Miracle-dz/UniFAR-FTUs huggingface dataset:
Face off: Travel Habits, Road Conditions and Traffic City Characteristics Bared Using Twitter

The adequacy of traditional transport related issues detection is often limited by physical sparse sensor coverage and reporting incident/issues to the emergency response system is labor intensive. The social media tweet text have been mined so as to identify the complaints regarding various road transportation issues of traffic, accident, and potholes. In order to identify and segregate tweets related to different issues, keyword-based approaches have been used previously, but these methods are solely dependent on seed keywords which are manually given and these set of keywords are not sufficient to cover all tweets posts. So, to overcome this issue, a novel approach has been proposed that captures the semantic context through dense word embedding by employing word2vec model. However, the process of tweet segregation on the basis of semantic similar keywords may suffer from the problem of pragmatic ambiguity. To handle this, Word2Vec model has been applied to match the semantically similar tweets with respect to each category. Furthermore, the hotspots have been identified corresponding to each category. However, due to the scarcity of geo-tagged tweets, we have proposed a hybrid method which amalgamates Named Entity Recognition (NER), Part of speech (POS), and Regular Expression (RE) to extract the location information from the tweet textual content. Due to the lack of availability of the ground truth dataset, model feasibility has been validated from the existing data records (i.e., published by government official accounts and reported on news media) and the evaluation results signify that the stated approach identifies few additional hotspots as compared to the existing reports while analyzing the tweets.
Single versus Multi-Source Discrimination in Birdcalls using Zero-Frequency Filtering

In the processing of bioacoustic recordings such as birdcalls, sometimes it is desirable to determine if a recording has one bird calling or has more than one. In this paper, we utilize the well-established zero-frequency filtering method, used for determining significant instants of excitation (also called epochs), for this task. By determining the average number of epochs per second, we are able to reliably discriminate birdcalls made by a single bird from those made by multiple birds. Experimental evaluation on three bioacoustic datasets confirms the reliability of the method. Species identification studies using deep neural network classifiers highlight the utility of the method.
Crowdsourcing Database Systems: Overview and Challenges

Many data management and analytics tasks, such as entity resolution, cannot be solely addressed by automated processes. Crowdsourcing is an effective way to harness the human cognitive ability to process these computer-hard tasks. Thanks to public crowdsourcing platforms, e.g., Amazon Mechanical Turk and CrowdFlower, we can easily involve hundreds of thousands of ordinary workers (i.e., the crowd) to address these computer-hard tasks. However it is rather inconvenient to interact with the crowdsourcing platforms, because the platforms require one to set parameters and even write codes. Inspired by traditional DBMS, crowdsourcing database systems have been proposed and widely studied to encapsulate the complexities of interacting with the crowd. In this tutorial, we will survey and synthesize a wide spectrum of existing studies on crowdsourcing database systems. We first give an overview of crowdsourcing, and then summarize the fundamental techniques in designing crowdsourcing databases, including task design, truth inference, task assignment, answer reasoning and latency reduction. Next we review the techniques on designing crowdsourced operators, including selection, join, sort, top-k, max/min, count, collect, and fill. Finally, we discuss the emerging challenges.
The Class III Peroxidase (POD) Gene Family in Cassava: Identification, Phylogeny, Duplication, and Expression

The class III peroxidase (POD) enzymes participate in plant development, hormone signaling, and stress responses. However, little is known about the POD family in cassava. Here, we identified 91 cassava POD genes (MePODs) and classified them into six subgroups using phylogenetic analysis. Conserved motif analysis demonstrated that all MePOD proteins have typical peroxidase domains, and gene structure analysis showed that MePOD genes have between one and nine exons. Duplication pattern analysis suggests that tandem duplication has played a role in MePOD gene expansion. Comprehensive transcriptomic analysis revealed that MePOD genes in cassava are involved in the drought response and postharvest physiological deterioration. Several MePODs underwent transcriptional changes after various stresses and related signaling treatments were applied. In sum, we characterized the POD family in cassava and uncovered the transcriptional control of POD genes in response to various stresses and postharvest physiological deterioration conditions. These results can be used to identify potential target genes for improving the stress tolerance of cassava crops.
Complementing a Clinical Trial With Human-Computer Interaction: Patients’ User Experience With Telehealth

