Miracle-dz/UniFAR-FTUs huggingface dataset:
A Discrete Queue-Based Model for Soft-Decision Demodulated Correlated Fading Channels

A discrete fading channel (DFC) consisting of a binary modulated time-correlated Rayleigh fading channel used in conjunction with coherent soft-decision demodulation of resolution q is considered. The capacity of the binary input 2^q-ary output DFC, which can be explicitly expressed in terms of a non-binary noise discrete channel with stationary ergodic $2^q$-ary noise, is evaluated in terms of q and the fading parameters. It is observed that considerable capacity gains can be achieved due to the channel's statistical memory and the use of as few as 2 bits for soft-decision over interleaving the channel (to render it memoryless) and hard-decision demodulation (q=1). The DFC is next fitted by a recently introduced analytically tractable queue-based (QB) Markovian noise model. The QB parameters are estimated via an iterative procedure that minimizes the Kullback-Leibler divergence rate between the DFC and QB noise sources. Modeling results, measured in terms of both channel noise correlation function and capacity reveal a good agreement between the two channels for a broad range of fading conditions.
Steady state electromagnetic analysis of the forward problem for Magneto-acoustic tomography

Magneto-acoustic tomography is a new EIT technology, which combines the traditional Electrical impedance tomography and Ultrasound Imaging, can provide high-spatial-resolution information. This paper expounds the steady state electromagnetic forward problem based on reciprocity theorem for Magneto-acoustic tomography. The FEM numerical simulation with a two-dimensional imaging model demonstrates the reasonability of the forward problem, improves the theory of Magneto-acoustic tomography, and also provides the theoretical foundation for the impedance reconstruction algorithm of Magneto-acoustic tomography. Furthermore, it does research on the impact of electrode placement on sensitivity of measured signal. This paper will give useful reference to further research on experiment setup of Magneto-acoustic tomography.
A PCA-based vehicle classification system in wireless sensor networks

We designed, implemented, and evaluated a compact signal processing system on a Berkeley mote for vehicle classification via acoustic characteristics. The main components of this system include a sound sampler, FFT converter, an energy-based adaptive CFAR detector, and a classifier. We chose principal component analysis (PCA) as the primary classifier because of its high accuracy, good scalability, and low resource requirements. This system enables a Berkeley mote to detect a passing vehicle and to decide its type. Only the result of the identification analysis is reported to sink nodes. With this proof-of-concept implementation, we explored limits of system design on a mote. Using a testbed based on this system, we compared classification quality, energy consumption, and latency of the PCA classifier with two typical classifiers in both centralized and distributed signal processing scenarios. Briefly, we found that the PCA yields better classification quality but has slightly lower energy efficiency than the others. By extensive simulations, we studied the dependency of PCA on signal quality and efficiency issues of signal processing in WSNs
Parent perceived challenges to treatment utilization in a publicly funded early intensive behavioral intervention program for children with autism spectrum disorder

Background: In recent years, the delivery of early intensive behavioral intervention (EIBI) for children with autism spectrum disorder (ASD) in the United States has significantly changed. More children with ASD than ever before are eligible to use publicly funded EIBI. Yet, the challenges to large-scale implementation of EIBI remain unclear. Specific Aims: We examined parent perceived challenges to treatment utilization, predictors of increased challenges to treatment utilization, and parent recommendations for increasing utilization in a statewide EIBI program. Method: Using a cross-sectional design, we surveyed parents of children with ASD receiving EIBI through South Carolina’s Pervasive Developmental Disorder Program (N = 145). To examine the contributions of parent demographic characteristics, parent social support, and child challenging behaviors to perceived challenges to utilization, we used multiple linear regression. Parent recommendations were collected using a single open-ended question. Findings: The most frequently endorsed challenges included the child’s school schedule (62.1%) and the child being overburdened with other treatment demands (65.2%). Greater child challenging behaviors were associated with a greater degree of perceived challenges, and social support was associated with a lesser degree of perceived challenges. Discussion: Parents perceived various challenges to utilization, and child and family characteristics may increase the risk for experiencing challenges to utilization. As the delivery of EIBI continues to evolve in the United States and elsewhere, these findings have implications for policy, programming, and future research.
Brief Monocular Deprivation as an Assay of Short-Term Visual Sensory Plasticity in Schizophrenia – “The Binocular Effect”

