Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Branched-Chain Amino Acids on Parameters Evaluating Sarcopenia in Liver Cirrhosis: Systematic Review and Meta-Analysis

Introduction Sarcopenia is a major element of malnutrition in liver cirrhosis (LC) and is present in 30–70% of this population, being associated with a poor overall prognosis due to related complications such as hepatic encephalopathy, ascites, and portal hypertension. This systematic review and meta-analysis aimed to evaluate the effects of branched-chain amino acids (BCAA) supplementation on several parameters used to assess sarcopenia in LC. Materials and Methods A comprehensive systematic electronic search was performed in PubMed, EMBASE, Scopus, Cochrane Library, and ClinicalTrials.gov databases using predefined keywords. We included full articles that satisfied the inclusion and exclusion criteria. Quality assessment of included studies was conducted using Cochrane Collaboration's tool and NHLBI quality assessment tools for interventional and observational studies, respectively. The principal summary outcome was the mean difference (MD) in the evaluated parameters. We performed a pre- and post-intervention analysis and comparison between two intervention groups (BCAA vs. controls) of the evaluated parameters when applicable. Results A total of 12 studies involving 1,225 subjects were included in our qualitative synthesis and five in our quantitative synthesis. At baseline vs. post-intervention assessment, subjects receiving BCAA supplementation were found to have a significant improvement in skeletal muscle index (SMI) (−0.347 [95% CI −0.628–0.067; p-value 0.015]) and mid-arm muscle circumference (MAMC) (−1.273 [95% CI (−2.251–0.294; p-value 0.011]). However, no improvements were reported in handgrip (-0.616 [95% CI −2.818–1.586; p-value 0.584]) and triceps subcutaneous fat (1.10 [95% CI −0.814–3.014; p-value 0.263]). Conclusion Following BCAA supplementation, several parameters used to evaluate sarcopenia in LC patients were found to be improved, including SMI and MAMC. Nevertheless, no improvements were seen in handgrip and triceps subcutaneous fat. Results should be interpreted with caution due to the limited methodological quality of the included studies.
A Scoping Review of Interventions Designed to Support Parents With Mental Illness That Would Be Appropriate for Parents With Psychosis

The experience of psychosis can present additional difficulties for parents, over and above the normal challenges of parenting. Although there is evidence about parenting interventions specifically targeted at parents with affective disorders, anxiety, and borderline personality disorder, there is currently limited evidence for parents with psychotic disorders. It is not yet known what, if any, interventions exist for this population, or what kinds of evaluations have been conducted. To address this, we conducted a scoping review to determine (1) what parenting interventions have been developed for parents with psychosis (either specifically for, or accessible by, this client group), (2) what components these interventions contain, and (3) what kinds of evaluations have been conducted. The eligibility criteria were broad; we included any report of an intervention for parents with a mental health diagnosis, in which parents with psychosis were eligible to take part, that had been published within the last 20 years. Two reviewers screened reports and extracted the data from the included reports. Thirty-eight studies of 34 interventions were included. The findings show that most interventions have been designed either for parents with any mental illness or parents with severe mental illness, and only two interventions were trialed with a group of parents with psychosis. After noting clusters of intervention components, five groups were formed focused on: (1) talking about parental mental illness, (2) improving parenting skills, (3) long-term tailored support for the whole family, (4) groups for parents with mental illness, and (5) family therapy. Twenty-three quantitative evaluations and 13 qualitative evaluations had been conducted but only eight interventions have or are being evaluated using a randomized controlled trial (RCT). More RCTs of these interventions are needed, in addition to further analysis of the components that are the most effective in changing outcomes for both the parent and their children, in order to support parents with psychosis and their families.
An in vivo Cell-Based Delivery Platform for Zinc Finger Artificial Transcription Factors in Pre-clinical Animal Models

