Miracle-dz/UniFAR-FTUs huggingface dataset:
The Dynamics of Subjective Well-Being Among Recurrent Flood Victims: Development and Testing of an Integrated Model

The Indian subcontinent is vulnerable to natural disasters, predominantly devastating floods. The north-eastern region of India, especially the state of Assam, is endowed with many natural water resources, making the area highly flood-prone. However, very few studies have investigated the population’s subjective well-being (SWB) in these areas despite such recurrent adversity. An integrated model of SWB is proposed and tested by combining the SWB homeostasis theory and the theory of conservation of resources. The integrated model indicated both subjective as well as objective variables as significant predictors of the SWB. A sample of 306 participants was randomly selected from two severely flood-affected areas in the state of Assam in India using a cross-sectional survey study design. Structural equation modeling was used to test two hypothesized integrated models (a direct and mediational path model). The results indicated that SWB homeostasis is maintained within the normative range of 60-65 points when measured on a 100-point continuum. Analysis of the direct path model showed that education, safe shelter, personality traits (extraversion, neuroticism, agreeableness, and openness), object and condition resources, psychological buffers (optimism and perceived control), and negative affect significantly predicted SWB. The mediational path model indicated that optimism is a significant mediator between personality traits (agreeableness, conscientiousness, and neuroticism), positive affect, resources (object resources and condition resources), and SWB. The study findings may have implications for counselling in addressing internal psychological buffers such as optimism and perceived control for maintaining the SWB of the disaster victims.
Yield and Yield Components of Durum Wheat as Influenced by Humic Acid, Zinc and Iron Application

A two-year field study was carried out at the Agricultural Experiment Station, Alexandria University in 2017/2018 and 2018/2019 winter seasons to investigate the effect of foliar spraying of humic acid (HA) (0 and 2.4 kg/ha) and both Fe and Zn micronutrients (0, 480 and 960 g/ha of FeSO4 and/or ZnSO4, respectively) on three durum wheat cultivars (Casino, Bani Sweif6 and Sohag3). The experiment was laid out in split-plot design with three replications, where combinations of HA levels and cultivars occupied the main plots, while combinations of Fe and Zn levels were randomly allocated to the sub plots.
Effect of Moshen Digui prescription for treatment of idiopathic membranous nephropathy—protocol for a randomized, controlled, and single-blind trial

Membranous nephropathy (MN) has been the leading cause of the nephrotic syndrome in nondiabetic adults (1-3). MN can be induced by many secondary causes, such as drugs, infections, and underlying diseases (4). However, most patients of MN are idiopathic (5). IMN is a kind of antibody-mediated autoimmune disease, which can be diagnosed by renal biopsy. The characterized renal biopsy of IMN is deposition of immune complex along the glomerular basement membrane. Moreover, IMN patients has high risk for progressive deterioration of renal function. Research found that 30–40% IMN patients could develop into ESRD (6). As we know, ACEI/ARB is the basic therapy for IMN. Research showed that ACEI/ARB has beneficial effect on decreasing proteinuria for IMN patients with non-nephrotic-range proteinuria (7,8). When patients proteinuria ≥4 g/24 h after 6-month conservative therapy, they should be applied immunosuppressive therapy (9). Cyclosporine and tacrolimus, mycophenolate mofetil (MMF), rituximab, and adrenocorticotropic hormone (ACTH) are recommended for IMN patients for immunosuppressive therapies (10). However the immunosuppressive therapies have side effects such as infection, tumor, and so on. Moreover, there are many IMN patients has high level of proteinuria and high risk of progression to ESRD after these active treatments. Thus, Study Protocol
Aquatic Contaminant and Mercury Simulation Modules Developed for Hydrologic and Hydraulic Models

Abstract : This report offers details regarding the theory and mathematical formulations implemented in the newly developed general constituent simulation module (GC), contaminant simulation module (CSM), and mercury simulation module (HgSM). The GC models simple kinetics for multiple size classes of solids and user-defined constituents in the water column. The CSM models the kinetics of user-defined contaminants in aquatic systems. The kinetic processes modeled in CSM include: ionization, multi-phase partitioning, degradation, photolysis, hydrolysis, volatilization, generalized second-order reaction, and transformations where one chemical species undergoes a reaction and is transformed to a daughter product. The HgSM models mercury species (elemental mercury, inorganic mercury, and methylmercury) and their cycling in aquatic systems. The three water quality modules only compute internal sources and sinks of each state variable for both water column and an underlying sediment layer. The GC, CSM and HgSM modules are written as plug in dynamic link libraries and compiled as GC.dll, CSM.dll and HgSM.dll respectively. These modules have been integrated into the HEC-RAS model and will also be integrated into other hydrologic and hydraulic models (e.g. AdH and SRH-2D).
Densify and Expand: A Global Analysis of Recent Urban Growth

