Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum visfatin in relation to insulin resistance and markers of hyperandrogenism in lean and obese women with polycystic ovary syndrome.

BACKGROUND Visfatin, a protein secreted by adipose tissue, is suggested to play a role in pathogenesis of insulin resistance. In polycystic ovary syndrome (PCOS), insulin resistance might be involved in the development of endocrine and metabolic abnormalities. The aim of the study was to asses the relation between serum visfatin concentration and insulin sensitivity and markers of hyperandrogenism in lean and obese PCOS patients. METHODS The study group consisted of 70 women with PCOS (23 lean and 47 obese) and 45 healthy women (25 lean and 20 obese). Euglycemic hyperinsulinemic clamp and the measurements of serum visfatin, sex hormones were performed. RESULTS The PCOS group had lower insulin sensitivity (P=0.00049) and higher serum visfatin (P=0.047) in comparison to the control group. The decrease in insulin sensitivity was present in both the lean (P=0.019) and obese (P=0.0077) PCOS subjects, whereas increase in serum visfatin was observed only in lean PCOS subjects (P=0.012). In the whole group, serum visfatin was negatively correlated with insulin sensitivity (r=-0.27, P=0.004). This relationship was also observed in the subgroup of lean (r=-0.30, P=0.038), but not obese women. Additionally, in lean women, visfatin was associated with serum testosterone (r=0.47, P=0.002) and free androgen index (r=0.48, P=0.002), independently of other potential confounding factors. CONCLUSIONS Visfatin is associated with insulin resistance and markers of hyperandrogenism in lean PCOS patients.
Improvement of Semantic Similarity Computation in Battlefield Information Services Matching

In Battlefield Information Services (BISs) matching, the concept similarity computation plays an important role. Because the influence of semantic asymmetry has not been considered in current concept similarity computation, the computation result is not accurate. To enhance the accuracy of the concept similarity computation, the similarity computation was improved by adding the direction factor and regulatory factor on the basis of the current research. Finally, the feasibility of the improved concept similarity computation can reflect semantic relationship between concepts more truly and the computation result is more in line with the objective really.
First-episode depression: Diffusion tensor imaging of deep white matter

The value of diffusion tensor imaging (DTI) was investigated in the cerebral white matter microstructural abnormalities in patients with first-episode depression. Thirteen patients with first-episode depression and fourteen age- and gender-matched healthy volunteers were performed DTI. The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) of prefrontal lobe deep white matter, the parahippocampal gyrus, the genu, body and splenium of the corpus callosum were recorded. FA and ADC in the deep white matter of frontal lobe, the right parahippocampal gyrus and the genu of the corpus callosum in the depression group were different from those of control group (P<;0.05). There were no significant differences of FA and ADC in the left parahippocampal gyrus and the body and splenium of the corpus callosum between two groups (P>0.05). DTI was valuable in detection of microstructural abnormalities of the white matter in patients with first-episode depression. The microstructural abnormalities in the deep white matter of frontal lobe, the right side of the parahippocampal gyrus and genu of the corpus callosum may be the neurobiological basis of first-episode depression.
T A Simulation Study on the Wired-Equivalent Capacity of Ad Hoc Networks

In this paper we demonstrate the concept of wired-equivalent capacity in ad-hoc networks through a large-scale simulation study. A capacity model that mimics conventional experience (e.g. on wired, infrastructured networks) is proposed under a specific, yet realistic and user-oriented, assumption of the maximum fair usage. Capacity is then the maximum throughput capacity per node under which packet loss is similar to that of a conventional wired network, for all nodes. We show how this capacity metric becomes predictable inside ad-hoc networks using a simple power-law while delay is bounded. I. INTRODUCTION he inherent flexibility of ad hoc networks brings uncertainties regarding network's performance. If we add to this the unreliability of the underlying wireless technologies, the problem of predicting the performance of the network and delivering quality-of-service becomes complex. A typical example is TCP performance, where dramatic sub-efficiencies were reported [1]. When considering real-time applications, the results can be even worse attending to the dynamics of a mobile ad hoc network. This paper looks at capacity of ad hoc networks from an empirical point-of-view, allowing a node to estimate the expected behaviour of the ad-hoc network, both in an isolated scenario and in as a stub network. To our knowledge, all studies regarding ad hoc networks capacity focus on either scaling laws under very specific assumptions or very scope-limited studies (e.g. [2,3,4,5]). In these studies, the proposed definitions of capacity are considered too scenario-specific. Gupta and Kumar [2] derived a scaling law for the throughput capacity of a network modelled after static nodes, randomly distributed in space with random source-destination
PLL FOR SINGLE PHASE GRID CONNECTED INVERTERS

