Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Transcriptome Profiling of Two Tomato Genotypes in Response to Potassium-Deficiency Stress

Tomato is a crop that requires a sufficient supply of potassium (K) for optimal productivity and quality. K+-deficiency stress decreases tomato yield and quality. To further delve into the mechanism of the response to K+-deficiency and to screen out low-K+ tolerant genes in tomatoes, BGISEQ-500-based RNA sequencing was performed using two tomato genotypes (low-K+ tolerant JZ34 and low-K+ sensitive JZ18). We identified 1936 differentially expressed genes (DEGs) in JZ18 and JZ34 at 12 and 24 h after K+-deficiency treatment. According to the Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses, the DEGs that changed significantly primarily included transcription factors, transporters, kinases, oxidative stress proteins, and hormone signaling-and glycometabolism-related genes. The experimental results confirmed the induced expression of the responsive genes in the low-K+ signaling pathway. The largest group of DEGs comprised up to 110 oxidative stress-related genes. In total, 19 ethylene response factors (ERFs) demonstrated differential expression between JZ18 and JZ34 in response to K+-deficiency. Furthermore, we confirmed 20 DEGs closely related to K+-deficiency stress by quantitative RT-PCR (qRT-PCR), some of which affected the root configuration, these DEGs could be further studied for use as molecular targets to explore novel approaches, and to acquire more effective K acquisition efficiencies for tomatoes. A hypothesis involving possible cross-talk between phytohormone signaling cues and reactive oxygen species (ROS) leading to root growth in JZ34 is proposed. The results provide a comprehensive foundation for the molecular mechanisms involved in the response of tomatoes to low K+ stress.
Recent Advances of Useful Cell Sources in the Periodontal Regeneration.

BACKGROUND Periodontitis is an inflammatory disease that can result in destruction of the tooth attachment apparatus. Therefore, periodontal tissue regeneration is currently an important focus of research in the field. Approaches using stem cells and reprogrammed cells, such as induced pluripotent stem cells (iPSCs) or trans-differentiated cells, represent the cutting edge in periodontal regeneration, and have led to many trials for their clinical application. Objectives and Results: In this review, we consider all available stem cell sources, methods to obtain the cells, their capability to differentiate into the desired cells, and the extent of their utilization in periodontal regeneration. In addition, we introduce the new concepts of using iPSCs and transdifferentiated cells for periodontal regeneration. Finally, we discuss the promise of tissue engineering for improving cell therapy outcomes for periodontal regeneration. CONCLUSIONS Despite their limitations, iPSCs and trans-differentiated cells may be promising cell sources for periodontal tissue regeneration. Further collaborative investigation is required for the effective and safe application of these cells in combination with tissue engineering elements, like scaffolds and biosignals.
Word Sense Disambiguation Based on Word Similarity Calculation Using Word Vector Representation from a Knowledge-based Graph

Word sense disambiguation (WSD) is the task to determine the word sense according to its context. Many existing WSD studies have been using an external knowledge-based unsupervised approach because it has fewer word set constraints than supervised approaches requiring training data. In this paper, we propose a new WSD method to generate the context of an ambiguous word by using similarities between an ambiguous word and words in the input document. In addition, to leverage our WSD method, we further propose a new word similarity calculation method based on the semantic network structure of BabelNet. We evaluate the proposed methods on the SemEval-13 and SemEval-15 for English WSD dataset. Experimental results demonstrate that the proposed WSD method significantly improves the baseline WSD method. Furthermore, our WSD system outperforms the state-of-the-art WSD systems in the Semeval-13 dataset. Finally, it has higher performance than the state-of-the-art unsupervised knowledge-based WSD system in the average performance of both datasets.
JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena

We here introduce a substantially extended version of JeSemE, an interactive website for visually exploring computationally derived time-variant information on word meanings and lexical emotions assembled from five large diachronic text corpora. JeSemE is designed for scholars in the (digital) humanities as an alternative to consulting manually compiled, printed dictionaries for such information (if available at all). This tool uniquely combines state-of-the-art distributional semantics with a nuanced model of human emotions, two information streams we deem beneficial for a data-driven interpretation of texts in the humanities.
Optogenetic manipulation of medullary neurons in the locust optic lobe

Locust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts (Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered firing of a postsynaptic, looming-sensitive neuron, the Lobula Giant Movement Detector (LGMD). These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects. New and Noteworthy Using Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and of an identified postsynaptic target neuron, the LGMD neuron. This technique allows to manipulate the neuronal activity in locust neural circuits using optogenetics.
Effect of proximity on recombination innovation in R&D collaboration: an empirical analysis

