Miracle-dz/UniFAR-FTUs huggingface dataset:
General Capacity Region for the Fully Connected Three-Node Packet Erasure Network

This paper studies the capacity region when three nodes {1, 2,3} communicate with each other by sending packets through unreliable wireless medium. For each time slot, with some probabilities a packet sent by node i may be received by both of the other nodes j and k; received only by node j (or node k); or received by neither node. Interference is avoided by enforcing that at most one node can transmit in each time slot. We assume that node i can always reach node j, possibly with the help of the third node k, for any i ≠ j pairs (thus the term fully connected). One notable example of this model is any CSMA-based Wi-Fi network with three nodes within the hearing range of each other. We consider the most general traffic demands possible in this setting. Namely, there are six private-information flows with rates (R1→2, R1→3, R2→1, R2→3, R3→1, R3→2), respectively, and three common-information flows with rates (R1→23, R2→31, R3→12), respectively. We characterize the 9-dimensional Shannon capacity region within a gap that is inversely proportional to the packet size (bits). The gap can be attributed to exchanging reception status (ACK/NACK) and can be further reduced to zero if we allow such feedbacks to be transmitted via a separate control channel. For normal-sized packets, say 12000 bits, our results effectively characterize the capacity region for many important scenarios, e.g., wireless access-point networks with client-to-client cooperative communications, and wireless two-way relay networks with packet-level coding and processing. Technical contributions of this paper include a new converse for many-to-many network communications and a new capacity-approaching scheme based on simple linear network coding operations.
A modular approach to adaptive structures

A remarkable property of nastic, shape changing plants is their complete fusion between actuators and structure. This is achieved by combining a large number of cells whose geometry, internal pressures and material properties are optimized for a given set of target shapes and stiffness requirements. An advantage of such a fusion is that cell walls are prestressed by cell pressures which increases, decreases the overall structural stiffness, weight. Inspired by the nastic movement of plants, Pagitz et al (2012 Bioinspir. Biomim. 7) published a novel concept for pressure actuated cellular structures. This article extends previous work by introducing a modular approach to adaptive structures. An algorithm that breaks down any continuous target shapes into a small number of standardized modules is presented. Furthermore it is shown how cytoskeletons within each cell enhance the properties of adaptive modules. An adaptive passenger seat and an aircrafts leading, trailing edge is used to demonstrate the potential of a modular approach.
The CYP19 RS4646 Polymorphism IS Related to the Prognosis of Stage I–II and Operable Stage III Breast Cancer

Purpose Aromatase, encoded by the CYP19 gene, catalyzes the final step of the conversion of androgens to estrogens. Given the critical role of CYP19 in estrogen synthesis, the potential influence of CYP19 rs4646 polymorphism on breast cancer survival, deserves further study. Methods Genotyping for CYP19 rs4646 variants was performed on 406 Chinese women with stage I–II and operable stage III breast cancer. Associations were evaluated between CYP19 rs4646 genotypes and disease-free survival (DFS). Results In premenopausal patients, women who are homozygous for the minor allele (AA) have a longer DFS compared with those carrying the major allele (CC or AC) (87 months versus 48.7 months; Hazard ratio (HR) = 0.56, 95 % CI = 0.318-0.985, P = 0.041). These differences were further demonstrated by a multivariate analysis (HR = 0.456, 95 % CI = 0.249-0.836, P = 0.011). Conversely, the same variant (AA) was estimated to be associated with a poorer DFS in postmenopausal women (AA versus AC or CC: 13.7 months versus 56.3 months; HR = 2.758, 95 % CI = 1.432-5.313, P = 0.002). Furthermore, the differences were confirmed by the COX proportional hazards model (HR = 2.983, 95% CI =1.494-5.955, P = 0.002). Conclusions The present study indicates that CYP19 rs4646 polymorphism is related to DFS in early breast cancer and that the prognosis index of the homozygous for the minor allele (AA) may depend on menopause status. The findings are novel, if confirmed, rs4646 genotypes may provide useful information for routine management in breast cancer.
Optimal PID Controller Design Using Krill Herd Algorithm for Frequency Stabilizing in an Isolated Wind-Diesel System

The main purpose of this paper is to design an optimal PID controller for frequency stabilization in an isolated wind-diesel power system. Optimal tuning of PID controller, formulated as an optimization problem and solved using Krill Herd (KH) algorithm. In order to prove the performance of proposed method, simulation carried out in four cases, step change in load of diesel side, step change in wind speed, random changing of the diesel side load, and random changing of the wind speed. Also, performance indices like overshoot, undershoot, settling time, ITAE and ISTSE are calculated and compared with Bee Colony (BC) algorithm. Results show that the proposed method is very robust and effective.
Offline Signature Verification using Euclidian Distance

