Regression coefficient, mean error and the coefficients of the non-linear Gompertz function used for the processing of the biomass of White Willow sample trees
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{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"},{slug:"intechopen-identified-as-one-of-the-most-significant-contributor-to-oa-book-growth-in-doab-20210809",title:"IntechOpen Identified as One of the Most Significant Contributors to OA Book Growth in DOAB"}]},book:{item:{type:"book",id:"1311",leadTitle:null,fullTitle:"Advances in Cancer Therapy",title:"Advances in Cancer Therapy",subtitle:null,reviewType:"peer-reviewed",abstract:"The book \"Advances in Cancer Therapy\" is a new addition to the Intech collection of books and aims at providing scientists and clinicians with a comprehensive overview of the state of current knowledge and latest research findings in the area of cancer therapy. For this purpose research articles, clinical investigations and review papers that are thought to improve the readers' understanding of cancer therapy developments and/or to keep them up to date with the most recent advances in this field have been included in this book. 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She received her PhD from Kansas State University, Manhattan, USA and joined AUB in 1994. She assumed many administrative positions at AUB including Interim Associate Provost, Chair of Enrollment Management, Chair of Biology Department and Director of Center for Drug Discovery. She is a prominent scholar with outstanding scientific contributions to the study of the role of natural products in cancer therapy and identifying their cellular and molecular mechanisms of action. She has published 95 peer reviewed articles, more than 10 book chapters and has edited a few books. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"314",title:"Regenerative Medicine and Tissue Engineering",subtitle:"Cells and Biomaterials",isOpenForSubmission:!1,hash:"bb67e80e480c86bb8315458012d65686",slug:"regenerative-medicine-and-tissue-engineering-cells-and-biomaterials",bookSignature:"Daniel Eberli",coverURL:"https://cdn.intechopen.com/books/images_new/314.jpg",editedByType:"Edited by",editors:[{id:"6495",title:"Dr.",name:"Daniel",surname:"Eberli",slug:"daniel-eberli",fullName:"Daniel Eberli"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"19221",title:"The Above-Ground Biomass Production and Distribution in White Willow Community During 11 Years of Primary Succession",doi:"10.5772/19990",slug:"the-above-ground-biomass-production-and-distribution-in-white-willow-community-during-11-years-of-pr",body:'\n\t\tIn 1996 the water level in the studied area, the central lake of the Nove Mlyny Reservoir, was reduced by 85 cm. The reason was the implementation of a project with the aim to remedy the negative effect of the reservoir on the biological function of the river corridor. Within the project two islands across the reservoir were to be constructed. After the water level was reduced, seedlings of White Willow appeared immediately on the uncovered sediments. The area of the Nove Mlyny Reservoir thus became a unique natural laboratory of the succession of soft floodplain forest in several dozens of hectares (Buček et al., 2004). The initial stages of the White Willow community, originating from the primary succession (Bergmann, 1999; Matic et al., 1999), prove to be highly productive ecosystems.
\n\t\t\tThe aim of research was to monitor the development of the successive community not only regarding the number and growth of individuals but also other production indicators, such as the biomass of stems, branches and leaves, the LAI or the stem volume, in order to create a natural model of community succession. A natural succession model can both bring some light into the principles of community growth and be a suitable source of knowledge concerning the cultivation of fast-growing woody plants on energetic plantations.
\n\t\tThe permanent research plot was established in 2005 in Vlckuv ostrov Island, the construction of which was finished in 2001. The middle Nove Mlyny reservoir is located approximately 40 km to the south of Brno (the Czech Republic), 16O 37´ E and 48 O 55 N, at an altitude of 170 m a.s.l. In the stand, aged 5 at the time, a rectangular area of 20 x 50 m was set up. The initial succession stages until the age of five were studied in smaller areas because of the high population density (Konůpek, 1998; Kovářová, 2003).
\n\t\t\t\tThe area is located in Northern Pannonian biogeographical subprovince (Culek et al., 1996); it is characterized by warm climate with low precipitation, therefore it belongs to a warm climatic region (Quitt, 1971). The soil in the research area has been artificially created. The sediments which had naturally sorted in the liquid environment were relocated from the reservoir bottom to the middle of the artificially created island embankments by suction dredgers. The upper horizon contains loamy particles, after 15-20 cm these are sandy. With the reservoir water permanent storage quota of 170 m a.s.l. the surface of ground water is 20 cm deep.
\n\t\t\tIn 2005 all trees in the research plot were numbered and their biometric characteristics – the height and the girth of the stem at breast height (using the VERTEX III altimeter and a tape) – were measured. The measuring was repeated annually, always after the end of the growing season. In 2010 individual trees were surveyed by means of the FieldMap (IFER) technology; the obtained data were used for the creation of a 3D visualization of the research plot (Fig.1), using SVS application.
\n\t\t\t\tvisualisation of research plot in age of 11 years
In order to gain production characteristic of the stand, the method published by Newbould (1967) was used in a form slightly modified by authors.
\n\t\t\t\tSix sample trees of different DBH (diameter at breast height) classes were destructively sampled during the research. The sample trees were taken from adjacent stands; the research plot was left for solely natural succession.
\n\t\t\t\tAfter felling, the sample trees were divided into meter sections and their leaves and branches were gradually removed. Twenty leaves were sampled in each section at random. The girth of the stem was measured each 20 cm; a cross section was extracted from the stem basis for the tree-ring analysis; and a part of stem was extracted for the establishment of wood density.
\n\t\t\t\tThe removed leaves and branches were dried at a temperature of 105O C until they reached constant weight. The series of 20 leaves from each section were scanned and their area was measured using the ImageTools application. Further, also these leaves were dried and their drymass was measured. The volume of wood samples was ascertained using a measuring cylinder, then the samples were dried again and their drymass was measured.
\n\t\t\t\tThe energy content accumulated in leaves, branches and wood was found out calorimetrically (Bomb Calorimeter PARR 1281).
