Miracle-dz/UniFAR-FTUs huggingface dataset:
Child self-report and parent ratings of health-related quality of life in school-aged children born preterm

Recent progress in science and medicine is that regions such as the United States, Canada, Australia, and Western Europe have witnessed dramatic declines in infant morbidity and mortality. The most significant of these declines has occurred among infants born prematurely and low birth weight (LBW)—the cohort that represents the highest proportion of illness and death among infants Despite these medical advances, recent longitudinal studies have provided clear evidence of physical health problems; cognitive and neuropsychological dysfunction; and other social, emotional, and behavioral problems among children born prematurely. A number of studies have indicated that premature and LBW infants are still at risk for psychosocial, physical, and mental problems despite the immediate contributions of post-natal interventions to their increased chance for survival. The extant research has demonstrated that children born prematurely and LBW are at risk for problems in health, neuropsychological functioning, learning, academic achievement, behavior, and psychosocial adjustment. Research has further demonstrated that a variety of physical and psychological conditions are associated with poorer QOL among children. However, few studies have examined pediatric QOL among preterm school-aged children. Moreover, existing studies have not explored the relationship between cognitive, academic, and social/emotional functioning and QOL. The current study compared child and parent ratings of health-related quality of life among schoolaged children born preterm (n = 26) and full-term (n = 28). Given the increased rates of physical, psychological, and cognitive problems among the preterm population, it was
Synthesis, Characterization, and Antibacterial Activities of Novel Sulfonamides Derived through Condensation of Amino Group Containing Drugs, Amino Acids, and Their Analogs

Novel sulfonamides were developed and structures of the new products were confirmed by elemental and spectral analysis (FT-IR, ESI-MS, 1HNMR, and 13CNMR). In vitro, developed compounds were screened for their antibacterial activities against medically important gram (+) and gram (−) bacterial strains, namely, S. aureus, B. subtilis, E. coli, and K. pneumoniae. The antibacterial activities have been determined by measuring MIC values (μg/mL) and zone of inhibitions (mm). Among the tested compounds, it was found that compounds 5a and 9a have most potent activity against E. coli with zone of inhibition: 31 ± 0.12 mm (MIC: 7.81 μg/mL) and 30 ± 0.12 mm (MIC: 7.81 μg/mL), respectively, nearly as active as ciprofloxacin (zone of inhibition: 32 ± 0.12 mm). In contrast, all the compounds were totally inactive against the gram (+) B. subtilis.
A Rate Distortion-Based Network Coding Design for Video Transmission

In the process of video transmission, packets loss may lead to the reconstruction distortion. When network coding is used for video transmission, the original error will cause propagation in the following nodes. To reduce the impact of error propagation, a random linear network coding (RLNC) based on the rate distortion is proposed to realize reliable video transmission. The method finds out the optimal rate allocation through rate distortion calculation to minimize the impact of packet loss. In addition, it adopts non-strict lower triangular global coding matrix (GCM) to prevent from declining of reconstructed quality of video caused by the insufficient rank in the GCM at the decoder. Theoretical analysis and simulation results show the correctness and effectiveness of the method.
Online parallel monitoring via hard-thresholding post-change estimation

The online parallel monitoring problem is studied when one is monitoring large-scale data streams, and an event occurs at an unknown time and affects an unknown subset of data streams. Efficient online parallel monitoring schemes are developed by combining the standard sequential change-point method with hard-thresholding post-change estimation. Theoretical analysis and simulation study demonstrate the usefulness of hard-thresholding for online parallel monitoring.
Spectrum Simulation Testbed for Dynamic Spectrum Access

The joint spectrum center (JSC) has developed a Spectrum Simulation Testbed to model networking and spectrum aspects of wireless tactical networks. The spectrum simulation testbed uses OPNET Modeler to model a dynamic spectrum manager (DSM) technique that uses geographic position and spectral use information to assign spectrum resources to communication nodes, while maintaining a sufficient level of interference protection to and from other environmental equipment in the same band. The prototype DSM is supported by a network management capability called mobile ad-hoc network (MANET) quality of service (QoS) that determines when the prototype DSM should be invoked. This paper will demonstrate how the Spectrum Simulation Testbed can be used to assess the spectrum resources needed and utilized for wireless tactical MANETs, when two different spectrum management (SM) methodologies are employed. Current SM will be compared to a DSM technique. These comparisons will be based upon the total spectrum bandwidth utilized and the spectrum efficiency achieved.
Situation Dependent Spatial Abstraction in Reinforcement Learning Based on Structural Knowledge

