Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatiotemporal Degradation of Abandoned Farmland and Associated Eco-Environmental Risks in the High Mountains of the Nepalese Himalayas

Globally, farmland abandonment has been a major phenomenon for eco-environmental and social landscape changes in the mountain regions. Farmland abandonment led to endangering the capacity of mountain ecosystems as well as variety of eco-environmental processes that play a pivotal role in regional as well local level eco-environment security. This research aims to (i) assess the spatiotemporal degradation of abandoned farmlands, (ii) identify the major causes of farmland degradation, and (iii) analyze the eco-environmental risks triggered or exacerbated by the degradation of abandoned farmlands. We conducted an inventory of the spatiotemporal distribution of abandoned farmlands and their degradation status with Google earth images and by modeling and interpreting low-height remote sensing images taken by an unmanned aerial vehicle (UAV). Geomorphic damages were mapped at the scale of individual abandoned farms. A multivariate regression statistical (MRS) model was used to identify the major causes of degradation. This research revealed that out of the total surveyed farmlands, 92% were already completely irreversibly damaged. The damages started with the disruption of terraces and bulging processes that occurred within the year after abandonment. This degradation induced diverse hazardous processes, such as landslides, debris flows, rock falls, the formation of gullies, soil erosion, and the development of sinkholes, which increase the negative effects of on both land resources and plant succession. Farmland abandonment does not automatically lead to plant colonization because geomorphic damage is intensified prior to colonization. Therefore, land management is required for plant colonization as well as other efforts to reduce degradation induced eco-environmental risk. This study thus could help land planners and environmentalists in the development of suitable guidelines (pre- or post-abandonment) plans, programmes, and legislation to effectively address the problem of abandoned farmland.
Research on the Influence of Board Governance on Enterprise Value - Mediating Effect based on R&D Investment of Listed Energy Companies

In order to promote energy enterprises to straighten out the board governance mechanism and ensure the standardization and modernization of enterprise management, based on the data of listed energy companies from 2013 to 2017, this paper studies the influence of board governance on enterprise value and the transmission mechanism of R&D investment from the perspective of R&D investment. The results showed that the size of the board of directors, the number of board meetings and the total annual salary of directors were significantly positively correlated with the enterprise value, while the combination of two positions, the proportion of independent directors and the shareholding of directors were significantly negatively correlated. Research and development investment show partial or complete mediating effect. Based on this, the paper puts forward some Suggestions on how to improve board governance and incentive mechanism, as well as how to coordinate R&D investment to enhance the enterprise value of listed energy companies.
UNIVERSIDADE FEDERAL DO RIO GRANDE DO NORTE CENTRO DE CIÊNCIAS DA SAÚDE PROGRAMA DE PÓS-GRADUAÇÃO EM FISIOTERAPIA VELOCIDADE DA MARCHA COMO PREDITOR DE FRAGILIDADE EM UMA AMOSTRA POPULACIONAL DE IDOSOS BRASILEIROS

Gait speed has been described as a predictive indicator of important adverse outcomes in older populations. Among the criteria to evaluate frailty, gait speed has been identified as the most reliable predictor of fragility, practical and low cost. Objective: This study assesses the discriminating capability of gait speed in determining the presence of fragility in the elderly community in northeast of Brazil. Method: We performed an observational analytic study with a transversal character with a sample of 391 community-living elders, aged 65 years or older, of both sexes, in the city of Santa Cruz-RN. Participants were interviewed using a multidimensional questionnaire to obtain sociodemographic information, physical-related and mental health-related information. The unintentional weight loss, muscle weakness, self-reported exhaustion, slow gait and low-physical activity were considered to evaluate the frailty syndrome. Gait velocity was measured as the time taken to walk the middle 4,6 meters of 8,6 meters (excluding 2 meters to warm-up phase and 2 meters to deceleration phase). We calculate the sensitivity and specificity of gait speed test in different cutoff points for the test run time, from which ROC curve was constructed as a measure of test predictive value to identify frail elders. The prevalence of frailty in Santa Cruz-RN was 17.1%. The gait speed test accuracy was 71%when speed is below 0,91m/s. Among women, the gait speed test accuracy was 80%(gait speed below 0.77m/s) and among men, the test accuracy was 86% (gait spend below 0,82%) (p<0,0001). Conclusion: our findings have clinical relevance when we consider that the detection of frailty presence by the gait speed test can be observed in elderly men and women by a simple, cheap and efficient exam.
DAD-FF: Hardening Designs by Delay-Adjustable D-Flip-Flop for Soft-Error-Rate Reduction

