Miracle-dz/UniFAR-FTUs huggingface dataset:
Virus–virus interactions and host ecology are associated with RNA virome structure in wild birds

Little is known about the factors that shape the ecology of RNA viruses in nature. Wild birds are an important case in point, as other than influenza A virus, avian samples are rarely tested for viruses, especially in the absence of overt disease. Using bulk RNA‐sequencing (“meta‐transcriptomics”), we revealed the viral diversity present in Australian wild birds through the lens of the ecological factors that may determine virome structure and abundance. A meta‐transcriptomic analysis of four Anseriformes (waterfowl) and Charadriiformes (shorebird) species sampled in temperate and arid Australia revealed the presence of 27 RNA virus genomes, 18 of which represent newly described species. The viruses identified included a previously described gammacoronavirus and influenza A viruses. Additionally, we identified novel virus species from the families Astroviridae, Caliciviridae, Reoviridae, Rhabdoviridae, Picobirnaviridae and Picornaviridae. We noted differences in virome structure that reflected underlying differences in location and influenza A infection status. Red‐necked Avocets (Recurvirostra novaehollandiae) from Australia's arid interior possessed the greatest viral diversity and abundance, markedly higher than individuals sampled in temperate Australia. In Ruddy Turnstones (Arenaria interpres) and dabbling ducks (Anas spp.), viral abundance and diversity were higher and more similar in hosts that were positive for influenza A infection compared to those that were negative for this virus, despite samples being collected on the same day and from the same location. This study highlights the extent and diversity of RNA viruses in wild birds and lays the foundation for understanding the factors that determine virome structure in wild populations.
Robust Neural Abstractive Summarization Systems and Evaluation against Adversarial Information

Sequence-to-sequence (seq2seq) neural models have been actively investigated for abstractive summarization. Nevertheless, existing neural abstractive systems frequently generate factually incorrect summaries and are vulnerable to adversarial information, suggesting a crucial lack of semantic understanding. In this paper, we propose a novel semantic-aware neural abstractive summarization model that learns to generate high quality summaries through semantic interpretation over salient content. A novel evaluation scheme with adversarial samples is introduced to measure how well a model identifies off-topic information, where our model yields significantly better performance than the popular pointer-generator summarizer. Human evaluation also confirms that our system summaries are uniformly more informative and faithful as well as less redundant than the seq2seq model.
Structural and mechanistic aspects of S-S bonds in the thioredoxin-like family of proteins

Abstract Disulfide bonds play a critical role in a variety of structural and mechanistic processes associated with proteins inside the cells and in the extracellular environment. The thioredoxin family of proteins like thioredoxin (Trx), glutaredoxin (Grx) and protein disulfide isomerase, are involved in the formation, transfer or isomerization of disulfide bonds through a characteristic thiol-disulfide exchange reaction. Here, we review the structural and mechanistic determinants behind the thiol-disulfide exchange reactions for the different enzyme types within this family, rationalizing the known experimental data in light of the results from computational studies. The analysis sheds new atomic-level insight into the structural and mechanistic variations that characterize the different enzymes in the family, helping to explain the associated functional diversity. Furthermore, we review here a pattern of stabilization/destabilization of the conserved active-site cysteine residues presented beforehand, which is fully consistent with the observed roles played by the thioredoxin family of enzymes.
RLDB: Robust Local Difference Binary Descriptor with Integrated Learning-based Optimization

Local binary descriptors are well-suited for many real-time and/or large-scale computer vision applications, while their low computational complexity is usually accompanied by the limitation of performance. In this paper, we propose a new optimization framework, RLDB (Robust-LDB), to improve a typical region-based binary descriptor LDB (local difference binary) and maintain its computational simplicity. RLDB extends the multi-feature strategy of LDB and applies a more complete region-comparing configuration. A cascade bit selection method is utilized to select the more representative patterns from massive comparison pairs and an online learning strategy further optimizes descriptor for each specific patch separately. They both incorporate LDP (linear discriminant projections) principle to jointly guarantee the robustness and distinctiveness of the features from various scales. Experimental results demonstrate that this integrated learning framework significantly enhances LDB. The improved descriptor achieves a performance comparable to floating-point descriptors on many benchmarks and retains a high computing speed similar to most binary descriptors, which better satisfies the demands of applications.
The State of Speech in HCI: Trends, Themes and Challenges

