Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of Mindful- based Intervention on Reasons for Living among B.Ed. Students with Suicidal Ideation

Background: The objective of the present study is to investigate the effectiveness of mindful-based interventions on reasons for living (RFL) among B.Ed. students with suicidal ideation. Material and Methods: This study employed pre-test post-test control group research design. Students having suicidal ideation were identified by administering Suicidal Ideation Scale and were randomly assigned to experimental and control groups of 40 students each. Linehan Reasons for living Inventory (LRFLI) was administered both in the experimental group and control group as pre-test. After the pre-test the experimental group was given mindfulness based intervention programme of 1 hour, thrice a week lasting for eight weeks. Data obtained from the respondents in the post-test and follow up phases - after 1st, 3rd and 6th months of the completion of the intervention programme by administering LRFLI were analyzed by repeated measures ANOVA. Result: Results revealed that 8-week intervention programme of mindful-based practices elicited an increase in mean score of RFL in the experimental group from base line to post-test and the increase in mean scores were retained over a follow-up period of six months. But the students in the control group retained the same mean score of RFL over the entire period of study. Conclusion: Mindful-based intervention is an effective method in increasing RFL among B.Ed. students with suicidal ideation. Keywords: Mindful- based Intervention, Suicide, Suicidal ideation, Reasons for living.
Trends in the Lethality of American Violence

Research on homicide trends has not adequately considered trends in interpersonal disputes. Aggregate homicide rates partly reflect the extent to which less serious forms of interpersonal violence escalate to deadly violence. This study argues that the rate of disputes in a society and the proportion that result in deadly violence vary independently. But both are necessary to understand lethality trends. The study compares rates of homicide in the Supplemental Homicide Report with rates of violence in the National Crime Victimization Survey to estimate lethality trends from 1992 to 2016. Findings are discussed regarding their implications for explanations of homicide trends.
Prognostic Value of Blood Lactate and Base Deficit in Refractory Cardiac Arrest Cases Undergoing Extracorporeal Life Support.

Objective Cardiac arrest (CA) resuscitation is associated with an 'ischaemia-reperfusion' syndrome characterised by lactic acidosis as assessed by lactate and base deficit (BD). Both biomarkers are usually measured in patients suffering from refractory CA (RCA) subjected to extracorporeal life support (ECLS) to evaluate tissue reperfusion. However, their prognostic value has never been compared. The aim of the present study was to compare the prognostic value of both biomarkers measured at 0 and 3 h after the initiation of ECLS in patients with RCA on mortality. Methods Patients who were admitted to the intensive care unit with RCA were consecutively included in the study. Results Sixty-six patients were included. Lactate correlated with BD (R2=0.44, p<0.001). An area under the curve of 0.72 (95% confidence interval (CI) 0.59-0.84) was found for lactate and of 0.60 (95% CI 0.46-0.73) for BD. Using multivariable logistic regression, lactate (odds ratio (OR) 1.22, 95% CI 1.03-1.48) remained associated with mortality on day 28, but not BD (OR 0.99, 95% CI 0.86-1.14). Conclusion We report a difference in the prognostic value of lactate and BD on mortality. Three hours from the initiation of ECLS in patients with RCA, lactate should be preferred to BD to predict the efficiency of ECLS.
Quantitative trait loci (QTL) mapping for intermittent drought tolerance in BRB 191 × SEQ 1027 Andean Intragene cross recombinant inbred line population of common bean (Phaseolus vulgaris L.)

