Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual Mode K-Best MIMO Detector Architecture and VLSI Implementation

Maximum likelihood (ML) detector is the optimal detector for multiple-input multiple-output (MIMO) communication systems. K-best decoding algorithm can achieve sub-optimal ML performance with reduced complexity. In this paper we present a novel dual mode architecture for implementation of K-best algorithm. The proposed architecture is fully parallel and can support both QPSK and 16-QAM modulation schemes. Implementation results show that detector's throughput can reach 480 Mbps.
Audio keywords detection in basketball video

This paper presents an audio keywords detection method for highlight retrieval in basketball video. The keywords contain shoes squeaking sound, speech, cheer, long whistle and short whistle, which correspond to basketball game events. After feature analysis, the Simple Excellent Feature Combination based on Pearson Correlation Coefficient (SEFC-PCC) is used to select efficient features, which contributes to a preferable performance and lower computational complexity. A novel multi-stage SVM classifier is proposed to do the final detection of the five audio keywords. There are 428 audio sequences about 704 seconds used in the validation experiment; it gives a performance evaluation with average detection accuracy of 92%∼99%.
Promoting Precision Cancer Medicine through a Community-Driven Knowledgebase

Increasing efforts are being dedicated towards improving cancer care via personalized medicine. These efforts depend to a large degree on the availability of a knowledge foundation. Unfortunately, existing knowledge linking cancer drugs and potential efficacy biomarkers is in its infancy; and where links are known, they are frequently unstructured and poorly documented. We have developed a new open-access knowledgebase for precision cancer medicine (the PCM Wiki and Knowledgebase). This knowledgebase was constructed using an innovative, two-pronged approach involving a structured knowledgebase at the back-end, and an intuitive knowledge-sharing interface and user-friendly query engine in front. The knowledgebase was seeded with several patient case reports and information was mined via text-mining and literature review by human curators. Using our novel Wiki-based platform to present and share knowledge stored in the PCM knowledgebase, users are able to suggest corrections, propose additions or point to errors in the knowledgebase. The result is a community-driven evolving knowledgebase holding integrated and consolidated knowledge of markers and indications for personalized cancer medicine. We suggest that the PCM Knowledgebase and Wiki could serve as an important tool for the advancement of clinical trials and care in the field of precision cancer medicine.
Physical activity counteracts increased whole‐body protein breakdown in chronic obstructive pulmonary disease patients

Chronic obstructive pulmonary disease (COPD) is associated with increased whole body protein breakdown and low‐grade systemic inflammation. We aimed to determine if physical training of patients with COPD induces anti‐inflammatory effects and decreases whole‐body protein breakdown. Nineteen subjects with severe (FEV1=31±1) COPD were randomized into a training group (n=9) and a control group (n=10). Twenty healthy subjects were studied for baseline comparison. The “COPD training” group participated in an outpatient rehabilitation program consisting of endurance training (walking at 85% of VO2max) twice weekly for 7 weeks plus daily home‐based training. Maximum walking distance increased by almost 70% in the training group after 7 weeks of training. At baseline, the concentrations of C‐reactive protein (CRP) and IL‐18 in plasma were increased in subjects with COPD compared with healthy subjects (P<0.05) and leucine rate of appearance (Ra) was ∼15% greater (P<0.05) in subjects with COPD. Training had no effect on the plasma concentration of inflammatory markers but decreased leucine Ra in subjects with COPD by ∼10% (P<0.05). In conclusion, 7 weeks of physical training markedly improved endurance in patients with COPD and accelerated whole‐body protein breakdown in patients with COPD was attenuated by physical training independent of changes in inflammatory markers.
Design of an intelligent agent-based supply chain simulation system

An intelligent agent-based supply chain simulation system is designed, in which a supply chain entity is represented by an agent. There are six layers in this system: raw material providers, component manufacturers, product assemblers, product holders, retailers, and final customers. A detailed agent structure is presented and various functions of the agent are described. Moreover, communication activities among agents are discussed. By using the proposed system, issues in supply chain integration, information sharing among supply chain partners, demand forecasting, supply chain risk management, and automated communication and negotiation, could be simulated and studied.
Zygotic vinculin is not essential for embryonic development in zebrafish