Speech interfaces are growing in popularity. Through a review of 99 research papers this work maps the trends, themes, findings and methods of empirical research on speech interfaces in the field of human–computer interaction (HCI). We find that studies are usability/theory-focused or explore wider system experiences, evaluating Wizard of Oz, prototypes or developed systems. Measuring task and interaction was common, as was using self-report questionnaires to measure concepts like usability and user attitudes. A thematic analysis of the research found that speech HCI work focuses on nine key topics: system speech production, design insight, modality comparison, experiences with interactive voice response systems, assistive technology and accessibility, user speech production, using speech technology for development, peoples’ experiences with intelligent personal assistants and how user memory affects speech interface interaction. From these insights we identify gaps and challenges in speech research, notably taking into account technological advancements, the need to develop theories of speech interface interaction, grow critical mass in this domain, increase design work and expand research from single to multiple user interaction contexts so as to reflect current use contexts. We also highlight the need to improve measure reliability, validity and consistency, in the wild deployment and reduce barriers to building fully functional speech interfaces for research.Most papers focused on usability/theory-based or wider system experience research with a focus on Wizard of Oz and developed systems Questionnaires on usability and user attitudes often used but few were reliable or validated Thematic analysis showed nine primary research topics Challenges identified in theoretical approaches and design guidelines, engaging with technological advances, multiple user and in the wild contexts, critical research mass and barriers to building speech interfaces
Dabigatran versus Warfarin for Acute Venous Thromboembolism in Elderly or Impaired Renal Function Patients: Pooled Analysis of RE-COVER and RE-COVER II

Abstract Management of acute venous thromboembolism (VTE) with anticoagulants in elderly patients and those with chronic kidney disease poses special challenges. The RE-COVER and RE-COVER II trials showed that dabigatran 150 mg twice daily was as effective as warfarin over 6 months in preventing recurrent VTE, with a lower bleeding risk. We now assess the effects of old age and renal impairment (RI) on pooled trial outcomes in 5,107 patients: 4,504 aged <75 years and 603 aged ≥75 years. The primary efficacy outcome was symptomatic VTE/VTE-related death. Safety outcomes were centrally adjudicated major bleeding events (MBEs), MBEs or clinically relevant non-major bleeding events (MBEs/CRBEs) and any bleeds. Baseline renal function was categorized as normal, mild RI or moderate RI. A total of 3,698 had normal renal function and 1,100 and 237 had mild and moderate RI, respectively (23 patients with severe RI and 49 with missing creatinine clearance data were not included). For dabigatran, VTE/VTE-related death decreased from 3.1% (normal renal function) to 1.9% for mild RI and to 0.0% for moderate RI. For warfarin, the event rates were 2.6, 1.6 and 4.1%, respectively. Overall, major bleeding increased with increasing RI (p = 0.0037) and with age (p = 0.4350), with no apparent difference between the dabigatran and warfarin patients. Dabigatran shows better efficacy than warfarin in RI and in the elderly patients, probably because of an increase in the concentration of dabigatran. However, bleeding risk increases with both dabigatran and warfarin in the presence of RI.
How to Stop Off-the-Shelf Deep Neural Networks from Overthinking