Background The use of telehealth to monitor patients from home is on the rise. Telehealth technology is evaluated in a clinical trial with measures of health outcomes and cost-effectiveness. However, what happens between a technology and the patients is not investigated during a clinical trial—the telehealth technology remains as a “black box. ” Meanwhile, three decades of research in the discipline of human-computer interaction (HCI) presents design, implementation, and evaluation of technologies with a primary emphasis on users. HCI research has exposed the importance of user experience (UX) as an essential part of technology development and evaluation. Objective This research investigates the UX of patients with type 2 diabetes mellitus (T2D) with a telehealth in-home monitoring device to manage T2D from home. We investigate how the UX during a clinical trial can be researched and what a clinical trial can learn from HCI research. Methods We adopted an ethnographic philosophy and conducted a contextual inquiry due to time limitations followed by semistructured interviews of 9 T2D patients. We defined the method as Clinical User-experience Evaluation (CUE). The patients were enrolled in a telehealth clinical trial of T2D; however, this research was an independent study conducted by information technologists and health researchers for a user-centered evaluation of telehealth. Results Key analytical findings were that patients valued the benefits of in-home monitoring, but the current device did not possess all functionalities that patients wanted. The results include patients’ experiences and emotions while using the device, patients’ perceived benefits of the device, and how patients domesticated the device. Further analysis showed the influence of the device on patients’ awareness, family involvement, and design implications for telehealth for T2D. Conclusions HCI could complement telehealth clinical trials and uncover knowledge about T2D patients’ UX and future design implications. Through HCI we can look into the “black box” phenomenon of clinical trials and create patient-centered telehealth solutions.
Respiratory Complications of Stroke

Stroke is the third leading cause of death in the United States. Stroke survivors often experience medical complications and long-term disability. Disturbances in respiratory system function and complications affecting the respiratory system are common after stroke. The nature of these disorders depends on the severity and site of neurological injury. Alterations in breathing control, respiratory mechanics, and breathing pattern are common and may lead to gas exchange abnormalities or the need for mechanical ventilation. Stroke can lead to sleep disordered breathing such as central or obstructive sleep apnea. Sleep disordered breathing may also play a role in the pathogenesis of cerebral infarction. Venous thromboembolism, swallowing abnormalities, aspiration, and pneumonia are among the most common respiratory complications of stroke. Neurogenic pulmonary edema occurs less often. Close observation of the stroke patient for these potential disturbances, and implementation of prophylactic measures can prevent significant morbidity and mortality.
Estimation of invasive physiological parameters from non invasive parameters using dimensionless numbers and Monte Carlo cross-validation

According to NCEP-ATPIII criterion, metabolic syndrome (MS) diagnosis is based in the measurement of invasive (triglycerides, HDL, glucose) and non invasive variables (height, weight, waist circumference). The aim of this work is find, since dimensionless numbers design from physiological (π<inf>1IS</inf>, π<inf>2IS</inf>) and heart rate variability (π<inf>1HRV</inf>, π<inf>2HRV</inf>) parameters, three polynomial equations (π<inf>1IS</inf>=f(π<inf>2HRV</inf>), π<inf>2IS</inf>=f(π<inf>1HRV</inf>), π<inf>2IS</inf>=f(π<inf>2HRV</inf>)) that relate invasive with non invasive variables. In this sense, a fitting using Monte Carlo cross validation (MCCV) was performed. A database of 40 subjects (25 control subjects and 15 subjects with MS) was employed. The results suggest that MCCV improves the coefficient of determination (R<sup>2</sup>), compared to the application of the least squares method only, in each polynomial: π<inf>1IS</inf>=f(π<inf>2HRV</inf>) (R<sup>2</sup>=0.62 vs. 0.21), π<inf>2IS</inf>=f(π<inf>1HRV</inf>) (R<sup>2</sup>=0.62 vs. 0.36) and π<inf>2IS</inf>=f(π<inf>2HRV</inf>) (R<sup>2</sup>=0.56 vs. 0.19). The fitting by MCCV allows the estimation of invasive from non invasive parameters.
Workload-Aware Subgraph Query Caching and Processing in Large Graphs

