Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing the Prototype Theory of Concepts

Abstract Four experiments were designed to test two predictions of Prototype Theory. The first prediction was that when the defining (necessary) features of a concept are only partially matched by an instance, then characteristic (nonnecessary) features of concepts can affect categorization. The test of this prediction was rendered problematic as successive experiments failed to identify clearly necessary features for a range of concepts. The second hypothesis related to the independence of features in determining similarity. Most versions of Prototype Theory assume a linear combination of feature matches, which would predict that the effect of changing a feature on category membership should be greatest when the probability of categorization is closest to 50% (i.e. at the category border). The results showed that, contrary to this prediction, the effect of changing a feature was greatest when other features were all positive, and so categorization probability was at a maximum. The results support either a logistic combination rule for assessing similarity on the basis of feature match (Medin & Shaffer, 1978), or an exponential generalization function relating similarity to prototype to the sum of matching features (Shepard, 1987).
Reducing Tempo Octave Errors by Periodicity Vector Coding And SVM Learning

In this paper we present a method for learning tempo classes in order to reduce tempo octave errors. There are two main contributions of this paper in the rhythm analysis field. Firstly, a novel technique is proposed to code the rhythm periodicity functions of a music signal. Target tempi range is divided into overlapping “tempo bands” and the periodicity function is filtered by triangular masks aligned to those tempo bands, in order to calculate the respective saliencies, followed by the application of the DCT transform on band strengths. The second contribution is the adoption of Support Vector Machines to learn broad tempo classes from the coded periodicity vectors. Training instances are assigned a tempo class according to annotated tempo. The classes are assumed to correspond to “music speed”. At classification phase, each target excerpt is assigned a tempo class label by the SVM. Target periodicity vector is masked by the predicted tempo class range, and tempo is estimated by peak picking in the reduced periodicity vector. The proposed method was evaluated on the benchmark ISMIR 2004 Tempo Induction Evaluation Exchange Dataset for both tempo class and tempo value estimation tasks. Results indicate that the proposed approach provides an efficient framework to tackle the tempo estimation task.
"Meanwhile I'm a Convinced 'Psychosomat'"—Case-Study of a Young Female Adult With Diabetes Mellitus Type 1 and Severe Anorexia

Wir berichten uber eine 19-jahrige Patientin mit Diabetes mellitus Typ 1 und einer ausgepragten hyporektischen Ess-Storung, die wiederholt unter lebensbedrohlichen Blutzuckerentgleisungen litt. Anhand der Kasuistik soll exemplarisch gezeigt werden, inwieweit beide Krankheitsbilder ineinander greifen, sich gegenseitig beeinflussen und wie zwei in der operationalisierten psychodynamischen Diagnostik (OPD) beschriebene zentrale Konflikte in dieser Doppelerkrankung Ausdruck finden bzw. von den PatientInnen zur Konfliktbearbeitung funktionalisiert werden. Bei der psychotherapeutischen Behandlung dieser in Kombination auftretenden Erkrankungen ist zu beachten, dass die TherapeutInnen die widerspruchlichen und ambivalenten Bedurfnisse der PatientInnen aushalten mussen und gleichzeitig nicht zu deren Spielball werden durfen. Ein klares, abgegrenztes und mit den PatientInnen immer wieder zu besprechendes, aber nicht zu diskutierendes Behandlungsregime kombiniert mit einer auf Dialog, Fursorge und Verstandnis basierenden Psychotherapie ist notwendig, um mit diesen PatientInnen konstruktiv arbeiten zu konnen. URN: urn:nbn:de:0114-fqs0501366
Personalized recommendation driven by information flow

