Search results for: index structural equation model

Authors: Anna Zoli

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In recent years, we have been witnessing a surge of locally-sustained communities committed to promoting new ethical economies while fostering the full participation of socially excluded groups and individuals into the labor market. This article explores the practices of a particular community development model, Transition Towns, as implemented in Monteveglio, Italy. Data were gathered throughout two years long ethnography, using multiple qualitative techniques, namely participant observation, document analysis, and semi-structured interviews. Data were analyzed triangulating from multiple sources of evidence and using hybrid thematic analysis. Major findings show that Transition Town movement works on two main axes, vertical and horizontal. Vertical transition involves interactions with an overreaching political, economic, and social structure which is not transitioning, and therefore poses structural resistances to the transformative social change fostered by the TT. Conversely, horizontal transition involves intragroup dynamics within the communal relational and geographical spaces and therefore poses process resistances between 'self and others' to the interpersonal communication between TT members. The study concludes that a psychosocial approach to community development is essential in order to conflate macro-social dynamics and psychological processes that may obstacle grassroots social movements to thrive. Skills from psychosocial disciplines are a unique set that could facilitate communication and relational processes for community development, and ultimately enabling social change.

Keywords: community development, grassroots social movements, psychosocial approaches, Transition Towns

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Authors: Stephen M. Magu

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The 9/11 and Christmas bombing attacks in the United States are mostly associated with the inability of intelligence agencies to connect dots based on intelligence that was already available. The 1998, 2002, 2013 and several 2014 terrorist attacks in Kenya, on the other hand, are probably driven by a completely different dynamic: the invisible hand of corruption. The World Bank and Transparency International annually compute the Worldwide Governance Indicators and the Corruption Perception Index respectively. What perhaps is not adequately captured in the corruption metrics is the impact of corruption on terrorism. The World Bank data includes variables such as the control of corruption, (estimates of) government effectiveness, political stability and absence of violence/terrorism, regulatory quality, rule of law and voice and accountability. TI's CPI does not include measures related to terrorism, but it is plausible that there is an expectation of some terrorism impact arising from corruption. This paper, by examining the incidence, frequency and total number of terrorist attacks that have occurred especially since 1990, and further examining the specific cases of Kenya and Nigeria, argues that in addition to having major effects on governance, corruption has an even more frightening impact: that of facilitating and/or violating security mechanisms to the extent that foreign nationals can easily obtain identification that enables them to perpetuate major events, targeting powerful countries' interests in countries with weak corruption-fighting mechanisms. The paper aims to model interactions that demonstrate the cost/benefit analysis and agents' rational calculations as being non-rational calculations, given the ultimate impact. It argues that eradication of corruption is not just a matter of a better business environment, but that it is implicit in national security, and that for anti-corruption crusaders, this is an argument more potent than the economic cost / cost of doing business argument.

Keywords: corruption, global south, identification, passports, terrorism

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Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

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In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

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Authors: Awais Ahmad, Mostafa Muhammad Selim, Ali Abdullah Alderfasi

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Water limitation is undoubtedly a critical environmental constraint limiting the crop production under arid and semiarid areas. Mung bean is susceptible to both drought and water logging stresses. Therefore, present study was conducted to assess the water deficit stress consequences of yield components and water use efficiency in Mung bean. A field experiment was conducted at Educational Farm, Crop Production Department, College of Food and Agricultural Sciences, Kind Saud University, Saudi Arabia. Trail comprised of four irrigation levels — total amount of irrigation divided into irrigation intervals — (3, 5, 7 and 9 days interval) and three Mung bean genotypes; Kawmay-1, VC-2010 and King from Egypt, Thailand and China respectively. Experiment was arranged under split plot design having irrigation as main while genotype as subplot treatment, and replicated thrice. Plant height, 100 seed weight, biological yield, seed yield, harvest index and water use efficiency were recorded at harvesting. Results revealed that decrease in irrigation have significantly hampered all the studied parameters. Mung bean genotypes have also shown significant differences for all parameters, whereas irrigation genotype interaction was highly significant for seed yield, harvest index and water use efficiency (WUE) while it was significant for biological yield. Plant height and 100 seed weight were recorded non-significant for irrigation genotype interaction. A statistically highly significant correlation among recorded parameters was observed. Minimum irrigation interval (3 days) significantly produced maximum values while VC-2010 comparatively performed better under low irrigation levels. It was concluded that Mung bean may be successfully adopted under Saudi Arabian climate but it needs high water or frequent irrigation, however, genotypic differences are a hope to develop some improved varieties with high water use efficiency.

