Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian multilevel model application on determinants of perinatal mortality in Ethiopia using 2011 and 2016 EDHS data

Perinatal mortality is the death of a fetus after the age of viability until the 7 day of life. Perinatal mortality is estimated by the addition of stillbirths plus the early neonatal mortality, which represents deaths occurring during the first 7 days after delivery. Perinatal mortality remains a great burden in Ethiopia. The purpose of this study was to assess and compare the demographic and socio-economic determinant factors of perinatal mortality in Ethiopia using the 2011 and 2016 Ethiopian Demographic Health Surveys (EDHS). For data analysis, the Bayesian multilevel Model was used in this study. The study revealed that there is a regional variation in perinatal mortality and this variation was high in 2011 EDHS than in 2016 EDHS data. Factors like sex of the child, age of mother, wealth index, family size, birth order, source of drinking water, place of residence, place of delivery, and child twin were found to be the determinant factors of perinatal mortality in both 2011 and 2016 EDHS. In this study, we found that perinatal mortality variation across regions has decreased from 2011 to 2016 surveys which shows the promising progress of health intervention in the country.
Role of Chemical Potential in Flake Shape and Edge Properties of Monolayer MoS2

The precise control of the edge geometry and crystal shape of monolayer MoS2 is of particular importance for their application in nanoelectronics and photoelectro catalysts. Here, we reveal a crucial role of chemical potential in the determination of equilibrium shape (ES) and edge structure of monolayer MoS2 by using density-functional theory calculations. Applying the Wulff construction rule, our results demonstrate the shape evolution of monolayer MoS2 flake from the dodecagonal shape, then to the hexagonal shape, to the triangular shape with the variation of chemical potential from the Mo-rich to the S-rich condition, and the edge structure of ES changes correspondingly from mixed zigzag/armchair edges to purely zigzag edges. This finding can be applied to explain extensive experimental observations about the morphology of MoS2 domains. Likewise, the edge magnetism and electronic structures of monolayer MoS2 domains are found to be dependent on their edge structure, which provides specific guidance fo.
The perceived value in ecotourism related to satisfaction and loyalty: A study from Costa Rica

Ecotourism allows activities in contact with nature in protected natural areas to contribute to environmental care. This study seeks to establish the dimensions of perceived value in ecotourism and analyze its relationship with satisfaction and loyalty. It was an in situ research carried out in two protected areas of Costa Rica: Arenal National Park and Cano Negro National Wildlife Refuge. The sample consisted of 310 surveys for domestic and foreign tourists. The data were interpreted through a factorial analysis to identify the dimensions that make up the perceived value. Also, Spearman's correlation technique and the stepwise multiple regression method were used to find the relationships among the variables. The findings show that there are three dimensions of perceived value: economic-functional, emotional, and social. Overall satisfaction and loyalty had a high average score, and the dimensions found are significantly and positively related to overall satisfaction. The "economic-functional value" dimension has a greater influence on overall satisfaction, and the "emotional value" dimension is the most significant predictor of the intentions to return, recommend, and say positive things about the ecotourism destination.
Assessment of Environmental Sensitivity Index to Desertification Using GIS: Case Study in West El-Minia Governorate, Egypt

The aim of this work is the identification of the Environmental Sensitivity Index (ESI) to desertification in West El-Minia Governorate of Egypt using GIS, based on the MEDALUS model. Three main indicators in this model were considered, including: soil quality, vegetation quality and climate quality. Topographic maps, geologic maps, Landsat-8 satellite image, DEM, NDVI, land surveying, laboratory analyses and climatic data were used for estimating the ESI to desertification in the studied area. The results obtained in this study reveal that the very sensitive and sensitive areas to desertification were in the eastern and central parts of the studied area, where the soil, vegetation and climatic qualities are low. These vulnerable areas are representing 81.49% of the study area (543575 ha.). The western parts of the study area are characterized by low sensitivity to desertification and represent 14.68% of the total area (97907 ha.). The low sensitivity for desertification in the study area is due to the good soil quality and vegetation quality. Small area in the western part of the study area are medium sensitive to desertification and represent 4.43% of the total area (29579 ha.). Sand dunes and Hills occupied 3.83% of the total area. The factors that effect on the sensitivity to desertification are parent material, soil texture, soil depth, slope, vegetation type, drought resistance and erosion protection. The integration of these factors may lead to plan a successful resistance to degradation and very important for decision making in ESI to desertification in the study area.
First report of detection of microcystins in farmed Mediterranean mussels Mytilus galloprovincialisin Thermaikos gulf-Greece, using ELISA and liquid chromatography high-resolution mass spectrometry