We propose that the information access behavior of a group of people can be modeled as an information flow issue, in which people intentionally or unintentionally influence and inspire each other, thus creating an interest in retrieving or getting a specific kind of information or product. Information flow models how information is propagated in a social network. It can be a real social network where interactions between people reside; it can be, moreover, a virtual social network in that people only influence each other unintentionally, for instance, through collaborative filtering. We leverage users' access patterns to model information flow and generate effective personalized recommendations. First, an early adoption based information flow (EABIF) network describes the influential relationships between people. Second, based on the fact that adoption is typically category specific, we propose a topic-sensitive EABIF (TEABIF) network, in which access patterns are clustered with respect to the categories. Once an item has been accessed by early adopters, personalized recommendations are achieved by estimating whom the information will be propagated to with high probabilities. In our experiments with an online document recommendation system, the results demonstrate that the EABIF and the TEABIF can respectively achieve an improved (precision, recall) of (91.0%, 87.1%) and (108.5%, 112.8%) compared to traditional collaborative filtering, given an early adopter exists.
High performance video compression based on improved VSPIHT algorithm

This paper proposes an effective I3D-DWT-VSPIHT video coding method, which reasonably organizes wavelet coefficients by integrated 2D-SPIHT with 3D-VSPIHT and the video sequence is partitioned into two alternate parts: original frames and residual frames, so the. similar coefficients can be compressed to one or fewer symbols by sufficiently using correlation between trees and the reconstructive image quality as well as memory saving can be improved. On the other hand, by effectively reducing redundant scan time it is available in real-time system. Simulated results show that the quality (PSNR) of reconstructed video at the same compression ratio is improved about 1/spl sim/5 dB for gray video as compared with existent 3D-DWT-SPIHT. By using the high performance video compression method, available for gray and color video sequences, very low bit rate and high quality of reconstructed image can be obtained.
Coarse molecular dynamics of a peptide fragment: Free energy, kinetics, and long-time dynamics computations

We present a “coarse molecular dynamics” approach and apply it to studying the kinetics and thermodynamics of a peptide fragment dissolved in water. Short bursts of appropriately initialized simulations are used to infer the deterministic and stochastic components of the peptide motion parametrized by an appropriate set of coarse variables. Techniques from traditional numerical analysis (Newton–Raphson, coarse projective integration) are thus enabled; these techniques help analyze important features of the free-energy landscape (coarse transition states, eigenvalues and eigenvectors, transition rates, etc.). Reverse integration of coarse variables backward in time can assist escape from free energy minima and trace low-dimensional free energy surfaces. To illustrate the coarse molecular dynamics approach, we combine multiple short (0.5 ps) replica simulations to map the free energy surface of the “alanine dipeptide” in water, and to determine the ∼1/(1000 ps) rate of interconversion between the two stable.
Television synchronization of a real time ultrasonic sector scanner

The interaction of the scan rates of ultrasonic scanning and television recording systems often causes portions of the resultant television image to be either over‐ or under‐scanned. This results in objectionable bright and dark sectors within the ultrasonic image on a television monitor during single‐frame playback. The usual method for dealing with this problem is to exchange time resolution for image quality when preparing pictures for analysis or presentation. Time resolution can be preserved by operating the ultrasonic scanner at a scan rate one‐half of the television frame rate and phase locking the ultrasonic scanner to the television system so that each angular scan of the ultrasonic system is initiated coincident with the beginning of each television frame.
CORDIC-Based MMSE-DFE Coefficient Computation

A modular parallel architecture for a MMSE-DFE coefficient computation processor is presented. The architecture is based on QR factorization of a channel-and-noise-dependent data matrix and is implemented using CORDIC processors within a systolic array architecture. Implementation issues including the number of CORDIC stages and the bit precision required in a fixed-point implementation are investigated through computer simulations. The proposed architecture accommodates fractionally spaced DFEs, co-channel interference, and multiple diversity paths.
Cognitive radios for dynamic spectrum access - polyphase multipath radio circuits for dynamic spectrum access

