Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends in intentional abuse or misuse of benzodiazepines and opioid analgesics and the associated mortality reported to poison centers across the United States from 2000 to 2014

Abstract Context: Prior works demonstrates an increased risk of death when opioid analgesics and benzodiazepines are used concomitantly to gain a high. Using poison center data, we described trends in abuse or misuse of benzodiazepines and opioid analgesics. We quantified mortality risk associated with abuse or misuse of benzodiazepines, opioid analgesics and the combination of opioid analgesics and benzodiazepines. Methods: This was a retrospective chart review of data from the National Poison Data System which collects information from 55 poison centers located across the United States. We identified reported cases of “intentional abuse or misuse” of benzodiazepine and/or opioid analgesic exposures. Poisson regression was used to compare the number of cases from each year between 2001 and 2014 to the year 2000. Logistic regression was used to determine whether cases exposed to both benzodiazepines and opioids had greater odds of death relative to cases exposed to opioid analgesics alone. Results: From 2000 to 2014, there were 125,485 benzodiazepine exposures and 84,627 opioid exposures among “intentional abuse or misuse” cases. Of the benzodiazepine exposures, 17.3% (n = 21,660) also involved an opioid. In 2010, exposures involving both opioids and benzodiazepines were 4.26-fold (95% CI: 3.87–4.70; p < .001) higher than in 2000. The risk of death was 1.55 (95% CI: 1.01–2.37; p = .04) times greater among those who used both an opioid and a benzodiazepine compared to opioids alone. This association held after adjusting for gender and age. Conclusion: Intentional abuse or misuse of benzodiazepines and opioids in combination increased significantly from 2000 to 2014. Benzodiazepine abuse or misuse far exceeded cases of opioid abuse or misuse. Death was greater with co-abuse or misuse of benzodiazepines and opioids. Population-level campaigns to inform the public about the risk of death with co-abuse or misuse of benzodiazepines and opioids are urgently needed to address this overdose epidemic.
Subcellular distribution and chemical forms of cadmium in Morus alba L.

ABSTRACT Morus alba L. (mulberry) is a perennial woody tree and a species with great potential for Cd phyremediation owing to its large biomass and extensive root system. The mechanisms involved in Cd detoxification were investigated by analyzing the subcellular distribution and chemical forms of Cd in mulberry in the present study. These results indicated that 53.27–70.17% of Cd mulberry accumulated was stored in the root and only about 10% were in the leaves. Lots of the Cd was located in the cell wall of the mulberry root and in soluble fraction of the mulberry leaf. Moreover, in roots, the largest amount of Cd was in the form of undissolved Cd-phosphate. While in mulberry leaves and stems, most of the Cd was extracted by 2% Acetic acid and 0.6 M HCl, representing Cd-phosphate and Cd-oxalate. It could be concluded that the Cd combination with peptides and organo-ligands in vacuole of leaf or complexed with proteins or cellulose in the cell wall of root might be contributed to the tolerance of mulberry to Cd stress. The mulberry could be used to remediate the Cd polluted farmland soils.
CIKM AnalytiCup 2017 Lazada Product Title Quality Challenge An Ensemble of Deep and Shallow Learning to predict the Quality of Product Titles

We present an approach where two different models (Deep and Shallow) are trained separately on the data and a weighted average of the outputs is taken as the final result. For the Deep approach, we use different combinations of models like Convolution Neural Network, pretrained word2vec embeddings and LSTMs to get representations which are then used to train a Deep Neural Network. For Clarity prediction, we also use an Attentive Pooling approach for the pooling operation so as to be aware of the Title-Category pair. For the shallow approach, we use boosting technique LightGBM on features generated using title and categories. We find that an ensemble of these approaches does a better job than using them alone suggesting that the results of the deep and shallow approach are highly complementary
Compressive sensing and matrix completion in Wireless Sensor Networks