Background Microcystins are emerging marine biotoxins, produced by potentially toxic cyanobacteria. Their presence has been reported in aquatic animals in Greek internal waters, while data are few in marine environments. Since the climate change induce eutrophication and harmful algal blooms in coastal marine ecosystems affecting the public health, further research on microcystins’ presence in marine waters is required. The aim of this study was to detect the potential presence of microcystins in mussels Mytilus galloprovincialis in the largest farming areas in Thermaikos gulf, in Northern Greece, and to investigate their temporal and spatial distribution, adding to the knowledge of microcystins presence in Greek Mediterranean mussels. Results A three years microcystins’ assessment was conducted from 2013 to 2016, in farmed Mediterranean mussels Mytilus galloprovincialis, in five sampling areas in Thermaikos gulf, in northern Greece, where the 90% of mussels’ farming activities is located. The isolation of potentially toxic cyanobacteria was confirmed by molecular methods. An initial screening was performed with a qualitative and quantitative direct monoclonal (DM) ELISA and results above 1ng/g were confirmed for the occurrence of the most common microcystins -RR, -LR and -YR, by Ultra High Performance Liquid Chromatography (UHPLC) coupled with a high- resolution mass spectrometer (HRMS) (Orbitrap analyzer). Microcystin -RR and microcystin -LR were detected, while the intensity of microcystin-YR was below the method detection limit. Most samples that exhibited concentrations above 1ng/g were detected during the warm seasons of the year and especially in Spring. Results indicated an overestimation of the ELISA method, since concentrations ranged between 0.70 ± 0.15 ng/g and 53.90 ± 3.18 ng/g, while the confirmation declared that the levels of microcystins were 6 to 22 times lower. Conclusions Microcystin RR and microcystin LR were detected for the first time in mussel Mytilus galloprovincialis, harvested from farms in Thermaikos gulf, in Central Macedonia, in Greece. Their presence was linked to potentially toxic cyanobacteria. Bioaccumulation in digestive gland was observed, while the concentrations in muscles were found extremely low. Samples with levels above 1ng/g were observed mostly during spring, confirming the seasonal distribution of microcystins. The comparison of the results by the ELISA and the LC-Orbitrap MS method indicated an overestimation of concentration by the ELISA method.
CD44-dependent hyaluronan-binding and T-lymphocyte migration

CD44 has been suggested to play a role in adhesive interactions mediating migration and extravasation of T cells into the tissues. This mediation is believed to occur as a result of CD44 binding to hyaluronic acid (HA) on the surface of endothelium. Among factors suggested to regulate this binding is the pro-inflammatory cytokine TNFa, which has been suggested to upregulate HA-binding through sulfation of the CD44 molecule. One of the objectives of this research proposal was aimed at determining the role of T cell activation, TNFa and TNFa receptors in HA binding by T lymphocytes. It was found that only highly activated T cells, which are the largest in cell size and expressed the highest levels of CD44 were the most efficient HA binders. TNFa exerts its effect on HA binding by regulating T cell activation. It increases HA binding under conditions where the cells were not optimally activated. The effects of TNFR1 (p55) and TNFR2 (p75) on HA binding can also be explained by their role in T cell activation. Thus, p55, which is not required for optimal T cell activation, has no effect on HA binding by anti-CD3 activated CD8 T cells. By contrast, p75" CD8 T cells, which were less optimally activated by anti-CD3 stimulation, bind much less HA than similarly activated wild type cells. The role of CD44 in migration of T lymphocytes in vivo was also determined. Various in vivo assays were used to determine whether CD44 was required for migration of polarized TH1 and TH2 cells into sites of inflammation and whether this migration correlated with HA binding. The role of CD44 in the migration of antigen-specific CD8 T cells at various times after antigen activation into lymphoid and non-lymphoid tissues was also determined. All these assays failed to demonstrate an essential role for CD44 in T cell migration. Thus, alternative mechanisms other than those mediated by CD44 are likely responsible for regulating T cell migration in vivo.
Development of Interactive-Multimedia-Assisted Social Cognitive Model for Early Reading Learning