Background: Visual sensory processing deficits are consistently observed in schizophrenia, with clear amplitude reduction of the visual evoked potential (VEP) during the initial 50–150 ms of processing. Similar deficits are seen in unaffected first-degree relatives and drug-naïve first-episode patients, pointing to these deficits as potential endophenotypic markers. Schizophrenia is also associated with deficits in neural plasticity, implicating dysfunction of both glutamatergic and GABAergic systems. Here, we sought to understand the intersection of these two domains, asking whether short-term plasticity during early visual processing is specifically affected in schizophrenia. Methods: Brief periods of monocular deprivation (MD) induce relatively rapid changes in the amplitude of the early VEP – i.e., short-term plasticity. Twenty patients and 20 non-psychiatric controls participated. VEPs were recorded during binocular viewing, and were compared to the sum of VEP responses during brief monocular viewing periods (i.e., Left-eye + Right-eye viewing). Results: Under monocular conditions, neurotypical controls exhibited an effect that patients failed to demonstrate. That is, the amplitude of the summed monocular VEPs was robustly greater than the amplitude elicited binocularly during the initial sensory processing period. In patients, this “binocular effect” was absent. Limitations: Patients were all medicated. Ideally, this study would also include first-episode unmedicated patients. Conclusion: These results suggest that short-term compensatory mechanisms that allow healthy individuals to generate robust VEPs in the context of MD are not effectively activated in patients with schizophrenia. This simple assay may provide a useful biomarker of short-term plasticity in the psychotic disorders and a target endophenotype for therapeutic interventions.
Study on Gray Numerical Model of Air Pollution in Wuan City

In connection with the uncertainty problem of pollutants diffusing in the atmosphere of Wuan city, we monitor and put forward a new conception about air ground pollution belt, and get two-dimensional finite difference equation of air pollution. Meanwhile dispersion coefficient and wind speed are considered as grey parameters. One grey numerical quality model of air pollution is built according to grey theory and applies to the air pollution diffusing system of Wuan city, and simulates SO2 and PM10 during heating times and unheating times. The result shows the gray numerical model is suitable for application. Meantime, according to the simulation result, put forward the control measures of air pollution in Wuan city.
Activated T Cell Exosomes Promote Tumor Invasion via Fas Signaling Pathway

Activated T cells release bioactive Fas ligand (FasL) in exosomes, which subsequently induce self-apoptosis of T cells. However, their potential effects on cell apoptosis in tumors are still unknown. In this study, we purified exosomes expressing FasL from activated CD8+ T cell from OT-I mice and found that activated T cell exosomes had little effect on apoptosis and proliferation of tumor cells but promoted the invasion of B16 and 3LL cancer cells in vitro via the Fas/FasL pathway. Activated T cell exosomes increased the amount of cellular FLICE inhibitory proteins and subsequently activated the ERK and NF-κB pathways, which subsequently increased MMP9 expression in the B16 murine melanoma cells. In a tumor-invasive model in vivo, we observed that the activated T cell exosomes promoted the migration of B16 tumor cells to lung. Interestingly, pretreatment with FasL mAb significantly reduced the migration of B16 tumor cells to lung. Furthermore, CD8 and FasL double-positive exosomes from tumor mice, but not normal mice, also increased the expression of MMP9 and promoted the invasive ability of B16 murine melanoma and 3LL lung cancer cells. In conclusion, our results indicate that activated T cell exosomes promote melanoma and lung cancer cell metastasis by increasing the expression of MMP9 via Fas signaling, revealing a new mechanism of tumor immune escape.
CUPID - Communication Pattern Informed Duty Cycling in Sensor Networks

Now that sensor networks are gradually deployed in commercial settings, they must live up to many expectations, particularly offering both years of unattended operation and low-delay event reporting. However, experiences from real-world trials have shown that decent trade-offs between these two conflicting goals are hard to find. In this paper, we show how staggered wake-ups achieve this. We call this low-delay and low-power duty cycle management scheme CUPID because its parameterization is based on the expected communication patterns in the network, duty-cycle and latency requirements. We show by simulations and real-world experiments with more than 150 nodes that our scheme significantly reduces the packet delay for low-duty cycle settings, especially in large networks.
Three classes of inhibitory amino acid terminals in the cochlear nucleus of the guinea pig