Drought is a major constraint of common bean (Phaseolus vulgaris L.) production in Uganda where irrigation for the crop is very uncommon. This study aimed to identify quantitative trait loci (QTLs) underlying drought tolerance in 128 F5 RILs derived from an Andean intra-gene cross between drought-tolerant SEQ 1027 and BRB 191. Eighteen traits were evaluated under drought stress and non-stress conditions in the field for 2 years and in the greenhouse for 1 year, respectively. A linkage map spanning 486.29 cM was constructed using 53 single nucleotide polymorphic markers (SNP) markers obtained from the KASP genotyping assay. Eleven consistent QTLs were detected on five linkage groups at a threshold of Logarithm of Odds (LOD) ≥ 3.0. Four QTLs were constitutive, seven were adaptive and were associated with 100 seed weight, grain yield, chlorophyll content, harvest index, dry weight of leaf and stem biomass and yield production efficiency. The QTL associated with a 100 seed weight (sw3.1BS) was the most consistent with the highest percentage of variation explained (21%). Co-localization of five drought-related factors QTLs was detected on pv10 suggesting pleiotropic effects on this chromosome. Identification of molecular markers closely linked to the QTLs identified in this study will facilitate marker assisted breeding for drought tolerance.
Streamwise and spanwise slip over a superhydrophobic surface

The near-wall turbulent flow over a superhydrophobic surface (SHS) with random texture was studied using three-dimensional Lagrangian particle tracking velocimetry (3D-PTV). The channel was operated at a constant mass flow rate over the SHS and a smooth surface at a Reynolds number of 7000 based on the bulk velocity of $0.93~\text{m}~\text{s}^{-1}$ and the full channel height. The friction Reynolds number was 217, based on the friction velocity and half channel height. The 3D-PTV processing was based on the shake-the-box algorithm applied to images of fluorescent tracers recorded using four high-speed cameras. The SHS was obtained by spray coating, resulting in a root-mean-square roughness of $0.29\unicode[STIX]{x1D706}$ and an average texture width of $5.0\unicode[STIX]{x1D706}$ , where $\unicode[STIX]{x1D706}=17~\unicode[STIX]{x03BC}\text{m}$ is the inner flow scale over the SHS. The 3D-PTV measurements confirmed an isotropic slip with a streamwise slip length of $5.9\unicode[STIX]{x1D706}$ and a spanwise slip length of $5.9\unicode[STIX]{x1D706}$ . As a result, both the near-wall mean streamwise and spanwise velocity profiles over the SHS were higher than the smooth surface. The streamwise and spanwise slip velocities over the SHS were $0.27~\text{m}~\text{s}^{-1}$ and $0.018~\text{m}~\text{s}^{-1}$ , respectively. The near-wall Reynolds stresses over the SHS were larger and shifted towards the wall when normalized by the corresponding inner scaling, despite the smaller friction Reynolds number of 180 over the SHS. The near-wall measurement of streamwise velocity showed that the shear-free pattern consists of streamwise-elongated regions with a length of $800\unicode[STIX]{x1D706}$ and a spanwise width of $300\unicode[STIX]{x1D706}$ . The plastron dimensions correspond to the mean distance of the largest roughness peaks $(20~\unicode[STIX]{x03BC}\text{m})$ obtained from profilometry of the SHS. The drag reduction over the SHS was 30 %–38 % as estimated from pressure measurement and the flow field using the 3D-PTV.
An Attempt to Develop A Scale on the Decision Process: The Manager Decision Time Scale

The aim of this study is to develop a valid and reliable data-obtaining tool for exploring which decision stage deems sufficient for managers in the public or private sector, how they use time and how they act in different occasions. Also, a scale demonstrating the approaches which managers are following in their decision processes has not been seen among past studies. This study has been carried out in order to close this gap. The scale has been developed in consideration of the managers’ recommendations about the decision process. Sampling method applied in research is easy sampling method. The 389 participant of this study consist of public and private sector managers in the cities of Gumushane and Bayburt in Turkey. The results of this study are assembled under four factors as “manager’s problem noticing time, manager’s problem defining time, manager’s problem solving time, and the manager’s decision time on different occasions. ” A “Manager Decision Time Scale” containing 13 items has been developed from these Likert scale factors. It has been tested for validity by Model-Defining Factor Analysis. The scale that was formed with the data obtained at the end of this study has been proved to be a valid and reliable data-obtaining tool.
A Many-Objective Evolutionary Algorithm With Pareto-Adaptive Reference Points

