Miracle-dz/UniFAR-FTUs huggingface dataset:
GameOn: p2p Gaming On Public Transport

Mobile games, and especially multiplayer games are a very popular daily distraction for many users. We hypothesise that commuters travelling on public buses or trains would enjoy being able to play multiplayer games with their fellow commuters to alleviate the commute burden and boredom. We present quantitative data to show that the typical one-way commute time is fairly long (at least 25 minutes on average) as well as survey results indicating that commuters are willing to play multiplayer games with other random commuters. In this paper, we present GameOn, a system that allows commuters to participate in multiplayer games with each other using p2p networking techniques that reduces the need to use high latency and possibly expensive cellular data connections. We show how GameOn uses a cloud-based matchmaking server to eliminate the overheads of discovery as well as show why GameOn uses Wi-Fi Direct over Bluetooth as the p2p networking medium. We describe the various system components of GameOn and their implementation. Finally, we present numerous results collected by using GameOn, with three real games, on many different public trains and buses with up to four human players in each game play.
Fuzzy auto-tuning scheme based on /spl alpha/-parameter ultimate sensitivity method for AC speed servo system

The authors introduce a load speed feedback control to prevent the mechanically-resonant vibration in AC servo motor drive motion system with two-mass mechanical motion load. In order to compensate three characteristic system gain parameters, the /spl alpha/-parameter ultimate sensitivity method based on partial model matching method is proposed. Moreover, a fuzzy reasoning algorithm is applied to compensate this parameter /spl alpha/. The effectiveness of this advanced auto-tuning control scheme in the AC speed servo system is verified by computer simulation.
Incremental Learning of Gaussian Mixture Models

Gaussian Mixture Modeling (GMM) is a parametric method for high dimensional density estimation. Incremental learning of GMM is very important in problems such as clustering of streaming data and robot localization in dynamic environments. Traditional GMM estimation algorithms like EM Clustering tend to be computationally very intensive in these scenarios. We present an incremental GMM estimation algorithm which improves the proposed solution by Song et al [4] by improving the underlying EM algorithm for accuracy and performance. Another novel aspect of the proposed approach is that the statistical equivalence among different components is established through Bregman divergence which is known to be very efficient and optimal for variety of distribution functions belonging to exponential family.
Low-Delay Joint Source-Channel Mappings for the Gaussian MAC

The bivariate Gaussian multiterminal source coding problem with transmission over the Gaussian multiple-access channel is studied. We propose the use of low-delay joint source - channel mappings and show how performance saturation, which is unavoidable with linear transmission, can be overcome by optimizing the mappings. The optimized mappings are in general nonlinear and perform a combination of hard and soft decision signaling for the error-resilient transmission of analog data.
Ad Hoc Solution of the Multicommodity-Flow-Over-Time Problem

Ad hoc shared-ride systems built upon intelligent-transportation-system (ITS) technology represent a promising scenario for investigating the multicommodity-flow-over-time problem. This type of problem is known to be strongly NP-hard. Furthermore, capacity assignment in this shared-ride system is a problem to be solved in highly dynamic transportation and communication networks. So far, the known heuristics to this problem are centralized and require global knowledge about the environment. This paper develops a decentralized ad hoc capacity-assignment approach. Based on a spatial decomposition of the global optimization problem, the solution provides effective agent decisions using only local knowledge. The effectiveness is assessed by the trip quality for ride clients and by the required communication effort.
A Low-Power GSM/EDGE/WCDMA Polar Transmitter in 65-nm CMOS

A low-power, multimode polar transmitter based on a two-point injection PLL with a linearized VCO is implemented in 65-nm CMOS technology. A wideband feedback loop, nested inside the PLL with negligible area and power consumption overhead, linearizes and accurately controls the tuning characteristic of the VCO, which is a key requirement when directly modulating the oscillator. Differential delay between AM-PM paths is predictable and is self-calibrated. In WCDMA mode, the transmitter achieves 42/-58-dBc ACLR at 5/10-MHz offsets, -159-dBc/Hz receive band noise, and 2.9% EVM at 0-dBm output power while drawing 40-mA from a 3.6-V battery. The DG09 battery current is 25-mA based on a typical PA gain profile and the chip active area is 0.7-mm2.
Resolution limitation in speakers clustering and segmentation problems

