Miracle-dz/UniFAR-FTUs huggingface dataset:
Difference in Interoception between Long-Distance Runners and Sprinters: An Event-related Potential Study.

PURPOSE Interoception is a sense of the physiological state of one's body. Interoception that is generated by processing physiological information in the insular cortex plays an important role in achieving optimal performance in competitive sports. This study aimed to reveal the difference in interoceptive ability between long-distance runners and sprinters and its neural correlates by recording the stimulus-preceding negativity (SPN) that is generated from the insular cortex. Based on previous findings, we predicted that long-distance runners would show better interoceptive ability and larger SPNs compared with sprinters. METHOD We used a questionnaire and a heartbeat counting task to evaluate the interoceptive sensitivity and accuracy, respectively, of both long-distance runners and sprinters. We recorded SPNs during the execution of a time estimation task where participants estimate 3 s by pressing a button. RESULTS Results of the questionnaire revealed that sprinters exhibited a higher interoceptive ability associated with attention control of their own bodies than did long-distance runners. Sprinters also showed a larger SPN over the left centroparietal regions compared with long-distance runners. CONCLUSION In contrast to our prediction, sprinters exhibited a superior interoceptive ability and a greater activity of the insular cortex relative to long-distance runners. These results suggest that sprinters might be more susceptible to their internal bodily signals compared with long-distance runners, exhibiting greater activation of the anterior insula.
Diabetes self-management education for older adults

This study examined the effects of a community-based diabetes self-management (DSM) and physical activity intervention on diabetes control in older adults from 33 senior centers in Georgia. Participants were a convenience sample (N = 144, mean age = 74 years, 84% female, 42% Caucasian, 57% African American). The preand post-tests included measurements of A1c and self-assessment of 12 DSM behaviors. At the pre-test, participants’ mean A1c was 7.0 ± 1.4% and 17% had A1c greater than 8%, which represents poor glucose control. During the 4 month intervention participants attended up to 8 lessons focused on DSM. At the post-test, participants significantly increased their DSM behaviors by an additional 1 or more days in these areas (P < .0001): following a healthy eating plan, following an eating plan prescribed by their doctor, eating five or more servings of fruits and vegetables, spacing carbohydrates, and inspecting the insides of their shoes. The mean decrease in A1c for the entire sample was 0.25% (SD = 0.82, N = 144, P = .0004) and those with an initial A1c >8% had a clinically and statistically significant decrease of 1.15% (SD = 1.09, n = 24, pre-test: 9.48% vs. 8.33%, P < .0001,). In summary, this intervention was found to be a feasible and efficacious approach to significantly improving A1c and DSM behaviors in older adults in community-based senior centers throughout Georgia. INDEX WORDS: Older Americans Act Nutrition Program, Senior Center, Diabetes SelfManagement, Diabetes Self-Management Behaviors, Diabetes Self-Management Education, Diabetes Self-Management Education Intervention. DIABETES SELF-MANAGEMENT EDUCATION FOR OLDER ADULTS
A variant in SMOC2, inhibiting BMP signaling by competitively binding to BMPR1B, causes multiple epiphyseal dysplasia

Previously study showed that SMOC, a matricellular protein, inhibits BMP signaling downstream of its receptor via activation of mitogen-activated protein kinase (MAPK) signaling. In our study, exome sequencing revealed a missense mutation (c.1076T>G, p.Leu359Arg) in EC domain of SMOC2 in a Chinese family with multiple epiphyseal disease (MED). The pathogenicity of this SMOC2 variant was verified by Smoc2L359R/L359R knock-in mice. Of note, decreasing phosphorylation of SMAD1/5/9 was detected in growth plates and primary chondrocytes from Smoc2L359R/L359R mice. Furthermore, binding affinity of mutant SMOC2 with collagen IX and HSPG in the extracellular matrix of cartilage were reduced while binding affinity with BMPRIB was intact. In addition, in contrast to previously results, that SMOC2 cannot antagonize BMP activity in the presence of a constitutively activated BMP receptor. These results support that SMOC2 with p.Leu359Arg variant act as an antagonist of canonical BMP pathway by competitively binding with BMP receptors.
Interpretable detection of novel human viruses from genome sequencing data

