Miracle-dz/UniFAR-FTUs huggingface dataset:
Ligand based 3D-QSAR approach of EGFR

This Human epidermal growth factor receptor (EGFR) family is one of the most studied protein family in various cell signaling mechanisms. It contains four membrane bound receptors namely epidermal growth factor receptor 14.Aberrant activation of ErbB receptor family proteins and their role in intra cellular signaling mechanisms and their mutations lead to cause the numerous human diseases. The first generation inhibitors failed to bind with the EGFR due to T790M mutation. The second generation inhibitors overcome the resistance when compared to the first generation compounds but failed in approval level. Reported publication data given a clear idea to develop new class inhibitors against the EGFR proteins. In this study, ligand based pharmacophore modeling and 3D-QSAR studies were carried out with the 100 ligands of EGFR. Fifteen pharmacophore hypotheses were developed and common AADRR hypothesis was selected for QSAR analysis. Further the model was screened against the 3D database of twenty million entries and 1436 structure analogues were obtained and subjected to XP docking with EGFR grid in GLIDE. One lead molecule is having the best binding interactions than the existing inhibitors. Lead 1 is further subjected to QPLD, IFD, binding free energy and molecular dynamics studies which deciphered better binding interactions with EGFR. Thus lead1was proposed as a novel lead against the EGFR.
THE RELATIONSHIP BETWEEN LOWER LIMB COORDINATION AND WALKING SPEED FOLLOWING STROKE: AN OBSERVATIONAL STUDY

i STATEMENT OF AUTHORSHIP . iii ACKNOWLEDGMENTS . v LIST OF TABLES . viii LIST OF FIGURES . x PUBLICATIONS AND PRESENTATIONS . xi CHAPTER 1: INTRODUCTION . 1 RATIONALE OF THE STUDY . 2 CONTRIBUTION OF IMPAIRMENTS TO WALKING DISABILITY AFTER STROKE . 5 NATURE OF INCOORDINATION AFTER STROKE . 10 MEASUREMENT OF COORDINATION . 12 AIMS AND RESEARCH QUESTIONS . 15 CHAPTER 2: METHODS . 17 DESIGN . 18 PARTICIPANTS . 18 OUTCOME MEASURES . 22 DATA REDUCTION . 25 DATA ANALYSIS . 28 CHAPTER 3: RESULTS . 29 CHARACTERISTICS OF PARTICIPANTS . 30 COORDINATION AND WALKING . 31 RELATIONSHIP BETWEEN THE TWO WALKING TESTS . 34
Brain Connectivity Analysis Under Semantic Vigilance and Enhanced Mental States

In this paper, we present a method to quantify the coupling between brain regions under vigilance and enhanced mental states by utilizing partial directed coherence (PDC) and graph theory analysis (GTA). The vigilance state is induced using a modified version of stroop color-word task (SCWT) while the enhancement state is based on audio stimulation with a pure tone of 250 Hz. The audio stimulation was presented to the right and left ears simultaneously for one-hour while participants perform the SCWT. The quantification of mental states was performed by means of statistical analysis of indexes based on GTA, behavioral responses of time-on-task (TOT), and Brunel Mood Scale (BRMUS). The results show that PDC is very sensitive to vigilance decrement and shows that the brain connectivity network is significantly reduced with increasing TOT, p < 0.05. Meanwhile, during the enhanced state, the connectivity network maintains high connectivity as time passes and shows significant improvements compared to vigilance state. The audio stimulation enhances the connectivity network over the frontal and parietal regions and the right hemisphere. The increase in the connectivity network correlates with individual differences in the magnitude of the vigilance enhancement assessed by response time to stimuli. Our results provide evidence for enhancement of cognitive processing efficiency with audio stimulation. The BRMUS was used to evaluate the emotional states of vigilance task before and after using the audio stimulation. BRMUS factors, such as fatigue, depression, and anger, significantly decrease in the enhancement group compared to vigilance group. On the other hand, happy and calmness factors increased with audio stimulation, p < 0.05.
Evidence Synthesis for Decision Making 1: Introduction. Medical Decision Making,

