Miracle-dz/UniFAR-FTUs huggingface dataset:
Increased Akkermansia abundance is associated with increased colonic mucosal Ï-3 fatty acids and decreased colonic mucosal PGE2 concentrations following healthy dietary pattern interventions

Both increased dietary intake of {omega}-3 polyunsaturated fatty acids (PUFA) and subsequent increases in colonic mucosal {omega}-3 PUFA concentrations have been linked to improved gut barrier function and decreased risks of metabolic diseases and cancer. In addition, increased dietary {omega}-3 PUFA has been linked to eubiosis in mouse studies. Increased {omega}-3 PUFA function in part to reduce cyclooxygenase-(COX) mediated prostaglandin E2 (PGE2) production, a biomarker of cancer risk linked to compromised gut barrier function. We analyzed data from a dietary intervention study in individuals at increased risk of colon cancer to determine whether changes in the mucosal microbiome composition were associated with changes in colonic mucosal {omega}-3/ {omega}-6 PUFA ratio. Microbiome analyses of colonic biopsies before and after the dietary intervention from 86 participants were done by sequencing the V4 region of the 16S rRNA gene. Multivariable linear regression models were used to evaluate further whether changes in Akkermansia was associated with changes in each colonic tissue variable: {omega}-3/{omega}-6 PUFA ratios, PGE2 concentrations, and expression of COX-1 and COX-2. The median dietary intake and mucosal {omega}-3/{omega}-6 PUFA ratio increased after intervention. Greater increases in mucosal {omega}-3/{omega}-6 PUFA ratios after intervention were significantly associated with several changes in taxon abundance, including increased Akkermansia muciniphilia relative abundance. An increased abundance of Akkermansia muciniphilia also was associated significantly with decreased PGE2 concentrations but not with changes in COX expression. Further studies are warranted to elucidate mechanisms by which Akkermansia may affect or is affected by these pathways and the relative importance of individual dietary components.
Axillary microbiota is associated with cognitive impairment in Parkinson's disease patients

Introduction: Cognitive impairment (CI) is among the most common non-motor symptoms of Parkinson's disease (PD) with substantially negative impact on patient management and outcome. The development and progression of CI exhibits high interindividual variability which requires better diagnostic and monitoring strategies. PD patients often display sweating disorders resulting from autonomic dysfunction which has been associated with CI. As the axillary microbiota is known to change with humidity level and sweat composition, we hypothesized that axillary microbiota of PD patients shifts in association with CI progression thus can be used as proxy for classification of CI stages in PD. Methods: We compared the axillary microbiota compositions of 103 PD patients (55 PD patients with dementia (PDD) and 48 PD patients with mild cognitive impairment (PD-MCI)) and 26 cognitively normal healthy controls (HC). Results: We found that axillary microbiota profiles differentiate HC, PD-MCI and PDD groups based on differential ranking analysis and detected an increasing trend in the log ratio of Corynebacterium to Anaerococcus in progression from HC to PDD. In addition, phylogenetic factorization revealed that the depletion of Anaerococcus, Peptoniphilus and W5053 genera is associated with PD-MCI and PDD. Moreover, functional predictions suggested significant increase of myo-inositol degradation, ergothioneine biosynthesis, propionate biosynthesis, menaquinone biosynthesis, and the proportion of aerobic bacteria and biofilm formation capacity in parallel to CI. Conclusion: Our results suggest that alterations in axillary microbiota are associated with CI in PD. Thus, axillary microbiota holds potential to be exploited as a non-invasive biomarker in the development of novel strategies.
Identification of Prognostic lncRNA Related to the Immune Microenvironment of Soft Tissue Sarcoma

