Miracle-dz/UniFAR-FTUs huggingface dataset:
NASH: Navigation-Assisted Seamless Handover Scheme for Smart Car in Ultradense Networks

In the vehicular network, the smart car provides various network services for the passenger by the user equipment (UE). However, the services might be interrupted since the handover procedure of the UE is performed frequently. The existing handover decision schemes in cellular networks are mostly based on received signal strength to make the handover decision. However, these schemes suffer from a ping-pong effect and, as a result, perform unnecessary handovers incurring extra signaling overhead and packet loss, which is even more exaggerated in the ultradense environment. The failure probability of the handover procedure will increase when the velocity of the car is fast. Therefore, in this paper, we propose a navigation-assisted seamless handover (NASH) scheme for reducing unnecessary handovers and the ping-pong effect. NASH uses the multiple input multiple output technique to perform the bicasting scheme and then it utilizes coordination multipoint and carrier aggregation mechanisms in the handover procedure to avoid the packet loss problem and enhance throughput. Moreover, a dynamic time to trigger mechanism is proposed according to the velocity of the car. The simulation results show that the proposed scheme has a better performance in terms of handover latency, packet loss, network throughput, handover failure probability, and the number of unnecessary handovers.
A Power-Efficient Accelerator for Convolutional Neural Networks

Convolutional neural networks(CNNs) have been widely applied in various applications. However, the computation-intensive convolutional layers and memory-intensive fully connected layers have brought many challenges to the implementation of CNN on embedded platforms. To overcome this problem, this work proposes a power-efficient accelerator for CNNs, and different methods are applied to optimize the convolutional layers and fully connected layers. For the convolutional layer, the accelerator first rearranges the input features into matrix on-the-fly when storing them to the on-chip buffers. Thus the computation of convolutional layer can be completed through matrix multiplication. For the fully connected layer, the batch-based method is used to reduce the required memory bandwidth, which also can be completed through matrix multiplication. Then a two-layer pipelined computation method for matrix multiplication is proposed to increase the throughput. As a case study, we implement a widely used CNN model, LeNet-5, on an embedded device. It can achieve a peak performance of 34.48 GOP/s and the power efficiency with the value of 19.45 GOP/s/W under 100MHz clock frequency which outperforms previous approaches.
Cloud Computing Fitness for E-Government Implementation: Importance-Performance Analysis

The means through which governments deliver services and the way they operate may be considerably enhanced through cloud computing. It can help to address e-government implementation challenges and revolutionize e-government systems in terms of cost savings and the professional use of resources. The aim of this paper is to analyze the importance and performance of the factors that influence the fitness of cloud computing for e-government implementation. This paper integrates the task technology fit model with the diffusion of innovation theory to address this issue. Yemeni public institutions were identified as sources for data collection and 292 information technology employees participated as sample respondents for a structured questionnaire. Security, compatibility, relative advantage, and tasks were the variables found to affect the fitness of cloud computing for e-government activities. However, no impact was seen from the standpoints of trialability and complexity of the technology. In terms of assessing the fitness of cloud computing for e-government services, a greater understanding among policy formulators was sought through the importance-performance matrix analysis (IPMA). The results of IPMA can help identifying areas for strategic focus to assess cloud computing as an alternative technology to implement e-government services.
ACID: Association Correction for Imbalanced Data in GWAS

Genome-wide association study (GWAS) has been widely witnessed as a powerful tool for revealing suspicious loci from various diseases. However, real world GWAS tasks always suffer from the data imbalance problem of sufficient control samples and limited case samples. This imbalance issue can cause serious biases to the result and thus leads to losses of significance for true causal markers. To tackle this problem, we proposed a computational framework to perform association correction for imbalanced data (ACID) that could potentially improve the performance of GWAS under the imbalance condition. ACID is inspired by the imbalance learning theory but is particularly modified to address the task of association discovery from sequential genomic data. Simulation studies demonstrate ACID can dramatically improve the power of traditional GWAS method on the dataset with severe imbalances. We further applied ACID to two imbalanced datasets (gastric cancer and bladder cancer) to conduct genome wide association analysis. Experimental results indicate that our method has better abilities in identifying suspicious loci than the regression approach and shows consistencies with existing discoveries.
Estimation system of construction equipment from field image by combination learning of its parts