Electron microscopic postembedding immunocytochemistry was used to analyze and assess the synaptic distribution of glycine (GLY) and γ‐amino butyric acid (GABA) immunoreactivities in the guinea pig cochlear nucleus (CN). Three classes of endings were identified containing immunolabeling for glycine, GABA, or both glycine and GABA (GLY/GABA). All classes were similar in that the terminals contained pleomorphic vesicles and formed symmetric synapses with their postsynaptic targets. A fourth class, which labeled with neither antibody, contained round vesicles and formed asymmetric synapses. Glycine endings predominated in the ventral CN, while GLY/GABA endings were prevalent in the dorsal CN. GABA endings were the least common and smallest in size. Glycine, GLY/GABA, and GABA endings differed in their proportions and patterns of distribution on the different classes of projection neurons in the CN, including spherical bushy, type I stellate/multipolar, and octopus cells in the ventral CN and fusiform cells in the dorsal CN. The vast majority of anatomically‐defined, putative inhibitory endings contain GLY, GABA, or both, suggesting that most of the inhibition in the cochlear nucleus is mediated by these three cytochemically and, probably, functionally distinct classes of endings. The results of this study also suggest that a large proportion of the GABA available for inhibition in the CN coexists in terminals with glycine. © 1996 Wiley‐Liss, Inc.
Fusion of Thermal and Visual Images for efficient Face Recognition using Gabor Filter

Face recognition from visual images is difficult task due to illumination problem and in thermal imaging the main problem is of glasses. The solution of both these problem is data fusion of thermal and visual images. This paper presents the implementation of Human face recognition system using data fusion of visual and thermal images. Gabor filtering technique which extracts facial features is used in the proposed face recognition. To our knowledge, this is the first visual and thermal data fusion recognition system which utilizes Gabor filter. Paper also discusses the performance improvement of face recognition along with issues of memory requirements.
Modeling and quantification of substrate noise induced by interconnects in SOCs

Interconnects carrying high-frequency signals are of the most important sources of substrate noise. This paper computes the amount of the interconnect-induced substrate noise. We develop a substrate extraction tool based on the Finite Difference Method and combine the extracted output model with accurate interconnect models. Through simulation of the complete substrate-interconnect model, we investigate the impacts of frequency and several interconnect geometrical parameters on the amount of the substrate noise.
Performance Analysis of Image Classification Algorithm Based on Feature Fusing Technique Model

Unclassified region deceases the efficiency and performance of PLSA and FLDA. The proper selection of feature sub set reduced the unclassified region of PLSA and FLDA. Now a day‟s binary classification are widely used in image classification. The mapping of data one space to another space creates diversity of outlier and noise and generate unclassified region for image classification. For the reduction of unclassified region we used radial basis function for sampling of feature and reduce the noise and outlier for feature space of data and increase the performance and efficiency of image classification. Our proposed method optimized the feature selection process and finally sends data to FLDA classifier for classification of data. Here we used fisher classifier. As a classifier FLDA suffering two problems (1) how to choose optimal feature sub set input and (2) how to set best kernel parameters. These problems influence the performance and accuracy of FLDA. Now the pre-sampling of feature reduced the feature selection process of FLDA for image classification.
“I’m Not Fragile. I’m Not Limited”: Career Aspirations of Youth With Perinatally Acquired HIV

Although children born with perinatally acquired HIV (PHIV) are now living into adulthood, little is known about their transition into the workforce and the ways they develop career aspirations. In this phenomenological study, 35 youth with PHIV (mean age 20.7) completed semistructured interviews regarding their career aspirations which were transcribed and coded for emergent themes using grounded theory. Approximately half of the participants were employed at the time of the interview. Sixteen participants aspired to work in helping professions. Others sought employment in the arts or business sector. Participants indicated that parents/guardians and medical providers were generally supportive of their career interests. Providers and social workers often helped them find jobs and construct resumes. Thirteen participants indicated that their HIV status had little impact on their career aspirations. Others believed HIV-related challenges related to transmission, physical difficulties, and emotional turmoil limited their ability to pursue certain careers. Several felt inspired to fight against HIV-related stigma/discrimination. It is important to encourage youth with PHIV to prepare for their future by routinely holding conversations regarding their career goals.
Ultrasensitivity in Phosphorylation-Dephosphorylation Cycles with Little Substrate

Cellular decision-making is driven by dynamic behaviours, such as the preparations for sunrise enabled by circadian rhythms and the choice of cell fates enabled by positive feedback. Such behaviours are often built upon ultrasensitive responses where a linear change in input generates a sigmoidal change in output. Phosphorylation-dephosphorylation cycles are one means to generate ultrasensitivity. Using bioinformatics, we show that in vivo levels of kinases and phosphatases frequently exceed the levels of their corresponding substrates in budding yeast. This result is in contrast to the conditions often required by zero-order ultrasensitivity, perhaps the most well known means for how such cycles become ultrasensitive. We therefore introduce a mechanism to generate ultrasensitivity when numbers of enzymes are higher than numbers of substrates. Our model combines distributive and non-distributive actions of the enzymes with two-stage binding and concerted allosteric transitions of the substrate. We use analytical and numerical methods to calculate the Hill number of the response. For a substrate with phosphosites, we find an upper bound of the Hill number of , and so even systems with a single phosphosite can be ultrasensitive. Two-stage binding, where an enzyme must first bind to a binding site on the substrate before it can access the substrate's phosphosites, allows the enzymes to sequester the substrate. Such sequestration combined with competition for each phosphosite provides an intuitive explanation for the sigmoidal shifts in levels of phosphorylated substrate. Additionally, we find cases for which the response is not monotonic, but shows instead a peak at intermediate levels of input. Given its generality, we expect the mechanism described by our model to often underlay decision-making circuits in eukaryotic cells.
Camouflage, detection and identification of moving targets

