Miracle-dz/UniFAR-FTUs huggingface dataset:
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding

Recently, the study on learned iterative shrinkage thresholding algorithm (LISTA) has attracted increasing attentions. A large number of experiments as well as some theories have proved the high efficiency of LISTA for solving sparse coding problems. However, existing LISTA methods are all serial connection. To address this issue, we propose a novel extragradient based LISTA (ELISTA), which has a residual structure and theoretical guarantees. Moreover, most LISTA methods use the soft thresholding function, which has been found to cause a large estimation bias. Therefore, we propose a thresholding function for ELISTA instead of soft thresholding. From a theoretical perspective, we prove that our method attains linear convergence. Through ablation experiments, the improvements of our method on the network structure and the thresholding function are verified in practice. Extensive empirical results verify the advantages of our method.
BODMAS: An Open Dataset for Learning based Temporal Analysis of PE Malware

We describe and release an open PE malware dataset called BODMAS to facilitate research efforts in machine learning based malware analysis. By closely examining existing open PE malware datasets, we identified two missing capabilities (i.e., recent/timestamped malware samples, and well-curated family information), which have limited researchers’ ability to study pressing issues such as concept drift and malware family evolution. For these reasons, we release a new dataset to fill in the gaps. The BODMAS dataset contains 57,293 malware samples and 77,142 benign samples collected from August 2019 to September 2020, with carefully curated family information (581 families). We also perform a preliminary analysis to illustrate the impact of concept drift and discuss how this dataset can help to facilitate existing and future research efforts.
RELATIONSHIP UNDERSTANDING BETWEEN PERFORMANCE APPRAISAL, SUCCESSION PLANNING, AND CAREER DEVELOPMENT

Purpose: This paper aims to explore an integrated relationship between performance appraisal, succession planning, and career development in the Indian context. A very few empirical studies could be seen in identifying a relationship between the proposed variables. Design/methodology/approach: An empirical study was conducted by employing the cross-sectional survey-based research design along with the convenience sampling method. Around, 167 questionnaires were circulated through online via Google forms. Finally, 134 responses were received from respondents having 80.23% response rate. The responses were subject to analysis using normality check, confirmatory factor analysis, correlation, model fit and multiple hierarchical regression analysis. Findings: Results reveal that all three study variables are positively associated with each other. This study fully supports the applicability of performance appraisal, and succession planning as crucial predictors of career development more specifically in the Indian context. Research limitations/implications: This current study is conducted using online data collection procedure, while future studies may use in-depth interview and daily diary studies. Practical implications: This study exhibits how employee career development can be initiated through succession planning and performance appraisal. This study also suggested that the organizations which emphasize on an effective policy guideline for systematic performance appraisal will probably support the succession planning and career development. Originality/value: Notably, no prior studies empirically investigate the proposed relationship in Indian context. Furthermore, the findings serve as a policy guideline for the performance appraisal, succession planning and career development literature in an Indian organizational setting.
The Influence of Brand Image, Service Quality, and Social Media Marketing on Purchase Decision at Restaurant Navy Seals Surabaya

Restaurant Navy Seals Surabaya has many determinants in purchasing decisions, these factors are Brand Image, Service Quality, Social Media Marketing. And these factors will be examined statistically which aims to determine how much influence. The variables used are four, namely Brand Image (X1), Service Quality (X2), Social Media Marketing (X3), and Purchase Decision (Y). Data collection was obtained from distributing questionnaires to customers of Restaurant Navy Seals Surabaya. The results show that the Brand Image variable (X1), Service Quality (X2), and Social Media Marketing (X3) simultaneously and partially have a significant effect on Purchase Decision (Y). This research is a quantitative study with a sample of 160 respondents. The analysis technique used is multiple linear regression analysis. Based on this research, Restaurant Navy Seals Surabaya can maintain Brand Image, Service Quality, and Social Media Marketing, so that customers survive and faithfully buy at the place.
Predictors of Psychological Stress in Bhutanese Hypertensive Adults

