Miracle-dz/UniFAR-FTUs huggingface dataset:
RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint

The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods.
Voltage unbalance vulnerability areas in power systems supplying high speed railway

High speed railway loads fed by the three phase power system represent an important source of unbalance perturbation in the grid. The degree of voltage and current unbalances depends on the train motion, load condition and power system supply configuration. The present paper deals with the identification procedure of a vulnerability area in which the voltage unbalance presents values that exceed the standard limits. A case study referred to the 63 buses CIGRE network analyzed in the paper gives rise to interesting comments and discussion.
A Model-Trust-Region Framework for Symmetric Generalized Eigenvalue Problems

A general inner-outer iteration for computing extreme eigenpairs of symmetric/positive-definite matrix pencils is proposed. The principle of the method is to produce a sequence of p-dimensional bases {Xk} that converge to a minimizer of a generalized Rayleigh quotient. The role of the inner iteration is to produce an “update” vector by (approximately) minimizing a quadratic model of the Rayleigh quotient within a neighbourhood of Xk where the model is trusted. The role of the outer iteration is to make the best out of the proposed update vector combined with previously-obtained information; it consists of a Rayleigh-Ritz process that minimizes the exact Rayleigh quotient in a low-dimensional subspace. This general scheme leaves a lot of leeway for choosing the algorithmic details of the inner and outer iterations. The global and local convergence of the scheme are analytically studied under weak assumptions on these algorithmic choices. Moreover, numerous experiments are carried out to explore the influence of the algorithmic choices on the performance of the scheme. In particular, the question of balancing the computational effort between the inner and outer iterations is investigated.
A Collaborative Filtering Recommendation Algorithm Improved by Trustworthiness

Recommender systems based on collaborative filtering have been well studied in both industry and academia fields. However, traditional collaborative filtering methods are typically in a low accuracy and lack of resistance towards attacks such as non-reliable information. To this end, in this paper, we propose a collaborative filtering recommendation algorithm improved by trustworthiness. Specifically, first we employ a content based method to identify a set of users with similar interests. Then, a trust model is applied as a scoring function, and higher ranked neighbors are selected as the evidence of prediction. Besides, we conducted extensive experiments using Netflix dataset, and the results show that our method is more efficient compared with others.
Adaptive sink mobility in event-driven multi-hop wireless sensor networks

Optimizing energy consumption in wireless sensor networks is of paramount importance. There is a recent trend to deal with this problem by introducing mobile elements (sensors or sink nodes) in the network. The majority of these approaches assume time-driven scenarios and/or single-hop communication between participating nodes. However, there are several real-life applications for which an event-based and multi-hop operation is more appropriate. In this paper we propose to adaptively move the sink node inside the covered region, according to the evolution of current events, so as to minimize the energy consumption incurred by the multi-hop transmission of the event-related data. Both analytical and simulation results are given for two optimization strategies: minimizing the overall energy consumption, and minimizing the maximum load on a specific sensor respectively. We show that by adaptively moving the sink, significant power saving can be achieved, prolonging the lifetime of the network.
Differential expression of protein tyrosine kinases in the cortical and medullary thymic epithelial cell lines.

Expression of protein tyrosine kinase (PTK) was evaluated and compared between cortical and medullary thymic epithelial cell (TEC) lines, TEC 14C18 and TEC1C6, respectively. Reverse transcription-polymerase chain reaction (RT-PCR) methods using degenerate primers for conserved sequence in catalytic domain of PTK revealed the expression of 13 kinds of PTKs in these cell lines. These PTKs included 6 receptor and 7 non-receptor types. In the next step, we compared the intensity of mRNA expression level of these kinases between cortical and medullary TEC lines. Tyrosine kinases of receptor type were differentially expressed between cortical and medullary TEC lines; e.g., mRNA expression of flg was observed more intensively in the cortical TEC line than in the medullary one, while mRNA expression of bek, met and sky was vice versa. On the other hand, expression of non-receptor tyrosine kinases, including four JAK-tyk family members, are comparable in both lines. These results suggested that these PTKs, especially of receptor type, might play an important role in the development of the thymic microenvironment.
Effects of Hybrid and Synthetic Social Gaze in Avatar-Mediated Interactions

Human gaze is a crucial element in social interactions and therefore an important topic for social Augmented, Mixed, and Virtual Reality (AR, MR, VR) applications. In this paper we systematically compare four modes of gaze transmission: (1) natural gaze, (2) hybrid gaze, which combines natural gaze transmission with a social gaze model, (3) synthesized gaze, which combines a random gaze transmission with a social gaze model, and (4) purely random gaze. Investigating dyadic interactions, results show a linear trend for the perception of virtual rapport, trust, and interpersonal attraction, suggesting that these measures increase with higher naturalness and social adequateness of the transmission mode. We further investigated the perception of realism as well as the resulting gaze behavior of the avatars and the human participants. We discuss these results and their implications.
Different Effects of Startling Acoustic Stimuli (SAS) on TMS-Induced Responses at Rest and during Sustained Voluntary Contraction

