Miracle-dz/UniFAR-FTUs huggingface dataset:
Subset selection with structured dictionaries in classification

This paper describes a new approach for the selection of discriminant time-frequency features for classification. Unlike previous approaches that use the individual discrimination power of expansion coefficients, the proposed approach selects a subset of features by implementing a classifier directed pruning of an initial redundant set of candidate features. The candidate features are calculated from a structured redundant time-frequency analysis of the signal, such as an undecimated wavelet transform. We show that the proposed approach has a performance that is as good as or better than traditional classification approaches while using a much smaller number of features. In particular, we provide experimental results to demonstrate the superior performance of the algorithm in the area of impact acoustic classification for food kernel inspection. The proposed algorithm achieved 91.8% and 98.5% classification accuracies in separating open shell from closed shell pistachio nuts and discriminating between empty and full hazelnuts respectively. Traditional methods used in this area resulted in 82% and 97% classification accuracies respectively.
Cancer stem cells in prostate cancer

Prostate cancer (P-Ca) remains a leading cause of cancer-related death in men. Lately, increasing evidence for a hierarchically organized cancer stem cell (CSC) model emerged for different tumors entities, including P-Ca. CSCs are defined by several characteristics including self-renewal, pluripotency and tumorigenicity and are thought to be responsible for tumor recurrence, metastasis and cancer related death. In this review we discuss the recent research in the field of CSCs, its limitations and therapeutical implications in general and specifically in P-Ca.
Generalizing Tree Transformations for Inductive Dependency Parsing

Previous studies in data-driven dependency parsing have shown that tree transformations can improve parsing accuracy for specific parsers and data sets. We investigate to what extent this can be generalized across languages/treebanks and parsers, focusing on pseudo-projective parsing, as a way of capturing non-projective dependencies, and transformations used to facilitate parsing of coordinate structures and verb groups. The results indicate that the beneficial effect of pseudo-projective parsing is independent of parsing strategy but sensitive to language or treebank specific properties. By contrast, the construction specific transformations appear to be more sensitive to parsing strategy but have a constant positive effect over several languages.
SUVpeak Performance in Lung Cancer: Comparison to Average SUV from the 40 Hottest Voxels

The performance of an average SUV over a 1-mL-volume sphere within an 18F-FDG–positive lesion resulting in the highest possible value (SUVpeakW) was compared with that of an average SUV computed from the 40 hottest voxels, irrespective of their location within the lesion (SUVmax-40). Methods: Dynamic PET performed in 20 lung cancer lesions yielded for each SUV metric its mean value, relative measurement error, and repeatability (MEr-R). Results: SUVpeakW mean value was significantly 9.66% lower than that of SUVmax-40 (P < 0.0001). SUVpeakW and SUVmax-40 MEr-R were significantly lower than the MEr-R of SUVmax (the hottest voxel): 9.35%–13.21% and 8.84%–12.49% versus 13.86%–19.59%, respectively, (95% confidence limit; P < 0.0001). Although being marginal, SUVpeakW MEr-R was not significantly greater than SUVmax-40 MEr-R (P = 0.086). Conclusion: SUVmax-40 is more likely to represent the most metabolically active portions of tumors than SUVpeakW, with close variability performance.
The dynamics of wettability driven droplets in smooth and corrugated microchannels

A multi-component lattice Boltzmann scheme is used to investigate the dynamics of a wettability driven droplet within a microchannel. The driving force for the motion is created by a stepwise change in the wettability of the channel walls. Moreover, an analytical solution is developed for evaluation of the dynamics of the droplet inside the channel. The effects of various parameters such as the height of the channel, the wetting pattern of the channel walls, the viscosity and the density ratio on the dynamics are studied. Also, the effect of grooves of different sizes on the channel surfaces on the dynamics of the droplet is investigated for both hydrophilic and hydrophobic surfaces. Finally, the effect of an obstacle in the channel on the motion of the droplet is studied. The numerical results are compared with the analytical solutions and close agreement between the results is found.
Process customization based on dependent topology in Software as a Service model

Software as a Service (SaaS) is a new software model for companies, which can provide them necessary software services based on a unique platform. In a general model of SaaS, the Independent Software Vendor (ISV) has a configurable and multi-tenant aware application. While in the actual working process, tenant always needs to do personal customization on different layers with individual requirements. To reduce the work in the process customization, this paper proposes a flexible process-customization program. By this program, tenant can customize the SaaS application from the processing layer on their own terms. To keep this process's validity and manage its generation, a topological algorithm based on the dependency of tasks is introduced. Experimental results show the efficiency of this algorithm.
Dramatically Low-Transistor-Count High-Speed Ternary Adders