\n\t\t\tThe annual measurement of all trees in the research plot was used to calculate:
\n\t\t\t\tPopulation density
Mortality
Number of sample trees in DBH and height classes
Mean height and DBH of stem
The drymass of leaves and branches of sample trees were added up for individual sections to gain the total drymass. The volume of stem was calculated using the formula for the blunted cone volume as the sum of volume of the 20cm sections. The stem drymass was calculated from the wood density by multiplying the stem volume. Further, the average specific leaf area (SLA) for the leaves of individual sections was calculated as the quotient of a leaf drymass and its area. The SLA value was then used to calculate the area of leaves in individual sections from the total leaf drymass.
\n\t\t\t\tTo derive the values of growth characteristics of sample trees non-linear Gompertz function was used:
\n\t\t\t\twhere “Y” is the mean value of biomass of sample trees in each DBH class, “x” is the mean diameter at breast height in cm for the particular DBH class, and coefficients a, b, c, d are presented in Table 1.
\n\t\t\t\tGrowth quantity | \n\t\t\t\t\t\t\tCoefficients | \n\t\t\t\t\t\t\tRegression coefficient | \n\t\t\t\t\t\t\tMean error | \n\t\t\t\t\t\t|||
\n\t\t\t\t\t\t\t | a | \n\t\t\t\t\t\t\tb | \n\t\t\t\t\t\t\tc | \n\t\t\t\t\t\t\td | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | [%] | \n\t\t\t\t\t\t
Stem volume | \n\t\t\t\t\t\t\t595 | \n\t\t\t\t\t\t\t5.9 | \n\t\t\t\t\t\t\t0.0925 | \n\t\t\t\t\t\t\t3.0 | \n\t\t\t\t\t\t\t0.992 | \n\t\t\t\t\t\t\t8.56 | \n\t\t\t\t\t\t
Stem biomass | \n\t\t\t\t\t\t\t235 | \n\t\t\t\t\t\t\t5.3 | \n\t\t\t\t\t\t\t0.08 | \n\t\t\t\t\t\t\t2.4 | \n\t\t\t\t\t\t\t0.993 | \n\t\t\t\t\t\t\t2.61 | \n\t\t\t\t\t\t
Branch biomass | \n\t\t\t\t\t\t\t98.8 | \n\t\t\t\t\t\t\t10.15 | \n\t\t\t\t\t\t\t0.095 | \n\t\t\t\t\t\t\t0.0 | \n\t\t\t\t\t\t\t0.999 | \n\t\t\t\t\t\t\t0.35 | \n\t\t\t\t\t\t
Leaf biomass | \n\t\t\t\t\t\t\t5.5 | \n\t\t\t\t\t\t\t8.8 | \n\t\t\t\t\t\t\t0.16 | \n\t\t\t\t\t\t\t0.008 | \n\t\t\t\t\t\t\t0.993 | \n\t\t\t\t\t\t\t0.13 | \n\t\t\t\t\t\t
Regression coefficient, mean error and the coefficients of the non-linear Gompertz function used for the processing of the biomass of White Willow sample trees
The data valid for a stand area unit (1 ha) were obtained by multiplying the mean values by the number of trees in each class and their summarization. The non-linear Gompertz functions were used to process the data of the White Willow biomass as they express the data very well, which is proved by the high values of regression coefficients (Table 1).
\n\t\t\tThe community of the White Willow sprang up as a cohort on the island – all trees are of the same age and the same species. In such a community the predominating relationship is intraspecific competition, which leads to high mortality related to the growth of individuals. This process is referred to as self-thinning and it follows the 3/2 rule (Slavíková, 1985). The development of the population density in the research plot (Fig. 2) complies with this ecological law.
\n\t\t\t\tPopulation density (No. of trees per hectar). development during succession
The gradual transition of trees from lower DBH classes to higher ones is expressed in Table 2. We can see the diversification of DBH values and the considerable mortality of trees in the lowest DBH classes which is caused by the lack of radiation in the lowest stand layers. With the succession of the community, the canopy closure expressed by LAI (see chapter 3.3) increases and for a light-demanding species, such as the White Willow, the amount of radiation soon drops under the value of the photosynthesis compensation point.
\n\t\t\t\tThe mortality in the second year of succession rose to 50%, then it dropped to about a third. The key moment came in the sixth year of succession when the intra-annual mortality reached 85%, which was reflected in the productivity stagnation. Since this year, the intra-annual mortality decreased gradually to 51%, 12%, and 9%. The total mortality after 11 years reached 99%!
\n\t\t\tThe gradual development of the mean DBH and the mean height is presented in Figures 3 and 4. At the age of 11, the average annual height increment was 1.4 m and the average annual diameter increment was 1.2 cm. However, the maximum height of dominant trees is up to 22.6 m and the maximum DBH is 28.6 cm. The stand now manifests a clear division into height layers. The height increment started to slow down from the age of 9, in contrast to the diameter increment, which continues with approximately the same speed. Moreover, the increase in the mean DBH is more noticeable thanks to the mortality of the trees from the lowest DBH classes.
\n\t\t\tThe difference in the SLA between the leaves in the shade and the leaves in the sun was considerable. The lowest SLA value of the leaves at the crown base of subdominant trees was 0.00433 g*cm-1; on the other hand, the highest SLA value measured in the sunny leaves at the crown top of dominant trees was 0.12748 g*cm-1. Therefore, the same drymass of sunny leaves takes a thirty times smaller area.
