Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Optimization of Iterative Clipping and Filtering for PAPR Reduction in OFDM Systems

Orthogonal frequency division multiplexing (OFDM) offers spectral efficiency advantage, however, it is limited by peak-to-average power (PAPR) problem. The PAPR can be reduced using iterative clipping and filtering (ICF) scheme but requires that the same signals are iteratively clipped with a fixed clipping threshold at different clipping iterations. This method warrants that fast-Fourier transform (FFT)/inverse FFT (IFFT) blocks must be driven in the order of iterations many times to attain a desired PAPR threshold which expends the system power and expands the processing time. Using a second-order cone program, the number of iterations required to attain the desired PAPR threshold was reduced. This optimized ICF (OICF) was later simplified using Lagrange multiplier (LM). In this paper, we apply an adaptive clipping threshold to the LM scheme to improve the performance of the simplified OICF (SOICF). Our results show significant reduction of the PAPR problem compared with the earlier SOICF scheme albeit with some degradation in the bit error ratio (BER) performance that can be under 1.0 dB depending on the chosen clipping threshold. In addition, we also illustrate the results of the performances and the theoretical relationships between the error vector magnitude (EVM) and PAPR, between clipping ratio (CR) and EVM, and lastly the inter-dependencies of EVM, PAPR, the number of OFDM subcarriers, and the CR.
Parameterized Neural Network Language Models for Information Retrieval

Information Retrieval (IR) models need to deal with two difficult issues, vocabulary mismatch and term dependencies. Vocabulary mismatch corresponds to the difficulty of retrieving relevant documents that do not contain exact query terms but semantically related terms. Term dependencies refers to the need of considering the relationship between the words of the query when estimating the relevance of a document. A multitude of solutions has been proposed to solve each of these two problems, but no principled model solve both. In parallel, in the last few years, language models based on neural networks have been used to cope with complex natural language processing tasks like emotion and paraphrase detection. Although they present good abilities to cope with both term dependencies and vocabulary mismatch problems, thanks to the distributed representation of words they are based upon, such models could not be used readily in IR, where the estimation of one language model per document (or query) is required. This is both computationally unfeasible and prone to over-fitting. Based on a recent work that proposed to learn a generic language model that can be modified through a set of document-specific parameters, we explore use of new neural network models that are adapted to ad-hoc IR tasks. Within the language model IR framework, we propose and study the use of a generic language model as well as a document-specific language model. Both can be used as a smoothing component, but the latter is more adapted to the document at hand and has the potential of being used as a full document language model. We experiment with such models and analyze their results on TREC-1 to 8 datasets.
Alcohol use initiation is associated with changes in personality trait trajectories from early adolescence to young adulthood.

BACKGROUND Recent work has demonstrated the codevelopment of personality traits and alcohol use characteristics from early adolescence to young adulthood. Few studies, however, have tested whether alcohol use initiation impacts trajectories of personality over this time period. We examined the effect of alcohol use initiation on personality development from early adolescence to young adulthood. METHODS Participants were male (nmen = 2,350) and female (nwomen = 2,618) twins and adoptees from 3 community-based longitudinal studies conducted at the Minnesota Center for Twin and Family Research. Data on personality traits of Positive Emotionality (PEM; Well-being), Negative Emotionality (NEM; Stress Reaction, Alienation, and Aggression), and Constraint (CON; Control and Harm Avoidance)-assessed via the Multidimensional Personality Questionnaire (MPQ)-and age of first drink were collected for up to 4 waves spanning ages 10 to 32. RESULTS Alcohol use initiation was associated with significant decreases in levels of Well-being and CON traits, most notably Control; and significant increases in levels of all NEM traits, particularly Aggression. In general, the effects of alcohol use initiation on personality traits were moderated by gender and enhanced among those with earlier age of first drink. CONCLUSIONS From early adolescence to young adulthood, alcohol use initiation predicts deviations from normative patterns of personality maturation. Such findings offer a potential mechanism underlying the codevelopment of personality traits and alcohol use characteristics during this formative period of development.
A Capsaicin (8%) Patch in the Treatment of Severe Persistent Inguinal Postherniorrhaphy Pain: A Randomized, Double-Blind, Placebo-Controlled Trial

