Miracle-dz/UniFAR-FTUs huggingface dataset:
A Finite-Volume Model for Numerical Solidification of Mg Alloys

Solidification of a wedge casting of magnesium alloy AZ31 in the presence of melt convection is investigated. The formulation used in the in-house code is developed based on the finite-volume method on unstructured grids and utilizes a colocated finite-volume framework. In the discretization of the mass and momentum equations all novelties proposed in [1] are implemented and a source based-energy equation is presented. The volume fraction of solid in the domain and the cooling rates at six different embedded thermocouples are predicted. These results are compared to previous experimental work and against similar results obtained with a widely used commercial software package.
Augmentation of Carrier-Phase DGPS with UWB Ranges for Relative Vehicle Positioning

In this paper, vehicle relative positioning applied in Vehicle-to-Infrastructure (V2I) navigation is described. GPS positioning augmented with Ultra-Wideband (UWB) ranges is reviewed. The relative solution is implemented in an extended Kalman filter where differential GPS pseudorange, Doppler and carrier phase measurements are used in conjunction with UWB ranges measured between the vehicle and two points on either side of the road. Results indicate that the GPS and UWB integrated positioning system can significantly improve the GPS float solution and ambiguity resolution compared to the GPS-only case. The probability of incorrect fix (PIF) can be improved considerably when adding UWB measurements, but only after the vehicle passes the intersection. The data rate of the GPS measurements has a significant impact on PIF values.
The research of EM wave absorbing properties of ferrite/silicon carbide double coated polyester woven fabric

Abstract In this paper, polyester woven fabric was selected as the fundamental fabric. Ferrite and silicon carbide were the underlying and surface layer absorbing agents, respectively. The influence of the content of the ferrite and silicon carbide absorbent and coating thickness on dielectric constant were discussed. Through the optimization of electromagnetic parameters, ferrite/silicon carbide double-coating polyester woven fabric absorbing materials with the best wave absorption performance were prepared. The results showed that through optimization, at high frequency (105 Hz < f < 107 Hz), when the ferrite content was 60%, the ferrite coating (bottom layer) had a thickness of 1.00 mm, the amount of silicon carbide was 48%, the silicon carbide coating layer (surface layer) was 0.50 mm, and the coated fabric had the best absorbing performance.
Antigen-Specific Responses Accelerate Bacterial Clearance in the Bladder1

Urinary tract infections (UTIs) cause patient morbidity and have a substantial economic impact. Half of all women will suffer a UTI at least once, and 25% of these women will have recurrent infections. That 75% of previously infected women do not become reinfected strongly suggests a role for an adaptive immune response. The goal of this study was to characterize the adaptive immune responses to uropathogenic Escherichia coli (UPEC), the predominant uropathogen. A novel murine model of UTI reinfection was developed using the prototypic cystitis UPEC isolate NU14 harboring a plasmid encoding OVA as a unique antigenic marker. Bacterial colonization of the bladder was quantified following one or more infections with NU14-OVA. Animals developed anti-OVA serum IgG and IgM titers after the initial infection and marked up-regulation of activation markers on splenic T cells. We observed a 95% reduction in bacterial colonization upon reinfection, and splenic leukocytes showed Ag-specific proliferation in vitro. Adoptive transfer of splenic T cells or passive transfer of serum from previously infected mice protected naive syngeneic mice from UPEC colonization. These findings support our hypothesis that adaptive immune responses to UPEC protect the bladder from reinfection and form the basis of understanding susceptibility to recurrent UTI in women.
Stromal-to-Epithelial Transition during Postpartum Endometrial Regeneration

Endometrium is the inner lining of the uterus which is composed of epithelial and stromal tissue compartments enclosed by the two smooth muscle layers of the myometrium. In women, much of the endometrium is shed and regenerated each month during the menstrual cycle. Endometrial regeneration also occurs after parturition. The cellular mechanisms that regulate endometrial regeneration are still poorly understood. Using genetic fate-mapping in the mouse, we found that the epithelial compartment of the endometrium maintains its epithelial identity during the estrous cycle and postpartum regeneration. However, whereas the stromal compartment maintains its identity during homeostatic cycling, after parturition a subset of stromal cells differentiates into epithelium that is subsequently maintained. These findings identify potential progenitor cells within the endometrial stromal compartment that produce long-term epithelial tissue during postpartum endometrial regeneration.
Dynamic Weight-Based Individual Similarity Calculation for Information Searching in Social Computing