Keywords: mung bean, irrigation intervals, water use efficiency, genotypes, yield

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Authors: Ankur Chaudhuri, Sibani Sen Chakraborty

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In human, glutaminyl cyclase activity is highly abundant in neuronal and secretory tissues and is preferentially restricted to hypothalamus and pituitary. The N-terminal modification of β-amyloids (Aβs) peptides by the generation of a pyro-glutamyl (pGlu) modified Aβs (pE-Aβs) is an important process in the initiation of the formation of neurotoxic plaques in Alzheimer’s disease (AD). This process is catalyzed by glutaminyl cyclase (QC). The expression of QC is characteristically up-regulated in the early stage of AD, and the hallmark of the inhibition of QC is the prevention of the formation of pE-Aβs and plaques. A computer-aided drug design (CADD) process was employed to give an idea for the designing of potentially active compounds to understand the inhibitory potency against human glutaminyl cyclase (QC). This work elaborates the ligand-based and structure-based pharmacophore exploration of glutaminyl cyclase (QC) by using the known inhibitors. Three dimensional (3D) quantitative structure-activity relationship (QSAR) methods were applied to 154 compounds with known IC50 values. All the inhibitors were divided into two sets, training-set, and test-sets. Generally, training-set was used to build the quantitative pharmacophore model based on the principle of structural diversity, whereas the test-set was employed to evaluate the predictive ability of the pharmacophore hypotheses. A chemical feature-based pharmacophore model was generated from the known 92 training-set compounds by HypoGen module implemented in Discovery Studio 2017 R2 software package. The best hypothesis was selected (Hypo1) based upon the highest correlation coefficient (0.8906), lowest total cost (463.72), and the lowest root mean square deviation (2.24Å) values. The highest correlation coefficient value indicates greater predictive activity of the hypothesis, whereas the lower root mean square deviation signifies a small deviation of experimental activity from the predicted one. The best pharmacophore model (Hypo1) of the candidate inhibitors predicted comprised four features: two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature. The Hypo1 was validated by several parameters such as test set activity prediction, cost analysis, Fischer's randomization test, leave-one-out method, and heat map of ligand profiler. The predicted features were then used for virtual screening of potential compounds from NCI, ASINEX, Maybridge and Chembridge databases. More than seven million compounds were used for this purpose. The hit compounds were filtered by drug-likeness and pharmacokinetics properties. The selective hits were docked to the high-resolution three-dimensional structure of the target protein glutaminyl cyclase (PDB ID: 2AFU/2AFW) to filter these hits further. To validate the molecular docking results, the most active compound from the dataset was selected as a reference molecule. From the density functional theory (DFT) study, ten molecules were selected based on their highest HOMO (highest occupied molecular orbitals) energy and the lowest bandgap values. Molecular dynamics simulations with explicit solvation systems of the final ten hit compounds revealed that a large number of non-covalent interactions were formed with the binding site of the human glutaminyl cyclase. It was suggested that the hit compounds reported in this study could help in future designing of potent inhibitors as leads against human glutaminyl cyclase.

Keywords: glutaminyl cyclase, hit lead, pharmacophore model, simulation

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Authors: Shen Jian, Hu Jie, Qi Jin, Liu Wei Jie, Chen Ji Yi, Peng Ying Hong

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In order to settle the problem of acquiring case in biological related to design problems, a biometrics instance acquisition method based on text mining is presented. Through the construction of corpus text vector space and knowledge mining, the feature selection, similarity measure and case retrieval method of text in the field of biology are studied. First, we establish a vector space model of the corpus in the biological field and complete the preprocessing steps. Then, the corpus is retrieved by using the vector space model combined with the functional keywords to obtain the biological domain examples related to the design problems. Finally, we verify the validity of this method by taking the example of text.