In grid connected applications the synchronization of output signals of the converters to be connected with grid parameters - frequency and phase is of great importance. Different methods based on Fourier transforms, zero-crossing detection, Kalman filters, phase-locked loops (PLL) and others are used for this synchronization. This paper presents a new PLL for synchronization of the output current of single-phase grid connected inverters with the utility grid voltage. It is based on trigonometric transformations - sine and cosine functions in a phase detector block. The proposed method’s simplicity and efficiency are proved by means of computer simulations and experimental analysis. The practical realization of the PLL is based on analog and digital programmable devices. Simulation and experimental results show good agreement with the results obtained by the theoretical analysis. Advantage of the proposed PLL is its insensibility to changes of the amplitude of the input signal after the synchronization has been achieved with its frequency and phase. Also, in the proposed PLL, the settling time both at a step change of frequency and phase is decreased.
Fast-Converging Filtered Regressor Algorithms for

{ We present a simple extension of standard Bussgang blind equalization algorithms that signiicantly improves their convergence properties. Our technique uses the inverse channel estimate to lter the regressor signal. The modiied algorithms provide quasi-Newton convergence in the vicinity of a local minimum of the chosen cost function with only a modest increase in the overall computational complexity of the system. An example of the technique as applied to the constant-modulus algorithm indicates its superior convergence behavior.
Speech and Language Processing: an Introduction to Speech Recognition, Computational Linguistics and Natural Language Processing. Daniel Jurafsky & 4 N-grams

But it must be recognized that the notion " probability of a sentence " is an entirely useless one, under any known interpretation of this term. Anytime a linguist leaves the group the recognition rate goes up. Radar O'Reilly, the mild-mannered clerk of the 4077th M*A*S*H unit, had an uncanny ability to guess what his interlocutor was about to say. Let's look at another kind of word prediction: what word is likely to follow this fragment? I'd like to make a collect. Hopefully most of you concluded that a very likely word is call, or international or phone, but probably not the. We will formalize this idea of word prediction by building probabilistic models of word sequences called N-grams, WORD PREDICTION which predict the next word from the previous N − 1 words. Such statistical models of word sequences are also called language models or LMs. Computing the LANGUAGE MODELS LM probability of the next word will turn out to be closely related to computing the probability of a sequence of words. The following sequence, for example, has a non-zero probability of being encountered in a text written in English:. all of a sudden I notice three guys standing on the sidewalk. while this same set of words in a different order has a very low probability: on guys all I of notice sidewalk three a sudden standing the 1 In an address to the first Workshop on the Evaluation of NLP Systems, Dec 7, 1988. The workshop is described in Palmer and Finin (1990) but the quote wasn't written down; some remember a more snappy version: Every time I fire a linguist the performance of the recognizer improves.
The efficiency of a turbine in a tidal channel

There is an upper bound to the amount of power that can be generated by turbines in tidal channels as too many turbines merely block the flow. One condition for achievement of the upper bound is that the turbines are deployed uniformly across the channel, with all the flow through them, but this may interfere with other uses of the channel. An isolated turbine is more effective in a channel than in an unbounded flow, but the current downstream is non-uniform between the wake of the turbines and the free stream. Hence some energy is lost when these streams merge, as may occur in a long channel. We show here, for ideal turbine models, that the fractional power loss increases from 1/3 to 2/3 as the fraction of the channel cross-section spanned by the turbines increases from 0 to close to 1. In another scenario, possibly appropriate for a short channel, the speed of the free stream outside the turbine wake is controlled by separation at the channel exit. In this case, the maximum power obtainable is slightly less than proportional to the fraction of the channel cross-section occupied by turbines.
An evaluation of the DiaSuite toolset by professional developers: learning cost and usability

This paper evaluates a design-driven, tool-based approach, named DiaSuite, dedicated to developing applications involving sensors and actuators. Specifically, we evaluate the usability and the learning cost of DiaSuite as a first step to assess the potential for transferring this technology to the industrial practice of this domain. We assess the cost of learning DiaSuite by involving four professional programmers in a usability study involving a software engineering task. This experiment brings preliminary evidence that the DiaSuite technology can be used effectively by professional developers after only half a day of training. We then present qualitative data about the usage and usability of DiaSuite, collected from developers, via questionnaires and interviews. Finally, we discuss lessons learned from this work.
30Music Listening and Playlists Dataset

