Miracle-dz/UniFAR-FTUs huggingface dataset:
Fingerprint Segmentation Based on Improved Active Contour

Snake (Active Contour)Model, introduced by Kass in 1987, is a dynamic curve model with energy-minimizing. Snake algorithm, which has advantages in extracting target object from a certain region, is an effective method in image segmentation. Based on the analysis of the snake model and the regional information of the edges of the fingerprint images, an improved active contour for the segmentation of fingerprints is presented in this paper. In this paper the limitations of the segmentation of fingerprint images using the snake as suggested in [5] are pointed out. The authors present a solution to the fingerprint segmentation by replacing the standard external energy in the snake energy balance equation with the difference between peaks in the directional histogram and gray variance, and a new external energy that is applied to control the snake outward expansion or inward contraction. This method has been tested by a large number of fingerprint images from different sources, and is found to be more accurate and robust.
2.5 GHz Wide Band Linear Amplifier with Feedforward Lineariser on a Board

A wide band feedforward lineariser amplifier we have developed is described. In particular, we report the IM3 improvement obtained without automatic adaptive control circuits, indicating the possibility of realizing small, low-cost products. We designed a lineariser amplifier for 2.5 GHz band to demonstrate the effectiveness of our approach and measurement revealed the wide band linearising capability of over 100 MHz.
Self-reported and objectively measured activity related to biomarkers using NHANES.

PURPOSE The purpose of this study was to examine the independent associations of self-reported and objectively measured (using accelerometers) moderate to vigorous physical activity (MVPA) with physiological and anthropometric biomarkers in a nationally representative sample of U.S. adults. METHODS Data from the cross-sectional National Health and Nutrition Examination Survey 2003-2006 data were analyzed. Adults 20 yr and older (N=5797) with self-reported PA and 4 d or more of accelerometer data were included in the analyses. Pregnant or lactating women were excluded. Outcomes were blood pressure, body mass index, waist circumference, triceps and subscapular skinfolds, cholesterol, triglyceride, C-reactive protein, homocysteine, and insulin resistance and hyperinsulinemia indices. RESULTS Objectively measured MVPA displayed stronger independent associations with the biomarkers than did self-reported MVPA, even after adjusting for sociodemographic and health factors (adjusted Wald F values=3.9-85.6, P<0.05-0.0001). Self-reported and objectively measured MVPA were independently associated with skinfold measures, HDL, and C-reactive protein when both were included in the model. CONCLUSIONS Objectively measured MVPA displayed stronger associations with physiological and anthropometric biomarkers than self-reported MVPA. However, self-reported and objectively measured MVPA appear to capture distinct aspects of PA that are independently associated with certain biomarkers. Further understanding of the distinct contributions of self-reported and objectively measured PA to health outcomes could help to better identify optimal activity level and pattern.
Montclair State University Digital Montclair State University Digital Commons Commons Spiritual Bypass: A Preliminary Investigation Spiritual Bypass: A Preliminary Investigation

The phenomenon of spiritual bypass has received limited attention in the transpersonai psychoiogy and counseiing iiterature and has not been sub-jected to empirical inquiry. This study examines the phenomenon of spirituai bypass by considering how spirituaiity, mindfuiness, aiexithymia (emotionai restrictiveness), and narcissism wori< together to influence depression and anxiety among coiiege students. Resuits suggested that mindfuiness and aiexithymia accounted for variance in depression beyond what is accounted for by spirituaiity and that aii 3 factors (mindfuiness, aiexithymia, and narcissism) accounted for variance in anxiety beyond what is accounted for by spirituaiity. impiications for counseiors are provided.
CALCULATION OF THE DIELECTRIC PROPERTIES OF BIOLOGICAL TISSUE USING SIMPLE MODELS OF CELL PATCHES