Keywords: text mining, vector space model, feature selection, biologically inspired design

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Authors: Ayelet Siman-Tov, Shlomo Kaniel

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Objectives: The research validates a multivariate model that predicts parental adjustment to coping successfully with an autistic child. The model comprises four elements: parental stress, parental resources, parental adjustment and the child's autism symptoms. Background and aims: The purpose of the current study is the construction and validation of a model for the adjustment of parents and a child with autism. The suggested model is based on theoretical views on stress and links personal resources, stress, perception, parental mental health and quality of marriage and child adjustment with autism. The family stress approach focuses on the family as a system made up of a dynamic interaction between its members, who constitute interdependent parts of the system, and thus, a change in one family member brings about changes in the processes of the entire family system. From this perspective, a rise of new demands in the family and stress in the role of one family member affects the family system as a whole. Materials and methods: 176 parents of children aged between 6 to 16 diagnosed with ASD answered several questionnaires measuring parental stress, personal resources (sense of coherence, locus of control, social support), adjustment (mental health and marriage quality) and the child's autism symptoms. Results: Path analysis showed that a sense of coherence, internal locus of control, social support and quality of marriage increase the ability to cope with the stress of parenting an autistic child. Directions for further research are suggested.

Keywords: stress, adjustment, resources, Autism, parents, coherence

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Authors: Jyoti Sahu, Vinay A. Juvekar

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Electrolytes are often used to bring about salting-in and salting-out of organic molecules and polymers (e.g. polyethylene glycols/proteins) from the aqueous solutions. For quantification of these phenomena, a thermodynamic model which can accurately predict activity coefficient of electrolyte as a function of temperature is needed. The thermodynamics models available in the literature contain a large number of empirical parameters. These parameters are estimated using lower/upper critical solution temperature of the solution in the electrolyte/organic molecule at different temperatures. Since the number of parameters is large, inaccuracy can bethe creep in during their estimation, which can affect the reliability of prediction beyond the range in which these parameters are estimated. Cloud point of solution is related to its free energy through temperature and composition derivative. Hence, the Cloud point measurement can be used for accurate estimation of the temperature and composition dependence of parameters in the model for free energy. Hence, if we use a two pronged procedure in which we first use cloud point of solution to estimate some of the parameters of the thermodynamic model and determine the rest using osmotic coefficient data, we gain on two counts. First, since the parameters, estimated in each of the two steps, are fewer, we achieve higher accuracy of estimation. The second and more important gain is that the resulting model parameters are more sensitive to temperature. This is crucial when we wish to use the model outside temperatures window within which the parameter estimation is sought. The focus of the present work is to prove this proposition. We have used electrolyte (NaCl/Na2CO3)-water-organic molecule (Iso-propanol/ethanol) as the model system. The model of Robinson-Stokes-Glukauf is modified by incorporating the temperature dependent Flory-Huggins interaction parameters. The Helmholtz free energy expression contains, in addition to electrostatic and translational entropic contributions, three Flory-Huggins pairwise interaction contributions viz., and (w-water, p-polymer, s-salt). These parameters depend both on temperature and concentrations. The concentration dependence is expressed in the form of a quadratic expression involving the volume fractions of the interacting species. The temperature dependence is expressed in the form .To obtain the temperature-dependent interaction parameters for organic molecule-water and electrolyte-water systems, Critical solution temperature of electrolyte -water-organic molecules is measured using cloud point measuring apparatus The temperature and composition dependent interaction parameters for electrolyte-water-organic molecule are estimated through measurement of cloud point of solution. The model is used to estimate critical solution temperature (CST) of electrolyte water-organic molecules solution. We have experimentally determined the critical solution temperature of different compositions of electrolyte-water-organic molecule solution and compared the results with the estimates based on our model. The two sets of values show good agreement. On the other hand when only osmotic coefficients are used for estimation of the free energy model, CST predicted using the resulting model show poor agreement with the experiments. Thus, the importance of the CST data in the estimation of parameters of the thermodynamic model is confirmed through this work.

