Miracle-dz/UniFAR-FTUs huggingface dataset:
Microstructure evolution of ZK40 magnesium alloy during high strain rate compression deformation at elevated temperatures

Abstract Microstructure evolution of the homogenised ZK40 magnesium alloy was investigated during compression in the temperature range of 250–400°C and at the strain rate range of 0·01–50 s−1. At a higher strain rate (⩾10 s−1), dynamic recrystallisation developed extensively at grain boundaries and twins, resulting in a more homogeneous microstructure than the other conditions. The hot deformation characteristics of ZK40 exhibited an abnormal relationship with the strain rate, i.e., the hot workability increased with increasing the strain rate. However, the dynamic recrystallisation grain size was almost the same with increasing the temperature at the strain rate of 10 s−1, while it increased obviously at the strain rates of 20 and 50 s−1. Therefore, hot deformation at the strain rate of 10 s−1 and temperature range of 250–400°C was desirable and feasible for the ZK40 alloy.
Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell’s own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors—tapasin for class I and HLA-DM for class II—contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity.
Low voltage ride-through of DFIG and brushless DFIG: Similarities and differences

The brushless doubly fed induction generator (BDFIG) has been proposed as a viable alternative in wind turbines to the commonly used doubly fed induction generator (DFIG). The BDFIG retains the beneﬁts of the DFIG, i.e. variable speed operation with a partially rated converter, but without the use of brush gear and slip rings, thereby conferring enhanced reliability. As low voltage ride-through (LVRT) performance of the DFIG-based wind turbine is well understood, this paper aims to analyze LVRT behavior of the BDFIG-based wind turbine in a similar way. In order to achieve this goal, the equivalence between their two-axis model parameters is investigated. The variation of ﬂux linkages, back-EMFs and currents of both types of generator are elaborated during three phase voltage dips. Moreover, the structural differences between the two generators, which lead to different equivalent parameters and hence different LVRT capabilities, are investigated. The analytical results are veriﬁed via time-domain simulations for medium size wind turbine genera- tors as well as experimental results of a voltage dip on a prototype 250 kVA BDFIG.
Direction selectivity in the larval zebrafish tectum is mediated by asymmetric inhibition

The extraction of the direction of motion is an important computation performed by many sensory systems and in particular, the mechanism by which direction-selective retinal ganglion cells (DS-RGCs) in the retina acquire their selective properties, has been studied extensively. However, whether DS-RGCs simply relay this information to downstream areas or whether additional and potentially de novo processing occurs in these recipient structures is a matter of great interest. Neurons in the larval zebrafish tectum, the largest retino-recipent area in this animal, show direction-selective (DS) responses to moving visual stimuli but how these properties are acquired is still unknown. In order to study this, we first used two-photon calcium imaging to classify the population responses of tectal cells to bars moving at different speeds and in different directions. Subsequently, we performed in vivo whole cell electrophysiology on these DS tectal neurons and we found that their inhibitory inputs were strongly biased toward the null direction of motion, whereas the excitatory inputs showed little selectivity. In addition, we found that excitatory currents evoked by a stimulus moving in the preferred direction occurred before the inhibitory currents whereas a stimulus moving in the null direction evoked currents in the reverse temporal order. The membrane potential modulations resulting from these currents were enhanced by the spike generation mechanism to generate amplified direction selectivity in the spike output. Thus, our results implicate a local inhibitory circuit in generating direction selectivity in tectal neurons.
Relation Extraction with Matrix Factorization and Universal Schemas

© 2013 Association for Computational Linguistics. Traditional relation extraction predicts relations within some fixed and finite target schema. Machine learning approaches to this task require either manual annotation or, in the case of distant supervision, existing structured sources of the same schema. The need for existing datasets can be avoided by using a universal schema: the union of all involved schemas (surface form predicates as in OpenIE, and relations in the schemas of preexisting databases). This schema has an almost unlimited set of relations (due to surface forms), and supports integration with existing structured data (through the relation types of existing databases). To populate a database of such schema we present matrix factorization models that learn latent feature vectors for entity tuples and relations. We show that such latent models achieve substantially higher accuracy than a traditional classification approach. More importantly, by operating simultaneously on relations observed in text and in pre-existing structured DBs such as Freebase, we are able to reason about unstructured and structured data in mutually-supporting ways. By doing so our approach outperforms stateof- the-Art distant supervision.
MMAN - a monitor for mobile ad hoc networks: design, implementation, and experimental evaluation