For the safety-critical applications such as biomedical and automobile electronics, the system failure induced by soft errors becomes a major issue of reliability. However, most of the commercial cell libraries do not include radiation-hardened components to build a safety-critical design. Therefore, a delay-adjustable D-flip-flop (DAD-FF) is proposed together with a design flow to construct a radiation-hardened system by automation. To enable such radiation-hardened design into the current design flow, DAD-FF is characterized as a general cell and compiled as a patch in the NanGate FreePDK45 bulk 45-nm open cell library, as an example. The experimental results show that DAD-FF is capable of reducing $1.3\times 10^{10}\text{X}$ soft errors with respect to the standard flip-flop (STD-FF) and resisting over 99.999997% strikes of heavy ions. Meanwhile, four radiation-hardened benchmark circuits are synthesized with DAD-FF cell, and further used to prove the effectiveness against soft errors compared to a prior work, built-in soft-error resilience (BISER), with 18% area and 40% timing improvement. To sum up, DAD-FF is elaborated from the modeling at the device-level to the validation at the system-level and exhibits its strong robustness to soft errors.
Natural drug leads as novel DPP-IV inhibitors targeting the management of type 2 diabetes mellitus

Aim: Number of type 2 diabetes mellitus (T2DM) patients using incretin based therapeutics has significantly increased in past few years. The development of novel incretin based therapeutics from natural sources has become an interesting area of drug discovery. The current review emphasizes the plants having DPP-IV inhibitory activity that can be used in the development of novel anti-diabetic agents. Methods: The relevant literature was collected form data sources as PubMed, Web of Science and Google Scholar. The references of articles were also examined to obtain further information. Results: To date, number of plants were documented for its� antidiabetic potential through DPP-IV inhibitory activity either in vivo or in vitro. The compounds which exert potent DPP-IV inhibitory action have been identified and their structures have been deduced in some research findings. The DPP-IV inhibitory activity has been compared with positive controls in most of the studies. Conclusion: The present review reports on natural DPP-IV inhibitors through the assessment of plant profile used in the management of DM and highlights a new pathway for the researches to develop novel molecules from herbal sources with DPP-IV inhibitory activity.
Depresión en adolescentes asociados a migración familiar, familia disfuncional y bullying en Huánuco 2018

Objetivos: Determinar si la migración familiar, la familia disfuncional y el bullying están asociados a la depresión en adolescentes en la I.E. Pedro Sánchez Gavidia de Huánuco. Materiales y métodos: estudio transversal correlacional ya que trata de evaluar la relación existente entre las variables en un mismo periodo de tiempo. La población fue de 400 adolescentes de los cuales se seleccionó con un muestreo aleatorio no probabilístico por estratos con un nivel de confianza del 95% (α< 0,05), una precisión absoluta de 5%. Resultados: De los 165 estudiantes adolescentes, el 16,4% presentaron sintomatología depresiva, el 54,5% fueron de sexo femenino, la media de las edades fue 14,53 años. Además, el 26,1 % provenían de otras regiones, 47,9% había sufrido algún tipo de bullying, el 21,8% presentaban disfuncionalidad familiar y el 39,40% presentaron una baja autoestima. El bullying (IC 95%; p=0,003) y autoestima (IC 95%; p=0,00) presentaron una relación significativa con la depresión. Conclusiones: Se determinó un porcentaje importante de depresión en los adolescentes, que fue mayor en el sexo femenino. Así mismo, se obtuvo relación significativa entre depresión - bullying y depresión –autoestima (variable interviniente); no se encontró asociación con migración familiar, ni disfunción familiar.
Superfície seletiva de frequências inteligente baseada em grafeno