Background Persistent pain after inguinal herniorrhaphy is a disabling condition with a lack of evidence-based pharmacological treatment options. This randomized placebo-controlled trial investigated the efficacy of a capsaicin 8% cutaneous patch in the treatment of severe persistent inguinal postherniorrhaphy pain. Methods Forty-six patients with persistent inguinal postherniorrhaphy pain were randomized to receive either a capsaicin 8% patch or a placebo patch. Pain intensity (Numerical Rating Scale [NRS 0–10]) was evaluated under standardized conditions (at rest, during movement, and during pressure) at baseline and at 1, 2 and 3 months after patch application. Skin punch biopsies for intraepidermal nerve fiber density (IENFD) measurements were taken at baseline and 1 month after patch application. Quantitative sensory testing was performed at baseline and at 1, 2, and 3 months after patch application. The primary outcome was comparisons of summed pain intensity differences (SPIDs) between capsaicin and placebo treatments at 1, 2 and 3 months after patch application (significance level P<0.01). Results The maximum difference in SPID, between capsaicin and placebo treatments, was observed at 1 month after patch application, but the pain reduction was not significant (NRS, mean difference [95% CI]: 5.0 [0.09 to 9.9]; P = 0.046). No differences in SPID between treatments were observed at 2 and 3 months after patch application. Changes in IENFD on the pain side, from baseline to 1 month after patch application, did not differ between capsaicin and placebo treatment: 1.9 [−0.1 to 3.9] and 0.6 [−1.2 to 2.5] fibers/mm, respectively (P = 0.32). No significant changes in sensory function, sleep quality or psychological factors were associated with capsaicin patch treatment. Conclusions The study did not demonstrate significant differences in pain relief between capsaicin and placebo treatment, although a trend toward pain improvement in capsaicin treated patients was observed 1 month after patch application. Trial Registration Clinicaltrialsregister.eu 2012-001540-22 ClinicalTrials.gov NCT01699854
Dual-tree Complex Wavelets Transforms for Image Denoising

The ridgelet transform was developed over several years to break the limitations of the wavelet transform. In this paper, a novel image denoising algorithm is proposed that incorporates the dual-tree complex wavelets into the ordinary ridgelet transform. The approximate shift invariant property of the dual-tree complex wavelet and the high directional sensitivity of the ridgelet transform make the new method a very good choice for image denoising. We apply the digital complex ridgelet transform to the denoising of some standard images embedded in white noise. A simple hard thresholding of the complex ridgelet coefficients is used. Experimental results show that by using dual-tree complex ridgelets, our algorithms obtain higher peak signal to noise ratio (PSNR) for all the denoised images with different noise levels. The new modified ridgelet denoising algorithm - MRDA is better than Wiener2 and the classical CRD A ridgelet image denoising. Complex ridgelet could be applied to curvelet image denoising as well.
Contents of Ag and other metals in food-contact plastics with nanosilver or Ag ion and their migration into food simulants

ABSTRACT Six nanosilver-labelled products and five silver ion (Ag+)-labelled products were investigated to measure the migration of Ag from food-contact plastics, including nanosilver into various food simulants. The products were obtained in Japanese markets in 2012. Zinc (Zn), another major antimicrobial agent, and three harmful metals, cadmium (Cd), lead (Pb) and arsenic (As), were also examined. Ag and Zn were detected in all six nanosilver products at concentrations of 21–200 and 8.4–140 mg kg−1, respectively. These metals were also detected in all five Ag+ products at the same level as nanosilver products. Cd, Pb and As were not detected in any sample. Migrations of Ag and Zn were highest in 4% acetic acid, but also observed in water and 20% ethanol. Big differences were not observed in the migration ratio between nanosilver products and Ag+ products. The ultrafiltration experiments suggested that the Ag that migrated from nanosilver products into 4% acetic acid was in its ionic form, while that into water and 20% ethanol was in its nanoparticle form.
Exploring the properties of the phases of QCD matter - research opportunities and priorities for the next decade

