Miracle-dz/UniFAR-FTUs huggingface dataset:
Shared decision-making in physical therapy: a cross-sectional observational study

Abstract Background The objectives of this study were to evaluate physical therapists’ shared-decision-making behaviour in a rehabilitation centre and a private practice, to determine agreement between patients’ preferred levels of involvement in shared-decision-making and therapists’ assumptions of patients’ preferences, and to examine predictors of shared-decision-making behaviour. Methods Thirty initial physical therapy consultations were audio-recorded. Shared-decision-making behaviour was observed using the observing patient involvement (OPTION) instrument. A pre-defined threshold of ≥35/100 points was considered to represent good shared-decision-making behaviour. The Control Preferences Scale was used to measure patients’ preferred levels of involvement in shared-decision-making and therapists’ assumptions. Shared-decision-making behaviour was analysed using descriptive statistics. Predictors of shared-decision-making behaviour were analysed by multiple regression. Results Shared-decision-making OPTION ratings were a median of 50.5/100 (25th, 75th percentiles 44.0, 66.0). Agreement between patients and physical therapists regarding shared-decision-making was poor (weighted kappa −0.26 (95% confidence interval −0.51 to −0.01). Therapy settings, education and the interaction of education and work experience predicted shared-decision-making behaviour (b = 15.76, p < 0.001; b = 8.05, p < 0.05; b = −0.33, p < 0.05). Conclusion Shared-decision-making behaviour was good, and predicted by therapy setting, education and the interaction of education with work experience. Because of the limited number of institutions and therapists with MSc or PhD qualifications in this study, further research is required into the relationship between education and communication skills.
Diversification rates and phylogenies: what are we estimating, and how good are the estimates?

Species-specific diversification rates, or “tip rates”, can be computed quickly from phylogenies and are widely used to study diversification rate variation in relation to geography, ecology, and phenotypes. These tip rates provide a number of theoretical and practical advantages, such as the relaxation of assumptions of rate homogeneity in trait-dependent modeling approaches. However, there is significant confusion in the literature regarding whether these metrics estimate speciation or net diversification rates. Additionally, no study has yet compared the relative performance and accuracy of tip rate metrics. We compared the statistical performance of three model-free rate metrics (inverse terminal branch lengths; node density metric; DR statistic) and a model-based approach (BAMM). We applied each method to a large set of simulated phylogenies that had been generated under different diversification processes; scenarios included multi-regime time-constant and diversity-dependent trees, as well as trees where the rate of speciation evolves under a diffusion process. We summarized performance in relation to the type of rate variation, the magnitude of rate heterogeneity and rate regime size. We also compared the ability of the metrics to estimate both speciation and net diversification rates. We show decisively that model-free tip rate metrics estimate the rate of speciation and not net diversification. Error in net diversification rate estimates is high and increases dramatically as a function of the relative extinction rate. In contrast, error in speciation rate estimates is low and relatively insensitive to extinction. Across all diversification scenarios, BAMM inferred the most accurate tip rates and exhibited lower error than non-model-based approaches. DR was highly correlated with true speciation rates but exhibited high sample variance, and was the best metric for very small rate regimes. We found that DR and BAMM are useful metrics for studying speciation rate dynamics and trait-dependent diversification. Although BAMM was more accurate than DR overall, the two approaches have complementary strengths. Because tip rate metrics are more reliable estimators of speciation rate, we recommend that empirical studies using these metrics exercise caution when drawing biological interpretations in any situation where the distinction between speciation and net diversification is important.
Gender Differential for Smart Phone Addiction and its Predictors among Adolescents: Assessing relationship with Self Control via SEM Approach

