Miracle-dz/UniFAR-FTUs huggingface dataset:
Ensemble Sequence Level Training for Multimodal MT: OSU-Baidu WMT18 Multimodal Machine Translation System Report

This paper describes multimodal machine translation systems developed jointly by Oregon State University and Baidu Research for WMT 2018 Shared Task on multimodal translation. In this paper, we introduce a simple approach to incorporate image information by feeding image features to the decoder side. We also explore different sequence level training methods including scheduled sampling and reinforcement learning which lead to substantial improvements. Our systems ensemble several models using different architectures and training methods and achieve the best performance for three subtasks: En-De and En-Cs in task 1 and (En+De+Fr)-Cs task 1B.
Thermal pretreatment facilitates recovery from prolonged low‐frequency force depression in rat fast‐twitch muscle

The aim of this study was to examine whether thermal pretreatment can accelerate recovery from prolonged low‐frequency force depression. The hindlimbs of thermal treated (T‐treated) rats were immersed in water heated to 42.0°C for 20 min (thermal pretreatment). The thermal pretreatment was performed once a day for 5 days before fatiguing stimulation. Intact gastrocnemius muscles were electrically stimulated via the sciatic nerve until force was reduced to ~50% of the initial and dissected immediately [recovery 0 (REC0)] or 60 min [recovery 60 (REC60)] following the cessation of stimulation. Using skinned fiber prepared from the superficial region, the ratio of force at 1 Hz to that at 50 Hz (low‐to‐high force ratio), the ratio of depolarization (depol)‐induced force to maximum Ca2+‐activated force (depol/max Ca2+ force ratio), the steepness of force‐Ca2+ concentration curves, and myofibrillar Ca2+ sensitivity were measured. At REC0, the low‐to‐high force ratio and depol/max Ca2+ force ratio decreased in stimulated muscles from both non‐ and thermal‐treated rats. At REC60, these two parameters remained depressed in non‐treated rats, whereas they reverted to resting levels in T‐treated rats. Thermal pretreatment exerted no effect on myofibrillar Ca2+ sensitivity. The present results reveal that thermal pretreatment can facilitate recovery of submaximum force after vigorous contraction, which is mediated via a quick return of Ca2+ release from the sarcoplasmic reticulum to resting levels.
Prevalence of persons contacting general practice for psychological stress in Denmark

Abstract Objective: The prevalence of psychological stress has previously been estimated based on self-reported questionnaires. This study aimed to investigate the prevalence of persons who contact the general practitioner (GP) for psychological stress and to explore associations between psychological stress and characteristics relating to the patient, the GP, and area-specific socioeconomic factors. Design: Cross-sectional computer assisted journal audit. Setting: General practice in the Region of Southern Denmark. Subjects: Patients aged 18–65 years with a consultation during a six-month period that was classified with a stress-related diagnosis code. Main outcome measures: Six months prevalence of GP-assessed psychological stress and characteristics relating to the patient, the GP, and area-specific socioeconomic factors. Results: Fifty-six GPs (7% of the invited) identified 1066 patients considered to have psychological stress among 51,422 listed patients. Accordingly, a 2.1% six months prevalence of psychological stress was estimated; 69% of cases were women. High prevalence of psychological stress was associated with female sex, age 35–54 years, high education level and low population density in the municipality, but not with unemployment in the municipality or household income in the postal district. GP female sex and age <50 years, few GPs in the practice and few patients per GP were also associated with a higher prevalence of psychological stress. Conclusions: A total of 2% of the working-age population contacted the GP during a six-month period for psychological stress. The prevalence of psychological stress varies with age, sex and characteristics of both the regional area and the GP. Key points Psychological stress is a leading cause of days on sick leave, but its prevalence has been based on population surveys rather than on assessment by health care professionals. • This study found that during six months 2.1% of all working-age persons have at least one contact with the GP regarding psychological stress. • The six months prevalence of psychological stress was associated with patient age and sex, GP age and sex, practices’ number of GPs and patients per GP, and area education and urbanization level.
Genome-Wide Association Studies Reveal Genetic Variation and Candidate Genes of Drought Stress Related Traits in Cotton (Gossypium hirsutum L.)