State space abstraction reduces the size of a representation by factoring out details that are not relevant for solving a task at hand. But even in abstract representations not every detail is relevant in any situation. In cases where the structure of the environment only allows for one particular action selection, all information that does not relate to the structure can be omitted. We present a method to identify such cases in a reinforcement learning setting and abstract from non-structural details when appropriate to shrink the state space and allow for knowledge reuse. A signicant performance improvement of this approach is demonstrated in a goal-directed robot navigation task.
NHI-NSF Visualization Research Challenges Report

In this report we describe some of the remarkable achievements visualization enables and discuss the major obstacles blocking the discipline ´ s advancement. Our ﬁndings and recommendations reﬂect not only information gathered from visualization and applications scientists during two workshops on Visualization Research Challenges but also input from the larger visualization community. This report is the product of the Visualization Research Challenges a pair of sponsored We are to the expert and visionary panelists to report on the potential of visualization this new report is to evaluate the progress of the field of visualization, to help focus and direct future research projects, and to provide guidance on how to apportion as and methods in the fast-paced realm of technology. We explore the state of the field, examine the potential impact of visualization on areas and present our findings and
Recognition of lung nodules from X-ray CT images using 3D Markov random field models

In this-paper we propose a new recognition method of lung nodule from X-ray CT images using 3D Markov random field (MRF) models. Pathological shadow candidates are detected by a mathematical morphology filter and volume of interest (VOI) areas which include the shadow candidates are extracted. The probabilities of the hypotheses that the VOI areas come from nodules (which are candidates of cancers) and blood vessels are calculated using nodule and blood vessel models evaluating the relations between these object models by 3D MRF models. If the probabilities for the nodule models are higher, the shadow candidates are determined to be abnormal. By applying this new recognition method to actual 38 CT images, good results were obtained.
TokyoTech's TRECVID2007 Notebook

1 Summary For the high-level feature extraction task, we use visual features (visual words of keyframe images and motion features), and do not use any audio information. Maximum entropy models [1] are employed to model these visual features. Because there was a material mistake in our submission, the inferred Average Precisions of our runs was almost zero. Therefore, in this notebook, we also show the results evaluated by ourselves with the truth judgments flle (qrels flle). Figure 1 brie∞y shows our visual feature extraction process. From each keyframe, we flrst extract A‐ne regions, then describe each of the regions with a SIFT descriptor. We quantize the SIFT descriptor using a tree-cluster codebook. We call this quantized descriptor \visual word". In addition to the visual word itself, we combine the visual word and motion information of the corresponding A‐ne region to get a \motion feature". Finally, we use the number of occurrences of the visual words and the motion features to construct a feature vector for a maximum entropy model.
The Application of Clustering Optimization in Data Mining Based on Multiple Kernel Function FCM Algorithm

Mono-nuclear kernel function is presented in this paper based on the fuzzy c-means clustering algorithm for data clustering to do the improvement in the field of data mining, puts forward the fuzzy c-means clustering algorithm based on multiple kernel function (MKFCM) algorithm. Under fully unsupervised learning method, a set of Gaussian kernel function combination are assigned different weights resolution to a new multiple kernel function, through application of the single fixed kernel function of the fuzzy c-means clustering algorithm (KFCM algorithm) has obvious advantages and reliability in the clustering class compared. The simulation results indicate that the MKFCM algorithm can be size and a few kinds of density difference very big bunch of good classification, compared KFCM algorithm of the phenomenon of the overlap between in data clustering have significant performance advantages, also has a better application prospect in the field of data mining.
Reducing cogging torque in permanent-magnet synchronous motors by auxiliary teeth method

Cogging torque in permanent-magnet motors is one of the most important problems to be considered in high performance applications especially in low speed and direct drive applications. In this paper, the analytical expression for cogging torque in permanent-magnet synchronous motors (PMSM) with auxiliary teeth is derived by the energy method and the Fourier series analysis, based on the air gap permeance and the flux density distribution in an equivalent slotless machine. Analytical method was proposed to determine an appropriate scope of auxiliary tooth width. In order to reduce cogging torque to the maximum extent, cogging torque corresponding to different slot openings was analyzed. To determine the auxiliary teeth width accurately, finite element method (FEM) which considered the effects of flux leakage and saturation was proposed. And then on this basis auxiliary teeth height was determined by analyzing the distribution of the radial component of the flux density in the air gap. Finally, calculation results of cogging torque corresponding to different distributions of the auxiliary teeth, the auxiliary teeth width as well as the auxiliary height were discussed.
Automatic detection of irregular phonation in continuous speech

