Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis Of Multi-Level Circuits Using EXOR

 There are many methods for the synthesis of logical functions. All these methods can be divided into two classes the first one is Two-Level Logic Synthesis and the second one is Multi-Level Logic Synthesis. The multi-level circuits and their structure are easier for practical realization if there is a large number of variables. In this paper we concentrate on a part of the second class synthesis of multi-level-circuits with EXOR-gates. We present six methods for EXOR-decomposition for both, completely and incompletely specified functions. In detail, we give an iterative algorithm for checking and calculating the EXORgroupability for the incompletely specified functions relating to sets of variables. Using this method, it is possible to fully utilize the characteristics and properties of incompletely specified functions enabling synthesis of very efficent circuits.
MR-microT: a MapReduce-based MicroRNA target prediction method

MicroRNAs (miRNAs) are small RNA molecules that inhibit the expression of particular genes, a function that makes them useful towards the treatment of many diseases. Computational methods that predict which genes are targeted by particular miRNA molecules are known as target prediction methods. In this paper, we present a MapReduce-based system, termed MR-microT, for one of the most popular and accurate, but computational intensive, prediction methods. MR-microT offers the highly requested by life scientists feature of predicting the targets of ad-hoc miRNA molecules in near-real time through an intuitive Web interface.
Academic Administrators’ Beliefs About Diversity

ABSTRACT As our nation and society becomes more racially and ethnically diverse, college campuses are experiencing a dynamic shift in the student demographic on campus as well. Purposes of the study were to: (a) analyze the beliefs of kinesiology academic unit leaders (i.e., chairs, directors, heads) regarding faculty and student diversity within their programs and departments and (b) inquire about strategic goals for faculty and student diversification within their programs and departments. The participants were 68 administrators (43 men, 25 women) and all current members of the American Kinesiology Association (AKA) as of 2015. Thematic content data analysis of the open-ended probes exposed the recurrent themes: (a) advocacy, motives, and actions; (b) diversity identified, but rarely defined; and (c) history, status, and outlook. Implications of the findings are that issues associated with diversity in kinesiology programs and departments should be addressed with vigor and progressive actions.
Context Forest for efficient object detection with large mixture models

We present Context Forest (ConF), a technique for predicting properties of the objects in an image based on its global appearance. Compared to standard nearest-neighbour techniques, ConF is more accurate, fast and memory efficient. We train ConF to predict which aspects of an object class are likely to appear in a given image (e.g. which viewpoint). This enables to speed-up multi-component object detectors, by automatically selecting the most relevant components to run on that image. This is particularly useful for detectors trained from large datasets, which typically need many components to fully absorb the data and reach their peak performance. ConF provides a speed-up of 2x for the DPM detector [1] and of 10x for the EE-SVM detector [2]. To show ConF's generality, we also train it to predict at which locations objects are likely to appear in an image. Incorporating this information in the detector score improves mAP performance by about 2% by removing false positive detections in unlikely locations.
Follow-up near-infrared spectroscopy of ultraluminous infrared galaxies observed by ISO

We present low resolution near-infrared spectroscopy of an unbiased sample of 24 ultraluminous infrared galaxies (ULIRGs), selected from samples previously observed spectroscopically in the mid-infrared with the Infrared Space Observatory (ISO). Qualitatively, the near-infrared spectra resemble those of starbursts. Only in one ULIRG, IRAS 04114-5117E, do we find spectroscopic evidence for AGN activity. The spectroscopic classification in the near-infrared is in very good agreement with the mid-infrared one. For a subset of our sample for which extinction corrections can be derived from $\mathrm{Pa\alpha}$and $\mbox{$\mathrm{Br\gamma}$}$, we find rather high $\mathrm{Pa\alpha}$luminosities, in accordance with the powering source of these galaxies being star formation. $\mathrm{[FeII]}$ emission is strong in ULIRGs and may be linked to starburst and superwind activity. Additionally, our sample includes two unusual objects. The first, IRAS F00183-7111, exhibits extreme $\mathrm{[FeII]}$ emission and the second, IRAS F23578-5307, is according to our knowledge one of the most luminous infrared galaxies in $\mbox{$\mathrm{H_2}$}$ rotation-vibration emission.
3D printing with flying robots

Extensive work has been devoted recently to the development of 3D printing or additive layer manufacturing technologies, as well as to the field of flying robots. However, to the best of the authors7 knowledge, no robotic prototype has been presented so far that combines additive layer manufacturing techniques with aerial robotics. In this paper, we examine the feasibility of such a hybrid approach and present the design and characterisation of an aerial 3D printer; a flying robot capable of depositing polyurethane expanding foam in mid-flight. We evaluate various printing materials and describe the design and integration of a lightweight printing module onto a quadcopter, as well as discuss the limitations and opportunities for aerial construction with flying robots using the developed technologies. Potential applications include ad-hoc construction of first response structures in search and rescue scenarios, printing structures to bridge gaps in discontinuous terrain, and repairing damaged surfaces in areas that are inaccessible by ground-based robots.
Full body image feature representations for gender profiling

