Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce

Building multi-turn information-seeking conversation systems is an important and challenging research topic. Although several advanced neural text matching models have been proposed for this task, they are generally not efficient for industrial applications. Furthermore, they rely on a large amount of labeled data, which may not be available in real-world applications. To alleviate these problems, we study transfer learning for multi-turn information seeking conversations in this paper. We first propose an efficient and effective multi-turn conversation model based on convolutional neural networks. After that, we extend our model to adapt the knowledge learned from a resource-rich domain to enhance the performance. Finally, we deployed our model in an industrial chatbot called AliMe Assist and observed a significant improvement over the existing online model.
Quantitative Secretomics Reveals Extrinsic Signals Involved in Human Pluripotent Stem Cell Cardiomyogenesis

Human pluripotent stem cells can be differentiated in vitro into cardiomyocytes (CMs) but the molecular mechanisms behind this process are still not fully understood. In particular, the identification of morphogens remained elusive because the mass spectrometry–based identification of secreted proteins from cell culture supernatants is impeded by high levels of albumin present in common differentiation media. An albumin‐free cardiomyogenic differentiation medium is established in this study and applied for secretomics at seven different time points during in vitro differentiation. By this analysis 4832 proteins are identified with 1802 being significantly altered during differentiation and 431 of these are annotated as secreted. Numerous extrinsic components of Wnt, TGFβ, Activin A, Nodal, BMP, or FGF signaling pathways are quantitatively assessed during differentiation. Notably, the abundance of pathway agonists is generally lower compared to the respective antagonists but their curves of progression over timer were rather similar. It is hypothesized that TGFβ, Activin A, and Nodal signaling are turned down shortly upon the initiation of cardiac differentiation whereas BMP signaling is switched on. Wnt and FGF signaling peaks between d0 and d3 of differentiation, and interestingly, Activin A and TGFβ signaling seem to be reactivated at the cardiac progenitor stages and/or in early CMs.
Pathophysiological implications of actin-free Gc-globulin concentration changes in blood plasma and cerebrospinal fluid collected from patients with Alzheimer's disease and other neurological disorders.

BACKGROUND The extracellular actin scavenging system (EASS) is composed of plasma Gc-globulin and gelsolin, and is responsible for the elimination of toxic actin from the bloodstream. OBJECTIVES In this study, we assessed the actin-free Gc-globulin concentrations in blood plasma and cerebrospinal fluid (CSF) obtained from subjects with neurodegenerative and inflammatory diseases of the central nervous system (CNS) as well as in a control group. MATERIAL AND METHODS Using an enzyme-linked immunosorbent assay (ELISA), we measured the actinfree Gc-globulin concentrations in blood plasma and CSF obtained from subjects diagnosed with Alzheimer's disease (AD) (n = 20), amyotrophic lateral sclerosis (ALS) (n = 12), multiple sclerosis (MS) (n = 42), tick-borne encephalitis (TBE) (n = 12), and from a control group (n = 20). RESULTS The concentrations of free Gc-globulin in plasma collected from patients diagnosed with AD (509.6 ±87.6 mg/L) and ALS (455.5 ±99.8 mg/L) did not differ significantly between each other, but were significantly higher compared to the reference group (311.7 ±87.5 mg/L) (p < 0.001 and p < 0.006, respectively) as well as to MS (310.8 ±66.6 mg/L) (p < 0.001 and p < 0.001, respectively) and TBE (256.7 ±76 mg/L) (p < 0.001 and p < 0.003, respectively). In CSF collected from patients diagnosed with AD and ALS, the concentrations of free Gc-globulin were 2.6 ±1.1 mg/L and 2.7 ±1.9 mg/L, respectively. They did not differ significantly between each other and were significantly higher compared to the reference group (1.5 ±0.9 mg/L) (p < 0.005 and p < 0.041, respectively). Interestingly, in patients with AD, significantly higher values of Gcglobulin were detected compared to multiple sclerosis patients (1.7 ±0.9 mg/L) (p < 0.013). CONCLUSIONS Higher concentrations of free Gc-globulin in blood plasma and CSF collected from patients suffering from neurodegenerative diseases may indicate a potential role of this protein in their pathogenesis, and represent a potential tool for the diagnosis of CNS diseases.
Calculation of the transfer function of a power transformer with online measuring data