Voice quality is one of the most important source characteristics of a speaker’s speech production process, and creakiness is one of the variations of voice quality. This paper describes the development of an algorithm to automatically detect irregular phonation, including creakiness and other variations, in continuous running speech. The algorithm is an extension of the Aperiodicity, Periodicity and Pitch (APP) Detector. The algorithm has been run on 485 files of the TIMIT database, which contained 677 instances of irregular phonation. The test set comprised of 97 speakers, of which 57 were male and 40 were female. The algorithm has been found to give an accuracy of 86.7 % on average, with performance being almost the same for both male and female speakers. Automatic detection of irregular phonation should help characterize speakers for speaker identification applications.
ERP a moving target

Enterprise Resource Planning systems are central elements in long term wide-ranging design and use networks. Present ERP research focuses on single-enterprise implementation and fails to address important features of the ERP networks such as multi-spatiality, the design of the generic and the dynamics over time. A six-field matrix is proposed as a conceptual frame, encompassing short- and long-term, and micro, meso and macro elements and leaving implementation as but one out of six aspects. Empirical research shows the long-term drift of an ERP community crosscutting locally and globally, and a single-enterprise case combines implementation and use underlining the marked reconfiguration of ERP modules and processes in a professional service company.
Characters and patterns of communities in networks

In this paper, we propose some new notions to characterize and analyze the communities. The new notions are general characters of the communities or local structures of networks. At first, we introduce the notions of internal dominating set and external dominating set of a community. We show that most communities in real networks have a small internal dominating set and a small external dominating set, and that the internal dominating set of a community keeps much of the information of the community. Secondly, based on the notions of the internal dominating set and the external dominating set, we define an internal slope (ISlope, for short) and an external slope (ESlope, for short) to measure the internal heterogeneity and external heterogeneity of a community respectively. We show that the internal slope (ISlope) of a community largely determines the structure of the community, that most communities in real networks are heterogeneous, meaning that most of the communities have a core/periphery structure, and that both ISlopes and ESlopes (reflecting the structure of communities) of all the communities of a network approximately follow a normal distribution. Therefore typical values of both ISolpes and ESoples of all the communities of a given network are in a narrow interval, and there is only a small number of communities having ISlopes or ESlopes out of the range of typical values of the ISlopes and ESlopes of the network. Finally, we show that all the communities of the real networks we studied, have a three degree separation phenomenon, that is, the average distance of communities is approximately 3, implying a general property of true communities for many real networks, and that good community finding algorithms find communities that amplify clustering coefficients of the networks, for many real networks.
Customer Satisfaction With Internet Banking Service Quality In The Ghanaian Banking Industry

This paper empirically examines Customer Satisfaction (CS) with internet banking service quality (IBSQ) in the Ghanaian banking industry. The study was a cross-sectional survey that employed the use self-administered questionnaire to collect primary data from a sample of 200 respondents of two banks through personal contact. The findings are that customers of Merchant Bank, Ghana (MBG) are more satisfied with the IBSQ than those of Ghana Commercial Bank (GCB). Moreover, income influenced the satisfaction of customers for IBSQ generally. It was found that, generally, customers of the two banks are dissatisfied with the promptness of reception of responses to customer request, the ability to be guided online to res olve problems, offering of preferentially lower fees/ rates and charges, and reasonability of the transaction fee for online banking transactions, but are less satisfied with the quickness of web pages loading when using online banking transactions. Theoretical and managerial implications of the findings have been discussed, and limitations are noted. The paper contributes to the literature in area of customer satisfaction in electronic banking.
Resolution of an Ambiguity in Dynamo Theory and Its Consequences for Back-Reaction Studies

An unsolved problem in turbulent dynamo theory is the "back-reaction" problem: to what degree does the mean magnetic field suppress the turbulent dynamo coefficients that are needed to drive its growth? The answer will ultimately derive from a combination of numerical and analytical studies. Here we show that analytic approaches to the dynamo and back-reaction problems require one to separate turbulent quantities into two components: those influenced by the mean field (which are therefore anisotropic) and those independent of the mean field (and are therefore isotropic), no matter how weak the mean field is. Upon revising the standard formalism to meet this requirement, we find the following: (1) The two types of components often appear in the same equation, so that standard treatments, which do not distinguish between them, are ambiguous. (2) The usual first-order smoothing approximation that is necessary to make progress in the standard treatment is unnecessary when the distinction is made. (3) In contrast to previous suggestions, the current helicity correction to the dynamo α-coefficient is actually independent of the mean field and therefore cannot be interpreted as a quenching.
The concept assignment problem in program understanding