Background: Almost a quarter of young people are so dependent on their smartphones that it has become an addiction. Mobile phone addiction is a sum effect of phubbing, internet addiction, or social media intrusion. Self-controlling behaviour is a necessity to avoid addiction. The study aims to find the gender differentials for the effect of predictors of mobile phone addiction and its effect on self-control via Smart phone addiction through SEM in two CBSE schools of Meerut, contributing a sample size of 400. Methods: Data Collection was done in part (1) Demographic information, Part (2) 5 structured scales: (i) The Phubbing Scale (ii) Adapted Mobile Phone Use Habits scale (iii) The Facebook Intrusion Questionnaire (iv) Internet Addiction Scale and (v) The Brief Self-Control Scale. Results: Male students are more phubbed (53%) than female students (25%), but the use of internet addiction is more in female students (48%) than male (33%). Self-control overall was 31%, more in males (35%) than female students (25%). Conclusion: Male students have a tendency to be more phubbed, and female students are more internet addicted. Self-controlling behaviour was less in females than their counterparts’ male students and so, were more addicted to Smart phone.
Improving Acoustic Models for Dysarthric Speech Recognition using Time Delay Neural Networks

Recently, deep learning approaches have been widely used to solve problems in the pattern recognition area, especially speech recognition. The deep structures of neural networks have made the system gain impressive performance for the normal speaker speech acoustic model. However, there has remained a challenge to build a speech recognition model for dysarthric speakers. This paper investigates the performance of speech recognition models for dysarthric speakers using time delay deep neural networks. Moreover, we also explore the model performance by combining dysarthria and normal speech corpus. Finally, well-tuned hyperparameters of deep neural network structures give promising results on Mandarin and English dysarthria speech.
The secreted salivary proteome of Asian citrus psyllid Diaphorina citri

The Asian citrus psyllid Diaphorina citri Kuwayama is a sap‐sucking hemipteran that serves as a vector for Candidatus Liberibacter asiaticus (CLas), the causal agent of citrus huanglongbing (HLB). Salivary secretions play critical roles in insect–host plant interactions and are responsible for the establishment of insect herbivory. In the present study, we aim to identify the major proteins in D. citri saliva. Saliva proteins are collected from the artificial diet upon D. citri feeding. Collected proteins are concentrated, filtered, digested and then analyzed using liquid chromatography‐tandem spectrometry (MS/MS). The MS/MS data are then analyzed by searching the D. citri genome deposited in the NCBI. Eighty‐nine proteins are identified in D. citri saliva. Eighty‐six of these proteins are from D. citri, whereas three proteins are from Wolbachia endosymbiont. The proteins identified belong to several functional groups, including enzymes, cytoskeletal proteins, sheath proteins, receptor proteins, transporter proteins, chromatin‐, RNA‐ and DNA‐binding proteins, and other proteins. These proteins could be involved in many key functions, including detoxification of plant defencee compounds and suppression of plant defence, as well as facilitation of stylet penetration, sap sucking and digestion. The identification of these proteins is an essential step for the understanding of D. citri–plant interactions. The identification of key enzymes in the saliva of D. citri could lead to a discovery of proper inhibitors that disrupt its feeding, consequently preventing the spread of the HLB pathogen.
Flight initiation distance, color and camouflage

Abstract Camouflage is widespread throughout the animal kingdom allowing individuals to avoid detection and hence save time and energy rather than escape from an approaching predator. Thus, camouflage is likely to have co-evolved with antipredator behavior. Here, we propose that camouflage results in dichotomous escape behavior within and among species with classes of individuals and species with cryptic coloration having shorter flight initiation distances (FIDs; the distance at which an individual takes flight when approached by a human). We report the results of 2 tests of this hypothesis. First, bird species with cryptically colored plumage have consistently shorter FID than closely related species without such color. Within species with sexually dimorphic plumage, brightly colored adult male common pheasants Phasianus colchicus and golden pheasants Chrysolophus pictus have long and variable FID, whereas cryptically colored juveniles and adult females have short and invariable FID. Second, FID in females was predicted by presence or absence of cryptic color, FID in males and their interaction. These findings are consistent with the hypothesis that risk-taking behavior has been attuned to camouflage, and that species with different levels of camouflage differ consistently in their FID.
Estimating Impacts of Land Use Change on Evapotranspiration for Three Agricultural Crops in Malta—A Preliminary Assessment

