Search results for: MATLAB reference model

Authors: Samawi Zepure, Beck Christine, Gallagher Peg

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This community immersion employs the NLN Excellence Model which challenges nursing programs to create student-centered, interactive, and innovative experiences to prepare students for roles in providing high quality care, effective teaching, and leadership in the delivery of nursing services to individuals, families, and communities (NLN, 2006). Senior nursing students collaborate with ethnically and linguistically diverse participants at community-based sites and develop leadership roles of coordination of care linkage within the larger healthcare system, adherence, and self-care management. The immersion encourages students to develop competencies of the NLN Nursing Education Competencies Model (NLN, 2012), proposed to address fast changes in health care delivery, which include values of caring, diversity, and holism; and integrating concepts of context and environment, relationship, and teamwork. Students engage in critical thinking and leadership as they: 1) assess health/illness beliefs, values, attitudes, and practices, explore community resources, interview key informants, and collaborate with community participants to identify learning goals, 2) develop and implement appropriate holistic health promotion and disease prevention teaching interventions promoting continuity, sustainability, and innovation, 3) evaluate interventions through participant feedback and focus groups and, 4) reflect on the immersion experience and future professional role as advocate and citizen.

Keywords: quality of care, health of communities, students as leaders, health promotion

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Authors: Simiksha Balkissoon, Jerome Andrew, Bruce Sithole

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Approximately half of the wood processed in the Forestry, Timber, Pulp and Paper (FTPP) sector is accumulated as waste. The concept of a “green economy” encourages industries to employ revolutionary, transformative technologies to eliminate waste generation by exploring the development of new value chains. The transition towards an almost paperless world driven by the rise of digital media has resulted in a decline in traditional paper markets, prompting the FTTP sector to reposition itself and expand its product offerings by unlocking the potential of value-adding opportunities from renewable resources such as wood to generate revenue and mitigate its environmental impact. The production of valuable products from wood waste such as sawdust has been extensively explored in recent years. Wood components such as lignin, cellulose and hemicelluloses, which can be extracted selectively by chemical processing, are suitable candidates for producing numerous high-value products. In this study, a novel approach to produce high-value cellulose products, such as dissolving wood pulp (DWP), from sawdust was developed. DWP is a high purity cellulose product used in several applications such as pharmaceutical, textile, food, paint and coatings industries. The proposed approach demonstrates the potential to eliminate several complex processing stages, such as pulping and bleaching, which are associated with traditional commercial processes to produce high purity cellulose products such as DWP, making it less chemically energy and water-intensive. The developed process followed the path of experimentally designed lab tests evaluating typical processing conditions such as residence time, chemical concentrations, liquid-to-solid ratios and temperature, followed by the application of suitable purification steps. Characterization of the product from the initial stage was conducted using commercially available DWP grades as reference materials. The chemical characteristics of the products thus far have shown similar properties to commercial products, making the proposed process a promising and viable option for the production of DWP from sawdust.

Keywords: biomass, cellulose, chemical treatment, dissolving wood pulp

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Authors: Padmaja Kaja, Kiran Kumar Gellaboina

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A lion’s share of agricultural work is contributed by women in India as it is the case in many developing countries, yet women are not securing the pride as a farmer. Many policies are supporting women empowerment in India, especially in agriculture sector considering the importance of sustainable food security. However these policies many times failed to achieve the targeted results of mainstreaming gender. Implementing the principles of governance would lead to gender equality in agriculture. This paper deals with the social norms and obligations prevailed with reference to Indian context which abstain women from having resources. This paper is formulated by using primary research done in eight districts of Telangana and Andhra Pradesh states of India supported by secondary research. Making amendments to Hindu Succession Act in united Andhra Pradesh much prior to the positioning of the amended act in the whole country lead to a better land holding a share of women in Andhra Pradesh. The policies like registering government distributed lands in the name of women in the state also have an added value. However, the women participation in decision-making process in agriculture is limited in elite families when compared to socially under privileged families, further too it was higher in drought affected districts like Mahbubnagar in Telangana when compared to resource-rich East Godavari district in Andhra Pradesh. Though National Gender Resource Centre for Agriculture (NGRCA) at centre and Gender Cells in the states were established a decade ago, extension reach to the women farmers is still lagging behind. Capturing the strength of women self groups in India especially in Andhra Pradesh to link up with agriculture extension might improve the extension reach of women farmers. Maintenance of micro level women data sets, creating women farmers networks with government departments like agriculture, irrigation, revenue and formal credit institutes would result in good governance to mainstream gender in agriculture. Further to add that continuous monitoring and impact assessments of the programmes and projects for gender inclusiveness would reiterate the government efforts.

Keywords: food security, gender, governance, mainstreaming

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Authors: E. A. Ojoko, G. B. Umbugadu

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This study aims at describing the expenditure pattern of households on millet, maize and sorghum across income groups in Nasarawa State. A multi-stage sampling technique was used to select a sample size of 316 respondents for the study. The Almost Ideal Demand System (AIDS) model was adopted in this study. Results from the study shows that the average household size was five persons with dependency ratio of 52 %, which plays an important role on the household’s expenditure pattern by increasing the household budget share. On the average 82 % were male headed households with an average age of 49 years and 13 years of formal education. Results on expenditure share show that maize has the highest expenditure share of 38 % across the three income groups and that most of the price effects are significantly different from zero at 5 % significant level. This shows that the low price of maize increased its demand as compared to other cereals. Household size and age of household members are major factors affecting the demand for cereals in the study. This agrees with the fact that increased household population (size) will bring about increase consumption. The results on factors influencing preferences for cereal grains reveals that cooking quality and appearance (65.7 %) were the most important factors affecting the demand for maize in the study area. This study recommends that cereal crop production should be prioritized in government policies and farming activities that help to boost food security and alleviate poverty should be subsidized.