Neste trabalho, uma formulacao baseada no metodo das diferencas finitas no dominio do tempo (FDTD) e na tecnica exponencial matriz e desenvolvida para modelar folhas de grafeno de espessura infinitesimal. Esta formulacao e validada atraves da reproducao numerica de problemas envolvendo superficies seletivas de frequencia (FSS) baseadas em grafeno, conhecidas na literatura. Dessa forma, propoe-se neste trabalho um dispositivo FSS de grafeno inteligente. Essa caracteristica e obtida por meio de uma celula unitaria formada por um anel de grafeno com uma folha de grafeno colocada em sua abertura. Atraves da regulacao apropriada dos potenciais quimicos dos elementos de grafeno, sao obtidos dois modos de operacao sintonizaveis em frequencia: modos de rejeicao single- ou dual-band. Quando o dispositivo opera em seu modo de rejeicao dual-band, qualquer uma das bandas de rejeicao pode ser deslocada individualmente no espectro de frequencias. Alem disso, ambas as bandas de rejeicao tambem podem ser reconfiguradas simultaneamente. Com o dispositivo operando no modo de rejeicao single-band, e possivel, tambem, deslocar sua banda de rejeicao no espectro de frequencias.
Whole-Genome Comparisons of Staphylococcus agnetis Isolates from Cattle and Chickens

Staphylococcus agnetis has been recently recognized as associated with disease in dairy cattle and meat-type chickens. The infections appear to be limited in cattle and systemic in broilers. This report details the molecular relationships between cattle and chicken isolates in order to understand how this recently recognized species infects different hosts with different disease manifestations. The data show that the chicken and cattle isolates are very closely related, but the chicken isolates all cluster together, suggesting a single jump from cattle to chickens. ABSTRACT Staphylococcus agnetis has been previously associated with subclinical or clinically mild cases of mastitis in dairy cattle and is one of several staphylococcal species that have been isolated from the bones and blood of lame broilers. We reported that S. agnetis could be obtained frequently from bacterial chondronecrosis with osteomyelitis (BCO) lesions of lame broilers (A. Al-Rubaye et al., PLoS One 10:e0143336, 2015 [https://doi.org/10.1371/journal.pone.0143336]). A particular isolate, S. agnetis 908, can induce lameness in over 50% of exposed chickens, exceeding normal BCO incidences in broiler operations. We reported the assembly and annotation of the genome of isolate 908. To better understand the relationship between dairy cattle and broiler isolates, we assembled 11 additional genomes for S. agnetis isolates, an additional chicken BCO strain, and ten isolates from cattle milk, mammary gland secretions, or udder skin from the collection at the University of Missouri. To trace phylogenetic relationships, we constructed phylogenetic trees based on multilocus sequence typing and genome-to-genome distance comparisons. Chicken isolate 908 clustered with two of the cattle isolates, along with three isolates from chickens in Denmark and an isolate of S. agnetis we isolated from a BCO lesion on a commercial broiler farm in Arkansas. We used a number of BLAST tools to compare the chicken isolates to those from cattle and identified 98 coding sequences distinguishing isolate 908 from the cattle isolates. None of the identified genes explain the differences in host or tissue tropism. These analyses are critical to understanding how staphylococci colonize and infect different hosts and potentially how they can transition to alternative niches (bone versus dermis). IMPORTANCE Staphylococcus agnetis has been recently recognized as associated with disease in dairy cattle and meat-type chickens. The infections appear to be limited in cattle and systemic in broilers. This report details the molecular relationships between cattle and chicken isolates in order to understand how this recently recognized species infects different hosts with different disease manifestations. The data show that the chicken and cattle isolates are very closely related, but the chicken isolates all cluster together, suggesting a single jump from cattle to chickens.
Early identification of anxiety disorders: The role of the pediatrician in primary care