In the social computing environment, the complete information about an individual is usually distributed in heterogeneous social networks, which are presented as linked data. Synthetically recognizing and integrating these distributed and heterogeneous data for efficiently information searching is an important but challenging work. In this paper, a dynamic weight (DW)-based similarity calculation is proposed to recognize and integrate similar individuals from distributed data environments. First, each link of an individual is weighted by applying DW. Then, a semantic similarity metric is proposed to combine the DW into similarity calculation. Then, a searching system framework for a similarity-based individual is designed and tested in real-world data sets. Finally, massive experiments are conducted both in benchmark and real-world social community data sets. The results show that our approach can produce a good result in similar individual searching in social networks. In addition, it performs significantly better than the existing state-of-the-art approaches in similar individual searching.
Dead-End Elimination as a Heuristic for Min-Cut Image Segmentation

We apply the dead-end elimination (DEE) strategy from protein design as a heuristic for the max-flow/min-cut formulation of the image segmentation problem. DEE combines aspects of constraint propagation and branch-and-bound to eliminate solutions incompatible with global optimization of the objective function. Though DEE can be used for segmentation into an arbitrary number of regions, in this paper we evaluate only the case of binary segmentation. We provide a runtime analysis and evaluation of DEE applied to two min-cut algorithms. Preliminary results show that DEE consistently reduces the search space for the Edmonds-Karp algorithm; tuning DEE as a heuristic for Boykov-Kolmogorov and other algorithms is future work.
Influence of Post-Implantation Annealing Temperature on MOSFET Performance and Oxide Reliability

In the present work, we studied the influence of the post-implantation annealing temperature on the performance and oxide reliability of lateral 4H-SiC MOSFETs. The maximum field effect mobility of the MOSFETs at 25°C decreases from 22.4cm2/Vs to 17.2cm2/Vs by increasing annealing temperature from 1600°C to 1800°C. Respectively, the measured meantime to failure is about one order of magnitude higher for the 1700°C annealed sample at an applied field of 8.5MV/cm compared to the 1600°C and 1800°C annealed samples.
Tracking the Evolution of Multiple In Vitro Hepatitis C Virus Replicon Variants under Protease Inhibitor Selection Pressure by 454 Deep Sequencing

ABSTRACT Resistance to hepatitis C virus (HCV) inhibitors targeting viral enzymes has been observed in in vitro replicon studies and during clinical trials. The factors determining the emergence of resistance and the changes in the viral quasispecies population under selective pressure are not fully understood. To assess the dynamics of variants emerging in vitro under various selective pressures with TMC380765, a potent macrocyclic HCV NS3/4A protease inhibitor, HCV genotype 1b replicon-containing cells were cultured in the presence of a low, high, or stepwise-increasing TMC380765 concentration(s). HCV replicon RNA from representative samples thus obtained was analyzed using (i) population, (ii) clonal, and (iii) 454 deep sequencing technologies. Depending on the concentration of TMC380765, distinct mutational patterns emerged. In particular, culturing with low concentrations resulted in the selection of low-level resistance mutations (F43S and A156G), whereas high concentrations resulted in the selection of high-level resistance mutations (A156V, D168V, and D168A). Clonal and 454 deep sequencing analysis of the replicon RNA allowed the identification of low-frequency preexisting mutations possibly contributing to the mutational pattern that emerged. Stepwise-increasing TMC380765 concentrations resulted in the emergence and disappearance of multiple replicon variants in response to the changing selection pressure. Moreover, two different codons for the wild-type amino acids were observed at certain NS3 positions within one population of replicons, which may contribute to the emerging mutational patterns. Deep sequencing technologies enabled the study of minority variants present in the HCV quasispecies population present at baseline and during antiviral drug pressure, giving new insights into the dynamics of resistance acquisition by HCV.
Multi-resolution sound rendering

Point-based multi-resolution representations have been used successfully for rendering highly complex three dimensional scenes in real-time. In this paper, we apply this paradigm to sound rendering: A hierarchy of stochastic sample sound sources is used to approximate complex sound environments (containing a large number of sound sources, such as a football stadium), allowing for interactive real-time walkthroughs. Additionally, the proposed technique can be used for observer-dependent auralizations of simple approximations of global sound propagation. Typical applications of the technique are in virtual reality and computer games, especially to complement established output-sensitive algorithms for rendering visual content.
Examining the Causal Relationship between Screen Size and Cellular Data Consumption

Abstract This study utilizes a terabyte dataset from a telecommunications company to examine the relationship between screen size and cellular data consumption for a large number of phone and tablet users. We find the relationship exhibits a different pattern within the two device categories of phones and tablets. For phone users, there is an overall positive and significant relationship over the range of screen size from 1 inch to below 7 inches, which is, however, mainly driven by the dramatic decrease in usage on traditional phones with screens less than 3 inches. Particularly for smartphones with screens 3.5 inches or higher, we do not find a significant relationship between screen size and cellular data consumption measured by either the time spent on the mobile network or the amount of data transmitted. For tablet users, we find evidence that suggests that people spend less time on tablets with bigger screens, which could potentially be due to the reduced portability of large tablets. Our findings can provide important implications for mobile network operators in promoting data plans to users with different devices. Keywords: big data, telecommunications, screen size, data usage, smartphone, tablet.
Safira: a tool for evaluating behavior preservation