Zinc finger (ZF), transcription activator-like effectors (TALE), and CRISPR/Cas9 therapies to regulate gene expression are becoming viable strategies to treat genetic disorders, although effective in vivo delivery systems for these proteins remain a major translational hurdle. We describe the use of a mesenchymal stem/stromal cell (MSC)-based delivery system for the secretion of a ZF protein (ZF-MSC) in transgenic mouse models and young rhesus monkeys. Secreted ZF protein from mouse ZF-MSC was detectable within the hippocampus 1 week following intracranial or cisterna magna (CM) injection. Secreted ZF activated the imprinted paternal Ube3a in a transgenic reporter mouse and ameliorated motor deficits in a Ube3a deletion Angelman Syndrome (AS) mouse. Intrathecally administered autologous rhesus MSCs were well-tolerated for 3 weeks following administration and secreted ZF protein was detectable within the cerebrospinal fluid (CSF), midbrain, and spinal cord. This approach is less invasive when compared to direct intracranial injection which requires a surgical procedure.
Conceptualization and Measurement of Flow in a Chinese Blended English as a Foreign Language Learning Context

This study takes a holistic view of flow and anti-flow experiences as interactive subsystems in blended English as a foreign language (EFL) learning and examines the dynamic complex construct in the field of instructed second language acquisition (ISLA). We first rephrased the 22-item Classroom Flow Questionnaire (CFQ) to better reflect the context of blended EFL learning. The modified CFQ was then administered to 661 first language Chinese EFL learners. A final 14-item Foreign Language Flow Scale (FLFS) was developed based on results from a series of reliability (e.g., item analysis, internal consistency, and test-retest reliability) and validity (e.g., construct validity, convergent validity, discriminant validity, and criterion validity) tests. Both exploratory and confirmatory factor analysis results have demonstrated that foreign language learning flow is a three-dimensional construct involving Enjoyment, Boredom, and Anxiety, thus conceptualizing and validating flow as a continuum with both positive and negative ends. Moreover, participants reported that they experienced the lowest degree of enjoyment, while with respect to the negative flow, they almost experienced similar degree of boredom and anxiety. The present study contributes to the development of the conceptual framework for flow in ISLA as well as constructive pedagogical implications for L2 researchers and educators. Suggestions for future research are also provided.
Post-traumatic Stress and Growth Among the Children and Adolescents in the Aftermath of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has enkindled many mental health problems across the globe. Prominent among them is the prevalence of post-traumatic stress (PTS) with hosts of its precipitating factors being present in the surrounding. With India witnessing severe impact of the second wave of COVID-19, marked by a large number of hospitalizations, deaths, unemployment, imposition of lockdowns, etc., its repercussions on children and adolescents demand particular attention. This study aims to examine the direct and the indirect exposure of COVID-19-related experiences on children and adolescents and its subsequent relationship with PTS and post-traumatic growth (PTG). The direct exposure was operationalized in terms of death or hospitalization in the family, while the indirect exposure was gauged in terms of exposure to media reports of the COVID situation. Data from 412 children and adolescents aged 9–20 years, collected online, revealed 68.9% of them with PTS. Interestingly, 39.8% of those reporting PTS were also experiencing PTG. Arousal appeared to be the most frequently reported characteristics of trauma. The multivariate analysis of variance (MANOVA) endorses significant difference between those with direct and indirect exposures to hospitalization. Those with direct exposure to hospitalization reported higher PTS. The indirect exposure of COVID-19-related news through electronic media was also significantly associated with higher PTS. Exposure through print media did not lead to significant difference in PTS, but those reading only magazines reported significantly higher PTG than not reading magazines. The findings are analyzed in the light of unfolding of events during the second wave of COVID-19 in India.
Differential Tractography and Correlation Tractography Findings on Patients With Mild Traumatic Brain Injury: A Pilot Study