Mechanical deformation in transformer windings can be detected with the transfer function (TF). Normally the transformer will be disconnected from the public power supply to record the TF (offline measuring). Another possibility is to calculate the TF from the transients overvoltages generated from switching operations or lightning strikes. With adequate sensors these overvoltages can be recorded during operation of the transformer (online-measuring). On the basis of these online-datas diverse problems like separation of excitationand response signal, too low signal-to-noise ratio, etc. and their solution will be shown in this paper.
HGR-Net: A Two-stage Convolutional Neural Network for Hand Gesture Segmentation and Recognition

Robust recognition of hand gesture in real-world applications is still a challenging task due to the many aspects such as cluttered backgrounds and uncontrolled environment factors. In most existing methods hand segmentation is a primary step for hand gesture recognition, because it reduces redundant information from the image background, before passing them to the recognition stages. Therefore, in this paper we propose a two-stage deep convolutional neural network (CNN) architecture called HGR-Net, where the first stage performs accurate pixel-level semantic segmentation into hand region and the second stage identifies hand gesture style. The segmentation stage architecture is based on the combination of fully convolutional deep residual neural network and atrous spatial pyramid pooling. Although the segmentation sub-network is trained without using depth information, it is robust enough against challenging situations such as changes in the lightning and complex backgrounds. In the recognition stage a two-stream CNN is used to obtain the best classification score. We also apply an effective data augmentation technique for maximizing the generalization capability of HGR-Net. Extensive experiments on public hand gesture datasets show that our deep architecture achieves prominent performance in segmentation and recognition for static hand gestures.
Addressable metasurfaces for dynamic holography and optical information encryption

We present addressable plasmonic metasurfaces for optical information encryption and holography. Metasurfaces enable manipulation of light propagation at an unprecedented level, benefitting from a number of merits unavailable to conventional optical elements, such as ultracompactness, precise phase and polarization control at deep subwavelength scale, and multifunctionalities. Recent progress in this field has witnessed a plethora of functional metasurfaces, ranging from lenses and vortex beam generation to holography. However, research endeavors have been mainly devoted to static devices, exploiting only a glimpse of opportunities that metasurfaces can offer. We demonstrate a dynamic metasurface platform, which allows independent manipulation of addressable subwavelength pixels at visible frequencies through controlled chemical reactions. In particular, we create dynamic metasurface holograms for advanced optical information processing and encryption. Plasmonic nanorods tailored to exhibit hierarchical reaction kinetics upon hydrogenation/dehydrogenation constitute addressable pixels in multiplexed metasurfaces. The helicity of light, hydrogen, oxygen, and reaction duration serve as multiple keys to encrypt the metasurfaces. One single metasurface can be deciphered into manifold messages with customized keys, featuring a compact data storage scheme as well as a high level of information security. Our work suggests a novel route to protect and transmit classified data, where highly restricted access of information is imposed.
Neural scene representation and rendering

A scene-internalizing computer program To train a computer to “recognize” elements of a scene supplied by its visual sensors, computer scientists typically use millions of images painstakingly labeled by humans. Eslami et al. developed an artificial vision system, dubbed the Generative Query Network (GQN), that has no need for such labeled data. Instead, the GQN first uses images taken from different viewpoints and creates an abstract description of the scene, learning its essentials. Next, on the basis of this representation, the network predicts what the scene would look like from a new, arbitrary viewpoint. Science, this issue p. 1204 A computer vision system predicts how a 3D scene looks from any viewpoint after just a few 2D views from other viewpoints. Scene representation—the process of converting visual sensory data into concise descriptions—is a requirement for intelligent behavior. Recent work has shown that neural networks excel at this task when provided with large, labeled datasets. However, removing the reliance on human labeling remains an important open problem. To this end, we introduce the Generative Query Network (GQN), a framework within which machines learn to represent scenes using only their own sensors. The GQN takes as input images of a scene taken from different viewpoints, constructs an internal representation, and uses this representation to predict the appearance of that scene from previously unobserved viewpoints. The GQN demonstrates representation learning without human labels or domain knowledge, paving the way toward machines that autonomously learn to understand the world around them.
Strategies for improving the specificity of siRNAs for enhanced therapeutic potential