As the size of In Wireless Sensor Networks (WSNs) continues to grow, the amount of data, for processing and transmitting becomes enormous. This large number of data is one of the factors that is speeding up power dissipation. Once the wireless devices are spatially distributed across the physical monitored field, their batteries, designed to operate for a determined period of time, cannot be changed anymore. This challenging issue requires effective mechanisms to handle constraints such as energy consumption, delay and cost. The Compressive Sensing (CS) theory as well as the Matrix Completion (MC) theory are two recently developed techniques in signal processing, which in combination with the sparse and correlated nature of WSNs data, hold promising enhancement to the network lifetime. In this paper, we compare the performance of the MC and the CS. These techniques take advantage of the intra-sensor (temporal) and the inter-sensors (spatial) data structure correlation differently. The simulation analysis shows that the MC with a naive random sampling scheme outperforms two high complex CS based algorithms.
Spectral efficiency gains through the use of FBMC/OQAM for DOCSIS systems

The Data-Over-Cable Service Interface Specification (DOCSIS) provides internet access via Hybrid Fiber Coax (HFC) networks. With the latest version DOCSIS 3.1, the Physical Layer changed from a Single-Carrier Quadrature Amplitude Modulation (SC-QAM) to Orthogonal Frequency Division Multiplex (OFDM). Apart from the DOCSIS standard, OFDM is used in many digital transmission systems such as Long-Term Evolution (LTE) or the most modern Digital Video Broadcasting (DVB) standards. Recent activities in the development of the 5th generation for mobile networks 5G investigated other modulation schemes beyond OFDM. One candidate was Filter Bank Multicarrier (FBMC), often used in combination with Offset QAM (OQAm). FBMC promises fewer out-of-band emissions and no overhead due to the Cyclic Prefix (CP). This paper presents an FBMC/OQAM software implementation adapted to the current DOCSIS 3.1 downstream specification. The FBMC/OQAM system is compared to the DOCSIS 3.1 CP-OFDM based downstream physical layer in terms of robustness and spectral efficiency. Simulations show that the FBMC/OQAM system can improve the spectral efficiency by approximately 10 % while providing similar robustness for HFC network channels with a short channel impulse response and a Signal-to-Noise Ratio (SNR) of less than 55 dB.
A MRF-based Multi-agent System for Remote Sensing Image Segmentation

Remote sensing is a technology for remote real-time monitoring surface information, remote sensing images are valuable in civil and military applications. In this paper, aiming at the design of remote sensing image segmentation algorithm, we propose a remote sensing image segmentation method based on multi-agent and MRF. The proposed method extracts and fuses the intensity, texture, edges, and the spatial information in collaboration and parallization, and it provides theoretical and technical support for remote sensing image segmentation task.
Persistent Memory Transactions

This paper presents a comprehensive analysis of performance trade offs between implementation choices for transaction runtime systems on persistent memory. We compare three implementations of transaction runtimes: undo logging, redo logging, and copy-on-write. We also present a memory allocator that plugs into these runtimes. Our microbenchmark based evaluation focuses on understanding the interplay between various factors that contribute to performance differences between the three runtimes -- read/write access patterns of workloads, size of the persistence domain (portion of the memory hierarchy where the data is effectively persistent), cache locality, and transaction runtime bookkeeping overheads. No single runtime emerges as a clear winner. We confirm our analysis in more realistic settings of three "real world" applications we developed with our transactional API: (i) a key-value store we implemented from scratch, (ii) a SQLite port, and (iii) a persistified version of memcached, a popular key-value store. These findings are not only consistent with our microbenchmark analysis, but also provide additional interesting insights into other factors (e.g. effects of multithreading and synchronization) that affect application performance.
The impact of shift work on the psychological and physical health of nurses in a general hospital: a comparison between rotating night shifts and day shifts