Keywords: concentrated electrolytes, Debye-Hückel theory, interaction parameters, Robinson-Stokes-Glueckauf model, Flory-Huggins model, critical solution temperature

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

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Authors: Karthiyayini Nagarajan, P. V. RamaKrishna

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Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar(SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System(lab bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench

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Authors: Lei Chen, Jian Jiao, Tingdi Zhao

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Failures of automotive electric/electronic systems, which are universally considered to be safety-critical and software-intensive, may cause catastrophic accidents. Analysis and verification of failures in these kinds of systems is a big challenge with increasing system complexity. Model-checking is often employed to allow formal verification by ensuring that the system model conforms to specified safety properties. The system-level effects of failures are established, and the effects on system behavior are observed through the formal verification. A hazard analysis technique, called Systems-Theoretic Process Analysis, is capable of identifying design flaws which may cause potential failure hazardous, including software and system design errors and unsafe interactions among multiple system components. This paper provides a concept on how to use model-checking integrated with Systems-Theoretic Process Analysis to perform failure analysis and verification of automotive electric/electronic systems. As a result, safety requirements are optimized, and failure propagation paths are found. Finally, an automotive electric/electronic system case study is used to verify the effectiveness and practicability of the method.

Keywords: failure analysis and verification, model checking, system-theoretic process analysis, automotive electric/electronic system

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Authors: Ehsan Sadie

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Today, the cost of repair and maintenance of structures is very important and by studying the behavior of reinforced concrete structures Will become specified several factors such as : Design and calculation errors, lack of proper implementation of structural changes, the damage caused by the introduction of random loads, concrete corrosion and environmental conditions reduce durability of the structures . Meanwhile building codes alteration also cause changes in the assessment and review of the design and structure rather if necessary will be improved and strengthened in the future.

Keywords: concrete building , expandable cement, honeycombed surface , reinforcement corrosion

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Authors: Ali Fallah Yeznabad, Mohammad H. Baziar, Alireza Saedi Azizkandi

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Rafts may be used when a low bearing capacity exists underneath the foundation and may be combined by piles in some special circumstances; such as to reduce settlements or high groundwater to control buoyancy. From structural point of view, these piles could be both connected or disconnected from the raft and are to be classified as Piled Rafts (PR) or Disconnected Piled Rafts (DPR). Although the researches about the behavior of piled rafts subjected to vertical loading is really extensive, in the context of dynamic load and earthquake loading, the studies are very limited. In this study, to clarify these foundations’ performance under dynamic loading, series of Shaking Table tests have been performed. The square raft and four piles in connected and disconnected configurations were used in dry silica sand and the model was experimented using a shaking table under 1-g conditions. Moreover, numerical investigation using finite element software have been conducted to better understand the differences and advantages. Our observations demonstrates that in connected Piled Rafts piles have to bear greater amount of moment in their upper parts, however this moments are approximately 40% lower in disconnected piled rafts in the same conditions and loading. Considering the Rafts’ lateral movement which be of crucial importance in foundations performance evaluation, connected piled rafts show much better performance with about 30% less lateral movement. Further, it was observed on confirmed both through laboratory tests and numerical analysis, that adding the superstructure over the piled raft foundation the raft separates from the soil and it significantly increases rocking of the raft which was observed to be the main reason of increase in piles’ moments under superstructure interaction with the foundation.

Keywords: Piled Rafts (PR), Disconnected Piled Rafts (DPR), dynamic loading, shaking table, seismic performance

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Authors: Gak-Gyu Kim, Won Il Jung

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According to a remarkable development of science and technology, function and role of the system of engineering fields has recently been diversified. The system has become increasingly more complex and precise, and thus, system designers intended to maximize reliability concentrate more effort at the design stage. This study deals with the reliability redundancy optimization problem (RROP) for k-out-of-n: G system configuration with cold standby and warm standby components. This paper further intends to present the optimal mathematical model through which the following three elements of (i) multiple components choices, (ii) redundant components quantity and (iii) the choice of redundancy strategies may be combined in order to maximize the reliability of the system. Therefore, we focus on the following three issues. First, we consider RROP that there exists warm standby state as well as cold standby state of the component. Second, as eliminating an approximation approach of the previous RROP studies, we construct a precise model for system reliability. Third, given transition time when the state of components changes, we present not simply a workable solution but the advanced method. For the wide applicability of RROPs, moreover, we use absorbing continuous time Markov chain and matrix analytic methods in the suggested mathematical model.