This document provides a summary of the discussions during the recent jointQCD Town Meeting at Temple University of the status of and future plans for theresearch program of the relativistic heavy-ion community. A list of compellingquestions is formulated, and a number of recommendations outlining the greatestresearch opportunities and detailing the research priorities of the heavy-ioncommunity, voted on and unanimously approved at the Town Meeting, arepresented. They are supported by a broad discussion of the underlying physicsand its relation to other subfields. Areas of overlapping interests with the"QCD and Hadron Structure" ("cold QCD") subcommunity, in particular therecommendation for the future construction of an Electron-Ion Collider, areemphasized. The agenda of activities of the "hot QCD" subcommunity at the TownMeeting is attached.
Mass transfer between double white dwarfs

Three periodically variable stars have recently been discovered (V407 Vul, P=9.5 min; ES Cet, P=10.3 min; RX J0806.3+1527, P=5.3 min) with properties that suggest that their photometric periods are also their orbital periods, making them the most compact binary stars known. If true, this might indicate that close, detached, double white dwarfs are able to survive the onset of mass transfer caused by gravitational wave radiation and emerge as the semi-detached, hydrogen-deficient stars known as the AM CVn stars. The accreting white dwarfs in such systems are large compared to the orbital separations. This has two effects. First, it makes it likely that the mass-transfer stream can hit the accretor directly. Secondly, it causes a loss of angular momentum from the orbit which can destabilize the mass transfer unless the angular momentum lost to the accretor can be transferred back to the orbit. The effect of the destabilization is to reduce the number of systems which survive mass transfer by as much as one hundredfold. In this paper we analyse this destabilization and the stabilizing effect of a dissipative torque between the accretor and the binary orbit. We obtain analytical criteria for the stability of both disc-fed and direct impact accretion, and we carry out numerical integrations to assess the importance of secondary effects, the chief one being that otherwise stable systems can exceed the Eddington accretion rate. We show that to have any effect upon survival rates, the synchronizing torque must act on a time-scale of the order of 1000 yr or less. If synchronization torques are this strong, then they will play a significant role in the spin rates of white dwarfs in cataclysmic variable stars as well.
Online meeting recognition in noisy environments with time-frequency mask based MVDR beamforming

This paper addresses our new online meeting recognition prototype, which works even in noisy environments. For speech enhancement, we employ a mask-based minimum variance distortionless response (MVDR) beamformer, which has recently shown to be a successful front-end for a state-of-the-art deep neural network (DNN)-based automatic speech recognition (ASR) system. To ensure more accurate and computationally efficient mask estimation for estimating steering vectors of a MVDR beamformer, which is challenging especially in an adverse environment, this work employs a probabilistic spatial dictionary. The dictionary consists of a pre-trained probability distribution of source location features for each of speaker location candidates. This dictionary significantly simplifies the problem to be solved, and therefore, realizes an accurate and efficient mask estimation. Our new prototype worked with stability with a latency of 3–5 seconds in a real exhibition situation. The quantitative evaluation results will be reported.
A Set of Microbenchmarks for Measuring OpenMP Task Overheads