\n\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t|||||||
\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
I (0.00–1.00) | \n\t\t\t\t\t\t\t247600 | \n\t\t\t\t\t\t\t46880 | \n\t\t\t\t\t\t\t8533 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t\t10 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t
II (1.00–2.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 78160 | \n\t\t\t\t\t\t\t27733 | \n\t\t\t\t\t\t\t1260 | \n\t\t\t\t\t\t\t450 | \n\t\t\t\t\t\t\t70 | \n\t\t\t\t\t\t\t10 | \n\t\t\t\t\t\t\t20 | \n\t\t\t\t\t\t
III (2.0–3.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 20667 | \n\t\t\t\t\t\t\t1670 | \n\t\t\t\t\t\t\t490 | \n\t\t\t\t\t\t\t70 | \n\t\t\t\t\t\t\t10 | \n\t\t\t\t\t\t\t10 | \n\t\t\t\t\t\t
IV (3.00–4.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 6800 | \n\t\t\t\t\t\t\t1740 | \n\t\t\t\t\t\t\t480 | \n\t\t\t\t\t\t\t60 | \n\t\t\t\t\t\t\t50 | \n\t\t\t\t\t\t\t0 | \n\t\t\t\t\t\t
V (4.00–5.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 2400 | \n\t\t\t\t\t\t\t1340 | \n\t\t\t\t\t\t\t610 | \n\t\t\t\t\t\t\t60 | \n\t\t\t\t\t\t\t40 | \n\t\t\t\t\t\t\t10 | \n\t\t\t\t\t\t
VI (5.00–6.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 2133 | \n\t\t\t\t\t\t\t1060 | \n\t\t\t\t\t\t\t670 | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t\t60 | \n\t\t\t\t\t\t\t50 | \n\t\t\t\t\t\t
VII (6.00–7.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 800 | \n\t\t\t\t\t\t\t710 | \n\t\t\t\t\t\t\t680 | \n\t\t\t\t\t\t\t230 | \n\t\t\t\t\t\t\t120 | \n\t\t\t\t\t\t\t120 | \n\t\t\t\t\t\t
VIII (7.00–8.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 400 | \n\t\t\t\t\t\t\t680 | \n\t\t\t\t\t\t\t470 | \n\t\t\t\t\t\t\t230 | \n\t\t\t\t\t\t\t230 | \n\t\t\t\t\t\t\t70 | \n\t\t\t\t\t\t
IX (8.00–9.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 267 | \n\t\t\t\t\t\t\t380 | \n\t\t\t\t\t\t\t410 | \n\t\t\t\t\t\t\t250 | \n\t\t\t\t\t\t\t180 | \n\t\t\t\t\t\t\t140 | \n\t\t\t\t\t\t
X (9.00–10.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 400 | \n\t\t\t\t\t\t\t380 | \n\t\t\t\t\t\t\t210 | \n\t\t\t\t\t\t\t170 | \n\t\t\t\t\t\t\t170 | \n\t\t\t\t\t\t
XI (10.00–11.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 530 | \n\t\t\t\t\t\t\t360 | \n\t\t\t\t\t\t\t280 | \n\t\t\t\t\t\t\t220 | \n\t\t\t\t\t\t\t190 | \n\t\t\t\t\t\t
XII (11.00–12.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 330 | \n\t\t\t\t\t\t\t380 | \n\t\t\t\t\t\t\t240 | \n\t\t\t\t\t\t\t230 | \n\t\t\t\t\t\t\t220 | \n\t\t\t\t\t\t
XIII (12.00–13.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 220 | \n\t\t\t\t\t\t\t310 | \n\t\t\t\t\t\t\t210 | \n\t\t\t\t\t\t\t190 | \n\t\t\t\t\t\t\t230 | \n\t\t\t\t\t\t
XIV (13.00–14.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 200 | \n\t\t\t\t\t\t\t230 | \n\t\t\t\t\t\t\t300 | \n\t\t\t\t\t\t\t240 | \n\t\t\t\t\t\t\t240 | \n\t\t\t\t\t\t
XV (14.00–15.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 70 | \n\t\t\t\t\t\t\t170 | \n\t\t\t\t\t\t\t120 | \n\t\t\t\t\t\t\t160 | \n\t\t\t\t\t\t\t130 | \n\t\t\t\t\t\t
XVI (15.00–16.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 100 | \n\t\t\t\t\t\t\t120 | \n\t\t\t\t\t\t\t230 | \n\t\t\t\t\t\t\t150 | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t
XVII (16.00–17.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 30 | \n\t\t\t\t\t\t\t50 | \n\t\t\t\t\t\t\t120 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t\t120 | \n\t\t\t\t\t\t
XVIII (17.00–18.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 30 | \n\t\t\t\t\t\t\t60 | \n\t\t\t\t\t\t\t110 | \n\t\t\t\t\t\t\t110 | \n\t\t\t\t\t\t\t200 | \n\t\t\t\t\t\t
XIX (18.00–19.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 30 | \n\t\t\t\t\t\t\t80 | \n\t\t\t\t\t\t\t90 | \n\t\t\t\t\t\t\t60 | \n\t\t\t\t\t\t
XX (19.00–20.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 80 | \n\t\t\t\t\t\t\t130 | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t
XXI (20.00–21.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 40 | \n\t\t\t\t\t\t\t50 | \n\t\t\t\t\t\t\t130 | \n\t\t\t\t\t\t
XXII (21.00–22.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 10 | \n\t\t\t\t\t\t\t70 | \n\t\t\t\t\t\t\t80 | \n\t\t\t\t\t\t
XXIII (22.00–23.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 10 | \n\t\t\t\t\t\t\t20 | \n\t\t\t\t\t\t\t40 | \n\t\t\t\t\t\t
XXIV (23.00–24.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 10 | \n\t\t\t\t\t\t\t30 | \n\t\t\t\t\t\t
XXV (24.00–25.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 0 | \n\t\t\t\t\t\t
XXVI (25.00–26.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 10 | \n\t\t\t\t\t\t
XXVII (26.00–27.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 0 | \n\t\t\t\t\t\t
XXVIII (27.00–28.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 10 | \n\t\t\t\t\t\t
XXIX (28.00–29.00) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | 10 | \n\t\t\t\t\t\t
Total | \n\t\t\t\t\t\t\t247600 | \n\t\t\t\t\t\t\t125040 | \n\t\t\t\t\t\t\t69733 | \n\t\t\t\t\t\t\t10950 | \n\t\t\t\t\t\t\t6360 | \n\t\t\t\t\t\t\t3110 | \n\t\t\t\t\t\t\t2740 | \n\t\t\t\t\t\t\t2490 | \n\t\t\t\t\t\t
The numbers of trees in DBH classes during succession
The development of the stand mean diameter at breast height [cm] during 11 years of succession
The development of the stand mean height [m] during 11 years of succession
The distribution of leaf area in the stand at different ages is visualized in Fig. 5 – there is an obvious shift of the crown space to higher layers or higher DBH classes and from the age of 9 the stand started to create particular layers; at the age of 11 there are three obvious layers and there are a few dominant trees.