ABSTRACT Introduction: RNA interference has become a tool of choice in the development of drugs in various therapeutic areas of Post Transcriptional Gene Silencing (PTGS). The critical element in developing successful RNAi therapeutics lies in designing small interfering RNA (siRNA) using an efficient algorithm satisfying the designing criteria. Further, translation of siRNA from bench-side to bedside needs an efficient delivery system and/or chemical modification. Areas covered: This review emphasizes the importance of dicer, the criteria for efficient siRNA design, the currently available algorithms and strategies to overcome off-target effects, immune stimulatory effects and endosomal trap. Expert opinion: Specificity and stability are the primary concerns for siRNA therapeutics. The design criteria and algorithms should be chosen rationally to have a siRNA sequence that binds to the corresponding mRNA as it happens in the Watson and Crick base pairing. However, it must evade a few more hurdles (Endocytosis, Serum stability etc.) to be functional in the cytosol.
Farrerol Relieve Lipopolysaccharide (LPS)-Induced Mastitis by Inhibiting AKT/NF-κB p65, ERK1/2 and P38 Signaling Pathway

Farrerol has been proved to have an anti-inflammatory effect. However, the effects of farrerol on mastitis have not been investigated. This study was aimed to investigate the effect and mechanism of farrerol in lipopolysaccharide (LPS)-induced mouse mastitis and LPS-induced inflammatory response of mouse mammary epithelial cells (mMECs). In vivo, LPS were injected to the tetrad pair of nipples for establishing mouse mastitis, and then tested the effect of farrerol on histopathological changes, inflammatory response and activation degree of protein kinase B (AKT), nuclear factor-kappa B p65 (NF-κB p65), p38, extracellular regulated protein kinase (ERK1/2). In vitro, the mMECs were incubated by farrerol for 1 h following by stimulating with LPS, and then the inflammatory response and the related signaling pathways were detected. The in vivo results found that farrerol could improve pathological injury of mammary gland, attenuate the activity of myeloperoxidase (MPO), inhibit the production of pro-inflammatory mediators and the phosphorylation of AKT, NF-κB p65, p38 and ERK1/2. The in vitro results also found farrerol inhibited inflammatory response and the related signaling pathways. Collectively, this study revealed that farrerol inhibits the further development of LPS-induced mastitis by inhibiting inflammatory response via down regulating phosphorylation of AKT, NF-κB p65, p38, and ERK1/2. These findings suggest that farrerol may be used as an anti-inflammatory drug for mastitis.
Ultrahigh verapamil-loaded controlled release polymeric beads using superamphiphobic substrate: D-optimal statistical design, in vitro and in vivo performance

Abstract Controlled-release multiparticulate systems of hydrophilic drugs usually suffer from poor encapsulation and rapid-release rate. In the present study, ultra-high loaded controlled release polymeric beads containing verapamil hydrochloride (VP) as hydrophilic model drug were efficiently prepared using superamphiphobic substrates aiming to improve patient compliance by reducing dosing frequency. Superamphiphobic substrates were fabricated using clean aluminum sheets etched with ammonia solution and were treated with 1.5% (w/v) perfluorodecyltriethoxysilane (PFDTS) alcoholic solution. The effect of the main polymer type (lactide/glycolide (PLGA) 5004A, PLGA 5010, and polycaprolactone (PCL)), copolymer (Eudragit RS100) content together with the effect of drug load on encapsulation efficiency (EE%) and in vitro drug release was statistically studied and optimized via D-optimal statistical design. In vivo pharmacokinetic study was carried out to compare the optimized system relative to the market product (Isoptin®). Results revealed that superamphiphobic substrates were successfully prepared showing a rough micro-sized hierarchical structured surface upon observing with scanning electron microscope and were confirmed by high contact angles of 151.60 ± 2.42 and 142.80°±05.23° for water and olive oil, respectively. The fabricated VP-loaded beads showed extremely high encapsulation efficiency exceeding 92.31% w/w. All the prepared systems exhibited a controlled release behavior with Q12 h ranging between 5.46 and 95.90%w/w. The optimized VP-loaded system composed of 150 mg (1.5% w/v) PCL without Eudragit RS100 together with 160 mg VP showed 2.7-folds mean residence time compared to the market product allowing once daily administration instead of three times per day.
Non-pathogenic Escherichia coli Enhance Stx2a Production of E. coli O157:H7 Through Both bamA-Dependent and Independent Mechanisms