Asynchronous tasks make it easy to express the parallelism in a broad variety of computations and are especially useful for writing parallel applications with irregular and/or dynamic workloads. Their introduction into the OpenMP specification has greatly extended the scope of this API. Yet the body of benchmarks using OpenMP tasks remains minimal. The EPCC OpenMP Microbenchmarks provide measurements of overheads incurred by OpenMP constructs in version 2.0-compliant implementations. These microbenchmarks are widely used to explore the behavior of OpenMP constructs on a given platform. To thoroughly test an OpenMP 3.0 implementation, we have extended these microbenchmarks by twenty-one new microbenchmarks that measure overheads incurred by various common uses of OpenMP tasks, including task synchronization. We include evaluations of both commercial and open source implementations of OpenMP tasks on various multicore platforms.
Power and resistance: leading change in medical education

A key role for educational leaders within undergraduate medical education is to continually improve the quality of education; global quality health care is the goal. This paper reports the findings from a study employing a power model to highlight how educational leaders influence the development of undergraduate medical curricula and the resistance they encounter related to this activity. Sixteen educational leaders at a medical university in Northern Europe were purposefully sampled and interviewed through semi-structured interviews. The results indicate that the educational leaders are feeling powerless when it comes to engaging their colleagues in the process of developing medical education. As a result, these leaders appear having to create a ‘vicarious legitimacy’; legitimacy connected to other areas than education, such as research or clinic. Research results from this study can be used to develop faculty development programs for health education leaders on national and international levels.
FlexRAM: Toward an advanced Intelligent Memory system

Major advances in Merged Logic DRAM (MLD) technology coupled with the popularization of memory-intensive applications provide fertile ground for architectures based on Intelligent Memory (IRAM) or Processors-in-Memory (PIM). The contribution of this paper is to explore one way to use the current state-of-the-art MLD technology for general-purpose computers. To satisfy requirements of general purpose and low programming cost, we place the PIM chips in the memory system and let them default to plain DRAM if the application is not enabled for intelligent memory. Since wide usability is crucial, we identify and analyze a range of real applications for PIM. Based on the requirements of these applications and current technological constraints, we design a PIM chip and a PIM-based memory system. We call the chip FlexRAM. We describe FlexRAMs design and floorplan, and the resulting memory system. Evaluation of the system through simulations shows that 4 FlexRAM chips often allow a workstation to run 25-40 times faster.
Shape Representation and Recognition in High Dimensional Feature Space

We present a novel approach for shape representation using support vector domain description (SVDD). The shape contour of an object is mapped to spherical surface in high dimensional feature space, where similar contours with different size look like concentric spheres in the learned feature/kernel space. Shape matching in cluttered image, therefore, can be seen as finding the corresponding super spherical surface after the nonlinear transformation. The shape model, which consists of several Support Vectors (SVs), is partially invariant to contour scaling and rotation. A coarse-to-fine strategy is then adopted for shape matching in the forward matching process. Experimental results show that the approach is robust and suitable for shape-based image retrieval. In addition, our approach enables the user to fast construct the template shape by a small quantity of points which represent the shape roughly. The precise shape contour is not needed. It can greatly improve the human-machine interaction friendliness of practical image retrieval systems. Though our analysis is based on 2D shapes, this idea can be easily extended to the 3D shapes.
Advances in nonverbal communication : sociocultural, clinical, esthetic, and literary perspectives

