Miracle-dz/UniFAR-FTUs huggingface dataset:
Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification

Aspect-based sentiment classification is a popular task aimed at identifying the corresponding emotion of a specific aspect. One sentence may contain various sentiments for different aspects. Many sophisticated methods such as attention mechanism and Convolutional Neural Networks (CNN) have been widely employed for handling this challenge. Recently, semantic dependency tree implemented by Graph Convolutional Networks (GCN) is introduced to describe the inner connection between aspects and the associated emotion words. But the improvement is limited due to the noise and instability of dependency trees. To this end, we propose a dependency graph enhanced dual-transformer network (named DGEDT) by jointly considering the flat representations learnt from Transformer and graph-based representations learnt from the corresponding dependency graph in an iterative interaction manner. Specifically, a dual-transformer structure is devised in DGEDT to support mutual reinforcement between the flat representation learning and graph-based representation learning. The idea is to allow the dependency graph to guide the representation learning of the transformer encoder and vice versa. The results on five datasets demonstrate that the proposed DGEDT outperforms all state-of-the-art alternatives with a large margin.
Association Between HIV-Related Tweets and HIV Incidence in the United States: Infodemiology Study

Background Adolescents and young adults in the age range of 13-24 years are at the highest risk of developing HIV infections. As social media platforms are extremely popular among youths, researchers can utilize these platforms to curb the HIV epidemic by investigating the associations between the discourses on HIV infections and the epidemiological data of HIV infections. Objective The goal of this study was to examine how Twitter activity among young men is related to the incidence of HIV infection in the population. Methods We used integrated human-computer techniques to characterize the HIV-related tweets by male adolescents and young male adults (age range: 13-24 years). We identified tweets related to HIV risk and prevention by using natural language processing (NLP). Our NLP algorithm identified 89.1% (2243/2517) relevant tweets, which were manually coded by expert coders. We coded 1577 HIV-prevention tweets and 17.5% (940/5372) of general sex-related tweets (including emojis, gifs, and images), and we achieved reliability with intraclass correlation at 0.80 or higher on key constructs. Bivariate and multivariate analyses were performed to identify the spatial patterns in posting HIV-related tweets as well as the relationships between the tweets and local HIV infection rates. Results We analyzed 2517 tweets that were identified as relevant to HIV risk and prevention tags; these tweets were geolocated in 109 counties throughout the United States. After adjusting for region, HIV prevalence, and social disadvantage index, our findings indicated that every 100-tweet increase in HIV-specific tweets per capita from noninstitutional accounts was associated with a multiplicative effect of 0.97 (95% CI [0.94-1.00]; P=.04) on the incidence of HIV infections in the following year in a given county. Conclusions Twitter may serve as a proxy of public behavior related to HIV infections, and the association between the number of HIV-related tweets and HIV infection rates further supports the use of social media for HIV disease prevention.
Standard methods for toxicology research in Apis mellifera

Summary Modern agriculture often involves the use of pesticides to protect crops. These substances are harmful to target organisms (pests and pathogens). Nevertheless, they can also damage non-target animals, such as pollinators and entomophagous arthropods. It is obvious that the undesirable side effects of pesticides on the environment should be reduced to a minimum. Western honey bees (Apis mellifera) are very important organisms from an agricultural perspective and are vulnerable to pesticide-induced impacts. They contribute actively to the pollination of cultivated crops and wild vegetation, making food production possible. Of course, since Apis mellifera occupies the same ecological niche as many other species of pollinators, the loss of honey bees caused by environmental pollutants suggests that other insects may experience a similar outcome. Because pesticides can harm honey bees and other pollinators, it is important to register pesticides that are as selective as possible. In this manuscript, we describe a selection of methods used for studying pesticide toxicity/selectiveness towards Apis mellifera. These methods may be used in risk assessment schemes and in scientific research aimed to explain acute and chronic effects of any target compound on Apis mellifera.
Bacterial microflora associated with farmed freshwater prawn Macrobrachium rosenbergii (de Man) and the aquaculture environment

The initial counts of bacteria associated with farmed giant freshwater prawn (Macrobrachium rosenbergii de Man) as well as with the water and sediment from two farms located at Kottayam district in Kerala (India) were determined. A total of 367 randomly selected isolates were characterized and identified. Prawn samples yielded mean microbiological counts of 4.92 log CFU g−1 of shell with muscle and 7.78 log CFU g−1 of intestine at 30°C. Bacterial numbers in the intestine of prawn were much higher than those in the pond water. Motile and non-motile aerobic Gram-negative bacteria together with Enterobacteriaceae accounted for 60–70% of the mesophiles isolated from water and prawn. However, the microorganisms isolated in significant numbers from shell with muscle and intestine of prawn were not recovered from the growing waters. Among Gram-positive bacteria, Micrococcus, Bacillus, coryneforms, and Arthrobacter were found. Faecal coliforms and enterococci were found in significant numbers in M. rosenbergii. The rearing practices such as feeding and pond fertilization could have influenced the microflora in prawn. The commensal microflora of freshwater prawn included opportunistic pathogens such as Aeromonas spp. and Streptococcus spp. Storage of prawn at elevated temperatures can permit their survival and growth leading to quality loss. Care should be exercised during handling and processing to prevent contamination of edible meat.
A Joint Model for Document Segmentation and Segment Labeling