\n\t\t\t\tThe distribution of leaf area [m2] in DBH classes in the White Willow stand during the succession
As regards the total leaf area, its development can be clearly shown using the leaf area index (LAI) (Fig. 6). In eleven years the initial negligible LAI values at the beginning of the succession grew up to a relatively high value of 6.6.
\n\t\t\tThe stem volume is a basic production characteristic of forest stands. The development of the wood volume storage during the succession is presented in Fig. 7.
\n\t\t\t\t\tThere is a clear fast increase in hectare storage during the first years of succession; from the age of 6 it decreases. The age of 6 is of key significance from the point of view of potential effectiveness of harvest. The stand had already achieved very high storage – 244.6 m3.ha-1 – with the mean DBH 5.2 cm and height 8.5 m. Moreover, the six-year-old stand reached the highest average annual increment – 40.75 [m3*ha-1*a-1].
\n\t\t\t\t\t\n\t\t\t\t\t\tFig. 8 shows that in the first two years of succession the entire storage was concentrated in the low DBH classes (up to 2 cm); at the age of 5, the core of the storage is still in the lowest DBH class but a considerable part is transferred to DBH classes up to 9 cm. In the sixth and seventh year of the succession the storage is quite evenly distributed in DBH classes 2–19 cm
\n\t\t\t\t\tThe development of the leaf area index of the White Willow stand during 11 years of succession
The development of the wood volume storage in stems [m3.ha-1] during succession connected by a trend curve and the development of the average annual volume increment [m3*ha-1*a-1]
with the maximum in 10–16 cm. In the last four years of succession, the wood storage in stems is gradually moved to the higher DBH classes and divided into three groups, with the concurrent decrease in significance of the trees in the lower DBH classes, which die out due to the intraspecific competition for light. The trees with diameters from 10 to 23 cm become the bearers of production. This fact is important for the selection of the optimum harvesting and transport technology.
\n\t\t\t\t\tThe distribution of the stem volume storage [m3*ha-1] in DBH classes during succession
The drymass stored in stems expresses the production of the community better as the wood of fast-growing woody species has a relatively low density. The density we calculated for the White Willow (as the quotient of the volume of a fresh sample and drymass) was 337 kg*m-3.
\n\t\t\t\t\tThe drymass accumulated in the stems is expressed in the following graph (Fig. 9). At the age of 11, the community reached 102 t*ha-1, but similarly to the values of stem volume, we can see the decrease in intra-annual growth starting at the age of 6. The average annual increment at the age of 6 was 14.38 t*ha-1*a-1.
\n\t\t\t\t\tThe development of the total production of biomass accumulated in the stems during succession expressed in drymass [t*ha-1]
The development of the total production of biomass accumulated in the branches during succession expressed in drymass [t*ha-1]
The branch biomass can also be used as an energy material. The drymass accumulated in the branches is visualized in Fig. 10. At the eleventh year of the community succession, the branch drymass reaches 22.29 t*ha-1, which is considerable 17% out of the total biomass.
\n\t\t\t\tThe development of the assimilation apparatus expressed by the leaf drymass in the individual years of succession shows an increasing production capacity of the community (Fig. 11).
\n\t\t\t\t\tThe development of the total production of biomass accumulated in the leaves during succession expressed in drymass [t*ha-1]
In the eleventh year of succession the leaf drymass exceeded 5 t*ha-1; it was 3.9% out of the total drymass of the above-ground biomass accumulated in the stand.
\n\t\t\t\tThe total production of the above-ground biomass of the community is a sum of the drymass of the stems, branches and leaves. Its development in the individual years of the succession is presented in Fig. 12. At the age of 11 the total production of the community above-ground biomass reached 129.4 t*ha-1.
\n\t\t\t\t\t\n\t\t\t\t\t\tFig. 13 shows the relative proportions of the drymass of the stems, branches and leaves in the total drymass of the above-ground biomass. The proportion of the stem drymass in comparison with branch and leaf drymass is the lowest in the initial stages of succession (80%). At the age of 5 the proportion of stem drymass is the highest and since this moment the proportion of branch and leaf drymass increases at the expense of the stem. Finally, in the eleventh year, the relative proportion of stem drymass is again 80%.
\n\t\t\t\t\tThe development of the total production of the community above-ground biomass during succession expressed in drymass [t*ha-1]
The relative proportion of stem drymass (red), branch drymass (green) and leaf drymass (blue) during succession
Another visualization of the distribution of drymass of the above-ground biomass in the stand during the succession is provided in the following graph (Fig. 14). In the initial stages of succession the lowest DBH classes are of the highest production significance in the community. This continues until the age of 5. Between the fifth and the sixth year of succession a significant change occurs in the structure of the stand. As the lowest DBH class trees had died, the trees of higher DBH classes gained space and their diameter increments started to increase fast. This trend, although slower, remains in the following years up to the age of 10. The eleventh year brought about another big leap of the plants into the higher DBH classes.
\n\t\t\t\t\tThe average annual production of the above-ground biomass expressed in drymass reaches 11.77 t*ha-1; however, the maximum values are ascertained for the age of 6, when the average annual production was 16.72 t*ha-1.
\n\t\t\t\t\tThe distribution of the total drymass of the above-ground biomass [t*ha-1] in DBH classes during succession
The content of energy accumulated in the above-ground biomass (of leaves, branches and wood) is presented in the following graph (Fig. 15). The average content of energy measured was 18.15 KJ*g-1 for leaves, 18.16 KJ*g-1 for branches and 17.83 KJ*g-1 for wood.
\n\t\t\t\tAs regards the average annual content of energy accumulated in the stand above-ground biomass (Fig. 16), the highest values were reached at the age of 6 – 298,827 MJ*ha-1. The
\n\t\t\t\tThe content of energy (MJ*ha-1) accumulated in stems (red), branches (green) and leaves (blue) of the stand during the succession
The average annual content of accumulated energy [MJ*ha-1] in the stand during the succession
values then decreased until they dropped to 214,000 MJ*ha-1 in the ninth year; subsequently, the average annual content of accumulate energy remains more or less constant.
\n\t\t\t\tThe same progress is also manifested by the stand output (Fig. 17), expressed in kW*ha-1: the highest value, 9.48 kW*ha-1, is reached at the age of 6, and in the eleven-year-old stand the output drops to 6.68 kW*ha-1.