Keywords: expenditure pattern, AIDS model, budget share, price cereal grains and consumption

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Authors: Zsuzsa Szakaly

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Several constitutions have explicit or implicit eternity clauses in the European Union, their classic roles were analyzed so far, albeit there are new possibilities emerging in relation to the identity of the constitutions of the Member States. The aim of the study is to look at the practice of the Constitutional Courts of the Member States in detail regarding eternity clauses where limiting constitutional amendment has practical bearing, and to examine the influence of such practice on Europeanization. There are some states that apply explicit eternity clauses embedded in the text of the constitution, e.g., Italy, Germany, and Romania. In other states, the Constitutional Court 'unearthed' the implicit eternity clauses from the text of the basic law, e.g., Slovakia and Croatia. By using comparative analysis to examine the explicit or implicit clauses of the concerned constitutions, taking into consideration the new trends of the judicial opinions of the Member States and the fresh scientific studies, the main questions are: How to wield the double-edged sword of eternity clauses? To support European Integration or to support the sovereignty of the Member State? To help Europeanization or to act against it? Eternity clauses can easily find themselves between a rock and a hard place, the law of the European Union and the law of a Member State, with more possible interpretations. As more and more Constitutional Courts started to declare elements of their Member States’ constitutional identities, these began to interfere with the eternity clauses. Will this trend eventually work against Europeanization? As a result of the research, it can be stated that a lowest common denominator exists in the practice of European Constitutional Courts regarding eternity clauses. The chance of a European model and the possibility of this model influencing the status quo between the European Union and the Member States will be examined by looking at the answers these courts have found so far.

Keywords: constitutional court, constitutional identity, eternity clause, European Integration

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Authors: Manuela Gamba, Niki Mandolesi

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Teenagers today have little knowledge about how to move or play together. The adults who are part of sports culture must find an effective way to foster this essential ability. Our research in Italy uses a 'holistic model' based on fantasy literature to explore the relationships between the game identities and self-identities of young people and the achievement of psycho-motor, emotional and social well-being in the realms of sport and education. Physical activity projects were carried out in schools and extra-curricular associations in Rome, combining outdoor activities and distance learning. This holistic and malleable game model is inspired by fantasy accounts of the journeys taken in The Lord of Rings and Harry Potter books. We know that many have a lot of resistance to the idea of using fantasy and play as a pedagogical tool, but the results obtained in this experience are surprising. Our interventions and investigations focused on promoting self-esteem, awareness, a sense of belonging, social integration, cooperation, well-being, and informed decision making: a basis for healthy and effective citizenship. For teenagers, creative thinking is the right stimulus to involve and compare the story of characters to their own journey through social and self-reflective identity analysis. We observed how important it is to engage students emotionally as well as cognitively and that enabling them to play with identity through relationships with peers. There is a need today for a multidisciplinary synthesis of analog and digital values, especially in response to recent distance-living experiences. There is a need for a global reconceptualization of free time and nature in the human experience.

Keywords: awareness, creativity, identity, play

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Authors: Tsung Chin Wu, Yu Chen Tsai, Rhay Hung Weng, Weir Sen Lin

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In recent years, nursing staff’s lower job satisfaction has led to higher turnover rates, and high turnover rates not only cause medical institution costs to increase but also the quality of medical care to decrease. From the perspective of internal marketing, institution staffs are internal customers, and institutions should focus and meet the needs of staff, so that staff will strive to meet the needs of external customers and provide them with the required care. However, few previous studies have investigated the impact of internal staff satisfaction on external customers. Therefore, this study aimed to conduct job satisfaction surveys on internal staff to investigate the relationship between job satisfaction and quality of medical care through statistical analysis of the study results. The related study results may serve as a reference for healthcare managers. This study was conducted using a questionnaire and the subjects were nursing staff from four hospitals. A total of 600 questionnaires were distributed and 577 valid questionnaires were returned with a response rate of 96.1%. After collecting the data, the reliability and validity of the study variables were confirmed by confirmatory factor analysis. The impact of internal marketing and job satisfaction on turnover intention of nursing staff was analyzed using descriptive analysis, one-way ANOVA, Pearson correlation analysis and multiple regression analysis. The study results showed that there was a significant difference between nursing staff’s job title and ‘professional participation’ and ‘shifts’. There was a significant difference between salary and ‘shifts’ and ‘turnover intention’, as well as between marriage and ‘remuneration’ and ‘turnover intention’. A significant difference was found between professional advancement and ‘professional growth’ and ‘type of leave’, as well as between division of service and ‘shifts’ and ‘turnover intention’. Pearson correlation analysis revealed a significant negative correlation between turnover intention and ‘internal marketing’, ‘interaction’, ‘professional participation’, ‘grasp of environment’, ‘remuneration’ and ‘shifts’, meaning that the higher the satisfaction, the lower the turnover intention. It is recommended that hospitals establish a comprehensive internal marketing mechanism to enhance staff satisfaction and in turn, reduce intention to resign, and the key to increasing job satisfaction is by establishing effective methods of internal communication.

Keywords: internal marketing, job satisfaction, turnover intention, nursing staff

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Authors: M. Paraipan, V. M. Javadova, S. I. Tyutyunnikov

