Miracle-dz/UniFAR-FTUs huggingface dataset:
Overcoming the challenges of imputation of rare variants in a Taiwanese cohort

Transl Cancer Res 2020;9(7):4065-4069 | http://dx.doi. org/10.21037/tcr-20-2395 Significant findings from genome-wide association studies (GWASs) only explain a limited proportion of the genetic variance (i.e., heritability) for many phenotypes (1,2). This proportion potentially increases when all variants typed or tagged by GWAS arrays are considered (3); however, the common disease/common variant (CDCV) hypothesis leads to detection of loci that explain, almost invariably, only a small part of the “missing heritability” (4). The focus of genetic association studies has thus shifted toward rarer alleles with larger effect sizes (5). Researchers refer to variants with minor allele frequencies (MAFs) between 1% and 5% as “less common” variants and those with MAFs <1% as “rare” variants. Rare variants are one of the sources contributing to missing heritability (6), although due to their rarity they may contribute very little to heritability, individually (3). This could be because either the variants are too rare to contribute population-wide, or because the effect size of each variant is, in general, very small. It has been theorized that the severity of diseases in individuals who have the risk variants and display disease symptoms may be largely due to the cumulative effect of a collection of possibly hundreds, or even thousands, of similar conditions that are associated with rare variants at individual loci (7). Rare variants constitute the bulk of genetic variation in the human genome and are predicted to have larger phenotypic effects than common variants (8); however, it has been challenging to analyze such variants with adequate power in population-based studies due to their poor representation in the genotyping arrays that are typically used in GWASs. The total number of loci that may contribute to a disease’s prevalence is dependent on the disease incidence, the frequency of rare variants per locus, and their effect size (the genotype relative risk) (9). For a disease with high heritability, with the increase of the number of contributing rare alleles in an individual, the relative risk rises steeply under a multiplicative model. However, if each of these variants explains most of the risk in just a few people, their effects will not explain enough of the variance in a total population, and therefore standard GWAS procedures would fail to detect them (9). Furthermore, they are scarcely tagged as single-nucleotide polymorphisms (SNPs) in genome-wide arrays, with the exception of family-based studies and studies with very large sample sizes. Moreover, most CDCV-based GWASs exclude rare variants from their analysis in the early quality control steps. Besides, assaying rare variants directly via arrays is expensive. Hence, researchers opt for the more Editorial Commentary
Analgesic and neuropharmacological activities of Berberis lycium Royle collected from district Sherani Balochistan, Pakistan.

Berberis lycium (family Berberidaceae) grows in district Sherani, Balochistan, Pakistan. It is used for the treatment of various disorders by the people of Balochistan. The present work was carried out to explore analgesic and neuropharamcological activities of crude methanolic extracts of B. lyceum. The analgesic activity was carried out by acetic acid induced writhing test and formalin test. Open field test, cage crossing test, rearing test, traction test and forced swimming test were carried out in neuropharmacological activities. The results reveal that crude methanolic extracts of B. lyceum showed significant (P<0.05) analgesic activity in acetic acid induced pain as well as with formalin test. In neuropharmacological activities, crude methanolic extracts of B. lyceum showed significant (P<0.05) central nervous system depressant activity and in forced swimming test it showed anxiolytic effects.
A PRACTICAL OPEN-SOURCE COMPARISON OF DISCRETE AND CONTINUOUS BIOMECHANICAL ANALYSIS TECHNIQUES

Recent work has challenged the practice of extracting and analysing discrete summary metrics from continuous biomechanical data. This paper presents a practical comparison of candidate data analysis techniques including frequentist and Bayesian discrete analysis, frequentist and Bayesian statistical parametric mapping, and vector coding. Example 1 compares knee and hip flexion / extension angles during flywheel and barbell squats. Example 2 compares pelvis and thorax transverse rotations during badminton jump smashes by an international and a regional player. All example data and scripts are open-source. Statistical parametric mapping enables comparison of continuous biomechanical variables at time points other than discrete local optima. Combining this approach with vector coding provides information regarding differences in proximal-distal joint coordination throughout a movement. These continuous open-source methodologies can increase the validity and intuitive practical application of biomechanical conclusions.
Abstract A07: Decline in the growth of murine T-cell lymphoma via modulation of PI3K signaling pathway: Key role of quercetin and PI-103

