stages of AD because they can be done in a seated or laying position and appear to be a practical model for a home-based exercise regimen [11].
Simple hand movements have been shown to increase CBF in contralateral hemisphere of healthy subjects [64]. An increase in CBF during meditation, with simultaneous chanting and finger movements (dual tasks), has been observed by SPECT in healthy volunteers [65].
Physical activities have positive effect on neuropsychiatric symptoms in dementia [37].
Physical and mental exercises alone, as well as a combination of the both, could modify CBF and improve cerebral metabolism, decrease hypoxia, increase availability of oxygen and nutrients to brain cells and structures, increase brain vitality and prolong an active life for patients with dementia.
Rehabilitation of AD patients is an emerging concept aimed at achieving optimum levels of physical cognitive and psychological functioning in the presence of neurodegenerative processes, aging, and progression of chronic medical illnesses.
Given the complexity regarding the pathogenesis of AD, we hypothesize that the simultaneous implementation of multiple rehabilitation modalities could delay the progression of dementia. To the best of our knowledge, there is no rehabilitation model designed for the treatment at home for many years. This program starts in the doctor’s office and continues in the home indefinitely.
From a practical point of view, we approach dementia rehabilitation with the 4M’s dementia rehabilitation model™, which includes treating memory, mood, movements, and mitochondria to increase the vitality of neurons and their connections by increasing CBF, as shown in Figure 2.
4M’s dementia rehabilitation model™.
The in-office part of the model includes (a) an assessment of cognitive functions and movements, with special attention paid to preserved areas in cognition and motor system; (b) education about AD, modifiable factors, which needs to be used; (c) teaching patients and caregivers stress reduction techniques, as well as appropriate physical and cognitive exercises, based on patient’s level of dementia; (d) physical and cognitive training during office visits; and (e) monitoring of treatment progress during subsequent office visits.
The home part of the model includes (a) physical exercises, cognitive training, and stress management techniques practiced as per the workbook and videos (which are given to each patient); (b) sensory activation (light, sound, relaxation videos with tranquil nature scenery; and (c) nutrition.
The physical and cognitive aspects of the rehabilitation program have been developed based on the physiological, real-life interplay between physical activity, attention, and procedural memory. Physical activities require attention and help with procedural memory. All of them have a direct effect on CBF [64, 65, 66]. During the progression of AD, all three components deteriorate at different rates over time. However, they are relatively preserved, compared to other cognitive functions until the late stages of AD.
Over the years, preservation of cognitive function has been demonstrated up to 72 months of treatment. Remaining at the same level of cognitive function at the initial visit is a significant treatment achievement [67, 68].
Even though the progression of dementia is going along with development of chronic hypoxia, there is still room for developing neuroplastic changes in response to sensory-motor stimulation [69]. In recent review, ischemic damages evoke an initiation of network reorganization in spared areas of the brain [70].
There are different goals for rehabilitation for chronic and acute brain diseases; even all available rehabilitation modalities are implemented simultaneously in both types of rehabilitation. The goal of rehabilitation in dementia is to prevent cognitive and physical decline and to preserve the level of functioning and the quality of life for as long as possible. Rehabilitation activities for people living at home have to continue without time limits, for many years. Home program refers to activities designed for joint patient and caregivers, which increase patient–caregiver connections. The office staff get training, related to interaction with patients and their caregivers. Much attention is placed on education and support of caregivers as well. Elements of physical, occupational, and speech therapy in outpatient clinics could be provided by office staff in the office and by caregivers at home. Cognitive and physical stabilization is expected, as demonstrated in Figure 3.
Rehabilitation in chronic brain disease.
In stroke and head trauma (acute brain catastrophes), the goal of rehabilitation is to return to the premorbid level as close as possible. Rehabilitation in this case is a time-limited process, lasting from several months to several years. Cognitive and physical improvement is expected, as shown in Figure 4.
Rehabilitation in acute brain trauma/stroke.
The six pillars of the program consist of pharmacological interventions, mild physical exercises, multisensory stimulation, cognitive training, nutrition, and emotional support. Each pillar has direct and indirect effects on the elements of the 4M’s Dementia Rehabilitation Model™.
Medications and supplements comprise the first pillar in this model. Cholinesterase inhibitors, NMDA receptor antagonists, antidepressants, neuroleptics, and mood stabilizers, along with medication for sleep and pain, are used when clinically appropriate. Supplements include vitamin D3, B-complex, fish oil, folic acid, alpha-lipolic acid, acetyl-l-carnitine, inositol, Ribose, and other vitamins.