Text segmentation aims to uncover latent structure by dividing text from a document into coherent sections. Where previous work on text segmentation considers the tasks of document segmentation and segment labeling separately, we show that the tasks contain complementary information and are best addressed jointly. We introduce Segment Pooling LSTM (S-LSTM), which is capable of jointly segmenting a document and labeling segments. In support of joint training, we develop a method for teaching the model to recover from errors by aligning the predicted and ground truth segments. We show that S-LSTM reduces segmentation error by 30% on average, while also improving segment labeling.
Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word Segmentation

Fully supervised neural approaches have achieved significant progress in the task of Chinese word segmentation (CWS). Nevertheless, the performance of supervised models always drops gravely if the domain shifts due to the distribution gap across domains and the out of vocabulary (OOV) problem. In order to simultaneously alleviate the issues, this paper intuitively couples distant annotation and adversarial training for cross-domain CWS. 1) We rethink the essence of “Chinese words” and design an automatic distant annotation mechanism, which does not need any supervision or pre-defined dictionaries on the target domain. The method could effectively explore domain-specific words and distantly annotate the raw texts for the target domain. 2) We further develop a sentence-level adversarial training procedure to perform noise reduction and maximum utilization of the source domain information. Experiments on multiple real-world datasets across various domains show the superiority and robustness of our model, significantly outperforming previous state-of-the-arts cross-domain CWS methods.
Metastatic Nasopharyngeal Carcinoma: Outcome from Cancer Institute, Chennai

Abstract Background: Optimal management of metastatic nasopharyngeal carcinoma (NPC) at presentation is debatable. The aim of this study was to investigate the treatment outcome of patients with metastatic NPC treated with concurrent chemoradiation or with radiation alone and to analyze the factors that correlate with the outcome. Methods: This was a retrospective study of patients with metastatic NPC treated in Cancer Institute, Chennai, from 1996 to 2015 with either chemoradiation or only radiation. Factors including age, sex, stage, treatment type, and type of metastasis were correlated with the outcome. Statistical analysis was done using SPSS version 20, and survival was estimated by Kaplan–Meier’s curve. Results: A total of 515 patients with NPC were treated during this period, and among them, 74 patients (14%) had metastasis at the time of presentation. The median follow-up was 14 months; the median progression-free survival and overall survival (OS) were 11 months and 19 months, respectively. About 72% (n = 53) were treated with chemoradiation and the rest 28% (n = 21) were treated with radiation alone. The 3-year OS was better in patients who received chemoradiation (39%) as compared to those who received only radiation (23.8%). Patients with the bone-only site of metastasis had better survival. Among them patients with oligometastatic bone disease (1–3 sites) had a better 3-year OS (51%) as compared to multiple bone metastasis (>3) 15.8%. Conclusion: Chemoradiation can be an option to treat metastatic NPC. Patients with oligometastatic bone disease had better survival.
Nutritive value of raw materials for rabbits: Egran tables 2002.

Feedstuff tables are presentad including the composition and the nutritive value of 53 raw materials used in compound diets for intensively reared rabbits. Each raw material is characterised by 23 analytical data and its digestible protein and energy values. Because of the importance of the fibre fractions in the nutrition of the rabbit, special efforts have been done to characterise the carbohydrate complex. The digestibility data were selected after a compilation of original literatura data and a discussion between the authors. The methodology used, in the different in vivo assays, was evaluated accurately in order to judge the reliability of the data. Besides digestible and metabolisable energy values are also presentad because they lead to a better mutual comparison between raw materials for formulation purposes. Finally, attention has been drawn that the presentad nutritiva values fit well with the proposed nutrient composition and show coherence in each category of feedstuffs.
Application of Genetically Engineered Pigs in Biomedical Research