\n\t\t\t\tThe output of 1 ha of the stand during the succession [kW*ha-1]
The paper describes selected production characteristics of a community of the White Willow which originated by means of natural oecesis on a newly constructed island in the middle of a water reservoir. The community succession was monitored for 11 years. During this period the stand developed completely naturally without any human interventions. The results were used to create a model of production properties of a natural ecosystem which can serve as a foundation for possible management rules for energy stands of the same species in similar conditions, such as bank stands or polders (Maděra et al., 2009).
\n\t\t\tThe results prove that the production of the above-ground biomass is very high in the monitored community of the White Willow. The highest average annual values of all monitored production characteristics were achieved at the age of 6 of the stand. The estimated value of drymass production is very favourable exceeding the majority of species which are grown for energy purposes in Central Europe. The values exceed the data measured by Bungart et al. (2000) in the region of Lusatia, Germany for 3–4-year-old stands of willows and poplars in mining areas approximately ten times. Kajba et al. (2004) mention that the overall mean DM production of all the investigated clones was 6.5 tons per hectare, the greatest production was exhibited by clones \'B44\', \'V093\' and \'V052\' (10.2, 9.2 and 9.1 t*ha-1, respectively).
\n\t\t\tBased on the obtained results, from the perspective of production the most appropriate moment for harvest in case of energy stands of the White Willow appears to be when a stand reaches six years of age.
\n\t\tThe study was supported by the research project MSM 6215648902 and Internal Grant Agency of Faculty of Forestry and Wood Technology Mendel University in Brno 12/2010.
\n\t\tCardiovascular disease (CVD) is the complex disease associated with morbidity, mortality and loss of quality of life [1]. Furthermore, it is the most significant cause of death in the diabetic population. South Africa is faced with an increasing number of people diagnosed with diabetes mellitus which intensify the burden on the health system. The number of adults with diabetes in South Africa has increased to 4.5 million [2]. This caused the country to expand its healthcare focus to include Diabetes Mellitus. Home-Based Carers (HBCs), also known as Community Health Workers (CHWs) are involved in caring for diabetes mellitus patients in collaboration with the Primary Health Care. The previous study done in the Southern African context revealed that patients lack respect to HBCs and the HBCs lack training on chronic conditions including diabetes mellitus [3]. HBCs need to undergo training before taking – up health-related jobs at the community level. HBCs who care for patients with cardiovascular diseases including diabetes mellitus at the community level need to be trained on how to care for their patients.
In this chapter, we present conceptual frameworks that can be followed to develop training programmes for HBCs systemically. A conceptual framework is a network of interlinked concepts that can provide a comprehensive understanding of a phenomenon [4]. Furthermore, it provides an interpretative approach to reality, to express and explain ideas and also to make inferences or draw conclusions [4, 5]. A framework is a layered structure indicating the kind of programs which should be built and how they would interrelate. The conceptual framework aims to guide the development of the training programme for HBCs necessary for empowering them with knowledge and skills useful during care of People with Cardiovascular diseases including Diabetes Mellitus.
The systematic literature review method was used to review literature related to diabetes mellitus, type 2 diabetes mellitus, Community Health Workers, CHWs diabetic knowledge and diabetes mellitus, diabetic training of CHWs. The theories where two themes with their subthemes that has emerged. Other related sources were used to support the themes that has emerged from the theories. The following themes and their subthemes have emerged: (1) The use of Practice orientated theory for training development which include the agent, the recipient, the context, the dynamics, procedure and terminus; (2) The use of the ADDIE model in the development of a training programme for HBCs which include Analysis, Design, Development, Implementation and Evaluation.
The issues that need to be addressed in the development of the conceptual framework are goal content, the prescriptions of the activity to attain the desired outcome, and the survey list to identify the gap between the intended activity and the prescriptions of the activity [5]. The main aim of the framework is to identify concepts that could be reflected in the training program. The concepts identified are utilised to describe the conceptual framework that guided the development of the training program for HBCs.
The ideas of Dickoff and others can be used to formulate the conceptual framework that guides the development of training for HBCs for cardiovascular patients. The six concepts of the survey list include agent, recipient, context, dynamics, procedure and terminus. The following questions are used as the basis for the formulation of the conceptual framework that informed the development training programme in this study were:
Who is the agent? -The agent refers to the person who performs the activity which is the development of the training programme to improve knowledge, skills and attitude of the HBCs who cares for diabetes people.
Who is the recipient? - The recipients of the activity who will benefit from the training program in this study are the HBCs who care for diabetes people.
What is the context? - The context of the training programme is where the HBCs provide care for PWD.
What are the dynamics? - Dynamics in this study, are the challenges and the training needs that motivated the development of the training programme.
What is the procedure? -The procedure included the processes followed during the development of the training programme.
What is the terminus? - Terminus refers to the end product of the activity which in this study are competent HBCs, autonomy to provide care to diabetic people and controlled blood glucose in diabetes people.
The agent is the first aspect of the survey list and refers to a person who performs the activity with the aim of Dickoff and others, which is the development and implementation of the training programme for HBCs who care for diabetes mellitus people. The agent should be the researcher who conducts needs analysis and facilitate the development of the training program for empowering HBCs who care for PWD. The agent as the facilitator in this study should possess certain characteristics. The agent is expected to develop a training programme and empower HBCs with knowledge and skills necessary for the provision of care to PWD. Therefore, the agent is expected to be competent and also required to possess personal qualities and abilities necessary to perform these activities [6]. Furthermore, the agent needs to possess the following characteristics knowledge, skills and attitude to be able to capacitate HBCs with the necessary information to be able to execute their expected tasks with ease. The following characteristics of the agent are described below: knowledge, skills and attitude.
Knowledge” refers to a body of facts or ideas acquired through study, investigation, observation or experience [7]. The role of the agent as a facilitator was to develop the training programme for the HBCs who care for PWD. The agent was required to be aware of the training needs of the HBCs to develop an effective training programme, therefore training needs analysis was necessary for the development of the training programme. The agent should possess scientific knowledge and research skills that will make it possible to explore and describe the knowledge and learning needs of the HBCs for people with diabetes. The agent should detect the challenges that inhibit quality care and management of PWD. The recipients will contribute towards the development of the training programme by pointing out their challenges and learning needs during the care of diabetes mellitus people.