Keywords: RROP, matrix analytic methods, k-out-of-n: G system, MTTF, absorbing continuous time Markov Chain

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Authors: Ella Tyuryumina, Alexey Neznanov

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This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

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Authors: Rituparna Pal, Faiz Ahmed

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Neighbourhood energy efficiency is a newly emerged term to address the quality of urban strata of built environment in terms of various covariates of sustainability. The concept of sustainability paradigm in developed nations has encouraged the policymakers for developing urban scale cities to envision plans under the aegis of urban scale sustainability. The concept of neighbourhood energy efficiency is realized a lot lately just when the cities, towns and other areas comprising this massive global urban strata have started facing a strong blow from climate change, energy crisis, cost hike and an alarming shortfall in the justice which the urban areas required. So this step of urban sustainability can be easily referred more as a ‘Retrofit Action’ which is to cover up the already affected urban structure. So even if we start energy efficiency for existing cities and urban areas the initial layer remains, for which a complete model of urban sustainability still lacks definition. Urban sustainability is a broadly spoken off word with end number of parameters and policies through which the loop can be met. Out of which neighbourhood energy efficiency can be an integral part where the concept and index of neighbourhood scale indicators, block level indicators and building physics parameters can be understood, analyzed and concluded to help emerge guidelines for urban scale sustainability. The future of neighbourhood energy efficiency not only lies in energy efficiency but also important parameters like quality of life, access to green, access to daylight, outdoor comfort, natural ventilation etc. So apart from designing less energy-hungry buildings, it is required to create a built environment which will create less stress on buildings to consume more energy. A lot of literary analysis has been done in the Western countries prominently in Spain, Paris and also Hong Kong, leaving a distinct gap in the Indian scenario in exploring the sustainability at the urban strata. The site for the study has been selected in the upcoming capital city of Amaravati which can be replicated with similar neighbourhood typologies in the area. The paper suggests a methodical intent to quantify energy and sustainability indices in detail taking by involving several macro, meso and micro level covariates and parameters. Several iterations have been made both at macro and micro level and have been subjected to simulation, computation and mathematical models and finally to comparative analysis. Parameters at all levels are analyzed to suggest the best case scenarios which in turn is extrapolated to the macro level finally coming out with a proposal model for energy efficient neighbourhood and worked out guidelines with significance and correlations derived.

Keywords: energy quantification, macro scale parameters, meso scale parameters, micro scale parameters

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Authors: Christopher S. Perez, Kendal C. Boyd

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global suicide rates have decreased in recent decades, rates in the United States have increased by 35.2 percent since 1999.American Indians and Alaska Natives (AI/AN) have the highest rates of suicide in the U.S., with approximately 22 suicides per 100,000 people as of 2019. AI/AN have experienced significant historical trauma resulting in disproportionate rates of substance abuse and mental disorders. This literature review aimed to identify the demographic and clinical risk and protective factors for American Indians and Alaska Natives and provide an overview of suicidality in this population. The literature reflected varying definitions of suicidality depending on region, with some AI/AN tribesconceptualizing suicide through a spiritual framework, while others defined suicide in the biomedical sense. Furthermore, AI/AN adults and adolescents experienced higher rates of suicidal ideation when compared to other racial groups. Religious preference, sexual orientation, prior suicidal behavior, psychiatric admission, history of abuse, substance abuse, family history of mental illness, family history of substance abuse, family history of suicidal behaviors, domestic violence, and trauma were discussed as factors related to suicidality. Recommendations included increasing access to and utilization of mental health and medical services, culturally adapting suicide prevention programs to AI/AN communities, increasing support for LGBTQ+ AI/AN, providing opportunities that reinforce ethnic identity, and post-hospitalization follow-up care. The following databases were utilized to obtain peer-reviewed articles for this literature review: Complementary Index, Academic Search Premier, Science Direct, PsycInfo, Social Sciences Citation Index, PsycArticles, PubMed, EbscoHost, and PsycBooks. Articles that examined Native populations outside of the United States did not cite a primary source and/or were published before 1990 were excluded.