In unlabeled and unsegmented conversation, i.e. no a-priori knowledge about speakers’ identity and segments boundaries is provided, it is very important to cluster the conversation (make a segmentation and labeling) with the best possible resolution. For low-resolution cases, i.e. the duration of the segment is long; the segments might contain data from several speakers. On the other hand, when short segments are used (high resolution) not enough statistics is provided to allow correct decision about the identity of the speakers. In this work the performance of a system, which employs different segment lengths, is presented. We assumed that the number of speakers, R, is known, and high-quality conversations were used. Each speaker was modeled by a Self-Organizing-Map (SOM). An iterative algorithm allows the data move from one model to another and adjust the SOMs. The restriction that the data can move only in small groups but not by moving each and every feature vector separately force the SOMs to adjust to speakers (instead of phonemes or other vocal events). We found that the optimal segment duration was half-second. The system has a clustering performance of about 90% for towspeaker conversation and over 80% for three-speaker conversations.
An Application of Fuzzy Clustering in Group-Positioning Analysis

Before designing a product and selecting marketing strategies, a company must conduct consumer studies in order to determine the optimum combination of product benefits desired by consumers. Due to large market size and the various sought-after product benefits, a company may also need to properly analyze different market segments in order to survive and succeed in a competitive environment. It is especially important for a company to understand its own market position as well as competitors' market strategies. This study integrates the concepts of market segmentation, strategic groups, and performance to construct a three-dimensional Fuzzy GroupPositioning Model (FGPM). The FGPM is proposed to closely emulate human thinking processes and better understand the relationship between consumer's consumption patterns, the competitive situation within the industry and the referential values of strategic position. In addition, this study modifies the "fuzzy cluster analytical method" to solve the cluster numbering and address the fuzziness among group boundaries.
Executive Function Profiles in Pediatric Traumatic Brain Injury

ABSTRACT Traumatic brain injury (TBI) results in heterogeneous patterns of neuropsychological impairment. This study investigated heterogeneity in executive function (EF) using the Comprehensive Trail Making Test (CTMT) to evaluate 121 children and adolescents with TBI and 121 matched normal controls. The TBI group performed approximately two standard deviations below controls. Cluster analyses indicated that a three-cluster solution best classified the TBI group and a four-cluster solution best classified controls. Greater impairment in EF was associated with lower intellectual, achievement, and neuropsychological test performance in the TBI group. Results suggest that EF deficits reflected in CTMT performance may be useful for classifying severity of TBI.
Generic Information Can Retrieve Known Biological Associations: Implications for Biomedical Knowledge Discovery

Motivation Weighted semantic networks built from text-mined literature can be used to retrieve known protein-protein or gene-disease associations, and have been shown to anticipate associations years before they are explicitly stated in the literature. Our text-mining system recognizes over 640,000 biomedical concepts: some are specific (i.e., names of genes or proteins) others generic (e.g., ‘Homo sapiens’). Generic concepts may play important roles in automated information retrieval, extraction, and inference but may also result in concept overload and confound retrieval and reasoning with low-relevance or even spurious links. Here, we attempted to optimize the retrieval performance for protein-protein interactions (PPI) by filtering generic concepts (node filtering) or links to generic concepts (edge filtering) from a weighted semantic network. First, we defined metrics based on network properties that quantify the specificity of concepts. Then using these metrics, we systematically filtered generic information from the network while monitoring retrieval performance of known protein-protein interactions. We also systematically filtered specific information from the network (inverse filtering), and assessed the retrieval performance of networks composed of generic information alone. Results Filtering generic or specific information induced a two-phase response in retrieval performance: initially the effects of filtering were minimal but beyond a critical threshold network performance suddenly drops. Contrary to expectations, networks composed exclusively of generic information demonstrated retrieval performance comparable to unfiltered networks that also contain specific concepts. Furthermore, an analysis using individual generic concepts demonstrated that they can effectively support the retrieval of known protein-protein interactions. For instance the concept “binding” is indicative for PPI retrieval and the concept “mutation abnormality” is indicative for gene-disease associations. Conclusion Generic concepts are important for information retrieval and cannot be removed from semantic networks without negative impact on retrieval performance.
Overview of the digital museum project