Mobile Ad hoc NETworks (MANETs) are networks in which mobile routers are connected via wireless links forming dynamic topologies. An important function of network management in a MANET is to observe network conditions: at the node level, this may mean keeping track of the traffic load; at the network level, the system must monitor active routes and changes in the network topology. In this research, we introduce a Monitor for Mobile Ad hoc Networks, (MMAN) to address the challenges of monitoring MANETs. We formulate an overall design structure and present an implementation of our framework for a MANET running the Optimized Link State Routing (OLSR) protocol. The unobtrusive and distributed nature of MMAN allows the system to adapt to the constantly changing nature of MANETs and to provide valuable network management, security assessment, and traffic analysis information. Our system produces a dynamic picture of the network level and node level information on a graphical user interface. The system is non-intrusive, generates no additional traffic in the MANET it monitors, and requires only modest processing and storage resources.
Dislocation dynamics simulations of plasticity at small scales

As metallic structures and devices are being created on a dimension comparable to the length scales of the underlying dislocation microstructures, the mechanical properties of them change drastically. Since such small structures are increasingly common in modern technologies, there is an emergent need to understand the critical roles of elasticity, plasticity, and fracture in small structures. Dislocation dynamics (DD) simulations, in which the dislocations are the simulated entities, offer a way to extend length scales beyond those of atomistic simulations and the results from DD simulations can be directly compared with the micromechanical tests. The primary objective of this research is to use 3-D DD simulations to study the plastic deformation of nano- and micro-scale materials and understand the correlation between dislocation motion, interactions and the mechanical response. Specifically, to identify what critical events (i.e., dislocation multiplication, cross-slip, storage, nucleation, junction and dipole formation, pinning etc.) determine the deformation response and how these change from bulk behavior as the system decreases in size and correlate and improve our current knowledge of bulk plasticity with the knowledge gained from the direct observations of small-scale plasticity. Our simulation results on single crystal micropillars and polycrystalline thin films can march the experiment results more » well and capture the essential features in small-scale plasticity. Furthermore, several simple and accurate models have been developed following our simulation results and can reasonably predict the plastic behavior of small scale materials. « less
Metabolic risk factors and primary liver cancer in a prospective study of 578,700 adults

Initial studies have indicated diabetes and obesity to be risk factors for hepatocellular carcinoma; but the association between other metabolic risk factors and primary liver cancer (PLC) has not been investigated. The metabolic syndrome and cancer project (Me‐Can) includes cohorts from Norway, Austria and Sweden with data on 578,700 subjects. We used Cox proportional hazard models to calculate relative risks (RRs) of PLC by body mass index (BMI), blood pressure and plasma levels of glucose, cholesterol and triglycerides as continuous standardized variables (z‐score with mean = 0 and standard deviation (SD) = 1) and their standardized sum of metabolic syndrome (MetS) z‐score. RRs were corrected for random error in measurements. During an average follow‐up of 12.0 years (SD = 7.8), 266 PLCs were diagnosed among cohort members. RR of liver cancer per unit increment of z‐score adjusted for age, smoking status and BMI and stratified by birth year, sex and sub‐cohorts, was for BMI 1.39 (95% confidence interval (CI) 1.24–1.58), mid blood pressure 2.08 (0.95–4.73), blood glucose 2.13 (1.55–2.94) cholesterol 0.62 (0.51–0.76) and serum triglycerides 0.85 (0.65–1.10). The RR per one unit increment of the MetS z‐score was 1.35 (1.12–1.61). BMI, glucose and a composite MetS score were positively and cholesterol negatively associated with risk of liver cancer.
The Neuromagnetic Dynamics of Time Perception

Examining real-time cortical dynamics is crucial for understanding time perception. Using magnetoencephalography we studied auditory duration discrimination of short (<.5 s) versus long tones (>.5 s) versus a pitch control. Time-frequency analysis of event-related fields showed widespread beta-band (13–30 Hz) desynchronization during all tone presentations. Synthetic aperture magnetometry indicated automatic primarily sensorimotor responses in short and pitch conditions, with activation specific to timing in bilateral inferior frontal gyrus. In the long condition, a right lateralized network was active, including lateral prefrontal cortices, inferior frontal gyrus, supramarginal gyrus and secondary auditory areas. Activation in this network peaked just after attention to tone duration was no longer necessary, suggesting a role in sustaining representation of the interval. These data expand our understanding of time perception by revealing its complex cortical spatiotemporal signature.
Diverse effects of Purkinje cell loss on deep cerebellar and vestibular nuclei neurons in Purkinje cell degeneration mutant mice: A possible compensatory mechanism