Estimating evapotranspiration is crucial for better management of catchment water resources. In this study, the FAO CropWat model was used to estimate reference evapotranspiration (ETo), crop evapotranspiration (ETc), and total gross water requirements for three economically important agricultural crops grown in Malta: potatoes, wheat, and vineyards for three years representative of a typically wet (2003), average (2009), and dry (2013) year. In addition, changes in ETc due to changes in land use were estimated for 2009 and 2013 relative to a 2003 baseline. Across all three years and crops, the average ETo rates were estimated to range between 3.7 mm day -1 (2003) and 4.0 mm day-1 (2013) while average ETc rates were estimated to range between 1.6 mm day-1 and 5.3 mm day-1, respectively. For all three years, the highest total gross water requirement was estimated for wheat, reaching a maximum of 1450 mm in 2013. The results suggest that changes in land use between 2003 and 2013 were the main driver for changes in crop water demand. Differences in water demand compared to 2003 were estimated to range between -38% and 60%. This could have a substantial impact on the future sustainability of Malta’s increasingly constrained water resources.
A Comparative Study of Sustainable Transition from Catch-up to Post Catch-up of South Korea and China

The essence of the experience of East Asia has been on technological capability building and dynamic industrial transitions from one stage to the next. While many studies for understanding the catch-up process and post catch-up agendas exist, empirical and comparative studies that consider the transition from catch-up to post catch-up are still rare. The significance of this research can be summarized in two ways. First, this study verifies the conformity of existing major catch-up to post catch-up transition studies with quantitative evidence. Second, by comparing commonalities and patterns from South Korea and China, this study examines the generality of the discourses and arguments about the transition from catch-up to post catch-up. The reflexive study of understanding transition from catch-up to post catch-up was conducted with a technology cycle time (TCT), self-citation ratio at a country level, and the basic research expenditure of Korea and China by using the US Patents and Trademark Office’s (USPTO) patent citation (for technology cycle time & self-citation ratio) and OECD’s database (basic research expenditure and gross domestic expenditure on basic research) for time period from 1998 to 2012. Empirical evidence of technology cycle time, self-citation ratio and gross domestic expenditure on basic research matched well with the prior transition arguments. First, Korea’s case shows a post catch-up trend with an increasing technology cycle time while China’s case presents catch-up trend (short-cycle period) and shifts to post catch-up trend (post catch-up trend). Self-citation ratios for both countries show increasing and converging pattern. In terms of basic research activities, both countries show increasing pattern. Korea exceeded the gross domestic expenditure on basic research of Japan and the US. Even though, China’s gross domestic expenditure on basic research has been tripled from 1998 to 2012, China’s gross domestic expenditure on basic research has still a long way to go to close the gap and to show a converging pattern. Many developing countries that once experienced a certain level of successful catch-up did not overcome the middle income trap have fallen behind. Understanding transition process of catch-up to post catch-up discussed in this paper may present a better understanding of long-term sequential development and economic sustainability of developing countries.
Allele Frequency of 15 Autosomal Short Tandem Repeat Loci in Iranian Population with Comparison to Some Other Population

Background: Shorttandemrepeat(STR)markersareextensivelybeingusedforhumanidentiﬁcationaswellaspaternityandforen-sic analysis of biological evidence. Objectives: The aim of this study was to investigate the allelic frequencies and several forensic and paternity parameters of 15 autosomal short tandem repeat (STR) loci D3S1358, D16S5391, D7S820, D8S1179, D21S11, D18S51, D5S818, D13S317, FGA, THO1, TPOX, CSF1PO, vWA , D2S1338, and D19S433 in the Iranian population. Methods: Estimation of allelic frequencies and several forensic and paternity parameters of 15 STR loci were performed with the AmpFLSTR Identiﬁlerr kit (Applied Biosystems) for 274 unrelated individuals living in Iran. Results: No deviation from Hardy-Weinberg equilibrium was found in any loci studied in this population. Among the 15 STR loci analyzed in the Iranian sample, the most discriminating loci were D21S11, D2S1338, D19S433, D18S51 and FGA with the highest power of discrimination. Theallelicdistributionalsowascomparedto13otherpopulationsincluding3IranianpopulationlivinginSyria, Dubai, the USA and in Fars province and 8 population from published studies of Azerbaijan, Bolu in Turkey, Morocco, Syria, Iraq, Saudi Arabia, Turkey, East Anatolia, and Pakistan. Conclusions: It was concluded that the population of present study had the least similarity with Azerbyjani (11 loci) and most similarity with the Iranian population in USA (15 loci).
Towards a fully automated surveillance of well-being status in laboratory mice using deep learning