The measurement of the dielectric properties of biological tissue is of increasing scientific relevance. Models for the comprehension of the dielectric properties at various frequencies have been successfully set up. However, students often have problems in understanding the effects taking place on cellular level which lead to the observed dispersion. A numerical model of a biological tissue brick composed of single cells (micron-dimensions) between two plate electrodes is presented in this study. An electrical current in a range of 1 Hz to 3 GHz was applied to the electrodes and hence to the tissue model. Using an equivalent series circuit of a resistor and a capacitor it is possible to calculate the effective equivalent dielectric properties of the whole tissue model. The results show an increasing conductivity and decreasing permittivity with increasing frequency. This corresponds to experimental results obtained with different biological tissues.
TCR-inducible PLZF transcription factor required for innate phenotype of a subset of γδ T cells with restricted TCR diversity

Some γδ and αβ T lymphocytes exhibit an “innate” phenotype associated with rapid cytokine responses. The PLZF transcription factor is essential for the innate phenotype of NKT cells. This report shows that PLZF is likewise responsible for the innate, NKT-like phenotype of Vγ1+Vδ6. 3/Vδ6. 4+ cells. TCR cross-linking induced PLZF expression in all polyclonal immature γδ thymocytes, suggesting that agonist selection might be required for PLZF induction. Transgenic expression of Vγ1Vδ6. 4 TCR was sufficient to support the development of large numbers of PLZF+ T cells, further supporting the importance of the TCR for PLZF induction. Interestingly, expression of this TCR transgene led to the development of spontaneous dermatitis.
Click-through-Based Word Embedding for Large Scale Image Retrieval

Similarity learning between textual query and visual images is a fundamental problem in large scale image retrieval. Traditional methods primarily rely on the surrounding texts of images for image search. However, as the volume of images on the web grows to new levels, it is likely that the surrounding textual information is noisy or even unavailable. Thus, determining how to bridge the semantic gap between textual queries and visual images remains an open problem. Inspired by the success of neural network language models and the usage of click-through data for search engines, we attempt to solve the image retrieval problem by learning the word embedding for the query words in the image feature space through modeling the probability distribution over images, conditioned on a given query. This model is called click-through-based word embedding (CWE), and it renders a direct comparison between textual query and visual image feasible. We conducted several experiments on the Microsoft Clickture dataset and found that CWE outperformed others in terms of both scalability and accuracy.
Energy Introspector : Standard Physical Library Interface for Full-System Microarchitecture and Multi-Physics Simulations

Modeling and simulation of future microarchitectures and applications require more than performance measurement and estimation. Analysis must be “holistic” including power, energy, thermal, and reliability concerns since these physical constraints and their coupled interactions have become major performance determinants of processors. Various models of different physical phenomena have been developed and released in tools such as 1) power models in Cacti/McPAT [8], [18], Orion/DSENT [5], [17], DRAMsim [10], 2) thermal models of HotSpot [4] and 3D-ICE [14], 3) wear models including negative-bias temperature instability (NBTI), time-dependent dielectric breakdown (TDDB) [15], [16], and 4) other proprietary or custom models [2], [19]. However, they are not generally integrated with microarchitecture simulators. We note that as a general practice these models are independently employed, for example via the prevalent use of offline trace-driven simulations, in which a trace generated from a simulator or tool drives another modeling tool as independent simulations shown in Fig. 1-(a). Such a practice is oblivious to the interacting nature of multiple physical phenomena and fundamentally limits studies of advanced research problems lying at the intersection of performance, energy/power, thermal/cooling, and reliability. To address this, we have been developing the Energy Introspector (EI) [11], [12] and integrating it with different simulation frameworks including Manifold [20], MacSim [7], Structural Simulation Toolkit (SST) [9], and IBM POWER7+ Architecture proprietary simulators. It is our position that the Energy Introspector will enable the holistic analysis which future processors will require. The EI has proven its ability to work with multiple simulation infrastructures, and its unique capability demonstrates a path forward for community-wide adoption. In this paper, we report on the design and motivate the use of an integrated physical modeling library interface, central to building full-system application-microarchitecture-physics co-simulation environment.
Non-clairvoyant Scheduling of Batched Parallel Jobs to Minimize Mean Response Time