We introduce the series of 7 tutorial papers on evidence synthesis methods for decision making, based on the Technical Support Documents in Evidence Synthesis prepared for the National Institute for Health and Clinical Excellence (NICE) Decision Support Unit. Although oriented to NICE’s Technology Appraisal process, which examines new pharmaceutical products in a cost-effectiveness framework, the methods presented throughout the tutorials are equally relevant to clinical guideline development and to comparisons between medical devices, or public health interventions. Detailed guidance is given on how to use the other tutorials in the series, which propose a single evidence synthesis framework that covers fixed and random effects models, pairwise meta-analysis, indirect comparisons, and network meta-analysis, and where outcomes expressed in several different reporting formats can be analyzed without recourse to normal approximations. We describe the principles of evidence synthesis required by the 2008 revision of the NICE Guide to the Methods of Technology Appraisal and explain how the approach proposed in these tutorials was designed to conform to those requirements. We finish with some suggestions on how to present the evidence, the synthesis methods, and the results.
WHY DOES HIERARCHY (SOMETIMES) WORK

Hierarchical reinforcement learning has demonstrated significant success at solving difficult reinforcement learning (RL) tasks. Previous works have motivated the use of hierarchy by appealing to a number of intuitive benefits, including learning over temporally extended transitions, exploring over temporally extended periods, and training and exploring in a more semantically meaningful action space, among others. However, in fully observed, Markovian settings, it is not immediately clear why hierarchical RL should provide benefits over standard “shallow” RL architectures. In this work, we isolate and evaluate the claimed benefits of hierarchical RL on a suite of tasks encompassing locomotion, navigation, and manipulation. Surprisingly, we find that most of the observed benefits of hierarchy can be attributed to improved exploration, as opposed to easier policy learning or imposed hierarchical structures. Given this insight, we present exploration techniques inspired by hierarchy that achieve performance competitive with hierarchical RL while at the same time being much simpler to use and implement.
CapsNet Clean : Recons : PGD : Recons : PGD : Recons : PGD : Recons

Adversarial examples raise questions about whether neural network models are sensitive to the same visual features as humans. In this paper, we first detect adversarial examples or otherwise corrupted images based on a class-conditional reconstruction of the input. To specifically attack our detection mechanism, we propose the Reconstructive Attack which seeks both to cause a misclassification and a low reconstruction error. This reconstructive attack produces undetected adversarial examples but with much smaller success rate. Among all these attacks, we find that CapsNets always perform better than convolutional networks. Then, we diagnose the adversarial examples for CapsNets and find that the success of the reconstructive attack was proportional to the visual similarity between the source and target class. Additionally, the resulting perturbations can cause the input image to appear visually more like the target class and hence become nonadversarial. These suggest that CapsNets use features that are more aligned with human perception and address the central issue raised by adversarial examples.
Homestay Employees Empowerment In Front Office Division Toward Competency Standard Practices To Improve The Services Quality In Kupang City

Kupang City is a multi-cultural and transit city for tourists who want to continue their journey to other islands in East Nusa Tenggara. Thus, Kupang City can be the potential to bring tourists with short length stay visits and the homestay significantly increases every year. For visitors, the role of the front office and hospitality service functions, even employees or hosts play an important role in supporting visitor service activities. The research uses a descriptive approach and sample methods by collecting survey data, observations, questionnaires, and interviews assisted by National Occupational Certification Schemes, which is front office employees and hosts of the homestay. As a result, this study determines the standard competency level of the front office employees or hosts services and help them in improving the quality of their services so that tourists have the maximum experience while staying and exploring the exotic of Kupang City.
Influence of Variable Selection and Forest Type on Forest Aboveground Biomass Estimation Using Machine Learning Algorithms