The formation of multicellular tissues during development is governed by mechanical forces that drive cell shape and tissue architecture. Protein complexes at sites of adhesion to the extracellular matrix (ECM) and cell neighbors, not only transmit these mechanical forces, but also allow cells to respond to changes in force by inducing biochemical feedback pathways. Such force-induced signaling processes are termed mechanotransduction. Vinculin is a central protein in mechanotransduction that in both integrin-mediated cell-ECM and cadherin-mediated cell-cell adhesions mediates force-induced cytoskeletal remodeling and adhesion strengthening. Vinculin was found to be important for the integrity and remodeling of epithelial tissues in cell culture models and could therefore be expected to be of broad importance in epithelial morphogenesis in vivo. Besides a function in mouse heart development, however, the importance of vinculin in morphogenesis of other vertebrate tissues has remained unclear. To investigate this further, we knocked out vinculin functioning in zebrafish, which contain two fully functional isoforms designated as vinculin A and vinculin B that both show high sequence conservation with higher vertebrates. Using TALEN and CRISPR-Cas gene editing technology we generated vinculin-deficient zebrafish. While single vinculin A mutants are viable and able to reproduce, additional loss of zygotic vinculin B was lethal after embryonic stages. Remarkably, vinculin-deficient embryos do not show major developmental defects, apart from mild pericardial edemas. These results lead to the conclusion that vinculin is not of broad importance for the development and morphogenesis of zebrafish tissues.
Generalized regressive motion: a visual cue to collision

Brains and sensory systems evolved to guide motion. Central to this task is controlling the approach to stationary obstacles and detecting moving organisms. Looming has been proposed as the main monocular visual cue for detecting the approach of other animals and avoiding collisions with stationary obstacles. Elegant neural mechanisms for looming detection have been found in the brain of insects and vertebrates. However, looming has not been analyzed in the context of collisions between two moving animals. We propose an alternative strategy, generalized regressive motion (GRM), which is consistent with recently observed behavior in fruit flies. Geometric analysis proves that GRM is a reliable cue to collision among conspecifics, whereas agent-based modeling suggests that GRM is a better cue than looming as a means to detect approach, prevent collisions and maintain mobility.
Feature-Budgeted Random Forest

We seek decision rules for prediction-time cost reduction, where complete data is available for training, but during prediction-time, each feature can only be acquired for an additional cost. We propose a novel random forest algorithm to minimize prediction error for a user-specified {\it average} feature acquisition budget. While random forests yield strong generalization performance, they do not explicitly account for feature costs and furthermore require low correlation among trees, which amplifies costs. Our random forest grows trees with low acquisition cost and high strength based on greedy minimax cost-weighted-impurity splits. Theoretically, we establish near-optimal acquisition cost guarantees for our algorithm. Empirically, on a number of benchmark datasets we demonstrate superior accuracy-cost curves against state-of-the-art prediction-time algorithms.
Molecular Epidemiology and Antimicrobial Resistance Mechanisms of Methicillin‐Resistant Staphylococcus aureus Isolated from Bovine Milk