Mild physical exercises are the second pillar in this rehabilitation. Muscle activities couple with increasing brain blood flow and simultaneously attention and procedural memory training. Exercises are designed for people with extremely limited physical capacities and problems with gait and ambulation. The physical exercises are safe and done in sitting positions and can be performed in the doctor’s office or at home.
Physical exercises mainly consist of simple, coordinated hand and leg exercises performed both with and without the use of simple objects, such as a tennis ball. Dual-task exercises consist of hand movements, coupled with counting and breathing. Special exercises have been developed for balance training and include eye movements for decreasing visual fields and working with neck movements.
Multisensory stimulations include pleasurable activities related to auditory, visual, and tactile and other sensory channels. For example, patients work on pegboards to increase finger mobility and right–left coordination, or patients read tongue twisters loudly, sing songs, or watch comedians.
Attention and memory training consist of computerized attention (“go, no-go”) and working memory exercises (“N-back” paradigm), tasks that are performed in the doctor’s office with different objects (words, numbers, shapes, pictures, textures) plus pen and paper cognitive exercises, performed at home.
Nutrition includes diet and digestive support for microbiome and pancreatic enzymes, if clinically indicated (loss of weight).
Emotional support consists of implementation of stress management tools, brief educational sessions, related to family relationships, psychotherapy for patient’s emotional reactions in response to decline of cognitive and physical functions. For caregivers, there are psychotherapy sessions for developing coping strategies to manage behavior problems in dementia and to recognize symptoms of burnout syndrome. The family understanding and support help dementia victims stay at home for a long period of time.
Here, we present two cases with mild dementia stabilized over years with an integrative treatment approach.
Patient was an 87-year-old, retired engineer, who first came to our office at age 68. Her diagnosis was mild dementia with episodes of depression, anxiety, insomnia, HTN, diabetes, neuropathy, arthritis, dizziness, and gait problems. Her current psychiatric medications are memantine, gabapentin, clonazepam, zolpidem, buproprion SR, donepezil, vitamin D, lovaza, magnesium oxide, B-complex, and folic acid.
This patient has been treated for 19 years (2001–2020). Cognitive assessments include the MMSE, clock-drawing task, verbal fluency animals, and verbal fluency letters tests. She was doing full rehabilitation protocol with any new modifications, which had been developed during this time interval in our office.
As you can see in Figures 5–8, this patient has been stable for the whole period of treatment based on the results of these 4 tests.
MMSE stabilization.
Clock-drawing task stabilization.
Verbal fluency animals.
Verbal fluency letters.
This patient was a 92-year-old female, retired clerk, who came for treatment at age 74. Her diagnosis was mild dementia with episodes of depression, anxiety, insomnia, HTN, CAD, diabetes, arthritis, dizziness, and gait problems. She had a mini-stroke in 2015. Current medications are Namenda, Trintellix, B-complex, folic acid, and magnesium oxide.
This patient has been treated for 16 years (2002–2020). Cognitive assessments include Mini-Mental Status Examination (MMSE), clock-drawing task, verbal fluency animals, and verbal fluency letters tests. She was doing full rehabilitation protocol with any new modifications as in the previous case 1.
After mini-stroke (2014–2015), her MMSE dropped to 22 and then returned to 25.
As you see in Figures 9–12, this patient has been stable for the whole period of treatment.
MMSE stabilization.
Clock-drawing task stabilization.
Verbal fluency animals.
Verbal fluency letters.
The theoretical basis of this rehabilitation model is rooted in emerging research related to neuroplasticity data. Other well-known facts regarding AD pathogenesis—including chronic hypoperfusion and hypoxia, oxidative stress, and mitochondrial and bioenergetics failure—also provide a solid theoretical foundation upon which to effectively design and test different treatment modalities available for rehabilitation in AD [69, 70, 71]. Additionally, modifiable risk factors for AD development and progression continue to be identified [72].
In a broader sense, rehabilitation in AD could include medications that are available today (and those that will become available in the future), in addition to all possible non-pharmacological modalities that are aimed at stabilizing brain and body functions, with special attention to physical and cognitive exercises, sensory stimulations, and dietary modifications.