Serious concerns with accelerating global warming have been translated into urgent calls for increasing urban densities: higher densities are associated with lower greenhouse gas emissions, especially those related to vehicle kilometers traveled (VKT). In order to densify meaningfully in the coming decades, cities need to make room within their existing footprints to accommodate more people. In the absence of adequate room within their existing footprints, cities create more room through outward expansion, typically resulting in lower overall densities. We introduce a quantitative dimension to this process, focusing on the population added to a global stratified sample of 200 cities between 1990 and 2014. In three-quarters of the cities we studied, the areas built before 1990 gained population and thus densified significantly. On average, however, only one-quarter of the total population added to the 200 cities in the sample in the 1990–2014 period were accommodated within their 1990 urban footprints, while three-quarters were accommodated within their newly built expansion areas. That resulted in an overall decline in average urban densities during the 1990–2014 period despite the near-global, decades-old and rarely questioned consensus that urban expansion must be contained.
Off-Cycle and Out of Sync: How Election Timing Influences Political Representation

Abstract States exert significant control over many different types of electoral institutions that influence the tone and direction of political representation in American democracy. Yet almost nothing is known about the consequences of the institution that has the greatest singular impact on the turnout and composition of the electorate: election timing. We argue that off-cycle elections will tend to produce governments that are not well-aligned with the political preferences of their median constituent. To empirically test this expectation, we examine the relationship between election timing and mass–elite congruence across local school district governments. Leveraging variation in election timing across districts within the same state, we find that board members are more likely to hold political preferences that are aligned with their constituents when boards are elected in on- versus off-cycle races. We conclude by discussing the implications of these findings for the study of representation and election timing, suggesting some possible avenues for future research.
Dynamics of mixing in 2D Stokes flows, numerics and experiments

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
Biological correlates of sea urchin recruitment in kelp forest and urchin barren habitats

Shifts between the alternate stable states of sea urchin barren grounds and kelp forests correspond to sea urchin density. In the Aleutian Archipelago, green sea urchins Strongylocentrotus polyacanthus are the dominant herbivores that graze kelp forests. Sea urchin recruitment is an important driver that influences sea urchin density, particularly in the absence of top-down control from a keystone predator such as the sea otter Enhydra lutris. To understand how the biological community may influence patterns of sea urchin recruitment, we compared sea urchin recruit (size ≤20 mm) densities with biomass of other benthic organisms in both barren ground and kelp forest habitats at 9 islands across the Aleutian Archipelago. Patterns of biological community structure between the 2 habitats did not explain patterns of sea urchin recruits; however, the same 10 specific taxa were found to correlate with sea urchin recruits in each habitat. Taxa that showed strong positive correlations included Codium, Constantinea, Schizymenia, and hydrozoans, while strong negative correlations were observed with Pachyarthron and Pugettia. Weak positive correlations were observed with Alcyonidium and ascidiaceans in both habitats, while weak variable relationships were detected with Polysiphonia and Corallina between habitats. The observed species-specific relationships may be due to small sea urchin displacement by larger conspecifics, larval responses to settlement cues, post-settlement survival via biogenic refugia, or potentially predation. These potential species-specific interactions were apparent, regardless of habitat, and it can be inferred that they would be preserved in the presence or absence of keystone predation.
The effects of additives on the reduction of the pour point of diesel fuel and fuel oil

ABSTRACT One important industrial problem is the wax precipitation of oil fractions. Factors such as oil composition, temperature, and pressure are effective in causing wax precipitation. One way to prevent wax precipitation is using of chemical inhibitors to reduce pour point. Studying the effects of additives on specific oil samples could help solve wax precipitation problems at various oil processing stages. Despite previous studies that have been done at this aim, finding materials that could decrease the pour point and be economically acceptable, environmentally well optimized, and reasonable is still an unsolved problem. So, it is important to make use of effective materials that could be influential in preventing of wax precipitation or reduction of the amount of precipitation and thus decrease the pour point temperature. In this study, the effects of industrial polymer additives and surfactants that are economically acceptable on decrement of pour point temperature were studied by using three oil product samples, namely light diesel, heavy diesel, and fuel oil (Purification Company of Esfahan). Furthermore, optimized type and concentration of the additives were studied. Results showed that copolymer ethylene-vinyl acetate 28% at a concentration of 500 ppm reduced pour point temperature by 12°C for diesel and that copolymer ethylene-vinyl acetate 19% at a concentration of 300 ppm reduced pour point temperature by 9°C for fuel oil.
Wire antennas for textiles applications