Viruses evolve extremely quickly, so reliable methods for viral host prediction are necessary to safeguard biosecurity and biosafety alike. Novel human-infecting viruses are difficult to detect with standard bioinformatics workflows. Here, we predict whether a virus can infect humans directly from next-generation sequencing reads. We show that deep neural architectures significantly outperform both shallow machine learning and standard, homology-based algorithms, cutting the error rates in half and generalizing to taxonomic units distant from those presented during training. Further, we develop a suite of interpretability tools and show that it can be applied also to other models beyond the host prediction task. We propose a new approach for convolutional filter visualization to disentangle the information content of each nucleotide from its contribution to the final classification decision. Nucleotide-resolution maps of the learned associations between pathogen genomes and the infectious phenotype can be used to detect regions of interest in novel agents, for example the SARS-CoV-2 coronavirus, unknown before it caused a COVID-19 pandemic in 2020. All methods presented here are implemented as easy-to-install packages enabling analysis of NGS datasets without requiring any deep learning skills, but also allowing advanced users to easily train and explain new models for genomics.
‘Let’s Move on, Please’: Trust and Employment Relations in Early-stage Start-ups

Abstract In Portugal, an evolving start-up hype has been promoted in recent years, presenting the country as an emergent European entrepreneurial hub, a rising start-up nation. In this context, less laudatory perspectives, focused on analysing labour relations or employment creation effects, are scarce or not particularly visible. In order to address this specific analytical dimension, this article conceives a start-up as a temporary organisational form, arraying temporariness not only as an organisational attribute, but also as a specific interaction condition that moulds employment relations established between start-uppers and entrepreneurs. Analytical work is anchored in in-depth interviews and direct observation data, collected during a 12-month longitudinal study, carried out in one of the most successful start-ups created or operating in Portugal. A narrative is used as an empirical illustration of observed temporariness effects and three employment relation-specific attributes are discussed as aspects that should be inform public funding endorsement decisions: the prevalence of task-focus managerial arrangements; low levels of trust and institutionalised reciprocity; short-lived social relations and conflict deprioritisation.
Evaluation of sucrose as carbon source in mixotrophic culture of Arthrospira platensis Gomont 1892

Cyanobacteria are photosynthetic microorganisms that use CO 2 as carbon source and sunlight as energy source. Although phototrophic cultivation is widely used in cyanobacterium production, heterotrophic and mixotrophic cultivations attract attention among researchers. In this study the effect of different concentrations (0[control] - 0.25 - 2.5 - 10 - 50 mM) of sucrose on the growth of Arthrospira platensis under mixotrophic cultivation was investigated. The purpose of this study was to investigate whether A. platensis biomass production could be performed regardless of high light intensity. Biomass, chlorophyll, lipid and carbohydrate contents were determined by spectrophotometrically. Also the physicochemical properties of the produced cyanobacterium were investigated by FTIR, TGA and DSC. The highest biomass productivity was detected as 1.33 g/L/day in the medium containing 2.5 mM sucrose and the specific growth rate increased 1.32 fold as compared to phototrophic culture. Additionally, t he highest lipid content (3.68 ±0.17 mg/g cell) was determined in the same medium. This suggests that A. platensis has adapted to the medium that contains low sucrose concentrations. Also, this study showed that sucrose containing medium supports lipid production.
Joint order allocation and transportation planning under uncertainty within a socially responsible supply chain

This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility (CSR), over a given multi-period horizon under uncertainty. Furthermore, a customer’s behavior to pay more money for items with CSR attributes is considered in the total market demand. ,The objective functions, i.e. social value of purchasing, total profit (TP), total delivery lead-time, total air pollution, total water pollution and total energy consumption with regard to a number of constraints are jointly considered in a multi-product system. It is worth noting that operational- and sustainable-related parameters are usually vague and imprecise in this area. Therefore, this paper develops a new fuzzy multi-objective optimization model to capture this inherent fuzziness in critical data. ,Through the numerical examples in the textile industry, the application of the model and usefulness of solution procedures are carried out. The numerical results obtained from the proposed approach indicate the efficiency of the solution algorithm in different instances. Moreover, the authors observe that social investment of the buyer, to stimulate market demand, can affect the TP and also involve the total contribution of suppliers in social responsibility. ,This research work concentrates on providing a procurement and inventory model through the lens of sustainability to enable textile supply chain managers and related industries to apply the approach to their inventory control and supply management. Totally, the proposed methodology could be applied by many fabric buyers of textile industry tackling purchasing issues and attempting to perfect understanding of social supply chains.
A genome-wide association study highlights a regulatory role for IFNG-AS1 contributing to cutaneous leishmaniasis in Brazil