In this paper, the authors first introduce the outline of "Mixed Reality Digital Museum" project which started as a 5 year national project under the sponsorship of MEXT (Ministry of Education, Culture, Sports, Science and Technology). Then, the basic concept and project formation of the project are quickly introduced. After that, among the many project subtopics, the authors introduce two types of museum system using Mixed Reality technology: "Digital Display Case" and "Digital Diorama. " Result of the implementation of the first stage prototypes are introduced and future plan is discussed.
Association of Soccer and Genu Varum in Adolescents

Background: Genu varum is a physical deformity marked by bowing of the leg. One of the risk factors of this musculoskeletal alignment is stress on the knee joint such as with exercise. Objectives: Since the evaluation of genu varum has not been widely studies, this study was conducted to examine the association between genu varum and playing soccer. Materials and Methods: Between Septembers 2010-2012, 750 soccer players and 750 non-soccer players 10-18 years of age were included in the study. A questionnaire of data including age, height, weight, body mass index (BMI), years of soccer participation, the average time of playing soccer per week, previous trauma to the lower limbs, history of any fractures of the knee, previous hospitalizations, and the distance of joint lines between the knees was assessed for all subjects. Chi-square, student t-test, and one-way ANOVA were used for statistical analysis by SPSS v.19. 0 software. In all tests, a P value of less than 0.05 was construed as statistically significant. Results: Both soccer players and controls had genu varum. However, the incidence of genu varum was higher in the soccer players (P = 0.0001) and it was more prevalent in the 16-18 year age group (P = 0.0001). The results revealed a statistically significant association between the degree of practices and the prevalence of genu varum (P = 0.0001). Moreover, previous trauma to the knees and practicing in load-bearing sports led to an increase in the degree of genu varum (P = 0.0001). Conclusions: There was a higher incidence of genu varum in soccer players than in control adolescents; the stress and load imposed on the knee joint led to more severe genu varum.
Downregulation of the Potassium Chloride Cotransporter KCC2 in Vulnerable Motoneurons in the SOD1-G93A Mouse Model of Amyotrophic Lateral Sclerosis

The balance between excitatory and inhibitory synaptic inputs is critical for the physiological control of motoneurons. The maintenance of a low-intracellular chloride concentration by the potassium chloride cotransporter 2 (KCC2) is essential for the efficacy of fast synaptic inhibition of mature motoneurons in response to the activation of ionotropic &ggr;-aminobutyric acid A and glycine receptors. Altered synaptic balance and excitotoxicity have been proposed as candidate pathophysiological processes in amyotrophic lateral sclerosis (ALS). Therefore, we investigated the expression patterns of KCC2 and its functional opponent, the chloride influx-mediating sodium-potassium chloride cotransporter 1 (NKCC1), in the superoxide dismutase 1 (SOD1-G93A) mouse model of ALS. We detected reduced KCC2 messenger RNA levels and less membrane-bound KCC2 immunoreactivity in ALS-vulnerable motoneurons in lumbar spinal cord and hypoglossal nuclei of SOD1-G93A mice but not in degeneration-resistant oculomotor nuclei. Downregulation of KCC2 started during late presymptomatic stages and accelerated in parallel to hind limb and tongue motor function deficits. In contrast, NKCC1 messenger RNA levels were unaltered in postnatal lumbar spinal cord motoneurons. Our data indicate that reductions in KCC2 gene expression may contribute to selective motor deficits and disease progression in vulnerable motoneurons in a mouse model of ALS.
Akt-mediated phosphorylation of Oct4 is associated with the proliferation of stem-like cancer cells