Differential tractography and correlation tractography are new tractography modalities to study neuronal changes in brain diseases, but their performances in detecting neuronal injuries are yet to be investigated in patients with mild traumatic brain injury (mTBI). Here we investigated the white matter injury in mTBI patients using differential and correlation tractography. The diffusion MRI was acquired at 33 mTBI patients and 31 health controls. 7 of the mTBI patients had one-year follow-up scans, and differential tractography was used to evaluate injured fiber bundles on these 7 patients. All subjects were evaluated using digital symbol substitution test (DSST) and trail making test A (TMT-A), and the correlation tractography was performed to explore the exact pathways related to the cognitive performance. Our results showed that differential tractography revealed neuronal changes in the corpus callosum in all 7 follow-up mTBI patients with FDR between 0.007 and 0.17. Further, the correlation tractography showed that the splenium of the corpus callosum, combined with the right superior longitudinal fasciculus and right cingulum, were correlated with DSST (FDR = 0.001669) in the acute mTBI patients. The cognitive impairment findings in the acute stage and the longitudinal findings in the corpus callosum in the chronic stage of mTBI patients suggest that differential tractography and correlation tractography are valuable tools in the diagnostic and prognostic evaluation of neuronal injuries in mTBI patients.
Direct Carotid Artery Exposure for Acute Cerebral Infarction in Hybrid Angiography Suite: Indications and Limitations

Objectives For the endovascular intervention of acute ischemic stroke, a transcervical route is an alternative approach in patients with challenging anatomical variations. Percutaneous puncture is a common way, but it can cause many fatal complications. Direct carotid artery exposure is an alternative for reducing complications. We demonstrate a technique of direct carotid exposure in patients for whom transfemoral or transbrachial approaches were impossible. We present patient outcomes and discuss the indications and limitations of this procedure. Methods We retrospectively reviewed the cases of patients undergoing direct carotid exposure for acute ischemic stroke in a hybrid angiography suite and presented the details of the technique. Results Among 548 consecutive patients with acute large vessel strokes who were treated by emergency endovascular thrombectomy or stenting between January 2015 and September 2020 in our center, only 8 (1.46%) required a transcervical approach. Of them, 7 underwent direct carotid exposure with successful recanalization and good clinical outcomes. Conclusions Direct carotid exposure for endovascular stroke treatment is effective and advantageous in patients with challenging anatomical variations. Performing this procedure in carefully selected patients in the hybrid angiography suite can be beneficial in terms of open surgeries, saving time, and decreasing the risk of postoperative complications.
Aquatic Macrophytes Are Associated With Variation in Biogeochemistry and Bacterial Assemblages of Mountain Lakes

In aquatic systems, microbes likely play critical roles in biogeochemical cycling and ecosystem processes, but much remains to be learned regarding microbial biogeography and ecology. The microbial ecology of mountain lakes is particularly understudied. We hypothesized that microbial distribution among lakes is shaped, in part, by aquatic plant communities and the biogeochemistry of the lake. Specifically, we investigated the associations of yellow water lilies (Nuphar polysepala) with the biogeochemistry and microbial assemblages within mountain lakes at two scales: within a single lake and among lakes within a mountain range. We first compared the biogeochemistry of lakes without water lilies to those colonized to varying degrees by water lilies. Lakes with >10% of the surface occupied by water lilies had lower pH and higher dissolved organic carbon than those without water lilies and had a different microbial composition. Notably, cyanobacteria were negatively associated with water lily presence, a result consistent with the past observation that macrophytes outcompete phytoplankton and can suppress cyanobacterial and algal blooms. To examine the influence of macrophytes on microbial distribution within a lake, we characterized microbial assemblages present on abaxial and adaxial water lily leaf surfaces and in the water column. Microbial diversity and composition varied among all three habitats, with the highest diversity of microbes observed on the adaxial side of leaves. Overall, this study suggests that water lilies influence the biogeochemistry and microbiology of mountains lakes.
Genome-Wide Identification of Maize Aquaporin and Functional Analysis During Seed Germination and Seedling Establishment