Background Cutaneous leishmaniasis (CL) caused by Leishmania braziliensis remains an important public health problem in Brazil. The goal of this study was to identify genetic risk factors for CL. Methods Genome-wide analysis was undertaken using DNAs from 956 CL cases and 868 controls (phase 1) and 1110 CL cases and 1178 controls (phase 2) genotyped using Illumina HumanCoreExome BeadChips. Imputation against 1000G data provided 4,498,586 quality-controlled single nucleotide variants (SNVs) common across phase 1 and phase 2 samples. Linear mixed models in FastLMM were used to take account of genetic diversity/ethnicity/admixture. Cellular cytokines were measured using flow cytometry. Results Combined analysis across cohorts found no associations that achieved genome-wide significance, commonly accepted as P<5×10-8. Support for variants at wound-healing genes previously studied as candidate genes for CL included SMAD2 (rs115582038/rs75753347; Pimputed_1000G=1.47×10-4). Top novel GWAS hits at P<5×10-5 in plausible candidate genes for CL included SERPINB10 (rs62097497;Pimputed_1000G=2.67×10-6), CRLF3 (rs75270613; Pimputed_1000G=5.12×10-6), STX7 (rs144488134;Pimputed_1000G=6.06×10-6), KRT80 (rs10783496 Pimputed_1000G=6.58×10-6), LAMP3 (rs74285558;Pimputed_1000G=6.54×10-6) and IFNG-AS1 (rs4913269;Pimputed_1000G=1.32×10-5). Of these, LAMP3 (Padjusted=9.25×10-12; +6-fold), STX7 (Padjusted=7.62×10-3; +1.3-fold) and CRLF3 (Padjusted=9.19×10-9; +1.97-fold) were all expressed more highly in CL biopsies compared to normal skin, whereas expression of KRT80 (Padjusted=3.07×10-8; −3-fold) was lower. Notably, the percent peripheral blood CD3+ T cells making interferon-γ in response to Leishmania antigen differed significantly by IFNG-AS1 genotype. Conclusions In addition to supporting variants in wound-healing genes as genetic risk factors for CL, our GWAS results provide important novel leads to understanding pathogenesis of CL including through the regulation of interferon-γ responses.
Accurate and versatile 3D segmentation of plant tissues at cellular resolution

Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs. In the last years, deep learning has provided robust automated algorithms that approach human performance, with applications to bio-image analysis now starting to emerge. Here, we present PlantSeg, a pipeline for volumetric segmentation of plant tissues into cells. PlantSeg employs a convolutional neural network to predict cell boundaries and graph partitioning to segment cells based on the neural network predictions. PlantSeg was trained on fixed and live plant organs imaged with confocal and light sheet microscopes. PlantSeg delivers accurate results and generalizes well across different tissues, scales, and acquisition settings. We present results of PlantSeg applications in diverse developmental contexts. PlantSeg is free and open-source, with both a command line and a user-friendly graphical interface.
TEKNIK XOR PADA MODE OPERASI ALGORITMA CIPHER BLOCK CHAINING (CBC) DENGAN KUNCI ACAK BLUM BLUM SHUB DALAM MENINGKATKAN KEAMANAN DATA

Penelitian ini bertujuan untuk mengkombinasikan teknik XOR dengan mode operasi Cipher Block Chaining (CBC) 256-bits dengan kunci yang dibangkitkan secara acak sepanjang 256-bits dengan algoritma Blum Blum Shub. Kombinasi algoritma yang dihasilkan diimplementasikan dengan bahasa pemrograman PHP untuk kemudian diuji dan dianalisis hasil proses enkripsi dan dekripsi terhadap sampel pesan yang digunakan. Hasil penelitian menunjukkan bahwa waktu proses yang dibutuhkan baik untuk enkripsi dan dekripsi sangat cepat, dan perangkat yang dibutuhkan untuk menjalankan aplikasi juga sangat ringan, sehingga algoritma yang dirancang dikategorikan hemat dalam hal sumber daya komputer dan waktu proses yang dibutuhkan. Hasil analisis keamanan juga menunjukkan bahwa dibutuhkan waktu 3,6717 x 1049 Juta Tahun untuk memecahkan kunci dengan menggunakan teknik bruto force dan asumsi 1014 percobaan perdetik. Cipher text yang dihasilkan juga sangat sensitif terhadap perubahan walau hanya 1 bit data yang dapat merusak seluruh cipher text setelahnya, sehingga keaslian cipher text juga terjaga karena setiap blok cipher text selalu berkaitan dengan blok sebelumnya. Setiap blok yang sama akan menghasilkan blok cipher text yang bervariasi dan benar-benar berbeda sehingga cipher text aman dari analisis frekuensi. Kata Kunci : CBC, XOR, Blum Blum Shub, Kriptografi
Triggers of Substance Abuse Slip and Relapse During Outpatient Treatment in Methadone/Buprenorphine Maintenance Therapy Clinics: A Predictive Model with Emphasis on Treatment-Related Factors