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The concept of energy amplifier or accelerator driven system (ADS) involves the use of a particle accelerator coupled with a nuclear reactor. The accelerated particle beam generates a supplementary source of neutrons, which allows the subcritical functioning of the reactor, and consequently a safe exploitation. The harder neutron spectrum realized ensures a better incineration of the actinides. The almost generalized opinion is that the optimal beam for ADS is represented by protons with energy around 1 GeV (gigaelectronvolt). In the present work, a systematic analysis of the energy gain for proton beams with energy from 0.5 to 3 GeV and ion beams from deuteron to neon with energies between 0.25 and 2 AGeV is performed. The target is an assembly of metallic U-Pu-Zr fuel rods in a bath of lead-bismuth eutectic coolant. The rods length is 150 cm. A beryllium converter with length 110 cm is used in order to maximize the energy released in the target. The case of a linear accelerator is considered, with a beam intensity of 1.25‧10¹⁶ p/s, and a total accelerator efficiency of 0.18 for proton beam. These values are planned to be achieved in the European Spallation Source project. The energy gain G is calculated as the ratio between the energy released in the target to the energy spent to accelerate the beam. The energy released is obtained through simulation with the code Geant4. The energy spent is calculating by scaling from the data about the accelerator efficiency for the reference particle (proton). The analysis concerns the G values, the net power produce, the accelerator length, and the period between refueling. The optimal energy for proton is 1.5 GeV. At this energy, G reaches a plateau around a value of 8 and a net power production of 120 MW (megawatt). Starting with alpha, ion beams have a higher G than 1.5 GeV protons. A beam of 0.25 AGeV(gigaelectronvolt per nucleon) ⁷Li realizes the same net power production as 1.5 GeV protons, has a G of 15, and needs an accelerator length 2.6 times lower than for protons, representing the best solution for ADS. Beams of ¹⁶O or ²⁰Ne with energy 0.75 AGeV, accelerated in an accelerator with the same length as 1.5 GeV protons produce approximately 900 MW net power, with a gain of 23-25. The study of the evolution of the isotopes composition during irradiation shows that the increase in power production diminishes the period between refueling. For a net power produced of 120 MW, the target can be irradiated approximately 5000 days without refueling, but only 600 days when the net power reaches 1 GW (gigawatt).

Keywords: accelerator driven system, ion beam, electrical power, energy gain

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Authors: Faranak Felfeliyan, Parvaneh Shokrani, Maryam Atarod

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Introduction Using electron beam is widespread in radiotherapy. The main criteria in radiation therapy is to irradiate the tumor volume with maximum prescribed dose and minimum dose to vital organs around it. Using abutting fields is common in radiotherapy. The main problem in using abutting fields is dose inhomogeneity in the junction region. Electron beam divergence and lateral scattering may lead to hot and cold spots in the junction region. One solution for this problem is using of a spoiler to broaden the penumbra and uniform dose in the junction region. The goal of this research was to compare titanium and aluminum effects as a spoiler for dose uniformity achievement in the junction region of oblique electron fields with Monte Carlo simulation. Dose uniformity in the junction region depends on density, scattering power, thickness of the spoiler and the angle between two fields. Materials and Methods In this study, Monte Carlo model of Siemens Primus linear accelerator was simulated for a 5 MeV nominal energy electron beam using manufacture provided specifications. BEAMnrc and EGSnrc user code were used to simulate the treatment head in electron mode (simulation of beam model). The resulting phase space file was used as a source for dose calculations for 10×10 cm2 field size at SSD=100 cm in a 30×30×45 cm3 water phantom using DOSXYZnrc user code (dose calculations). An automatic MP3-M water phantom tank, MEPHYSTO mc2 software platform and a Semi-Flex Chamber-31010 with sensitive vol­ume of 0.125 cm3 (PTW, Freiburg, Germany) were used for dose distribution measurements. Moreover, the electron field size was 10×10 cm2 and SSD=100 cm. Validation of devel­oped beam model was done by comparing the measured and calculated depth and lateral dose distributions (verification of electron beam model). Simulation of spoilers (using SLAB compo­nent module) placed at the end of the electron applicator, was done using previously vali­dated phase space file for a 5 MeV nominal energy and 10×10 cm2 field size (simulation of spoiler). An in-house routine was developed in order to calculate the combined isodose curves re­sulting from the two simulated abutting fields (calculation of dose distribution in abutting electron fields). Results Verification of the developed 5.9 MeV elec­tron beam model was done by comparing the calculated and measured dose distributions. The maximum percentage difference between calculated and measured PDD was 1%, except for the build-up region in which the difference was 2%. The difference between calculated and measured profile was 2% at the edges of the field and less than 1% in other regions. The effect of PMMA, aluminum, titanium and chromium in dose uniformity achievement in abutting normal electron fields with equivalent thicknesses to 5mm PMMA was evaluated. Comparing R90 and uniformity index of different materials, aluminum was chosen as the optimum spoiler. Titanium has the maximum surface dose. Thus, aluminum and titanium had been chosen to use for dose uniformity achievement in oblique electron fields. Using the optimum beam spoiler, junction dose decreased from 160% to 110% for 15 degrees, from 180% to 120% for 30 degrees, from 160% to 120% for 45 degrees and from 180% to 100% for 60 degrees oblique abutting fields. Using Titanium spoiler, junction dose decreased from 160% to 120% for 15 degrees, 180% to 120% for 30 degrees, 160% to 120% for 45 degrees and 180% to 110% for 60 degrees. In addition, penumbra width for 15 degrees, without spoiler in the surface was 10 mm and was increased to 15.5 mm with titanium spoiler. For 30 degrees, from 9 mm to 15 mm, for 45 degrees from 4 mm to 6 mm and for 60 degrees, from 5 mm to 8 mm. Conclusion Using spoilers, penumbra width at the surface increased, size and depth of hot spots was decreased and dose homogeneity improved at the junc­tion of abutting electron fields. Dose at the junction region of abutting oblique fields was improved significantly by using spoiler. Maximum dose at the junction region for 15⁰, 30⁰, 45⁰ and 60⁰ was decreased about 40%, 60%, 40% and 70% respectively for Titanium and about 50%, 60%, 40% and 80% for Aluminum. Considering significantly decrease in maximum dose using titanium spoiler, unfortunately, dose distribution in the junction region was not decreased less than 110%.