A subgraph query q that finds as output all its subgraph-isomorphic embeddings from a data graph g has been core to modern declarative querying in large graphs. In this paper, we address subgraph queries with the availability of query workload information, W = {w1,. , wn}, where wi in W is a previously issued query with all its subgraph-isomorphic embeddings cached beforehand. We introduce a workload-aware subgraph querying framework, WaSQ, that leverages query workload for subgraph query rewriting, search plan refinement, partial results reusing, and false positive filtering towards facilitating the whole subgraph querying process. Experimental studies in real-world graphs demonstrate that WaSQ achieves significant and consistent performance gains in comparison with state-of-the-art, workload-oblivious solutions for large-scale subgraph querying.
Modern unexplored martial arts – what can mixed martial arts and Brazilian Jiu-Jitsu do for youth development?

Abstract Contemporarily, two martial arts have emerged as highly popular among youth; Mixed Martial Arts (MMA) and Brazilian Jiu-Jitsu (BJJ). Despite their popularity, we know little of how they affect individuals sociopsychologically. The current study sought to explore how the currently underexplored martial art disciplines may contribute to sociopsychological development among young people. In addition, it was investigated whether individuals who are predisposed to different traits may favour one sport over the other. This study was conducted with a longitudinal design; over the course of 5 months, 113 participants completed training in either condition. The results show that both groups displayed increased self-control and pro-social behaviour; however, MMA practitioners also reported increased aggressiveness, whereas BJJ practitioners experienced a decline in aggression. Accordingly, individuals who trained in MMA displayed substantially higher pre-existing aggression levels than the BJJ practitioners. The current results further corroborate research suggesting that modern martial arts and MMA may not be suitable for at-risk youth to practice, whereas traditional martial arts and sports with a healthy philosophical foundation may be effective in reducing antisocial behaviour while enhancing socially desirable behaviour among young people.
Traditional Chinese medicine therapy reduces the risk of total knee replacement in patients with knee osteoarthritis

Abstract Knee osteoarthritis is a degenerative disease occurring in elderly people worldwide. For severe knee osteoarthritis, total knee replacement is the final treatment option. Traditional Chinese medicine (TCM) is popular in Taiwan and has been shown to exert therapeutic effects on knee osteoarthritis. We investigated the long-term clinical effects of TCM for reducing the need for total knee replacement risk in patients with knee osteoarthritis. We used the National Health Insurance Research Database to conduct a retrospective study of patients with knee osteoarthritis between 1997 and 2003 in Taiwan. Data from the date of diagnosis of knee osteoarthritis to total knee replacement were assessed using the Cox regression proportional hazards model, and the Kaplan–Meier survival curve was used to determine the association between total knee replacement risk and TCM use. A total of 34,231 patients with knee osteoarthritis, who were diagnosed by orthopedic or rehabilitation physicians between 1997 and 2003 were included. Patients were categorized into 2 groups: 26,257 (76.7%) were TCM users and 7974 (23.3%) were TCM non-users. The mean follow-up period was 9.26 years. Multivariate regression demonstrated that using TCM may decrease the need for total knee replacement in patients with knee osteoarthritis (adjusted hazards ratio [aHR] = 0.69, 95% confidence interval [95% CI]: 0.64–0.77) compared with TCM non-users. A relationship between longer TCM use and reduced total knee replacement use was observed, especially in patients who used TCM for ≥120 days (aHR = 0.49, 95% CI: 0.42–0.56). The results of this study suggested that TCM is associated with a reduced risk of total knee replacement in patients with knee osteoarthritis, with enhanced benefits from longer durations of TCM use.
Constructing Features for Detecting Android Malicious Applications: Issues, Taxonomy and Directions

