Miracle-dz/UniFAR-FTUs huggingface dataset:
Convolutional Neural Network: Text Classification Model for Open Domain Question Answering System

Recently machine learning is being applied to almost every data domain one of which is Question Answering Systems (QAS). A typical Question Answering System is fairly an information retrieval system, which matches documents or text and retrieve the most accurate one. The idea of open domain question answering system put forth, involves convolutional neural network text classifiers. The Classification model presented in this paper is multi-class text classifier. The neural network classifier can be trained on large dataset. We report series of experiments conducted on Convolution Neural Network (CNN) by training it on two different datasets. Neural network model is trained on top of word embedding. Softmax layer is applied to calculate loss and mapping of semantically related words. Gathered results can help justify the fact that proposed hypothetical QAS is feasible. We further propose a method to integrate Convolutional Neural Network Classifier to an open domain question answering system. The idea of Open domain will be further explained, but the generality of it indicates to the system of domain specific trainable models, thus making it an open domain.
Nutrient-Driven O-GlcNAcylation at Promoters Impacts Genome-Wide RNA Pol II Distribution

Nutrient-driven O-GlcNAcylation has been linked to epigenetic regulation of gene expression in metazoans. In C. elegans, O-GlcNAc marks the promoters of over 800 developmental, metabolic, and stress-related genes; these O-GlcNAc marked genes show a strong 5′, promoter-proximal bias in the distribution of RNA Polymerase II (Pol II). In response to starvation or feeding, the steady state distribution of O-GlcNAc at promoters remain nearly constant presumably due to dynamic cycling mediated by the transferase OGT-1 and the O-GlcNAcase OGA-1. However, in viable mutants lacking either of these enzymes of O-GlcNAc metabolism, the nutrient-responsive GlcNAcylation of promoters is dramatically altered. Blocked O-GlcNAc cycling leads to a striking nutrient-dependent accumulation of O-GlcNAc on RNA Pol II. O-GlcNAc cycling mutants also show an exaggerated, nutrient-responsive redistribution of promoter-proximal RNA Pol II isoforms and extensive transcriptional deregulation. Our findings suggest a complex interplay between the O-GlcNAc modification at promoters, the kinase-dependent “CTD-code,” and co-factors regulating RNA Pol II dynamics. Nutrient-responsive O-GlcNAc cycling may buffer the transcriptional apparatus from dramatic swings in nutrient availability by modulating promoter activity to meet metabolic and developmental needs.
Early Functional and Morphological Muscle Adaptations During Short-Term Inertial-Squat Training

Purpose: To assess early changes in muscle function and hypertrophy, measured as increases in muscle cross-sectional areas (CSAs) and total volume, over a 4 weeks inertial resistance training (RT) program. Methods: Ten young RT-naive volunteers (age 23.4 ± 4.1 years) underwent 10 training sessions (2–3 per week) consisting of five sets of 10 flywheel squats (moment of inertia 900 kg⋅cm2). Magnetic resonance imaging (MRI) scans of both thighs were performed before (PRE), and after 2 (IN) and 4 (POST) weeks of training to compute individual muscle volumes and regional CSAs. Scans were performed after ≥96 h of recovery after training sessions, to avoid any influence of acute muscle swelling. PRE and POST regional muscle activation was assessed using muscle functional MRI (mfMRI) scans. Concentric (CON) and eccentric (ECC) squat force and power, as well as maximal voluntary isometric contraction force (MVIC) of knee extensors and flexors, were measured in every training session. Results: Significant quadriceps hypertrophy was detected during (IN: 5.5% ± 1.9%) and after (POST: 8.6% ± 3.6%) the training program. Increases in squat force (CON: 32% ± 15%, ECC: 31 ± 15%) and power (CON: 51% ± 30%, ECC: 48% ± 27%) were observed over the training program. Knee extensor MVIC significantly increased 28% ± 17% after training, but no changes were seen in knee flexor MVIC. No correlation was found between regional muscular activation in the first session and the % of increase in regional CSAs (r = -0.043, P = 0.164). Conclusion: This study reports the earliest onset of whole-muscle hypertrophy documented to date. The process initiates early and continues in response to RT, contributing to initial increases in force. The results call into question the reliability of mfMRI as a tool for predicting the potential hypertrophic effects of a given strengthening exercise.
MAPPs for the identification of immunogenic hotspots of biotherapeutics; an overview of the technology and its application to the biopharmaceutical arena