The aim of this study was to identify methicillin‐resistant Staphylococcus aureus (MRSA) strains gathered from 2002 to 2006 from milk samples in Aydin region in Turkey. Among 93 S. aureus strains isolated from bovine milk with mastitis, 16 were resistant to methicillin. Methicillin‐resistant S. aureus strains were studied further for their staphylococcal cassette chromosome mec (SCCmec) types, pulsotypes, spa and MLST types, antimicrobial susceptibilities, mechanisms of resistance and presence of Panton–Valentine leucocidin (PVL) toxin gene. The MRSA strains were multi‐drug resistant. The susceptibility rates to antimicrobials tested were 0%, 0%, 0%, 0%, 6.25%, 16.25% and 56.25% for erythromycin, clindamycin, chloramphenicol, gentamicin, tetracyclin, ciprofloxacin and vancomycin, respectively. All tetracycline and gentamicin resistant strains carried tet(M) and aac(6)‐aph(2) gene, respectively. Among macrolide‐resistant isolates, nine had erm(A), and seven had both erm(A) and erm(B) genes. The molecular characterization by pulsed‐field gel electrophoresis showed presence of three pulsotypes with their variants. The pulsotype B strains were type IV with SCCmec typing, and representative of pulsotype B was t190 by spa typing and ST8 by MLST typing. The strains with pulsotype A and C were SCCmec III, and representative of these pulsotypes was t030 by spa typing. The MLST type of pulsotype A was ST239 and pulsotype C was one allele variant of ST239. None of the isolates harboured the PVL gene. Presence of hospital‐related MRSA strains may indicate transmission of these strains between human and animals. In case of clonal spread beside the infected animals’ treatment of MRSA carrier, farm workers should also be considered. Hygienic measures and rational antibiotic use may avoid resistance selection, clonal dissemination of resistant strains and decrease losses because of mastitis in dairy herds.
Quantitative Emergence -- A Refined Approach Based on Divergence Measures

The article addresses the phenomenon of emergence from a technical viewpoint. A technical system exhibits emergence when it has certain kinds of properties or qualities that are irreducible in the sense that they are not traceable to the constituent parts of the system. In particular, we show how emergence in technical systems can be detected and measured gradually using techniques from the field of probability theory and information theory. To detect or measure emergence we observe the system and extract characteristic attributes from those observations. As an extension of earlier work in the field, we propose emergence measures that are well-suited for continuous attributes (or hybrid attribute sets) using either non-parametric or model-based probability density estimation techniques. We also replace the known entropy-based emergence measures by divergence measures for probability densities (e.g., the Kullback-Leibler divergence or the Hellinger distance). We discuss advantages and drawbacks of these measures by means of some simulation experiments using artificial data sets and a real-world data set from the field of intrusion detection.
An Improved PI Regulator Based Load Regulation in Constant Photovoltaic Power Supply System

Due to scarcity of fossil fuel and increasing demand of power supply, we are forced to utilize the renewable energy resources. Considering easy availability and vast potential, world has turned to solar photovoltaic energy to meet its ever increasing energy requirement. In photovoltaic (PV) applications the grid tied systems often use a boost type converter to step up the output voltage to the utility level before the inverter stage. In grid connected PV systems due to load variation the output voltage may deviate from its nominal value. Hence, there is a need for closed loop control to regulate the output voltage and switching frequency of the PWM pulses are varied depends on the error. In order to regulate the converter due to non linearity, conventional controller like PI controller is proposed and simulated. The performance of the PI controller is improved by including error limiter algorithm. The results reveal that the output voltage is regulated satisfactorily for increasing load current.
Analysis of Quality of the Design of the Object Oriented Software using Fuzzy Logic

of the software fail due to poor quality. Estimating software quality is an important task in the software development. The development of large software system is a time consuming and resource consuming activity. Software metrics are necessary to identify where the resources are needed; they are a crucial source of information for decision making. To produce high quality object oriented applications, a strong emphasis on design aspects, especially during the early phases of software development is necessary. Design metrics play an important role in helping developers to appreciate design aspects of software i.e. improve software quality. By analyzing the metric data we can forecast the quality of the object oriented system. In this paper we propose a model based on fuzzy logic which serves as an integrated means to provide an interpretation of the OOD metrics of the CK metric suite.
Implications of a regime-switching model on natural gas storage valuation and optimal operation