Cotton is an important industrial crop worldwide and upland cotton (Gossypium hirsutum L.) is most widely cultivated in the world. Due to ever-increasing water deficit, drought stress brings a major threat to cotton production. Thus, it is important to reveal the genetic basis under drought stress and develop drought tolerant cotton cultivars. To address this issue, in present study, 319 upland cotton accessions were genotyped by 55,060 single nucleotide polymorphisms (SNPs) from high-density CottonSNP80K array and phenotyped nine drought tolerance related traits. The two datasets were used to identify quantitative trait nucleotides (QTNs) for the above nine traits using multi-locus random-SNP-effect mixed linear model method. As a result, a total of 20 QTNs distributed on 16 chromosomes were found to be significantly associated with six drought tolerance related traits. Of the 1,326 genes around the 20 QTNs, 205 were induced after drought stress treatment, and 46 were further mapped to Gene ontology (GO) term “response to stress. ” Taken genome-wide association study (GWAS) analysis, RNA-seq data and qRT-PCR verification, four genes, RD2 encoding a response to desiccation 2 protein, HAT22 encoding a homeobox-leucine zipper protein, PIP2 encoding a plasma membrane intrinsic protein 2, and PP2C encoding a protein phosphatase 2C, were proposed to be potentially important for drought tolerance in cotton. These results will deepen our understanding of the genetic basis of drought stress tolerance in cotton and provide candidate markers to accelerate the development of drought-tolerant cotton cultivars.
Isolation of bovine foamy virus in Japan

Bovine foamy virus (BFV) is endemic in many countries, but has not been reported in Japan. A syncytium-forming virus was isolated from peripheral blood leukocytes of clinically healthy cattle on a farm in Kanagawa prefecture during a periodic epidemiological survey of viral diseases. The isolate was propagated in primary fetal bovine muscle cells and subsequently passaged in Madin–Darby bovine kidney cells. Since the isolate appeared to be distinct from the viruses with syncytium-forming ability previously isolated in Japan, we attempted to identify it using genomic analyses and electron microscopy. A phylogenetic analysis revealed that the isolate belongs to the bovine foamy virus cluster and is highly similar to a BFV strain isolated in China. A sero-epidemiological survey was performed using agar gel immunodiffusion test with the isolated virus as the antigen, and five of the 57 cattle tested were found to be seropositive.
A Formula That Generates Hash Collisions

We present an explicit formula that produces hash collisions for the Merkle-Damg{\aa}rd construction. The formula works for arbitrary choice of message block and irrespective of the standardized constants used in hash functions, although some padding schemes may cause the formula to fail. This formula bears no obvious practical implications because at least one of any pair of colliding messages will have length double exponential in the security parameter. However, due to ambiguity in existing definitions of collision resistance, this formula arguably breaks the collision resistance of some hash functions.
Relevance-Aware Information Dissemination in Vehicular Networks

As a step towards fully autonomous driving, Advanced Driver Assistance Systems provide convenience-and safety-related functions to drivers. In addition to data gathered by local sensors, these systems rely on events generated by other vehicles that need to be disseminated to a potentially large audience. Today, this geocast-functionality relies either on subscriptions covering certain areas (e.g., cities) or on individual route-based subscriptions. While the former exhibits suboptimal precision in filtering, the latter introduces significant complexity and assume that routes are known in advance. We propose a prediction-based assessment of the relevance of events without requiring prior route knowledge. Relevance is modeled based on the street network and spatio-temporal characteristics of events. We evaluate our approach in a realistic city setting, relying on the SUMO vehicular mobility simulator. Our first results show that relevance-aware information dissemination reduces the communication overhead by 68%, while at the same time achieving near perfect recall compared to route-based subscrintions.
Design Trade-Offs for Medium- and High-Frequency Transformers for Isolated Power Converters in Distribution System Applications