Keywords: abutting fields, electron beam, radiation therapy, spoilers

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Authors: A. O. Adebayo, G. A. Idowu, F. Odegbemi

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Investigations on the recovery of nickel from aqueous solution using 2-hydroxy-5-nonyl- acetophenone oxime (LIX-84I) impregnated on activated charcoal was carried out. The LIX-84I was impregnated onto the pores of dried activated charcoal by dry method and optimum conditions for different equilibrium parameters (pH, adsorbent dosage, extractant concentration, agitation time and temperature) were determined using a simulated solution of nickel. The kinetics and adsorption isotherm studies were also evaluated. It was observed that the efficiency of recovery with LIX-84I impregnated on charcoal was dependent on the pH of the aqueous solution as there was little or no recovery at pH below 4. However, as the pH was raised, percentage recovery increases and peaked at pH 5.0. The recovery was found to increase with temperature up to 60ºC. Also it was observed that nickel adsorbed onto the loaded charcoal best at a lower concentration (0.1M) of the extractant when compared with higher concentrations. Similarly, a moderately low dosage (1 g) of the adsorbent showed better recovery than larger dosages. These optimum conditions were used to recover nickel from the leachate of Ni-MH batteries dissolved with sulphuric acid, and a 99.6% recovery was attained. Adsorption isotherm studies showed that the equilibrium data fitted best to Temkin model, with a negative value of constant, b (-1.017 J/mol) and a high correlation coefficient, R² of 0.9913. Kinetic studies showed that the adsorption process followed a pseudo-second order model. Thermodynamic parameter values (∆G⁰, ∆H⁰, and ∆S⁰) showed that the adsorption was endothermic and spontaneous. The impregnated charcoal appreciably recovered nickel using a relatively smaller volume of extractant than what is required in solvent extraction. Desorption studies showed that the loaded charcoal is reusable for three times, and so might be economical for nickel recovery from waste battery.

Keywords: charcoal, impregnated, LIX-84I, nickel, recovery

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Authors: M. A. García, J. Vinolas, A. Hernando

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Steel is nowadays one of the most important structural materials because of its outstanding mechanical properties. Therefore, in order to look for a sustainable economic model and to optimize the use of extensive resources, new methods to monitor and prevent failure of steel-based facilities are required. The classical mechanical tests, as for instance building tasting, are invasive and destructive. Moreover, for facilities where the steel element is embedded, (as reinforced concrete) these techniques are directly non applicable. Hence, non-invasive monitoring techniques to prevent failure, without altering the structural properties of the elements are required. Among them, electromagnetic methods are particularly suitable for non-invasive inspection of the mechanical state of steel-based elements. The magnetoelastic coupling effects induce a modification of the electromagnetic properties of an element upon applied stress. Since most steels are ferromagnetic because of their large Fe content, it is possible to inspect their structure and state in a non-invasive way. We present here a distinct electromagnetic method for contactless evaluation of internal stress in steel-based elements. In particular, this method relies on measuring the magnetic induction between two coils with the steel specimen in between them. We found that the alteration of electromagnetic properties of the steel specimen induced by applied stress-induced changes in the induction allowed us to detect stress well below half of the elastic limit of the material. Hence, it represents an outstanding non-invasive method to prevent failure in steel-based facilities. We here describe the theoretical model, present experimental results to validate it and finally we show a practical application for detection of stress and inhomogeneities in train railways.

Keywords: magnetoelastic, magnetic induction, mechanical stress, steel

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Authors: Nipun Ansal

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People guard their beliefs and opinions with their lives. Beliefs that they’ve formed over a period of time, and can go to any lengths to defy, desist from, resist and negate any outward stimulus that has the potential to shake them. Cognitive dissonance is term used to describe it in theory. And every human being, in order to defend himself from cognitive dissonance applies 4 rings of defense viz. Selective Exposure, Selective Perception, Selective Attention, and Selective Retention. This paper is a discursive analysis on how the onslaught of social media, complete with its intrusive weaponry, has amorphized the external ring of defense: the selective exposure. The stimulus-response model of communication is one of the most inherent model that encompasses communication behaviours of children and elderly, individual and masses, humans and animals alike. The paper deliberates on how information bombardment through the uncontrollable channels of the social media, Facebook and Twitter in particular, have dismantled our outer sphere of exposure, leading users online to a state of constant dissonance, and thus feeding impulsive action-taking. It applies case study method citing an example to corroborate how knowledge generation has given in to the information overload and the effect it has on decision making. With stimulus increasing in number of encounters, opinion formation precedes knowledge because of the increased demand of participation and decrease in time for the information to permeate from the outer sphere of exposure to the sphere of retention, which of course, is through perception and attention. This paper discusses the challenge posed by this fleeting, stimulus rich, peer-dominated media on the traditional models of communication and meaning-generation.

Keywords: communication, discretion, exposure, social media, stimulus

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Authors: Zahidul Islam

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This study investigates the effectiveness of resourcing in post-disaster housing reconstruction with reference to Cyclones Sidr and Aila in Bangladesh. Through evaluating three key theories- Build Back Better approach, Balance Scorecard approach and Dynamic Competency theories, the synthesis of literature, and empirical fieldwork, this research develops a dynamic theoretical framework that moves the trajectory of post-disaster housing reconstruction towards the reconstruction of more resilient houses. The ultimate goal of any post-disaster housing reconstruction project is to provide quality houses and to achieve high levels of satisfaction for beneficiaries. However, post-disaster reconstruction projects often fail in their stated objectives; only 10-20% housing needs are met, with most houses constructed on a temporary rather than permanent basis. A number of scholars have argued that access to resources can significantly increase the capacity and capability of disaster victims to rebuild their lives, including the construction of new homes. This study draws on structured interviews of 285 villagers affected by cyclones to investigate the effectiveness of resourcing in rebuilding houses after Cyclone Sidr in 2007 and Cyclone Aila in 2009. Furthermore, semi-structured interviews were conducted with 20 key stakeholders in UNDP, Oxfam, government officials, and national and international NGOs. The results of this study show that recovery rate of cyclone resilient houses that can withstand cyclone is very low and majority of the population are still vulnerable. Furthermore, hierarchical regression of survey data and thematic analyses of qualitative data indicate that access to resources, level of education, quality of building materials and income generating activities of the respondents are critical for effective post-disaster recovery. Conversely, resource availability, lack of coordination among participant organisations, corruption and lack of access to appropriate land constituted significant obstacles to livelihood recovery. Finally, this study makes significant theoretical contributions to theories of post-disaster recovery by introducing new variables and measures for evaluating the quality and effectiveness of post-disaster housing.