Deregulation in cell proliferation, oxidative status, antiapoptosis and survival are involved in development of cancer. The cellular signaling cascades mediated by Phosphatidylinositol 3-kinase (PI3K) with their ability to stimulate cell proliferation and suppress apoptosis, has been considered to play key role in tumor initiation, promotion, and progression. Therefore, use of inhibitors or antioxidants like natural flavonoids could be promising strategy to target PI3K pathway for suppression of carcinogenic process. The present study was aimed to investigate the anti-cancer activity of quercetin, a natural flavonoid and PI-103, a synthetic inhibitor in transplantable murine T-cell lymphoma. Cytotoxicity, apoptotic potential, cell survival, cell proliferation as well as antioxidant defense are evaluated in ascite cells of murine T-cell lymphoma in vivo and in primary culture. Significant decline in level of AKT1, PKCα, COX 2 as well as regulatory domain of PI3K (p85α), AKT1 and Bad, suggested implication of quercetin in regression of lymphoma by down regulation of cell proliferation and survival. Improvement of active PKCδ, p53, active caspase 3, 9 and cleaved PARP supported its cell apoptotic mechanism in cancer prevention. Additionally, decreased ROS level and LDH A activity contributes to reduced survival of cancer cells. Inhibition of p110α by PI-103 resulted in suppression of phospho-AKT and p85α level in primary culture. Modulation of various molecular targets including PI3K/AKT signaling by quercetin and PI-103 in vitro and in vivo tumor models suggests the importance and contribution of antioxidant quercetin in the prevention of cancer. Citation Format: Akhilendra Kumar Maurya, Manjula Vinayak. Decline in the growth of murine T-cell lymphoma via modulation of PI3K signaling pathway: Key role of quercetin and PI-103. [abstract]. In: Proceedings of the AACR Special Conference: Targeting the PI3K-mTOR Network in Cancer; Sep 14-17, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(7 Suppl):Abstract nr A07.
A New Approach for Navigation and Traffic Signs Indication Using Map Integrated Augmented Reality for Self-Driving Cars

Self-driving vehicles are one of the emerging technologies. This technology has potential to save lives and make lives comfortable. However, the technology used in self driving cars has to perform series of task for building perceptions. This has some certain prerequisites related to road infrastructure and is affected by daylight and weather conditions of the place. If these prerequisites are not satisfied then it could affect the performance of the vehicle and can be considered as compromise with safety of the users. This research work is focused on trying to find a new approach using which the underdeveloped countries will also be able to implement self driving cars in their county. The objective of this paper is to propose a new approach to supplement the technology used in the self-driving cars for perception. Using this approach the countries who don’t satisfy the prerequisites would be eligible to implement them without compromising the safety.The proposed approach uses the technology Augmented Reality to create and augment artificial objects of navigational signs and traffic signals based on vehicles location to reality. Later the augmented scene is fed into the conventional Deep learning object detection algorithm to detect the navigational artificial objected along with other real objects. This approach help navigate the vehicle even if the road infrastructure does not have very good sign indications and marking.The approach was tested locally by creating a local navigational system and a smartphone based augmented reality app. The approach performed better than the conventional method as the objects were clearer in the frame which made it each for the object detection to detect them.
Exact (Then Approximate) Dynamic Programming for Deep Reinforcement Learning