Ternary logic has inherently the potential of high computational speed in comparison with conventional binary logic. A new low-transistor-count, high-speed ternary half adder is presented in this paper. Carbon nanotube field effect transistors are utilized to realize the new design methodology. Unique characteristics of this technology provide multi-Vt circuitry with the flexibility which is highly essential for MVL designs. The given structure also benefits from high driving power and capability of operating in low voltages. It has only 26 transistors. A new high-performance ternary full adder is also presented. Finally, the proposed adder cells are put together in order to construct a 4-bit ternary ripple adder.
Synergy, Redundancy, and Independence in Population Codes, Revisited

Decoding the activity of a population of neurons is a fundamental problem in neuroscience. A key aspect of this problem is determining whether correlations in the activity, i.e., noise correlations, are important. If they are important, then the decoding problem is high dimensional: decoding algorithms must take the correlational structure in the activity into account. If they are not important, or if they play a minor role, then the decoding problem can be reduced to lower dimension and thus made more tractable. The issue of whether correlations are important has been a subject of heated debate. The debate centers around the validity of the measures used to address it. Here, we evaluate three of the most commonly used ones: synergy, ΔIshuffled, and ΔI. We show that synergy and ΔIshuffled are confounded measures: they can be zero when correlations are clearly important for decoding and positive when they are not. In contrast, ΔI is not confounded. It is zero only when correlations are not important for decoding and positive only when they are; that is, it is zero only when one can decode exactly as well using a decoder that ignores correlations as one can using a decoder that does not, and it is positive only when one cannot decode as well. Finally, we show that ΔI has an information theoretic interpretation; it is an upper bound on the information lost when correlations are ignored.
Androgen receptor is a new potential therapeutic target for the treatment of hepatocellular carcinoma.

BACKGROUND & AIMS Androgen effects on hepatocellular carcinoma (HCC) remain controversial and androgen ablation therapy to treat HCC also leads to inconsistent results. Here we examine androgen receptor (AR) roles in hepatocarcinogenesis using mice lacking AR in hepatocytes. METHODS By using the Cre-Lox conditional knockout mice model injected with carcinogen, we examined the AR roles in hepatocarcinogenesis. We also tested the possible roles of AR in cellular oxidative stress and DNA damage sensing/repairing systems. By using AR degrading compound, ASC-J9, or AR-small interference RNA, we also examined the therapeutic potentials of targeting AR in HCC. RESULTS We found AR expression was increased in human HCC compared with normal livers. We also found mice lacking hepatic AR developed later and less HCC than their wild-type littermates with comparable serum testosterone in both male and female mice. Addition of functional AR in human HCC cells also resulted in the promotion of cell growth in the absence or presence of 5alpha-dihydrotestosterone. Mechanistic dissection suggests that AR may promote hepatocarcinogenesis via increased cellular oxidative stress and DNA damage, as well as suppression of p53-mediated DNA damage sensing/repairing system and cell apoptosis. Targeting AR directly via either AR-small interference RNA or ASC-J9 resulted in suppression of HCC in both ex vivo cell lines and in vivo mice models. CONCLUSIONS Our data point to AR, but not androgens, as a potential new and better therapeutic target for the battle of HCC.
Optimal mesh signal transforms

We describe a simple autoregressive model for 3D mesh geometry based on linear prediction. Assuming a Gaussian error term, we show that the resulting probabilistic distribution is a multivariate Gaussian, which may be singular. Furthermore, if the prediction operator is symmetric positive semi-definite, then its eigenvectors coincide with that of the covariance matrix for the distribution. This implies that the mesh signal transform induced by the prediction operator is optimal, with respect to a specific class of mesh distributions and in the sense of basis restriction errors.
Automatic centralized controller design for modular and reconfigurable robot manipulators

We address the problem of controlling modular robot manipulators. The challenge of modular-robot control is that the overall system dynamics are unknown due to its flexible composition from given modules. Most previous work has faced this problem by designing decentralized controllers. Simple decentralized controllers do not guarantee global asymptotic stability without knowledge of the overall system dynamics and alternative versions involving communication with neighboring modules result in complicated control concepts. Our approach is completely different: we store parameters regarding the dynamics and kinematics of each module and a unique identification number in itself. After finishing the assembly of the modules, the parameters are gathered in a central controller, which also detects the configuration using the identification numbers. Our centralized controller uses this information to synthesize model-based control laws on-the-fly as if the full system dynamics are known beforehand. We introduce a novel and compact notation to automate this procedure and to generalize the derivation of the kinematic and dynamic model for heterogeneous modules. Finally, a possible application is shown using simulations.
DOPPLER IMAGING OF STELLAR SURFACE STRUCTURE. V. THE LONG-PERIOD RS CVN BINARY HD 81410 = IL HYDRAE