We propose a new many-objective evolutionary algorithm with Pareto-adaptive reference points. In this algorithm, the shape of the Pareto-optimal front (PF) is estimated based on a ratio of Euclidean distances. If the estimated shape is likely to be convex, the nadir point is used as the reference point to calculate the convergence and diversity indicators for individuals. Otherwise, the reference point is set to the ideal point. In addition, the estimation of the nadir point is different from what was widely used in the literature. The nadir point, together with the ideal point, provides a feasible way to deal with dominance resistant solutions, which are difficult to be detected and eliminated in Pareto-based algorithms. The proposed algorithm is compared with the state-of-the-art many-objective optimization algorithms on a number of unconstrained and constrained test problems with up to 15 objectives. The experimental results show that it performs better than other algorithms in most of the test instances. Moreover, the new algorithm shows good performance on problems whose PFs are irregular (being discontinuous, degenerated, bent, or mixed). The observed high performance and inherent good properties (such as being free of weight vectors and control parameters) make the new proposal a promising tool for other similar problems.
Analysis of Photovoltaic Performance Loss Rates of Six Module Types in Five Geographical Locations

In this paper, the annual performance loss rates (PLRs) of five different grid-connected photovoltaic (PV) technologies based on outdoor field measurements were computed. The data used were collected in five different geographical locations covering five climatic zones. The PLR values were determined as absolute and relative measures for all sites and module types using seasonal time series decomposition using local regression. The results are very consistent and show a clustering of the PLR for each technology, provided some explainable outliers are removed. This allows the conclusion that in presence of properly sized and quality-driven systems, the influence of different climates on the degradation of PV modules is not very strong. In the first approximation, individual degradations rate values computed in a single climatic zone can be seen as representative for the technology in general. The reason for this is that for defects there is an associated activation energy, which has not been reached yet in the systems analyzed in this study.
Effectiveness of Social Enterprise in Managing Intellectual Capital

In order to successfully accomplish the social and business mission, social enterprises need to identify the appropriate elements of resources that affect their performance since the management of resources is important to ensure the effectiveness of social enterprise. Thus, this study aims to examine the role of intellectual capital, in terms of human capital, structural capital and relational capital on the effectiveness of social enterprise which is represented by the financial viability. Information on the financial viability and intellectual capital were obtained from the content analysis of the annual reports of 210 social enterprises registered under the Registry of Societies (ROS) in Malaysia for the financial period 2010. The results from the statistical analysis revealed that on average, most of the social enterprises in Malaysia would be able to financially sustain in the future. Based on the multivariate analysis, the results highlighted that human capital has a significant positive influence on the financial viability of social enterprise while structural capital and relational capital do not have significant positive relationship with the financial viability of social enterprise. Overall, the findings concluded that human capital was the most influential factor in enabling the effectiveness of social enterprise.
Child welfare workers' perceptions of reunification services: Are timeframes feasible?

This descriptive study explored Child Welfare Worker's perceptions on current reunification timelines imposed by the Adoptions and Safe Families Act of 1997. A survey containing both ordinal and nominal questions was completed by 72 Child Welfare workers in San Bernardino County, Department of Children's Services. The sample consisted of predominately females (80%) with a median age between 41 to 50 years old. The participants were asked to complete 13 questions, including demographics related to child welfare workers feelings on reunification timelines. Descriptive statistical procedures were utilized to determine how child welfare workers felt about shortened timeframes. The implications for social work practice and recommendations for research are discussed.
Green synthesized materials for sensor, actuator, energy storage and energy generation: a review

ABSTRACT Green synthesis methods have attracted enormous research interest as replacements for dangerous chemicals due to their abundance and eco-friendliness. The remarkable properties of green synthesized materials include environmental friendliness, high abundance, antimicrobial, antioxidant and biodegradability. The integration of green synthesized materials in electronic devices not only enhances the economic benefit of natural waste resources but also conserves our environment. This review article is dealing with the current research efforts in green synthesized materials trends, challenges and their potential applications in sensors, actuators, energy storage and energy generation.
Patients’ and Carers’ Perspectives of Psychopharmacological Interventions Targeting Anorexia Nervosa Symptoms

