Miracle-dz/UniFAR-FTUs huggingface dataset:
CPW fed elliptical zeroth order resonant antenna for WiMax applications

In this paper, a new compact coplanar waveguide (CPW) fed elliptical zeroth order resonant (ZOR) antenna based on Composite Right/Left Handed (CRLH) transmission line is proposed. The performance of the antenna is designed and simulated by Ansoft HFSS. The reflection coefficient, gain and antenna efficiency of the proposed antenna are observed to be - 38.3108dB, 2.1930dB and 77.286% respectively at the zeroth mode of 4.89GHz. In this paper an effort is made to circumvent the narrow bandwidth problem and fabrication complexity as exhibited by popular microstrip based ZOR antennas with vias. It is observed that an extended bandwidth of about 6.6% at the zeroth mode is obtained. Since the proposed antenna is implemented by using a combination of open ended spiral and anti-spiral inductors using CPW feeding technique, so vias are not required which enables the fabrication of this antenna simple and easy. The proposed antenna also has an additional advantage of being a very low profile one exhibiting an omni-directional radiation pattern typical of monopole antennas. Hence the antenna is suitable for modern wired and wireless systems and also suitable for Worldwide interoperability for Microwave Access (WiMax) applications (IEEE 802.11a standard).
Voice activity detection using the phase vector in microphone array

If desired speech source is located at different position from interference, it is possible to exploit spatial selectivity for reliable speech detection. In this paper, we propose a voice activity detector (VAD) for the microphone array system, using spatial information obtained by the eigendecomposition of multi-channel correlation matrix. We use the phase vector as a measure for VAD, which is derived from the principal eigenvector. Voice activity is detected by the log likelihood ratio test under the assumption that phase vectors of speech absent and present signals have complex Gaussian distributions. The proposed algo-rithm is tested with the real data recorded by 8 microphones and the result shows that it performs better than GSC-based method.
Effects of Anti-VEGF Treatment Duration on Tumor Growth, Tumor Regrowth, and Treatment Efficacy

Purpose: Inhibition of the vascular endothelial growth factor (VEGF) axis is the basis of all currently approved antiangiogenic therapies. In preclinical models, anti-VEGF blocking antibodies have shown broad efficacy that is dependent on both tumor context and treatment duration. We aimed to characterize this activity and to evaluate the effects of discontinuation of treatment on the dynamics of tumor regrowth. Experimental Design: We evaluated the effects of anti-VEGF treatment on tumor growth and survival in 30 xenograft models and in genetic mouse models of cancer. Histologic analysis was used to evaluate the effects of treatment on tumor vasculature. We used a variety of treatment regimens to allow analysis of the effects of treatment duration and cessation on growth rate, survival, and vascular density. Results: Preclinical tumor models were characterized for their varied dependence on VEGF, thereby defining models for testing other agents that may complement or augment anti-VEGF therapy. We also found that longer exposure to anti-VEGF monoclonal antibodies delayed tumor growth and extended survival in established tumors from both cell transplants and genetic tumor models and prevented regrowth of a subset of residual tumors following cytoablative therapy. Discontinuation of anti-VEGF in established tumors resulted in regrowth at a rate slower than that in control-treated animals, with no evidence of accelerated tumor growth or rebound. However, more rapid regrowth was observed following discontinuation of certain chemotherapies. Concurrent administration of anti-VEGF seemed to normalize these accelerated growth rates. Conclusions: In diverse preclinical models, continuous VEGF suppression provides maximal benefit as a single agent, combined with chemotherapy, or as maintenance therapy once chemotherapy has been stopped. Clin Cancer Res; 16(15); 3887–900. ©2010 AACR.
Socialization, Social Support, and Social Cognitive Theory: An Examination of the Graduate Teaching Assistant.