The problem of discovering individual human oriented concepts and assigning them to their implementation-oriented counterparts for a given program is the concept assignment problem. It is argued that the solution to this problem requires methods that have a strong plausible reasoning component. These ideas are illustrated through recovery system called DESIRE. DESIRE is evaluated based on its use on real-world problems over the years. <<ETX>>
Improving recurrent network load forecasting

We present a not fully connected recurrent network applied to the problem of load forecasting. Although many authors have pointed out that recurrent networks were able to model NARMAX processes, we present a constructing scheme for the MA part. In addition we present a modification of the learning step which improves learning convergence and the accuracy of the forecast. At last, the use of a continuous learning scheme and a robust learning scheme, which appeared to be necessary when using a MA part, enables us to reach a good precision of the forecast, compared to the accuracy of the model in use at the utility at present.
On the multicast throughput for half-duplex butterfly network using deterministic approach

This paper considers the multicast throughput of a special butterfly network which is made up of two sources, two destinations and a half-duplex relay. Each destination requires to decode the data from two independent sources. All the nodes are assumed to be half-duplex. When the relay transmits signal, other nodes of the system should keep in receiving state to reduce processing complexity and interference. First, we present an explicit expression of the maximal multicast throughput in deterministic butterfly network which is derived from Aves-timehr, Diggavi and Tse's deterministic model. Based on the result obtained in deterministic butterfly network, we propose a near-optimal transmitting and decoding policy to approach the maximal throughput by using network coding in Gaussian butterfly network. Finally, we evaluate the gap between our achievable rate region with an outer bound and show it consists of a constant item which is less than 2.45 bits and a variable item which only exists in some cases and increases logarithmically with the signal to noise ratio (SNR) over all the links.
Seamless Mobility Management between IP-based Networks

This article represents an approach of providing seamless services to the mobile consumer in an area having convergence of different Radio Access Technologies (RATs). In particular, the proposed framework is capable of managing session mobility between General Packet Radio Service (GPRS) and Worldwide Interoperability for Microwave Access (WiMAX) at the core network level. Within this interworking architecture, IP Multimedia Subsystem (IMS) was applied as a common platform at the application layer for session mobility and Mobile IP was applied at the network layer to maintain IP mobility. The unique contribution of this architecture is the hypothetical user mobile device having multiple transceivers along with intelligence of making decisions of handover. The article comes to an end by narrating the potential advantages of the proposed approach in eliminating the packet loss due to handover.
Circulating adiponectin and plasma fatty acid profile.

BACKGROUND The amount and type of fat in the diet influence the development of obesity and related inflammatory activity. Knowledge of the possible influence of dietary habits on circulating adiponectin, a molecule with putative antiinflammatory properties, may be helpful in preventing atherosclerosis and type 2 diabetes. METHODS The association between dietary fat, as inferred from plasma fatty acid composition (gas-liquid chromatography), and circulating adiponectin (RIA) was evaluated in 116 healthy individuals. RESULTS The proportion of saturated fatty acids in plasma was significantly associated with circulating adiponectin concentration (r = -0.24; P = 0.01). Specifically, percentage of palmitic acid (C16:0) was significantly associated with lower adiponectin concentration (r = -0.28; P = 0.002), particularly among women (r = -0.37; P = 0.02) and nonsmokers (r = -0.30; P = 0.007). Percentage of myristic acid (C14:0) was also significantly associated with lower adiponectin among nonsmokers (r = -0.26; P = 0.02) and women (r = -0.39; P = 0.01). The other fatty acids were not significantly associated with adiponectin except for eicosanoic acid (C20:1 omega-9), which was significantly and positively associated with adiponectin in all individuals (r = 0.23; P = 0.01). This latter association was most significant in smokers (r = 0.43; P = 0.007). In a multivariate regression analysis to predict circulating adiponectin, after controlling for age, body mass index, waist-to-hip ratio, and the individual remaining fatty acids, the percentages of palmitic (P = 0.005) and eicosanoic acid (P = 0.03) contributed independently (6% and 3%, respectively) to adiponectin variance. Among nonsmokers, the percentages of palmitic acid (P = 0.01) and omega-3 fatty acids contributed 8% and 7%, respectively, to adiponectin variance. Among smokers, the percentage of eicosanoic acid (P = 0.03) contributed to 10% of adiponectin variance, independently of body mass index, age, waist-to hip ratio, and the remaining individual fatty acids. CONCLUSIONS Saturated and omega-3 fatty acids of dietary origin (as inferred from plasma fatty acid concentration) are associated with circulating adiponectin concentrations in healthy humans. The proportion of eicosanoic acid also appears to be positively associated with circulating adiponectin. The knowledge of how these interactions occur may be helpful in the planning of dietary measures aimed at the modulation of inflammatory activity.