ABSTRACT Recombination innovation is a process of creatively combining different knowledge domains in an invention. Recombination innovation in R&D collaboration – joint recombination process, which is integration of the organisation’s internal knowledge with the partner’s new knowledge, serves as the stepping stone of the knowledge search in the technological space. This paper tries to illuminate how different dimensions of proximity of the collaborating partners affect the probability of the collaborative innovation to be recombination innovation. Our result shows that technological proximity has a negative effect on joint recombination innovation. Geographical proximity has an inverted U-shaped effect on joint recombination innovation. The positive effect of organisational proximity on joint recombination innovation is not supported.
Bridge Video and Text with Cascade Syntactic Structure

We present a video captioning approach that encodes features by progressively completing syntactic structure (LSTM-CSS). To construct basic syntactic structure (i.e., subject, predicate, and object), we use a Conditional Random Field to label semantic representations (i.e., motions, objects). We argue that in order to improve the comprehensiveness of the description, the local features within object regions can be used to generate complementary syntactic elements (e.g., attribute, adverbial). Inspired by redundancy of human receptors, we utilize a Region Proposal Network to focus on the object regions. To model the final temporal dynamics, Recurrent Neural Network with Path Embeddings is adopted. We demonstrate the effectiveness of LSTM-CSS on generating natural sentences: 42.3% and 28.5% in terms of BLEU@4 and METEOR. Superior performance when compared to state-of-the-art methods are reported on a large video description dataset (i.e., MSR-VTT-2016).
Knockdown of Sestrin2 Increases Lipopolysaccharide-Induced Oxidative Stress, Apoptosis, and Fibrotic Reactions in H9c2 Cells and Heart Tissues of Mice via an AMPK-Dependent Mechanism

Sestrin2 (sesn2) is an endogenous antioxidant protein that has recently gained attention for its potential to treat various inflammatory diseases. However, the relationship of sesn2 with cardiomyopathy is still unclear. In H9c2 cells, sesn2 knockdown reduced the level of 5′ adenosine monophosphate-activated protein kinase (AMPK) phosphorylation, downregulated antioxidant genes including catalase and superoxide dismutase (SOD2), and increased reactive oxygen species (ROS) production upon lipopolysaccharide (LPS) treatment. LPS-mediated cell death and the expression of matrix metalloproteinase (MMP) 2 and MMP9 were significantly increased by sesn2 knockdown. However, these increases were prevented by treatment with 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR), an AMPK activator. Consistent with the in vitro results, AMPK phosphorylation was decreased in heart tissue from sesn2 knockdown mice compared to heart tissue from control C57BL/6 mice, which was associated with decreased expression of antioxidant genes and increased LPS-mediated cell death signaling. Furthermore, the decrease in AMPK phosphorylation caused by sesn2 knockdown increased LPS-mediated expression of cardiac fibrotic factors, including collagen type I and type III, in addition to MMP2 and MMP9, in heart tissue from C57BL/6 mice. These results suggest that sesn2 is a novel potential therapeutic target for cardiomyopathy under inflammatory conditions.
The Role of Direct Oral Anticoagulants in Treatment of Cancer-Associated Thrombosis

Venous thromboembolism (VTE) complicates the clinical course of approximately 5–10% of all cancer patients. Anticoagulation of the cancer patient often presents unique challenges as these patients have both a higher risk of recurrent VTE and a higher risk of bleeding than patients without cancer. Although low molecular weight heparins (LMWH) are the standard of care for the management of cancer-associated VTE, their use requires once or twice daily subcutaneous injections, which can be a significant burden for many cancer patients who often require a long duration of anticoagulation. The direct oral anticoagulants (DOACs) are attractive options for patients with malignancy. DOACs offer immediate onset of action and short half-lives, properties similar to LMWH, but the oral route of administration is a significant advantage. Given the higher risks of recurrent VTE and bleeding, there has been concern about the efficacy and safety of DOACs in this patient population. Data are now emerging for the use of DOACs in the cancer patient population from dedicated clinical trials. While recently published data suggest that DOACs hold promise for the treatment of cancer associated VTE, additional studies are needed to establish DOACs as the standard-of-care treatment. Many such studies are currently underway. The available data for the use of DOACs in the treatment of cancer-associated VTE will be reviewed, focusing on efficacy, safety, and other considerations relevant to the cancer patient.
ESMO Consensus Conference on testicular germ cell cancer: diagnosis, treatment and follow-up