A research report from USAID PRIORITAS (2017) shows gaps in the quality and quantity of the processes and learning resources available to students in Indonesia, which causes poor quality of their reading capabilities. Therefore, it is important to develop a model to facilitate early reading learning for students in Indonesia. This paper discusses designbased research to develop the Interactive-Multimedia-Assisted Social Cognitive Model for Early Reading Learning and its implementation in a natural setting. The model is based on social cognitive theory, which states that learning occurs through interaction between intrapersonal factors, behavioural factors, and environmental factors (Bandura, 2012). Social cognitive learning happens in four steps: attention, retention, production, and motivation (Bandura, 2010). To aid the implementation of social cognitive theory in early reading learning, interactive multimedia for early reading is also developed. Development of the model and interactive multimedia is conducted following design-based research steps proposed by Reeves (2006). The result of this research is a model called Interactive-Multimedia-Assisted Social Cognitive Model for Early Reading Learning (IMAS Model for Early Reading Learning). IMAS model was implemented to teach early reading at two private elementary schools in Bandung. The increase in students’ average early reading scores shows that the model is effective to improve the early reading skills of students. The result of this study can be used as a reference to develop a similar model and interactive multimedia for other subjects or other levels
DESIGNING A LOGISTIC NETWORK FOR HOSPITAL WASTE MANAGEMENT: A BENDERS DECOMPOSITION ALGORITHM

Healthcare wastes are produced from all medical and therapeutic activities in hospitals and healthcare centres. Around 15-20% of these wastes are classified as infectious wastes that could be hazardous. Therefore, an effective approach is required for handling costs and environmental issues. In this paper, a bi-objective Mixed-Integer Linear Programming (MILP) model is presented for logistics of infectious and non-infectious wastes. The proposed bi-objective model aims to minimize network costs and the risk of exposure to contamination. In this respect, a multi-stage network consisting of hospitals, recycling centres, treatment centres, disposal centres, mainly covering the location-routing problem, is considered. To deal with computational complexity of the proposed model, a Benders Decomposition Algorithm (BDA) has been employed. The researchers were faced with two important questions: (1) whether the proposed model can be applied to real-world scenarios or not, and (2) how efficient is the proposed algorithm in solving standard test problems and real-world cases. To answer these questions, the outputs of the BDA have been compared with the optimal solutions provided by the CPLEX software. The results imply that the BDA has been able to achieve optimal solutions in less computation times. Moreover, the proposed model and algorithm have been applied to a real-world study in Alborz Province of Iran. The outputs demonstrate that the proposed model and algorithm can yield applicable solutions for the case study which have been approved by experts. The proposed model can be extended by considering compatibility of wastes in storage.
Diffusive Motions of Molecular Hydrogen Confined in THF Clathrate Hydrate

Clathrates hydrates are nanoporous crystalline materials made of water cages encapsulating guest molecules. By inserting H2 molecules with the help of a promoter (tetrahydrofuran, noted THF), systems relevant for hydrogen storage application are formed by using relatively soft pressure (of the order of 100 bar) near room temperature. Dynamic properties of hydrogen molecules confined in the small cages of the deuterated THF clathrate hydrate have been investigated at equilibrium by means of incoherent quasi-elastic neutron scattering (QENS). These QENS investigations provide direct experimental evidence about the fundamental aspect of translational diffusive motions of the hydrogen molecules. A comprehensive study of the hydrogen molecules dynamics above 100 K has been achieved through a quantitative analysis of the structure factors (i.e., the spatial extend of the H2 diffusive motion) as well as of the QENS broadening (i.e., the characteristic time of the diffusive motion). On the probed time scale, the .
Relationship between stress components in brazilian judo athletes