We propose a tool (Safira) capable of determining if a transformation is behavior preserving through test generation for entities impacted by transformation. We use Safira to evaluate mutation testing and refactoring tools. We have detected 17 bugs in MuJava, and 27 bugs in refactorings implemented by Eclipse and JRRT.
"Vection field" for pedestrian traffic control

Visual signs and audio cues are commonly used for pedestrian control in the field of general traffic research. Because pedestrians need to first acquire and then recognize such cues, time delays invariably occur between cognition and action. To better cope with this issue of delays, wearable devices have been proposed to control pedestrians more intuitively. However, the attaching and removing of the devices can be cumbersome and impractical. In this study, we propose a new visual navigation method for pedestrians using a "Vection Field" in which the optical flow is presented on the ground. The optical flow is presented using a lenticular lens, a passive optical element that generates a visual stimulus based on a pedestrian's movement without an electrical power supply. In this paper we present a design for the fundamental visual stimulus and evaluate the principle of our proposed method for directional navigation. Results revealed that the optical-flow of a stripe and random-dot pattern displaced pedestrian pathways significantly, and that implementation with a lenticular lens is feasible.
Progress in CVD synthesis of layered hexagonal boron nitride with tunable properties and their applications

A very thin layer of hexagonal boron nitride (h-BN) is an important 2D nanomaterial, sometimes called ‘white graphene’, with many properties distinct from graphene. However, the lack of controlled synthesis of high quality and wide-area films largely prevents realisation of the full potential of this material. In this review article, a comprehensive overview of the current status of the synthesis, growth mechanism using chemical vapour deposition, structure and electronic properties to tune the bandgap is covered. In particular, the progress towards achieving the improved quality and functionalities of the h-BN films via epitaxial growth and control of grain size, number of layers, morphology and orientation have been critically reviewed. In addition to synthesis and properties of the atomically thin (mono and few layer) h-BN, the applications in possible and emerging areas are also described and discussed.
Computation of Perfect DCJ Rearrangement Scenarios with Linear and Circular Chromosomes

We study the problem of transforming a multichromosomal genome into another using Double Cut-and-Join (DCJ) operations, which simulates several types of rearrangements, as reversals, translocations, and block-interchanges. We introduce the notion of a DCJ scenario that does not break families of common intervals (groups of genes co-localized in both genomes). Such scenarios are called perfect, and their properties are well known when the only considered rearrangements are reversals. We show that computing the minimum perfect DCJ rearrangement scenario is NP-hard, and describe an exact algorithm which exponential running time is bounded in terms of a specific pattern used in the NP-completeness proof. The study of perfect DCJ rearrangement leads to some surprising properties. The DCJ model has often yielded algorithmic problems which complexities are comparable to the reversal-only model. In the perfect rearrangement framework, however, while perfect sorting by reversals is NP-hard if the family of common intervals to be preserved is nested, we show that finding a shortest perfect DCJ scenario can be answered in polynomial time in this case. Conversely, while perfect sorting by reversals is tractable when the family of common intervals is weakly separable, we show that the corresponding problem is still NP-hard in the DCJ case. This shows that despite the similarity of the two operations, easy patterns for reversals are hard ones for DCJ, and vice versa.
Rhizobium fix genes mediate at least two communication steps in symbiotic nodule development

To identify bacterial genes involved in symbiotic nodule development, ineffective nodules of alfalfa (Medicago sativa) induced by 64 different Fix-mutants of Rhizobium meliloti were characterized by assaying for symbiotic gene expression and by morphological studies. The expression of leghemoglobin and nodulin-25 genes from alfalfa and of the nifHD genes from R. meliloti were monitored by hybridizing the appropriate DNA probes to RNA samples prepared from nodules. The mutants were accordingly divided into three groups. In group I none of the genes were expressed, in group II only the plant genes were expressed and in group III all three genes were transcribed. Light and electron microscopical analysis of nodules revealed that nodule development was halted at different stages in nodules induced by different group I mutants. In most cases nodules were empty lacking infection threads and bacteroids or nodules contained infection threads and a few released bacteroids. In nodules induced by a third mutant class bacteria were released into the host cells, however the formation of the peribacteroid membrane was not normal. On this basis we suggest that peribacteroid membrane formation precedes leghemoglobin and nodulin-25 induction, moreover, after induction of nodulation by the nod genes at least two communication steps between the bacteria and the host plants are necessary for the development of the mature nodule. By complementing each mutant of group I with a genomic R. meliloti library made in pLAFRl, four new fix loci were identified, indicating that several bacterial genes are involved in late nodule development.
Interactive tracking of movable objects for the blind on the basis of environment models and perception-oriented object recognition methods