In this paper, we propose a one-factor regime-switching model for the risk adjusted natural gas spot price and study the implications of the model on the valuation and optimal operation of natural gas storage facilities. We calibrate the model parameters to both market futures and options on futures. Calibration results indicate that the regime-switching model is a better fit to market data compared to a one-factor mean-reverting model similar to those used by other authors to value gas storage. We extend a semi-Lagrangian timestepping scheme from Chen and Forsyth (2007) to solve the gas storage pricing problem, essentially a stochastic control problem, and conduct a convergence analysis of the scheme. Numerical results also indicate that the regime-switching model can generate operational strategies for gas storage facilities that reflect the existence of multiple regimes in the market as well as the regime shifts due to various exogenous events.
Configuration and trajectory optimization for a Gecko Inspired climbing robot with a Pendular waist

Inspired by gecko's movement characteristics, we proposed a gecko inspired climbing robot, which is based on the GPL (Gecko inspired mechanism with a Pendular waist and Linear legs) model. In this paper, further research is made to analysis its gait and continuity. We optimist the driving angle to maintain the cyclical movement. Furthermore, the issues related configuration and motion planning are discussed. We find that the waist joint elastic coefficient has significant effect on the driving force. The optimization trajectory is given based on energy consumption. In the end, we do the prototype experiment to verify the theoretical analysis. The results also reveal the rationality of the big gecko bionic configuration on the other hand.
Metric Based Attribute Reduction Method in Dynamic Decision Tables

Abstract Feature selection is a vital problem which needs to be effectively solved in knowledge discovery in databases and pattern recognition due to two basic reasons: minimizing costs and accurately classifying data. Feature selection using rough set theory is also called attribute reduction. It has attracted a lot of attention from researchers and numerous potential results have been gained. However, most of them are applied on static data and attribute reduction in dynamic databases is still in its early stages. This paper focuses on developing incremental methods and algorithms to derive reducts, employing a distance measure when decision systems vary in condition attribute set. We also conduct experiments on UCI data sets and the experimental results show that the proposed algorithms are better in terms of time consumption and reducts’ cardinality in comparison with non-incremental heuristic algorithm and the incremental approach using information entropy proposed by authors in [17].
Evaluating the Effect of Oxygen Concentrations on Antibiotic Sensitivity, Growth, and Biofilm Formation of Human Pathogens

Standard antimicrobial susceptibility tests are performed in vitro under normal room oxygen conditions to predict the in vivo effectiveness of antimicrobial therapy. The aim of this study was to conduct a comprehensive analysis of the effect of different oxygen levels on the antibiotic susceptibility of two strains of Staphylococcus aureus, Pseudomonas aeruginosa, and Klebsiella pneumoniae. It was found that anoxic conditions caused reduced sensitivity of bacteria to aminoglycoside antibiotics in four of six bacteria used in the study. In addition, oxygen limitation decreased the susceptibility of P. aeruginosa strains and K. pneumoniae strains to piperacillin/tazobactam and azithromycin, respectively. In contrast, five of six bacteria became more susceptible to tetracycline antibiotics under oxygen-limiting conditions. Our data highlight the importance of considering the potential in vivo oxygen levels within the infection site when setting susceptibility breakpoints for evaluating the therapeutic potential of a drug and its effect on antibiotic sensitivity of the pathogen.
A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes

Parametric policy search algorithms are one of the methods of choice for the optimisation of Markov Decision Processes, with Expectation Maximisation and natural gradient ascent being popular methods in this field. In this article we provide a unifying perspective of these two algorithms by showing that their search-directions in the parameter space are closely related to the search-direction of an approximate Newton method. This analysis leads naturally to the consideration of this approximate Newton method as an alternative optimisation method for Markov Decision Processes. We are able to show that the algorithm has numerous desirable properties, absent in the naive application of Newton's method, that make it a viable alternative to either Expectation Maximisation or natural gradient ascent. Empirical results suggest that the algorithm has excellent convergence and robustness properties, performing strongly in comparison to both Expectation Maximisation and natural gradient ascent.
Characterization of a 4$\,\times\,$ 4 Gb/s Parallel Electronic Bus to WDM Optical Link Silicon Photonic Translator