Signature authentication is the most widely used method of verifying a person’s identity. The texture and topological features are the static features of a signature image. Baseline slant angle, aspect ratio, normalized area, center of gravity of the whole signature image and the slope of the line joining the center of gravities of two halves of a signature image are used as the texture and topological features of the signature. The system is initially trained using a set of original signatures obtained from individuals whose signatures have to be authenticated by the system. The mean values and standard deviations of all the original signature features are computed. This mean signature features acts as the template for verification against a claimed test signature. Euclidian distance in the feature space between the claimed signature and the template serves as a measure of similarity between the two. If this distance is less than a pre-defined threshold, the test signature is verified to be that of the original signature otherwise detected as a forgery. The system gives the result to classify original and forgery signature with accuracy up to 100%. Keywords— Signature verification, Euclidian distance, Signature recognition, Feature extraction, Biometric.
The impact of image quality on the performance of face recognition

The performance of a face recognition system depends on the quality of both test and reference images participating in the face comparison process. In a forensic evaluation case involving face recognition, we do not have any control over the quality of the trace (image captured by a CCTV at a crime scene) and it is usually of very low quality. However, forensic investigators have some control over the quality of suspects reference images. In this paper, we investigate if it is useful to modify the quality of the reference (usually, good quality mug shot) images in order to achieve better recognition performance using a view based face recognition system. We found that approximately matching non-frontal pose between test and reference images can greatly improve recognition performance. Moreover, it is the relative difference in pose between the test and reference image that determines the extent of influence that other quality parameters like illumination, noise, motion blur, and resolution have on the face recognition performance.
Regulating Executive Pay: Using the Tax Code to Influence Chief Executive Officer Compensation

This study explores corporate responses to 1993 legislation that capped the corporate tax deductibility of top management compensation not qualified as “performance‐based. ” Our analysis suggests that the cap may have created a focal point for salary compensation but had little effect on total compensation levels or growth rates at firms likely to be affected by the limit. There is little evidence that the policy significantly increased the performance sensitivity of chief executive officer (CEO) pay at affected firms. We conclude that corporate pay decisions have been relatively insulated from this policy intervention.
Retrieval of similar chess positions

We address the problem of retrieving chess game positions similar to a given query position from a collection of archived chess games. We investigate this problem from an information retrieval (IR) perspective. The advantage of our proposed IR-based approach is that it allows using the standard inverted organization of stored chess positions, leading to an efficient retrieval. Moreover, in contrast to retrieving exactly identical board positions, the IR-based approach is able to provide approximate search functionality. In order to define the similarity between two chess board positions, we encode each game state with a textual representation. This textual encoding is designed to represent the position, reachability and the connectivity between chess pieces. Due to the absence of a standard IR dataset that can be used for this search task, a new evaluation benchmark dataset was constructed comprising of documents (chess positions) from a freely available chess game archive. Experiments conducted on this dataset demonstrate that our proposed method of similarity computation, which takes into account a combination of the mobility and the connectivities between the chess pieces, performs well on the search task, achieving MAP and nDCG values of 0:4233 and 0:6922 respectively.
Docking Studies and Anti-inflammatory Activity of β-Hydroxy-β-arylpropanoic Acids

The article describes a two-step synthesis of diastereomeric 3-hydroxy-2-methyl-3-(4-biphenylyl)butanoic acids. In the first step an intermediate α-bromo propanoic acid 1-ethoxyethyl ester was synthesized. The second step is a new modified Reformatsky reaction in presence of Zn in tetrahydrofuran (THF) at –5 to 10 °C between the previously synthesized intermediate and 4-acetylbiphenyl. Synthesis of the other studied β-hydroxy-β-arylpropanoic acids has already been reported. These β-hydroxy-β-arylpropanoic acids belong to the arylpropanoic acid class of compounds, structurally similar to the NSAIDs such as ibuprofen. The anti-inflammatory activity and gastric tolerability of the synthesized compounds were evaluated. Molecular docking experiments were carried out to identify potential COX-2 inhibitors among the β-hydroxy-β-aryl-alkanoic acids class. The results indicate that all compounds possess significant anti-inflammatory activity after oral administration and that the compounds 2-(9-(9-hydroxy-fluorenyl))-2-methylpropanoic acid (5) and 3-hydroxy-3,3-diphenyl-propanoic acid (3) possess the strongest anti-inflammatory activity, comparable to that of ibuprofen, a standard NSAID, and that none of tested substances or ibuprofen produced any significant gastric lesions.
C-Reactive Protein: Clinical and Epidemiological Perspectives