Forest biomass is a major store of carbon and plays a crucial role in the regional and global carbon cycle. Accurate forest biomass assessment is important for monitoring and mapping the status of and changes in forests. However, while remote sensing-based forest biomass estimation in general is well developed and extensively used, improving the accuracy of biomass estimation remains challenging. In this paper, we used China’s National Forest Continuous Inventory data and Landsat 8 Operational Land Imager data in combination with three algorithms, either the linear regression (LR), random forest (RF), or extreme gradient boosting (XGBoost), to establish biomass estimation models based on forest type. In the modeling process, two methods of variable selection, e.g., stepwise regression and variable importance-base method, were used to select optimal variable subsets for LR and machine learning algorithms (e.g., RF and XGBoost), respectively. Comfortingly, the accuracy of models was significantly improved, and thus the following conclusions were drawn: (1) Variable selection is very important for improving the performance of models, especially for machine learning algorithms, and the influence of variable selection on XGBoost is significantly greater than that of RF. (2) Machine learning algorithms have advantages in aboveground biomass (AGB) estimation, and the XGBoost and RF models significantly improved the estimation accuracy compared with the LR models. Despite that the problems of overestimation and underestimation were not fully eliminated, the XGBoost algorithm worked well and reduced these problems to a certain extent. (3) The approach of AGB modeling based on forest type is a very advantageous method for improving the performance at the lower and higher values of AGB. Some conclusions in this paper were probably different as the study area changed. The methods used in this paper provide an optional and useful approach for improving the accuracy of AGB estimation based on remote sensing data, and the estimation of AGB was a reference basis for monitoring the forest ecosystem of the study area.
Cultural Values’ Dimensions of Tambak Lorok Fisheries Community

This study is about categorizing Tambak Lorok fisheries community based on the cultural values they share. The community is unique because even though they live in suburb area near metropolis city, based on the observation, the social practice articulated by the community show that there is influence of the traditional Javanese values. This interests us to do serious research, because the finding will be benefit for making policy regarding their social roles. Data are text produced by five informants selected randomly. To collect the data, depth interview is used. The result shows that Tambak Lorok fisheries community tends to be the community that are harmonious, collective, hierarchical, and have high power distance. This is different from the cultural values shared by general fisheries communities. This may be influenced by the valued shared by the Javanese community in general. The abstract needs to summarize the content of the paper.
What motivates posting online travel reviews? Integrating gratifications with technological acceptance factors

Purpose –The aim of the present study is to understand the effect of travelers’ motivations and technological acceptance factors on intentions to post online reviews. Design-Uses and gratification and the extended unified theory of acceptance and use of technology (UTAUT2) were applied as the basis of the present study. Methodology – A structured questionnaire was designed on the basis of the previous literature. 600 questionnaires were distributed out of which 273 valid responses were considered for statistical analysis. Findings – The results reveal that altruism, reciprocity, effort expectancy, habit and hedonic motivations have positive influence, whereas economic rewards negatively influence the intentions of travelers to post online reviews. However, there is no significant relationship between social influence and review posting intentions of travelers. Moreover, a significant relationship was observed between altruism and effort expectancy; reciprocity and effort expectancy and habit and effort expectancy. Further, both behavioural intentions and habit were significant predictors of actual usage. Originality/ Value – The present study is among the few studies which investigate the effect of motivational factors in conjunction with technological acceptance factors on travel review posting intentions.
Influence of the Duration of Microwave Irradiation of Scots Pine (Pinus sylvestris L.) Cones on the Quality of Harvested Seeds