Assessing the well-being of an animal is hindered by the limitations of efficient communication between humans and animals. Instead of direct communication, a variety of behavioral, biochemical, physiological, and physical parameters are employed to evaluate the well-being of an animal. Especially in the field of biomedical research, scientifically sound tools to assess pain, suffering, and distress for experimental animals are highly demanded due to ethical and legal reasons. For mice, the most commonly used laboratory animals, a valuable tool is the Mouse Grimace Scale (MGS), a coding system for facial expressions of pain in mice which has been shown to be accurate and reliable. Currently, MGS scoring is very time and effort consuming as it is manually performed by humans being thoroughly trained in using this method. Therefore, we aim to develop a fully automated system for the surveillance of well-being in mice. Our work introduces a semi-automated pipeline as a first step towards this goal. We use and provide a new data set of images of black-furred laboratory mice that were moving freely, thus the images contain natural variation with regard to perspective and background. The analysis of this data set is therefore more challenging but reflects realistic conditions as it would be obtainable without human intervention. Images were obtained after anesthesia (with isoflurane or ketamine/xylazine combination) and surgery (castration). We deploy two pre-trained state of the art deep convolutional neural network (CNN) architectures (ResNet50 and InceptionV3) and compare to a third CNN architecture without pre-training. Depending on the particular treatment, we achieve an accuracy of up to 99% for binary “pain”/”no-pain” classification. Author summary In the field of animal research, it is crucial to assess the well-being of an animal. For mice, the most commonly used laboratory animals, there is a variety of indicators for well-being. Especially the facial expression of a mouse can give us important information on its well-being state. However, currently the surveillance of well-being can only be ensured if a human is present. Therefore, we developed a first approach towards a fully automated surveillance of the well-being status of a mouse. We trained neural networks on face images of black-furred mice, which were either untreated or underwent anesthesia or surgery, to distinguish between an impaired and unimpaired well-being state. Our systems successfully learnt to assess whether the well-being of a mouse was impaired and, depending on the particular treatment, its decision was correct in up to 99%. A tool that visualizes the features used for the decision making process indicated that the decision was mainly based on the facial expressions of a mouse.
Emotional Coregulation Patterns of Romantic Partners

This study aims to examine the coregulation patterns in the positive and negative affect of normative romantic partners and to replicate the previous findings in the emotion regulation field. For this aim, 37 romantic couples (74 individuals) completed daily records for 14 consecutive days. We hypothesized that one’s daily positive/negative affect would be positively associated with the partner’s daily positive/negative affect. We also expected that changes in one’s daily positive/negative affect would be positively associated with changes in the partner’s daily positive/negative affect. The hypothesis was partially supported, as results of multilevel analyses revealed that partners’ daily positive and negative affect positively predict one’s own positive and negative affect. Moreover, change in partners’ positive affect positively predicted one’s own change in positive affect. Change in partners’ negative affect did not predict one’s own change in negative affect. Overall, the findings demonstrated the coregulation pattern in positive affect but not for negative affect for romantic dyads. The findings made an important contribution to the field of emotion regulation by replicating previous findings and providing further evidence for the emotional coregulation of romantic couples.
Multi-Technology Correction Based 3D Human Pose Estimation for Jump Analysis in Figure Skating