Water uptake facilitates the initiation of seed germination. It is presumed that aquaporin (AQP)-mediated water inflow contributes to seed germination, but the genetic evidence is still lacking. This study aimed at genome-wide identification of ZmAQPs and further determined the physiological functions. Following a comprehensive search, a total of 41 ZmAQPs were identified according to the latest genome database. Through bioinformatic approaches, the physicochemical characteristics, phylogenetic relationships, and structural features of ZmAQPs were analyzed. The gene expression analysis of 20 high-resolution and multi-tissues samples showed that ZmAQPs had distinct spatiotemporal and tissue-specific expression profiles during seed germination and early seedling development. We then focused on the aquaporin of maize tonoplast intrinsic protein 3 (ZmTIP3), which is specifically expressed in germinating seed. A mutant zmtip3-1 with disruption of the ZmTIP3-1 gene showed shorter shoot and root length, and decreased seedling dry weight compared with the control (W22). The result revealed that ZmTIP3-1 improved the absolute content of seed protein and promoted storage reserves mobilization, suggesting that ZmTIP3 may be a positive regulator of seed vigor. This work provides valuable clues for understanding the function and possible regulatory mechanism of ZmAQPs in seed germination and seedling growth.
Implementation of Long Short-Term Memory (LSTM) Models for Engagement Estimation in Online Learning

Considering that engagement is a dynamic inner state, understanding learners' engagement is an essential component for educators to provide personalized pedagogy in any learning setting. In online learning settings, reliable engagement estimation of learners is crucial for monitoring the quality of learning. In this paper, we discuss sequence-based engagement estimations using Long Short-Term Memory (LSTM) models with The Dataset for the Affective States in E-Environment (DAiSEE). The engagement states were classified as Not Engaged, Normally Engaged, and Very Engaged. We aimed to identify the most effective combination of pre-processing methods for an imbalanced distribution dataset by applying pre-processed meth-ods: undersampling, oversampling, normalization, dimensional reduction, and the combination scenarios where the order of the pre-processed methods. The processed data were then used as the input to test four different LSTM models: single-LSTM, stacked-LSTM, Bidirectional LSTM (Bi-LSTM), and Multilayer Bi-LSTM. Overall, the Multilayer Bi-LSTM in the pre-processing scenario 4 yield the best performance, with a validation accuracy of 0.902.
Evaluation framework for control of integrated urban drainage systems

Control solutions are slowly finding their way into urban drainage systems although the potential of the technology was acknowledged already in the mid seventies. This paper addresses the problem of how to evaluate the potential of real time control solutions to urban drainage systems. As a starting point the paper looks at some drivers for real time control. This is followed by a general discussion on the role of uncertainties involved with modelling of urban drainage systems and in particular with model predictive control. Finally an early stochastic evaluation framework to assess the control potential is proposed . If the control solution turns out to be the favoured option, this will imply the development of stochastic adaptive controllers.
Analog Demultiplexer Operating at up to 200 GS/s Using Four Time Interleaved Switched Emitter Followers with a 50% Duty Cycle Clock

This paper presents the design and experimental results of a voltage mode analog demultiplexer (ADeMUX) that uses four time interleaved switched emitter follower track-and-hold (T/H) circuits. The preamplifiers and sampling cores are linearized for ultra-broadband operation. With the utilized 90-nm SiGe-BiCMOS technology offering 300 GHz fT and 480 GHz fmax, we are able to operate the ADeMUX with up to 4 x 50 GS/s = 200 GS/s - the highest reported sampling rate to date. Compared with the state-of-the-art current mode ADeMUX circuits, the presented device offers an increase in sampling rate of more than 50%. At 128 GS/s, the chip shows the highest input bandwidth of more than 50 GHz and a linearity of more than 3 bit. This ultra-broadband analog time interleaver can be used to feed four analog-to-digital converters in CMOS technology, due to the reduced bandwidth requirement of only 16 GHz for operation at 128 GS/s or 25 GHz for 200 GS/s.
Neural Joint Source-Channel Decoding using Arithmetic Codes