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation—detection, identification and capture—in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely ‘break’ camouflage.
Optimal Configuration of IEEE 802.11e EDCA with Variable Packet Length

This paper addresses the optimal configuration in IEEE 802.11e enhanced distributed channel access (EDCA) wireless local area networks (WLANs). Most of the previous studies assumed that all access categories (ACs) have the same packet length. However, this assumption is not true in most practical cases. Generally, different applications have different traffic characteristics including packet length. In this paper, we study how to achieve the maximal protocol capacity of EDCA by properly choosing the protocol parameters. We prove that the maximal protocol capacity can be approximately achieved by setting the network at an optimal operating point. Furthermore, we propose a parameter configuration scheme to achieve efficient channel utilization and proportional fairness among different ACs. The proposed scheme is validated through analysis and extensive simulation.
Splitting methods for monotone operators and bifunctions

The purpose of this article is to investigate fixed point problems of a nonexpansive mapping, solutions of quasi variational inclusion problem, and solutions of a generalized equilibrium problem based on a splitting method. Our convergence theorems are established under mild restrictions imposed on the control sequences. The main results improve and extend the recent corresponding results. c ©2016 All rights reserved.
Early Coronary Angiography and Survival After Out-of-Hospital Cardiac Arrest

Background—Although out-of-hospital cardiac arrest is common because of acute myocardial infarction, it is unknown whether early coronary angiography is associated with improved survival in these patients. Methods and Results—Using data from the Cardiac Arrest Registry to Enhance Survival (CARES), we identified 4029 adult patients admitted to 374 hospitals after successful resuscitation from out-of-hospital cardiac arrest because of ventricular fibrillation, pulseless ventricular tachycardia, or unknown shockable rhythm between January 2010 and December 2013. Early coronary angiography (occurring within one calendar day of cardiac arrest) was performed in 1953 (48.5%) patients, of whom 1253 (64.2%) received coronary revascularization. Patients who underwent early coronary angiography were younger (59.9 versus 62.0 years); more likely to be men (78.1% versus 64.3%), have a witnessed arrest (84.6% versus 77.4%), and have ST-segment–elevation myocardial infarction (32.7% versus 7.9%); and less likely to have known cardiovascular disease (22.8% versus 35.0%), diabetes mellitus (11.0% versus 17.0%), and renal disease (1.8% versus 5.8%; P<0.01 for all comparisons). In analysis of 1312 propensity score–matched pairs, early coronary angiography was associated with higher odds of survival to discharge (odds ratio 1.52 [95% confidence interval 1.28–1.80]; P<0.0001) and survival with favorable neurological outcome (odds ratio 1.47 [95% confidence interval 1.25–1.71]; P<0.0001). Further adjustment for coronary revascularization in our models significantly attenuated both odds ratios, suggesting that revascularization was a key mediator of the survival benefit. Conclusions—Among initial survivors of out-of-hospital cardiac arrest caused by VF or pulseless VT, we found early coronary angiography was associated with higher odds of survival to discharge and favorable neurological outcome.
Plane Detection in Point Cloud Data

Plane detection is a prerequisite to a wide variety of vision tasks. RANdomSAmple Consensus (RANSAC) algorithm is widely used for plane detectionin point cloud data. Minimum description length (MDL) principle is used todeal with several competing hypothesis. This paper presents a new approachto the plane detection by integrating RANSAC and MDL. The method couldavoid detecting wrong planes due to the complex geometry of the 3D data.The paper tests the performance of proposed method on both synthetic andreal data.
Development of a vertical optical coupler using a slanted etching of InP/InGaAsP waveguide

We demonstrate a simple and efficient optical coupler for vertical coupling between optical fibers and InP-based waveguides using a slant-etched mirror. The angle of the etched mirror can be controlled by using an aluminum jig with a beveled surface inserted under the substrate during RIE (reactive ion etching) of InP/InGaAsP. The offchip coupler is fabricated simultaneously with a high-mesa waveguide with only one etching process. Coupling loss of 7.3 dB between the tapered single-mode fibers is obtained within the wavelength of 1530– 1570 nm.