ABSTRACT Introduction: Anti-drug antibody (ADA) responses are becoming an increasing concern as more highly engineered and sophisticated biotherapeutics enter the clinic. An arsenal of tools has been developed to identify potential T cell epitopes that may drive unwanted immunological responses to protein therapeutics; one such tool is termed ‘Major Histocompatibility Complex-Associated Peptide Proteomics’ (MAPPs). This review highlights the evolution of this MHC II profiling technology, its technological advantages and limitations, and its utility in helping to de-risk the immunogenicity of biotherapeutics. Areas covered: A comprehensive literature review was performed along with discussions with key leaders in the field of MAPPs to summarize the importance of monitoring potential immunogenicity of clinical molecules. Herein we also describe how MAPPs has been applied specifically for monitoring MHC II peptides derived from biotherapeutics. Expert commentary: Given the importance of this growing field we discuss the complementary tools used in conjunction with MAPPs and review case studies where this approach has informed clinical studies and in some cases allowed re-engineering of the biotherapeutic moiety to a less immunogenic format.
Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation

We develop new stochastic gradient methods for efficiently solving sparse linear regression in a partial attribute observation setting, where learners are only allowed to observe a fixed number of actively chosen attributes per example at training and prediction times. It is shown that the methods achieve essentially a sample complexity of $O(1/\varepsilon)$ to attain an error of $\varepsilon$ under a variant of restricted eigenvalue condition, and the rate has better dependency on the problem dimension than existing methods. Particularly, if the smallest magnitude of the non-zero components of the optimal solution is not too small, the rate of our proposed {\it Hybrid} algorithm can be boosted to near the minimax optimal sample complexity of {\it full information} algorithms. The core ideas are (i) efficient construction of an unbiased gradient estimator by the iterative usage of the hard thresholding operator for configuring an exploration algorithm; and (ii) an adaptive combination of the exploration and an exploitation algorithms for quickly identifying the support of the optimum and efficiently searching the optimal parameter in its support. Experimental results are presented to validate our theoretical findings and the superiority of our proposed methods.
A DNA Methylation Signature of Addiction in T Cells and Its Reversal With DHEA Intervention

Previous studies in animal models of cocaine craving have delineated broad changes in DNA methylation profiles in the nucleus accumbens. A crucial factor for progress in behavioral and mental health epigenetics is the discovery of epigenetic markers in peripheral tissues. Several studies in primates and humans have associated differences in behavioral phenotypes with changes in DNA methylation in T cells and brain. Herein, we present a pilot study (n = 27) showing that the T cell DNA methylation profile differentiates persons with a substance use disorder from controls. Intervention with dehydroepiandrosterone (DHEA), previously shown to have a long-term therapeutic effect on human addicts herein resulted in reversal of DNA methylation changes in genes related to pathways associated with the addictive state.
Pathways to and Results of Psychiatric Consultation for Patients Referred from the Emergency Department. Are there Differences between Migrant and Native Patients?