Previous studies have shown that a habituated startling acoustic stimulus (SAS) can cause a transient suppression of motor evoked potentials (MEPs) induced by transcranial magnetic stimulation (TMS) during light muscle contraction. However, it is still unknown whether this phenomenon persists when at rest or during a sustained voluntary contraction task. Therefore, the purpose of this study was to determine whether a conditioning SAS has different effects. TMS was delivered to the hot spot for the left biceps on 11 subjects at rest both with and without a conditioning SAS. Of the 11subjects, 9 also had TMS delivered during isometric flexion of the left elbow, also with and without a conditioning SAS. TMS-induced MEPs, TMS-induced force, and silent periods were used to determine the effect of conditioning SAS. Consistent with previous findings, TMS-induced MEPs were smaller with a conditioning SAS (0.49 ± 0.37 mV) as compared without the SAS (0.69 ± 0.52 mV) at rest. However, a conditioning SAS during the voluntary contraction tasks resulted in a significant shortening of the MEP silent period (187.22 ± 22.99 ms with SAS vs. 200.56 ± 29.71 ms without SAS) without any changes in the amplitude of the MEP (1.37 ± 0.9 mV with SAS V.S. 1.32 ± 0.92 mV without SAS) or the TMS-induced force (3.11 ± 2.03 N-m with SAS V.S. 3.62 ± 1.33 N-m without SAS). Our results provide novel evidence that a conditioning SAS has different effects on the excitability of the motor cortex when at rest or during sustained voluntary contractions.
AN ANALYTICAL MODEL FOR PREDICTION OF CONTROLLED RELEASE FROM BULK BIODEGRADING POLYMER MICROSPHERES

Objective: A convenient numerical model has been developed to predict release profile of different types of agents from bulk biodegrading polymer microspheres, including magnitude methods are less accurate than analytical methods. Usually, this study used analytical solutions for the model and compared the analytical results with numerical solution and experimental data. Methods: The objective drug controlled release profiles were modeled based on a four-phase pattern. Then, a specific formulation was considered based on Fick’s second law. After calculating various parameters, the equations were solved using an analytical method. Results: Comparison results showed that analytical solution can reproduce experimental behavior of controlled release systems with a higher accuracy. Conclusion: Although in previous work, drug release profile from a polymer matrix composed of poly lactic-co-glycolic acid was predicted using readily attainable parameters and representing tunable matrix properties by a numerical method, the proposed analytical method can give more accurate results compared to the numerical method.
Evolution of Reinforcement Learning in Uncertain Environments: A Simple Explanation for Complex Foraging Behaviors

Reinforcement learning is a fundamental process by which organisms learn to achieve goals from their interactions with the environment. Using evolutionary computation techniques we evolve (near-)optimal neuronal learning rules in a simple neural network model of reinforcement learning in bumblebees foraging for nectar. The resulting neural networks exhibit efficient reinforcement learning, allowing the bees to respond rapidly to changes in reward contingencies. The evolved synaptic plasticity dynamics give rise to varying exploration/exploitation levels and to the well-documented choice strategies of risk aversion and probability matching. Additionally, risk aversion is shown to emerge even when bees are evolved in a completely risk-less environment. In contrast to existing theories in economics and game theory, risk-averse behavior is shown to be a direct consequence of (near-)optimal reinforcement learning, without requiring additional assumptions such as the existence of a nonlinear subjective utility function for rewards. Our results are corroborated by a rigorous mathematical analysis, and their robustness in real-world situations is supported by experiments in a mobile robot. Thus we provide a biologically founded, parsimonious, and novel explanation for risk aversion and probability matching.
Determination of surface properties and elastic constants of FCC metals: a comparison among different EAM potentials in thin film and bulk scale

