HiCArch: A Deep Learning-based Hi-C Data Predictor

Hi-C sequencing analysis is one of the most popular methods to study three-dimensional (3D) genome structures, which affect the gene expression and other cellular activities by allowing distal regulations in spatial proximity. Hi-C sequencing analysis enhances understanding of chromatin functionality. However, due to the high cost of Hi-C sequencing, the publicly available Hi-C data of high resolutions (such as 10kb) are limited in only a few cell types. In this paper we present HiCArch, a light-weight deep neural network that predicts Hi-C contact matrices from 11 common 1D epigenomic features. HiCArch identifies topological associated domains (TADs) of 10kb resolution within the distance of 10Mb. HiCArch obtains train Pearson correlation score at 0.9123 and test Pearson correlation score at 0.9195 when trained on K562 cell line. which are significantly higher than previous approaches, such as HiC-Reg, Akita, DeepC, and Epiphany.

Combined endo- and epicardial pace-mapping to localize ventricular tachycardia isthmus in ischaemic and non-ischaemic cardiomyopathy

Aims A high-density pace-mapping can depict an abrupt transition in paced QRS morphology from a poor to excellent match, unmasking the critical component of ventricular tachycardia (VT) isthmus from the entrance to exit. We sought to assess pace-mapping at multiple sites within the endo- and epicardial scars to identify the VT isthmus in patients with ischaemic (ICM) and non-ischaemic cardiomyopathy (NICM). Methods and results Colour-coded maps correlating to the percentage matches between 12-lead electrocardiograms during VT and pace-mapping [referred to as correlation score maps (CSMs)] were analysed. We studied 115 CSMs (80 endo- and 35 epicardial CSMs) in 37 patients (17 ICM, 20 NICM). The CSM with an abrupt change (AC) in pacemap score (AC-type) on the endocardium was more frequently observed in ICM than in NICM [11/39 (28%) vs. 1/41 (2%); P = 0.001]. Among 35 CSMs that were analysed by the combined endo- and epicardial mapping, 10 (29%) CSMs exhibited non-AC-type on the endocardium; however, AC-type was present on the opposite epicardium. Although 24 (69%) CSMs did not show AC-type on both the endocardium and epicardium, 16 of them had either an excellent (>90%) or poor (<0%) correlation score on either side, associated with isthmus exit or entrance, respectively. However, the remaining eight CSMs had neither excellent nor poor scores. Conclusion The CSM may provide electrophysiological information to localize the endo- and epicardial VT isthmus. The absence of AC-type CSM on the endocardium, which is frequently observed in NICM, appears to indicate the sub-epicardial or intramural course of the critical isthmus.

CORRELATION BETWEEN STUDENTS' INTEREST AND THEIR ACADEMIC ACHIEVEMENT

This study focuses on students’ interest in English, and how it influences students’ achievement. The aim of this study is to figure out whether there is a correlation between students’ interest and their academic achievement in learning English. The number of the sample in this research are 87 students at the second grade of SMA Negeri 1 Tomohon. This study used quantitative research design which is non-experimental research. The data collected with questionnaire to obtain the information about students’ interest and students’ achievement in learning English. The questionnaire consists of 31 items divided into positive and negative statements. The items were tested with SPPS to determent the validity and the reliability of each items. The data was analysed by using the formula of Pearson Product Moment Correlation. It was found that the correlation score was 0.424. The significance value was 0.217 showed in the r table. The score of correlation 0.424 was higher than the significance value 0.217, means that the alternative hypothesis was accepted. Based on the result, it can be concluded that there was a positive correlation between students’ interest and their academic achievement in learning English. The researcher suggests that the case interest is very important particularly in affecting students’ achievement, therefore it must be improved.

Hubungan Kecenderungan Social Media Addiction dengan Empati pada Remaja di Surabaya

Adolescent is impotant to build a teenager’s personality, because their social-emotional-physical development starts and ends at adolescent phase. One of the important factor that can build teenager is empathy. Empathy is a response of understanding feelings and know the reason behind the feelings, empathy consists of affective and cognitive component. Right now, empathy on teenagers is stunted because of social media that can influence them into having low empathy, seeing news that’s full with hoax and teenage violence. This study’s purpose is to know the correlation between social media addiction tendency and empathy on teenagers in Surabaya. The participants were chosen using purposive sampling technique. The normality test was not fulfilled, so researcher use non-parametric statistical technique (Kendall’s Tau-b). The result shows significancy score = 0,000 (p < 0.05) and correlation score (r) = 0,106. With that, it can be concluded that there is a positive correlation between social media addiction tendency and empathy on teenagers in Surabaya.