Objective: To examine the prediction of illness perception, religiosity, and social support on psychological stress among adults with hypertension in Bhutan Material and Methods: A predictive correlational design was used, from 120 adults with hypertension; recruited from Jigme Dorji Wangchuk National Referral Hospital, using the simple random sampling technique. Data were self-reported through a demographic data questionnaire, Perceived Stress Scale (PSS, Cronbach’s α=0.76), Brief Illness Perception Questionnaire (Brief IPQ, Cronbach’s α=0.81), Belief into Action Scale (BIAC, Cronbach’s α=0.87) and Multidimensional Scale of Perceived Social Support (MSPSS, Cronbach’s α=0.91); between March, 2020 and April, 2020. Data were analyzed using descriptive statistics, Pearson’s product moment correlations and Standard Multiple Regression. Results: Regression analysis revealed that psychological stress was predicted by illness perception (β=0.70, p-value 0.738). The model explained 67.0% of the total variance for psychological stress. (R2 =0.67, p-value< 0.001). The mean scores were; psychological stress (20.23±5.58), illness perception (44.50±12.31), religiosity (53.48± 16.01), and social support (61.61±12.08). Conclusion: The findings support the role of illness perception and social support in explaining psychological stress among hypertensive people. Therefore, illness perception and social support may be considered in interventions to manage psychological stress in hypertension patients.
Capillary zone electrophoresis determination of cordycepin in Cordyceps spp. extracted by using ultrasonic

The technology of using ultrasonic in the extraction of cordycepin in Cordyceps spp. was presented in this paper. The extracting effects of four methods and different petreatments to the samples were compared, and the regents for extraction and duration of ultrasonication were tested. Capillary zone electrophoresis was used to separate and determine cordycepin. Cordycepin in Cordyceps kyushuensis Kob. was reported for the first time.
EXPERIENCES IN USING IT-BASED SERVICE TOWARD STUDENTS SATISFACTION AT UNIVERSITY(THE STUDY ON PRIVATE UNIVERSITIES IN CENTRAL JAVA INDONESIA)

Information technology has become an integral part in the life of a universities.This researchexplores how the use of IT-based service experiences effect on students'perceptions of IT-based services and traditional services (represented by SERVQUAL)at university as well as perceptions of IT-based services and traditional services effect on student satisfaction. Sample data which is collected from several universities were tested by structural equation modeling approachby means of WarpPLS 3.0. The result shows that students evaluations on the options IT-based services and traditional services at the university is positively influenced by the experience in using information technology services provided by other service providers outside the university, such as ATMs, e-banking and m-banking. This study also identified that IT-based services effect on perception of traditional services. Furthermore, the perception of the IT-based services and traditional services affect student satisfaction.
Abnormal Situation Detection on Surveillance Video Using Object Detection and Action Recognition

Security control using surveillance cameras is established when people observe all surveillance videos directly. However, this task is labor-intensive and it is difficult to detect all abnormal situations. In this paper, we propose a deep neural network model, called AT-Net, that automatically detects abnormal situations in the surveillance video, and introduces an automatic video surveillance system developed based on this network model. In particular, AT-Net alleviates the ambiguity of existing abnormal situation detection methods by mapping features representing relationships between people and objects in surveillance video to the new tensor structure based on sparse coding. Through experiments on actual surveillance videos, AT-Net achieved an F1-score of about 89%, and improved abnormal situation detection performance by more than 25% compared to existing methods.
Utility of MRI Enhancement Pattern in Myelopathies With Longitudinally Extensive T2 Lesions