A 4times4 Gb/s microring modulator cascade, which can directly convert data from a parallel electrical bus to a multiple-wavelength optical signal in a single silicon-on-insulator waveguide, is demonstrated and characterized. The integrity of the modulated optical signal is verified using Q-factor extrapolations. In addition, the frequency characteristics and crosstalk, in terms of total harmonic distortion, are quantified. A transparent translator from electronics to optics such as this is crucial for the development of large-scale high-bandwidth interconnects based on photonic integrated circuits
Improving flow analyses via ΓCFA: abstract garbage collection and counting

We present two independent and complementary improvements for flow-based analysis of higher-order languages: (1) abstract garbage collection and (2) abstract counting, collectively titled ΓCFA. Abstract garbage collection is an analog to its concrete counterpart: we determine when an abstract resource has become unreachable, and then reallocate it as fresh. This prevents flow sets from merging in the abstract, which has two immediate effects: (1) the precision of the analysis is increased, and (2) the running time of the analysis is frequently reduced. In some nontrivial cases, we achieve an order of magnitude improvement in precision and time simultaneously.In abstract counting, we track how many times an abstract resource has been allocated. A count of one implies that the abstract resource momentarily represents only one concrete resource. This, in turn, allows us to perform environment analysis and to expand the kinds (rather than just the degree) of optimizations available to the compiler.
An edge detection algorithm based on multi-resolution image

In this paper, a multi scale Gaussian edge detector is constructed. According to transfer properties across scales of the wavelet modules of the signal edge and the noise edge, we combine the properties of edges in different scales and propose a multi scale edge fusion algorithm consisting of edge transfer, edge inherit and edge growth. The edge is an important content of obtaining information of a picture, as the most basic characteristic of images. The wavelet transform can detect part mutation , and can do it combining multi scale information, so wavelet has become a good too l of detecting information of edge images. The result of experiments show s that this algorithm can get rid of the affect of noise and the edges fused have precise posit ion and intact contour.
Turn-taking in Mandarin Dialogue: Interactions of Tone and Intonation

Fluent dialogue requires that speakers successfully negotiate and signal turn-taking. While many cues to turn change have been proposed, especially in multi-modal frameworks, here we focus on the use of prosodic cues to these functions. In particular, we consider the use of prosodic cues in a tone language, Mandarin Chinese, where variations in pitch height and slope additionally serve to determine word meaning. Within a corpus of spontaneous Chinese dialogues, we find that turn-unit final syllables are significantly lower in average pitch and intensity than turnunit initial syllables in both smooth turn changes and segments ended by speaker overlap. Interruptions are characterized by significant prosodic differences from smooth turn initiations. Furthermore, we demonstrate that these contrasts correspond to an overall lowering across all tones in final position, which largely preserves the relative heights of the lexical tones. In classification tasks, we contrast the use of text and prosodic features. Finally, we demonstrate that, on balanced training and test sets, we can distinguish turnunit final words from other words at ≈ 93% accuracy and interruptions from smooth turn unit initiations at 62% accuracy.
Dimensional reduction of the heterotic string over nearly-Kähler manifolds

Our aim is to derive the effective action in four dimensions resulting by reducing dimensionally the ten-dimensional = 1 heterotic supergravity coupled to = 1 super Yang-Mills over manifolds admitting a nearly-K? hler structure. Given the fact that all homogeneous six-dimensional nearly-K? hler manifolds are included in the class of the corresponding non-symmetric coset spaces plus a group manifold, our procedure amounts in applying the Coset Space Dimensional Reduction scheme using these coset spaces as internal manifolds. In our examination firstly the rules of the reduction of the theory over a general six-dimensional non-symmetric manifold are stated and subsequently a detailed case by case analysis is performed for all the three non-symmetric coset spaces. For each case the four-dimensional scalar potential is derived and the corresponding nearly-K? hler limit is obtained. Finally, we determine the corresponding supergravity description of the four-dimensional theory employing the heterotic Gukov-Vafa-Witten formula and results of the special K? hler geometry.