While deep neural networks (DNNs) can perform complex classification tasks, most of their natural inputs do not necessitate the depth of the modern architectures. This leads to wasted computation, as the network overthinks on the simpler inputs. The overthinking problem could be prevented if standard DNNs could produce early predictions. However, prior work suggests that this is challenging in existing architectures, such as ResNet, as their internal layers are not trained for classification and optimizing them for accurate predictions hurts the end performance. In this paper, we explore the overthinking problem, and, as a remedy, we propose a generic modification to off-the-shelf DNNs---the Shallow-Deep Network (SDN). With this modification, a DNN can efficiently produce predictions from either shallow or deep layers, as appropriate for the given input. We employ feature reduction and a layer-wise objective function to train these progressively deeper internal classifiers while preserving the end-performance. We can apply the SDN modification either by training from scratch or by tuning a pre-trained model. Experiments on four architectures (VGG, ResNet, WideResNet, and MobileNet) and three image classifications tasks suggest that, for an average input, an SDN can produce a correct prediction before its middle layer. By avoiding unnecessary computation, the SDN can reduce the required number of operations for an input by 41% over the original network. Finally, we observe that disagreements among the early classifiers reliably indicate inputs where the network is likely to make a mistake. Building on this observation we propose an internal confusion metric and a method to diagnose misclassifications by visualizing these disagreements.
Restorative Effect of Semecarpus Anacardium on Altered Energy Metabolism in Type-2 Diabetes Mellitus–Induced Cardiac Dysfunction in Rats

Abstract Semecarpus anacardium is an important herbal drug that has been used against various ailments. To evaluate the cardioprotective effect of the drug against altered cardiac energy metabolism in type-2 diabetes rats, type-2 diabetes was induced in rats by feeding them with a high-fat diet for 2 weeks followed by intraperitoneal injection of streptozotocin (STZ) 35 mg/kg body weight twice 24 h apart and left for 12 weeks to develop cardiovascular complication. The effects of the nut milk extract on the glucose metabolizing enzymes and mitochondrial complex enzymes were studied using biochemical assays. The drug effectively ameliorated the alteration in cardiac energy metabolism in diabetic rats. The cardioprotective effect may be mediated through the ability of the drug to enhance glucose utilization and control the oxidative stress under diabetic conditions.
Analgesic effectiveness, pharmacokinetics, and safety of a paracetamol/ibuprofen fixed‐dose combination in children undergoing adenotonsillectomy: A randomized, single‐blind, parallel group trial

Pain following tonsillectomy is often poorly managed in the home setting. Multimodal analgesia with acetaminophen (paracetamol) and nonsteroidal anti‐inflammatory drugs offers superior analgesia over monotherapy but may be difficult for caregivers to manage. A fixed‐dose combination oral suspension product containing paracetamol and ibuprofen has been developed to facilitate pediatric dosing.
Contemporary global perspectives of medical students on research during undergraduate medical education: a systematic literature review

ABSTRACT Background: The need for increased expertise in evidence-based medicine and concerns about the decreasing numbers of physician-scientists have underscored the need for promoting and encouraging research in medical education. The critical shortage of physician-scientists has assumed a dimension demanding a coordinated global response. This systematic review examined the perceptions of medical students regarding research during undergraduate medical school from a global perspective. Methods: Articles for this review were searched using PubMed, SCOPUS and Cochrane. Studies published within the last 10 years of the start date of the study that met specified criteria were included. Identified articles were initially screened by title as well as keywords and their abstracts were further screened to determine relevance. Full-text of screened articles were read for validation prior to inclusion. Results: A total of 26 articles from the literature met the set criteria for final inclusion. Contents of the abstracts and corresponding full-text articles were analyzed for themes on the research perspectives of medical students. The themes derived comprised: research interest, physician-scientist decline and shortage, responses to physician-scientist shortage, curriculum issues, skills (motivation and self-efficacy), research needs, socioeconomic and cultural issues, and barriers. Conclusion: Despite the wide variations in medical education systems worldwide, the perspectives of medical students on research in undergraduate medical education shared many common themes. Globally, medical students underscored the necessity and importance of research in medical education as reflected by many students reporting positive attitudes and interest in research endeavors. Moreover, a worldwide consensus emerged regarding the decline in the numbers of physician-scientists and the necessity for a reversal of that trend. Various barriers to research engagement and participation were highlighted.
The application and teaching evaluation of Japanese films and TV series corpus in JFL classroom