This paper presents a new scheduling algorithm RAD, and shows that RAD efficiently schedules batched parallel jobs on multiprocessors. An early result by Deng et al. shows that Dynamic Equi-partitioning is 4-competitive for mean response time when the number of jobs is not more than the number of processors. Then, in STOC 97, Edmonds et al. show that the mean response time obtained by Equi-partitioning is 2 + √ 3 ≈ 3.74 competitive for jobs with multiple phases of arbitrary nondecreasing and sublinear speedup functions. We consider more realistic DAG job model, and schedule them without any prior information of jobs. Our main result shows that, RAD is 3-competitive with respect to mean response time for any batched DAG jobs under arbitrary workload. To the best of our knowledge, RAD offers the best mean response time bound for the schedule of batched parallel jobs. Furthermore, we offer a general technique for the proof of the mean response time for batched parallel jobs. We apply this technique in the analysis of Equi-partitioning. By using a much simpler proof, we can achieve the same bound 2 + √ 3 as Edmonds et al. Moreover, their old analysis is restricted to the class of jobs with multiple phases of arbitrary nondecreasing and sublinear speedup functions, while our new result is applicable to arbitrary DAG jobs. Technical Report TR-07-02, Center for Advanced Information System, School of Computer Engineering, Nanyang Technological University, Singapore. The authors’ e-mail addresses are: {heyu0006, sunh0007, hsu}@ntu.edu. sg This research was supported in part by Singapore-MIT Alliance.
Equine Herpesvirus Protein E10 Induces Membrane Recruitment and Phosphorylation of Its Cellular Homologue, Bcl-10

v-E10, a caspase recruitment domain (CARD)-containing gene product of equine herpesvirus 2, is the viral homologue of the bcl-10 protein whose gene was found to be translocated in mucosa-associated lymphoid tissue (MALT) lymphomas. v-E10 efficiently activates the c-jun NH2-terminal kinase (JNK), p38 stress kinase, and the nuclear factor (NF)-κB transcriptional pathway and interacts with its cellular homologue, bcl-10, via a CARD-mediated interaction. Here we demonstrate that v-E10 contains a COOH-terminal geranylgeranylation consensus site which is responsible for its plasma membrane localization. Expression of v-E10 induces hyperphosphorylation and redistribution of bcl-10 from the cytoplasm to the plasma membrane, a process which is dependent on the intactness of the v-E10 CARD motif. Both membrane localization and a functional CARD motif are important for v-E10–mediated NF-κB induction, but not for JNK activation, which instead requires a functional v-E10 binding site for tumor necrosis factor receptor–associated factor (TRAF)6. Moreover, v-E10–induced NF-κB activation is inhibited by a dominant negative version of the bcl-10 binding protein TRAF1, suggesting that v-E10–induced membrane recruitment of cellular bcl-10 induces constitutive TRAF-mediated NF-κB activation.
Transient peak currents in permanent magnet synchronous motors for symmetrical short circuits

To enable constant-power areas with permanent magnet synchronous motors, flux weakening has to be applied. In that mode, the inverter protection measure, e.g. in case of overcurrent, is a crucial point, since the open-circuit induced terminal voltage may exceed the allowed inverter limit. That is why a symmetrical short circuit (SSC) is currently favoured as alternative protection measure. Though the steady state short circuit current may be acceptable, this contribution shows that the transient current may seriously exceed the allowed limit. The worst case SSC will not occur during flux weakening but in regenerative operation at rated speed. Such high peak currents include the risk of permanent demagnetization of the magnets. As a result, SSC should applied only during flux weakening as protection measure, while for the lower speed range the conventional converter shut down is proposed
Fast Variational Sparse Bayesian Learning With Automatic Relevance Determination for Superimposed Signals