Medium- and High-Frequency Transformers (MFTs/HFTs) are a fundamental component in many isolated power-converter topologies proposed for electric distribution applications (e.g., solid-state power substations). Previous work presented detailed transformer design methodologies and addressed core loss limitations of different core materials and operating frequencies. However, MFT/HFT designs become significantly challenging for high power levels that are typical of distribution systems (e.g., greater than 100 kVA). Furthermore, few references include specific requirements in the design methodology like desired leakage and/or magnetizing inductances (which are normally specified for high-power applications). A design methodology for MFTs/HFTs is presented in this paper that accounts for tradeoffs like having a given leakage inductance for maximum power transfer (e.g., in the case of dual-active bridges (DABs)) or a given magnetizing inductance (to either attain a certain power transfer or to limit the power semiconductor currents). The design methodology is verified via Finite-Element Analysis (FEA) using ANSYS™ and an experimental prototype.
Global PCA for In-Field Compression of Seismic Data Acquisition

This paper presents a new global approach by using the Principal Component Analysis (PCA) to compress seismic data. The proposed method is based on the idea that a global covariance matrix can be derived from local statistics of the data at each sensor. A numerical simulation is implemented to demonstrate the performance of the global PCA technique, which reaches a compression ratio 10 times higher than the traditional local PCA technique.
Accelerated Fog Removal from Real Images for Car Detection

Image dehazing improves the visual quality of images in computer vision applications, such as object detection and object tracking. An accelerated image enhancement technique is presented for car detection as part of an effort to count cars using existing street cameras for the purpose of traffic management. Two aspects of car detection are tackled: 1) An existing image fog removal technique is accelerated by replacing a time consuming image filter with a faster filter while maintaining negligible image degradation, 2) A quick and practical algorithm to detect a car in a fog-free image is proposed and applied to a database of about 100 car images. Acceleration is the main goal of this research, in addition to car detection accuracy. The improved fog removal technique is performed by estimating the transmission map using the Proposed Adaptive Filter (PAF) to recover the scene depth of the foggy image. After filtering, a simple, yet exact and effective, car detection algorithm is executed to confirm the presence or absence of a car in the processed image. The system is fairly robust and although all images were obtained from existing sources, the proposed algorithm is expected to perform equally well with any side-view image of a car in the presence of heavy fog and under real conditions.
Length Scale-Based Differential Evolution

Differential Evolution (DE) has shown a superior performance for solving global continuous optimization problems. The crucial idea of DE is modifying the population of the candidate solutions toward the weighted differences of randomly selected candidate solutions. In this paper, we propose the length scale-based DE which utilizes the obtained information of a landscape analysis metric, the length scale metric, to enhance its own performance. Landscape analysis methods attempt to gain the properties of optimization problems. For two sample points, length scale metric calculates their objective function changes with respect to the distance between them. By computing length scale values of all possible pairs of candidate solutions, DE can employ the pairs of candidate solutions with the greater length scale values to calculate the difference vector in its mutation operator. The length scale-based DE is evaluated on CEC-2014 benchmark functions. Two dimensions, 50 and 100, are considered for benchmark functions. Simulation results confirm that the proposed algorithm obtains a promising performance on the majority of the benchmark functions on both dimensions.
Enhanced Bacterial Growth and Gene Expression of D-Amino Acid Dehydrogenase With D-Glutamate as the Sole Carbon Source