Model-free reinforcement learning methods such as Q-learning and actor-critic methods have shown considerable success on a variety of problems. However, when combined with function approximation, these methods are notoriously brittle, and often face instability during training. At the heart of these methods is dynamic programming, where a value function is trained by bootstrapping values off itself with a temporal difference loss. As a result, these bootstrapped values may be incorrect, non-stationary, or even divergent, during a substantial portion of training. Such training conditions pose a unique challenge for deep networks, which have been shown to require more data and generalize poorly when trained with noisy labels. Motivated by these challenges, we propose a simple technique to stabilize deep Q learning by decoupling dynamic programming and function approximation. To do so, we quan-tize the agent’s experience, run value iteration on the discrete graph, train a neural network policy via supervised learning on the tabular targets, and ﬁnally ﬁnetune the policy with deep Q learning. We observe that, across a range of challenging image based ofﬂine RL tasks, this approach consistently outperforms prior approaches such as double DQN and BCQ, which often diverge or fail completely, while generalizing more effectively than directly applying the tabular policy.
Antimicrobial Electrospun Nanofibers

With the growing public health awareness of the pathogenic effects, malodors and stain formations caused by microorganisms, there is an increasing need for antimicrobial materials in many application areas, especially as protective clothing for medical and chemical workers, first responders, sportswear, underwear and other health related products, which will act against a wide range of gram-positive and gram-negative bacteria by inhibiting their growth. Many antimicrobial agents, such as antibiotics, silver ions, quaternary ammonium, N-halamines, and other biocidal agents, have been applied to textiles and membrane materials by various chemical and physicochemical finishing techniques to protect the substrates from chemical and biological activities [1].
Gene regulatory and pro-tumourigenic mechanisms of the bHLH-PAS transcription factor SIM2s.

Single-minded 2 (SIM2), a class I basic Helix-Loop-Helix/PAS (bHLH/PAS) transcription factor, is essential for early development, and the short isoform (SIM2s) is selectively up-regulated in pancreatic and prostate tumours. Mechanistic role(s) for SIM2 that are essential for development and in these cancers is unknown, largely due to the fact that few bona fide target genes have been described for SIM2. SIM2 must heterodimerise with the obligate class II partner factor ARNT to regulate transcription. Surprisingly, these studies reveal SIM2 plays a role in the regulation of the ARNT homologues, ARNT1 and ARNT2. Two nonexclusive mechanisms were identified; enhanced protein stabilisation, and the specific increased transcription of ARNT2. The regulation of ARNT by a class I family member was found to be unique to the SIM homologues. These findings suggest novel insights into how elevated levels of SIM2s in tumours may confer increased transcriptional activities and/or increase the availability of the essential partner factor for other class I family members to promote their respective activities and functions in developmental and/or tumourigeneic processes. Furthermore, microarray studies in prostate DU145 cells identified the pro-cell death gene, BNIP3 (Bcl-2/adenovirus E1B 19kDa interacting protein 3), as a novel target of SIM2s mediated repression. Further validation showed BNIP3 repression in several prostate and pancreatic carcinoma derived cell lines with ectopic expression of human SIM2s via SIM2s activities at the proximal promoter hypoxia response element (HRE), the site through which bHLH/PAS family member, HypoxiaInducible Factor 1α (HIF1α), induces BNIP3. SIM2s attenuates BNIP3 hypoxic induction via the HRE, and increased hypoxic induction of BNIP3 occurs with siRNA knockdown of endogenous SIM2s in prostate PC3AR+ cells. BNIP3 is implicated in hypoxia-induced cell-death processes. PC3AR+ cells expressing Abstract
Effects of the Adoption of Transparency and Accountability Practices on Procurement Performance of the Judiciary, Kenya