Oct4 protein encoded by POU5F1 plays a pivotal role in maintaining the self-renewal of pluripotent stem cells; however, its presence in cancer cells remains controversial. In the present study, we provided evidence that the transcripts of authentic OCT4 gene (OCT4A) and its multiple pseudogenes were detected in a variety of cancer cell lines. A few major bands were also detected by western blotting using an anti-Oct4A monoclonal antibody. Moreover, an anti-Oct4-pT235 antibody was used to identify a band in the majority of the tested cancer cell lines that coincided with one of the anti-Oct4A bands which was decreasable by a specific shRNA. The Oct4-pT235 signals were also detected in human glioblastoma and liver cancer specimens by immunofluorescence microscopy and immunohistochemistry. U87 glioblastoma cells were cultured in a neural stem cell medium to induce the formation of neurospheres rich in stem-like cancer cells. The levels of Oct4-pT235 in the sphere cells were markedly increased compared to their monolayer parental cells, a result that was accompanied by upregulation of the PI3K-Akt pathway. Akti-1/2, a specific inhibitor of Akt, effectively reduced the level of Oct4-pT235 and attenuated the proliferation of U87 sphere cells. ITE, an agonist of the aryl hydrocarbon receptor, also significantly attenuated the Akt-mediated phosphorylation of Oct4 in glioblastoma and liver cancer cells, and reduced their tumorigenic potential in a xenograft tumor model. Taken together, we concluded that the Akt-mediated phosphorylation of Oct4A or its homolog protein was associated with the proliferation of stem-like cancer cells that may serve as a novel biomarker and drug target for certain types of cancer.
M-theory on seven-dimensional manifolds with SU(3) structure

In this paper we study M-theory compactifications on seven-dimensional manifolds with SU(3) structure. As such manifolds naturally pick out a specific direction, the resulting effective theory can be cast into a form which is similar to type IIA compactifications to four dimensions. We derive the gravitino mass matrix in four dimensions and show that for different internal manifolds (torsion classes) the vacuum preserves either no supersymmetry, or N=2 supersymmetry or, through spontaneous partial supersymmetry breaking, N=1 supersymmetry. For the latter case we derive the effective N=1 theory and give explicit examples where all the moduli are stabilised without the need of non-perturbative effects.
Fault ride-through capability of a microgrid with wtgs and supercapacitor storage during balanced and unbalanced utility voltage sags

The concept of microgrids is recently attracting considerable interest. However, in order to widely integrate microgrids within the distribution networks, a shift in the philosophy of interconnecting them with the utility grid seems necessary. A grid-connected microgrid is required to possess Faults Ride-Through (FRT) capabilities, as well as provide ancillary services during abnormal grid operation. In this paper, a control strategy for improving the ability of an inverter-based microgrid to ride though symmetrical and asymmetrical grid faults is proposed. The microgrid is formed of several Distributed Energy Resources (DERs), which utilize Wind Turbine Generators (WTGs) as primary renewable energy source, each combined with a Supercapacitor Energy Storage System (SCESS). During balanced and unbalanced grid voltage sags, aim of the proposed control strategy is to keep the microgrid connected to the grid, according to the FRT requirements, while maintaining an acceptable voltage profile within the common ac bus. Each DER is controlled to support the voltage within the microgrid by injecting reactive power, without any physical communication. During unbalanced utility voltage conditions, the DERs operate collectively in order to compensate the undesirable negative and zero sequence voltage components. Thus, a set of balanced three-phase voltages is provided within the common ac bus. Simulation results demonstrate that the microgrid can ride through heavily balanced and unbalanced utility voltage sags, while supplying its loads with a high quality voltage profile.
Automatic Verb Valency Frames Disambiguation for Czech