In clinical practice, patients with anorexia nervosa (AN), their carers and clinicians often disagree about psychopharmacological treatment. We developed two corresponding questionnaires to survey the perspectives of patients with AN and their carers on psychopharmacological treatment. These questionnaires were distributed to 36 patients and 37 carers as a quality improvement project on a specialist unit for eating disorders at the South London and Maudsley NHS Foundation Trust. Although most patients did not believe that medication could help with AN, the majority thought that medication for AN should help with anxiety (61.1%), concentration (52.8%), sleep problems (52.8%) and anorexic thoughts (55.6%). Most of the carers shared the view that drug treatment for AN should help with anxiety (54%) and anorexic thoughts (64.8%). Most patients had concerns about potential weight gain, increased appetite, changes in body shape and metabolism during psychopharmacological treatment. By contrast, the majority of carers were not concerned about these specific side effects. Some of the concerns expressed by the patients seem to be AN-related. However, their desire for help with anxiety and anorexic thoughts, which is shared by their carers, should be taken seriously by clinicians when choosing a medication or planning psychopharmacological studies.
Contributions of Foehn and Urban Heat Island to the Extreme High-Temperature Event in Niigata City during the Night of 23-24 August 2018

We quantitatively evaluated the contributions of foehn winds and the urban heat island (UHI) effect to an extreme high-temperature nocturnal event at Niigata city on 23−24 August 2018. During this event, southeasterly winds blew continually across the Niigata Plain and temperatures on the plain were higher than those in the windward region of the mountain range. Back-trajectory analysis and numerical simulations with and without topography showed that the southeasterly winds were foehn winds that caused precipitation and latent heating on the windward slope of the mountain range. The foehn winds and UHI contributed about 2.8°C and 1.9°C, respectively, to the extreme high-temperature of 31.0°C at 2100 JST in Niigata city. The combined impact of the foehn winds and the UHI at Niigata was about 4.0°C during the night. The contribution of the foehn winds was greater at around midnight, whereas that of the UHI was greater during the early night. (Citation: Nishi, A., H. Kusaka, L. L. Vitanova, and Y. Imai, 2019: Contributions of foehn and urban heat island to the extreme high-temperature event in Niigata City during the night of 23−24 August 2018. SOLA, 15, 132−136.)
Impact of Technology Adoption on the Performance of Small and Medium Enterprises in India

Technological innovation is believed to improve organization’s performance stimulates growth and the survival of the organization. Many factors influence the SME performance on technology adoption, such as formal strategy, Organization size, customer and supply relationship, technical capabilities, innovative cost and innovative support. The current study examines the performance of SMEs on technology adoption. It also examines the business performance along with the manufacturing performance of SMEs on adoption of newer technologies. The study uses logistic regression and linear regression to estimate manufacturing and business performance of SMEs. The results convey that the adoption of technologies by SMEs influence their manufacturing performance. Further, it can be concluded that, drivers of technology adoption partly influence the business performance of SMEs.
On the application of a non-intrusive coupling strategy for the local enrichment of NURBS patches: geometrical details

With the introduction of the IsoGeometric Analysis (IGA) [1], the computation of structures has become possible using the exact geometry of the Computer-Aided Design (CAD) model regardless of the mesh density. For that, Lagrange polynomials are replaced by Non-Uniform-Rational-B-Splines (NURBS) functions to perform the analysis. NURBS functions have a higher order of continuity, namely C ( p − 1) through the elements of the mesh for a polynomial degree p , which on a per-degree-of-freedom basis exhibits increased accuracy in comparison to standard Finite Element Methods (FEM). However, difﬁculties are still encountered to model local behaviors such as geometrical details in a NURBS patch. To answer the issue, new splines like T-Splines [2] may be used. Nevertheless, this technique can still appear complex to implement and additional efforts may be necessary to answer the issue of describing a local behavior different from the global one (inclusions). Furthermore, this approach may suffer from some intrusiveness
On the strong consistency of feature‐weighted k‐means clustering in a nearmetric space