Background Shift work is considered necessary to ensure continuity of care in hospitals and residential facilities. In particular, the night shift is one of the most frequent reasons for the disruption of circadian rhythms, causing significant alterations of sleep and biological functions that can affect physical and psychological well-being and negatively impact work performance. Objectives The aim of this study was to highlight if shift work with nights, as compared with day work only, is associated with risk factors predisposing nurses to poorer health conditions and lower job satisfaction. Methods This cross-sectional study was conducted from June 1, 2015 to July 31, 2015 in 17 wards of a general hospital and a residential facility of a northern Italian city. This study involved 213 nurses working in rotating night shifts and 65 in day shifts. The instrument used for data collection was the “Standard Shift Work Index,” validated in Italian. Data were statistically analyzed. Results The response rate was 86%. The nurses engaged in rotating night shifts were statistically significantly younger, more frequently single, and had Bachelors and Masters degrees in nursing. They reported the lowest mean score in the items of job satisfaction, quality and quantity of sleep, with more frequent chronic fatigue, psychological, and cardiovascular symptoms in comparison with the day shift workers, in a statistically significant way. Conclusion Our results suggest that nurses with rotating night schedule need special attention due to the higher risk for both job dissatisfaction and undesirable health effects.
A new Turbo equalizer with linear complexity

In this paper a new soft input - soft output (SISO) equalizer of linear complexity is developed. The algorithm can be used in the so-called Turbo equalization scheme as a low cost solution in place of the Maximum A-Posteriori (MAP) equalization algorithm which has a prohibitive complexity for most real world applications. The proposed equalizer consists of two parts, namely, a Soft Interference Canceller (SIC) and a pre-processing part which is a new Variable-Threshold Decision Feedback Equalizer (VTDFE). The role of the second part is to increase the amount of a-priori information supplied to the SIC. Simulation results have shown that the proposed turbo equalizer exhibits a superior performance as compared to the turbo equalization scheme based on the conventional SIC as well as other linear complexity SISO equalizers.
New calibration method of plenoptic camera using CCD camera model

This paper presents a convenient method to estimate the internal parameters of a plenoptic camera by applying a CCD camera calibration method and some formulas to be analytically derived. A microlens based plenoptic camera is effectively same as a virtual camera array placed in regular intervals. For calibration, we employ a homogeneous intrinsic matrix based on the plenoptic camera model. Using various check board patterns, as in a CCD camera calibration, the disparities of pixels, the center positions of the virtual cameras, the baseline between the virtual cameras, and the distance to a point in the scene are extracted in the sub-aperture image domains. We formulate four equations for calibration of the plenoptic camera and then performs a nonlinear optimization technique to find a solution to these equations. To evaluate the estimation performance, we generate an artificial plenoptic image whose internal parameters are definite. Then estimation results are compared with the true parameters. In addition, the reprojection error by the estimated parameters is demonstrated.
Spike context: A neuromorphic descriptor for pattern recognition

Although the neuromorphic vision community has developed useful event-based descriptors in the recent past, a robust general purpose descriptor that can handle scale and rotation variations has been elusive to achieve. This is partly because event cameras do not output frames at fixed intervals (like standard cameras) that are easy to work with, but an asynchronous sequence of spikes at microsecond to millisecond time resolutions. In this paper, we present Spike Context, a spatio-temporal neuromorphic descriptor that is inspired by the distribution of photo-receptors in the primate fovea. To demonstrate the effectiveness of the spike context descriptors, they are employed as semi-local features in the bag-of-features classification framework. In the first set of experiments on the N-MNIST dataset, we obtained very high results compared to existing works. In addition, we outperformed the state-of-the-art algorithms on the smaller MNIST-DVS dataset. Finally, we demonstrate the ability of the descriptor in handling scale variations by using the leave-one-scale-out protocol on the MNIST-DVS dataset.
Dynamic Analysis of Reinforced Concrete Rectangular Liquid Storage Structures Considering Liquid-structure Interaction

Because influence of liquids,the dynamic reponse of liquid storage structures are different with other kind of structures.In this paper,taking into account the action of rebar in concrete materials,the current finite element software ADINA is used to do finite element simulation for the reinforced concrete rectangular liquid storage structures.The influences of gravity wave of the liquids surface,the stiffness of wainscots and the shape of the structures on the dynamic response with liquid-structure interaction are discussed,and the dynamic responses are also discussed in the action of unidirectional,bidirectional and three-directional coupling seismic actions.The result provides the theoretical basis for reinforced concrete rectangular liquid storage structures.
Exploring Different Granularity in Mongolian-Chinese Machine Translation Based on CNN