The agent should be able to build good interpersonal relationships with the recipients and other stakeholders (dietician and the pharmacist) to relate and create an environment conducive for implementation of the training programme. An agent should be able to motivate and empower the participants to bring out the best in them through management skills. An agent listens actively to hear the participants’ thoughts and messages and respond appropriately through listening skills. Good communication skills enable the agent to create a healthy interaction among the participants, communicate effectively so that he/she can understand problems, elaborates the points of the team and his own, and effectively conveys ideas and messages, clarity and confidence to the participants.
The agent treats the participants equally during training and know-how to consider the differences in each one’s personalities. The agent is friendly and honest to the participants to create an admirable and pleasant environment good for interaction. People love to be with a person who has a desirable attitude and a pleasant manner of dealing with other people. The agent should be patient and persevering to be able to appreciate and understand the difficulties of the participants and determined to see objectives achieved. The agent also has a sense of empathy for the participants who need to be understood. The agent should competent and demonstrate a professional attitude in carrying out their function. The agent should be respectable, reliable and committed to helping the participants learn for themselves and also confident to project a positive and purposeful atmosphere in the workshop.
The recipients refer to a person who receives the activity [5]. The recipients were all the HBCs who care for the diabetes mellitus people and benefited from the training programme design. The HBCs have the responsibility to provide effective and efficient quality health care to people with diabetes. The agent should be informed by the recipients’ experiences in the context they are providing service that the training programme is needed to address the training needs identified during situational analysis. The recipients interact with the agent by reacting during the implementation of the training programme to achieve their desired goals.
The recipients are expected to have certain characteristics that enable them to benefit from the programme and to participate fruitfully during the training. They are expected to be caring for people with diabetes to be able to participate in the training programme to achieve the desired outcomes of providing quality care. The HBCs as the recipients of the training programme in this context should be emotionally intelligent to be able to change and cope during training [8]. Attending the training programme would enhance knowledge, skills and attitudes to enable the recipients to perform their expected activities.
The HBCs as the recipients are expected to have the following characteristics of adult learners by Malcolm Knowles as outlined in Klopper (2009): self-concept, adult learner experience, readiness to learn, orientation to learning and motivation to learn. These characteristics offer HBCs a wide range of benefits, including improved comprehension of key concepts and a boost in knowledge retention.
HBCs as the recipients in this study and as adult learners are entitled to make their own decisions and take control of their own lives. The HBCs as adults identify the value of attending training because they want to learn what will be useful to them. The researcher role as a facilitator during the implementation of the training programme is to guide and direct them.
HBCs gain a lot of experience when working with diabetes mellitus patients on treatment at, therefore the training programme should focus on their unique training needs. HBCs as adult learners employed their learned experiences during care of diabetic people before they participated in the study to direct their learning because and to be actively involved in their learning.
HBCs as the recipients of the training were ready to challenge themselves with new learning experiences that offer some sort of social development benefit. They are ready to challenge themselves with new learning opportunities that will help them to fine-tune skills that pertain to their working environment.
As the recipients of the training, HBCs as adult learners are expected to change their perspective from one of postponed application of knowledge to immediacy of application. Their orientation towards learning was expected to shift from one of subject-centeredness to one of problem centeredness so that they will be able to solve problems related to their work problems.
HBCs need learning activities that will demonstrate how learning is going to benefit their work area.
The roles of the recipients during programme development included participation during needs analysis to assess their knowledge and point out their practices, sources of information, challenges and training needs. The HBCs knowledge gaps and learning needs lead to the plan used to develop a collective training programme including the nurse, dietician and a pharmacist.
HBCs as recipients possess different skillsets which assist in the execution of their daily tasks and to relate well with others to achieve the desired programme development goals as planned including communication skills, interpersonal skills, listening skills and patience.
Context according to Dickoff and others refers to the setting in which activity took take place [5]. The context is also described as an environment where data were collected about knowledge, experiences and the learning needs of HBCs who care for PWD and also where the training programme was implemented. The functions of the HBCs in this context are mandated by the Department of Health (DoH) which operates under the legal framework of the South African government. For the development of an effective training programme, the researcher needs to take into consideration the Guidelines on the Implementation of the Three Streams of Primary Healthcare Re-engineering [9], in line with the Policy Framework and Strategy Ward Based Primary Healthcare Outreach Teams [9] which regulate the functioning of the HBCs in this context.
The agent and the recipient need to understand the context concerning legal and policy frameworks that govern the activities of the HBCs. It was necessary for the agent and the recipient to understand the policies that regulate the day-to-day activities of HBCs in this context. To support the HBCs to improve quality health care provision, it is important to establish the relationship between legal frameworks, health context policies/guidelines and procedures [10]. Context of the training programme provides learning opportunities for recipients who are the HBCs. The context of the training can be influenced by the internal sources of the agent that guides her activities including competence and communication competence and the external resources available for maintaining and supporting the agent’s capacities and power.
Dynamics refers to the energy source or motivation for the activity inside an individual or the internal motivating factors for success [5]. Dickoff and others further explain that dynamics explore the physical, biological, psychological and chemical power sources of recipients and agents [5]. The training programme needs the dynamics that serve as the motivating factors that can be utilised to accomplish the activities of training programme development. The training programme needs to address the motivating factors as outlined by the HBCs during needs analysis to improve their knowledge, skills and attitude:
This aspect of the survey list is the guiding procedure, technique or the protocol of the activity [5]. This refers to the general rule that guides the activity and provides steps to be followed to achieve the set goals of the programme. Dickoff and others indicate that the procedure highlights the path, steps or pattern followed when performing an activity [5]. Furthermore, Dickoff and others indicate that procedures are the guiding rules, protocols or techniques while an activity takes place and do not prescribe particular features [5]. The procedure that provided steps followed during the development of the training programme to achieve the training goals was described. The procedure that can be followed for the development of a comprehensive training programme is the ADDIE Model of instruction [11]. The procedure for the development of the training programme described steps for creation of the following: learning outcomes, subject content, assessment strategies, instructional strategies, resources and trainers. Problem-based learning encourages the recipients of the programme to solve work-related problems by completing the given activities.