Objective To determine whether MRI gadolinium enhancement patterns in myelopathies with longitudinally extensive T2 lesions can be reliably distinguished and assist in diagnosis. Methods We retrospectively identified 74 Mayo Clinic patients (January 1, 1996–December 31, 2019) fulfilling the following criteria: (1) clinical myelopathy; (2) MRI spine available; (3) longitudinally extensive T2 hyperintensity (≥3 vertebral segments); and (4) characteristic gadolinium enhancement pattern associated with a specific myelopathy etiology. Thirty-nine cases with alternative myelopathy etiologies, without previously described enhancement patterns, were included as controls. Two independent readers, educated on enhancement patterns, reviewed T2-weighted and postgadolinium T1-weighted images and selected the diagnosis based on this knowledge. These were compared with the true diagnoses, and agreement was measured with Kappa coefficient. Results Among all cases and controls (n = 113), there was excellent agreement for diagnosis using postgadolinium images (kappa, 0.76) but poor agreement with T2-weighted characteristics alone (kappa, 0.25). A correct diagnosis was more likely when assessing postgadolinium image characteristics than with T2-weighted images alone (rater 1: 100/113 [88%] vs 61/113 [54%] correct, p < 0.0001; rater 2: 95/113 [84%] vs 68/113 [60%] correct, p < 0.0001). Of the 74 with characteristic enhancement patterns, 55 (74%) were assigned an alternative incorrect or nonspecific diagnosis when originally evaluated in clinical practice, 12 (16%) received immunotherapy for noninflammatory myelopathies, and 2 (3%) underwent unnecessary spinal cord biopsy. Conclusions Misdiagnosis of myelopathies is common. The gadolinium enhancement patterns characteristic of specific diagnoses can be identified with excellent agreement between raters educated on this topic. This study highlights the potential diagnostic utility of enhancement patterns in myelopathies with longitudinally extensive T2 lesions.
In silico Multi Subunit Vaccine Design Referring Spike Glycoprotein of SARS-COV-2 (COVID-19): The World Pandemic

Contagious human coronavirus belong to family Coronaviridae and infects human respiratory system causing the disease known as COVID-19 (WHO). To eradicate the severe acute respiratory syndrome coronavirus 2 pandemic, an effective vaccine should be developed. In the current study immunoinformatics procedures were employed to introduce a novel multi-epitope subunit vaccine. This multi-epitope vaccine can activate equally class I and II human leukocyte antigen and antibody mediated immune responses. Spike glycoprotein (PDB Id: 6VSB) of the coronavirus was selected and analysed using immune epitope database server for prediction of potential immunogenic B and T-cell epitopes. Population conservation studies of the selected protein and predicted epitopes were also performed using population conservancy analysis tool of immune epitope database resource. The two dimensional and three dimensional structure of multi-epitope vaccine were predicted and authenticated using PROCheck and Raptor-X servers. Docking results of the multi-epitope vaccine peptide with human leukocyte antigen class I and II alleles predicted efficient binding and the resulted docked models were stable during simulation. In silico immune evaluation using C-ImmSim server showed that the peptide could concurrently elicit cell-mediated and humoral immune responses. Immune simulation studies significantly anticipated high levels of IgM and IgG, T-helper, T-cytotoxic cells, INF-γ.
Solution-processed multifunctional transparent conductive films based on long silver nanowires/polyimide structure with highly thermostable and antibacterial properties

Flexible transparent films that have excellent photoelectric properties, mechanical and thermal stability, and antibacterial properties, are highly desirable for applications in flexible and wearable electronics. Multifunctional transparent conductive films (TCFs) with long silver nanowires (AgNWs, average length = 80 μm and average diameter = 88 nm)/transparent polyimide (PI) structures which were fabricated by using a facile, scalable, environmentally-friendly, and full-solution process, can satisfy all the requirements above. The AgNW/PI composite films show excellent opto-electrical properties (e.g., 7.5 ohm sq−1, at 81.1% transmittance) and mechanical flexibility across a wide temperature range, from room temperature to 300 °C. The AgNW networks were embedded into the transparent PI film surface, which could decrease the surface roughness (Rrms < 2.0 nm), and enhance the composite films' resistance to peeling, fracture, and oxidation, which expands the range of TCF applications considerably. Additionally, in exploring promising applications, the function of the transparent heater and the antibacterial properties of the composite films were also studied. These characteristics make the composite films excellent candidates for substrates for flexible and wearable electronic devices.
Contagion in Futures Metal Markets during the Recent Global Financial Crisis: Evidence from Gold, Silver, Copper, Zinc and Aluminium