Dynamic access of unused spectrum via a cognitive radio asks for flexible radio circuits that can work at an arbitrary radio frequency. This article reviews techniques to realize radios without resorting to frequency selective dedicated filters. In particular, a recently proposed polyphase multipath technique canceling harmonics and sidebands is discussed. Using this technique, a wideband and flexible power upconverter with a clean output spectrum has been realized on a CMOS chip, aiming at flexible radio transmitter application. Prototype chips can transmit at an arbitrary frequency between DC and 2.4 GHz. Unwanted harmonics and sidebands are more than 40 dB lower than the desired signal up to the 17th harmonic of the transmit frequency
Save Money or Feel Cozy?: A Field Experiment Evaluation of a Smart Thermostat that Learns Heating Preferences

We present the design of a fully autonomous smart thermostat that supports end-users in managing their heating preferences in a real-time pricing regime. The thermostat uses a machine learning algorithm to learn how a user wants to trade off comfort versus cost. We evaluate the thermostat in a field experiment in the UK involving 30 users over a period of 30 days. We make two main contributions. First, we study whether our smart thermostat enables end-users to handle real-time prices, and in particular, whether machine learning can help them. We find that the users trust the system and that they can successfully express their preferences; overall, the smart thermostat enables the users to manage their heating given real-time prices. Moreover, our machine learning-based thermostats outperform a baseline without machine learning in terms of usability. Second, we present a quantitative analysis of the users' economic behavior, including their reaction to price changes, their price sensitivity, and their comfort-cost trade-offs. We find a wide variety regarding the users' willingness to make trade-offs. But in aggregate, the users' settings enabled a large amount of demand response, reducing the average energy consumption during peak hours by 38%.
Bargaining over Strategies of Non-Cooperative Games

We propose a bargaining process supergame over the strategies to play in a non-cooperative game. The agreement reached by players at the end of the bargaining process is the strategy profile that they will play in the original non-cooperative game. We analyze the subgame perfect equilibria of this supergame, and its implications on the original game. We discuss existence, uniqueness, and efficiency of the agreement reachable through this bargaining process. We illustrate the consequences of applying such a process to several common two-player non-cooperative games: the Prisoner’s Dilemma, the Hawk-Dove Game, the Trust Game, and the Ultimatum Game. In each of them, the proposed bargaining process gives rise to Pareto-efficient agreements that are typically different from the Nash equilibrium of the original games.
Physical education and sport programs at an inner city school: exploring possibilities for positive youth development

Background: School-based recreational opportunities for youth from low-income inner-city neighbourhoods are often lacking. School programs represent an ideal location for promoting youth development in low-income areas because they can provide safe, supervised, and structured activities. Such activities should include not only physical education (PE) programs, but other extra-curricular activities such as intramural sports and school sport teams. Because we were interested in how these programs were associated with youth development, we used the concept of positive youth development (PYD) to guide this study. Purpose: This case study examined school staff members’ and children's perceptions of school PE, intramural sports, and sport teams with a view to establish factors that facilitated or impeded PYD. Method: Data were collected via individual interviews with eight teachers and 59 children from an inner-city school that had a mission to promote positive behaviors consistent with PYD. Interviews were transcribed verbatim and subjected to a categorical aggregation analysis procedure. Results: Findings showed factors that facilitated or impeded PYD varied across different contexts. In PE, the importance of a specialist PE teacher and establishing clear boundaries during lessons while providing children with perceptions of choice were important. Children enjoyed intramural sports, but there were few attempts to create an appropriate developmental atmosphere during these sessions. In fact, intramural sports were associated with negative student interactions. Coaches of the sport teams used techniques to promote social interactions and respect. Most notable student outcomes associated with PYD related to fostering empathy and social connections. Conclusion: These findings showed differences in contextual factors across the PE/sport programs that helped promote or impeded PYD. These differences revealed some practical suggestions for promoting PYD, which include focusing on the developmental orientation of PE classes, the fun of intramurals, and the ‘life skills’ focus of the sport teams. Furthermore, we suggest an integrated, school-wide approach is required to help promote PYD.
A Spectral Clustering Algorithm Based on Self-Adaption