Purpose The aim of this paper is to solve the problem of lack of real context in JFL (Japanese as Foreign Language) classroom with video corpus-based teaching. It also offers reference for the development of video corpus. Design/methodology/approach The authors designed an intelligent Japanese online video corpus, namely the JV Finder, which is a corpus of Japanese films and TV series. The authors applied the JV Finder to JFL teaching to solve the problem of lack of real context and designed several teaching experiments to validate its benefits. Findings The results of teaching experiments show that the video corpus-based teaching significantly improves the learning effect. The JV Finder can help students memorize vocabularies and understand the meaning of new vocabularies in a better way. Research limitations/implications There are still some differences in language context between real life and films, which cannot fully reflect the state of native speaker in real life. Meanwhile, the number of students participating in this experiment is relatively small, so the universality of the result need further study. Practical implications This study combined linguistics with software engineering to solve the problem of lack of real context. Video corpus-based teaching not only can be used in Japanese teaching field but also provide value for other foreign language teaching. Social implications The JV Finder has obtained Chinese national patent license (patent no. 20131118). The video corpus (the JV Finder) has a far-reaching impact on JFL teaching. Originality/value This paper provides an intelligent Japanese online video corpus. It is applied to JFL teaching to solve the problem of lack of real context. The findings show that the video corpus can significantly improve the effectiveness of Japanese learning.
A comprehensive approach of the determinants of use of care in dementia: the Recaredem (recourse to care in dementia) cross-sectional study

ABSTRACT Background: Given the rate of the undiagnosed cases of dementia and the consequences of inappropriate care, understanding the factors that explain the use of medical and health care in dementia is a critical concern. Our objective was to identify the psychosocial and medical determinants of use of care in dementia. Methods: The study sample consisted of 308 participants: the persons with dementia (n = 99) selected from three French population-based cohorts (i.e. PAQUID, 3C, AMI), their family caregivers (primary, n = 96, and secondary, n = 51), and their general practitioners (n = 62). Use of care in dementia was considered according to two indicators: (1) recourse to secondary care, (2) number of community and health services used. Results: Multiple logistic models including sociodemographics and psychosocial variables revealed that the determinants of nonuse of care are similar both for the recourse to secondary care and for the number of community and health services used: lack of education and the contribution of the people with dementia to the decisions regarding their own care and dementia care services in the community area. In addition, satisfaction of the primary caregiver with the services used by his/her relative is associated with non-recourse to secondary care. Conclusions: Taken together, these results highlight the predominant role of psychosocial factors in the use of care in dementia and the importance of addressing this issue through an integrative approach including psychological, social, medical, and family dimensions.
Soft tissue substitutes to increase gingival thickness: Histologic and volumetric analyses in dogs

OBJECTIVES To evaluate the histologic and volumetric changes of gingival tissues following grafting with collagen-based matrices at labial aspect of teeth in canines. MATERIALS AND METHODS Gingival augmentation was performed in the mandibular incisor area using two types of xenogeneic cross-linked collagen matrices (CCMs), bovine CCM for BCCM group and porcine CCM for PCCM group, whereas the contralateral sides remained untreated (B-control group and P-control group). Descriptive histology, histometric and volumetric analyses were performed after 12 weeks. For statistical comparison between each test group and respective control group, paired t test was used for histometric analysis, and repeated-measured analysis of variance was used for volumetric analysis (p < 0.05). RESULTS An increased number of rete pegs and an enhanced formation of new blood vessels were observed at both grafted sites compared to the corresponding control sites. There was statistically significant gain of horizontal thickness only in BCCM group (1.36 ± 0.27 mm vs. 1.26 ± 0.34 mm; p < 0.05) compared to the B-control groups. CONCLUSION BCCM was effective for gingival augmentation in terms of horizontal thickness at the labial aspect of teeth at 12 weeks post-surgery.
People infuse their passwords with autobiographical information