OF DISSERTATION SOCIALIZATION, SOCIAL SUPPORT, AND SOCIAL COGNITIVE THEORY: AN EXAMINATION OF THE GRADUATE TEACHING ASSISTANT Graduate teaching assistants (GTAs) face the unknown as they negotiate their multiple roles and identities within the graduate school and classroom setting as teachers, students, and researchers. The purpose of this study is to identify the role that institutionalized socialization, social support, and behavioral observation and modeling play for GTAs as they navigate their way through the organizational socialization process. Interviews with twenty two current and former graduate teaching assistants from a Communication department at a large, southeastern university (GSU) were conducted and analyzed. Findings indicate that institutionalized socialization, which exists at both the graduate school and departmental level, serves to both reduce and create uncertainty and anxiety for GTAs based on messages communicated and also serves the purpose of relationship formation. In examining the social support aspect, findings indicate that the socialization process is facilitated for GTAs through House‘s (1981) four categories of emotional, instrumental, informational, and appraisal support. Finally, behavioral observation aids in the socialization process for GTAs. Observation is used by GTAs to obtain information about teaching behaviors, specifically what they should and should not do in the GSU classroom. Observation also highlighted both positive and negative aspects of the departmental culture and helped GTAs to understand how things work in the department. Implications, limitations, ideas for what can be done to improve the process for GTAs, and areas for future research are also discussed.
Dependency Parsing with Transformed Feature

Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the un-indexed strings and alleviate the feature sparse problem. The model transforms the extracted features to transformed features via applying a feature weight matrix, which consists of similarities between the feature strings. Since the matrix is usually rank-deficient because of similar feature strings, it would influence the strength of constraints. However, it is proven that the duplicate transformed features do not degrade the optimization algorithm: the margin infused relaxed algorithm. Moreover, this problem can be alleviated by reducing the number of the nearest transformed features of a feature. In addition, to further improve the parsing accuracy, a fusion parser is introduced to integrate transformed and original features. Our experiments verify that both transform-based and fusion parser improve the parsing accuracy compared to the corresponding feature-based parser.
Counterfactual Regret Minimization for Decentralized Planning

Regret minimization is an effective technique for almost surely producing Nash equilibrium policies in coordination games in the strategic form. Decentralized POMDPs offer a realistic model for sequential coordination problems, but they yield doubly exponential sized games in the strategic form. Recently, counterfactual regret has offered a way to decompose total regret along a (extensive form) game tree into components that can be individually controlled, such that minimizing all of them minimizes the total regret as well. However, a straightforward extension of this decomposition in decentralized POMDPs leads to a complexity exponential in both the joint action and joint observation spaces. We present a more tractable approach to regret minimization where the regret is decomposed along the nodes of agents’ policy trees that yields a complexity exponential only in the joint observation space. We present an algorithm, REMIT, to minimize regret by this decomposition and prove that it converges to a Nash equilibrium policy in the limit. We also use a stronger convergence criterion with REMIT, such that if this criterion is met then the algorithm must output a Nash equilibrium policy in finite time. We found empirically that in every benchmark problems that we tested, this criterion was indeed met and (near) optimal Nash equilibrium policies were achieved.
Evaluating IPv6 Connectivity for IEEE 802.15.4 and Bluetooth Low Energy

IPv6 is seen as a key building block for the Internet of Things (IoT). In this work, IEEE 802.15. 4 and Bluetooth Low Energy (BLE) protocols are evaluated with respect to service ratio, delay, and energy efficiency under IPv6 traffic. While the performance is terms of delay is similar between the two technologies, BLE outperforms 802.15. 4 in terms of service ratio and energy efficiency. Header compression increases all performance indicators but requires a shared context to be set up and managed. IPv6 multicast is also investigated in combination with data link layer broadcast and sequential unicast. Finally, the impact of IPv6 connection establishment and maintenance is evaluated. This is particularly relevant for BLE devices using privacy features. It is shown that the procedures for registering IPv6 addresses and updating contexts affect the delay significantly, but only at very low traffic intensity.
Low Power Arithmetic Circuits in Feedthrough Dynamic CMOS Logic