ABSTRACT Este estudo teve como objetivo descrever a relação entre os principais componentes do estresse em 93 atletas do judô masculino e feminino de nível competitivo. Os participantes preencheram quatro formulários: Positive and Negative Affect Schedule (PANAS), o Brief COPE (referente às estratégias de coping), o Primary Appraisal Adjective Checklist (PAAC) e Wrestling Coping Resources Questionnaire (WCRQ). Os resultados mostraram uma relação positiva entre ameaça, dano e afeto negativo, bem como entre desafio, benefício e afeto positivo. Encontramos uma relação negativa entre avaliação cognitiva secundária e estratégias de recusa e desinvestimento comportamental. Este estudo confirmou a relação entre os componentes da teoria de Lazarus e Folkman.
EFFECT OF PRE-ANNEALING TEMPERATURE ON THE GROWTH OF ALIGNED α-Fe2O3 NANOWIRES VIA A TWO-STEP THERMAL OXIDATION

Pre-annealing as part of a two-step thermal oxidation process has a significant effect on the growth of hematite (α-Fe2O3) nanowires on Fe foil. High-density aligned nanowires were obtained on iron foils pre-annealed at 300∘C under a dry air flow for 30min. The X-ray diffraction (XRD) patterns indicate that the nanowires are transformed from the small α-Fe2O3 grains and uniquely grow in the (110) direction. The formation of a high-density of small grains by pre-annealing improved the alignment and density of the α-Fe2O3 nanowires.
Artificial Intelligence Based Approach to Validate the Authenticity of News

Misinformation isn’t definitely new thing; it is way before the inception of social media. It is evolving since 14th century but the term like "fake news", "post truth" are used commonly during movement of 2016 US presidential election. People use social media to read news as it is lost cost and user friendly platform; also it is possible to share news on social media with one click. With this merit, it is also having major disadvantage. If the news is false or misleading news then spread of such news will have adverse consequence on civilization. Therefore, battling fake news is important and has now become developing area of research. Researchers are using Artificial Intelligence based approach such as machine learning and natural language processing to battle with the fake news. This paper presents a comprehensive overview of the earlier detection techniques as well as proposes mathematical model and methodology to improve the result.
Construction of open-loop electromechanical system fundamental matrix and its application for calculation of state variables transients

The article considers the methods of calculating the transition matrix of a dynamic system, which is based on the transient matrix representation by the matrix exponent and on the use of the system signal graph. The advantages of the transition matrix calculating using a signal graph are shown. The application of these methods to find the transition matrix demonstrated on the simple electromechanical system example. It is shown that the expression for the transition matrix as a matrix exponent completely corresponds to the expression found by means of the inverse matrix and based on the use of the signal graph. The transient matrix of a dynamical system thus found as a matrix exponent can be used to analyze processes in a system that is described by differential equations with integer derivatives. The formation of a transient matrix for the analysis of system processes, which is described by equations with fractional derivatives, is also considered. It is shown that the description of processes in systems with fractional derivatives based on the transient matrix and the representation of the fractional derivative in the form of Caputo-Fabrizio makes it possible to study coordinate transients without approximations in the description of the fractional derivative.
NIR Spectroscopy Detects Chlorpyrifos-Methyl Pesticide Residue in Rough, Brown, and Milled Rice