The rehabilitation of AD has to be seen as an ongoing treatment approach not limited by time constraints. It can be adapted to the different stages of this illness, including even the preclinical stage.
Not all motor and cognitive functions are equally affected in AD. At various levels of dementia and in each cognitive domain, there is a time-related evolution of brain disability. Meanwhile, there is a growing body of data related to the preservation of some of the brain functions in AD, including certain learning and procedural memory capacities, emotional and movement controls, and the ability to use external memory aids [72, 73, 74, 75, 76].
The multifaceted rehabilitation model for home usage presented here demonstrates strategies that go beyond the prescribing of medications to alleviate AD progression alone. It is a dynamic framework that is open to the addition of any newfound medications or innovations in nonpharmacological interventions. This model is based on a proactive, 24/7 approach to battling AD—starting with doctor’s office visits and continuing into the patient’s home for an indefinite period of time.
These rehabilitation strategies become meaningful only with ongoing support from caregivers who help the patients at home with nutrition and everyday physical and cognitive activities. This model is flexible, and the key to it is to use all the five elements of the program simultaneously. This kind of simultaneous approach is already commonly used in the treatment of many other progressive chronic ailments, such as cardiac problems, dyslipidemia, hypertension, and diabetes.
The cost for implementation of this home-based rehabilitation model is minimal (workbook, videos, and tennis ball). In addition, this model may ease the financial burden of this deadly disease on the health care system as a whole by reducing secondary medical problems from progressive dementia and delaying nursing home placement.
A multifaceted rehabilitation model for dementia at home offers a promising strategy for postponing cognitive and physical decline in dementia. Modifiable factors in dementia could be implemented at low cost.
The development of comprehensive therapy models for rehabilitation in dementia is a matter of time. There is an urgent need for the designing of long-term studies, in which all available modalities will be simultaneously implemented and for as long as possible. Further research is needed to assess the efficacy and economic impact of this multifaceted rehabilitation model.
Epidemiological studies have identified a number of modifiable factors in the onset and progression of dementia.
A new understanding of the pathogenesis of dementia has revealed that protein changes in the brain develop simultaneously with cerebrovascular pathology.
Progression of clinical dementia depends on the stress, emotional reactions, CBF, digestive system, medical illnesses profile, cognitive activities, and muscle health.
Physical and mental activities may contribute to the delay of the onset of dementia and slow down the disease progression.
A novel treatment model for dementia patients is the simultaneous use of nonpharmacological modifiable factors and pharmacological interventions for many years.
Thank you to Vian Shekhtman and Nora Zagranichny for their assistance in preparation of this chapter.
The authors declare that they have no competing interests. The authors have no financial interests in this project.
No grant support was received for this project.
I want to thank the patients that have been treated in our center. Their participation and feedbacks were very valuable, and we are grateful for it.
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Many researches have been conducted to determine the best control method for vortex flow in pump sumps so that the pump lifespan can be maximized. In this study, a vortex control principle designed to minimize the impact of submerged vortex flow in pump sump on major pump components is presented. This principle employs a device called the plate type floor splitter which serves the function of eliminating vortices formed on the sump floor and reduces the intensity of swirling motion in the intake flow. A pump sump model was built to carry out the study by installing a floor splitter plate sample under the pump suction inlet and the corresponding parameters used to quantify the swirl intensity known as the swirl angle was measured. Procedures for the measurement were conducted based on ANSI/HI 9.8-2018 standard. A numerical simulation was performed to study the flow in a full-scale pump sump. The results showed that the installation of floor splitter plate can eliminate vortices efficiently and reduce swirl angle significantly. 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One of the most plausible applications of nanotechnology is to produce nanoparticles of high thermal conductivity and mixing with the base fluids that transfer energy forming what is called nanofluids. Adding of nanoparticles to the base fluid shows a remarkable enhancement of the thermal properties of the base properties. Nanotechnology has greatly improved the science of heat transfer by improving the properties of the energy-transmitting fluids. A high heat transfer could be obtained through the creation of innovative fluid (nanofluids). This also reduces the size of heat transfer equipment and saves energy.",book:{id:"8887",slug:"thermophysical-properties-of-complex-materials",title:"Thermophysical Properties of Complex Materials",fullTitle:"Thermophysical Properties of Complex Materials"},signatures:"Mahmoud Salem Ahmed",authors:null}],onlineFirstChaptersFilter:{topicId:"157",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:287,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. 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