Abstract—In this paper, a translation model based on Convolutional Neural Network (CNN) architecture is introduced into the Mongolian-Chinese translation task. Mongolian language has rich morphology structure, so we use byte-pair encoding (BPE) to segment the Mongolian word. In addition, the Mongolian Correction approach is adopted to reduce coding errors occurred in Mongolian corpus. The statistics data show that BPE and Mongolian Correction are alleviate the data sparsity that results from very low-resource Mongolian-Chinese parallel corpus. On Mongolian-Chinese translation task, we achieve the best result 35.37 BLEU that exceeds the baseline system by 1.4 BLEU. In the experiments, effect of different translation granularity on the translation result is investigated. The experiment results show that sub-word unit is more suitable than word unit for Mongolian-Chinese translation.
Diagnosis prognosis and prevention of breast cancer based on present scenario of human life

Statistics of standard health organizations shows that the breast cancer is subsequently a critical setback to the human that creates more death rates. Early diagnosis of any health problem may heal the crisis quickly. In this research study the breast cancer analysis performed with fifteen attributes that reflect the present scenario of human life. The K-means clustering algorithm and the decision tree mechanisms are used in this study and the analysis is focused on finding the precision, recall, accuracy and the F-measure. The RMSE, mSe and Kappa statistic values estimated through this study is less than one and proves that the attributes focused in this study must be carefully maintained in specified levels to prevent the breast cancer and to increase the human life time after breast cancer.
An Investigation on Social Representations: Inanimate Agent Can Mislead Dogs (Canis familiaris) in a Food Choice Task

The nature of mental representation of others plays a crucial role in social interactions. Dogs present an ideal model species for the investigation of such mental representations because they develop social ties with both conspecifics and heterospecifics. Former studies found that dogs’ preference for larger food quantity could be reversed by humans who indicate the smaller quantity. The question is whether this social bias is restricted to human partners. We suggest that after a short positive social experience, an unfamiliar moving inanimate agent (UMO) can also change dogs’ choice between two food quantities. We tested four groups of dogs with different partners: In the (1) Helper UMO and (2) Helper UMO Control groups the partner was an interactive remote control car that helped the dog to obtain an otherwise unreachable food. In the (3) Non-helper UMO and (4) Human partner groups dogs had restricted interaction with the remote control car and the unfamiliar human partners. In the Human partner, Helper UMO and Helper UMO Control groups the partners were able to revert dogs’ choice for the small amount by indicating the small one, but the Non-helper UMO was not. We suggest that dogs are able to generalize their wide range of experiences with humans to another type of agent as well, based on the recognition of similarities in simple behavioural patterns.
Event detection in Hungarian texts with dependency and constituency parsing and WordNet

Besides named entity recognition, the detection of events in natural language is an important area of Information Extraction. The detection and analysis of events in natural language texts play an important role in several NLP applications such as summarization and question answering. Most events are denoted by verbs in texts and the verbs usually denote events. But other parts of speech (e.g. noun, participle) can also denote events. In our work we deal with the detection of verbal, infinitival and nominal events. These are the most common events. In this study we introduce a machine learning-based approach with a rich feature set that can automatically detect events in Hungarian texts based on dependency and constituency parsing and WordNet. Additional methods were also applied beside the features, which improved the results and decreased running time. To our best knowledge, ours is the first result for detecting events in Hungarian natural language texts, with dependency and constituency parsing and WordNet. Having evaluated them on test databases, our algorithms achieve competitive results as compared to the current results.
IDENTIFICATION OF MICRORNAS IN 12 PLANT SPECIES OF FABACEAE