Keywords: disaster, resourcing, housing, resilience

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Authors: Sylvana A. Vega, Cesar E. Huilinir, Carlos J. Gonzalez

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Co-digestion in anaerobic biodigesters is a technology improving hydrolysis by increasing methane generation. In the present study, the dimensional computational fluid dynamics (CFD) is numerically analyzed using Ansys Fluent software for agitation in a full-scale Continuous Stirred Tank Reactor (CSTR) biodigester during the co-digestion process. For this, a rheological study of the substrate is carried out, establishing rotation speeds of the stirrers depending on the microbial activity and energy ranges. The substrate is organic waste from industrial sources of sanitary water, butcher, fishmonger, and dairy. Once the rheological behavior curves have been obtained, it is obtained that it is a non-Newtonian fluid of the pseudoplastic type, with a solids rate of 12%. In the simulation, the rheological results of the fluid are considered, and the full-scale CSTR biodigester is modeled. It was coupling the second-order continuity differential equations, the three-dimensional Navier Stokes, the power-law model for non-Newtonian fluids, and three turbulence models: k-ε RNG, k-ε Realizable, and RMS (Reynolds Stress Model), for a 45° tilt vane impeller. It is simulated for three minutes since it is desired to study an intermittent mixture with a saving benefit of energy consumed. The results show that the absolute errors of the power number associated with the k-ε RNG, k-ε Realizable, and RMS models were 7.62%, 1.85%, and 5.05%, respectively, the numbers of power obtained from the analytical-experimental equation of Nagata. The results of the generalized Reynolds number show that the fluid dynamics have a transition-turbulent flow regime. Concerning the Froude number, the result indicates there is no need to implement baffles in the biodigester design, and the power number provides a steady trend close to 1.5. It is observed that the levels of design speeds within the biodigester are approximately 0.1 m/s, which are speeds suitable for the microbial community, where they can coexist and feed on the substrate in co-digestion. It is concluded that the model that more accurately predicts the behavior of fluid dynamics within the reactor is the k-ε Realizable model. The flow paths obtained are consistent with what is stated in the referenced literature, where the 45° inclination PBT impeller is the right type of agitator to keep particles in suspension and, in turn, increase the dispersion of gas in the liquid phase. If a 24/7 complete mix is considered under stirred agitation, with a plant factor of 80%, 51,840 kWh/year are estimated. On the contrary, if intermittent agitations of 3 min every 15 min are used under the same design conditions, reduce almost 80% of energy costs. It is a feasible solution to predict the energy expenditure of an anaerobic biodigester CSTR. It is recommended to use high mixing intensities, at the beginning and end of the joint phase acetogenesis/methanogenesis. This high intensity of mixing, in the beginning, produces the activation of the bacteria, and once reaching the end of the Hydraulic Retention Time period, it produces another increase in the mixing agitations, favoring the final dispersion of the biogas that may be trapped in the biodigester bottom.

Keywords: anaerobic co-digestion, computational fluid dynamics, CFD, net power, organic waste

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Authors: Juzhong Tan, William Kerr

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Conching is one critical procedure in chocolate processing, where special flavors are developed, and smooth mouse feel the texture of the chocolate is developed due to particle size reduction of cocoa mass and other additives. Therefore, determination of the particle size and volatile compounds profile of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products. Currently, precise particle size measurement is usually done by laser scattering which is expensive and inaccessible to small/medium size chocolate manufacturers. Also, some other alternatives, such as micrometer and microscopy, can’t provide good measurements and provide little information. Volatile compounds analysis of cocoa during conching, has similar problems due to its high cost and limited accessibility. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was inserted to a conching machine and was used to monitoring the volatile compound profile of chocolate during the conching. A model correlated volatile compounds profiles along with factors including the content of cocoa, sugar, and the temperature during the conching to particle size of chocolate particles by genetic programming was established. The model was used to predict the particle size reduction of chocolates with different cocoa mass to sugar ratio (1:2, 1:1, 1.5:1, 2:1) at 8 conching time (15min, 30min, 1h, 1.5h, 2h, 4h, 8h, and 24h). And the predictions were compared to laser scattering measurements of the same chocolate samples. 91.3% of the predictions were within the range of later scatting measurement ± 5% deviation. 99.3% were within the range of later scatting measurement ± 10% deviation.

Keywords: cocoa bean, conching, electronic nose, genetic programming

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Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

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The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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Authors: Shafait Hussain Ali

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Since its outbreak in China, the Covid_19 19 disease has been caused by the corona virus SARS N coyote 2. Italy was the first Western country to be severely affected, and the first country to take drastic measures to control the disease. In start of December 2019, the sudden outbreaks of the Coronary Virus Disease was caused by a new Corona 2 virus (SARS-CO2) of acute respiratory syndrome in china city Wuhan. The World Health Organization declared the epidemic a public health emergency of international concern on January 30, 2020,. On February 14, 2020, 49,053 laboratory-confirmed deaths and 1481 deaths have been reported worldwide. The threat of the disease has forced most of the governments to implement various control measures. Therefore it becomes necessary to analyze the Italian data very carefully, in particular to investigates and to find out the present condition and the number of infected persons in the form of positive cases, death, hospitalized or some other features of infected persons will clear in simple form. So used such a model that will clearly shows the real facts and figures and also understandable to every readable person which can get some real benefit after reading it. The model used must includes(total positive cases, current positive cases, hospitalized patients, death, recovered peoples frequency rates ) all features that explains and clear the wide range facts in very simple form and helpful to administration of that country.