We introduce the 30Music dataset 1 , a collection of listening and playlists data retrieved from Internet radio stations through Last.fm API. In this paper we describe the creation process, its content, and its possible uses. Attractive features of the 30Music dataset that dierentiate it from existing public datasets include, among the others, (i) the user listening sessions complete of contextual time information, (ii) the user playlists, and (iii) the positive user ratings, key information to experiment with the task of modeling user taste and recommending playlists.
Automatic vs. Crowdsourced Sentiment Analysis

Due to the amount of work needed in manual sentiment analysis of written texts, techniques in automatic sentiment analysis have been widely studied. However, compared to manual sentiment analysis, the accuracy of automatic systems range only from low to medium. In this study, we solve a sentiment analysis problem by crowdsourcing. Crowdsourcing is a problem solving approach that uses the cognitive power of people to achieve specific computational goals. It is implemented through an online platform, which can either be paid or volunteer-based. We deploy crowdsourcing applications in paid and volunteer-based platforms to classify teaching evaluation comments from students. We present a comparison of the results produced by crowdsourcing, manual sentiment analysis, and an existing automatic sentiment analysis system. Our findings show that the crowdsourced sentiment analysis in both paid and volunteer-based platforms are considerably more accurate than the automatic sentiment analysis algorithm but still fail to achieve high accuracy compared to the manual method. To improve accuracy, the effect of increasing the size of the crowd could be explored in the future.
A distributed tree algorithms for WDM network protection/restoration

High-speed optical networks need efficient protectionhestoration schemes. A heuristic distributed MST algorithm, called the Pick-up-Parent (PUP) Algorithm, is proposed in this paper. A node would activate this algorithm after receiving a special message, called a pick-up-parent message, in order to form a logical spanning tree for network protection. The restoration strategy for this tree network protection lies in two points: Using tree links to protect nontree links, and seeking a shortest path from a node to its parent in order to protect the corresponding tree link. Performance analysis of the algorithm executed in some topologies based on existing networks is presented in this paper.
Personalization of user profiles for content-based music retrieval based on relevance feedback

Numerous efforts on content-based music information retrieval have been presented in recent years. However, the object of such existing research is to retrieve a specific song from a large music database. In this research, we propose a music retrieval method which retrieves songs based on the user's musical preferences. This enables users to discover new songs which they are expected to like. Since music preferences are expected to be highly ambiguous, we propose the implementation of relevance feedback methods to improve the performance of our music information retrieval method. In order to reduce the burden of users to input learning data to the system, we also propose a method to generate user profiles based on genre preferences, and refinement of such profiles based on relevance feedback. Evaluation experiments are conducted based on a corpus of music data with user ratings. Results of these experiments prove the effectiveness of our method.
The value of strong inapproximability results for clique

We consider approximations of the form n ~-°(1) for the Maximum Clique problem, where n is the number of vertices in the input graph and where the "o(1)" term goes to zero as n increases. We show that sufficiently strong negative results for such problems, which we call strong inapproximability results, have interesting consequences for exact computation. In particular, we show that for some such clique approximation problems that seem likely to require superpolynomial time in view of the results of Engebretsen and Holmerin (Manuscript, 1999), even certain low-degree polynomial lower bounds on their complexity will prove that N P ~ P. Our approach also leads to approximation algorithms: e.g., for (weighted) Maximum Clique and Maximum Independent Set, and for a class of maximization problems that includes the packing integer programs. A simple sampling method underlies most of our results.
Load-aware shedding in stream processing systems

Load shedding is a technique employed by stream processing systems to handle unpredictable spikes in the input load whenever available computing resources are not adequately provisioned. A load shedder drops tuples to keep the input load below a critical threshold and thus avoid tuple queuing and system trashing. In this paper we propose Load-Aware Shedding (LAS), a novel load shedding solution that drops tuples with the aim of maintaining queuing times below a tunable threshold. Tuple execution durations are estimated at runtime using efficient sketch data structures. We provide a theoretical analysis proving that LAS is an (ε, δ)-approximation of the optimal online load shedder and show its performance through a practical evaluation based both on simulations and on a running prototype.
Multiresolutional Quasi-Monte Carlo-based particle filters

Quasi-Monte Carlo (QMC)-based particle filters can obtain more accurate estimation than the general particle filters, with formidable computational complexity, however. Spatial-domain multiresolutional particle filters are more efficient by reducing the number of particles, but unevenly samples may cause estimation error. Aiming at these, we combine QMC numerical technique and multiresolutional methodology to improve the accuracy of filtering and computational efficiency. According to the idea, two QMC-based particle filters using thresholded wavelets in the spatial domain are proposed in this paper. The simulation shows that both the algorithms reduce the number of particles, meanwhile maintaining the estimation performance of particle filters with QMC methodology.
Evaluation of a wake-up wireless module with Bloom-filter-based ID matching