An important etiopathogenic component of cardiovascular disease is atherosclerosis, with inflammation being an essential event in the pathophysiology of all clinical pictures it comprises. In recent years, several molecules implicated in this process have been studied in order to assess cardiovascular risk in both primary and secondary prevention. C-reactive protein is a plasmatic protein of the pentraxin family and an acute phase reactant, very useful as a general inflammation marker. Currently, it is one of the most profoundly researched molecules in the cardiovascular field, yet its clinical applicability regarding cardiovascular risk remains an object of discussion, considered by some as a simple marker and by others as a true risk factor. In this sense, numerous studies propose its utilization as a predictor of cardiovascular risk through the use of high-sensitivity quantification methods for the detection of values <1 mg/L, following strict international guidelines. Increasing interest in these clinical findings has led to the creation of modified score systems including C-reactive protein concentrations, in order to enhance risk scores commonly used in clinical practice and offer improved care to patients with cardiovascular disease, which remains the first cause of mortality at the worldwide, national, and regional scenarios.
Optimized clothes segmentation to boost gender classification in unconstrained scenarios

Several applications require demographic information of ordinary people in unconstrained scenarios. This is not a trivial task due to significant human appearance variations. In this work, we introduce trixels for clustering image regions, enumerating their advantages compared to superpixels. The classical GrabCut algorithm is later modified to segment trixels instead of pixels in an unsupervised context. Combining with face detection lead us to a clothes segmentation approach close to real time. The study uses the challenging Pascal VOC dataset for segmentation evaluation experiments. A final experiment analyzes the fusion of clothes features with state-of-the-art gender classifiers in ClothesDB, revealing a significant performance improvement in gender classification.
An Analysis of Non-periodic Oscillation During a Learning of a Complex-valued BAM

Bidirectional associative memories have been proposed by Kosko[1]. Kosko’s model consists of two layers of neurons with synaptic connections between the layers. In the original model, the synaptic weight connections are determined by a correlation matrix of stored patterns. However, when the training pattern vectors are not orthogonal, cross-talk noise may occur in the system. To solve such problem, Oh.et. al. have been proposed Pseudorelaxation learning algorithm for BAM (PRLAB) which uses a projection method[2]. PRLAB does not require orthogonality or any special encoding of the training pairs and extremely increase the storage capacity. We extend the real-valued PRLAB algorithm to complex value. In the case that the complex-valued BAM trained by the extended PRLAB, we show that the storage capacity increases as the same as in the real-valued PRLAB. Moreover, it is also shown that when the complex-valued BAM fails to store the patterns to have high storage capacity, the time series of directional cosine during the training show non-periodic oscillation. We analyze the non-periodic oscillation in the present paper. As a result the non-periodic oscillation has a low-dimensional structure.
Dependence Based Value Prediction

This paper introduces dependence-based value prediction: prediction based on information that can be propagated through dependences. We propose an organization for a dependence-based value predictor and investigate how to use different types of dependence information to predict values produced by instructions. We consider first register dependences and then memory dependences. Memory dependence prediction is employed for propagating the history used for predicting output values. When considering only register dependences average prediction of 75% is achieved with a 64K entry table. The use of memory dependence prediction increases average accuracy for a 64K entry table to 82%. Several benchmarks achieve value prediction accuracy over 90%. We provide evidence that the proposed predictor requires small amount of speculative state (for speculative updates) which may suggest its design feasibility.
Slow Cortical Potentials and Amplification—Part II: Acoustic Measures

In a previous study, we investigated slow cortical potential (SCP) N1-P2 amplitudes and N1 latencies in aided and unaided conditions, with the finding that despite being set to provide 20 or 40 dB of gain, none of the hearing aids resulted in a reliable increase in SCP response amplitude relative to the unaided (Marynewich et al., in press). The current study investigates the effects of hearing-aid processing on acoustic measures for two 1000-Hz tonal stimuli: short (60 ms) and long (757 ms), presented at three intensities (30, 50, 70 dB SPL) in aided and unaided conditions using three hearing aids (Analog, DigitalA, DigitalB) with two gain settings (20, 40 dB). Acoustic results indicate that gain achieved by the hearing aids, measured at 30 ms after stimulus onset, for both the short and long stimuli, was less than real-ear insertion gain measured with standard hearing aid test signals. Additionally, the digital hearing aids altered the rise time of the stimuli such that maximum gain was reached well past 30 ms after stimulus onset; rise times differed between the digital aids. These results indicate that aided SCP results must be cautiously interpreted and that further research is required for clinical application.
Singing Voice Melody Transcription Using Deep Neural Networks

This paper presents a system for the transcription of singing voice melodies in polyphonic music signals based on Deep Neural Network (DNN) models. In particular, a new DNN system is introduced for performing the f 0 estimation of the melody, and another DNN, inspired from recent studies, is learned for segmenting vocal sequences. Preparation of the data and learning conﬁgurations related to the speciﬁcity of both tasks are described. The performance of the melody f 0 estimation system is compared with a state-of-the-art method and exhibits highest accuracy through a better generalization on two different music databases. Insights into the global functioning of this DNN are proposed. Finally, an evaluation of the global system combining the two DNNs for singing voice melody transcription is presented.
Perceptual Reasoning for Perceptual Computing: A Similarity-Based Approach