Multiwavelength Doppler images of the long-period RS CVn binary IL Hydrae from March 1994 and Feb.-March 1995 reveal a cool polar spot and several features at low latitudes. Their average temperature is approximately 500 K below the photospheric temperature of 4700 K. Due to the relatively small rotational velocity of 26.5±1 km s−1 and the relatively cool, low-gravity atmosphere with many weak absorption blends, Doppler imaging of IL Hydrae is challenging but resulted in encouragingly similar maps from altogether seven spectral regions near 6400 Å. Latitude-dependent differential rotation is detected from our Doppler maps and indicate faster rotation at the stellar equator as compared to the polar regions. Lines from the secondary component are sometimes seen in our red-wavelength spectra and a double-lined spectroscopic orbit is presented. We also give a more precise rotational period from three consecutive years of V -band photometry. A spectral classification of K0III-IV and a mass of 2.2±0.2 M for the primary, and mid to late F main sequence or maybe ≈G0V-IV and a mass of 1.3±0.2 M for the secondary, are suggested. Hα equivalent widths measured over a single rotation cycle exhibit a sinusoidal variation in phase with the photospheric V -band light curve. The maximum of the residual Hα emission coincides with the lightcurve minimum and is thus likely linked to the starspot-covered stellar surface. A steady, redshifted absorption component possibly indicates an isotropic inward flow at the Hα line-forming region at approximately 60 km s−1.
A repetitive modular oscillation underlies human brain electric activity

The modular function j, central in the assessment of abstract mathematical problems, describes elliptic, intertwined trajectories that move in the planes of both real and complex numbers. Recent clues suggest that the j-function might display a physical counterpart, equipped with a quantifiable real component and a hidden imaginary one, currently undetectable by our senses and instruments. Here we evaluate whether the real part of the modular function can be spotted in the electric activity of the human brain. We assessed EEGs from five healthy males, eyes-closed and resting state, and superimposed the electric traces with the bidimensional curves predicted by the j-function. We found that the two trajectories matched in more than 85% of cases, independent from the subtending electric rhythm and the electrode location. Therefore, the real part of the j-function’s peculiar wave is ubiquitously endowed all over normal EEGs paths. We discuss the implications of such correlation in neuroscience and neurology, highlighting how the j-function might stand for the one of the basic oscillations of the brain, and how the still unexplored imaginary part might underlie several physiological and pathological nervous features. SIGNIFICANCE STATEMENT Our results point towards the brain as ubiquitously equipped with j-function’s oscillations, which movements take place on the plane of the complex numbers. It means that there must be, in brain electric activity, also a veiled complex part, which can be assessed with the help of imaginary numbers. The modular j-function provides further dimensions to the real numbers, in order to enlarge their predictive powers: it suggests the possible presence of hidden (functional or spatial) brain extra-dimensions. Furthermore, j-oscillations could be disrupted during pathologies, paving the way to novel approaches to central nervous system’s diseases.
Gait as a Biometric for Person Identification in Video Sequences

The term gait recognition is typically used to signify the identification of individuals in image sequences ‘by the way they walk’. There is an increased interest in gait as a biometric, mainly due to its non-intrusive as well as non-concealable nature. Considerable research efforts are being devoted in the computer vision community to characterize and extract gait dynamics automatically from video. The objective is to use gait as a filter (indicator) to effectively enhance the overall recognition performance of a system that uses multiple modalities. In this proposal, we present (describe) two different gait recognition methods; a non-parametric method that uses the self-similarity plot of a walking sequence as the input feature for classification; and a parametric method that estimates the spatiotemporal parameters of gait (the cadence and stride length) and exploits their linear relationship as a cue for identification. Finally, because carried loads are gait-altering, we also present a motion-based method to detect whether a walking person carries an object (load).
A Validity Analysis of a User Model Employed in a Research Activity Support System

Many students in higher education are required to complete graduate work while learning state-of-the-art technologies and theories in their laboratories. To obtain their objectives efficiently, although it is important that students accumulate, share, and apply "research know-how", these are generally tough tasks because most students graduate without conveying their know-how to juniors. Inspired by the concepts of Knowledge Management (KM) and Human-Agent Interaction (HAI), we previously proposed a system to support the research activity of students. It presents appropriate know-how based on two types of model: the first expresses relationships between tagged information, the second represents features and trends of information retrieved and evaluated by the students. In this paper, we conducted several experiments using the prototype of our developed system: (i) to evaluate the validity of the user model constructed for respective users (students) based on their usage history of the prototype system, and (ii) to discuss whether the user model adequately estimates users' trends in terms of know-how retrieval/evaluation.
TV-Based Caring Videophone System for the Elderly in the Smart Home Environment