Background Soft tissue sarcoma is a malignant tumor with high degree of malignancy and poor prognosis, originating from mesenchymal tissue. Long noncoding RNAs (lncRNAs) are involved in various biological and pathological processes in the body. They perform preprocessing, splicing, transport, degradation, and translation of mRNA to achieve posttranscriptional level regulation, resulting in the occurrence, invasion, and metastasis of tumors. Therefore, they are highly relevant with regard to early diagnoses and as prognostic indicators. Objective The objective of the present study was to identify immune microenvironment-related lncRNAs that can be used to predict soft tissue sarcomas. Methods Clinical data and follow-up data were obtained from the cBioPortal database, and RNA sequencing data used for the model structure can be accessed from The Cancer Genome Atlas (TCGA) database. LncRNAs were screened by differential expression analysis and coexpression analysis. The Cox regression model and Kaplan–Meier analysis were used to study the association between lncRNAs and soft tissue sarcoma prognosis in the immune microenvironment. Unsupervised cluster analysis was then completed to discover the impact of screening lncRNAs on disease. We constructed an mRNA-lncRNA network by Cytoscape software. Finally, qRT-PCR was used to verify the difference in the expression of the lncRNAs in normal cells and sarcoma cells. Results Unsupervised cluster analysis revealed that the 210 lncRNAs screened showed strong correlation with the tumor immune microenvironment. Two signatures containing seven and five lncRNAs related to the tumor microenvironment were constructed and used to predict overall survival (OS) and disease-free survival (DFS). The Kaplan–Meier (K-M) survival curve showed that the prognoses of patients in the high-risk and low-risk groups differed significantly, and the prognosis associated with the low-risk group was better than that associated with the high-risk group. Two nomograms with predictive capabilities were established. qRT-PCR results showed that the expression of AC108134.3 and AL031717.1 was significantly different in normal and sarcoma cells. Conclusion In summary, the experimental results showed that lncrnA associated with immune microenvironment was related to tumor, which may provide a new idea for immunotherapy of STS.
Collaborative Robot Risk of Passage Among Dynamic Obstacles

Industry 4.0 projects ubiquitous collaborative robots in smart factories of the future, particularly in assembly and material handling. To ensure efficient and safe human-robot collaborative interactions, this paper presents a novel algorithm for estimating Risk of Passage (ROP) a robot incurs by passing between dynamic obstacles (humans, moving equipment, etc.). This paper posits that robot trajectory durations will be shorter and safer if the robot can react proactively to predicted collision between a robot and human worker before it occurs, compared to reacting when it is imminent. I.e., if the risk that obstacles may prohibit robot passage at a future time in the robot’s trajectory is greater than a user defined risk limit, then an Obstacle Pair Volume (OPV), encompassing the obstacles at that time, is added to the planning scene. Results found from simulation show that an ROP algorithm can be trained in ∼120 workcell cycles. Further, it is demonstrated that when a trained ROP algorithm introduces an OPV, trajectory durations are shorter compared to those avoiding obstacles without the introduction of an OPV. The use of ROP estimation with addition of OPV allows workcells to operate proactively smoother with shorter cycle times in the presence of unforeseen obstacles.
Telehealth in paediatric occupational therapy: a scoping review

This study reviewed the use of telehealth in paediatric occupational therapy practice and its clinical outcomes over the past 20 years. A scoping review following Arksey and O'Malley's five stages was undertaken using six databases and Google Scholar. The scoping review covered articles from January 2000 to April 2020. A total of 22 articles were reviewed. Most studies indicated positive outcomes of using telehealth in paediatric occupational therapy practice. Although there is insufficient evidence, the results indicated that telehealth can be more effective than face-to-face interventions when there are mobility or travel challenges for children. The use of telehealth in paediatric occupational therapy is an alternative service delivery model, facilitating access for children and their families to the rehabilitation services. Further research is needed to address the difficulties and potential solutions to expand the use of telehealth services to help children with disadvantages alongside their families.
Optimal Configuration of Hybrid AC/DC Distribution Network Considering the Temporal Power Flow Complementarity on Lines

To mitigate the voltage violation and overloading caused by the integration of Distributed Generation (DG) and Electric Vehicle Charging (EVC) loads, a feasible solution is to convert some AC medium voltage distribution lines to DC ones and formulate an AC/DC hybrid distribution network, based on which flexible power shifting between lines can be achieved. However, the complementarity of power flows amongst AC/DC lines is hardly described and embedded in existing configuration optimization methods in which only the average loading or the variations of loading for a certain period is considered. Solution space will be geometrically increased if operation scenarios are fully simulated for configuration caused by the strong uncertainties of DGs and EVC loads. This paper proposes an analytic quantifiable method to describe the power complementarity between AC/DC lines. The Gaussian mixture model is used to depict the temporal correlation and uncertainties. The complementarity is calculated by the conditional probability of multi-dimensional joint probability density function of AC/DC hybrid lines. Accordingly, an optimal configuration method of hybrid AC/DC distribution network is proposed considering the complementarity of power flows on AC/DC lines, in which the size and location of Voltage Source Converters (VSCs) are optimized. Simulations studies are performed to verify the proposed method.
Black and White Couples: Exploring the Role of Religiosity on Perceived Racial Discrimination and Relationship Satisfaction

Abstract The current study set out to examine the influence of religiosity on the relationship between interracial Black-White (IBW) couples’ perceived discrimination and marital satisfaction. Data from 178 Black-White couples were used to test a common fate moderation model. Results revealed a negative association between partners’ perceived discrimination and marital satisfaction. Also, White partners’ religiosity was found to moderate the effects of discrimination on satisfaction, whereby a higher level of religiosity contributed to higher satisfaction when couples experienced discrimination. Results suggested that religiosity may be an important resource to help Black-White couples manage discrimination stress.
Microstructural deficits of the thalamus in major depressive disorder