ABSTRACT Anxiety disorders are the most common psychiatric disorder of childhood, and are associated with high risk for development of future psychopathology. Yet, pediatric anxiety disorders continue to be under diagnosed in primary care, leaving many children untreated. Pediatricians in primary care settings are in a unique position to detect child anxiety within the context of well-child visits. While important efforts are currently under way, such as increased behavioral screening, one of the most important challenges is that pediatricians do not receive an adequate level of training in the evaluation, management, and treatment of anxiety disorders. We review recent assessment initiatives in this area and call for increased efforts to promote early detection in primary care and reduce potential barriers for pediatricians, consistent with the movement toward integrated behavioral health models. Finally, we describe a current initiative that utilizes collaboration between psychologists and pediatric faculty to train pediatric residents to detect, diagnose, counsel, and refer young children with anxiety.
Meta-Analysis: Satu Dekade Penelitian Manajemen Laba di Indonesia

This study aims to examine whether corporate characteristics and information asymmetry affects earnings management in Indonesia. This study use meta-analysis techniques approach with 35 samples from international and national accredited journals as well as Indonesian National Symposium of Accounting proceedings. Research results reinforce meta- analysis findings of previous studies where earnings management is done for different purposes. Management’s motivation to perform earnings management varies between opportunistic and efficient contract motives. Empirical evidence shows that corporate characteristics are predictors of earnings management. Cash flow from operations and information asymmetry significantly affect earnings management. This empirical evidence supports several previous meta-analysis in accounting field where moderator measurement variables has an effect on heterogeneity of research findings.
Numerical taxonomic study of some euphorbiaceae species within Ambrose Alli University Main Campus, Edo State, Nigeria

Numerical taxonomic studies have been described as highly effective in plant classification and delimitation even in difficult cases. This study employed numeric taxonomic methods in studying different Euphorbiaceae species within Ambrose Alli University campus with the goal of identifying similarities and differences between different species within the family. Twenty-five species comprising thirteen genera were studied using thirty-five morphological characters which included plant habit, colour of leaf, fruit shape, presence of sap, pubescence of leaves, presence of three-cell ovary, and inflorescence type. Data generated from the different morphological characters were scored and converted to binary numbers used for generating clusters of the Operation Taxonomic Units (OTUs) according to their overall similar Euclidean distance. Using both single and complete linkage, dendrograms were drawn to illustrate the relationship among the species. The dissimilarity shown in the OTUs were split into two clusters, C1 and C2 each comprising 10 and 15 species respectively. Species within the same cluster had greater similarity than those in the other cluster. Amongst diverse findings from the study is a great affinity between Jatropha curcas and Jatropha tanjorensis , Alcornea laxifolia and Mallotus oppositifolius ; Hevea brasilensis and Croton zambesicus ; and Acalypha hispida and Alcalypha wikisiena . Great dissimilarity was observed between Riccinodendron heudelotti and Euphorbia milli . The results from this study have shown that there is great similarity, and at the same time variety and heterogeneity among the different species of Euphorbiaceae considered. Keywords: Dendrogram; Euphorbiaceae; Numerical Taxonomy; Species
PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detection

Surface defect detection is a critical task in industrial production process. Nowadays, there are lots of detection methods based on computer vision and have been successfully applied in industry, they also achieved good results. However, achieving full automation of surface defect detection remains a challenge, due to the complexity of surface defect, in intraclass. While the defects between interclass contain similar parts, there are large differences in appearance of the defects. To address these issues, this article proposes a pyramid feature fusion and global context attention network for pixel-wise detection of surface defect, called PGA-Net. In the framework, the multiscale features are extracted at first from backbone network. Then the pyramid feature fusion module is used to fuse these features into five resolutions through some efficient dense skip connections. Finally, the global context attention module is applied to the fusion feature maps of adjacent resolution, which allows effective information propagate from low-resolution fusion feature maps to high-resolution fusion ones. In addition, the boundary refinement block is added to the framework to refine the boundary of defect and improve the result of the prediction. The final prediction is the fusion of the five resolutions fusion feature maps. The results of evaluation on four real-world defect datasets demonstrate that the proposed method outperforms the state-of-the-art methods on mean intersection of union and mean pixel accuracy (NEU-Seg: 82.15%, DAGM 2007: 74.78%, MT_defect: 71.31%, Road_defect: 79.54%).
Productivity and profitability of maize-legume cropping systems under conservation agriculture among smallholder farmers in Malawi