The European Society for Medical Oncology (ESMO) consensus conference on testicular cancer was held on 3-5 November 2016 in Paris, France. The conference included a multidisciplinary panel of 36 leading experts in the diagnosis and treatment of testicular cancer (34 panel members attended the conference; an additional two panel members [CB and K-PD] participated in all preparatory work and subsequent manuscript development). The aim of the conference was to develop detailed recommendations on topics relating to testicular cancer that are not covered in detail in the current ESMO Clinical Practice Guidelines (CPGs) and where the available level of evidence is insufficient. The main topics identified for discussion related to: (1) diagnostic work-up and patient assessment; (2) stage I disease; (3) stage II-III disease; (4) post-chemotherapy surgery, salvage chemotherapy, salvage and desperation surgery and special topics; and (5) survivorship and follow-up schemes. The experts addressed questions relating to one of the five topics within five working groups. Relevant scientific literature was reviewed in advance. Recommendations were developed by the working groups and then presented to the entire panel. A consensus vote was obtained following whole-panel discussions, and the consensus recommendations were then further developed in post-meeting discussions in written form. This manuscript presents the results of the expert panel discussions, including the consensus recommendations and a summary of evidence supporting each recommendation. All participants approved the final manuscript.
Improving Neural Machine Translation by Incorporating Hierarchical Subword Features

This paper focuses on subword-based Neural Machine Translation (NMT). We hypothesize that in the NMT model, the appropriate subword units for the following three modules (layers) can differ: (1) the encoder embedding layer, (2) the decoder embedding layer, and (3) the decoder output layer. We find the subword based on Sennrich et al. (2016) has a feature that a large vocabulary is a superset of a small vocabulary and modify the NMT model enables the incorporation of several different subword units in a single embedding layer. We refer these small subword features as hierarchical subword features. To empirically investigate our assumption, we compare the performance of several different subword units and hierarchical subword features for both the encoder and decoder embedding layers. We confirmed that incorporating hierarchical subword features in the encoder consistently improves BLEU scores on the IWSLT evaluation datasets.
Voluntary Disclosure of Private Information and Unraveling in the Market for Lemons: An Experiment

We experimentally analyze a lemons market with a labor-market framing. Sellers are referred to as “workers” and have the possibility to provide “employers” with costly but credible information about their “productivity”. Economic theory suggests that in this setup, unraveling takes place and a number of different types are correctly identified in equilibrium. While we do observe a substantial degree of information disclosure, we also find that unraveling is typically not as complete as predicted by economic theory. The behavior of both workers and employers impedes unraveling in that there is too little disclosure. Workers are generally reluctant to disclose their private information, and employers enforce this behavior by bidding less competitively if workers reveal compared to the case where they conceal information.
Influence of Screen Size and Field of View on Perceived Brightness

We present a study into the perception of display brightness as related to the physical size and distance of the screen from the observer. Brightness perception is a complex topic, which is influenced by a number of lower- and higher-order factors—with empirical evidence from the cinema industry suggesting that display size may play a significant role. To test this hypothesis, we conducted a series of user studies exploring brightness perception for a range of displays and distances from the observer that span representative use scenarios. Our results suggest that retinal size is not sufficient to explain the range of discovered brightness variations, but is sufficient in combination with physical distance from the observer. The resulting model can be used as a step toward perceptually correcting image brightness perception based on target display parameters. This can be leveraged for energy management and the preservation of artistic intent. A pilot study suggests that adaptation luminance is an additional factor for the magnitude of the effect.
Predictors of Outcome in Selective Laser Trabeculoplasty: A Long-term Observation Study in Primary Angle-closure Glaucoma After Laser Peripheral Iridotomy Compared With Primary Open-angle Glaucoma

Purpose: To evaluate the efficacy of selective laser trabeculoplasty (SLT) for patients with primary angle-closure glaucoma (PACG) following a YAG laser peripheral iridotomy (PI) in comparison with primary open-angle glaucoma (POAG) and to assess the predictors of outcome of SLT. Patients and Methods: In retrospective study 68 patients with PACG after PI (68 eyes) and 74 POAG patients (74 eyes) were observed for 6 years. The effectiveness of SLT (20% reduction of intraocular pressure) was assessed using Kaplan-Meier survival analysis. The parameters for distinguishing the eyes with success and failure of SLT were detected by means of area under receiver operating characteristic curve (AUC). The predictive factors affecting SLT outcome were determined using Cox-regression analysis. Results: The success ratio was 87% in both groups in 1 year and dropped to 4% in PACG and to 6% in POAG in 6 years. Corneal hysteresis [odds ratio (ОR)=0.367, Р=0.005 for PACG, ОR=0.446, Р=0.008 for POAG] and age (OR=1.182, P=0.012 for PACG, OR=1.164, P=0.002 for POAG) were detected as the predictors of SLT outcome. In PACG pre-SLT anterior chamber depth was additional predictor (ОR=0.242, Р=0.001). The number of pre-SLT pressure-lowing medications was higher in the eyes with SLT failure (AUC, 0.794; P=0.0005 in PACG and AUC, 0.760; P=0.014 in POAG). Conclusions: One-year efficacy of SLT in POAG and PACG after PI was high, but it was reduced in long-term period. Corneal hysteresis, age, and number of pre-SLT hypotensive eye drops were significant prognostic factors for treatment success in both glaucoma forms. In PACG pre-SLT anterior chamber depth affected the SLT outcome.
Reproducing and Regularizing the SCRN Model