The number of applications (apps) available for smart devices or Android based IoT (Internet of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill-designed or malicious apps (malapps) has been growing explosively. To ensure the quality and security of the apps in the markets, many approaches have been proposed in recent years to discriminate malapps from benign ones. Machine learning is usually utilized in classification process. Accurately characterizing apps’ behaviors, or so-called features, directly affects the detection results with machine learning algorithms. Android apps evolve very fast. The size of current apps has become increasingly large and the behaviors of apps have become increasingly complicated. The extracting effective and representative features from apps is thus an ongoing challenge. Although many types of features have been extracted in existing work, to the best of our knowledge, no work has systematically surveyed the features constructed for detecting Android malapps. In this paper, we are motivated to provide a clear and comprehensive survey of the state-of-the-art work that detects malapps by characterizing behaviors of apps with various types of features. Through the designed criteria, we collect a total of 1947 papers in which 236 papers are used for the survey with four dimensions: the features extracted, the feature selection methods employed if any, the detection methods used, and the scale of evaluation performed. Based on our in-depth survey, we highlight the issues of exploring effective features from apps, provide the taxonomy of these features and indicate the future directions.
Inhibition by fluoxetine of LH-stimulated cyclic AMP synthesis in tumor Leydig cells partly involves AMPK activation

Fluoxetine (FLX), a widely used antidepressant primarily acting as a selective serotonin reuptake inhibitor (SSRI), has been shown to exhibit other mechanisms of action in various cell types. Consequently, it might have unexpected adverse effects not related to its intended use, possibly in the endocrine regulation of reproduction. We show in the present report that after a 1-hour preincubation of MLTC-1 Leydig cells with FLX, the intracellular cyclic adenosine monophosphate (cAMP) responses to Luteinizing Hormone (LH) and forskolin (FSK) are reduced through AMPK-dependent and -independent pathways respectively. FLX at low concentrations (12.5μM and 25μM) induced this inhibition without triggering AMPK phosphorylation, while higher FLX concentrations (50μM and 100μM) induced AMPK phosphorylation and lowered ATP concentration similarly to Metformin. Pretreatment with the specific AMPK inhibitor Compound C (CpdC), significantly diminished the inhibition of cAMP synthesis caused by high concentration of FLX. Moreover, as expected FLX also caused a decline of steroidogenesis which is under the control of cAMP. Taken together, these findings demonstrate that the inhibition of cAMP synthesis by FLX is dose-dependent and occurs in MLTC-1 cells through two mechanisms, AMPK-independent and AMPK-dependent, at low and high concentrations, respectively. FLX also inhibited hormone-induced steroidogenesis in MLTC-1 cells and mouse testicular Leydig cells, suggesting similar mechanisms in both cell types.
Phylogenomics reveals an ancient hybrid origin of the Persian walnut.

Persian walnut (Juglans regia) is cultivated worldwide for its high-quality wood and nuts, but its origin has remained mysterious because in phylogenies it occupies an unresolved position between American black walnuts and Asian butternuts. Equally unclear is the origin of the only American butternut, J. cinerea. We re-sequenced the whole genome of 80 individuals from 19 of the 22 species of Juglans and assembled the genome of its relatives Pterocarya stenoptera and Platycarya strobilacea. Using phylogenetic-network analysis of single-copy nuclear genes, genome-wide site pattern probabilities, and Approximate Bayesian Computation (ABC) we discovered that J. regia (and its landrace J. sigillata) arose as a hybrid between the American and the Asian lineages and that J. cinerea resulted from massive introgression from an immigrating Asian butternut into the genome of an American black walnut. ABC modelling placed the hybrid origin in the late Pliocene, ∼3.45 Ma, with both parental lineages since having gone extinct in Europe.
Soluble Nogo receptor 1 fusion protein protects neural progenitor cells in rats with ischemic stroke