Validity and Reliability Measurement of Bengali Translated Questionnaire for Urinary Incontinence Diagnosis

Objective: The aim of this study was to translate and verify the validity and reliability of the Bengali translated questionnaire for Urinary Incontinence Diagnosis (QUID), to ensure the diagnosis of urinary incontinence in Bangladesh.Material and Methods: Adaptation and psychometric properties testing of the Bengali-QUID were conducted with 67 respondents. Twenty respondents were included for pre-testing and adaptation; whereas, 47 respondents were considered for test-retest reliability. The content validity of the questionnaire was measured by expert opinion. Cornbach’s alpha statistical test was used to measure the internal consistency of the questionnaire, while the test-retest reliability was measured using the Intra-Class Correlation (2,1) model.Results: Content validity for all items of the questionnaire was >0.75. In addition, the Cronbach's Alpha values for interitem correlation for Stress Urinary Incontinence and Urge Urinary Incontinence were (α>0.8) and (α>0.7), respectively. Furthermore, the reliability of the Bengali-QUID questionnaire had an Intra-class correlation score of 0.76.Conclusion: This study demonstrated that the Bengali version of QUID questionnaire was highly valid, and reliable for diagnosis of urinary incontinence among Bangladeshi women.

An Appearance Invariant Gait Recognition Technique Using Dynamic Gait Features

Gait recognition-based person identification is an emerging trend in visual surveillance due to its uniqueness and adaptability to low-resolution video. Existing gait feature extraction techniques such as gait silhouette and Gait Energy Image rely on the human body’s shape. The shape of the human body varies according to the subject’s clothing and carrying conditions. The clothing choice changes every day and results in higher intraclass variance and lower interclass variance. Thus, gait verification and gait recognition are required for person identification. Moreover, clothing choices are highly influenced by the subject’s cultural background, and publicly available gait datasets lack the representation of South Asian Native clothing for gait recognition. We propose a Dynamic Gait Features extraction technique that preserves the spatiotemporal gait pattern with motion estimation. The Dynamic Gait Features under different Use Cases of clothing and carrying conditions are adaptable for gait verification and recognition. The Cross-Correlation score of Dynamic Gait Features resolves the problem of Gait verification. The standard deviation of Cross-Correlation Score lies in the range of 0.12 to 0.2 and reflects a strong correlation in Dynamic Gait Features of the same class. We achieved 98.5% accuracy on Support Vector Machine based gait recognition. Additionally, we develop a multiappearance-based gait dataset that captures the effects of South Asian Native Clothing (SACV-Gait dataset). We evaluated our work on CASIA-B, OUISIR-B, TUM-IITKGP, and SACV-Gait datasets and achieved an accuracy of 98%, 100%, 97.1%, and 98.8%, respectively.

Pathogenic gene prediction based on network embedding

In disease research, the study of gene–disease correlation has always been an important topic. With the emergence of large-scale connected data sets in biology, we use known correlations between the entities, which may be from different sets, to build a biological heterogeneous network and propose a new network embedded representation algorithm to calculate the correlation between disease and genes, using the correlation score to predict pathogenic genes. Then, we conduct several experiments to compare our method to other state-of-the-art methods. The results reveal that our method achieves better performance than the traditional methods.

Boosting Face Recognition under Drastic Views Using a Pose AutoAugment Manner

Face recognition under drastic pose drops rapidly due to the limited samples during the model training. In this paper, we propose a pose-autoaugment face recognition framework (PAFR) based on the training of a Convolutional Neural Network (CNN) with multi-view face augmentation. The proposed framework consists of three parts: face augmentation, CNN training, and face matching. The face augmentation part is composed of pose autoaugment and background appending for increasing the pose variations of each subject. In the second part, we train a CNN model with the generated facial images to enhance the pose-invariant feature extraction. In the third part, we concatenate the feature vectors of each face and its horizontally flipped face from the trained CNN model to obtain a robust feature. The correlation score between the two faces is computed by the cosine similarity of their robust features. Comparable experiments are demonstrated on Bosphorus and CASIA-3D databases.

A method for validating the accuracy of NMR protein structures

We present a method that measures the accuracy of NMR protein structures. It compares random coil index [RCI] against local rigidity predicted by mathematical rigidity theory, calculated from NMR structures [FIRST], using a correlation score (which assesses secondary structure), and an RMSD score (which measures overall rigidity). We test its performance using: structures refined in explicit solvent, which are much better than unrefined structures; decoy structures generated for 89 NMR structures; and conventional predictors of accuracy such as number of restraints per residue, restraint violations, energy of structure, ensemble RMSD, Ramachandran distribution, and clashscore. Restraint violations and RMSD are poor measures of accuracy. Comparisons of NMR to crystal structures show that secondary structure is equally accurate, but crystal structures are typically too rigid in loops, whereas NMR structures are typically too floppy overall. We show that the method is a useful addition to existing measures of accuracy.

Correlation of Self-Efficacy with Decision Making Continuing Studies in Students at Islamic Based Universities

Decision making requires courage and confidence from individuals to be able to make decisions even though it has consequences where self-efficacy is a factor because people believe in their ability to make decisions. This study aims to determine the correlation of self-efficacy with decision making continuing studies in students at Islamic based universities. The study population was students of the Raden Intan State Islamic University, Lampung, with a random sampling method. The total sample of 504 students. The instruments in this study were the scale of self-efficacy, and the scale of decision making by Jannis and Leon Mann. Data analysis using the Karl Spearman correlation test was assisted by SPSS software for Windows 23. The correlation score from the results of the study was 0.628 which showed a strong relationship between self-efficacy and respondent decision making so that the Self-Efficacy of Raden Intan Students of the State Islamic University has strong in making decisions in continuing their studies