This paper deals with automatic disambiguation of verb valency frames on Czech data. Main contribution lies in determining of the most useful features for valency frame disambiguation. We experimented with diverse types of features, including morphological, syntax-based, idiomatic, animacy and WordNet-based. The considered features were classified using decision trees, rule-based learning and Näıve Bayes classifier. On a set of 7 778 sentences we achieved accuracy of 79.86% against baseline 68.27% obtained by assigning the most frequent frame.
Answering queries over incomplete data stream histories

Purpose – Distributed data streams are an important topic of current research. In such a setting, data values will be missed, e.g. due to network errors. This paper aims to allow this incompleteness to be detected and overcome with either the user not being affected or the effects of the incompleteness being reported to the user.Design/methodology/approach – A model for representing the incomplete information has been developed that captures the information that is known about the missing data. Techniques for query answering involving certain and possible answer sets have been extended so that queries over incomplete data stream histories can be answered.Findings – It is possible to detect when a distributed data stream is missing one or more values. When such data values are missing there will be some information that is known about the data and this is stored in an appropriate format. Even when the available data are incomplete, it is possible in some circumstances to answer a query completely. When thi.
A Hybrid Improved Particle Swarm Optimization Based on Dynamic Parameters Control and Metropolis Accept Rule Strategy

Particle Swarm Optimization (PSO), a population-based intelligent modern heuristic algorithm, is inspired from the simulation of flock prayer behavior. It is vastly employed in various industrial applications due to its fast convergence and easy to carry out. Based on the analysis of current existing PSO algorithms, a Hybrid Improved PSO (HIPSO) is proposed in this paper, in which chaos initialization is introduced to improve the population diversity, and adaptive parameters' control strategy is employed to make it independent from specific problem, besides, novel acceptance policy based on Metropolis rule, which comes from Simulated Annealing, is taken to guarantee the convergence of the algorithm. In order to verify the effectiveness of the HIPSO, two typical numerical benchmarks are employed for comparison study with the other 3 well-known PSOs. Statistical optimization results show that, the new proposed HIPSO has outperformed the other PSOs, either on solution optimality, or on convergence speed.
Feeling connected to younger versus older selves: The asymmetric impact of life stage orientation

The concept of life-stage orientation is proposed. Youth is a period of time characterised by strong feelings and emotions, but weak reasoning and cognitive skill. Conversely, adulthood is characterised by strong rationality, but weak emotionality. Two studies revealed that merely bringing these concepts to mind changes real-time feelings and behaviour. Participants who were instructed to act like their “adult” selves exhibited greater self-control in a cold pressor test than control participants and those who acted like their “youth” selves (Experiment 1). However, being induced to feel connected to youth enhanced enjoyment for fun videos (Experiment 2). Hence, the extent to which people are oriented towards youth versus adulthood has asymmetric costs and benefits for the present. Connecting to youth boosts experiential capacities (in this case, enjoying oneself) at the cost of agency, whereas connecting to adulthood boosts agentic capacities (in this case, exerting will-power) at the cost of experience.
Trust and Innovation in Europe: Causal, spatial and non-linear forces

This paper investigates the effect of trust on innovation. In addition to generalised trust we use a range of other indicators that could measure trust and investigate which trust related variables could explain innovation in 20 European countries divided into 135 regions. We specifically look at causal, non-linear and spatial forces. Our findings indicate that only generalised trust and non-egoistic fairness have robust effects on innovation in Europe. Using historical data on the extent and existence of universities and an instrumental variable strategy we set up a causal relationship between trust and innovation. Even after controlling for causal, spatial and non-linear forces there is a significant direct impact of trust on innovation.
Effect of topological and traffic variations on quality of service using RSVP/ns

Provision of quality of service (QoS) in todays Internet is an area that attracts the current state-of-the-art research. In this paper, we study the effect of topological and traffic variations on the provision of QoS using RSVP/ns. In our performance evaluation, we focus on the effect of varying packet size, number of flows, and mixing of best-effort flows with RSVP flows on the bandwidth reservations.