This paper investigates the use of a Genetic Algorithm to produce an optimized compact monopole antenna for textile application. The antenna characteristics are examined using the Numerical Electromagnetic code (NEC2) with genetic algorithm (GA). The design objective for the antennas considered here is to drive the S11 to be less than or at least, as close as possible to -10dB, targeting this application (850-950 MHz) band. Results of return loss are also presented. The purpose of this study is to build a genetic algorithm (GA) optimisation of wire antennas for application at 900MHz. These antennas are fully textile, flexible and wearable. Measurement test was performed by placing the textile antenna sample close to the human chest while results were compared with simulation on a body phantom. Specific absorption rate was evaluated in CST Microwave Studio. To validate our results, four linear wire antenna designs, planar and embroidered antennas were fabricated, measured and compared with the simulation. Simulated and measured results show that all the antennas can operate at 900 MHz band. Key words: Genetic algorithm, linear wire, segment length, population, chromosome, specific absorption rate.
In vitro study after exposure to the aqueous extract of Piper amalago L. shows changes of morphology, proliferation, cytoskeleton and molecules of the extracellular matrix

Piper amalago L. is a medicinal plant traditionally used as a healing agent for wounds, burns, abscesses, boils, and insect bites. The current study aimed to evaluate the possible effects of the aqueous crude extract obtained from P. amalago leaves, in different concentrations and in different incubation times, using the in vitro model of mouse Research, Society and Development, v. 10, n. 4, e0110413289, 2021 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi. org/10.33448/rsd-v10i4.13289 2 fibroblasts (3T3). The extract was tested in different concentrations at the 24 h incubation time for analysis of cell viability, cytotoxicity, proliferation, cell morphology, immunostaining, adhesion and cell spreading assays, as well as to determine the hydroxyproline concentration and activity of the metalloproteinase MMP2. Morphologically, after exposure to the concentrations of 15 and 150 μg/mL, the cells maintained the morphology, yet a greater number of cells with more expansions of the cell body and larger than the control cells were observed. The treated cell culture also showed a greater number of cells, larger cells, a greater expansion of the cell body, adherent cells spread over the substrate, and a more juxtaposed, central and spherical nucleus. The treatment induced greater cell adhesion to the polymer, fibronectin, and collagen I. Biochemical results showed a significant increase in the hydroxyproline amino acid after exposure for 96 h. The extract did not induce loss of cell viability until the concentration reached 150 μg/mL, positively modulating proliferation, morphology, adhesion, degree of spreading, and organization of microfilaments. The extract also promoted a significant increase in the hydroxyproline amino acid.
Antibacterial activity of aquatic actinomycete,Actinoplanes digitatisDnj-2 (MN567713)

Introduction and Aim: There are centers for antibiotics in the nature to treat disease by looking for different sources, for example, actinomycetes, are approximately two-thirds of naturally occurring antibiotics, having much of medical importance, have been isolated from actinomycetes.The aim of the present study was to isolate and to identify the actinomycetes having antagonistic activity. Materials and Methods: An actinomycetes strain isolated from dam soil sample collected from Alnajl dam of Hadhramout Yemen, showed antibacterial activity against selected microbial pathogens. The nutritional requirements and cultural conditions for maximal growth to produce secondary metabolites have been optimized under shake flask conditions. The growth and production of secondary metabolites were maximal with the use of SCA medium supplemented at pH 7.0, and incubation temperature and time of 37? and 20 days respectively. Results:Based on morphological, biochemical, physiological and phylogenetic characterization, the strain was identified as Actinoplanes digitatisDnj-2 (MN567713). The ethyl acetate extract (1g/mL) obtained from the isolate showed significant antibacterial activity against Gram-negative bacteria- Escherichiacoli (21cm) and Pseudomonas aeruginosa (29cm) and Gram-positive bacteria- Bacillus subtitles(31cm) and Staphylococcus aureus (22cm) when compared with penicillin G 10 units. Conclusion:In conclusion, the isolated strain has broad spectrum of antagonistic activity against Gram-positive and Gram-negativebacteria.
Environmental Marketing Strategy and Customer Citizenship Behavior: An Investigation in a Café Setting