Keywords: machine learning tools and techniques, rapid miner tool, Naive-Bayes algorithm, predictions

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Authors: Amirhossein Dodankeh, Hadi Dabiryan, Saeed Hamze

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Using fabrics to reinforce composites considerably leads to improved mechanical properties, including resistance to the impact load and the energy absorption of composites. Warp-knitted spacer fabrics (WKSF) are fabrics consisting of two layers of warp-knitted fabric connected by pile yarns. These connections create a space between the layers filled by pile yarns and give the fabric a three-dimensional shape. Today because of the unique properties of spacer fabrics, they are widely used in the transportation, construction, and sports industries. Polyurethane (PU) foams are commonly used as energy absorbers, but WKSF has much better properties in moisture transfer, compressive properties, and lower heat resistance than PU foam. It seems that the use of warp-knitted spacer fabric reinforced PU foam (WKSFRF) can lead to the production and use of composite, which has better properties in terms of energy absorption from the foam, its mold formation is enhanced, and its mechanical properties have been improved. In this paper, the energy absorption efficiency (EAE) of WKSFRF under low-velocity impact is investigated experimentally. The contribution of the effect of each of the structural parameters of the WKSF on the absorption of impact energy has also been investigated. For this purpose, WKSF with different structures such as two different thicknesses, small and large mesh sizes, and position of the meshes facing each other and not facing each other were produced. Then 6 types of composite samples with different structural parameters were fabricated. The physical properties of samples like weight per unit area and fiber volume fraction of composite were measured for 3 samples of any type of composites. Low-velocity impact with an initial energy of 5 J was carried out on 3 samples of any type of composite. The output of the low-velocity impact test is acceleration-time (A-T) graph with a lot deviation point, in order to achieve the appropriate results, these points were removed using the FILTFILT function of MATLAB R2018a. Using Newtonian laws of physics force-displacement (F-D) graph was drawn from an A-T graph. We know that the amount of energy absorbed is equal to the area under the F-D curve. Determination shows the maximum energy absorption is 2.858 J which is related to the samples reinforced with fabric with large mesh, high thickness, and not facing of the meshes relative to each other. An index called energy absorption efficiency was defined, which means absorption energy of any kind of our composite divided by its fiber volume fraction. With using this index, the best EAE between the samples is 21.6 that occurs in the sample with large mesh, high thickness, and meshes facing each other. Also, the EAE of this sample is 15.6% better than the average EAE of other composite samples. Generally, the energy absorption on average has been increased 21.2% by increasing the thickness, 9.5% by increasing the size of the meshes from small to big, and 47.3% by changing the position of the meshes from facing to non-facing.

Keywords: composites, energy absorption efficiency, foam, geometrical parameters, low-velocity impact, warp-knitted spacer fabric

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Juan Huang, Nanqu Huang, Jingshan Shi, Yu Qiu

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Objectives: There are pathophysiological connections between type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD), and research on drugs with hypoglycemic and beta-amyloid (Aβ)-clearing effects have great therapeutic potential for AD. Dendrobium nobile Lindl. Alkaloids (DNLA) as one of the active compounds of Dendrobium nobile Lindl. In this study, we attempted to verify the hypoglycemic effect and investigate the effects of DNLA on the amyloid precursor protein (APP) metabolic pathway of the hippocampus in db/db mice. Methods: 4-weeks-old male C57BL/KsJ mice were the control group. And the same age and sexuality db/db mice were: model, DNLA-L (20 mg/kg), DNLA-M (40 mg/kg), and DNLA-H (80 mg/kg). After, mice were treated with different concentrations of DNLA for 17 weeks. The fasting blood glucose (FBG) was detected by glucose oxidase assay every week from the 4th to last week. The protein expression of β-amyloid 1-42 (Aβ1-42), β-site amyloid precursor protein-cleaving enzyme 1 (BACE1), and APP were examined by Western blotting. Results: The concentration of FBG and the protein expression of Aβ1-42, BACE1, and APP were increased in the hippocampus of the model group. Moreover, DNLA not only significantly decreased the concentration of FBG but also reduced the protein expressions of Aβ1-42, BACE1 and APP in the hippocampus of db/db mice in a dose-dependent manner. Conclusions: DNLA can decrease the protein expressions of Aβ1-42 in the hippocampus of db/db mice, and the mechanism may be involved in the APP metabolic pathway.

Keywords: Alzheimer's disease, type 2 diabetes mellitus, β-site amyloid precursor protein-cleaving enzyme 1, traditional Chinese medicines, beta-amyloid

Procedia PDF Downloads 219

Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, Cassandra R. Rickertsen, Kamala Clark-Swanson, Scott A. Whitmire, Kristin R. Swanson

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Glioblastoma Multiforme (GBM), the most common primary brain tumor, often presents with hyperintensity on T2-weighted or T2-weighted fluid attenuated inversion recovery (T2/FLAIR) magnetic resonance imaging (MRI). This hyperintensity corresponds with vasogenic edema, however there are likely many infiltrating tumor cells within the hyperintensity as well. While MRIs do not directly indicate tumor cells, MRIs do reflect the microenvironmental water abnormalities caused by the presence of tumor cells and edema. The inherent heterogeneity and resulting MRI features of GBMs complicate assessing disease response. To understand how hyperintensity on T2/FLAIR MRI may correlate with edema in the extracellular space (ECS), a multi-compartmental MRI signal equation which takes into account tissue compartments and their associated volumes with input coming from a mathematical model of glioma growth that incorporates edema formation was explored. The reasonableness of two possible extracellular space schema was evaluated by varying the T2 of the edema compartment and calculating the possible resulting T2s in tumor and peripheral edema. In the mathematical model, gliomas were comprised of vasculature and three tumor cellular phenotypes: normoxic, hypoxic, and necrotic. Edema was characterized as fluid leaking from abnormal tumor vessels. Spatial maps of tumor cell density and edema for virtual tumors were simulated with different rates of proliferation and invasion and various ECS expansion schemes. These spatial maps were then passed into a multi-compartmental MRI signal model for generating simulated T2/FLAIR MR images. Individual compartments’ T2 values in the signal equation were either from literature or estimated and the T2 for edema specifically was varied over a wide range (200 ms – 9200 ms). T2 maps were calculated from simulated images. T2 values based on simulated images were evaluated for regions of interest (ROIs) in normal appearing white matter, tumor, and peripheral edema. The ROI T2 values were compared to T2 values reported in literature. The expanding scheme of extracellular space is had T2 values similar to the literature calculated values. The static scheme of extracellular space had a much lower T2 values and no matter what T2 was associated with edema, the intensities did not come close to literature values. Expanding the extracellular space is necessary to achieve simulated edema intensities commiserate with acquired MRIs.