Intestinal colonization by the foodborne pathogen Escherichia coli O157:H7 leads to serious disease symptoms, including hemolytic uremic syndrome (HUS) and hemorrhagic colitis (HC). Synthesis of one or more Shiga toxins (Stx) is essential for HUS and HC development. The genes encoding Stx, including Stx2a, are found within a lambdoid prophage integrated in the E. coli O157:H7 chromosome. Enhanced Stx2a expression was reported when specific non-pathogenic E. coli strains were co-cultured with E. coli O157:H7, and it was hypothesized that this phenotype required the non-pathogenic E. coli to be sensitive to stx-converting phage infection. We tested this hypothesis by generating phage resistant non-pathogenic E. coli strains where bamA (an essential gene and Stx phage receptor) was replaced with an ortholog from other species. Such heterologous gene replacement abolished the ability of the laboratory strain E. coli C600 to enhance toxin production when co-cultured with E. coli O157:H7 strain PA2, which belongs to the hypervirulent clade 8. The extracellular loops of BamA (loop 4, 6, 7) were further shown to be important for infection by stx2a-converting phages. However, similar gene replacement in another commensal E. coli, designated 1.1954, revealed a bamA-independent mechanism for toxin amplification. Toxin enhancement by 1.1954 was not the result of phage infection through an alternative receptor (LamB or FadL), lysogen formation by stx2a-converting phages, or the production of a secreted molecule. Collectively, these data suggest that non-pathogenic E. coli can enhance toxin production through at least two mechanisms.
Cellular dynamics of conjugation in the ciliate euplotes aediculatus. II. Cellular membranes

The formation and subsequent dissolution of a common bridge of cytoplasm between conjugating ciliated protozoan cells provides an excellent opportunity to follow the dynamics of the cellular membrane systems involved in this process. In particular, separation of conjugant partners offers the chance to observe, at a fixed site on the cell surface, how the ciliate surface complex of plasma and alveolar membranes (collectively termed the “pellicle”) is constructed. Consequently, cortical and cellular membranes of Euplotes aediculatus were studied by light and electron microscopy through the conjugation sequence. A conjugant fusion zone of shared cytoplasm elaborates between the partner cells within their respective oral fields (peristomes) to include microtubules, cytosol, and a concentrated endoplasmic reticulum (heavily stained by osmium impregnation techniques) that may also be continuous with cortical ER of each cell. Cortical membranes displacd by fusion are autolyzed in acid phosphatase‐positive lysosomes in the fusion zone. As conjugants separate, expansion of the plasma membrane may occur through the fusion of vesicles with the plasma membrane, presumably at bare membrane, presumably at bare membrane patches near the fusion zone. The underlying cortical alveolar membranes and their plate‐like contents are reconstructed beneath the plasma membrane, apparently by multiple fusions of dense‐cored alveolar precursor vesicles (APVs). These precursor vesicles themselves appear to condense directly from the smooth ER present in the fusion zone. No Golgi apparatus was visible in the fusion zone cytoplasm, and no step of APV maturation that might involve the Golgi complex was noted.
Nearly Zero-Shot Learning for Semantic Decoding in Spoken Dialogue Systems

This paper presents two ways of dealing with scarce data in semantic decoding using N-Best speech recognition hypotheses. First, we learn features by using a deep learning architecture in which the weights for the unknown and known categories are jointly optimised. Second, an unsupervised method is used for further tuning the weights. Sharing weights injects prior knowledge to unknown categories. The unsupervised tuning (i.e. the risk minimisation) improves the F-Measure when recognising nearly zero-shot data on the DSTC3 corpus. This unsupervised method can be applied subject to two assumptions: the rank of the class marginal is assumed to be known and the class-conditional scores of the classifier are assumed to follow a Gaussian distribution.
Direction-dependent interaction rules enrich pattern formation in an individual-based model of collective behavior