This paper describes the development of a robust object recognition system which combines object's parts, for automatic construction equipment tracking camera on unmanned construction site. Although a construction equipment operator monitors manually and operates construction equipment through captured surveillance camera video in the worksite of unmanned construction, they need an automatic tracking system for construction equipment in order to work efficiently. Since there is difficulty of automation such as some parts of construction equipment are not captured in the video because of construction works, we have developed a robust system which recognizes construction equipment using combination of their parts. Before we start making whole system, we developed object recognition algorithm for construction equipment. The object: construction equipment, recognition algorithm discussed in this paper is developed based on estimating its type by combining its parts found in an image. This system has three features to realize the process: part extraction step, part recognition step and part combination step. The part extraction step extracts object candidates including parts of construction equipment from an input image. In the part recognition step, they are recognized and labeled. The part combination step combines the labeled data and estimates construction equipment's type using neural networks. Experimental results show that the system which combines parts of construction equipment is able to estimate its type even if some parts of it are hidden. We also describe its improvement in terms of the processing time.
Microstructural Evolution in Clay‐Based Ceramics II: Ternary and Quaternary Mixtures of Clay, Flux, and Quartz Filler

The complex microstructural evolution in mixtures of kaolinite clay, quartz, nepheline syenite, and soda–lime–silica (SLS) glass has been revisited. Detailed descriptions of reactions leading to dense whiteware bodies backed by semi-quantitative X-ray diffraction analysis reveal that ternary mixtures containing nepheline syenite differ from those containing SLS glass, as new crystalline phases develop inside and at the interfaces among SLS glass particles and decomposed clay and quartz. In SLS glass-fluxed mixtures, tridymite formation was hindered and cristobalite formed at ≥750°C followed by wollastonite at ≥800°C. Albite and plagioclase formed from interaction between clay and molten SLS glass above 800°C. Wollastonite was not present ≥1100°C, leaving only cristobalite in the surrounding regions. Quartz partially dissolves at temperatures ≥1000°C after interacting with molten SLS glass. In quaternary mixtures containing 6.25 wt% SLS glass and 17.25 wt% nepheline syenite fluxes, formation of types II and III secondary mullite was more pronounced than in the fully SLS glass-fluxed mixture. The more fluid liquid from nepheline syenite enhances the growth kinetics of mullite. The body fired at the optimum firing temperature (1100°C) has a microstructure containing primary type I and secondary types II and III mullites, remnant cristobalite, plagioclase, and partially dissolved quartz embedded in the glassy phase. Providing a roadmap for microstructural design in clay-based systems may have significant commercial impact in the emerging technology of use of waste materials in clay-based ceramics.
Target Motion Compensation by Means of Adjustable Heavy-Ion Beam Slow Extraction: Simulations

Abstract Purpose: The treatment of moving tumors with scanned ion beam therapy requires motion mitigation. The purpose of this work was to investigate a technique using adjustable beam slow extraction time of the synchrotron in carbon ion radiation therapy with pencil beam scanning to effectively reduce the sensitivity against target motion. Materials and Methods: Assuming a realistic beam delivery system, the authors performed computer simulations to evaluate the new method comprehensively. When a scan point is exposed to different durations of the adjustable beam slow extraction for a constant particle number within a beam spill, the irradiation time at the point differs. An averaging effect may result in nearly homogeneous dose coverage over the target volume when the nominal scan point can be scanned several times with the elongated beam extraction time. In fact, a combination consisting of adjustable beam slow extraction with beam rescanning and increase in the overlap of the adjacent spot beams may .
SURFACEACOUSTICWAVE-DRIVENACTIVEPLASMONICSBASEDON DYNAMIC PATTERNINGOFNANOPARTICLESINMICROFLUIDIC CHANNELS

Thenanoparticles redistribution ina microfluidic channel through adynamic patterning process will locally change therefractive indexofthemediumaround the nanodisk arrays, aswellastheLSPR.Thedynamic patterning ofnanoparticles wasachieved byastanding surface acoustic wave(SSAW), fromwhichtheacoustic force generated andforce theparticles tothepressure nodes. TheSSAW wereformedthrough twoparallel interdigital transducers (IDTs) onaLiNbO3substrate, on whichthegoldnanodisk arrays werefabricated through a nanosphere lithography. A PDMS microchannel was aligned withtheIDTsandbonded withthesubstrate to coverthenanodisk arrays. A solution offluorescent polystyrene beads(diameter: 320nm)wasinjected into thechannel through apressure driven flow. WhenSSAW wason,theoriginal peak(X=694 nm)issplit into two peaks at)1=662 nmandX2=746 nm,respectively. } . ~~~~~~Laser Out
Dynamic popularity driven caching optimization at base station

Caching at base station (BS) has attracted significant research efforts for future wireless networks. Most existing works are based on the assumption of static content catalogue and stationary popularity distribution, which however is far away from the reality as recently reported in the literature. In this paper, we take the popularity dynamics into account, and study the caching policy at BS for a traffic model consisting of two categories of contents respectively with long and short lifespans. By modeling the two categories of contents with Independent Reference Model (IRM) and Shot Noise Model (SNM), we formulate a cache resource allocation problem to maximize the total cache hit ratio for both categories of contents, which gives rise to a hybrid proactive and reactive caching policy. We solve the problem numerically for general case and provide closed-form solutions for several special cases. Numerical and simulation results demonstrate remarkable performance gain of the proposed caching policy over non-hybrid caching polices.
Calibrating well-being, quality of life and common mental disorder items: psychometric epidemiology in public mental health research