To improve the process of seed extraction, new solutions have been investigated in an attempt to develop guidelines for the construction of small seed extraction equipment. One of the solutions proposed in this field is the use of electromagnetic radiation in the first stage of hulling cones, reducing their initial moisture content, which will result in quicker scale opening. It is proposed that cones should be irradiated for a relatively short period in the first stage. This operation will allow a quicker loss of moisture from the cones that are still closed, which will result in a more intensive opening of cone scales and will also positively affect the exposure of seeds for the next phase of hulling. The aim of the study was to evaluate the effect of microwave irradiation of pine cones on the quality of the seeds obtained. Cones were exposed to microwaves produced by an 800 W generator. The research was performed in several modes, in which the variable parameters were the duration of microwave irradiation, arrangement of cones with the apex pointed towards either the inner or outer part of the turntable, and the number of cones. The temperature distribution on the surface of and inside the cones was determined using the THERM v2 (Vigo System SA, Ozarow Mazowiecki, Poland) thermal image processing software. We also assessed the energy (vitality) and germinability (quality class) of seeds that were not exposed and those after microwave treatment. The results of the research allowed us to state that, with the assumed parameters of the process, it is possible to obtain second quality class seeds after exposure to microwaves for 5 s. This result was comparable to the quality of seeds obtained without the use of microwaves. When the irradiation time was increased above 5 s, the vitality of seeds decreased and their quality was not satisfactory.
CT reconstructions and relationships of the Early Cretaceous tribosphenidan mammal, Slaughteria eruptens (Trinity Group Texas, USA)

Among the nine taxa of tribosphenidan (boreosphenidan) mammals named from the Early Cretaceous Trinity Group of Texas and Oklahoma, Slaughteria eruptens provides unique information about the evolution of tooth replacement. High-resolution CT scans and SEM imagery elucidate the jaw anatomy of S. eruptens. Associated upper and lower dentitions from Asian Cretaceous mammals provide the basis for a statistical model to quantify the tooth size relationships of the often cited Trinity Group mammals Pappotherium pattersoni and Holoclemensia texana, which were named based upon upper molar teeth. Two groups of Trinity mammals are evident based on lower molar size. Most large teeth are referable to H. texana. The lower m1 of S. eruptens fits neatly into the size range predicted for lower molars of P. pattersoni, and it shares compatible tooth cusp relationships. Slaughteria eruptens is regarded most parsimoniously as a junior synonym of P. pattersoni. Pappotherium pattersoni thus shares the alternate premolar replacement pattern of more primitive therian mammals and basal eutherians, but lacks any hint of a submolariform last premolar, as typifies Eutheria. Other small therian mammal teeth from the Trinity Group should be evaluated as possible deciduous teeth. Dale A. Winkler. Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275 USA. dwinkler@smu.edu Louis L. Jacobs. Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275 USA. jacobs@smu.edu Yoshi Kobayashi. Hokkaido University Museum, N10 W8 Kita Ku, Sapporo, Hokkaido 060-0810, Japan. ykobayashi@museum.hokudai. ac.jp Michael J. Polcyn. Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275 USA. mpolcyn@smu.edu
An Inter- and Intraindividual Perspective of the Substitutability of Fairness Rules for Trust Within Teams

The present study longitudinally assesses fairness allocation rule importance and equity allocation preference under conditions of evolving team trust. We predicted an interchangeable relationship between trust and allocation rules using an uncertainty management theory framework (Lind & Van den Bos, 2002; Van den Bos & Lind, 2002). From an interindividual perspective, lower initial trust toward team members predicted a higher degree of importance for the use of preferred allocation rules and greater use of the equity heuristic. An intraindividual change in trust predicted an inverse change in use of the equity heuristic, but not the expected change in allocation rule importance. Implications of these results for future research and practice are discussed. jasp_831 850.873
GQ-Net: Training Quantization-Friendly Deep Networks