We present a wake-up wireless communication system, which can drastically reduce idle listening energy for long idle listening applications by using a wake-up wireless module. We consider chance encounter communication, which is communication during opportunistic encounters, as a long idle listening application. There are three requirements for applying the wake-up system to chance encounter communication: a group selective wake-up, a multiple group support, and small circuit size. In order to achieve these three requirements, we introduce Bloom-filter-based ID matching to the wake-up wireless module. The present paper describes the design of the wake-up module using a Bloom-filter-based ID matching mechanism. We evaluate the proposed module by performing circuit-level simulations. The simulation results show that the proposed system can reduce listening power by a factor of 1,000 to 10,000 compared to conventional Wi-Fi modules.
S3K: Scalable Security With Symmetric Keys—DTLS Key Establishment for the Internet of Things

DTLS is becoming the de facto standard for communication security in the Internet of Things (IoT). In order to run the DTLS protocol, one needs to establish keys between the communicating devices. The default method of key establishment requires X.509 certificates and a Public Key Infrastructure, an approach which is often too resource consuming for small IoT devices. DTLS also supports the use of preshared keys and raw public keys. These modes are more lightweight, but they are not scalable to a large number of devices.
Barriers and facilitators for general practitioners to engage in advance care planning: A systematic review

Abstract Objective. The aim of this systematic review is to identify the perceived factors hindering or facilitating GPs in engaging in advance care planning (ACP) with their patients about care at the end of life. Design. Studies from 1990 to 2011 were found in four electronic databases (PubMed, CINAHL, EMBASE, PsycINFO); by contacting first authors of included studies and key experts; and searching through relevant journals and reference lists. Studies were screened, graded for quality, and analysed independently by two authors; those reporting the perception by GPs of barriers and facilitators to engagement in ACP were included. Results. Eight qualitative studies and seven cross-sectional studies were included for data extraction. All barriers and facilitators identified were categorized as GP characteristics, perceived patient factors, or health care system characteristics. Stronger evidence was found for the following barriers: lack of skills to deal with patients’ vague requests, difficulties with defining the right moment, the attitude that it is the patient who should initiate ACP, and fear of depriving patients of hope. Stronger evidence was found for the following facilitators: accumulated skills, the ability to foresee health problems in the future, skills to respond to a patient's initiation of ACP, personal convictions about who to involve in ACP, and a longstanding patient–GP relationship and the home setting. Conclusion. Initiation of ACP in general practice may be improved by targeting the GPs’ skills, attitudes, and beliefs but changes in health care organization and financing could also contribute.
Connectivism: Learning Theory or Pastime of the Self-Amused?

Behaviorism, cognitivism, and constructivism are the three broad learning theories most often utilized in the creation of instructional environments. These theories, however, were developed in a time when learning was not impacted through technology. Over the last twenty years, technology has reorganized how we live, how we communicate, and how we learn. Learning needs and theories that describe learning principles and processes, should be reflective of underlying social environments. Vaill emphasizes that “learning must be a way of being—an ongoing set of attitudes and actions by individuals and groups that they employ to try to keep abreast of the surprising, novel, messy, obtrusive, recurring events . ” (1996, p. 42).
CUED Submission for the WMT 10 Translation Shared Task

This paper describes the Cambridge University Engineering Department (CUED) system for the ACL 2010 fifth workshop on statistical machine translation (WMT10). We participated in the FrenchEnglish and Spanish-English translation shared tasks in both directions. The CUED system is a hierarchical phrase-based system that uses finite-state transducers and lattice rescoring. In the French-English task, we investigated the use of contextdependent alignments.
Emergent stop for Humanoid Robots

This paper describes a real-time gait change for a walking humanoid robot. We propose a control method to change the gait motion by modifying a pre-defined zero moment point (ZMP) trajectory in real time. The stable gait change is generated by adjusting the amount of the ZMP modification according to the timing of stop command. The modified ZMP trajectory is given so that the humanoid robot can change the current motion without falling down. The modification criteria is defined from the relation between the predicted ZMP trajectory using a preview controller and the support polygon. The preview controller employs table-cart model and it derives center of mass (CoM) trajectory from ZMP reference in real-time. We make the map of relation between the ZMP modification and the timing of command for stable gate modification. The robot executes the best motion referring to the map. In this method, the humanoid robot can stop immediately within one step to avoid a collision, if humans or objects appeared unexpectedly in front of the walking humanoid robot. The stop motion is typically divided two mode; single leg stop motion and double leg stop motion. The stop mode and the next landing position are decided according to the command time of the stop signal. The validity of the proposed method is confirmed by experiment using a humanoid robot HRP-2