This paper presents the design of low power high performance arithmetic circuits using the feedthrough logic (FTL) [1] concept. Low power FTL arithmetic circuits provide for smaller propagation time delay (2.6 times), lower energy consumption (31%), and similar combined delay, power consumption, and active area product, when compared with the standard CMOS technologies.
Regenerative Potential of Cardiosphere-Derived Cells Expanded From Percutaneous Endomyocardial Biopsy Specimens

Background— Ex vivo expansion of resident cardiac stem cells, followed by delivery to the heart, may favor regeneration and functional improvement. Methods and Results— Percutaneous endomyocardial biopsy specimens grown in primary culture developed multicellular clusters known as cardiospheres, which were plated to yield cardiosphere-derived cells (CDCs). CDCs from human biopsy specimens and from comparable porcine samples were examined in vitro for biophysical and cytochemical evidence of cardiogenic differentiation. In addition, human CDCs were injected into the border zone of acute myocardial infarcts in immunodeficient mice. Biopsy specimens from 69 of 70 patients yielded cardiosphere-forming cells. Cardiospheres and CDCs expressed antigenic characteristics of stem cells at each stage of processing, as well as proteins vital for cardiac contractile and electrical function. Human and porcine CDCs cocultured with neonatal rat ventricular myocytes exhibited biophysical signatures characteristic of myocytes, including calcium transients synchronous with those of neighboring myocytes. Human CDCs injected into the border zone of myocardial infarcts engrafted and migrated into the infarct zone. After 20 days, the percentage of viable myocardium within the infarct zone was greater in the CDC-treated group than in the fibroblast-treated control group; likewise, left ventricular ejection fraction was higher in the CDC-treated group. Conclusions— A method is presented for the isolation of adult human stem cells from endomyocardial biopsy specimens. CDCs are cardiogenic in vitro; they promote cardiac regeneration and improve heart function in a mouse infarct model, which provides motivation for further development for therapeutic applications in patients.
Dynamic-average Characteristics of Late Wave of Auditory Evoked Potentials for Synaptic Malfunction Rat Model

The aim of this study is to investigate dynamic characteristics of late wave of auditory evoked potentials (AEPs) in synaptic malfunction rat model. Two dynamic characteristics relative to cognitive function were investigated which are dynamic latency and dynamic amplitude of P1. Synaptic malfunction model was made by Sprague-Dawley rats via microinjecting beta-amyloid protein (A-beta) into hippocampal CA1 area of rat. Dynamic AEPs with high background noise were recorded for both model and normal rats in experiments. Dynamic late wave were taken from dynamic AEPs using third-order correlation and wavelet technology. The dynamic-average latency and the dynamic-average amplitude of P1 in a small time window (5s) were performed as dynamic index in this study, which remain most of dynamic information because the average window was very small. Then dynamic-average latency and the dynamic-average latency of P1 were compared between synaptic malfunction rat and normal group. The results of this study have demonstrated that: (1) the dynamic-average latency of P1 for model rats prolonged remarkably than control (P<0.01, alpha =0.05); (2) the dynamic-average amplitude of P1 for model rats increased remarkably than control(P<0.01,alpha =0.05). The conclusion is that dynamic-average latency and dynamic-average amplitude in the synaptic malfunction rats model has obvious difference with normal group
Multiple Imputation of Missing Values: Update

This article describes a substantial update to mvis, which brings it more closely in line with the feature set of S. van Buuren and C. G. M. Oudshoorn's implementation of the MICE system in R and S-PLUS (for details, see http://www.multiple-imputation.com). To make a clear distinction from mvis, the principal program of the new Stata release is called ice. I will give details of how to use the new features and a practical illustrative example using real data. All the facilities of mvis are retained by ice. Some improvements to micombine for computing estimates from multiply imputed datasets are also described.
On Recognizing Abnormal Human Behaviours by Data Stream Mining with Misclassified Recalls