This paper seeks to investigate the time-varying dynamic conditional correlations to the five most important future metal markets, namely Gold, Silver, Copper, Zinc and Aluminium. We employ a multivariate Fractionally Integrated Generalized ARCH (FIGARCH) dynamic conditional correlation (cDCC) model to generate the potential contagion effects between the markets. The under investigation period is during the period 2006-2011. Empirical results show the existence of contagion or the increase in dynamic conditional correlation for all the pairs of markets, indicating the correlations risky from an investor’s point of view and implying the portfolio strategies difficult to apply. Additionally, Zinc is proved to be the most immune future metal market. The results are of interest to policymakers who provide regulations for the future metal markets. JEL Codes: C58, C61, G11, G15, L61.
Effect of Amaranth Grain with and without Enzyme in Leghorn Roosters

According to the Food Agriculture Organization (FAO) and the World Health Organization (WHO), Amaranth after the egg and upper than cow's milk, is the second most valuable substance in the world in the protein value chart (Cai et al. 2003). Amaranth is the most important plant from Pseudocereals (FAO/WHO/UNU, 1985). Pseudocereals are plants that produce fruits or seeds which are used and consumed as grains, though botanically pseudocereals are neither grasses nor true cereal grains. Pseudocereals are typically high in protein and other nutrients, gluten-free, and are considered whole grains. Many so-called "ancient grains" are pseudocereals (Gordon, 2006). Today, the introduction and development of forgotten plants such as pseudocereals have been able to help To determine chemical composition as well as apparent metabolizable energy corrected to zero nitrogen balance (AMEn) estimates of Amaranth grain in adult roosters by regression method, firstly, a specie of Amaranthus hybridus chorostachys were cultivated in a farm pilot at agriculture research station (Khalat Poushan-TabrizEast AzarbaijanIran). After harvesting, amaranth grain was sifted and milled. Finally, the chemical composition of amaranth grain produced in the Advanced Animal Nutrition Laboratory was analyzed. Adult roosters 96-week-old Leghorn in individual metabolic cages for nine days used to determine AMEn content by the regression method. The basal diet was based on corn-soybean with 3200 kcal/kg metabolizable energy and 12% protein. Two experiments with raw amaranth grain (RAG) and processing amaranth grain (PAG), started separately using 40 leghorn roosters in the form of completely random by factorial method (25), that each experiment consisted of two levels of Rovabio multi-enzyme (0 and 0.055%) and five amaranth grain levels (0, 15, 30, 45, 60% of replacement or embedment of energizing part of the diet). Each experiment included four replicates that included one bird, it was subjected to biological experiments in metabolic cages by total excreta collection method. The obtained results of regression equations in adult roosters showed that AMEn content for raw amaranth without enzyme (RAG), raw amaranth with an enzyme (RAG), processed amaranth without enzyme (PAG), and processed amaranth with an enzyme (PAG) were 3250.24, 3433.18, 3242.18 and 3438.09 kcal/kg, respectively. The total results of this study showed that according to amaranth's adaptable and nutritious agricultural features, it can have a good potential in supplementation of poultry diets with enzymes for improving the energy and nutrition quality.
IMPLEMENTASI DAN ANALISIS PERFORMANSI METODE YOU ONLY LOOK ONCE (YOLO) SEBAGAI SENSOR PORNOGRAFI PADA VIDEO IMPLEMENTATION AND PERFORMANCE ANALYSIS OF YOU ONLY LOOK ONCE (YOLO) METHOD AS PORN CENSORSHIP IN VIDEO