Background The assessment of ‘general health and well-being’ in public mental health research stimulates debates around relative merits of questionnaire instruments and their items. Little evidence regarding alignment or differential advantages of instruments or items has appeared to date. Aims Population-based psychometric study of items employed in public mental health narratives. Method Multidimensional item response theory was applied to General Health Questionnaire (GHQ-12), Warwick-Edinburgh Mental Well-being Scale (WEMWBS) and EQ-5D items (Health Survey for England, 2010–2012; n = 19 290). Results A bifactor model provided the best account of the data and showed that the GHQ-12 and WEMWBS items assess mainly the same construct. Only one item of the EQ-5D showed relevant overlap with this dimension (anxiety/depression). Findings were corroborated by comparisons with alternative models and cross-validation analyses. Conclusions The consequences of this lack of differentiation (GHQ-12 v. WEMWBS) for mental health and well-being narratives deserves discussion to enrich debates on priorities in public mental health and its assessment.
Modulators of actin-myosin dissociation: basis for muscle type functional differences during fatigue

The muscle types present with variable fatigue tolerance, in part due to the myosin isoform expressed. However, the critical steps that define “fatigability” in vivo of fast vs. slow myosin isoforms, at the molecular level, are not yet fully understood. We examined the modulation of the ATP-induced myosin subfragment 1 (S1) dissociation from pyrene-actin by inorganic phosphate (Pi), pH, and temperature using a specially modified stopped-flow system that allowed fast kinetics measurements at physiological temperature. We contrasted the properties of rabbit psoas (fast) and bovine masseter (slow) myosins (obtained from samples collected from New Zealand rabbits and from a licensed abattoir, respectively, according to institutional and national ethics permits). To identify ATP cycling biochemical intermediates, we assessed ATP binding to a preequilibrated mixture of actomyosin and variable [ADP], pH (pH 7 vs. pH 6.2), and Pi (zero, 15, or 30 added mM Pi) in a range of temperatures (5 to 45°C). Temperature and pH variations had little, if any, effect on the ADP dissociation constant (KADP) for fast S1, but for slow S1, KADP was weakened with increasing temperature or low pH. In the absence of ADP, the dissociation constant for phosphate (KPi) was weakened with increasing temperature for fast S1. In the presence of ADP, myosin type differences were revealed at the apparent phosphate affinity, depending on pH and temperature. Overall, the newly revealed kinetic differences between myosin types could help explain the in vivo observed muscle type functional differences at rest and during fatigue.
Semantics-Based Analysis of Content Security Policy Deployment

Content Security Policy (CSP) is a recent W3C standard introduced to prevent and mitigate the impact of content injection vulnerabilities on websites. In this article, we introduce a formal semantics for the latest stable version of the standard, CSP Level 2. We then perform a systematic, large-scale analysis of the effectiveness of the current CSP deployment, using the formal semantics to substantiate our methodology and to assess the impact of the detected issues. We focus on four key aspects that affect the effectiveness of CSP: browser support, website adoption, correct configuration, and constant maintenance. Our analysis shows that browser support for CSP is largely satisfactory, with the exception of a few notable issues. However, there are several shortcomings relative to the other three aspects. CSP appears to have a rather limited deployment as yet and, more crucially, existing policies exhibit a number of weaknesses and misconfiguration errors. Moreover, content security policies are not regularly updated to ban insecure practices and remove unintended security violations. We argue that many of these problems can be fixed by better exploiting the monitoring facilities of CSP, while other issues deserve additional research, being more rooted into the CSP design.
Using Cell Aware Diagnostic Patterns to Improve Diagnosis Resolution for Cell Internal Defects

The industry is encountering an increasing number of front-end-of-line defects in the most advanced FinFET technology nodes due to extremely small feature size and complex manufacturing processes. Traditional diagnostic pattern generation based on stuck-at faults becomes less effective for these complex cell internal defects due to various reasons. In this work, we propose a new method to generate cell aware diagnostic patterns for cell internal defects based on accurate defect models extracted by analog simulation. Special UDFM faults covering all possible input combinations and all fault effect propagation scenarios can be used to maximize the diagnosis resolution. The enhanced diagnostic patterns can effectively detect and differentiate cell internal defects, and thus dramatically improve the diagnosis resolution. Experimental results for real silicon cases showed that the number of suspects can be reduced by 14.9X on the average. Furthermore, detailed analysis for extra failure data from cell aware diagnostic patterns provides valuable information for physical failure analysis.
Late N‐acetylcysteine treatment prevents the deficits induced in the offspring of dams exposed to an immune stress during gestation