Progress in genetic engineering over the past few decades has made it possible to develop methods that have led to the production of transgenic animals. The development of transgenesis has created new directions in research and possibilities for its practical application. Generating transgenic animal species is not only aimed towards accelerating traditional breeding programs and improving animal health and the quality of animal products for consumption but can also be used in biomedicine. Animal studies are conducted to develop models used in gene function and regulation research and the genetic determinants of certain human diseases. Another direction of research, described in this review, focuses on the use of transgenic animals as a source of high-quality biopharmaceuticals, such as recombinant proteins. The further aspect discussed is the use of genetically modified animals as a source of cells, tissues, and organs for transplantation into human recipients, i.e., xenotransplantation. Numerous studies have shown that the pig (Sus scrofa domestica) is the most suitable species both as a research model for human diseases and as an optimal organ donor for xenotransplantation. Short pregnancy, short generation interval, and high litter size make the production of transgenic pigs less time-consuming in comparison with other livestock species This review describes genetically modified pigs used for biomedical research and the future challenges and perspectives for the use of the swine animal models.
Screening of Chloroquine, Hydroxychloroquine and its derivatives for their binding affinity to multiple SARS-CoV-2 protein drug targets

Abstract Recently Chloroquine and its derivative Hydroxychloroquine have garnered enormous interest amongst the clinicians and health authorities’ world over as a potential treatment to contain COVID-19 pandemic. The present research aims at investigating the therapeutic potential of Chloroquine and its potent derivative Hydroxychloroquine against SARS-CoV-2 viral proteins. At the same time screening was performed for some chemically synthesized derivatives of Chloroquine and compared their binding efficacy with chemically synthesized Chloroquine derivatives through in silico approaches. For the purpose of the study, some essential viral proteins and enzymes were selected that are implicated in SARS-CoV-2 replication and multiplication as putative drug targets. Chloroquine, Hydroxychloroquine, and some of their chemically synthesized derivatives, taken from earlier published studies were selected as drug molecules. We have conducted molecular docking and related studies between Chloroquine and its derivatives and SARS-CoV-2 viral proteins, and the findings show that both Chloroquine and Hydroxychloroquine can bind to specific structural and non-structural proteins implicated in the pathogenesis of SARS-CoV-2 infection with different efficiencies. Our current study also shows that some of the chemically synthesized Chloroquine derivatives can also potentially inhibit various SARS-CoV-2 viral proteins by binding to them and concomitantly effectively disrupting the active site of these proteins. These findings bring into light another possible mechanism of action of Chloroquine and Hydroxychloroquine and also pave the way for further drug repurposing and remodeling. Communicated by Ramaswamy H. Sarma
Multimodal Imaging in the Management of Choroidal Neovascularization Secondary to Central Serous Chorioretinopathy

The diagnosis and treatment of choroidal neovascularization (CNV) in eyes with chronic central serous chorioretinopathy (CSCR) can be challenging. The purpose of this study was to classify eyes with suspected CNV using multimodal imaging. The effect of intravitreal anti-vascular endothelial growth factor (VEGF) was assessed and compared to controls. This retrospective study included chronic CSCR patients with suspected secondary CNV who received intravitreal bevacizumab. Eyes were divided into “definite CNV” and “no CNV” based on optical coherence tomography angiography (OCTA). Eyes that did not undergo OCTA imaging were considered as “presumed CNV”. One-year outcome in visual acuity (VA) and central foveal thickness (CFT) were investigated and compared to non-treated control patients to assess the response to anti-VEGF. Logistic regression analysis was used to explore predictive biomarkers of CNV detection and improvement after anti-VEGF. Ninety-two eyes with chronic CSCR from 88 participants were included in this study. Sixty-one eyes received bevacizumab and 31 eyes were non-treated control subjects. The presence of subretinal hyperreflective material (SHRM) and shallow irregular retinal pigment epithelium (RPE) elevation (SIRE) with sub-RPE hyperreflectivity on OCT was associated with a significantly increased risk of detecting CNV on OCTA. Intravitreal anti-VEGF caused significant functional and anatomical improvement in patients with neovascular CSCR as compared to non-treated eyes. In contrast, VA and CFT changes were not significantly different between treated and non-treated CSCR with no evidence of CNV on OCTA. No clinical or anatomical biomarkers were found to be associated with response to treatment. In conclusion, OCTA should be used to confirm the presence CNV in suspected chronic CSCR patients. Intravitreal anti-VEGF treatment resulted in a significantly better one-year outcome in patients with definitive OCTA evidence of CNV.
Paraphrase Generation by Learning How to Edit from Samples

Neural sequence to sequence text generation has been proved to be a viable approach to paraphrase generation. Despite promising results, paraphrases generated by these models mostly suffer from lack of quality and diversity. To address these problems, we propose a novel retrieval-based method for paraphrase generation. Our model first retrieves a paraphrase pair similar to the input sentence from a pre-defined index. With its novel editor module, the model then paraphrases the input sequence by editing it using the extracted relations between the retrieved pair of sentences. In order to have fine-grained control over the editing process, our model uses the newly introduced concept of Micro Edit Vectors. It both extracts and exploits these vectors using the attention mechanism in the Transformer architecture. Experimental results show the superiority of our paraphrase generation method in terms of both automatic metrics, and human evaluation of relevance, grammaticality, and diversity of generated paraphrases.
An Energy-Efficient and Adaptive Channel Coding Approach for Narrowband Internet of Things (NB-IoT) Systems