The genetic defect in the Purkinje cell degeneration (PCD) mutant mouse completely disrupts the cerebellar corticonuclear connection through intrinsic action on the final integrating unit of the cerebellar cortex, the Purkinje cell (PC). The postsynaptic target neurons of the PC in the deep cerebellar nuclei (DCN) and the vestibular nuclei (VN) are denervated by this PC loss by more than two‐thirds of their total γ‐aminobutyric acid (GABA)‐ergic innervation. This massive disinhibition should be reflected in an increased and thus electrophysiologically detectable activity of the respective neurons. To address this question, we performed extracellular recordings of PCD mutant and corresponding wild‐type VN neurons under sinusoidal vestibular stimulation.
Hepatitis B Infection in Vietnam

Hepatitis B virus (HBV) infection remains a major public health problem in Vietnam. Recent studies have found that prevalence of current HBV infection (HBsAg+) ranges from 10% to 20% in the general population and 20% to 40% among injecting drug users and HIV+ patients. However, HBV prevention and control in Vietnam relies heavily on universal infant vaccination program and HBsAg screening for blood donors. Currently, HBV prevention and control is underfunded by the government and receives little support from international agencies. HBV-related liver disease will continue to create a heavy burden for public health in Vietnam in the next several decades unless appropriate interventions are undertaken urgently. Establishment of a national strategy for HBV prevention and control is crucial to develop and implement effective interventions.
Achieving high convection volumes in postdilution online hemodiafiltration: a prospective multicenter study

Abstract Background. Available evidence suggests a reduced mortality risk for patients treated with high-volume postdilution hemodiafiltration (HDF) when compared with hemodialysis (HD) patients. As the magnitude of the convection volume depends on treatment-related factors rather than patient-related characteristics, we prospectively investigated whether a high convection volume (defined as ≥22 L/session) is feasible in the majority of patients (>75%). Methods. A multicenter study was performed in adult prevalent dialysis patients. Nonparticipating eligible patients formed the control group. Using a stepwise protocol, treatment time (up to 4 hours), blood flow rate (up to 400 mL/min) and filtration fraction (up to 33%) were optimized as much as possible. The convection volume was determined at the end of this optimization phase and at 4 and 8 weeks thereafter. Results. Baseline characteristics were comparable in participants (n = 86) and controls (n = 58). At the end of the optimization and 8 weeks thereafter, 71/86 (83%) and 66/83 (80%) of the patients achieved high-volume HDF (mean 25.5 ± 3.6 and 26.0 ± 3.4 L/session, respectively). While treatment time remained unaltered, mean blood flow rate increased by 27% and filtration fraction increased by 23%. Patients with <22 L/session had a higher percentage of central venous catheters (CVCs), a shorter treatment time and lower blood flow rate when compared with patients with ≥22 L/session. Conclusions. High-volume HDF is feasible in a clear majority of dialysis patients. Since none of the patients agreed to increase treatment time, these findings indicate that high-volume HDF is feasible just by increasing blood flow rate and filtration fraction.
Prediction of Acute Mammalian Toxicity Using QSAR Methods: A Case Study of Sulfur Mustard and Its Breakdown Products

Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has matured over recent years to the point that the predictions can be used to help identify missing comparison values in a substance’s database. In this manuscript we investigate using the lethal dose that kills fifty percent of a test population (the LD50) for determining relative toxicity of a number of substances. In general, the smaller the LD50 value, the more toxic the chemical, and the larger the LD50 value, the lower the toxicity. When systemic toxicity and other specific toxicity data are unavailable for the chemical(s) of interest, during emergency responses, LD50 values may be employed to determine the relative toxicity of a series of chemicals. In the present study, a group of chemical warfare agents and their breakdown products have been evaluated using four available rat oral QSAR LD50 models. The QSAR analysis shows that the breakdown products of Sulfur Mustard (HD) are predicted to be less toxic than the parent compound as well as other known breakdown products that have known toxicities. The QSAR estimated break down products LD50 values ranged from 299 mg/kg to 5,764 mg/kg. This evaluation allows for the ranking and toxicity estimation of compounds for which little toxicity information existed; thus leading to better risk decision making in the field.
A comparison of vertex ordering algorithms for large graph visualization