Prenatal infection is a major stressful experience leading to enhanced susceptibility for mental illnesses in humans. We recently reported in rats, that oxidative stress and glutathione (GSH) shortage occurred in fetal male brain after lipopolysaccharide (LPS) to the dams and that these responses might be involved in the neurodevelopmental deficits observed in adolescent offspring. Furthermore, pretreatment with N‐acetylcysteine (NAC) before LPS avoided both delayed synaptic plasticity and mnesic performance deficits. Since NAC is one of the few medications permitted in pregnant women, this study evaluated the ability of NAC to serve as a protective therapy even after the LPS challenge. Pregnant rats received a single ip injection of E. coli LPS, two days before delivery, and were given NAC in their tap water after the LPS. GSH was evaluated at the time of its expected drop in the hippocampus of male fetuses, whereas long‐term potentiation (LTP) in the CA1 area of the hippocampus and spatial memory in the water‐maze were recorded in 28‐day‐old male offspring. Post‐treatment with NAC, four hours after the LPS challenge fully prevented the drop in the GSH hippocampal content. LTP, as well as spatial learning were completely protected. NAC administration at delivery also partially restored the LTP whereas post‐treatment two days later was inefficient. Another set of dams were supplemented with α‐tocopherol prior to LPS exposure, enhancing the α‐tocopherol levels in fetal hippocampus. This treatment did not prevent the LPS‐induced synaptic plasticity impairment. These results point to fetal hippocampal GSH as a major target of the detrimental effects of in utero LPS challenge. The therapeutic window of NAC extends up to birth, suggesting that this drug might be clinically useful even after an immuno‐inflammatory episode. © 2008 Wiley‐Liss, Inc.
Confocal endomicroscopy in diagnosis of intestinal chronic graft‐versus‐host disease

Graft‐versus‐host disease (GvHD) is a major complication of allogeneic stem cell transplantation. High‐resolution in vivo histology of the intestine by confocal endomicroscopy (CEM) detects acute GvHD (aGvHD) with high sensitivity. This pilot study aims to evaluate the diagnostic value of CEM for intestinal chronic GvHD (cGvHD). The study included 20 patients with gastrointestinal symptoms and confirmed cGvHD in other organs as well as 20 patients with clinically suspected acute GvHD for control. Confocal endomicroscopy was performed as gastroscopy followed by sigmoidoscopy after intravenous injection of fluorescein (10%) and topical application of acriflavine (0.05%). Histopathology from H&E‐stained biopsy samples throughout the intestinal tract complemented the survey. All histological features of intestinal cGvHD were predominantly mild to moderate. Stroma fibrosis detected by standard histology (16/20 patients) was not seen by CEM. Apoptosis assessed by histology in 12/20 patients was concordant with CEM (8/12 patients). Confocal endomicroscopy revealed esophageal manifestation of cGvHD in 3 patients. For each biopsy site, CEM correlated with intestinal histology (r = 0.64). Classical histology from intestinal biopsy samples taken under CEM monitoring confirmed the final diagnosis of cGvHD. The sensitivity of CEM with 40% in cGvHD was significantly lower compared to 70% in patients with aGvHD. Confocal endomicroscopy detected acute features of cGvHD and contributed to the diagnosis of esophageal cGvHD but failed to display stroma fibrosis in vivo. Although CEM represents a useful noninvasive tool in routine diagnostic of intestinal aGvHD, the method is not sufficient to fully establish the diagnosis of cGvHD within the intestinal tract. Confocal endomicroscopy allowed acquisition of targeted biopsies in patients suspected of having cGvHD.
Alternative processing routes for RAINBOW-type piezoelectric devices

In this work an alternative method for fabricating RAINBOW-type devices is proposed, in which the necessary shape and internal electrode structure are created during sintering. This has been achieved through combining Viscous Processing with silver (I) oxide doping of a soft doped PZT material. The small difference in sintering shrinkage between low and high silver content compositions has been utilised in laminated structures to produce as-fired curvatures. In addition, the necessary Unimorph structure has been created simultaneously, through engineering a conductive cermet phase. Results from the devices thus produced are shown in terms of sintered microstructure and actuation response.
Determination of the end of the positioning phase using support vector machine

In many positioning control systems, the end of the positioning phase must be determined correctly in order to initiate the start of the next task. A simple way of determining the end of the positioning phase is to wait for several sampling periods in order to confirm that the output does not exceed the error bound. This makes the unnecessary wait inevitable. This paper proposes a method to determine the end of the positioning phase using a support vector machine (SVM). The effectiveness of the proposed method is verified by performing experiment.