Keywords: alaska native, american indian, protective factors, risk factors, suicidality, suicide

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Authors: Ella Sèdé Maforikan

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Sustained water management requires quantitative information and the knowledge of spatiotemporal dynamics of hydrological system within the basin. This can be achieved through the research. Several studies have investigated both surface water and groundwater in Beterou catchment. However, there are few published papers on the application of the SWAT modeling in Beterou catchment. The objective of this study was to evaluate the performance of SWAT to simulate the water balance within the watershed. The inputs data consist of digital elevation model, land use maps, soil map, climatic data and discharge records. The model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI2) approach. The calibrated started from 1989 to 2006 with four years warming up period (1985-1988); and validation was from 2007 to 2020. The goodness of the model was assessed using five indices, i.e., Nash–Sutcliffe efficiency (NSE), the ratio of the root means square error to the standard deviation of measured data (RSR), percent bias (PBIAS), the coefficient of determination (R²), and Kling Gupta efficiency (KGE). Results showed that SWAT model successfully simulated river flow in Beterou catchment with NSE = 0.79, R2 = 0.80 and KGE= 0.83 for the calibration process against validation process that provides NSE = 0.78, R2 = 0.78 and KGE= 0.85 using site-based streamflow data. The relative error (PBIAS) ranges from -12.2% to 3.1%. The parameters runoff curve number (CN2), Moist Bulk Density (SOL_BD), Base Flow Alpha Factor (ALPHA_BF), and the available water capacity of the soil layer (SOL_AWC) were the most sensitive parameter. The study provides further research with uncertainty analysis and recommendations for model improvement and provision of an efficient means to improve rainfall and discharges measurement data.

Keywords: watershed, water balance, SWAT modeling, Beterou

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Authors: Cheng Fang Hsu

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Call center is the core of building customer relationship management system. Under the strong competitive stress, it becomes a new profiting challenge for a successful enterprise. Call center is a department not only to provide customer service but also to bring business profit. This is the qualitative case study in Taiwan bank service industry which goes on deeper exploration, and analysis by business interviews and industrial analysis. This study starts from the establishment, development, and management after the reforming of the case call center. Through SWOT analysis, and industrial analysis, this study adopted 7S model to explain how the call center reforms from service oriented to profit oriented and from cost management to profit management. The results indicated how service innovation management promotes call center to be operated as a market profit competition center. The recommendations are indicated to support the call center on marketing profit by service innovation management.

Keywords: call center, 7S model, service innovation management, bioinformatics

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Authors: Lizhi Ma, Chengcheng Hu, Fuxian Wong

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Partial reduce (P-Reduce) has set a state-of-the-art performance on distributed machine learning in the heterogeneous environment over the All-Reduce architecture. The dynamic P-Reduce based on the exponential moving average (EMA) approach predicts all the intermediate model parameters, which raises unreliability. It is noticed that the approximation trick leads the wrong way to obtaining model parameters in all the nodes. In this paper, SAP-Reduce is proposed, which is a variant of the All-Reduce distributed training model with staleness-aware dynamic P-Reduce. SAP-Reduce directly utilizes the EMA-like algorithm to generate the normalized weights. To demonstrate the effectiveness of the algorithm, the experiments are set based on a number of deep learning models, comparing the single-step training acceleration ratio and convergence time. It is found that SAP-Reduce simplifying dynamic P-Reduce outperforms the intermediate approximation one. The empirical results show SAP-Reduce is 1.3× −2.1× faster than existing baselines.

Keywords: collective communication, decentralized distributed training, machine learning, P-Reduce

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Authors: L. Pavithra, R. Sharmila, Shivani Sridhar

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Columns severe structural damage needs proportioning a significant portion of earthquake energy can be dissipated yielding in the beams. Presence of axial load along with cyclic loading has a significant influence on column. The objective of this paper is to present the analytical results of columns subjected to biaxial cyclic loading.