At present, video that contains pornographic content are very easy to access. People of all ages and backgrounds can easily watch it. Therefore, an effort is needed to complicate people to be able to watch pornographic videos. This research will use one of the object detection algorithms, namely You Only Look Once (YOLO) to detect the presence of pornographic content in the video for censorship purpose. YOLO is one of the developments of Convolutional Neural Network (CNN) object detection algorithm, and YOLO is able to detect an object with a fairly high accuracy and higher frame rate compared to other state-of-the-art object detectional gorithms. The model in this research will be trained by using dataset that contains 6267 images that will be classified into 3 classes, namely non-porn easy, non-porn difficult, and porn. In this research, the dataset scheme is using 2507 train data, 2507 validation data, and 1253 test data. The dataset is divided into 3 classes, namely npe (non-porn easy), npd (non-porn difficult), and porn. Performance parameter that is evaluated is mean Average Precission (mAP). The highest mAP value is 48.13% by using hyperparameter configuration of 0.001 learning rate, 100 epoch, and 32 batch size for the training phase, and with addition on fine-tuning process with 0.0001 learning rate, 35 epoch, and 4 batch size. The model is succesfully implemented on the desktop application for detecting and censoring pornographic image in a video with average frame rate of 25 fps.
Adaptive Perturb and Observe with Simulated Annealing for the Maximum Power Point Tracking of Photovoltaic Modules in Multiple Shading Scenarios

This paper proposes a method that combines the Adaptive Perturb and Observe (Adaptive P&O) and Simulated Annealing (SA) optimization approaches to identify the global maximum power point in photovoltaic (PV) modules. This identification is critical to enable that such modules can deliver their maximum power to the utility network, considering different shading conditions. The Adaptive P&O method combines fast convergence and low steady-state oscillations, but it tends to return local rather than global maximum power values. Thus, it does not ensure the total efficiency of the modules. The SA approach is used to avoid this P&O limitation, creating a hybrid approach that explores the best features of each method. In order to test the proposed method, it has been applied to the Canadian Solar CSP-320 module under multiple shading by means of Matlab/Simulink simulations. Firstly, the module model was validated from its datasheet information, then, it was submitted to different shading conditions. Under these conditions, the proposed method converged to the maximum global power.
Identifying the potential regulators of neutrophils recruitment in hepatocellular carcinoma using bioinformatics method

Background Neutrophils play a crucial role in the development and progression of hepatocellular carcinoma (HCC); however, the mechanism underlying neutrophil recruitment is not fully understood. Therefore, we aimed to explore the potential genes or pathways related to neutrophil recruitment in the cancer microenvironment. Methods We downloaded TCGA HCC gene expression profiles, the abundance of 22 different immune cells in HCC patients, and patient survival information. We used Kaplan-Meier survival analysis to determine if neutrophils were related to survival. Next, we screened different expression genes (DEGs) between patients with high and low level of neutrophils. We then identified the transcription factor and its targets in the fence of DEGs. Then, we carried out enrichment analysis and gene set variation analysis (GSVA) for targets. Finally, we explored the potential mechanism of targets via calculating correlation scores. Results Our survival analysis results showed that neutrophils were significantly associated with patient survival. A total of 736 DEGs were screened. Next, we identified transcription factor larger E26 transformation-specific (ETS) homologous factor (EHF) and 702 targets of EHF from 736 DEGs. Among these targets, the level of FGD6 expression had the highest correlation with the level of EHF expression. Enrichment and GSVA analysis for FGD6 showed that the level of GO:0043547 had a positive regulatory effect on GTPase activity and the GO:0007010 cytoskeleton organization was significantly difference between the high and low neutrophils counts. By calculating the correlation between FGD6 and genes in GO:0043547 and GO:0007010, we identified RIC8B and SIPA1L3. Conclusions These findings demonstrated that transcription factor EHF can influence recruitment of neutrophils by mediating the transcription of FGD6. Further investigations are needed to shed new light on EHF and its target FGD6.