Terminus refers to the last stop, end-point of the activity [5]. Terminus is the desired outcome an agent wishes to attain by implementing a particular procedure. The terminus confirms whether the desired goals have been attained or not. The participants have to express the need for diabetes mellitus training to enhance their knowledge and skills relevant to the provision of quality care to diabetes people. The training programme aims to empower HBCs with knowledge related to the management of people with diabetes mellitus. The training-related needs of the recipients should be accommodated in the training programme with the result of having competent HBCs. The HBCs are expected to be competent when providing care to diabetes people which can be achieved by attending diabetes mellitus training before commencing their duties.
Empowering HBCs may introduce the following benefits: enhancing the development of HBCs knowledge and skills, ensuring the provision of quality care to diabetes mellitus people, increase self-confidence in HBCs during provision of care, prevent diabetes mellitus complication and control of blood glucose in PWD. Training assists HBCs with relevant knowledge and proper information that will assist in coping during the provision of service to PWD and the community may develop trust in the services provided by HBCs.
ADDIE model is a systematic instructional design and abbreviation of the following logical steps: Analysis, Design, Development, Implementation and Evaluation [11]. These steps are sequential meaning the output of one step becomes the input for the next step [12]. It is also called an iterative feedback model because the results of the last stage are returned to the point of origin for feedback, to close the loopholes and or to refine the learning product [12]. ADDIE model is pursued to ensure that correct steps are followed to develop appropriate learning material optimally, to meet the needs of the HBCs [13]. The model was helpful because it is process-based and follows a systemic problem-solving approach that provides well defined basic and easy to follow steps [14, 15, 16, 17]. The benefit of using this model is that it permits to refer and revisit previous steps during the process.
Instructional design system following the ADDIE model provided practical steps for organising training development project. According to Branch, ADDIE’s model describes and prescribes what needs to happen during the process [11].
The analysis is the first step of ADDIE’s model which is used to identify training needs to develop the training programme for the HBCs and formed the basis of all other steps [18]. On this step, needs analysis should be conducted to identify gaps in diabetes knowledge and practices of HBCs. Major knowledge gaps and training topics suggested serve as the foundation for specifying the learning outcomes, content and activities, instructional strategies and assessment strategies. Knowledge gaps are identified through the needs analysis to develop training [17, 19]. The analysis provides an opportunity to complete a thorough analysis of HBCs’ training needs that will guide the designing and the development of the training programme.
The design step is the blueprint of how the training programme is created [20]. The purpose of the designing step is to define the anticipated performance and suitable evaluation methods [11]. In the design step, learning outcomes are identified and formulated because the success of the training implementation depends on clearly formulated learning outcomes, to meet the needs of HBCs. There are two types of the learning outcomes namely; critical cross-field outcomes and specific learning outcomes which should be formulated. The information gathered during the analysis step (situational analysis) should be used to create a plan to bridge the learning gaps (training needs) identified and developed the specific learning outcomes. Based on the learning outcomes, the training content, teaching/learning methods, instructional strategies and assessment criteria should be designed.
The format of the design should encompass the following elements: the name of the training programme, NQF level, Credits, Purpose of the training programme, duration of the programme, learning assumed to be in place, critical cross-field outcomes, specific outcomes and assessment criteria, Unit standard and programme assessment [21]. The HBCs have a job description that describes their activities for caring for people with chronic conditions that are context-specific and is developed by NGOs managers. The designing of the training is based on SAQA because it was established to create a single, integrated, national education and training framework for the whole nation, and to improve the quality of education and training in South Africa. The adaptation of the SAQA standards format for guiding the design of the training programme should be helpful in the planning.
The clear and precise learning outcomes are formulated using Bloom’s Taxonomy to classify the following levels of learning: remember, understand, apply, analyse, evaluate and create [22]. Critical cross-field outcomes to address the participants’ needs and requirements and Specific Learning Outcomes for HBCs to achieve should be included.
Content is the focal point for engaging the HBCs during the process of knowledge construction. The content which is consistent with the learning outcomes should also be established and designed at this step.
The development step is where the researcher create and assemble the content of the programme assets created in the design phase [23]. This step is aimed to create the learning content that incorporates all the learning needs of the HBCs, and also to develop learning materials with learning outcomes that are relevant, legible and reader-friendly for the level of the HBCs. The structure and content of the training programme including learning activities, instructional and assessment strategies are aligned with developed learning outcomes.
Learning materials that covered all the SLO should be developed at this stage. During the development of the learning materials, the researcher should consider the competency level of the HBCs. The training materials should be drafted first and then submitted for evaluation for representativeness, appropriateness, completeness and importance to the research supervisors, psychologist, dietician and pharmacist before a final version can be concluded. The professional nurse, psychologist, dietician and Pharmacist should be included because they formed part of the implementation of this training programme.
The researcher should consider the following aspects during content development: the relevancy of the content included in the specific learning outcomes and objectives to achieve the SLO. The process of preparing the content should be based on the gaps identified during needs analysis and it matches the learning outcomes identified in the design step [24]. The content is divided in line with the SLO.
Learner-centred and problem-orientated strategies guide frameworks for accomplishing the learning outcomes. The instructional strategies should accommodate individual learner’s rates of learning and learning style based on reviewed literature. The following instructional strategies lecturer method, discussion, active learning, and cooperative learning/group discussions, role-plays and case-based exercises can be used [25].
The strategies for assessment should be developed at this stage to measure success gained from the developed programme Assessment should be undertaken regularly throughout the implementation of the training and there is an activity interlinked with all activities. The formative assessment strategies such as open-ended questions, group discussions, and peer assessment to assess the understanding and achievement of the learning outcomes during the workshop should be used. The assessment questions should be formulated at the end of every activity to assess comprehension of the content done concerning the learning outcomes of the specific unit.
The training materials including hard copies of training manuals should be printed for all the trainees and also the PowerPoint slides which covered all the SLO should be created.
A training program for HBCs who care for people with cardiovascular diseases including diabetes mellitus is delivered at this step. The subject matter included should be based on the previously developed material and the research articles. Efforts should be made to use the most recent information about DM. All the trainees should be provided with a hard copy of the training material to use before the training commences.