Keywords: extracellular space, glioblastoma multiforme, magnetic resonance imaging, mathematical modeling

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Authors: D. Avila

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The tourism industry is a phenomenon that has become a growing presence in international socio-economic dynamics, which in most cases exceeds the control parameters in the various environmental regulations and sustainability of existing resources. Because of this, the effects on the natural environment at the regional and national levels represent a challenge, for which a number of strategies are necessary to minimize the environmental impact generated by the occupation of the territory. The hotel tourist building and sustainable development in the coastal zone, have an important impact on the environment and on the physical and psychological health of the inhabitants. Environmental quality associated with the comfort of humans to the sustainable development of natural resources; applied to the hotel architecture this concept involves the incorporation of new demands on all of the constructive process of a building, changing customs of developers and users. The methodology developed provides an initial analysis to determine and rank the different tourist buildings, with the above it will be feasible to establish methods of study and environmental impact assessment. Finally, it is necessary to establish an overview regarding the best way to implement tourism development on the coast, containing guidelines to improve and protect the natural environment. This paper analyzes the parameters and strategies to reduce environmental impacts derived from deployments tourism on the coast, through a series of recommendations towards sustainability, in the context of the Bahia de Banderas, Puerto Vallarta, Jalisco. The environmental impact caused by the implementation of tourism development, perceived in a coastal environment, forcing a series of processes, ranging from the identification of impacts, prediction and evaluation of them. For this purpose are described below, different techniques and valuation procedures: Identification of impacts. Methods for the identification of damage caused to the environment pursue general purpose to obtain a group of negative indicators that are subsequently used in the study of environmental impact. There are several systematic methods to identify the impacts caused by human activities. In the present work, develops a procedure based and adapted from the Ministry of works public urban reference in studies of environmental impacts, the representative methods are: list of contrast, arrays, and networks, method of transparencies and superposition of maps.

Keywords: environmental impact, physical health, sustainability, tourist building

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).

Keywords: intrusion detection, architectures, characteristic, tools, security, web server

Procedia PDF Downloads 401

Authors: Mozhdeh Khalili Kordabadi

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. By adopting these strategies, the textile industry can contribute to a more sustainable and environmentally friendly future. Introduction: Textiles, particularly clothing, are essential to human existence. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion: The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension.

Procedia PDF Downloads 76

Authors: Lahcen Daoudi, Fatima Zahra Omdi, Abldelali Gourfi

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In Morocco, as in most Mediterranean countries, water scarcity is a common situation because of low and unevenly distributed rainfall. The expansions of irrigated lands, as well as the growth of urban and industrial areas and tourist resorts, contribute to an increase of water demand. Therefore in the 1960s Morocco embarked on an ambitious program to increase the number of dams to boost water retention capacity. However, the decrease in the capacity of these reservoirs caused by sedimentation is a major problem; it is estimated at 75 million m3/year. Dams and reservoirs became unusable for their intended purposes due to sedimentation in large rivers that result from soil erosion. Soil erosion presents an important driving force in the process affecting the landscape. It has become one of the most serious environmental problems that raised much interest throughout the world. Monitoring soil erosion risk is an important part of soil conservation practices. The estimation of soil loss risk is the first step for a successful control of water erosion. The aim of this study is to estimate the soil loss risk and its spatial distribution in the different fields of Morocco and to prioritize areas for soil conservation interventions. The approach followed is the Revised Universal Soil Loss Equation (RUSLE) using remote sensing and GIS, which is the most popular empirically based model used globally for erosion prediction and control. This model has been tested in many agricultural watersheds in the world, particularly for large-scale basins due to the simplicity of the model formulation and easy availability of the dataset. The spatial distribution of the annual soil loss was elaborated by the combination of several factors: rainfall erosivity, soil erodability, topography, and land cover. The average annual soil loss estimated in several basins watershed of Morocco varies from 0 to 50t/ha/year. Watersheds characterized by high-erosion-vulnerability are located in the North (Rif Mountains) and more particularly in the Central part of Morocco (High Atlas Mountains). This variation of vulnerability is highly correlated to slope variation which indicates that the topography factor is the main agent of soil erosion within these basin catchments. These results could be helpful for the planning of natural resources management and for implementing sustainable long-term management strategies which are necessary for soil conservation and for increasing over the projected economic life of the dam implemented.