HighlightsNIR spectroscopy detects quantitative and qualitative levels of chlorpyrifos-methyl residues in bulk rice.Levels of chlorpyrifos-methyl residues in bulk rice can be differentiated at 78% to 100% correct classification.Important NIR wavelengths for chlorpyrifos-methyl residue detection were identified.NIR spectroscopy can be used to detect maximum residue levels of chlorpyrifos-methyl pesticide in rice.Abstract. A rapid technique that uses near-infrared reflectance (NIR) spectroscopy for simultaneous qualitative and quantitative determination of the presence of varying concentrations of chlorpyrifos-methyl in bulk samples of rough, brown, and milled rice was established. Five rice varieties, free of pesticides, obtained from RiceTec Inc. and USDA-ARS Arkansas experimental field were used as rough rice samples and also processed to obtain corresponding brown and milled rice. Rice samples were treated with StorcideTM II containing varying levels of the active ingredient, chlorpyrifos-methyl: 0, 1.5, 3, 6, 9, and 12 ppm for rough rice, 0, 0.75, 1.5, 3, 4.5, and 6 ppm for brown rice, and 0, 0.1, 0.2, 0.4, 0.6, and 0.8 ppm for milled rice. Concentrations of chlorpyrifos-methyl were verified using gas chromatography-mass spectrometry analyses. A commercial NIR spectrometer (950-1650 nm wavelength range) was used to obtain spectra of bulk samples. Using partial least squares analysis for quantitative analysis, independent validation showed that chlorpyrifos-methyl residues in rough, brown, and milled rice are predictable with R2 ranging from 0.702 to 0.839 and standard error of prediction (SEP) of 1.763 to 2.374 for rough rice, R2 ranging from 0.722 to 0.800 and SEP of 0.953 to 1.168 for brown rice, and R2 ranging from 0.693 to 0.789 and SEP of 0.131 to 0.164 for milled rice. For qualitative analysis obtained using discriminant analysis, rough rice samples with concentrations of 0, 1.5, and 3 ppm pooled as low pesticide level (LPL) is distinguishable to 6, 9, and 12 ppm which were pooled as high pesticide level (HPL). Similarly, for brown and milled rice, the lower three concentrations pooled as LPL is distinguishable from the higher three concentrations pooled as HPL. Independent validation showed overall correct classifications ranging from 77.8% to 92.6% for rough rice, 79.6% to 88.9% for brown rice, and 94.4% to 100% for milled rice. Keywords: Food safety, Grain quality, NIR spectroscopy, Pesticide residue, Rice.
Mode of delivery of Cognitive Behavioral Therapy for Insomnia: a randomized controlled non-inferiority trial of digital and face-to-face therapy

Abstract Study Objectives Digital Cognitive Behavioral Therapy for Insomnia (dCBT-I) has demonstrated efficacy in reducing insomnia severity in self-referred and community samples. It is unknown, however, how dCBT-I compares to individual face-to-face (FtF) CBT-I for individuals referred to clinical secondary services. We undertook a randomized controlled trial to test whether fully automated dCBT-I is non-inferior to individual FtF CBT-I in reducing insomnia severity. Methods Eligible participants were adult patients with a diagnosis of insomnia disorder recruited from a sleep clinic provided via public mental health services in Norway. The Insomnia Severity Index (ISI) was the primary outcome measure. The non-inferiority margin was defined a priori as 2.0 points on the ISI at week 33. Results Individuals were randomized to FtF CBT-I (n = 52) or dCBT-I (n = 49); mean baseline ISI scores were 18.4 (SD 3.7) and 19.4 (SD 4.1), respectively. At week 33, the mean scores were 8.9 (SD 6.0) and 12.3 (SD 6.9), respectively. There was a significant time effect for both interventions (p < 0.001); and the mean difference in ISI at week 33 was −2.8 (95% CI: −4.8 to −0.8; p = 0.007, Cohen’s d = 0.7), and −4.6 at week 9 (95% CI −6.6 to −2.7; p < 0.001), Cohen’s d = 1.2. Conclusions At the primary endpoint at week 33, the 95% CI of the estimated treatment difference included the non-inferiority margin and was wholly to the left of zero. Thus, this result is inconclusive regarding the possible inferiority or non-inferiority of dCBT-I over FtF CBT-I, but dCBT-I performed significantly worse than FtF CBT-I. At week 9, dCBT-I was inferior to FtF CBT-I as the 95% CI was fully outside the non-inferiority margin. These findings highlight the need for more clinical research to clarify the optimal application, dissemination, and implementation of dCBT-I. Clinicaltrials.gov: NCT02044263: Cognitive Behavioral Therapy for Insomnia Delivered by a Therapist or on the Internet: a Randomized Controlled Non-inferiority Trial.