The aim of this study was to compare migrants and native Italians on the pathways to care and results of psychiatric consultation (PC) in the emergency department (ED). Patients who were referred from the ED for psychiatric consultation (EDPC) at the Maggiore della Carità Hospital between March 2008 and March 2015 were recruited consecutively. Socio-demographic, clinical and consultation variables were recorded along with information about suicidal behaviours; migrants (n = 379; 42.74% males, 57.26% females; age: 45.38 ± 16.95 years) were compared with native Italians (n = 2942; 43.51% males, 56.49% females; age: 42.08 ± 15.89 years). Migrants were younger, more likely to be unemployed and less likely to be already under the care of a psychiatrist. Symptoms related to use of alcohol or substances were more frequent in migrants, especially female migrants. Migrants were less likely than native Italians to be referred for PC because of the presence of psychiatric symptoms, however they were more likely to be referred because of self-harming behaviour. Nonetheless, migrant status was not identified as a risk factor for suicidal behaviour in the multivariate analysis. The outcome of EDPC showed differences between migrants and natives. In absolute terms migrants were less likely to be admitted to a psychiatric ward after the EDPC than native Italians, while they were more likely to be monitored in the ED before being discharged or referred to outpatient care. In a high percentage of psychiatric examinations of migrants, no psychiatric symptoms were identified. Further studies are warranted to disentangle the meaning of these findings.
Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models

We propose an unsupervised method to obtain cross-lingual embeddings without any parallel data or pre-trained word embeddings. The proposed model, which we call multilingual neural language models, takes sentences of multiple languages as an input. The proposed model contains bidirectional LSTMs that perform as forward and backward language models, and these networks are shared among all the languages. The other parameters, i.e. word embeddings and linear transformation between hidden states and outputs, are specific to each language. The shared LSTMs can capture the common sentence structure among all languages. Accordingly, word embeddings of each language are mapped into a common latent space, making it possible to measure the similarity of words across multiple languages. We evaluate the quality of the cross-lingual word embeddings on a word alignment task. Our experiments demonstrate that our model can obtain cross-lingual embeddings of much higher quality than existing unsupervised models when only a small amount of monolingual data (i.e. 50k sentences) are available, or the domains of monolingual data are different across languages.
Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem

In this paper, we consider the convex and non-convex composition problem with the structure $\frac{1}{n}\sum\nolimits_{i = 1}^n {{F_i}( {G( x )} )}$, where $G( x )=\frac{1}{n}\sum\nolimits_{j = 1}^n {{G_j}( x )} $ is the inner function, and $F_i(\cdot)$ is the outer function. We explore the variance reduction based method to solve the composition optimization. Due to the fact that when the number of inner function and outer function are large, it is not reasonable to estimate them directly, thus we apply the stochastically controlled stochastic gradient (SCSG) method to estimate the gradient of the composition function and the value of the inner function. The query complexity of our proposed method for the convex and non-convex problem is equal to or better than the current method for the composition problem. Furthermore, we also present the mini-batch version of the proposed method, which has the improved the query complexity with related to the size of the mini-batch.
MRI tracking of polyethylene glycol-coated superparamagnetic iron oxide-labelled placenta-derived mesenchymal stem cells toward glioblastoma stem-like cells in a mouse model

Abstract Mesenchymal stem cells (MSCs) that display homing and infiltration properties towards tumor cells are a promising cellular targeting vector for brain tumor therapy but are limited to local-regional delivery in current preclinical models. Here, we investigated whether placenta-derived MSCs (P-MSCs) are a superior cellular vector for systemic targeting of glioblastoma stem-like cells (GSCs), with an imaging modality to real-time monitor the trafficking P-MSCs to glioblastoma sites. Results demonstrated that P-MSCs had greater migratory activity towards GSCs and across blood–brain barrier compared with bone marrow-derived MSCs, and this activity was enhanced by hypoxia precondition. Chemokine ligand 5 was identified as a chemoattractant responsible for the glioblastoma tropism of P-MSCs. Polyethylene glycol-coated superparamagnetic iron oxide (PEG–SPIO) was synthesized for cellular labelling and imaging P-MSCs, displaying high cellular uptake and no cytotoxic effect on P-MSCs cell proliferation or stemness property. The homing effects of intravenously administered PEG–SPIO-labelled P-MSCs towards intracerebral GSCs were able to be detected in mice models through T2-weighted magnetic resonance imaging (MRI). This study suggests the possibility of innovative systemic P-MSC-based cell therapy for aggressive GSCs, developing a state-of-the-art theranostic technique for real-time tracking of therapeutic P-MSCs tumor infiltration through cellular MRI.
In-group comparison is painful but meaningful: The moderator of classroom ethnic composition and the mediators of self-esteem and school belonging for upward comparisons