Direction-dependent interaction rules are incorporated into a one-dimensional discrete-time stochastic individual-based model (IBM) of collective behavior to compare pattern formation with an existing partial differential equation (PDE) model. The IBM is formulated in terms of three social interaction forces: repulsion, alignment, and attraction, and includes information regarding conspecifics’ direction of travel. The IBM produces a variety of spatial patterns which qualitatively match patterns observed in a PDE model. The addition of direction-dependent interaction rules exemplifies how directional information transfer within a group of individuals can result in enriched pattern formation. Our individual-based modelling framework reveals the influence that direction-dependent interaction rules such as biological communication can have upon individual movement trajectories and how these trajectories combine to form group patterns.
The classification of pediatric and young adult renal cell carcinomas registered on the children's oncology group (COG) protocol AREN03B2 after focused genetic testing

Renal cell carcinomas (RCCs) are rare in young patients. Knowledge of their pathologic and molecular spectrum remains limited, and no prospective studies have been performed to date in this population. This study analyzes patients diagnosed with RCC who were prospectively enrolled in the AREN03B2 Children's Oncology Group (COG). The objective was to classify these tumors with the aid of focused genetic testing and to characterize their features.
Delineating FtsQ-mediated regulation of cell division in Mycobacterium tuberculosis

Identifying and characterizing the individual contributors to bacterial cellular elongation and division will improve our understanding of their impact on cell growth and division. Here, we delineated the role of ftsQ, a terminal gene of the highly conserved division cell wall (dcw) operon, in growth, survival, and cell length maintenance in the human pathogen Mycobacterium tuberculosis (Mtb). We found that FtsQ overexpression significantly increases the cell length and number of multiseptate cells. FtsQ depletion in Mtb resulted in cells that were shorter than WT cells during the initial growth stages (4 days after FtsQ depletion) but were longer than WT cells at later stages (10 days after FtsQ depletion) and compromised the survival in vitro and in differentiated THP1 macrophages. Overexpression of N- and C-terminal FtsQ regions altered the cell length, and the C-terminal domain alone complemented the FtsQ depletion phenotype. MS analyses suggested robust FtsQ phosphorylation on Thr-24, and although phosphoablative and -mimetic mutants rescued the FtsQ depletion–associated cell viability defects, they failed to complement the cell length defects. MS and coimmunoprecipitation experiments identified 63 FtsQ-interacting partners, and we show that the interaction of FtsQ with the recently identified cell division protein SepIVA is independent of FtsQ phosphorylation and suggests a role of FtsQ in modulating cell division. FtsQ exhibited predominantly septal localization in both the presence and absence of SepIVA. Our results suggest a role for FtsQ in modulating the length, division, and survival of Mtb cells both in vitro and in the host.
Preferred sampler inlet configurations for collection of aerosolized nano-scale materials

ABSTRACT Background: Due to the lack of standard industrial hygiene sampling protocols for collection of nano-scale materials, sampling inlet device selection is left to individual researchers and professionals. Objective: The objective of this study was to compare nano-scale aspiration efficiency for common inlet configurations with that of an open-ended sampler tube that is a commonly used inlet for direct reading instruments such as a condensation particle counter. Methods: A polydisperse aerosol was generated using an electric motor as the aerosol source. Typical aerosols generated by this method produced particles with geometric mean mobility diameters of approximately 30 nm with geometric standard deviations of approximately 2. Comparison of raw particle counts in size ranges measured with a scanning mobility particle analyzer was made by determining the fractional difference between the selected inlet and that of the open-ended tube. Results: Particle size distributions were nearly identical for all inlet types. The same held true for numbers of particles collected with the exception that the needle inlet was highly variable. Conclusions: When completing air monitoring for nano-scale materials, inlets on most collection devices (filters, tubing) do not impact aspiration efficiency. This means that it is not necessary to match inlet configurations when using multiple methods to collect and analyze nano-scale materials.