ABSTRACT Passwords might unlock more than our computer accounts. A New York Times Magazine described anecdotes of people who infused their passwords with autobiographical information [Urbina, I. (2014, November 20). The Secret Life of Passwords. New York Times. Retrieved from https://www.nytimes. com/2014/11/19/magazine/the-secret-life-of-passwords.html]. We suspected people infused their passwords with autobiographical information so they could privately remember that information. Across two studies we took a systematic approach to address the extent to which people infused passwords with autobiographical information and the functions that information served. We also examined the self-reported consequences of people infusing their passwords with autobiographical information. Across both studies, 41.6–71.1% of people infused their passwords with autobiographical memories; in Study 2, 9.3% of people infused their passwords with episodic future thoughts. People who infused their password with autobiographical information reported that information served identity, social, and directive functions, and they created their password to remember that information. These studies show that people do not simply use passwords to unlock their computer accounts. Some people might use passwords as mementos to cue autobiographical information.
The Synthesis of Ascorbic Acid in Rice Roots Plays an Important Role in the Salt Tolerance of Rice by Scavenging ROS

The root plays an important role in the responses of plants to stresses, but the detailed mechanisms of roots in stress responses are still obscure. The GDP-mannose pyrophosphate synthetase (GMPase) OsVTC1-3 is a key factor of ascorbic acid (AsA) synthesis in rice roots. The present study showed that the transcript of OsVTC1-3 was induced by salt stress in roots, but not in leaves. Inhibiting the expression of OsVTC1-3 by RNA interfering (RI) technology significantly impaired the tolerance of rice to salt stress. The roots of OsVTC1-3 RI plants rapidly produced more O2−, and later accumulated amounts of H2O2 under salt stress, indicating the impaired tolerance of OsVTC1-3 RI plants to salt stress due to the decreasing ability of scavenging reactive oxygen species (ROS). Moreover, exogenous AsA restored the salt tolerance of OsVTC1-3 RI plants, indicating that the AsA synthesis in rice roots is an important factor for the response of rice to salt stress. Further studies showed that the salt-induced AsA synthesis was limited in the roots of OsVTC1-3 RI plants. The above results showed that specifically regulating AsA synthesis to scavenge ROS in rice roots was one of important factors in enhancing the tolerance of rice to salt stress.
Acute Levodopa Challenge Test in Patients with de novo Parkinson's Disease: Data from the DeNoPa Cohort

The precise clinical diagnosis of Parkinson's disease (PD) can be difficult in the early stages. Diagnostic criteria include the response of key motor features to levodopa as a supportive prospective criterion. Data are sparse on the diagnostic value of the acute levodopa challenge test (LDCT) in patients with de novo PD. The objective of this study was to validate the LDCT as a tool in the early clinical diagnosis of PD.
Achieving Covert Wireless Communications Using a Full-Duplex Receiver

Covert communications hide the transmission of a message from a watchful adversary while ensuring a certain decoding performance at the receiver. In this paper, a wireless communication system under fading channels is considered where covertness is achieved by using a full-duplex receiver. More precisely, the receiver of covert information generates artificial noise with a varying power causing uncertainty at the adversary, Willie, regarding the statistics of the received signals. Given that Willie’s optimal detector is a threshold test on the received power, we derive a closed-form expression for the optimal detection performance of Willie averaged over the fading channel realizations. Furthermore, we provide guidelines for the optimal choice of artificial noise power range, and the optimal transmission probability of covert information to maximize the detection errors at Willie. Our analysis shows that the transmission of artificial noise, although causing self-interference, provides the opportunity of achieving covertness but its transmit power levels need to be managed carefully. We also demonstrate that the prior transmission probability of 0.5 is not always the best choice for achieving the maximum possible covertness when the covert transmission probability and artificial noise power can be jointly optimized.