We reproduce the Structurally Constrained Recurrent Network (SCRN) model, and then regularize it using the existing widespread techniques, such as naive dropout, variational dropout, and weight tying. We show that when regularized and optimized appropriately the SCRN model can achieve performance comparable with the ubiquitous LSTM model in language modeling task on English data, while outperforming it on non-English data.
Adversarial Multi-lingual Neural Relation Extraction

Multi-lingual relation extraction aims to find unknown relational facts from text in various languages. Existing models cannot well capture the consistency and diversity of relation patterns in different languages. To address these issues, we propose an adversarial multi-lingual neural relation extraction (AMNRE) model, which builds both consistent and individual representations for each sentence to consider the consistency and diversity among languages. Further, we adopt an adversarial training strategy to ensure those consistent sentence representations could effectively extract the language-consistent relation patterns. The experimental results on real-world datasets demonstrate that our AMNRE model significantly outperforms the state-of-the-art models. The source code of this paper can be obtained from https://github.com/thunlp/AMNRE.
Prediction Governors for Input-Affine Nonlinear Systems and Application to Automatic Driving Control

In recent years, automatic driving control has attracted attention. To achieve a satisfactory driving control performance, the prediction accuracy of the traveling route is important. If a highly accurate prediction method can be used, an accurate traveling route can be obtained. Despite the considerable efforts that have been invested in improving prediction methods, prediction errors do occur in general. Thus, a method to minimize the influence of prediction errors on automatic driving control systems is required. This need motivated us to focus on the design of a mechanism for shaping prediction signals, which is called a prediction governor. In this study, we first extended our previous study to the input-affine nonlinear system case. Then, we analytically derived a solution to an optimal design problem of prediction governors. Finally, we applied the solution to an automatic driving control system, and demonstrated its usefulness through a numerical example and an experiment using a radio controlled car.
Obstructive Sleep Apnea Increases Sudden Cardiac Death in Incident Hemodialysis Patients

Background: Mortality in end-stage renal disease (ESRD) occurs predominantly from cardiovascular disease (CVD) and sudden cardiac death (SCD). Obstructive sleep apnea (OSA) is characterized by periodic airflow limitation associated with sleep arousal and oxygen desaturation and is prevalent in patients with ESRD. Whether OSA increases the risk for SCD, cardiovascular and all-cause mortality among hemodialysis patients remains unknown. Methods: In a prospective cohort of 558 incident hemodialysis patients, we examined the association of OSA with all-cause mortality, cardiovascular mortality, and SCD using Cox proportional hazards models controlling for traditional CVD risk factors. Results: Sixty-six incident hemodialysis patients (12%) had OSA. Mean age (56 years) and percentage of males (56%) were identical in OSA and no-OSA groups. Fewer African Americans had OSA than non-African Americans (9 vs. 18%, respectively). Participants with OSA had higher body-mass index, Charlson comorbidity score, and left ventricular mass index and greater prevalence of diabetes and coronary artery disease. During 1,080 person-years of follow-up, 104 deaths occurred, 29% of which were cardiovascular. OSA was associated with a higher risk of all-cause mortality (HR 1.90 [95% CI 1.04–3.46]) and cardiovascular mortality (HR 3.62 [95% CI 1.36–9.66]) after adjusting for demographics and body-mass index. OSA was associated with a higher risk of SCD after adjusting for demographics (HR 3.28 [95% CI 1.12–9.57]) and multiple cardiovascular risk factors. Conclusions: Incident hemodialysis patients with OSA are at increased risk of all-cause and cardiovascular mortality and SCD. Future studies should assess the impact of screening for OSA and OSA-targeted interventions on mortality in ESRD.
Mitigating Sybils in Federated Learning Poisoning

Machine learning (ML) over distributed multi-party data is required for a variety of domains. Existing approaches, such as federated learning, collect the outputs computed by a group of devices at a central aggregator and run iterative algorithms to train a globally shared model. Unfortunately, such approaches are susceptible to a variety of attacks, including model poisoning, which is made substantially worse in the presence of sybils. In this paper we first evaluate the vulnerability of federated learning to sybil-based poisoning attacks. We then describe \emph{FoolsGold}, a novel defense to this problem that identifies poisoning sybils based on the diversity of client updates in the distributed learning process. Unlike prior work, our system does not bound the expected number of attackers, requires no auxiliary information outside of the learning process, and makes fewer assumptions about clients and their data. In our evaluation we show that FoolsGold exceeds the capabilities of existing state of the art approaches to countering sybil-based label-flipping and backdoor poisoning attacks. Our results hold for different distributions of client data, varying poisoning targets, and various sybil strategies. Code can be found at: this https URL