Human activity recognition (HAR) has been a popular research topic, because of its importance in security and healthcare contributing to aging societies. One of the emerging applications of HAR is to monitor needy people such as elders, patients of disabled, or undergoing physical rehabilitation, using sensing technology. In this paper, an improved version of Very Fast Decision Tree (VFDT) is proposed which makes use of misclassified results for post-learning. Specifically, a new technique namely Misclassified Recall (MR) which is a post-processing step for relearning a new concept, is formulated. In HAR, most misclassified instances are those belonging to ambiguous movements. For examples, squatting involves actions in between standing and sitting, falling straight down is a sequence of standing, possibly body tiling or curling, bending legs, squatting and crashing down on the floor; and there may be totally new (unseen) actions beyond the training instances when it comes to classifying "abnormal" human behaviours. Think about the extreme postures of how a person collapses and free falling from height. Experiments using wearable sensing data for multi-class HAR is used, to test the efficacy of the new methodology VFDT+MR, in comparison to a classical data stream mining algorithm VFDT alone.
Recognizing a voice from its model

Investigates a potential solution to the "large-population" speaker identification problem by characterizing a voice by the entailments in two different kinds of models. These entailments are found in the representational models of neuro-linguistic programming (NLP) and in the model of the mechanics of the voice as revealed by the continuous wavelet transform (CWT). Results to date have been obtained from examining samples in the TIMIT database and human subjects. Local features correlated with individual speakers for selected vowel sounds have been found in the CWT space. Features of NLP representation systems have also been found and are compared with voice features for speakers whose NLP representation systems are known a priori. Gaussian mixture models are used to calculate probability density functions from the local feature distributions. This speaker identification strategy combines three elements of novelty. First, it exploits the fact that the 2D CWT of a 1D signal can be interpreted as an image, and can thus use feature extraction techniques first developed for image processing. Second, voice waveforms are systematically studied to identify features that are attributed to the speaker's mental representation. Third, the reliability of the identification is strengthened by combining entailments from these two completely different aspects of the speaker's identity: the mechanical aspects of the speaker's vocal tract and the pattern of representation.
Quasirandom load balancing

We propose a simple distributed algorithm for balancing indivisible tokens on graphs. The algorithm is completely deterministic, though it tries to imitate (and enhance) a random algorithm by keeping the accumulated rounding errors as small as possible. Our new algorithm approximates the idealized process (where the tokens are divisible) on important network topologies surprisingly closely. On d-dimensional torus graphs with n nodes it deviates from the idealized process only by an additive constant. In contrast to that, the randomized rounding approach of Friedrich and Sauerwald [8] can deviate up to Ω(polylog n) and the deterministic algorithm of Rabani, Sinclair and Wanka [23] has a deviation of Ω(n1/d). This makes our quasirandom algorithm the first known algorithm for this setting which is optimal both in time and achieved smoothness. We further show that also on the hypercube our algorithm has a smaller deviation from the idealized process than the previous algorithms. To prove these results, we derive several combinatorial and probabilistic results that we believe to be of independent interest. In particular, we show that first-passage probabilities of a random walk on a path with arbitrary weights can be expressed as a convolution of independent geometric probability distributions.
CardioGenBase: A Literature Based Multi-Omics Database for Major Cardiovascular Diseases

Cardiovascular diseases (CVDs) account for high morbidity and mortality worldwide. Both, genetic and epigenetic factors are involved in the enumeration of various cardiovascular diseases. In recent years, a vast amount of multi-omics data are accumulated in the field of cardiovascular research, yet the understanding of key mechanistic aspects of CVDs remain uncovered. Hence, a comprehensive online resource tool is required to comprehend previous research findings and to draw novel methodology for understanding disease pathophysiology. Here, we have developed a literature-based database, CardioGenBase, collecting gene-disease association from Pubmed and MEDLINE. The database covers major cardiovascular diseases such as cerebrovascular disease, coronary artery disease (CAD), hypertensive heart disease, inflammatory heart disease, ischemic heart disease and rheumatic heart disease. It contains ~1,500 cardiovascular disease genes from ~2,4000 research articles. For each gene, literature evidence, ontology, pathways, single nucleotide polymorphism, protein-protein interaction network, normal gene expression, protein expressions in various body fluids and tissues are provided. In addition, tools like gene-disease association finder and gene expression finder are made available for the users with figures, tables, maps and venn diagram to fit their needs. To our knowledge, CardioGenBase is the only database to provide gene-disease association for above mentioned major cardiovascular diseases in a single portal. CardioGenBase is a vital online resource to support genome-wide analysis, genetic, epigenetic and pharmacological studies.
Mechanisms of Cardioprotection by Volatile Anesthetics