Background: Most addicts relapse in the ﬁrst year of treatment especially in the ﬁrst 3 - 6 months, which is the most vulnerable period. Objectives: Thepresentstudyaimedtoassessthepredictorsof substanceabuseslipandrelapseamongaddictsintheﬁrst6months of treatment with an emphasis on treatment related factors. Methods: The data of this cross-sectional study collected through assessment of 148 patients who were referred to the Methadone/Buprenorphine maintenance therapy clinics of Kermanshah city during April to September of 2015. Demographic, history, treatment checklist, comorbidity index, and medical records were used for collecting data. Data was analyzed through chi-square, t-test, and Binary logistic regression analysis. Results: The mean age of total participants was 42.4 ± 11.3 years and 98% of them were male. 27% and 35.1% of the patients, respec-tively,hadaslipandrelapseduringtheﬁrst6monthsof treatment. Afteradjustmentforalldemographicdata,itwasindicatedthat self-employment (P = 0.037), more treatment costs (P = 0.049), previous treatment history (P = 0.027), not satisﬁed dose of medication (P = 0.012), and lack of medical therapy history under physicians supervision (P = 0.046) can increase the possibility of a slip signiﬁcantly. Conclusions: Despite the fact that prevention of re-abuse and relapse of disease includes multi-factorial approach, it seems that the treatment-related factors are as the most major factors in relapse and slip during the ﬁrst 6 months of treatment. Health prac-titioners’ special attention to treatment related factors in addiction, especially previous treatment history as the most important predictor of relapse, are probably eﬀective in the control and decrease of a slip and relapse.
Comparison of Anatomical and Clinical Scores in Predicting Outcomes in Primary Percutaneous Coronary Intervention

Fundamento: Diferentes escores baseados em variaveis anatomicas e/ou clinicas tem sido desenvolvidos para estratificacao de risco em pacientes submetidos a intervencao coronariana percutânea (ICP). Estudos comparando a capacidade desses modelos na predicao de eventos cardiacos e cerebrovasculares adversos maiores (ECCAM) em pacientes submetidos a ICP primaria sao escassos. Objetivo: O objetivo desse estudo foi o de comparar os escores SYNTAX (SS), Clinical SYNTAX (CSS), ACEF e ACEF modificado (ACEFMod) na predicao de ECCAM em pacientes com infarto agudo do miocardico com supradesnivelamento do segmento ST (IAMCSST) submetidos a ICP primaria. Metodos: Foram analisados 311 pacientes consecutivos com IAMCSST submetidos a ICP primaria entre abril/2011 e dezembro/2015. As areas sob a curva caracteristica de operacao do receptor (ROC) foram calculadas para avaliar a habilidade desses escores em predizer ECCAM. O nivel de significância adotado em todos os testes foi de 5%. Resultados: Os pacientes apresentaram idade media de 60,2 ± 12,0 anos, 35,4% eram do sexo feminino e 22,5% eram diabeticos. A ocorrencia de ECCAM foi observada em 23,8% dos participantes. A area sob a curva ROC foi 0,586 (p = 0,028) para ACEF, 0,616 (p = 0,003) para SS, 0,623 (p = 0,002) para ACEFMod e 0,658 (p < 0,001) para CSS. Na analise multivariada, apenas SS (p = 0,011) e CSS (p = 0,002) foram preditores independentes de ECCAM. Conclusoes: SS e CSS elevados foram preditores independentes de ECCAM. Em nossa coorte de pacientes com IAMCSST submetidos a ICP primaria, o SS calculado a cineangiocoronariografia inicial mostrou-se uma ferramenta util para predizer ECCAM. (Int J Cardiovasc Sci. 2017; [online].ahead print, PP.0-0)
Effects of Motivation-Based Academic Group Psychotherapy on Psychological and Physiological Academic Stress Responses among Korean Middle School Students