Traditional iterative joint source-channel coding (JSCD) scheme based on soft-in-soft-out (SISO) decoding for arithmetic codes (AC) has a very high implementation complexity, which will cause an unbearable decoding latency due to a plenty of AC decoding steps and cross-layer interactions between physical layer and application layer. To tackle this, we propose a learning-based joint source-channel decoding approach, neural-JSCD, which consists of a series of AC SISO decoders and channel SISO decoders. The proposed approach introduces weights and offset factors to the simplified AC SISO decoders and damping factors to the output extrinsic information of both AC and channel SISO decoders, cooperated with trainable low-density parity-check (LDPC) neural decoders to realize the iterative decoding for AC. Through a greedy training method based on gradient descent, the learnable factors of neural-JSCD can be tuned to learn the a priori information of arithmetic codes, thus avoiding the great number of AC decoding steps together with cross-layer interactions during the iterative decoding process and rapidly reducing the implementation complexity of iterative AC decoding. Simulation results show that with a better decoding performance, neural-JSCD can reduce the number of iterations by at least 50% with no AC decoding steps and cross-layer interactions compared to traditional JSCD, in consequence, it greatly reduces the decoding latency of iterative decoding.
Improved Multi-step FCS-MPCC with Disturbance Compensation for PMSM Drives

In this paper, an improved multi-step finite control set model predictive current control (FCS-MPCC) strategy with speed loop disturbance compensation for permanent magnet synchronous machine (PMSM) drives system is proposed. In order to improve the steady-state performance of the system, multi-step prediction has been proposed in FCS-MPCC strategy. However, because the conventional multi-step prediction has the defect of heavy computational burden, an improved multi-step finite control set model predictive current control (IM MPCC) strategy is proposed. Furthermore, in order to improve the dynamic response of the system, a disturbance compensation (DC) mechanism based on extended state observer (ESO) is added to estimate and compensate the total disturbance in the speed loop for PMSM system. The simulation results validate the effectiveness of the proposed control strategy.
An Investigation of Compound Variable Names Toward Automated Detection of Confusing Variable Pairs

A successful naming of variables is key to making the source code readable. Programmers may use a compound variable name by concatenating two or more words to make it easier to understand and more informative. While each compound variable name itself may be easy-to-understand, a collection of such variables sometimes makes a “confusing” variable pair if their names are highly similar, e.g., “shippingHeight,” vs. “shippingWeight. ” A confusing variable pair would adversely affect the code readability because it may cause a misreading or a mix-up of variables. Toward automated support for enhancing the code readability, this paper conducts a large-scale investigation of compound variable names in Java programs to find quantitative criteria of the confusing variable pairs. The investigation collects 31,806,749 pairs of compound-named variables from 684 open-source Java projects and analyzes them from two different perspectives of name similarity: the string similarity and the semantic similarity.
A Model for Analysis of IoT based Aquarium Water Quality Data using CNN Model

Water is essential for the survival and wellness of humans and other ecosystems. The mix of physical and chemical characteristics in a water sample is referred to as water quality. Mainly, water quality is critical in achieving a long-term sustainable aquaculture system. Conducting water quality parameter evaluations is crucial for executing an assessment operation and developing a more effective water resources management and planning strategy in aquaculture. The cumulative impact of water quality parameters may devastate the whole system if not managed properly. Predominantly, early diagnosis of fish illnesses and identifying the underlying causes are critical for farmers to take precautions to prevent an epidemic. Typically, fish illnesses are caused by viruses and bacteria. The presence of these pathogens may alter the pH, D.O. , BOD, COD, E.C. , PO43-, NO3-N, and NH3-N levels in the water. Previously, water quality was measured using handheld devices and mathematical functions. But these models fail in getting practical water quality analysis. The advances of IoT and deep learning technology adopted to aquaculture give insight analysis on the water for aquaculture. Most of the researchers working with water quality data based on one parameter and analysis with limited samples. This paper used the convolution neural networks (CNN)to classify water quality data to classify the water quality effectively for fish growth and survival with all the water quality parameters and with a good number of samples. The proposed model is compared with the existing models. Performance results show the impact of the proposed model.