Macroscopic structural abnormalities in the thalamus and thalamic circuits have been shown to contribute to the neuropathology of major depressive disorder (MDD). However, cytoarchitectonic properties underlying these macroscopic abnormalities remain unknown. The purpose of this study was to identify systematic deficits of brain architecture in depression, from structural brain network organization to microstructural properties. A multi-modal neuroimaging approach including diffusion, anatomical and quantitative magnetic resonance imaging (MRI) was used to examine structural-related alternations in 56 MDD patients compared with 35 age- and sex-matched controls. Structural networks were constructed and analyzed using seed-based probabilistic tractography. Morphometric measurements, including cortical thickness and voxel-based morphometry (VBM), were evaluated across the whole brain. A conjunction analysis was then conducted to identify key regions showing common structural alternations across modalities. The microstructural properties, macromolecular tissue volume (MTV) and T1 relaxation times of identified key regions were then calculated. Results showed multiple alterations of structural connectivity within a set of subcortical areas and their connections to cortical regions in MDD patients. These subcortical regions included the putamen, thalamus and caudate, which are predominately involved in the limbic-cortical-striatal-pallidal-thalamic network (LCSPT). Structural connectivity was disrupted within and between large-scale networks, mainly including subcortical networks, default mode networks and salience/ventral attention networks. Consistently, these regions also exhibited widespread volume reductions in MDD patients, specifically the bilateral thalamus, left putamen and right caudate. Importantly, the microstructural properties, T1 relaxation time of left thalamus were increased and negatively correlated with its gray matter volume in MDD patients. The present work to date sheds light on the neuropathological disruptions of LCSPT circuit in MDD, providing the first multi-modal neuroimaging evidence for the macro-micro structural abnormalities of the thalamus in patients with MDD. These findings have implications in understanding the abnormal changes of brain structures across development of MDD.
LSTM Android Malicious Behavior Analysis Based on Feature Weighting

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.
A Cluster of FPAAs to Recognize Images Using Neural Networks

Analog computing has been recovering its relevance in the recent years. Field-Programmable Analog Arrays (FPAAs) are the equivalent to Field-Programmable Gate Arrays (FPGAs) but in the analog and mixed-signal domain. In order to increase the amount of analog resources, in this brief a cluster of 40 FPAAs is proposed. As a use case, a 19-8-6-4 feedforward Neural Network has been implemented on such cluster. With the help of a DCT-based software framework, this NN is able to classify <inline-formula> <tex-math notation="LaTeX">$28 \times 28$ </tex-math></inline-formula> images from MNIST. Results show that the analog network is able to obtain similar results as the software baseline network.
Active Restoration Initiates High Quality Forest Succession In A Deforested Landscape In Amazonia

Background: Amazonia is well known for its high natural regeneration capacity; for this reason, passive restoration is normally recommended for the recovery of its degraded forests. However, highly deforested landscapes in southern Amazonia require active restoration. Since restoration methods can shape the quality and speed of early forest recovery, this study aimed to verify how active restoration pushes non-resilient sites towards forest recovery. Methods: We evaluated early forest succession at active restoration sites, i.e. soil plowing, direct seeding of pioneer species and seedling stock planting at low density. We analyzed forest structure, diversity and species composition in two age classes, 0.5 – 3.5 and 4.5 – 7.5 years old. As reference, we evaluated natural regeneration as performed on more resilient sites in the same region. We sampled 36 active restoration and 31 natural regeneration sites along the Madeira river, southern Amazonia. Results: Active restoration triggered succession to similar or higher levels of forest structure than sites where natural regeneration was taking place. The most dominant species did not overlap between active restoration and natural regeneration sites. The overall composition of species was different between the two restoration methods. Dominant species and size class distribution indicate that active restoration is performing successfully. Conclusions: Soil preparation combined with a high availability of seeds of pioneer trees resulted in a high stem density and basal area of facilitative pioneer trees. Planted seedlings added species diversity and increased density of large trees. Interventions to increase the odds of natural regeneration can be effective for non-resilient sites located in resilient landscapes.
COVID-19 Impact on Socioeconomic in the Hospitality Industry