In a search for life-supporting, not life-assisting, D-amino acid metabolism, an environmental strain that grows better with D-glutamate as the sole carbon source was isolated from an ordinary river. The strain, designated as A25, exhibited a faster growth rate and greater cell yield with D-glutamate than with L-glutamate. Conversely, the D/L ratio of total cellular glutamate was as low as 4/96, which suggests that D-glutamate is more likely catabolized than anabolized. Strain A25 was phylogenetically most closely related to the gamma-proteobacterial species Raoultella ornithinolytica, with a 16S rRNA gene sequence similarity of 100%. A standard strain, R. ornithinolytica JCM 6096T, also showed similarly enhanced growth with D-glutamate, which was proven for the first time. Gene expression of the enzymes involved in D-amino acid metabolism was assayed by reverse-transcription quantitative PCR (RT-qPCR) using specifically designed primers. The targets were the genes encoding D-amino acid dehydrogenase (DAD; EC 1.4.99.1), glutamate racemase (EC 5.1.1.3), D-glutamate oxidase (EC 1.4.3.7 or EC 1.4.3.15), and UDP-N-acetyl-α-D-muramoyl-L-alanyl-D-glutamate ligase (EC 6.3.2.9). As a result, the growth of strains A25 and R. ornithinolytica JCM 6096T on D-glutamate was conspicuously associated with the enhanced expression of the DAD gene (dadA) in the exponential phase compared with the other enzyme genes. Pseudomonas aeruginosa is also known to grow on D-glutamate as the sole carbon source but to a lesser degree than with L-glutamate. A standard strain of P. aeruginosa, JCM 5962T, was tested for gene expression of the relevant enzymes by RT-qPCR and also showed enhanced dadA expression, but in the stationary phase. Reduction of ferricyanide with D-glutamate was detected in cell extracts of the tested strains, implying probable involvement of DAD in the D-glutamate catabolizing activity. DAD-mediated catalysis may have advantages in the one-step production of α-keto acids and non-production of H2O2 over other enzymes such as racemase and D-amino acid oxidase. The physiological and biochemical importance of DAD in D-amino acid metabolism is discussed.
Robust DOA Estimation for MIMO Radar in Unknown Nonuniform Noise and Mutual Coupling

In this paper, the DOA estimation issue for MIMO radar in unknown nonuniform noise and mutual coupling is addressed by proposing a robust sparse bayesian learning algorithm. In the proposed method, the influence of mutual coupling is eliminated by exploiting the banded complex symmetric Toeplitz structure of the mutual coupling matrices. Then a robust bayesian learning algorithm is formulated for DOA estimation, in which the covariances of unknown nonuniform noise are updated by using the least square(LS) strategy. Compared with the existing sparse signal recover based algorithms, the proposed method works well and provides better angle estimation performance in unknown nonuniform noise and mutual coupling. Simulation results are used to verify the effectiveness of the proposed method.
Towards Accurate Indoor Localization Using Channel State Information

Indoor location-based mobile applications have been gaining momentum in reshaping the daily activities of Internet users. A large number of indoor localization techniques achieve the localization goal by analyzing the received signal strength indication (RSSI) of pervasive WiFi signals. Compared with RSSI, the channel state information (CSI) provides more comprehensive time and space information with more complex hardware and software cost. In this paper, we proposed two CSI-based indoor localization algorithms: 1) a localization algorithm based on the weighted linear discriminant analysis; 2) a localization algorithm based on two-dimensional principal component analysis. The experimental results show that the proposed algorithms outperform the basic Bayesian algorithm based on the principal component analysis on improving the localization accuracy and reducing the computational complexity.
Cubic Dynamic Uncertain Causality Graph: A New Methodology for Modeling and Reasoning About Complex Faults With Negative Feedbacks