Dates for training should be identified and arrangements made with the managers of the HBC centres to release the HBCs for teaching. The training programme is at Level 4 of the National Qualification Framework (NQF) with 11/2 credits. The contact sessions for interactive facilitation with HBCs and different facilitators should be scheduled. Training should take place at a central venue away from the HBCs workplace to avoid disturbances during training and to enhance learning.
The evaluation of the training programme was guided by Kirkpatrick four-level evaluation model [26].
Reaction refers to the way in HBCs measure their satisfaction with the training [27]. Evaluation indicators should include training objectives, topic, content, venue, time, environment, facilitator’s knowledge and preparedness, training manuals, the benefits of training on the job and what HBCs think should have been included in the training. HBCs have to be asked to rate these indicators on a 3-point Likert scale. Additionally, HBCs should also be asked to write suggestions on the training in the comment box. HBCs can be given 45 minutes to complete the evaluation tools at the end of the session.
Learning in this study refers to the extent to which the attitudes of the HBCs change, their knowledge increases and their skills broadened post-implementation of training [27, 28]. The evaluation of learning measures what the participants have learned and gained from the training programme [29]. The questionnaire can be used to evaluate learning and it can be the major focus to evaluate knowledge of HBCs post-training compared with pre-training analysis.
The focus of the behaviour level was on the exploration of the extent to which the knowledge and skills acquired in the training were applied back at work [29]. The trainees should report on their changes in behaviour when they returned to work after attending the training.
Results level focused on the realisation of aimed objectives and change in productivity after training [29]. HBCs should be encouraged to report on the challenges they experienced in the application of knowledge and skills learned during training.
The conceptual framework has a vital purpose in creating situations to achieve the desired goals or outcomes [5]. Development of the training programme was necessary because its availability and training of HBCs will increase disease-specific knowledge. The suggested ideas of the survey list of Dickoff and others used successfully as a reasoning map to describe the conceptual framework for the development of the training programme for HBCs. The utilisation of ADDIE’s model of instructional design in the development of the training programme will benefit both the quality of the training content, teaching strategies, and assessments methods. The utilisation of ADDIE’s model of instructional design in the development of the training programme can benefit both the quality of the training content, teaching strategies, and assessments methods. The six elements of the survey list of Practice orientated theory form the base of the training programme development. The training programme that would be developed based on the elements of Practice Orientated Theory to provide benefits for both the HBCs and the people with cardiovascular diseases.
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Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. 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. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. 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He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. 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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"351159",title:"BSc.",name:"Kalum J.",middleName:null,surname:"Ost",slug:"kalum-j.-ost",fullName:"Kalum J. Ost",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"325029",title:"Dr.",name:"Prem Chand",middleName:null,surname:"Jain",slug:"prem-chand-jain",fullName:"Prem Chand Jain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Shiv Nadar University",country:{name:"India"}}},{id:"357275",title:"Dr.",name:"Thomas",middleName:null,surname:"Mih",slug:"thomas-mih",fullName:"Thomas Mih",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Buea",country:{name:"Cameroon"}}},{id:"305305",title:"Dr.",name:"Arturo Yosimar",middleName:null,surname:"Jaen-Cuellar",slug:"arturo-yosimar-jaen-cuellar",fullName:"Arturo Yosimar Jaen-Cuellar",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"305315",title:"Dr.",name:"David Alejandro",middleName:null,surname:"Elvira-Ortiz",slug:"david-alejandro-elvira-ortiz",fullName:"David Alejandro Elvira-Ortiz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"344374",title:"Dr.",name:"Manuel",middleName:null,surname:"Toledano-Ayala",slug:"manuel-toledano-ayala",fullName:"Manuel Toledano-Ayala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}}]}},subseries:{item:{id:"8",type:"subseries",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",hasOnlineFirst:!1,hasPublishedBooks:!0,annualVolume:11404,editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",slug:"adriano-andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",biography:"Dr. Adriano de Oliveira Andrade graduated in Electrical Engineering at the Federal University of Goiás (Brazil) in 1997. He received his MSc and PhD in Biomedical Engineering respectively from the Federal University of Uberlândia (UFU, Brazil) in 2000 and from the University of Reading (UK) in 2005. He completed a one-year Post-Doctoral Fellowship awarded by the DFAIT (Foreign Affairs and International Trade Canada) at the Institute of Biomedical Engineering of the University of New Brunswick (Canada) in 2010. Currently, he is Professor in the Faculty of Electrical Engineering (UFU). He has authored and co-authored more than 200 peer-reviewed publications in Biomedical Engineering. He has been a researcher of The National Council for Scientific and Technological Development (CNPq-Brazil) since 2009. He has served as an ad-hoc consultant for CNPq, CAPES (Coordination for the Improvement of Higher Education Personnel), FINEP (Brazilian Innovation Agency), and other funding bodies on several occasions. He was the Secretary of the Brazilian Society of Biomedical Engineering (SBEB) from 2015 to 2016, President of SBEB (2017-2018) and Vice-President of SBEB (2019-2020). He was the head of the undergraduate program in Biomedical Engineering of the Federal University of Uberlândia (2015 - June/2019) and the head of the Centre for Innovation and Technology Assessment in Health (NIATS/UFU) since 2010. He is the head of the Postgraduate Program in Biomedical Engineering (UFU, July/2019 - to date). He was the secretary of the Parkinson's Disease Association of Uberlândia (2018-2019). Dr. Andrade's primary area of research is focused towards getting information from the neuromuscular system to understand its strategies of organization, adaptation and controlling in the context of motor neuron diseases. His research interests include Biomedical Signal Processing and Modelling, Assistive Technology, Rehabilitation Engineering, Neuroengineering and Parkinson's Disease.",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,series:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343"},editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",slug:"hitoshi-tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",slug:"marcus-vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",slug:"ramana-vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},onlineFirstChapters:{paginationCount:7,paginationItems:[{id:"79909",title:"Cryopreservation Methods and Frontiers in the Art of Freezing Life in Animal Models",doi:"10.5772/intechopen.101750",signatures:"Feda S. 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Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. 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We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. 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Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. 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Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. 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