Weighted k‐means (WK‐means) is a well‐known method for automated feature weight learning in a conventional k‐means clustering framework. In this paper, we analytically explore the strong consistency of the WK‐means algorithm under independent and identically distributed sampling of the data points. The choice of dissimilarity measure plays a key role in data partitioning and detecting the inherent groups existing in a dataset. We propose a proof of strong consistency of the WK‐means algorithm when the dissimilarity measure used is assumed to be a nearmetric. The proof can be further extended to those dissimilarity measures which are an increasing function of a nearmetric. Through detailed experiments, we demonstrate that WK‐means‐type algorithms, equipped with a nearmetric, can be pretty effective especially when some of the features are unimportant in revealing the cluster structure of the dataset.
Using automatic clothing labeling to improve the quality of clothing retrieval systems

Desde hace varios anos que el mercado de las ventas en linea presenta un crecimiento sostenido debido a la oportunidad y facilidad que le entrega a usuarios de las nuevas tecnologias para adquirir lo que ellos deseen sin tener que salir de sus casas. Un caso particular de este fenomeno es la industria de la moda. Esto ultimo se ve favorecido principalmente por el uso masivo de redes sociales, las cuales le permiten a los usuarios compartir la manera en que se visten convirtiendose en iconos de la moda solo al subir fotos. Varias tiendas y redes sociales han visto este hecho como una oportunidad de negocio, la cual consiste en permitirle a sus usuarios tomar fotos de sus idolos de moda y buscar en diferentes tiendas prendas similares a las que ellos ocupan, de manera de ``compartir'' su estilo. En la comunidad de vision por computadora este proceso se trata como un problema de busqueda por similitud. Esto es, dada una consulta, mostrar al usuario los productos que se parecen mas al objeto buscado. En el caso de la moda la problematica surge al intentar comparar las consultas con las imagenes de los catalogos de diferentes tiendas, ya que estas ultimas tienden a presentar a una modelo usando mas de una prenda que la imagen trata de representar, lo que se traduce en que la imagen de consulta y las de los catalogos no son comparables directamente. Este ultimo punto empeora la calidad de los resultados de cualquier sistema de recuperacion. Considerando el problema anterior es que este trabajo busca estudiar metodos de etiquetado (o deteccion) de ropa que permitan descubrir las reales zonas de interes de las imagenes de los catalogos de manera de poder comparar estas regiones con las consultas. De esta manera nuestra hipotesis es que el usar metodos de etiquetado de ropa para preprocesar los catalogos mejora la calidad de los sistemas de recuperacion con respecto a los resultados obtenidos sin pre procesarlos. Entrenamos Faster R-CNN y YOLOv2 como metodos de etiquetado, de los cuales Faster R-CNN presenta mejores resultados. Para entrenar estos metodos recolectamos un dataset con alrededor de 150,000 imagenes etiquetadas. Los datos se recolectan usando crowd sourcing. Una vez entrenados dos metodos de etiquetado presentamos experimentos que permiten medir la calidad del etiquetado, y luego otros que permiten validar nuestra hipotesis. Estos ultimos experimentos miden la calidad de la recuperacion con respecto al estado del arte en funcion de dos puntos: calidad de los resultados y usabilidad en una aplicacion real. Vemos que la calidad de los resultados al usar el etiquetado es similar a la de los metodos del estado del arte, sin embargo, nuestro metodo se traduce en tiempos de busqueda 18x menores. Finalmente presentamos los resultados de dichos experimentos presentando metricas estandar que permiten medir la calidad de los resultados. Ademas se analiza la usabilidad de las tecnicas presentadas. Mostramos ademas ejemplos visuales de los resultados obtenidos.