ABSTRACT This study examined the moderation of classroom ethnic composition and the mediation of group identification in the relationships between upward comparisons, depression, and self-efficacy in a sample of 359 Taiwanese aboriginal students. A stronger negative effect was found in highly ethnically concentrated classes. Upward comparisons were found to reinforce depression, decrease self-esteem, and reduce school belonging in aborigines-only classes but not in mainstream classes. Two pathways—self-esteem and school belonging—were found to process the negative indirect effects on depression and academic and social self-efficacy. The indirect effect through school belonging was particularly strong in the aborigines-only classes compared with the mainstream classes. The suppression effect showed that when self-esteem and school belonging were sustained, the aboriginal students in aborigines-only classes could increase their social self-efficacy through upward comparisons.
Recombinant Escherichia coli BL21-pET28a-egfp Cultivated with Nanomaterials in a Modified Microchannel for Biofilm Formation

The application of whole cells as catalytic biofilms in microchannels has attracted increasing scientific interest. However, the excessive biomass formation and structure of biofilms in a reactor limits their use. A microchannel reactor with surface modification was used to colonize recombinant Escherichia coil BL21-pET28a-egfp rapidly and accelerated growth of biofilms in the microchannel. The segmented flow system of ‘air/culture medium containing nanomaterials’ was firstly used to modulate the biofilms formation of recombinant E. coil; the inhibitory effects of nanomaterials on biofilm formation were investigated. The results indicated that the segmental flow mode has a significant impact on the structure and development of biofilms. Using the channels modified by silane reagent, the culture time of biofilms (30 h) was reduced by 6 h compared to unmodified channels. With the addition of graphene sheets (10 mg/L) in Luria-Bertani (LB) medium, the graphene sheets possessed a minimum inhibition rate of 3.23% against recombinant E. coil. The biofilms cultivated by the LB medium with added graphene sheets were stably formed in 20 h; the formation time was 33.33% shorter than that by LB medium without graphene. The developed method provides an efficient and simple approach for rapid preparation of catalytic biofilms in microchannel reactors.
Extracting Speaker's Gender, Accent, Age and Emotional State from Speech

We demonstrate a speaker characteristics assessment solution to extract speaker’s information like gender, age, emotion, language and accent from telephone quality speech. The solution has been designed using machine learning algorithms ranging from Gaussian mixture models to deep neural networks and utilize websocket technology for real-time bidirectional interface to provide live updates in a scalable manner. The service is utilized on our demonstration web-page where user can upload or record audio ﬁle and obtain the speaker’s characteristics. Such speaker characteristics information can be used as metadata in many real life applications designed for an emotionally sensitive human to machine interaction and human to human interaction.
TGF-β and BMPR2 Signaling in PAH: Two Black Sheep in One Family

Knowledge pertaining to the involvement of transforming growth factor β (TGF-β) and bone morphogenetic protein (BMP) signaling in pulmonary arterial hypertension (PAH) is continuously increasing. There is a growing understanding of the function of individual components involved in the pathway, but a clear synthesis of how these interact in PAH is currently lacking. Most of the focus has been on signaling downstream of BMPR2, but it is imperative to include the role of TGF-β signaling in PAH. This review gives a state of the art overview of disturbed signaling through the receptors of the TGF-β family with respect to vascular remodeling and cardiac effects as observed in PAH. Recent (pre)-clinical studies in which these two pathways were targeted will be discussed with an extended view on cardiovascular research fields outside of PAH, indicating novel future perspectives.
The effects of audio stimuli on auditory-evoked potential in normal hearing Malay adults