In this work, a new fast variational sparse Bayesian learning (SBL) approach with automatic relevance determination (ARD) is proposed. The sparse Bayesian modeling, exemplified by the relevance vector machine (RVM), allows a sparse regression or classification function to be constructed as a linear combination of a few basis functions. It is demonstrated that, by computing the stationary points of the variational update expressions with noninformative (ARD) hyperpriors, a fast version of variational SBL can be constructed. Analysis of the computed stationary points indicates that SBL with Gaussian sparsity priors and noninformative hyperpriors corresponds to removing components with signal-to-noise ratio below a 0 dB threshold; this threshold can also be adjusted to significantly improve the convergence rate and sparsity of SBL. It is demonstrated that the pruning conditions derived for fast variational SBL coincide with those obtained for fast marginal likelihood maximization; moreover, the parameters that maximize the variational lower bound also maximize the marginal likelihood function. The effectiveness of fast variational SBL is demonstrated with synthetic as well as with real data.
Quantifying Spatiotemporal Properties of Vocal Fold Dynamics Based on a Multiscale Analysis of Phonovibrograms

In order to objectively assess the laryngeal vibratory behavior, endoscopic high-speed cameras capture several thousand frames per second of the vocal folds during phonation. However, judging all inherent clinically relevant features is a challenging task and requires well-founded expert knowledge. In this study, an automated wavelet-based analysis of laryngeal high-speed videos based on phonovibrograms is presented. The phonovibrogram is an image representation of the spatiotemporal pattern of vocal fold vibration and constitutes the basis for a computer-based analysis of laryngeal dynamics. The features extracted from the wavelet transform are shown to be closely related to a basic set of video-based measurements categorized by the European Laryngological Society for a subjective assessment of pathologic voices. The wavelet-based analysis further offers information about irregularity and lateral asymmetry and asynchrony. It is demonstrated in healthy and pathologic subjects as well as for a surgical group that was examined before and after the removal of a vocal fold polyp. The features were found to not only classify glottal closure characteristics but also quantify the impact of pathologies on the vibratory behavior. The interpretability and the discriminative power of the proposed feature set show promising relevance for a computer-assisted diagnosis and classification of voice disorders.
Improving electrical conductivity of poly methyl methacrylate by utilization of carbon nanotube and CO2 laser

In this work, the electrical surface conductivity enhancement of injection-molded multiwalled carbon nanotube (MWCNT)/poly(methyl methacrylate) (PMMA) nanocomposite by using CO2 laser processing was studied. Variable input factors are considered as MWCNT concentration (in three levels 0.5, 1, and 1.5 wt %), the laser feed angle with the flow direction (in five levels 08 ,3 08 ,4 58 ,7 58, and 908), and the cavity machining method that were produced by electrodischarge machining and computer numerical control milling with finishing process. The studies show that the irradiation of laser and utilization of covering gas could enhance the CNT-CNT contacts and the surface electrical conductivity. The morphology of laser-irradiated surface by using scanning electron microscope certified that the conductive network generated from CNT-CNT contacts can transfer the electrical current. The findings clearly show that the laser feed angle with the flow direction influenced the electrical conductivity. The maximum conductiv- ity ( 5.310 3 10 24 S) was observed at 758. V C 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 42671.
The ray attack, an inefficient trial to break RSA cryptosystems

The basic properties of RSA cryptosystems and some classical attacks on them are described. Derived from geometric properties of the Euler functions, the Euler function rays, a new ansatz to attack RSA cryptosystems is presented. A resulting, albeit inefficient, algorithm is given. It essentially consists of a loop with starting value determined by the Euler function ray and with step width given by a function $\omega_e(n)$ being a multiple of the order $\mathrm{ord}_n(e)$, where $e$ denotes the public key exponent and $n$ the RSA modulus. For $n=pq$ and an estimate $r<\sqrt{pq}$ for the smaller prime factor $p$, the running time is given by $T(e,n,r) = O((r-p)\ln e \ln n \ln r). $
Enforcement of State Indoor Tanning Laws in the United States