ABSTRACT This study investigates the role that environmental marketing strategy plays in enhancing customer citizenship behavior (CCB) – directly, indirectly, and interactively with brand familiarity. Drawing on data collected from 439 Starbucks customers in Lebanon, the findings of the study support the exists of a positive relationship between environmental marketing strategy and two forms of CCB – namely, the policing of other customers and the helping of other customers. Evidence indicated that corporate reputation plays a mediating role in the relationship between environmental marketing strategy and CCB. Moreover, brand familiarity served as a moderator factor that positively influences the relationship between environmental marketing strategy and CCB. Further, the conditional indirect effect of brand familiarity on the relationship between environmental marketing strategy and CCB through corporate reputation indicated a significant positive impact.
Molecular Epidemiology of First Lumpy Skin Disease Outbreak in Odisha, India

Lumpy skin disease virus (LSDV) is the causative agent of lumpy skin disease (LSD) which is a member of Capripoxvirus. It is an economically critical transboundary disease affecting cattle. This study records the first LSD incidence in cattle of Ganjam district and analyses data from LSD outbreak in August 2020 on epidemiological and genetic characterization. Out of 452 animals clinically examined (59 farms), 63 animals were clinically affected with LSD, with a total morbidity rate of 13.93%. The morbidity rates in the villages (ten villages) varied from 5.55 to 21.62%. The multivariable logistic regression showed that grazing of animals (P=0.023; OR: 1.90; 95% CI: 1.09-3.32), and lactation and pregnancy status of animals (P=0.007; OR: 2.86; 95% CI: 1.32-6.17) were the potential risk factors for the occurrence of lumpy skin disease. Out of 53 clinically suspected animals collected from Ganjam district of Odisha, 18 samples (33.96%) were found positive by PCR for both P32 and F genes of capripox virus. Phylogenetic analysis of P32 gene of LSD (MW147486) showed 100% similarity with other isolates from India, Bangladesh, Egypt and Saudi Arabia. Additionally, phylogenetic analysis of F gene of LSD (MW147485) revealed a similarity of 97.99 %, 97.36%, and 96.60% with, Odisha India (MT074110), Beni Suif Egypt (MN694826) and Marsa Matrouh Egypt (MN699855), respectively.
Determination of Pre-service Teachers’ Sensitivity to Violence Against Children

Article History: Purpose: Violence against children in the world and Turkey is increasing day by day, and this alarming increase harms the development of children and the future of society. Therefore, pre-service teachers' sensitivity to violence against children is of great importance in terms of revealing the violence and conducting preventive and directive services. This study aimed to determine pre-service teachers' sensitivity to violence against children. Research Methods: This was a case study using a qualitative research design. The study group consisted of sixteen pre-service teachers who were studying in eight different departments, in the third and fourth grades of the Faculty of Education in a state university in Central Anatolia. The content analysis method was used for data analysis. Received: 25 Dec. 2019 Received in revised form: 16 Feb. 2021 Accepted: 23 Feb. 2021 DOI: 10.14689/ejer.2021. 92.10
iResponse: An AI and IoT-Enabled Framework for Autonomous COVID-19 Pandemic Management

SARS-CoV-2, a tiny virus, is severely affecting the social, economic, and environmental sustainability of our planet, causing infections and deaths (2,674,151 deaths, as of 17 March 2021), relationship breakdowns, depression, economic downturn, riots, and much more. The lessons that have been learned from good practices by various countries include containing the virus rapidly; enforcing containment measures; growing COVID-19 testing capability; discovering cures; providing stimulus packages to the affected; easing monetary policies; developing new pandemic-related industries; support plans for controlling unemployment; and overcoming inequalities. Coordination and multi-term planning have been found to be the key among the successful national and global endeavors to fight the pandemic. The current research and practice have mainly focused on specific aspects of COVID-19 response. There is a need to automate the learning process such that we can learn from good and bad practices during pandemics and normal times. To this end, this paper proposes a technology-driven framework, iResponse, for coordinated and autonomous pandemic management, allowing pandemic-related monitoring and policy enforcement, resource planning and provisioning, and data-driven planning and decision-making. The framework consists of five modules: Monitoring and Break-the-Chain, Cure Development and Treatment, Resource Planner, Data Analytics and Decision Making, and Data Storage and Management. All modules collaborate dynamically to make coordinated and informed decisions. We provide the technical system architecture of a system based on the proposed iResponse framework along with the design details of each of its five components. The challenges related to the design of the individual modules and the whole system are discussed. We provide six case studies in the paper to elaborate on the different functionalities of the iResponse framework and how the framework can be implemented. These include a sentiment analysis case study, a case study on the recognition of human activities, and four case studies using deep learning and other data-driven methods to show how to develop sustainability-related optimal strategies for pandemic management using seven real-world datasets. A number of important findings are extracted from these case studies.