In traditional spectral clustering algorithms, the number of cluster is choosen in advance. A self-adaption spectral clustering algorithm is proposed to decide the cluster number automatically, which eliminates the drawbacks of two kinds of spectral clustering methods. In our algorithm, eigengap is used to discover the clustering stability and decide the cluster number automatically. We prove theoretically the rationality of cluster number using matrix perturbation theory. A kernel based fuzzy c-means is introduced to spectral clustering algorithm to separate clusters. Finally the experiments prove that our algorithm tested in the UCI data sets may get better results than c-means, Ng et.al's algorithm and Francesco et.al's algorithm.
Using event-based metric for event-based neural network weight adjustment

The problem of adjusting the parameters of an event-based network model is addressed here at the programmatic level. Considering temporal processing, the goal is to adjust the network units weights so that the outcoming events correspond to what is desired. The present work proposes, in the deterministic and discrete case, a way to adapt usual alignment metrics in order to derive suitable adjustment rules. At the numerical level, the stability and unbiasness of the method is verified.
Lazy prefetching

High latency of memory accesses is critical to the performance of shared memory multiprocessors. The technology trends indicate that this gap between processor and memory speeds is likely to increase in the future. To cope with memory latency problem two software-controlled techniques have been investigated: prefetching and remote write. Prefetching is a consumer-initiated technique which moves data close to the processor before they are actually needed by explicit execution prefetch instruction. Remote write, a producer-initiated technique moves data close to the processor estimated to be the next consumer. However these techniques can degrade the performance in the case of misprediction of future needs and/or consumers. The new method called lazy prefetching which combines good properties of prefetching and remote write techniques is presented. The experimental methodology used for performance analysis is also described.
Effectiveness of Peripheral Level of Detail Degradation When Used with Head-Mounted Displays

Two user studies were performed to evaluate the effectiveness of level of detail (LOD) degradation in the periphery of head-mounted displays. In the first study, spatial detail was degraded by reducing resolution. In the second study, detail was degraded in the color domain by using grayscale in the periphery. In each study, ten subjects were given a complex search task that required users to indicate whether or not a target object was present among distractors. Subjects used several different displays varying in the amount of detail presented. Frame rate, object location, subject input method, and order of display use were all controlled. Primary dependent measures were search time on correctly performed trials, and the percentage of all trials correctly performed. Results indicated that peripheral LOD degradation can be used to reduce visual complexity by almost half without hurting performance. Users were more sensitive to decreases in LOD than increases in degraded display area.
Doctors’ versus patients’ global assessments of treatment effectiveness: empirical survey of diverse treatments in clinical trials

Objective To examine whether doctors’ global assessments of treatment effects agree with patients’ global assessments. Design Survey of trials included in systematic reviews of treatments for diverse conditions. Data sources Cochrane database of systematic reviews. Data extracted Data on patients’ global assessments and on doctors’ global assessment for the same treatment against the same comparator. Main outcome measures Relative odds ratio (ratio of odds ratios of global improvement with the experimental intervention versus control according to doctors compared with patients), and improvement rates according to doctors and patients. Results Doctors’ global assessments were compared with patients’ global assessments for 63 different treatment comparisons (240 trials) in 18 conditions. The summary relative odds ratio across the comparisons was not significant (0.98, 95% confidence interval 0.88 to 1.08; I2=0%, 95% confidence interval 0% to 30%). In 62 of the 63 comparisons the effects of treatment rated by patients and by doctors did not differ beyond chance, but for single comparisons the confidence intervals were large. Rates of improvement on average did not differ between doctors’ assessments and patients’ assessments (summary relative odds ratio 0.98, 0.88 to 1.06; I2=0%, 0% to 24%). Conclusion Doctors’ global assessments of the effects of treatments are on average similar to those of patients.
Early Nephrology Referral Reduces the Economic Costs among Patients Who Start Renal Replacement Therapy: A Prospective Cohort Study in Korea