Public procurement is a fundamental goal of any government arm striving to deliver goods and services to its citizens and it is expected that it provides an ample framework for utilization of citizen resources. Unfortunately, it is reported that Kenya loses about 200 billion shillings annually as a result of flaws in procurement performance emanating from inability to uphold public procurement and disposal principles (EACC, 2010). Reviewed studies attempted to examine the relationship between adoption of transparency and accountability practices and procurement performance. However, no study reviewed looked at the effect of the adoption of ethical practices (transparency and accountability) on performance of procurement performance and information on such findings is therefore lacking. It is in this regard that the current study purposed to establish the effect of the adoption of transparency and accountability on the procurement performance of the Judiciary in Kenya. The study was anchored on legitimacy and normalization theories. Correlation research design was adopted to study a target population of 100 respondents, from which a sample size of 50 respondents arrived at using Yamane’s formula was selected. The study used primary data which were collected using structured questionnaire. A pilot study of the data collection instrument was conducted using 5 employees of the Judiciary who did not participate in the final study. The instrument reliability was ascertained using Cronbach’s Alpha where analpha coefficient of 0.7505 which is above the threshold of 0.7 was established indicating high levels of instrument reliability. For validity test the instrument was reviewed by Supply Chain Management Lectures andpractitioners whose opinions were incorporated in the final instrument. Using linear regression analysis, the study established that transparency & accountability practices adoption has a significant effect on performance (β = 0.294, α=0.012). This implies that a unit increase in adoption of transparency practice would lead to an increase in procurement performance of the judiciary.The study therefore recommends that the Judiciary as well as other organization adopt transparency and ethical practices in order to elevateperformance of the procurement function.
A Study to Evaluate the Effectiveness of Structured Educational Programme on Knowledge and Practice Regarding Breast Cancer and Breast Self-Examination among the B.Ed. Students Studying in Shivaji College of Education, Karwar, Karnataka

Background: Breast cancer is the second leading cause of cancer death in women (only lung cancer kills more women each year). The chance that a woman will die from breast cancer is about 1 in 38 (about 2.6%). Aim: To evaluate the effectiveness of structured educational programme on knowledge and practice regarding breast cancer and breast self-examination among the B.Ed. students studying in Shivaji College of Education, Karwar. Method: An evaluative approach with pre experimental pre-test-post-test design was used for the study. Forty two B.Ed. students were selected by purposive non probability sampling method based on inclusion criteria. The structured knowledge questionnaire is prepared to assess the knowledge related to breast cancer and breast selfexamination and an observation checklist is prepared to evaluate the practice of breast selfexamination. The questionnaire consists of eight items to obtain socio demographic data, and forty items to assess the level of knowledge regarding breast cancer and breast self-examination. A structured educational programme was prepared and administered regarding breast cancer and breast self-examination after conducting pre-test to the students. Post-test was conducted after six days of administration of structured educational programme. The data collected was analysed using descriptive and inferential statistics. Result: The findings revealed that the pre-test knowledge scores of B.Ed. students were 54% (average knowledge) and 46% (poor knowledge) and the post-test knowledge scores were 17% (good knowledge), 79% (average knowledge) and 4% (poor knowledge) respectively. The distribution of practice scores for B.Ed. students includes pre-test practice scores i.e. 4% (average practice) and 96% (poor practice knowledge) and the post-test practice scores were 11% (good practice), 75% (average practice) and 14% (poor practice) respectively. Conclusion: The study findings revealed that there was significant increase in knowledge and practice level of B.Ed. students after administration of the structured educational programme.
Effects of Virgin Coconut Oil on the Histomorphometric Parameters in the Aortae and Hearts of Rats Fed with Repeatedly Heated Palm Oil

The study was carried out to investigate the effects of virgin coconut oil (VCO) on histomorphometric changes in the aorta and heart of thermoxidized palm oil-fed rats. Thirty two male Sprague-Dawley rats were divided into four groups: control group fed with normal diet; 5 times heated palm oil-fed group (5HPO) fortified with 15% of 5HPO; VCO group supplemented with 1.43ml/kg of VCO; and 5HPO + VCO group. The treatment lasted for four months. Upon sacrifice, aortic and heart tissues were processed for light microscopic studies. Light microscopic studies showed thickened intima and media of the aorta in two out of eight rats in the 5HPO group only, while the rest of the rats did not show any thickening of either the intima or media of the aorta. Intima media area (IMA) in the VCO, 5HPO and 5HPO+VCO was significantly increased compared to the control group. Circumferential wall tension (CWT) and tensile stress (TS) in the aorta of 5HPO showed a significant increase compared to the other groups. Cardiomyofibre width in 5HPO group showed a significant increase in size compared to the control, VCO and 5HPO+VCO groups. Cardiomyofibre nuclear size in the 5HPO group decreased in size significantly compared to the control, VCO and 5HPO+VCO groups. VCO supplementation at a dose of 1.43ml/kg showed protective effects on the aorta and heart of thermoxidized palm oil fed rats.
Kevlar Based Fibre Reinforced Polymer Composite- A Review