MicroRNAs (miRNAs) are tiny, non-coding and regulatory RNAs approximately 21 nucleotides in length. They are reported in various plants but still needs discovery in important plant species. The 12 plant species of Fabaceae were subjected this time to identify their miRNAs. The comparative genomics approaches with combination of various bioinformatics’ tools were applied to find the novel miRNAs. This research leads to the finding of 29 miRNAs belonging to 13 miRNA families. From the 29 miRNAs, nine belongs to Arachis duranensis, four to Lotus japonicas, three to each Pisum sativum and Arachis hypogaea, two to each Arachis ipaensis and Phaseolus vulgaris and one to each Cicer arietinum, Phaseolus acutifolius, Lupinus luteus, Glycyrrhiza uralensis, Robinia pseudoacacia and Lathyrus odoratus. These findings will be useful in the future to design and develop desirable traits in the 12 plant species of Fabaceae.
Design and Evaluation of a Novel 5 DoF Underactuated Thumb-Exoskeleton

This letter presents the design of a new exoskeleton for thumb. The main feature of this device is a high degree of underactuation. In fact, the five degrees of freedom (dof) of the thumb are actuated by just one linear actuator. Other features of the thumb-exos are its capability of exert only forces normal to the phalanx axis in the contact point, and its adaptability to different finger sizes. In this letter, the spatial kinematic model is described and the link lengths are determined by means of a genetic algorithm (GA) over four basic grasping poses and the open hand pose. Finally, the thumb-exos mechanism was implemented and integrated in a full hand exoskeleton device. Performance of the thumb exoskeleton in terms of adaptation to different objects and hand sizes, and in terms of grasping forces have been evaluated through experiments and measuring muscular activity, grasping pressure and forces at different locations of the mechanism.
Low-molecular weight Clq-binding immunoglobulin G in Patients with Systemic Lupus Erythematosus Consists of Aptoantibodies to the Collagen-like Region of Clq

The majority of Clq-binding IgG in sera of some patients with systemic lupus erythematosus (SLE) cosediments with monomeric IgG. This study was undertaken to provide definitive proof that the low-molecular weight Clq-binding IgG consists of autoantibodies to Clq. Monomeric Clq-binding IgG was isolated from five SLE plasmas by Clq affinity chromatography and gel 'filtration. All Clq-binding IgG preparations and their F(ab')2 fragments bound to both Clq and the collagen-like region of Clq by an ELISA. To rule out the possibility that small DNA-antiDNA immune complexes caused this binding activity, Fab' fragments of the Clq-binding IgG preparations were digested with DNase I to degrade any DNA. The Fab' fragments continued to bind to Clq and its collagen-like region after this treatment. Clq-binding' IgG was heterogenous on isoelectric focusing. Interaction of Clq-binding IgG with solid-ph0ase Clq was retained in 1 M NaCJ, whereas the binding of DNA or heat-aggregated IgG to solid-phase Clq was abro-gated or markedly diminished. The association constant of Clq-binding IgG with solid-phase Clq was 2.7 X 107 M-. We conclude that low-molecular weight Clq-binding IgG in the studied patients with SLE consists ofautoantibodies to the collagen-like region of Clq.
c-Myb and C/EBPβ regulate OPN and other senescence-associated secretory phenotype factors

Tumorigenesis results from the convergence of cell autonomous mutations and corresponding stromal changes that promote tumor cell growth. Senescent cells, which secrete a plethora of pro-tumorigenic factors termed the senescence-associated secretory phenotype (SASP), play an important role in tumor formation. Investigation into SASP regulation revealed that many but not all SASP factors are subject to NF-kB and p38MAPK regulation. However, many pro-tumorigenic SASP factors, including osteopontin (OPN), are not responsive to these canonical pathways leaving the regulation of these factors an open question. We report that the transcription factor c-Myb regulates OPN, IL-6, and IL-8 in addition to 57 other SASP factors. The regulation of OPN is direct as c-Myb binds to the OPN promoter in response to senescence. Further, OPN is also regulated by the known SASP regulator C/EBPβ. In response to senescence, the full-length activating C/EBPβ isoform LAP2 increases binding to the OPN, IL-6, and IL-8 promoters. The importance of both c-Myb and C/EBPβ is underscored by our finding that the depletion of either factor reduces the ability of senescent fibroblasts to promote the growth of preneoplastic epithelial cells.