In this paper we focus on building robust image representations for gender classification from full human bodies. We first investigate a number of state-of-the-art image representations with regard to their suitability for gender profiling from static body images. Features include Histogram of Gradients (HOG), spatial pyramid HOG and spatial pyramid bag of words etc. These representations are learnt and combined based on a kernel support vector machine (SVM) classifier. We compare a number of different SVM kernels for this task but conclude that the simple linear kernel appears to give the best overall performance. Our study shows that individual adoption of these representations for gender classification is not as promising as might be expected, given their good performance in the tasks of pedestrian detection on INRIA datasets, and object categorisation on Caltech 101 and Caltech 256 datasets. Our best results, 80% classification accuracy, were achieved from a combination of spatial shape information, captured by HOG, and colour information captured by HSV histogram based features. Additionally, to the best of our knowledge, currently there is no publicly available dataset for full body gender recognition. Hence, we further introduce a novel body gender dataset covering a large diversity of human body appearance.
Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks

In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property. Therefore, it combines in a learning system the flexibility and general advantages of a neural network model with the representational power of a structured domain. As a result, a completely new approach to quantitative structure-activity relationship/quantitative structure-property relationship (QSPR/QSAR) analysis is obtained. An original representation of the molecular structures has been developed accounting for both the occurrence of specific atoms/groups and the topological relationships among them. Gibbs free energy of solvation in water, Delta(solv)G degrees , has been chosen as a benchmark for the model. The different approaches proposed in the literature for the prediction of this property have been reconsidered from a general perspective. The advantages of RecNN as a suitable tool for the automatization of fundamental parts of the QSPR/QSAR analysis have been highlighted. The RecNN model has been applied to the analysis of the Delta(solv)G degrees in water of 138 monofunctional acyclic organic compounds and tested on an external data set of 33 compounds. As a result of the statistical analysis, we obtained, for the predictive accuracy estimated on the test set, correlation coefficient R = 0.9985, standard deviation S = 0.68 kJ mol(-1), and mean absolute error MAE = 0.46 kJ mol(-1). The inherent ability of RecNN to abstract chemical knowledge through the adaptive learning process has been investigated by principal components analysis of the internal representations computed by the network. It has been found that the model recognizes the chemical compounds on the basis of a nontrivial combination of their chemical structure and target property.
Bayesian multiple-instance motif discovery with BAMBI: inference of recombinase and transcription factor binding sites

Finding conserved motifs in genomic sequences represents one of essential bioinformatic problems. However, achieving high discovery performance without imposing substantial auxiliary constraints on possible motif features remains a key algorithmic challenge. This work describes BAMBI—a sequential Monte Carlo motif-identification algorithm, which is based on a position weight matrix model that does not require additional constraints and is able to estimate such motif properties as length, logo, number of instances and their locations solely on the basis of primary nucleotide sequence data. Furthermore, should biologically meaningful information about motif attributes be available, BAMBI takes advantage of this knowledge to further refine the discovery results. In practical applications, we show that the proposed approach can be used to find sites of such diverse DNA-binding molecules as the cAMP receptor protein (CRP) and Din-family site-specific serine recombinases. Results obtained by BAMBI in these and other settings demonstrate better statistical performance than any of the four widely-used profile-based motif discovery methods: MEME, BioProspector with BioOptimizer, SeSiMCMC and Motif Sampler as measured by the nucleotide-level correlation coefficient. Additionally, in the case of Din-family recombinase target site discovery, the BAMBI-inferred motif is found to be the only one functionally accurate from the underlying biochemical mechanism standpoint. C++ and Matlab code is available at http://www.ee. columbia.edu/~guido/BAMBI or http://genomics.lbl. gov/BAMBI/.
Recent advances in importance sampling for statistical model checking

In the following work we present an overview of recent advances in rare event simulation for model checking made at the University of Twente. The overview is divided into the several model classes for which we propose algorithms, namely multicomponent systems, Markov chains and stochastic Petri nets, and probabilistic timed automata.
Judeo-Spanish and Turkish Proverbs and Idioms with Djoha and Hodja Nasrettin: Questioning Wittiness via Conceptual Metaphors