In this study, we examine the use of graph ordering algorithms for visual analysis of data sets using visual similarity matrices. Visual similarity matrices display the relationships between data items in a dot-matrix plot format, with the axes labeled with the data items and points drawn if there is a relationship between two data items. The biggest challenge for displaying data using this representation is finding an ordering of the data items that reveals the internal structure of the data set. Poor orderings are indistinguishable from noise whereas a good ordering can reveal complex and subtle features of the data. We consider three general classes of algorithms for generating orderings: simple graph theoretic algorithms, symbolic sparse matrix reordering algorithms, and spectral decomposition algorithms. We apply each algorithm to synthetic and real world data sets and evaluate each algorithm for interpretability (i.e., does the algorithm lead to images with usable visual features? ) and stability (i.e., does the algorithm consistently produce similar results? ). We also provide a detailed discussion of the results for each algorithm across the different graph types and include a discussion of some strategies for using ordering algorithms for data analysis based on these results.
Radix Stellariae extract prevents high-fat-diet-induced obesity in C57BL/6 mice by accelerating energy metabolism

Stellaria dichotoma L. is widely distributed in Ningxia and surrounding areas in northwestern China. Its root, Radix Stellariae (RS), has been used in herbal formulae for treating asthenic-fever, infection, malaria, dyspepsia in children and several other symptoms. This study investigated whether the RS extract (RSE) alleviates metabolic disorders. The results indicated that RSE significantly inhibited body weight gain in high-fat (HF)-diet-fed C57BL/6 mice, reduced fasting glucose levels, and improved insulin tolerance. Moreover, RSE increased the body temperature of the mice and the expression of uncoupling proteins and peroxisome proliferator-activated receptors in the white adipose tissue. Thus, RSE alleviated metabolic disorders in HF-diet-fed C57BL/6 mice by potentially activating UCP and PPAR signaling.
Complex sentence comprehension and working memory in children with specific language impairment.

PURPOSE This study investigated the association of 2 mechanisms of working memory (phonological short-term memory [PSTM], attentional resource capacity/allocation) with the sentence comprehension of school-age children with specific language impairment (SLI) and 2 groups of control children. METHOD Twenty-four children with SLI, 18 age-matched (CA) children, and 16 language- and memory-matched (LMM) children completed a nonword repetition task (PSTM), the competing language processing task (CLPT; resource capacity/allocation), and a sentence comprehension task comprising complex and simple sentences. RESULTS (1) The SLI group performed worse than the CA group on each memory task; (2) all 3 groups showed comparable simple sentence comprehension, but for complex sentences, the SLI and LMM groups performed worse than the CA group; (3) for the SLI group, (a) CLPT correlated with complex sentence comprehension, and (b) nonword repetition correlated with simple sentence comprehension; (4) for CA children, neither memory variable correlated with either sentence type; and (5) for LMM children, only CLPT correlated with complex sentences. CONCLUSIONS Comprehension of both complex and simple grammar by school-age children with SLI is a mentally demanding activity, requiring significant working memory resources.
Booms and Banking Crises

Banking crises are rare events that break out in the midst of credit-intensive booms and bring about deep and long-lasting recessions. This paper presents a textbook dynamic stochastic general equilibrium model to explain these phenomena. The model features a nontrivial banking sector, where bank heterogeneity gives rise to an interbank market. Moral hazard and asymmetric information in this market may lead to sudden market freezes, banking crises, credit crunches, and severe “financial” recessions. Those recessions follow credit booms and are not necessarily triggered by large exogenous adverse shocks.
Binary nanoparticle superlattices of soft-particle systems

Significance The phase diagram of a system of two species of particles with different diameters interacting with a soft (1/r12) potential is provided. The results provide a general framework to predict the crystalline phases observed in nanoparticle superlattices. The approach is particularly relevant for nanoparticles with hydrocarbon capping ligands where theoretical descriptions have been based on hard-sphere systems and is general enough to consider supercrystals obtained by DNA programmable self-assembly, thus providing a conceptual unification for general nanoparticle superlattice systems. The solid-phase diagram of binary systems consisting of particles of diameter σA=σ and σB=γσ (γ≤1) interacting with an inverse p = 12 power law is investigated as a paradigm of a soft potential. In addition to the diameter ratio γ that characterizes hard-sphere models, the phase diagram is a function of an additional parameter that controls the relative interaction strength between the different particle types. Phase diagrams are determined from extremes of thermodynamic functions by considering 15 candidate lattices. In general, it is shown that the phase diagram of a soft repulsive potential leads to the morphological diversity observed in experiments with binary nanoparticles, thus providing a general framework to understand their phase diagrams. Particular emphasis is given to the two most successful crystallization strategies so far: evaporation of solvent from nanoparticles with grafted hydrocarbon ligands and DNA programmable self-assembly.