Soluble Nogo66 receptor-Fc protein (sNgR-Fc) enhances axonal regeneration following central nervous system injury. However, the underlying mechanisms remain unclear. In this study, we investigated the effects of sNgR-Fc on the proliferation and differentiation of neural progenitor cells. The photothrombotic cortical injury model of ischemic stroke was produced in the parietal cortex of Sprague-Dawley rats. The rats with photothrombotic cortical injury were randomized to receive infusion of 400 μg/kg sNgR-Fc (sNgR-Fc group) or an equal volume of phosphate-buffered saline (photothrombotic cortical injury group) into the lateral ventricle for 3 days. The effects of sNgR-Fc on the proliferation and differentiation of endogenous neural progenitor cells were examined using BrdU staining. Neurological function was evaluated with the Morris water maze test. To further examine the effects of sNgR-Fc treatment on neural progenitor cells, photothrombotic cortical injury was produced in another group of rats that received transplantation of neural progenitor cells from the hippocampus of embryonic Sprague-Dawley rats. The animals were then given an infusion of phosphate-buffered saline (neural progenitor cells group) or sNgR-Fc (sNgR-Fc + neural progenitor cells group) into the lateral ventricle for 3 days. sNgR-Fc enhanced the proliferation of cultured neural progenitor cells in vitro as well as that of endogenous neural progenitor cells in vivo, compared with phosphate-buffered saline, and it also induced the differentiation of neural progenitor cells into neurons. Compared with the photothrombotic cortical injury group, escape latency in the Morris water maze and neurological severity score were greatly reduced, and distance traveled in the target quadrant was considerably increased in the sNgR-Fc group, indicating a substantial improvement in neurological function. Furthermore, compared with phosphate-buffered saline infusion, sNgR-Fc infusion strikingly improved the survival and differentiation of grafted neural progenitor cells. Our findings show that sNgR-Fc regulates neural progenitor cell proliferation, migration and differentiation. Therefore, sNgR-Fc is a potential novel therapy for stroke and neurodegenerative diseases, The protocols were approved by the Committee on the Use of Live Animals in Teaching and Research of the University of Hong Kong (approval No. 4560-17) in November, 2015.
Self-reported needs and experiences of people with dementia living in nursing homes: a scoping review

Abstract Objectives: With rates of dementia continuing to rise, the impetus on improving care for people with dementia is growing. Unmet needs of people with dementia living in nursing homes have been linked with worsening neuropsychiatric symptoms, higher levels of depression, and reduced quality of life. Furthermore, proxy accounts exploring the needs of people with dementia have frequently been shown to be unreliable. Therefore, this literature review aims to explore the self-reported needs and experiences of people with dementia in nursing homes. Method: A scoping review of the literature was carried out using the databases PubMed and PsycINFO to search for relevant articles according to PRISMA guidelines. Search terms were designed to include both quantitative and qualitative study designs. Thematic synthesis was used to categorise findings into themes related to self-reported needs and experiences. Results: A total of 41 articles met the eligibility criteria. An analysis of study characteristics revealed more than half of studies used a qualitative design. Thematic synthesis resulted in eight themes: activities, maintaining previous roles, reminiscence, freedom and choice, appropriate environment, meaningful relationships, support with grief and loss, end-of-life care. Conclusion: Whilst the voice of people with dementia has previously been neglected in research, this review has shown that people with dementia in nursing homes are able to describe their experiences and communicate their needs. The findings in this review have provided a contribution towards guiding evidence-based practice that is tailored to the needs of nursing home residents with dementia.
Jasmonate and auxin perception: how plants keep F-boxes in check.

Phytohormones regulate the plasticity of plant growth and development, and responses to biotic and abiotic stresses. Many hormone signal transduction cascades involve ubiquitination and subsequent degradation of proteins by the 26S proteasome. The conjugation of ubiquitin to a substrate is facilitated by the E1 activating, E2 conjugating and the substrate-specifying E3 ligase. The most prevalent type of E3 ligase in plants is the Cullin-RING ligase (CRL)-type with F-box proteins (FBPs) as the substrate recognition component. The activity of these SKP-Cullin-F-box (SCF) complexes needs to be tightly regulated in time and place. Here, we review the regulation of SCF function in plants on multiple levels, with a focus on the auxin and jasmonate SCF-type receptor complexes. We particularly discuss the relevance of protein-protein interactions and posttranslational modifications as mechanisms to keep SCF functioning under control. Additionally, we highlight the unique property of SCFTIR1/AFB and SCFCOI1 to recognize substrates by forming co-receptor complexes. Finally, we explore how engineered selective agonists can be used to study and uncouple the outcomes of the complex auxin and jasmonate signaling networks that are governed by these FBPs.