Perceptual reasoning (PR) is an approximate reasoning method that can be used as a computing-with-words (CWW) engine in perceptual computing. There can be different approaches to implement PR, e.g., firing-interval-based PR (FI-PR), which has been proposed in J. M. Mendel and D. Wu, IEEE Trans. Fuzzy Syst. , vol. 16, no. 6, pp. 1550-1564, Dec. 2008 and similarity-based PR (S-PR), which is proposed in this paper. Both approaches satisfy the requirement on a CWW engine that the result of combining fired rules should lead to a footprint of uncertainty (FOU) that resembles the three kinds of FOUs in a CWW codebook. A comparative study shows that S-PR leads to output FOUs that resemble word FOUs, which are obtained from subject data, much more closely than FI-PR; hence, S-PR is a better choice for a CWW engine than FI-PR.
Model-Checking Processes with States: An Industrial Case Study

ln this paper we present a formal specification of part of the SACI-1 microsatellite on-board computer whose development is led by the Brazilian Space Research Institute (INPE). The specification is written in CSP-Z, a specification language that integrates CSP (which allows one to focus on the concurrent aspects of the application) and Z (for modeling the relevant data structures). We also describe a strategy for model-checking processes with states (developed by the authors) and its implementation using the FOR model-checker. Finally, using this tool, we carry out an automatic proof that the SACI-1 specification is deadlock-free.
Three-dimension Test Wrapper Design based on Multi-objective Cuckoo Search

The main methodologies and recent patents on test wrapper design have been reviewed in this paper. The de- sign of three-dimension test wrapper for IP module in System on Chip is a NP Hard problem. As the test time of an IP module is determined by the longest wrapper scan chain and each TSV has area costs and is a potential source of defects, it is necessary to shorten the longest wrapper chain and use less TSV. The paper proposes MOCS (Multi-Objective Cuckoo Search) algorithm to achieve the purpose of minimization of the IP module test time and the number of TSV used. The proposed algorithm, which is based on swarm intelligence, through levy flight operation and discovery rate, can achieve balance of the wrapper scan chains and use less TSV. Typical IP modules in ITC'02 benchmarks are used to prove the effectiveness of the proposed algorithm. Experimental results show that the algorithm can get better Pateto solutions Set, compared with NSGAII, and can reduce the test cost.
A high level development, modeling and simulation methodology for complex multicore Network Processors

Network Processors (NPs) are attracting and powerful platforms for the fast development of high performance network applications. However, despite their greater flexibility and limited cost with respect to specialized hardware design, NP still face developers with significant difficulties. As they target complex and high-performance applications, programmers are often forced to write assembly code in order to better exploit the hardware. In this paper we propose an approach to NP programming which is based on a three-phase development methodology, and we apply it to Intel NPs of the IXP2XXX family. By exploiting a composition of software tools, a high-level definition of the application is turned first into a distributed program, then into an NP prototype, and finally into an efficient NP executable. The methodology we describe takes advantage of the ASSIST technology, which allows for the porting, testing, modeling and profiling of parallel applications on a cluster of standard PCs. We developed a C library that acts as a communication layer, hiding the hardware details of NP programming and allowing for high performance code development. The ultimate goal of this approach is to let programmers write C code, exploiting ASSIST-provided hints to (1) perform functional debugging and performance analysis and (2) to experiment with different parallel structures. The resulting code can be then directly compiled for the NP without modifications, largely reducing the overall coding effort.
Aren ’ t Those Questions Interesting Enough ? Investigating the Root Causes of Unanswered Questions

Stack Overflow is a highly successful questionanswering website in the programming community, which not only provide quick solutions to programmers’ questions but also is considered as a large repository of valuable software engineering knowledge. However, despite having a very engaged and active user community, Stack Overflow currently has more than 300K unanswered questions. In this paper, we mine Stack Overflow dataset to investigate why these questions remain unanswered by applying a combination of statistical and data mining techniques. Our results indicate that although there are some topics that were never answered, most questions remained unanswered because they apparently are of little interest to the user community.
An information theory-based tool for characterizing the interaction environment of a protein

In recent years large amounts of information have been accumulated in proteomic, genetic and metabolic databases. Much effort has been dedicated to developing methods that successfully exploit, organize and structure this information. However, there is no application, that we know of, that semantically characterizes the interaction environment in which a protein exists. A high-throughput software package has been developed to retrieve information from publicly available databases, such as the Gene Ontology Annotation (GOA) database and the Human Proteome Resource Database (HPRD) and structure their information. This information is presented to the user as groups of semantically described dense interaction subnetworks that interact with a target protein.