This paper analyzes Judeo-Spanish and Turkish proverbs and idioms where Hodja Nasrettin (he is known as Djoha in Judeo-Spanish) is depicted as a joyful, gullible, nasty, or an intelligent person. It suggests that some different and similar conceptualizations are employed in the proverbs and idioms of both languages in order to describe Hodja Nasrettin from an anthropological linguistic point of view. These conceptualizations of the concept of cleverness and credulity are based on the Conceptual Metaphor Theory of Lakoff and Johnson (1980); however, the two researchers had never mentioned these conceptualizations in their works. These conceptualizations related to cultural and social experiences of Judeo-Spanish and Turkish speakers have been presented in this study for the first time. Besides, in Turkish Hodja is an old character, whereas in Judeo-Spanish, he is presented sometimes as an old, and sometimes as a young character. However, he gives advice to people from different age groups.
An IB Method for Non-Newtonian-Fluid Flexible-Structure Interactions in Three-Dimensions

Problems involving fluid flexible-structure interactions (FFSI) are ubiquitous in engineering and sciences. Peskin’s immersed boundary (IB) method is the first framework for modeling and simulation of such problems. This paper addresses a three-dimensional extension of the IB framework for non-Newtonian fluids which include power-law fluid, Oldroyd-B fluid, and FENE-P fluid. The motion of the non-Newtonian fluids are modelled by the lattice Boltzmann equations (D3Q19 model). The differential constitutive equations of Oldroyd-B and FENE-P fluids are solved by the D3Q7 model. Numerical results indicate that the new method is first-order accurate and conditionally stable. To show the capability of the new method, it is tested on three FFSI toy problems: a power-law fluid past a flexible sheet fixed at its midline, a flexible sheet being flapped periodically at its midline in an Oldroyd-B fluid, and a flexible sheet being rotated at one edge in a FENE-P fluid.
Normally off operation GaN-based MOSFETs for power electronics applications

Gallium nitride (GaN) is a promising electronic semiconductor material for high-power, high-temperature devices due to its remarkable material properties like wide bandgap, large critical electric field and high saturation velocity compared with Si. The metal-oxide–semiconductor (MOS) field-effect transistor (MOSFET) structure can be operated at a positive threshold voltage, namely the normally off mode, which is preferable for power transistors in terms of fail-safe operation. However in order to minimize the power losses in MOSFET operation, good interface quality at SiO2/GaN and low resistance in the n+-contact layer are strongly required. The MOS capacitors were used to characterize the interface states at SiO2/GaN, and the interface state density at Ec − 0.4 eV was less than 1 × 1011 cm−2 eV−1 after annealing at 900 °C for 30 min by the furnace. In addition, the activation annealing of Si-implanted GaN was performed at 1260 °C for 30 s in rapid thermal annealing (RTA) and its sheet resistance was 23 kΩ sq−1. Finally, we have fabricated GaN MOSFETs and have achieved more than 1 A operation in the normally off mode at more than 250 °C. The breakdown voltage was more than 1500 V. We also confirmed more than 100 h of consecutive operation at 250 °C at the moment.
Optimal power allocation and user selection in non-orthogonal multiple access systems

In this paper, we focus on the design of an optimal power allocation algorithm and an efficient user selection scheme for the downlink of a non-orthogonal multiple access (NOMA) system with power-domain user multiplexing at the transmitter side and successive interference cancellation (SIC) on the receiver side. We have derived an optimal power allocation solution in closed-form with the objective of maximizing the weighted sum rate subject to a maximum power constraint. The optimization problem is solved using the Karush-Kuhn-Tucker (KKT) conditions. A greedy user selection algorithm is used to schedule the best set of multiplexed users satisfying the criterion of maximizing sum proportional fairness (PF) metric. Systemlevel simulation results are provided to assess and compare the performance gains of the proposed algorithm in terms of important key system performance indicators.
Student assessment in the ubiquitously connected world

Student cheating on university assessments from entrance exams to finals and from contract cheating on coursework to requesting exam answers using a mobile phone during the exam, has received more and more attention of late. As connection to the Internet becomes ubiquitous and computing and communications technology more embedded in our environment, it is argued that a re-focussing on providing educational opportunities is needed in higher education, rather than chasing the ever-retreating prospect of perfect, or even adequate, assessment for the purposes of qualification.
A FAST MONTE CARLO SCHEME FOR THERMAL RADIATION IN SEMICONDUCTOR PROCESSING APPLICATIONS

Thermal radiation is the most effective way for rapid thermal processing (RTP) and rapid thermal chemical vapor deposition (RTCVD) of wafers. It is well known in the semiconductor equipment design community that the Monte Carlo method for radiation is the only method that can accurately model radiative transport in RTP and RTCVD reactors. However, it has often been argued that it is expensive and difficult to use as a commercial design tool. In this article, a fast Monte Carlo scheme is presented. The basic algorithm is the classical surface-to-surface ray-tracing algorithm. In addition, a modified form of the binary spatial partitioning (BSP) algorithm is implemented to speed up ray tracing by at least a factor of 3. The results demonstrate a high level of accuracy with fairly low computational cost.
Rapid Increase of Scrub Typhus: An Epidemiology and Spatial-Temporal Cluster Analysis in Guangzhou City, Southern China, 2006–2012