Background The nature of cost-saving effects of early referral to a nephrologist in patients with chronic kidney disease (CKD) is not fully evaluated. We evaluated the health care costs before and after dialysis according to the referral time. Methods A total of 879 patients who were newly diagnosed as having end-stage renal disease from August 2008 to June 2011 were prospectively enrolled. The early referral (ER) group was defined as patients who were referred to a nephrologist more than a year before dialysis and had visited a nephrology clinic 2 or more times. Patients whose referral time was less than a year were considered the late referral (LR) group. Information about medical costs was acquired from the claim data of the Korea Health Insurance Review and Assessment Service. Results The total medical costs during the first 12 months after the initiation of dialysis were not different between the 526 ER patients and the 353 LR patients. However, the costs of the ER patients during the first month were significantly lower than those of the LR patients (ER vs. LR: 3029±2219 vs. 3438±2821 US dollars [USD], P = 0.025). The total 12-month health care costs before the initiation of dialysis were significantly lower in the ER group (ER vs. LR: 6206±5873 vs. 8610±7820 USD, P<0.001). In the multivariate analysis, ER significantly lowered the health care costs during the 12 months before (2534.0±436.2 USD, P<0.001) and the first month (428.5±172.3 USD, P = 0.013) after the initiation of dialysis. Conclusions The ER of patients with CKD to a nephrologist is associated with decreased medical costs during the pretreatment period of renal replacement therapy and the early period of dialysis initiation.
The Effects of Parent-Implemented Enhanced Milieu Teaching on the Social Communication of Children Who Have Autism

This study examined the effects of training six parents to use Enhanced Milieu Teaching (EMT) with their preschool children with autism or pervasive development disabilities. A modified single subject design across the six families was used to assess the parents' acquisition and generalized use of the EMT strategies. The parents learned to use the naturalistic language intervention strategies during 24 individual training sessions in the clinic and generalized their use of the strategies to home interactions at the end of the intervention. Follow- up observations in the clinic and home observations six months after the intervention indicated that parents maintained their use of the newly-learned procedures throughout the follow-up period but at levels lower than those achieved during the clinic training. Positive effects were observed on the use of communication targets for all children and on the complexity and diversity of productive language for most children. Child effects generalized and maintained for four of six children and there was evidence of change on developmental assessments of language for five of six children. Parent satisfaction with the intervention procedures and child outcomes was high.
Role of PKCδ in Insulin Sensitivity and Skeletal Muscle Metabolism

Protein kinase C (PKC)δ has been shown to be increased in liver in obesity and plays an important role in the development of hepatic insulin resistance in both mice and humans. In the current study, we explored the role of PKCδ in skeletal muscle in the control of insulin sensitivity and glucose metabolism by generating mice in which PKCδ was deleted specifically in muscle using Cre-lox recombination. Deletion of PKCδ in muscle improved insulin signaling in young mice, especially at low insulin doses; however, this did not change glucose tolerance or insulin tolerance tests done with pharmacological levels of insulin. Likewise, in young mice, muscle-specific deletion of PKCδ did not rescue high-fat diet–induced insulin resistance or glucose intolerance. However, with an increase in age, PKCδ levels in muscle increased, and by 6 to 7 months of age, muscle-specific deletion of PKCδ improved whole-body insulin sensitivity and muscle insulin resistance and by 15 months of age improved the age-related decline in whole-body glucose tolerance. At 15 months of age, M-PKCδKO mice also exhibited decreased metabolic rate and lower levels of some proteins of the OXPHOS complex suggesting a role for PKCδ in the regulation of mitochondrial mass at older age. These data indicate an important role of PKCδ in the regulation of insulin sensitivity and mitochondrial homeostasis in skeletal muscle with aging.