Most of the current research work on the Narrowband Internet of Things (NB-IoT) is focused on enhancing its network coverage. Many of the existing NB-IoT channel coding techniques are based on repeating transmission data and control signals as a way of enhancing the network’s reliability and therefore, enabling long-distance transmissions. Although most of these efforts are made at the expense of reducing the energy consumption of the NB-IoT network, they do not always consider the channel conditions. Therefore, this work proposes a novel NB-IoT Energy-Efficient Adaptive Channel Coding (EEACC) scheme. The EEACC approach is a two-dimensional (2D) approach which not only selects an appropriate channel coding scheme based on the estimated channel conditions (dynamically classified as bad, medium or good from initial based on a periodically assessed BLER performance outcome) but also minimizes the transmission repetition number under a pre-assessed probability of successful transmission (based on the ratio of previous successful transmissions over the total number of transmissions). This results in creating a single mixed gradient based on which a higher or lower Modulating Coding Scheme (MCS) is selected on each transmission. It is aimed at enhancing the overall energy efficiency of the network by dynamically selecting the appropriate Modulation Coding Scheme (MCS) number and efficiently minimizing the transmission repetition number. Link-level simulations are performed under different channel conditions (good, medium, or bad) considerations to assess the performance of the proposed up-link adaptation technique for NB-IoT. The obtained results demonstrate that the proposed technique outperforms the existing Narrowband Link Adaptation (NBLA) as well as the traditional repetition schemes in terms of the achieved energy efficiency as well as network reliability, latency, and scalability.
Bicarbonate-Mediated CO2 Formation on Both Sides of Photosystem II

The effect of bicarbonate (HCO3–) on photosystem II (PSII) activity was discovered in the 1950s, but only recently have its molecular mechanisms begun to be clarified. Two chemical mechanisms have been proposed. One is for the electron-donor side, in which mobile HCO3– enhances and possibly regulates water oxidation by acting as proton acceptor, after which it dissociates into CO2 and H2O. The other is for the electron-acceptor side, in which (i) reduction of the QA quinone leads to the release of HCO3– from its binding site on the non-heme iron and (ii) the Em potential of the QA/QA•– couple increases when HCO3– dissociates. This suggested a protective/regulatory role of HCO3– as it is known that increasing the Em of QA decreases the extent of back-reaction-associated photodamage. Here we demonstrate, using plant thylakoids, that time-resolved membrane-inlet mass spectrometry together with 13C isotope labeling of HCO3– allows donor- and acceptor-side formation of CO2 by PSII to be demonstrated and distinguished, which opens the door for future studies of the importance of both mechanisms under in vivo conditions.
Selectins—The Two Dr. Jekyll and Mr. Hyde Faces of Adhesion Molecules—A Review

Selectins belong to a group of adhesion molecules that fulfill an essential role in immune and inflammatory responses and tissue healing. Selectins are glycoproteins that decode the information carried by glycan structures, and non-covalent interactions of selectins with these glycan structures mediate biological processes. The sialylated and fucosylated tetrasaccharide sLex is an essential glycan recognized by selectins. Several glycosyltransferases are responsible for the biosynthesis of the sLex tetrasaccharide. Selectins are involved in a sequence of interactions of circulated leukocytes with endothelial cells in the blood called the adhesion cascade. Recently, it has become evident that cancer cells utilize a similar adhesion cascade to promote metastases. However, like Dr. Jekyll and Mr. Hyde’s two faces, selectins also contribute to tissue destruction during some infections and inflammatory diseases. The most prominent function of selectins is associated with the initial stage of the leukocyte adhesion cascade, in which selectin binding enables tethering and rolling. The first adhesive event occurs through specific non-covalent interactions between selectins and their ligands, with glycans functioning as an interface between leukocytes or cancer cells and the endothelium. Targeting these interactions remains a principal strategy aimed at developing new therapies for the treatment of immune and inflammatory disorders and cancer. In this review, we will survey the significant contributions to and the current status of the understanding of the structure of selectins and the role of selectins in various biological processes. The potential of selectins and their ligands as therapeutic targets in chronic and acute inflammatory diseases and cancer will also be discussed. We will emphasize the structural characteristic of selectins and the catalytic mechanisms of glycosyltransferases involved in the biosynthesis of glycan recognition determinants. Furthermore, recent achievements in the synthesis of selectin inhibitors will be reviewed with a focus on the various strategies used for the development of glycosyltransferase inhibitors, including substrate analog inhibitors and transition state analog inhibitors, which are based on knowledge of the catalytic mechanism.