Three independent elastic constants C11, C12, and C44 were calculated and compared using available potentials of eight different metals with FCC crystal structure; Gold, Silver, Copper, Nickel, Platinum, Palladium, Aluminum and Lead. In order to calculate the elastic constants, the second derivative of the energy density of each system was calculated with respect to different directions of strains. Each set of the elastic constants of the metals in bulk scale was compared with experimental results, and the average relative error was for each was calculated and compared with other available potentials. Then, using the Voigt-Reuss-Hill method, approximated values for Young and shear moduli and Poisson’s ratio of the FCC metals in the bulk scale were found for each potential. Furthermore, to observe the surface effects on the metals in nanoscale, surface elastic constants of the thin films of the metals have been calculated. In the study of the thin films of materials in nanoscale, the number of surface atoms is considerable compared to all atoms of the object. This leads to an increase in the surface effects, which influence the elastic properties. By considering this fact and employing related definitions and equations, the properties of the thin films of the metals were calculated, and the surface effects for different crystallographic directions were compared. Subsequently, in some cases, comparisons among characteristics of the metals in the thin film and bulk material were made.
Identification and characterization of a novel extracellular matrix protein nephronectin that is associated with integrin α8β1 in the embryonic kidney

The epithelial–mesenchymal interactions required for kidney organogenesis are disrupted in mice lacking the integrin α8β1. None of this integrin's known ligands, however, appears to account for this phenotype. To identify a more relevant ligand, a soluble integrin α8β1 heterodimer fused to alkaline phosphatase (AP) has been used to probe blots and cDNA libraries. In newborn mouse kidney extracts, α8β1-AP detects a novel ligand of 70–90 kD. This protein, named nephronectin, is an extracellular matrix protein with five EGF-like repeats, a mucin region containing a RGD sequence, and a COOH-terminal MAM domain. Integrin α8β1 and several additional RGD-binding integrins bind nephronectin. Nephronectin mRNA is expressed in the ureteric bud epithelium, whereas α8β1 is expressed in the metanephric mesenchyme. Nephronectin is localized in the extracellular matrix in the same distribution as the ligand detected by α8β1-AP and forms a complex with α8β1 in vivo. Thus, these results strongly suggest that nephronectin is a relevant ligand mediating α8β1 function in the kidney. Nephronectin is expressed at numerous sites outside the kidney, so it may also have wider roles in development. The approaches used here should be generally useful for characterizing the interactions of novel extracellular matrix proteins identified through genomic sequencing projects.
A systematic comparison between on-line and off-line methods for signature verification with hidden Markov models

This paper presents an extensive investigation of various HMM-based techniques for signature verification Different feature extraction methods and HMM topologies are compared in order to obtain an optimized high performance signature verification system. Furthermore, this paper may be the first systematic comparison of online and off-line methods for signature verification using exactly the same database, and leading to the surprising result that the difference in performance for both approaches is relatively small.
Performance of Rapid Diagnostic Tests for Plasmodium ovale Malaria in Japanese Travellers

Background: Rapid diagnostic tests (RDTs) are used widely in the diagnosis of malaria. Although the effectiveness of RDTs for malaria has been described in many previous studies, the low performance of RDT particularly for Plasmodium ovale malaria in traveller has rarely been reported. Methods: This was a retrospective cohort study conducted on Japanese travellers diagnosed with malaria at the National Center for Global Health and Medicine between January 2004 and June 2013. The diagnosis of malaria was confirmed by microscopic examination, RDT, and polymerase chain reaction in all patients. The RDTs used in our study were Binax NOW Malaria (Binax Inc., Scarborough, Maine, USA) (BN) and SD Malaria Antigen Pf/Pan (Standard Diagnostics Inc., Korea) (SDMA). We compared the sensitivity of the RDTs to P. ovale malaria and Plasmodium vivax malaria. Results: A total of 153 cases of malaria were observed, 113 of which were found among Japanese travellers. Nine patients with P. ovale malaria and 17 patients with P. vivax malaria undergoing RDTs were evaluated. The overall sensitivity of RDTs for P. ovale malaria and P. vivax malaria was 22.2% and 94.1%, respectively (P < 0.001). The sensitivity of SDMA for P. ovale malaria and P. vivax malaria was 50% and 100%, respectively. The sensitivity of BN for P. vivax malaria was 90.0%, but it was ineffective in detecting the cases of P. ovale malaria. Conclusions: The sensitivity of RDTs was not high enough to diagnose P. ovale malaria in our study. In order not to overlook P. ovale malaria, therefore, microscopic examination is indispensable.
Laser extraction of a defibrillator lead from a persistent left superior vena cava.