Keywords: RC column, Seismic behaviour, cyclic behaviour, biaxial testing, ductile behaviour

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Authors: Ana Paula Mousinho, Ronaldo D. Mansano, Nelson Ordonez

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Carbon nanotubes are one of the main elements in nanotechnologies; their applications are in microelectronics, nano-electronics devices (photonics, spintronic), chemical sensors, structural material and currently in clean energy devices (supercapacitors and fuel cells). The use of magnetic particle decorated carbon nanotubes increases the applications in magnetic devices, magnetic memory, and magnetic oriented drug delivery. In this work, single-walled carbon nanotubes (CNTs) forest decorated with chromium were deposited at room temperature by high-density plasma chemical vapor deposition (HDPCVD) system. The CNTs forest was obtained using pure methane plasmas and chromium, as precursor material (seed) and for decorating the CNTs. Magnetron sputtering deposited the chromium on silicon wafers before the CNTs' growth. Scanning electron microscopy, atomic force microscopy, micro-Raman spectroscopy, and X-ray diffraction characterized the single-walled CNTs forest decorated with chromium. In general, the CNTs' spectra show a unique emission band, but due to the presence of the chromium, the spectra obtained in this work showed many bands that are related to the CNTs with different diameters. The CNTs obtained by the HDPCVD system are highly aligned and showed metallic features, and they can be used as photonic material, due to the unique structural and electrical properties. The results of this work proved the possibility of obtaining the controlled deposition of aligned single-walled CNTs forest films decorated with chromium by high-density plasma chemical vapor deposition system.

Keywords: CNTs forest, high density plasma deposition, high-aligned CNTs, nanomaterials

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Authors: D. Muley, H. S. Al-Mandhari

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This paper evaluates the performance of a multi-lane four-legged modern roundabout operating in Muscat using SIDRA model. The performance measures include Degree of Saturation (DOS), average delay, and queue lengths. The geometric and traffic data were used for model preparation. Gap acceptance parameters, critical gap, and follow-up headway were used for calibration of SIDRA model. The results from the analysis showed that currently the roundabout is experiencing delays up to 610 seconds with DOS 1.67 during peak hour. Further, sensitivity analysis for general and roundabout parameters was performed, amongst lane width, cruise speed, inscribed diameter, entry radius, and entry angle showed that inscribed diameter is the most crucial factor affecting delay and DOS. Upgradation of the roundabout to the fully signalized junction was found as the suitable solution which will serve for future years with LOS C for design year having DOS of 0.9 with average control delay of 51.9 seconds per vehicle.

Keywords: performance analysis, roundabout, sensitivity analysis, SIDRA

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Authors: Violeta Damjanovic-Behrendt

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This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

Keywords: security, internet of things, cloud computing, stackelberg game, machine learning, naive q-learning

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Kaoutar Jraida

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Growing evidence demonstrates that thermal conditions in office buildings broadly influence productivity of workers. The purpose of this study is to evaluate and analyze the indoor thermal comfort in an office space based on the calculation of predicted mean vote and predicted percentage of dissatisfied (PMV-PPD) model and field survey.

Keywords: Office, Predicted Mean Vote (PMV), Percentage People Dissatisfied (PPD), Thermal comfort

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Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system

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Authors: Riadh Zorgati, Thomas Triboulet