Objectives: The hearing process in the brain is very complicated and hard to solve. However, an understanding of the hearing process is an essential issue and needed in many rehabilitation or treatment applications. This study investigates and compares the effects of simple and complex sounds on latency and amplitude of various event-related potential (ERP) components to male ethnic Malay adults. Comparisons were made with previous studies. Materials and Methods: Simple and complex sounds were used (pure tones and the naturally produced Malay consonant–vowels [CVs]) to evoke the cortical auditory-evoked potential (CAEP) signals. Moreover, this study analyzed the influence of related CAEP components that are distinct to the selected population and determined which of the ERP components among (CAEP) components is most affected by the two distinct stimuli. Moreover, the study used classification algorithms to discover the ability of the brain in distinguishing CAEP evoked by stimuli contrasts. Results: The results showed some resemblance between our results and ERP waveforms outlined in previous studies conducted on native speakers of English. On the other hand, it was also observed that the P1 and N2 had a significant effect in amplitude due to different stimulus. Conclusion: The results show high classification accuracy for the brain to distinguish auditory stimuli. Moreover, the results indicated some resemblance to previous studies conducted on native English speakers using similar tones and English CV stimuli. However, the amplitudes and latencies of the P1 were found to have a significant difference due to stimuli complexity.
Performance Evaluation of the Quorum Blockchain Platform

Quorum is a permissioned blockchain platform built from the Ethereum codebase with adaptations to make it a permissioned consortium platform. It is one of the key contenders in the permissioned ledger space. Quorum supports confidentiality and privacy of smart contracts and transactions, and crash and Byzantine fault tolerant consensus algorithms. In this paper, we characterize the performance features of Quorum. We study the throughput and latency characteristics of Quorum with different workloads and consensus algorithms that it supports. Through a suite of micro-benchmarks, we explore how certain transaction and smart contract parameters can affect transaction latencies.
Studying Confirmation Bias in Hashtag Usage on Twitter

The micro-blogging platform Twitter allows its nearly 320 million monthly active users to build a network of follower connections to other Twitter users (i.e., followees) in order to subscribe to content posted by these users. With this feature, Twitter has become one of the most popular social networks on the Web and was also the first platform that offered the concept of hashtags. Hashtags are freely-chosen keywords, which start with the hash character, to annotate, categorize and contextualize Twitter posts (i.e., tweets). Although hashtags are widely accepted and used by the Twitter community, the heavy reuse of hashtags that are popular in the personal Twitter networks (i.e., own hashtags and hashtags used by followees) can lead to filter bubble effects and thus, to situations, in which only content associated with these hashtags are presented to the user. These filter bubble effects are also highly associated with the concept of confirmation bias, which is the tendency to favor and reuse information that confirms personal preferences. One example would be a Twitter user who is interested in political tweets of US president Donald Trump. Depending on the hashtags used, the user could either be stuck in a pro-Trump (e.g., #MAGA) or contra-Trump (e.g., #fakepresident) filter bubble. Therefore, the goal of this paper is to study confirmation bias and filter bubble effects in hashtag usage on Twitter by treating the reuse of hashtags as a phenomenon that fosters confirmation bias.
Oxygen-Carrying Micro/Nanobubbles: Composition, Synthesis Techniques and Potential Prospects in Photo-Triggered Theranostics

Microbubbles and nanobubbles (MNBs) can be prepared using various shells, such as phospholipids, polymers, proteins, and surfactants. MNBs contain gas cores due to which they are echogenic and can be used as contrast agents for ultrasonic and photoacoustic imaging. These bubbles can be engineered in various sizes as vehicles for gas and drug delivery applications with novel properties and flexible structures. Hypoxic areas in tumors develop owing to an imbalance of oxygen supply and demand. In tumors, hypoxic regions have shown more resistance to chemotherapy, radiotherapy, and photodynamic therapies. The efficacy of photodynamic therapy depends on the effective accumulation of photosensitizer drug in tumors and the availability of oxygen in the tumor to generate reactive oxygen species. MNBs have been shown to reverse hypoxic conditions, degradation of hypoxia inducible factor 1α protein, and increase tissue oxygen levels. This review summarizes the synthesis methods and shell compositions of micro/nanobubbles and methods deployed for oxygen delivery. Methods of functionalization of MNBs, their ability to deliver oxygen and drugs, incorporation of photosensitizers and potential application of photo-triggered theranostics, have also been discussed.