A RAPIDLY growing body of evidence indicates that volatile anesthetics protect myocardium against reversible and irreversible ischemic injury. Identifying the mechanisms by which volatile agents mediate these antiischemic actions is the subject of intense research. This objective has been difficult to accomplish because volatile anesthetics also profoundly affect cardiovascular function. Volatile agents reduce arterial and coronary perfusion pressure, cause dose-related depression of myocardial contractility, produce coronary vasodilation, affect electrophysiologic function, and modify autonomic nervous system activity to varying degrees. Therefore, the antiischemic effects of volatile anesthetics may be mediated, at least in part, by favorable alterations in myocardial oxygen supply–demand relations, preservation of energy-dependent cellular functions, and increased coronary blood flow. However, it seems unlikely that changes in myocardial metabolism and coronary perfusion caused by volatile anesthetics are solely responsible for protection against ischemic damage. Instead, several endogenous signal transduction pathways, acting through the adenosine triphosphate (ATP)–sensitive potassium (KATP) channel and involving the generation of reactive oxygen species (ROS), have been implicated in mediating the antiischemic actions of volatile anesthetics. The experimental and clinical findings documenting the phenomenon of volatile anesthetic preconditioning against ischemic injury of myocardium are evaluated. Recent findings in vitro and in vivo that seek to define the intracellular mechanisms responsible for these beneficial actions are also summarized.
Development of a microcontroller-based, photovoltaic maximum power point tracking control system

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to maximize the photovoltaic array output power, irrespective of the temperature and irradiation conditions and of the load electrical characteristics. A new MPPT system has been developed, consisting of a buck-type DC/DC converter, which is controlled by a microcontroller-based unit. The main difference between the method used in the proposed MPPT system and other techniques used in the past is that the PV array output power is used to directly control the DC/DC converter, thus reducing the complexity of the system. The resulting system has high-efficiency, lower-cost and can be easily modified to handle more energy sources (e.g., wind-generators). The experimental results show that the use of the proposed MPPT control increases the PV output power by as much as 15% compared to the case where the DC/DC converter duty cycle is set such that the PV array produces the maximum power at 1 kW/m/sup 2/ and 25/spl deg/C.
Adaptive mutations in the genomes of enterovirus 71 strains following infection of mouse cells expressing human P-selectin glycoprotein ligand-1

We recently identified human P-selectin glycoprotein ligand-1 (PSGL-1) as a functional enterovirus 71 (EV71) receptor and demonstrated PSGL-1-dependent replication for some EV71 strains in human leukocytes. Here, we report that four out of five PSGL-1-binding strains of EV71 replicated poorly in mouse L929 cells stably expressing human PSGL-1 (L-PSGL-1 cells). Therefore, we compared the replication kinetics and entire genomic sequence of five original EV71 strains and the corresponding EV71 variants (EV71-LPS), which were propagated once in L-PSGL-1 cells. Direct sequence comparison of the entire genome of the original EV71 strains and EV71-LPS variants identified several possible adaptive mutations during the course of replication in L-PSGL-1 cells, including a putative determinant of the adaptive phenotype in L-PSGL-1 cells at VP2-149. The results suggest that an adaptive mutation, along with a PSGL-1-binding phenotype, may facilitate efficient PSGL-1-dependent replication of the EV71 strains in L-PSGL-1 cells.