Scientific modeling and analysis for fault spreading process is a promising way for guaranteeing the safe, reliable, and efficient operation of complex system. However, the representing and reasoning of uncertain, time-varying, and sophisticated dependences are difficult, especially for the complex issues of dynamic negative feedback loops in multivariate time series. Dynamic uncertain causality graph (DUCG) provides a dynamic inference method without causality propagation across time slices, the disadvantage of which lies in the interpretability and applicability. In order to overcome the shortcomings of DUCG and extend its capabilities of temporal causality representation and dynamic reasoning, this paper proposes a new methodology named Cubic DUCG. The fundamental idea is to continuously generate the cubic causality graph online according to the sequential observations by discarding the restrictive Markov and conditional independence assumptions. Based on the complete causal dependencies representing the real-time fault spreading behaviors, the efficient and rigorous inference algorithm is thus proposed. The method is validated on fault data of the secondary loop of two nuclear power plant simulators, concerning the effectiveness, and in particular, the capability of dealing with complex dynamics and negative feedback processes.
PANDA - Discovering Part Name in Noisy Text Data

Part identification plays a key role in vehicle prognostics and health management. Part identifiers are often expressed as nomenclature and buried in noisy free text data found in maintenance reports, supply chain management records, service and support communication logs, and manufacturing quality data. There is little consistency in how part names are actually described in noisy free text, with variations spawned by typos, ad hoc abbreviations, acronyms, and incomplete names. This makes search and analysis of parts involved in this data extremely challenging. In this paper, we will discuss our method and tool PANDA (PArt Name Discovery Analytics), based on a unique method that exploits statistical, linguistic and machine learning techniques in a unique way to discover part names in noisy free text. The algorithm is very scalable and efficient, and provides actionable results for analysis of vehicle health management.
Variational graph auto-encoder using triplets of nodes for preserving proximity

In this paper, we present a scalable approach for unsupervised learning on graph-structured data that is based on variational auto-encoder. Most previous unsupervised methods for graph representation only consider the reconstruction errors. To train our model, we add different nodes of triplets as input, where one triplet consists of a given reference node vr, a positive node vp which is a adjacent node of vr, and a negative node vn which is a long-distance node of vr. Then, we adopt triplet-based loss function that minimize the reconstruction errors and minimize the distance between vr and vp than the distance between vr and vn. The method captures the relationships between nodes and complex features of a graph by exploiting the variational auto-encoder while still preserves both structure and text information. Experimental results in three real-world citation data show that our approach outperforms the top competitors in link prediction.
Effect of human tubal fluid medium and hyperactivation inducers on stallion sperm capacitation and hyperactivation

Conventional in vitro fertilization has not yet been implemented in the equine species. One of the main reasons has been the inability to develop a culture medium and incubation conditions supporting high levels of stallion sperm capacitation and hyperactivation in vitro. Although different culture media have been used for this purpose, human tubal fluid (HTF) medium, widely used in the manipulation of human and mice gametes, has not been reported so far in stallion sperm culture. The first part of this study aimed to compare HTF and Whitten's media on different stallion sperm quality and capacitation variables. Additionally, the effect of procaine, aminopyridine and caffeine in both media was evaluated on sperm motility parameters at different incubation times. Integrity and destabilization of the plasma membrane were evaluated by merocyanine 540/SYTOX Green (MC540), mitochondrial membrane potential (∆Ψm) using tetramethylrhodamine methyl ester perchlorate (TMRM), acrosome membrane integrity by PNA/FITC and tyrosine phosphorylation by P-tyrosine mouse mAb conjugated to Alexa Fluor® by flow cytometry. Motility parameters were evaluated using the integrated semen analysis system (ISAS®). We found no differences between Whitten's and HTF media and incubation time in terms of sperm viability, uninduced acrosome membrane damage or mitochondrial membrane potential at 30- and 120-min incubation. Membrane fluidity (MC540) increased in both media at 30- and 120-min incubation compared to noncapacitating conditions. Similarly, tyrosine phosphorylation increased in both media in capacitating conditions at 2- and 4-hr incubation compared to noncapacitating conditions. Although procaine showed the best result in terms of sperm hyperactivated motility in both media, aminopyridine also showed parameters consistent with the hyperactivation including an increase in curvilinear velocity and decrease in straightness. In conclusion, HTF medium and aminopyridine equally support capacitation-related parameters in stallion sperm.