ABSTRACT A study was conducted from 2014 to 2017 in Malawi to elucidate the short-term effects of maize-legume intercropping and rotation systems under conservation agriculture (CA) and conventional tillage (CT) on crop productivity and profitability. Twelve farmers hosted on-farm trials per district, in three districts, with each farmer having six plots. The design of the study was randomised complete block design arranged in a split plot fashion with tillage as main plot and cropping systems as sub-plots, with each farmer acting as a replicate. CA had 1400 and 3200 kg ha−1 more maize grain yield in the second and third seasons, respectively compared with CT. In the first two seasons, CT had 310, 180 and 270 kg ha−1 more cowpea, soybean and pigeon pea grain yields in Salima, Mzimba and Mangochi districts, respectively, compared with CA. Similarly, CA had 1100 and 950 kg ha−1 more groundnut grain yields than CT in Salima and Mzimba districts in the second and third seasons, respectively. Over the three-year study period, partial land equivalent ratio for maize ranged from 0.78 to 1.24. Largest net returns were achieved by intercropping maize with pigeon pea in Mangochi and rotating maize and groundnut in Mzimba and Salima districts.
Capturing Rationalization Bias and Differential Item Functioning: A Unified Bayesian Scaling Approach

Information about the ideological positions of different political actors is crucial in answering questions regarding political representation, polarization, and voting behavior. One way to obtain such information is to ask survey respondents to place actors on a common ideological scale, but, unfortunately, respondents typically display a set of biases when performing such placements. Key among these are rationalization bias and differential item functioning (DIF). While Aldrich–McKelvey (AM) scaling offers a useful solution to DIF, it ignores the issue of rationalization bias, and this study presents Monte Carlo simulations demonstrating that AM-type models thus can give inaccurate results. As a response to this challenge, this study develops an alternative Bayesian scaling approach, which simultaneously estimates DIF and rationalization bias, and therefore performs better when the latter bias is present.
Hyperspectral imagery classification with cascaded support vector machines and multi-scale superpixel segmentation

ABSTRACT Hyperspectral imagery (HSI) classification is a rapidly growing and highly active research area in the field of hyperspectral community. The method that combines both spatial and spectral information for hyperspectral image classification has made a great advance. The focus of spectral-spatial classification is how to extract discriminating features and how to combine the spectral and spatial information effectively. In this paper, we propose a new spectral-spatial method to solve these two problems. The first part is a series of support vector machines (SVMs) that are cascaded to form the enhanced features, where the predicted information of the preceding layer can provide correction information for the subsequent layer, and then a new superpixel segmentation method is adopted to introduce multi-scale spatial information, which can generate multi-scale superpixels at one time and is as accurate as the state-of-the-art methods. The final label is determined by majority voting of different scales.
A NEURAL NETWORK BOOSTED DOUBLE OVERDISPERSED POISSON CLAIMS RESERVING MODEL

Abstract We present an actuarial claims reserving technique that takes into account both claim counts and claim amounts. Separate (overdispersed) Poisson models for the claim counts and the claim amounts are combined by a joint embedding into a neural network architecture. As starting point of the neural network calibration, we use exactly these two separate (overdispersed) Poisson models. Such a nested model can be interpreted as a boosting machine. It allows us for joint modeling and mutual learning of claim counts and claim amounts beyond the two individual (overdispersed) Poisson models.