Jump analysis in figure skating is important. Recovering the 3D pose of a figure skater has become increasingly important. However, issues such as restrictions from an athlete’s clothing, self-occlusion, abnormal pose and so on will result in poor results. This paper proposes a multi-technology correction framework to obtain a 3D human pose. The framework consists of three key components: temporal information-based mutational point correction, multi-perspective-based reconstructed point selection and trajectory smoothness-based inaccurate point correction. Firstly, temporal information is used to correct the mutational points at the 2D level. Secondly, a multi-perspective is used to select the correct spatial points at the 3D level. Thirdly, trajectory smoothness is used to correct inaccuracies at the 3D level. This work will serve the purpose of displaying the 3D animated pose of a figure skater. The quality grade of the result rate on the test sequences is 87.25%.
Posisi Ulama dalam Pemilihan Gubenur Jawa Timur Perspektif Fiqh Siyasah

This paper aims to find out the Ulama's standpoint in the practice of Election of Governors from fiqh siyasah perspective. The results of the study concluded that the election of governor in East Java conducted through direct election by the people. The influence of Ulama in the election of governors and deputy governors of East Java to the people drawn the interest of politicians. It is because the Ulama have the legality, influence, and social capital that are the parameters that can influence the tide of votes in the election of the Governor of East Java that is still heavily associated with Pesantren culture. In Islam, there is no prohibition for Ulama to take part in political life as the Prophet besides being the bearer of the treatise of Allah also become as umara'. At the time of khulafaur Rasidin almost every line of sUlama held the government position. The most important thing is to be able to control the umara/government in carrying out its duties as the people's representative. This kind of indicator will elevate the image of the Ulama as a servant of God among other creatures.
Effect of Pre-Enhancement on False-Rejection Cases of Fingerprint Verification System

We investigated false-rejection problems of the active fingerprint verification system. We found that the system denies persons who own his/her identities because of his/her improper impression conditions, growth conditions, and skin conditions. These false-rejection problems resulted in a time-delay, human assistance requirement, and further investigation. We performed fingerprint pre-enhancement to improve the quality of input to alleviate these false-rejection problems. We employed five fingerprint enhancement algorithms from previously published works and one from the industry for the possibility of reducing the rejection rate. The experimental results show that the enhancement method from the industry can maximally reduce the rejection rate by 22%.
PENGARUH KINERJA KEUANGAN TERHADAP NILAI PERUSAHAAN DENGAN CSR SEBAGAI VARIABEL MODERASI

This research aims to analyze the effect of Financial Performance on Company Value and Analyze the role of Corporate Social Responsibility as a moderating variable in the effect of Financial Performance on Company Value on mining companies listed on the Stock Exchange for 2016-2018. The sampling technique in this study is the purposive sampling method and the MRA (Moderated Regression Analysis) Test is the data analysis used in this study. The model test results showed an R square value of 87.2%, so it can be concluded that the research model has a good match with the data. This means that the variable performance and CSR as a moderating have a good ability to predict variations in value on the company's value variable. Hypothesis test results concluded that financial performance variables statistically have a positive and significant effect on firm value. While CSR is also statistically proven to have a negative moderating effect on firm value.
Weighted Nonnegative Matrix Factorization for Image Inpainting and Clustering

Conventional nonnegative matrix factorization and its variants cannot separate the noise data space into a clean space and learn an effective low-dimensional subspace from Salt and Pepper noise or Contiguous Occlusion. This paper proposes a weighted nonnegative matrix factorization (WNMF) to improve the robustness of existing nonnegative matrix factorization. In WNMF, a weighted graph is constructed to label the uncorrupted data as 1 and the corrupted data as 0, and an effective matrix factorization model is proposed to recover the noise data and achieve clustering from the recovered data. Extensive experiments on the image datasets corrupted by Salt and Pepper noise or Contiguous Occlusion are presented to demonstrate the effectiveness and robustness of the proposed method in image inpainting and clustering.