A 60-year-old man underwent attempted cardiac resynchronization with defibrillator therapy utilizing a left-sided approach. A persistent left-sided superior vena cava (SVC) was identified and a dual-coil defibrillator lead (Sprint Fidelis; Medtronic) and atrial lead were deployed via this route ( Figure 1A ). No left ventricular (LV) branches of …
Super-resolution of 3D MR images and its application to brain segmentation

This paper presents super resolution (SR) of 3D MR images which is effective for brain segmentation as practical application. Brain segmentation is one of important tasks to analyze brain morphometry. An accurate brain segmentation helps improve accuracy of post-processing. The segmentation is affected by the resolution of 3D MR images. In particular, the resolution in slice-select direction is much lower than the in-plane direction in some type of 3D MR images (e.g. T2-weighted images and proton density images). Therefore, we apply a learning-based SR method using sparse representation and self-similarity for generating high-resolution (HR) in slice-select direction to be same resolution in in-plane direction. With the visualized evaluation, it can be seen that the segmentation accuracy in SR results are improved by reducing partial volume effect. With the quantitative evaluation, one can confirm that the DICE value of SR results are higher than conventional interpolation method.
Synthesis of aluminum ethylphenylphosphinate flame retardant and its application in epoxy resin

A novel flame retardant additive, aluminum ethylphenylphosphinate (AEPP), was synthesized from diethyl phenylphosphonite and aluminum chloride hexahydrate, and characterized by FTIR, 1H NMR, and 31P NMR. AEPP was added into diglycidyl ether of bisphenol A epoxy resin (EP) cured by bisphenol A‐formaldehyde novolac resin. The flame retardancy of the cured EP was investigated by limited oxygen index, UL 94 test, and cone calorimeter test. The results revealed that the EP composite containing 15% AEPP had a limited oxygen index value of 28.2% with a UL 94 V‐0 rating. The incorporation of AEPP effectively decreased the peak heat release rate and the total heat release in cone calorimeter test analysis. Scanning electron microscopy results showed that the introduction of AEPP benefited to the formation of a smooth and continuous char layer during combustion of the flame retarded EP. The thermogravimetric analysis results indicated that the incorporation of AEPP promoted the initial decomposition of EP matrix, but AEPP/EP composites had a higher char yield at high temperatures. Moreover, the flexural properties of the flame retarded EP composites were studied.
Cortico–Cortical Connections of Primary Sensory Areas and Associated Symptoms in Migraine

Abstract Migraine is a recurring, episodic neurological disorder characterized by headache, nausea, vomiting, and sensory disturbances. These events are thought to arise from the activation and sensitization of neurons along the trigemino–vascular pathway. From animal studies, it is known that thalamocortical projections play an important role in the transmission of nociceptive signals from the meninges to the cortex. However, little is currently known about the potential involvement of cortico–cortical feedback projections from higher-order multisensory areas and/or feedforward projections from principle primary sensory areas or subcortical structures. In a large cohort of human migraine patients (N = 40) and matched healthy control subjects (N = 40), we used resting-state intrinsic functional connectivity to examine the cortical networks associated with the three main sensory perceptual modalities of vision, audition, and somatosensation. Specifically, we sought to explore the complexity of the sensory networks as they converge and become functionally coupled in multimodal systems. We also compared self-reported retrospective migraine symptoms in the same patients, examining the prevalence of sensory symptoms across the different phases of the migraine cycle. Our results show widespread and persistent disturbances in the perceptions of multiple sensory modalities. Consistent with this observation, we discovered that primary sensory areas maintain local functional connectivity but express impaired long-range connections to higher-order association areas (including regions of the default mode and salience network). We speculate that cortico–cortical interactions are necessary for the integration of information within and across the sensory modalities and, thus, could play an important role in the initiation of migraine and/or the development of its associated symptoms.
Single Photon Counting Performance and Noise Analysis of CMOS SPAD-Based Image Sensors

SPAD-based solid state CMOS image sensors utilising analogue integrators have attained deep sub-electron read noise (DSERN) permitting single photon counting (SPC) imaging. A new method is proposed to determine the read noise in DSERN image sensors by evaluating the peak separation and width (PSW) of single photon peaks in a photon counting histogram (PCH). The technique is used to identify and analyse cumulative noise in analogue integrating SPC SPAD-based pixels. The DSERN of our SPAD image sensor is exploited to confirm recent multi-photon threshold quanta image sensor (QIS) theory. Finally, various single and multiple photon spatio-temporal oversampling techniques are reviewed.
Balanced allocations and double hashing

With double hashing, for an item x, one generates two hash values f(x) and g(x), and then uses combinations (f(x) +ig(x)) mod n for i=0,1,2,. to generate multiple hash values from the initial two. We show that the performance difference between double hashing and fully random hashing appears negligible in the standard balanced allocation paradigm, where each item is placed in the least loaded of d choices, as well as several related variants. We perform an empirical study, and consider multiple theoretical approaches. While several techniques can be used to show asymptotic results for the maximum load, we demonstrate how fluid limit methods explain why the behavior of double hashing and fully random hashing are essentially indistinguishable in this context.