Keywords: soil loss, RUSLE, GIS-remote sensing, watershed, Morocco

Procedia PDF Downloads 444

Authors: Achirawatt Tungsombatsanti, Toansakul Santiboon, Kamon Ponkham

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Strategies of the STEM education was aimed to prepare of an interdisciplinary and applied approach for the instructional of science, technology, engineering, and mathematics in an integrated students for enhancing engagement of their science skills to the Problem-Based Learning (PBL) method in Borabu School with a sample consists of 80 students in 2 classes at the 12th grade level of their learning achievements on electromagnetic issue. Research administrations were to separate on two different instructional model groups, the 40-experimental group was designed with the STEM instructional experimenting preparation and induction in a 40-student class and the controlling group using the PBL was designed to students identify what they already know, what they need to know, and how and where to access new information that may lead to the resolution of the problem in other class. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) The term scaling was applied to the attempts to measure the attitude objectively with the TOPRA was used to assess students’ perceptions of their science attitude toward physics. Comparisons between pretest and posttest techniques were assessed students’ learning achievements on each their outcomes from each instructional model, differently. The results of these findings revealed that the efficiency of the PLB and the STEM based on criteria indicate that are higher than the standard level of the 80/80. Statistically, significant of students’ learning achievements to their later outcomes on the controlling and experimental physics class groups with the PLB and the STEM instructional designs were differentiated between groups at the .05 level, evidently. Comparisons between the averages mean scores of students’ responses to their instructional activities in the STEM education method are higher than the average mean scores of the PLB model. Associations between students’ perceptions of their physics classes to their attitudes toward physics, the predictive efficiency R2 values indicate that 77%, and 83% of the variances in students’ attitudes for the PLEI and the TOPRA in physics environment classes were attributable to their perceptions of their physics PLB and the STEM instructional design classes, consequently. An important of these findings was contributed to student understanding of scientific concepts, attitudes, and skills as evidence with STEM instructional ought to higher responding than PBL educational teaching. Statistically significant between students’ learning achievements were differentiated of pre and post assessments which overall on two instructional models.

Keywords: learning instructional managements, problem-based learning, STEM education, method, enhancement, students learning achievements, science attitude, physics classes

Procedia PDF Downloads 218

Authors: Camilo Souza, Lidia Melo, Fernanda Terra, Francisco Caio, Marcelo Reis

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SIDIA is a research and development (R&D) institute that belongs to Samsung’s global software development process. The SIDIA’s Model Team (MT) is a part of Samsung’s Mobile Division Area, which is responsible for the development of Android releases embedded in Samsung mobile devices. Basically, in this software development process, the kickoff occurs in some strategic countries (e.g., South Korea) where some software requirements are applied and the initial software tests are performed. When the software achieves a more mature level, a new branch is derived, and the development continues in subsidiaries from other strategic countries (e.g., SIDIA-Brazil). However, even in the newly created branches, there are several interactions between developers from different nationalities in order to fix bugs reported during test activities, apply some specific requirements from partners and develop new features as well. Despite the GSD strategy contributes to improving software development, some challenges are also introduced as well. In this paper, we share the initial results about the application of the failure modes and effect analysis (FMEA) concept in the software development process followed by the SIDIA’s model team. The main goal was to identify and mitigate the process potential failures through the application of recommended actions. The initial results show that the application of the FMEA concept allows us to identify the potential failures in our GSD process as well as to propose corrective actions to mitigate them. Finally, FMEA encouraged members of different teams to take actions that contribute to improving our GSD process.

Keywords: global software development, potential failures, FMEA, recommended actions

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Authors: Sahar Essa, Hussain A. Safar, Raj Raghupathy

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Human cytomegalovirus (CMV) continues to be a source of severe complications in immunologically immature and immunocompromised hosts. Effective CMV vaccines that help diminish CMV disease in transplant patients and avoid congenital infection are of great importance. Though the exact roles of defense mechanisms are unidentified, viral-specific antibodies and cytokine responses are known to be involved in controlling CMV infections. CMV envelope glycoprotein B (UL55/gB), matrix proteins (UL83/pp65, UL99/pp28, UL32/pp150), and assembly protein UL80a/pp38 are known to be targets of antiviral immune responses. We immunized mice intraperitoneally with these five CMV-related proteins (commercial) for their ability to induce specific antibody responses (in-house immunoassay) and cytokine production (commercial assay) in a mouse model. We observed a significant CMV-antigen-specific antibody response to pp38 and pp65 (E/C ˃2.0, p˂0.001). Mice immunized with pp38 had significantly higher concentrations of GM-CSF, IFN-α, IL-2 IL-4, IL-5, and IL-17A (p˂0.05). Mice immunized with pp65 showed significantly higher concentrations of GM-CSF, IFN-γ, IL-2 IL-4, IL-10, IL-12, IL-17A, and TNF-α. Th1 to Th2 cytokines ratios revealed a Th1 cytokine bias in mice immunized with pp38, pp65, pp150, and gB. We suggest that stimulation with multiple CMV-related proteins, which include pp38, pp65, and gB antigens, will allow both humoral and cellular immune responses to be efficiently activated, thus serving as appropriate CMV antigens for future vaccines.

Keywords: cytomegalovirus, UL99/pp28, UL80a/pp38, UL83/pp65, UL32/pp150, UL55/gB, CMV-antigen-specific antibody, CMV antigen-specific cytokine responses

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Authors: Mayowa Adeyeye

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This study was conducted to investigate the psychological variables motivating sport participation and involvement among student-athletes of tertiary institutions in south-west Nigeria. One thousand three hundred and fifty (N-1350) student-athletes were randomly selected in all sports from nine tertiary institutions in south-west Nigeria. These tertiary institutions include University of Lagos, Lagos State University, Obafemi Awolowo University, Osun State University, University of Ibadan, University of Agriculture Abeokuta, Federal University of Technology Akungba, University of Ilorin, and Kwara State University. The descriptive survey research method was adopted while a self developed validated likert type questionnaire named Sport Participation Scale (SPS) was used to elicit opinion from respondents. The test-retest reliability value obtained for the instrument, using Pearson Product Moment Correlation Co-efficient was 0.96. Out of the one thousand three hundred and fifty (N-1350) questionnaire administered, only one thousand two hundred and five (N-1286) were correctly filled, coded and analysed using inferential statistics of Chi-Square (X2) while all the tested hypotheses were set at .05 alpha level. Based on the findings of this study, the result revealed that several psychological factors influence student athletes to continue participation in sport, which includes love for the game, famous athletes as role model and family support. However, the analysis further revealed that the stipends the student-athletes get from their universities have no influence on their participation and involvement in sport.

Keywords: sport participation, involvement, student-athletes, role model, family, peer

Procedia PDF Downloads 408