Objective - This paper provides an overview of the COVID-19 crisis and the impact of restriction orders on the hospitality industry in Malaysia. The authors review existing studies related to COVID-19 and the hospitality industry while focusing on challenges faced by the hospitality industry in Malaysia. Then, the authors summarize the socioeconomic impact of COVID-19 on the hospitality industry. Methodology/Technique - This paper examines previous COVID-19 related research published in top-tier hospitality journals during the pandemic period of December 2019 to September 2021. Research studies were categorized by topic area, hospitality industry segment, and research methods used. Additionally, the authors explored the socioeconomic impact of the COVID-19 on hospitality industry using content analysis. Findings - Most articles focused on administration/strategy, marketing, and human resources. The findings showed some potential shifts in the methods used by researchers who published during the pandemic. The findings revealed that the pandemic has negatively impacted the socioeconomic situation in many countries. Employment, public safety, finance, and physical and mental health are among the pressing issues highlighted by most researchers. Based on the findings, the authors provide insights and recommendations for further research. Novelty - This paper represents a pioneering attempt to identify a potentially unexplored area of research related to COVID-19, particularly in Malaysia. The novelty of this paper is that the authors provide substantial discussion on the socioeconomic impact of the COVID-19 on various countries' hospitality and tourism industries. Type of Paper - Empirical. Keywords: Foodservice; Hospitality; Hotel; Malaysia; Pandemic; Socioeconomic impact; Tourism. JEL Classification: Z30
Optical Energy Harvesting in Vibrate Maglev Graphite

In this paper, we design an optical energy harvesting system composed of a magnet with a smooth surface, magnetically levitated pyrolytic graphite, and a light source. A periodic force field was constructed by modulating the light absorption of graphite at different positions through the interference of light on the smooth magnet surface and the linear variation of graphite magnetization with light absorption, thereby driving the graphite to vibrate periodically. It is confirmed in our study that this photo-magnetic effect can convert continuous light energy into vibrational kinetic energy, the driving light intensity can be reduced by 3-4 orders of magnitude and the amplitude can reach tens of microns, and the wavelength range of the driving light can cover the visible and infrared light bands, which makes it possible to develop a new type of light-driven micro-nano mechanical motor or light energy harvesting system.
Empirical Research Frameworks in a Changing World: The Case of Audit Data Analytics

The field of auditing is undergoing a fundamental change due to advances in data analytics. The main objective of this paper is to develop a holistic, multidimensional framework in order to better understand the dynamics of diffusion of audit data analytics and to address issues related to change, especially from the perspective of empirical research. The framework we developed covers categories related to the diffusion of data analytics (the technology, the actors using it, and the external rules that regulate it) and to the actors reproducing rules and technologies (focusing on the audit process, and cognitive processes). Examining these different categories and their relationships helps to understand the evolving issues, and to view existing problems from a new angle. We also analyse key findings of 37 empirical studies within and across the interrelated categories in order to identify new directions for impactful empirical research. By illustrating the insights that emerge from this holistic perspective, the paper is especially of interest to audit researchers as well as to standard setters and audit practice.
Development as Flourishing

Although economists have broadened their interests considerably since Robert Lucas equated economic development with income growth, the ultimate objective of development is hitherto often defined in monetary terms. Amartya Sen’s capability approach offers a much richer account of a good life and has influenced development debates in academia and beyond. Nevertheless, mainstream economists appear reluctant to embrace Sen’s ideas due to their immense complexity, explicit treatment of values, and operationalisation challenges. The aim of this dissertation is to propose a novel operationalisation of the capability approach, one that is sufficiently precise and simple to be applied at scale, yet at the same time remains true to the spirit of Sen’s ideas. The proposal is based on the concept of human flourishing borrowed from the emerging field of positive psychology. In particular, the dissertation addresses two objectives. First, it demonstrates that flourishing is a theoretically sound operationalisation of the capability approach by critically analysing the concept in terms of the four requirements proposed by Comim (2008). Second, it demonstrates that flourishing can offer novel and useful insights about development to economics by evaluating existing evidence on the correlates and antecedents of flourishing using a rapid literature review. Taken together, the findings of this dissertation strongly suggest that flourishing could be employed as an overarching objective of development in economics. The conclusion has exciting implications for development research and practice.
Wealth creation through market concentration in the Asia-Pacific banking sector

We analyze the financial sector consolidation in the Asia-Pacific region using a sample of 581 bank merger and acquisition (M&A) announcements. We find that Asian bidders and their rivals benefit from consolidation, particularly in case of larger bidders and national transactions. Tar-gets and their rivals likewise gain, with larger banks more likely targeted by Asian institutions. We also document significant increases in target countries' market concentration ratios following transactions. Contrary to most research focusing on the U.S. and Europe, we provide strong evidence that market power considerations are the dominant motivation behind bank M&As in the Asia-Pacific region.