In previous work we have presented a prototype of an assistant system for the blind that can be used for self-localization and interactive object identification of static objects stored within 3D environment models. In this paper we present a new method for interactive tracking of various types of movable objects. The state of fixed movable objects, like doors, can be recognized by comparing the distance between sensor data and a 3D model. For the identification and model-based tracking of free movable objects, like chairs, we have developed an algorithm that is similar to human perception, based on shape and color comparisons to trained objects. Further, using a common face detection algorithm, our assistant system informs the user of the presence of people, and enables the localization of a real person based on interactive tracking of virtual models of humans.
Zero–One Laws for Connectivity in Random Key Graphs

The random key graph is a random graph naturally associated with the random key predistribution scheme introduced by Eschenauer and Gligor in the context of wireless sensor networks (WSNs). For this class of random graphs, we establish a new version of a conjectured zero-one law for graph connectivity as the number of nodes becomes unboundedly large. The results reported here complement and strengthen recent work on this conjecture by Blackburn and Gerke. In particular, the results are given under conditions which are more realistic for applications to WSNs.
An adaptive H/sup /spl infin// controller design for bank-to-turn missiles using ridge Gaussian neural networks

A new autopilot design for bank-to-turn (BTT) missiles is presented. In the design of autopilot, a ridge Gaussian neural network with local learning capability and fewer tuning parameters than Gaussian neural networks is proposed to model the controlled nonlinear systems. We prove that the proposed ridge Gaussian neural network, which can be a universal approximator, equals the expansions of rotated and scaled Gaussian functions. Although ridge Gaussian neural networks can approximate the nonlinear and complex systems accurately, the small approximation errors may affect the tracking performance significantly. Therefore, by employing the H/sup /spl infin// control theory, it is easy to attenuate the effects of the approximation errors of the ridge Gaussian neural networks to a prescribed level. Computer simulation results confirm the effectiveness of the proposed ridge Gaussian neural networks-based autopilot with H/sup /spl infin// stabilization.
Chrysopogon zizanioides aqueous extract mediated synthesis, characterization of crystalline silver and gold nanoparticles for biomedical applications

The exploitation of various plant materials for the biosynthesis of nanoparticles is considered a green technology as it does not involve any harmful chemicals. The aim of this study was to develop a simple biological method for the synthesis of silver and gold nanoparticles using Chrysopogon zizanioides. To exploit various plant materials for the biosynthesis of nanoparticles was considered a green technology. An aqueous leaf extract of C. zizanioides was used to synthesize silver and gold nanoparticles by the bioreduction of silver nitrate (AgNO3) and chloroauric acid (HAuCl4) respectively. Water-soluble organics present in the plant materials were mainly responsible for reducing silver or gold ions to nanosized Ag or Au particles. The synthesized silver and gold nanoparticles were characterized by ultraviolet (UV)-visible spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDAX), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) analysis. The kinetics decline reactions of aqueous silver/gold ion with the C. zizanioides crude extract were determined by UV-visible spectroscopy. SEM analysis showed that aqueous gold ions, when exposed to the extract were reduced and resulted in the biosynthesis of gold nanoparticles in the size range 20–50 nm. This eco-friendly approach for the synthesis of nanoparticles is simple, can be scaled up for large-scale production with powerful bioactivity as demonstrated by the synthesized silver nanoparticles. The synthesized nanoparticles can have clinical use as antibacterial, antioxidant, as well as cytotoxic agents and can be used for biomedical applications.
Combine CRF and MMSEG to Boost Chinese Word Segmentation in Social Media

In this paper, we propose a joint algorithm for the word segmentation on Chinese social media. Previous work mainly focus on word segmentation for plain Chinese text, in order to develop a Chinese social media processing tool, we need to take the main features of social media into account, whose grammatical structure is not rigorous, and the tendency of using colloquial and Internet terms makes the existing Chinese-processing tools inefficient to obtain good performance on social media. In our approach, we combine CRF and MMSEG algorithm and extend features of traditional CRF algorithm to train the model for word segmentation, We use Internet lexicon in order to improve the performance of our model on Chinese social media. Our experimental result on Sina Weibo shows that our approach outperforms the state-of-the-art model.
A tool for home-based rehabilitation allowing for clinical evaluation in a visual markerless scenario

This work deals with the design of an interactive monitoring tool for home-based physical rehabilitation. The software platform includes a video processing stage and the exercise performance evaluation. Image features are extracted by a Kinect v2 sensor and elaborated to return the exercises score. Furthermore the tool provides to physiotherapists a quantitative exercise evaluation of subject's performances. The proposed tool for home rehabilitation has been tested on 5 subjects and 5 different exercises and results are presented. In particular both exercises and relative evaluation indexes were selected by specialists in neurorehabilitation.