ABSTRACT This study investigated the effects of motivation-based academic group psychotherapy on psychological and physiological academic stress responses. Indicators of academic stress were the psychological measures of academic burnout and physiological measures of salivary cortisol. The intervention group was expected to show higher salivary cortisol levels initially and that both measures of academic burnout and salivary cortisol would decrease post-intervention. After the first measurement, the intervention group received group psychotherapy, and the comparison group received no treatment. Means, standard deviations, and correlation coefficients were calculated and general linear modeling was conducted. No initial between-group difference was detected in salivary cortisol. Post-intervention, signs of academic burnout decreased in the intervention group, mostly for cynicism. However, salivary cortisol increased in both groups. Accordingly, possible mechanisms and implications are discussed.
Analyzing Customer Needs of Product Ecosystems Using Online Product Reviews

It is necessary to analyze customer needs of a product ecosystem in order to increase customer satisfaction and user experience, which will, in turn, enhance its business strategy and profits. However, it is often time-consuming and challenging to identify and analyze customer needs of product ecosystems using traditional methods due to numerous products and services as well as their interdependence within the product ecosystem. In this paper, we analyzed customer needs of a product ecosystem by capitalizing on online product reviews of multiple products and services of the Amazon product ecosystem with machine learning techniques. First, we filtered the noise involved in the reviews using a fastText method to categorize the reviews into informative and uninformative regarding customer needs. Second, we extracted various customer needs related topics using a latent Dirichlet allocation technique. Third, we conducted sentiment analysis using a valence aware dictionary and sentiment reasoner method, which not only predicted the sentiment of the reviews, but also its intensity. Based on the first three steps, we classified customer needs using an analytical Kano model dynamically. The case study of Amazon product ecosystem showed the potential of the proposed method.
Implementation Extreme Learning Machine for Rainfall Forecasting

Indonesia is one of country that have a large number of rainfall days in a year. So, make any sense ‎that forecasting is important to get any strategies to overcome the problem of erratic rainfall. ‎There are a lot of method that can conduct forecast rainfall, ‎the new one is Extreme Machine Learning. ‎Extreme Learning Machine (ELM) is a new learning method of artificial neural networks. ELM is an easy-to use and effective learning algorithm of single-‎hidden layer feed-forward neural networks (SLFNs). Therefore, ELM has the advantages of ‎fast learning speed and good generalization performance. This research conducted by using rainfall data in Sleman city to get forecasting in one year. It found that the ELM method has a smaller value compared to the GARCH method for all six rainfall station stations in Sleman region.
Veterinary software application for comparison of thermograms for pathology evaluation

The bilateral symmetry property in mammals allows for the detection of pathology by comparison of opposing sides. For any pathological disorder, thermal patterns differ compared to the normal body part. A software application for veterinary clinics has been under development to input two thermograms of body parts on both sides, one normal and the other unknown, and the application compares them based on extracted features and appropriate similarity and difference measures and outputs the likelihood of pathology. Here thermographic image data from 19° C to 40° C was linearly remapped to create images with 256 gray level values. Features were extracted from these images, including histogram, texture and spectral features. The comparison metrics used are the vector inner product, Tanimoto, Euclidean, city block, Minkowski and maximum value metric. Previous research with the anterior cruciate ligament (ACL) pathology in dogs suggested any thermogram variation below a threshold of 40% of Euclidean distance is normal and above 40% is abnormal. Here the 40% threshold was applied to a new ACL image set and achieved a sensitivity of 75%, an improvement from the 55% sensitivity of the previous work. With the new data set it was determined that using a threshold of 20% provided a much improved 92% sensitivity metric. However, this will require further research to determine the corresponding specificity success rate. Additionally, it was found that the anterior view provided better results than the lateral view. It was also determined that better results were obtained with all three feature sets than with just the histogram and texture sets. Further experiments are ongoing with larger image datasets, and pathologies, new features and comparison metric evaluation for determination of more accurate threshold values to separate normal and abnormal images.