Introduction Twenty-eight US states have passed legislation for indoor tanning facilities. To our knowledge, whether these state laws are actually enforced has not been evaluated previously in all 28 states. Therefore, we interviewed key informants in these states to assess enforcement practices. Methods Two trained interviewers used a structured survey instrument to interview 28 key informants who were knowledgeable about enforcement practices for laws regarding indoor tanning. Respondents provided information specific to the most populous city in their states. Results Licensure for indoor tanning businesses was required in 22 of the 28 cities. Slightly less than half of the cities gave citations to tanning facilities that violated state law. Approximately 32% of the cities did not inspect indoor tanning facilities for compliance with state law, and another 32% conducted inspections less than annually. Of those cities that inspected at all, most conducted unannounced inspections. Conclusion The relatively low rates of annual inspections and citations are of concern. We recommend that future studies assess whether legislation, enforcement practices, or a combination of the 2 affects the practices of indoor tanning facilities or of consumers.
On Scaling Laws of Diversity Schemes in Decentralized Estimation

This paper is concerned with decentralized estimation of a Gaussian source using multiple sensors. We consider a diversity scheme where only the sensor with the best channel sends their measurements over a fading channel to a fusion center, using the analog amplify and forwarding technique. The fusion centre reconstructs a minimum mean squared error (MMSE) estimate of the source based on the received measurements. A distributed version of the diversity scheme where sensors decide whether to transmit based only on their local channel information is also considered. We derive asymptotic expressions for the expected distortion (of the MMSE estimate at the fusion centre) of these schemes as the number of sensors becomes large. For comparison, asymptotic expressions for the expected distortion for a coherent multiaccess scheme and an orthogonal access scheme are derived. It is seen that as opposed to the coherent multiaccess scheme and the orthogonal scheme (where the expected distortion decays as 1/M, M being the number of sensors), the expected distortion decays only as 1/ln(M) for the diversity schemes. This reduction of the decay rate can be seen as a tradeoff between the simplicity of the diversity schemes and the strict synchronization and large bandwidth requirements for the coherent multiaccess and the orthogonal schemes, respectively. We study for the diversity schemes, the optimal power allocation for minimizing the expected distortion subject to average power constraints. The effect of optimizing the probability of transmission on the expected distortion in the distributed scenario is also studied. It is proved that for Rayleigh fading optimal sensor transmit power allocation achieves the same asymptotic scaling law as the constant power allocation scheme, whereas it is observed that optimizing the sensor transmission probability (with or without optimal power allocation) in the distributed case makes very little difference to the asymptotic scaling laws.
A novel approach to fault diagnosis in multicircuit transmission lines using fuzzy ARTmap neural networks

The work described in this paper addresses the problems of fault diagnosis in complex multicircuit transmission systems, in particular those arising due to mutual coupling between the two parallel circuits under different fault conditions; the problems are compounded by the fact that this mutual coupling is highly variable in nature. In this respect, artificial intelligence (AI) technique provides the ability to classify the faulted phase/phases by identifying different patterns of the associated voltages and currents. In this paper, a Fuzzy ARTmap (Adaptive Resonance Theory) neural network is employed and is found to be well-suited for solving the complex fault classification problem under various system and fault conditions. Emphasis is placed on introducing the background of AI techniques as applied to the specific problem, followed by a description of the methodology adopted for training the Fuzzy ARTmap neural network, which is proving to be a very useful and powerful tool for power system engineers. Furthermore, this classification technique is compared with a Neural Network (NN) technique based on the error backpropagation (EBP) training algorithm, and it is shown that the former technique is better suited for solving the fault diagnosis problem in complex multicircuit transmission systems.
The series elastic componet of muscle

The properties have been examined of the undamped elastic component which lies in series with the contractile component of muscle. At higher tensions the elasticity is normal; the form of the load-extension curve as a whole must be largely due to the statistical distribution of tendon length in different fibres. The mechanical (elastic) energy of a contracting muscle is expressed graphically as a function of its tension. Even under completely isometric conditions this elastic energy is a significant fraction of the heat production in a twitch.