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In quite diverse application areas such as astronomy, medical imaging, geophysics or nondestructive evaluation, many problems related to calibration, fitting or estimation of a large number of input parameters of a model from a small amount of output noisy data, can be cast as inverse problems. Due to noisy data corruption, insufficient data and model errors, most inverse problems are ill-posed in a Hadamard sense, i.e. existence, uniqueness and stability of the solution are not guaranteed. A wide class of inverse problems in physics relates to the Fredholm equation of the first kind. The ill-posedness of such inverse problem results, after discretization, in a very ill-conditioned linear system of equations, the condition number of the associated matrix can typically range from 109 to 1018. This condition number plays the role of an amplifier of uncertainties on data during inversion and then, renders the inverse problem difficult to handle numerically. Similar problems appear in other areas such as numerical optimization when using interior points algorithms for solving linear programs leads to face ill-conditioned systems of linear equations. Devising efficient solution approaches for such system of equations is therefore of great practical interest. Efficient iterative algorithms are proposed for solving a system of linear equations. The approach is based on a preconditioning of the initial matrix of the system with an approximation of a generalized inverse leading to a stochastic preconditioned matrix. This approach, valid for non-negative matrices, is first extended to hermitian, semi-definite positive matrices and then generalized to any complex rectangular matrices. The main results obtained are as follows: 1) We are able to build a generalized inverse of any complex rectangular matrix which satisfies the convergence condition requested in iterative algorithms for solving a system of linear equations. This completes the (short) list of generalized inverse having this property, after Kaczmarz and Cimmino matrices. Theoretical results on both the characterization of the type of generalized inverse obtained and the convergence are derived. 2) Thanks to its properties, this matrix can be efficiently used in different solving schemes as Richardson-Tanabe or preconditioned conjugate gradients. 3) By using Lp norms, we propose generalized Kaczmarz’s type matrices. We also show how Cimmino's matrix can be considered as a particular case consisting in choosing the Euclidian norm in an asymmetrical structure. 4) Regarding numerical results obtained on some pathological well-known test-cases (Hilbert, Nakasaka, …), some of the proposed algorithms are empirically shown to be more efficient on ill-conditioned problems and more robust to error propagation than the known classical techniques we have tested (Gauss, Moore-Penrose inverse, minimum residue, conjugate gradients, Kaczmarz, Cimmino). We end on a very early prospective application of our approach based on stochastic matrices aiming at computing some parameters (such as the extreme values, the mean, the variance, …) of the solution of a linear system prior to its resolution. Such an approach, if it were to be efficient, would be a source of information on the solution of a system of linear equations.

Keywords: conditioning, generalized inverse, linear system, norms, stochastic matrix

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Authors: Aniekan Peter, ECS Naidu, Edidiong Akang, U. Offor, R. Kalhapure, A. A. Chuturgoon, T. Govender, O. O. Azu

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Introduction: Nano-drugs are novel innovations in the management of human immunodeficiency virus (HIV) pandemic, especially resistant strains of the virus in their sanctuary sites: testis and the brain. There are safety concerns to be addressed to achieve the full potential of this new drug delivery system. Aim of study: Our study was designed to investigate toxicity profile of Tenofovir Nanoparticle (TDF-N) synthesized by University of Kwazulu-Natal (UKZN) Nano-team for prevention and treatment of HIV infection. Methodology: Ten adult male Sprague-Dawley rats maintained at the Animal House of the Biomedical Resources Unit UKZN were used for the study. The animals were weighed and divided into two groups of 5 animal each. Control animals (A) were administered with normal saline. Therapeutic dose (4.3 mg/kg) of TDF-N was administered to group B. At the end of four weeks, animals were weighed and sacrificed. Liver and kidney were removed fixed in formal saline, processed and stained using H/E, PAS and MT stains for light microscopy. Serum was obtained for renal function test (RFT), liver function test (LFT) and full blood count (FBC) using appropriate analysers. Cellular measurements were done using ImageJ and Leica software 2.0. Data were analysed using graph pad 6, values < 0.05 were significant. Results: We reported no histological alterations in the liver, kidney, FBC, LFT and RFT between the TDF-N animals and saline control. There were no significant differences in weight, organo-somatic index and histological measurements in the treatment group when compared with saline control. Conclusion/recommendations: TDF-N is not toxic to the liver, kidney and blood cells in our study. More studies using human subjects is recommended.

Keywords: tenofovir nanoparticles, liver, kidney, blood cells

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Authors: M. Y. Ismail, M. Inam, A. F. M. Zain, N. Misran

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Progressive phase distribution is an important consideration in reflect array antenna design which is required to form a planar wave in front of the reflect array aperture. This paper presents a detailed mathematical model in order to determine the required reflection phase values from individual element of a reflect array designed in Ku-band frequency range. The proposed technique of obtaining reflection phase can be applied for any geometrical design of elements and is independent of number of array elements. Moreover the model also deals with the solution of reflect array antenna design with both centre and off-set feed configurations. The theoretical modeling has also been implemented for reflect arrays constructed on 0.508 mm thickness of different dielectric substrates. The results show an increase in the slope of the phase curve from 4.61°/mm to 22.35°/mm by varying the material properties.

Keywords: mathematical modeling, progressive phase distribution, reflect array antenna, reflection phase

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