A novel videophone system for the elderly-care application is proposed. Based on the detailed analysis of the elderly's physical and psychological characteristics, a TV-based caring videophone system for the elderly is developed: an embedded multimedia device is designed to implement the interactive video and audio processing and IP-based communication, in which TV is adopted as the display terminal to achieve a low-cost but high-quality service. Considering the user's convenience, many personalized designs, such as photo-based address book, photo-click-dialing, and touch pad based remote controller, are developed tomake the proposed videophone systemmore intuitive and easy to use for the elderly. Based on Support Vector Machine (SVM) algorithms, an evaluation model is also developed with the data collected from the embedded multimedia device. It is useful to evaluate the physical and psychological health of the elderly.
Histogram of Oriented Gradients and Normalized Correlation Coefficient based Two-wheeler Detection System using Adaboost

In this paper, we present a new algorithm to detect the two-wheelers riding on people for the normalized cross correlation (NCC) and its application of histogram of oriented gradients (HOGs). Using the NCC algorithm, local ge- ometric information is used as weighting value to the HOG features. Experi- mental results show that the new approach gives higher detection accuracy than that of the conventional method.
Some Evidence for the Cognitive Primacy of Categorization and Its Functional Basis.

Categorization of sound patterns and of objects and events in the real world is basic to learning a language. This thesis was developed by Brown (1956) who termed first language learning "a process of cognitive socialization" involving "the coordination of speech cate gories with categories of the nonlinguistic world [p. 247]. " More recently, Lenneberg (1967) has argued that categorization must be the basic cognitive process: "Thus categorization by a principle, or the formation of an (abstract) concept is apparently prior to and more primitive than the association of a sound pattern with a specific sensory experience. " And, "the abstractness underlying meanings in general . may best be understood by considering concept-formation the primary cognitive process, and naming (as well as acquiring a name) the secondary cognitive process. Concepts . are not so much the product of man's cognition, but conceptualization is the cognitive process itself [pp. 332-333, italics in the original]. " In this view, both differentiation and "interrelating of categories or the perception of and tolerance for transformations" derive from the basic mode of organization which is categorization. Thus, for Lenne berg, words tag cognitive processes and it is words that make these processes seem more static than they actually are. The difference between Brown's (1956) view and Lenneberg's lies in the distinction between categories that exist ready-made in the world outside the child (linguistic and nonlinguistic) and cate gories generated by the child himself. Essentially this is the distinc
Nonlinear cointegration analysis and the environmental Kuznets curve

Recent years have seen a growing literature on the environmental Kuznets curve (EKC) that resorts in a large part to cointegration techniques. The EKC literature has failed to acknowledge that such regressions involve unit root nonstationary regressors and their integer powers (e.g. GDP and GDP squared), which behave differently from linear cointegrating regressions. Here we provide the necessary tools for EKC analysis by deriving estimation and testing theory for cointegrating equations including stationary regressors, deterministic regressors, unit root nonstationary regressors and their integer powers. We consider fully modified OLS estimation, specification tests based on augmented and auxiliary regressions, as well as a sub-sample KPSS type cointegration test. We present simulation results illustrating the performance of the estimators and tests. In the empirical application for CO2 and SO2 emissions for 19 early industrialized countries over the period 1870-2000 we find evidence for an EKC in roughly half of the countries.
FORWARD AND REVERSE MIDDLE EAR FREQUENCY RESPONSES WITH VARIOUS TERMINAL LOADS

An analog network model of the human middle ear is used to study the effect of terminal loads on the middle ear frequency response. A new transformer ratio value is computed and used to improve the model of the middle ear through the use of an ideal transformer. The terminal loads are taken as the loads on either side of the middle ear. The forward and reverse frequency characteristics of the middle ear are computed using various cochlear and outer ear impedances as the terminal load, respectively. The cochlear loads used are an open circuit, a resistive load and an RCL load. The outer ear loads used are an open circuit, a outer ear transmission line model having a constant auditory canal radius and an outer ear transmission line model having a varying auditory canal radius. The components of the cochlear and outer ear loads are computed using previously published anatomical data. The RCL load proved to give the most accurate response for the forward frequency response whereas the open circuit response proved to be the most accurate for the reverse frequency response. The outer ear load models used give minimal accuracy as terminal loads and should thus be improved.
Leadership's Activation of Team Cohesion As A Strategic Asset: An Empirical Simulation

The current study examined the linkage between leadership, team cohesion, andsuperior performance using group process and performance data collected froma strategic management simulation conducted over a four-month period. Resultsshowed that organizational leadership was not directly associated with superiorperformance (SP) of simulated firms. However, leadership was significantly associatedwith team cohesion, which in turn was significantly associated with SF,suggesting that leadership may strengthen performance indirectly by effectuatingkey group process mechanisms. Consistent with the Resource Based View of thefirm, these findings suggest that leader behavior, through its positive impact onthe development of team cohesion, can yield superior performance.