Network quantization is a model compression and acceleration technique that has become essential to neural network deployment. Most quantization methods perform fine-tuning on a pretrained network, but this sometimes results in a large loss in accuracy compared to the original network. We introduce a new technique to train quantization-friendly networks, which can be directly converted to an accurate quantized network without the need for additional fine-tuning. Our technique allows quantizing the weights and activations of all network layers down to 4 bits, achieving high efficiency and facilitating deployment in practical settings. Compared to other fully quantized networks operating at 4 bits, we show substantial improvements in accuracy, for example 66.68% top-1 accuracy on ImageNet using ResNet-18, compared to the previous state-of-the-art accuracy of 61.52% Louizos et al. (2019) and a full precision reference accuracy of 69.76%. We performed a thorough set of experiments to test the efficacy of our method and also conducted ablation studies on different aspects of the method and techniques to improve training stability and accuracy. Our codebase and trained models are available on GitHub.
Video Motion Depth Motion Depth Depth Depth

We propose DeepV2D, an end-to-end deep learning architecture for predicting depth from video. DeepV2D combines the representation ability of neural networks with the geometric principles governing image formation. We compose a collection of classical geometric algorithms, which are converted into trainable modules and combined into an end-to-end differentiable architecture. DeepV2D interleaves two stages: motion estimation and depth estimation. During inference, motion and depth estimation are alternated and converge to accurate depth. Code is available https://github.com/princeton-vl/DeepV2D.
HOW LEADER ALIGNMENT OF WORDS AND DEEDS AFFECTS FOLLOWERS: A META-ANALYSIS OF BEHAVIORAL INTEGRITY RESEARCH

Substantial recent research examines the follower consequences of leader (mis)alignment of words and deeds, but no research has quantitatively reviewed these effects. This study examines extant research on behavioral integrity (BI) and contrasts it with two other constructs that focus on (mis)alignment: moral integrity and psychological contract breaches. We compare effect sizes between the three constructs, and find that BI has stronger effects on trust, in-role task performance and citizenship behavior (OCB) than moral integrity and stronger effects on commitment and OCB than psychological contract breach. These stronger attitudinal consequences run counter to our initial expectations, but they provide evidence of important conceptual distinctions and mechanisms that we articulate. BI theory suggests that BI’s greater performance impact is due to the notion that BI affects communication clarity in addition to attitudes. Results of meta-analytic structural equation modeling are consistent with this proposed dual path of BI’s impact. We highlight avenues for future research on BI and discuss how our findings inform the broader research on leader (mis)alignment.
S1478951519000269jra 1..9

Objective. In the emotionally intense field of healthcare, the ability to peacefully inhabit one’s body, maintain good boundaries, and be fully present during care is essential. This study aimed to validate the recently developed Mindful Self-Care Scale (MSCS) among hospice and healthcare professionals and develop a brief version of the 33-item MSCS. Method. A sample of hospice and healthcare professionals from all 50 states (n = 858) was used. A confirmatory factor analysis was run using a rigorous methodology for validation and item reduction to develop a brief version of the 33-itemMSCS. The brief MSCS (B-MSCS) was developed by identifying items for exclusion through examination of conceptual overlap, descriptive statistics by detecting sources of improvement model fit using confirmatory factor analysis. Model modifications were done sequentially and with regard to theoretical considerations. Result. The existing model, 33-item MSCS with six subscales, had good fit to the data with all indicators in acceptable ranges (chi-square/df = 3.08, df (480), p < 0.01, root mean square error of approximation = 0.059, comparative fit index = 0.915, Tucker and Lewis’s index of fit = 0.907). Nine items were excluded on the basis of very low loadings and conceptual and empirical overlap with other items. Significance of results. The final 24-item, B-MSCS model was consistent with the original conceptual model and had a closer fit to the data (chi-square/df = 1.85, df (215), p < 0.01, root mean square error of approximation = 0.041, comparative fit index = 0.961, Tucker and Lewis’s index of fit = 0.955). In addition, the reliability, construct, and concurrent validity of the MSCS and B-MSCS were in the acceptable and good ranges, respectively. Mean and standard deviation of the MSCS and B-MSCS scores were similar; B-MSCS mean scores well approximated the MSCS scores. Informal mindful self-care, in the process of everyday life, was practiced more regularly and associated with increased wellness and reduced burnout risk than formal mind-body practices.