3Dept. of Mech Engg, Gayathri Vidya Parishad.College of Engineering, Vishakhapatnam, Andhra Pradesh, India --------------------------------------------------------------------------***--------------------------------------------------------------------ABSTRACT: The review article showcased here is to understand the mechanical and tribological characteristics such as tensile, flexural, impact, wear, chemical and thermal properties of various available fibres such as Glass, carbon, Graphite and Kevlar fiber reinforced polymer matrix composites. The characteristics of the various fibre-reinforced polymer composites with reference to their proportion and the areas of usage are discussed. The review looks into the studies on various types of Kevlar composites. It provides an orientation to optimise the present day Kevlar materials and a platform to explore and investigate new combinations
All-cause excess mortality and COVID-19-related deaths in Iran

Background: Iran reported its first COVID-19 deaths on February 19, 2020 and announced 1284 deaths with a laboratory-confirmed SARS-CoV-2 infection by March 19, 2020 (end of the winter 1398 SH). We estimated all-cause excess mortality, compared to the historical trends, to obtain an indirect estimate of COVID-19-related deaths. Methods: We assembled time series of the seasonal number of all-cause mortalities from March 21, 2013 (spring of 1392 SH) to March 19, 2020 (winter 1398 SH) for each province of Iran and nationwide with the vital statistics data from the National Organization for Civil Registration (NOCR). We estimated the expected seasonal mortality and excess mortality (the difference between the number of registered and expected deaths). Moreover, we reviewed the provincial number of confirmed cases of COVID-19 to assess their association with excess deaths. Results: The results of our analysis showed around 7507 (95% CI: 3,350 – 11,664) and 5180 (95% CI: 1,023 – 9,337) all-cause excess mortality in fall and winter, respectively. There were 3778 excess deaths occurred in Qom, Gilan, Mazandaran, and Golestan provinces in the winter, all among the COVID-19 epicenters based on the number of confirmed cases. Conclusion: We think most of the excess deaths in the winter were related to COVID-19. Also, we think the influenza epidemic might have been the main reason for the excess mortality in the fall and parts of excess deaths in the winter of 1398 SH. Moreover, a review of all available clinical and paraclinical records and through analyses of the surveillance data for severe acute respiratory infections (SARI) can help to obtain a more accurate estimate of COVID-19 mortality.
MULTI-TASK LEARNING PARADIGM FOR SOUND EVENT DETECTION

In this technical report, we describe our system submitted to DCASE2020 task 4. This task evaluates systems for the detection of sound events in domestic environments using large-scale weakly labeled data. To perform this task, we propose resdual convolutional recurrent neural networks (CRNN) as our system and trained by datasets including strong and weak labels. We also use mean-teacher model based on conﬁdence thresholding and smooth embedding method. In addition, we also apply specaugment for the labeled data shortage problem. Finally, we achieve better performance than DCASE2020 baseline system
Energy Crossover from Leader to Followers: A Time-lagged Study of the Effects of Energy Discrepancy and Leader-Member Exchange

This study investigates the effects of the difference between leaders’ and followers’ level of subjective energy on the change in subordinates’ energy one year later, and on customer-oriented citizenship behaviors. Building mainly on the crossover model, our time-lagged model also examines the moderating role of leader-member exchange. Results of polynomial regression and response surface analyses performed with a sample of 277 dyads in the retail sector indicate that the effect of the energy gap is asymmetrical, such that followers paired with a more energetic leader gain energy one year later, whereas those matched with less energetic leaders experience energy depletion. As expected, a high-quality relationship buffers the de-energizing effect of leaders with lower energy and augments the gain of energy triggered by more energetic leaders.