Background Scrub typhus has been increasingly reported in Southern China, and public health authorities are concerned about its increased incidence. Additionally, little evidence is available on the epidemiology of scrub typhus in Southern China. This study aims to analyze the epidemiological and geographic features of ST in Guangzhou City, Southern China, to guide the future prevention efforts. Methods Scrub typhus surveillance data in Guangzhou City during 2006–2012 were obtained from the Chinese National Communicable Disease Surveillance Network. We first conducted a descriptive analysis to analyze the epidemiological features of scrub typhus. Then we used space-time scan statistic based on a discrete Poisson model to detect and evaluate high-risk spatial-temporal clusters of scrub typhus. Results There were 4,001 cases of scrub typhus in Guangzhou City during the study period. The incidence of scrub typhus increased from 3.29 per 100,000 in 2006 to 9.85 per 100,000 in 2012. A summer peak was observed in June and July with a second peak in September and October except year 2009 and 2011. The majority of the cases (71.4%) were among persons aged ≥40 years, and female incidence was higher than male incidence in persons ≥50 years. In the space-time analysis, high-risk clusters were concentrated in rural areas in Guangzhou City. Over the past 7 years, Haizhu District, an urban area, was found to be a high-risk cluster for the first time in 2012. Conclusion The resurgence of scrub typhus epidemics in Guangzhou population in 2012 necessitates more effective measures for minimizing future epidemics. Consideration of high-risk population and historical spatial-temporal clusters may help prevent scrub typhus. The risk of scrub typhus in urban areas should not be neglected and needs more attention from public health authorities.
Hybridization for Stability Analysis of Switched Linear Systems

In this paper, we present a hybridization method for stability analysis of switched linear hybrid system (LHS), that constructs a switched system with polyhedral inclusion dynamics (PHS) using a state-space partition that is specific to stability analysis. We use a previous result based on quantitative predicate abstraction to analyse the stability of PHS. We show completeness of the hybridization based verification technique for the class of asymptotically stable linear system and a subclass of switched linear systems whose dynamics are pairwise Lipschitz continuous on the state-space and uniformly converging in time. For this class of systems, we show that by increasing the granularity of the region partition, we eventually reach an abstract switched system with polyhedral inclusion dynamics that is asymptotically stable. On the practical side, we implemented our approach in the tool averist, and experimentally compared our approach with a state-of-the-art tool for stability analysis of hybrid systems based on Lyapunov functions. Our experimental results illustrate that our method is less prone to numerical errors and scales better than the traditional approaches. In addition, our tool returns a counterexample in the event that it fails to prove stability, providing feedback regarding the potential reason for instability. We also examined heuristics for the choice of state-space partition during refinement.
The Interstellar Extinction Law toward the Galactic Center. II. V, J, H, and Ks Bands

We have determined the ratios of total to selective extinction directly from observations in the optical V band and near-infrared J band toward the Galactic center. The OGLE (Optical Gravitational Lensing Experiment) Galactic bulge fields have been observed with the SIRIUS camera on the Infrared Survey Facility telescope, and we obtain AV/EV–J = 1.251 ± 0.014 and AJ/EV–J = 0.225 ± 0.007. From these ratios, we derive AJ/AV = 0.188 ± 0.005; combining this with the near-infrared extinction ratios obtained in Paper I for more reddened fields near the Galactic center, we obtain AV:AJ:AH:AKs = 1:0.188:0.108:0.062, which implies steeply declining extinction toward longer wavelengths. In particular, it is striking that the Ks-band extinction is ≈1/16 the visual extinction AV, much smaller than the 1/10 usually employed.
Admired Rich or Resented Rich? How Two Cultures Vary in Envy

Rich people inhabit a distinct social category that may elicit universal images or perhaps different perceptions in different cultures. Whereas inequality research has mostly focused on lower socioeconomic classes, the current research investigates cultural variations of prejudices about rich groups, toward understanding societal dynamics. Three studies investigate stereotype content and evaluations of rich people in China and the United States, cultures that might be expected to differ. Consistent with U.S. data from the stereotype content model, Study 1 demonstrates mainland Chinese likewise view the rich in general ambivalently as competent but cold. Examining a more specific level, Study 2 identifies both distinctive and overlapping rich subgroups across the two cultures, but both reporting mixed stereotype content. Study 3 tests whether clearer cultural contrasts might occur in implicit (vs. explicit) stereotypes toward rich people: Both U.S. and Chinese respondents, however, expressed positive implicit stereotypes toward the rich compared with middle class, in contrast with their self-reported explicitly ambivalent (or, rarely, negative) wealth stereotypes. This research is the first to examine stereotype content about rich people on the subgroup level, and both implicit and explicit levels, offering theory-based social structure predictors of this culturally shared but somewhat variable stereotype content.