Part 1 Theoretical research perspectives in nonverbal communication studies: the interaction of visual and verbal features in human communication, Juergen Streeck and Mark L. Knapp auditory communication - non-verbal, pre-verbal and co-verbal, Roger W. Wescott the audible-visual approach to speech as basic to nonverbal communication research, Fernando Poyatos prolegomenon to the elaboration of a new discipline - ethnogestics, Bernard Koechlin the rational of gestures in the West - a history from the 3rd to the 13th centuries, Jean-Claude Schmitt. Part 2 Social and clinical aspects of nonverbal interaction: does nonverbal communication cause happiness? , Michael Argyle the dissociation between motor and symbolic movements in coverbal behaviour, Uri Hadar the relevance of logical formalisms for nonverbal clinical observations, Francis Lowenthal children's artificial limbs - intrapersonal and interpersonal implications, Paul McDonnel. Part 3 Cultural and crosscultural perspectives on gestures: six characters in search of a gesture - Chinese graphs and corporal behaviour, Yau Shun-chiu facial and manula components of Italian symbolic gestures, Pio Enrico Ricci Bitti the veiled face and expressiveness among the Tuaregs, Helene Hawad-Claudot many gestures, many meanings - nonverbal diversity in Israel, Raphael Schneller. Part 4 Nonverbal communication in literature - advancements in literary anthropology: nonverbal communication in the classics - research opportunities, James P. Holoka affect displays in the epic poetry of Homer, Vergil and Ovid, Donald Lateiner nonverbal expressiveness in late Greek epic - Quintus of Smyrna and Nonnus, Ronald Newbold describing nonverbal behaviour in the "Odyssey" - scenes and verbal frames as translation problems, Hans J. Vermeer paralanguage and quasiparalinguistic sounds as a concern of literary analysis, Fernando Poyatos. Part 5 Art and literature - the visual recreaction: visual meaning in Greek drama - Sophocles' "Ajax" and the art of dying, Herbert Golder. Part 6 New academic perspectives on nonverbal communication: the interdisciplinary teaching of nonverbal communication - academic and social implications, Fernando Poyatos.
Augmented Feature Fusion for Image Retrieval System

The performance of current image retrieval system is largely determined by the quality and discriminative capability of features. Therefore, using what features and how to effectively combine the power of appropriate features are important in the system. We adopt the reciprocal neighbor based graph fusion approach for feature fusion. More importantly, we explicitly augment the original approach with the following two strategies: 1) we investigate the most suitable feature combinations on various datasets, including the deep learning feature, which has been popular for image retrieval recently; 2) we further improve the robustness of original graph fusion approach by the SVM prediction strategy. Extensive experiments are performed on three benchmark datasets including UKbench, Holidays and Corel-5K, to validate the impressive performance of the augmented feature fusion. On the three datasets, our retrieval system significantly outperforms several existing algorithms. For example on UKbench, the N-S score of our approach achieves 3.88, which is one of the highest accuracies to the best of our knowledge.
Attitudinal and behavioral consequences of work‐family conflict and family‐work conflict

Purpose – The purpose of this paper is to develop and test a conceptual model to examine the effects of work‐family conflict, family‐work conflict, and emotional exhaustion on job performance and turnover intentions. The paper also aims to investigate the role of gender as a moderator of the posited relationships.Design/methodology/approach – A sample of frontline hotel employees in Turkey serves as the study setting. Data were collected via self‐administered questionnaires. A total of 723 usable responses were obtained.Findings – The results show that employees facing conflicts originating from their work (family) and family (work) roles become emotionally exhausted. These two forms of interrole conflicts are also significant predictors of frontline employees' turnover intentions. Gender moderates several of the relationships proposed in this paper.Practical implications – Turkish hotels will benefit from establishing a family‐supportive work environment to lessen the detrimental impact of conflicts in t.
Mining sentiment terminology through time

The correspondence between sentiment terminology and the active language used for expressing opinions is a crucial prerequisite for effective sentiment analysis. Mining sentiment terminology includes the detection of new opinion words as well as inferring their polarities. In this paper, we first propose a novel approach based on the interchangeability characteristic of words to detect new opinion words through time. We then show that the current non-time-based polarity inference approaches may assign opposite polarity to the same opinion word at different times. To tackle this issue, we consider the polarity scores computed at different times as polarity evidences (with the possibility of flawed evidences) and combine them to compute a globally correct polarity score for each opinion word. The experiments show that our approach is effective both in terms of the quality of the discovered new opinion words as well as its ability in inferring their polarities through time. Furthermore, we show the application of mining sentiment terminology through time in the sentiment classification (SC) task. The experiments show that mining more recent new opinion words leads to greater improvement in the performance of SC. To the best of our knowledge, this is the first work that investigates "time" as an important factor in mining sentiment terminology.