Miracle-dz/UniFAR-FTUs huggingface dataset:
Aerobic capacity and cognitive control in elementary school-age children.

PURPOSE The current study examined the relationship between children's performance on the Progressive Aerobic Cardiovascular Endurance Run subtest of the FitnessGram® and aspects of cognitive control that are believed to support academic success. METHODS Hierarchical linear regression analyses were conducted on a sample of second- and third-grade children (n = 397) who completed modified versions of a flanker task and spatial n-back task to assess inhibitory control and working memory, respectively. RESULTS Greater aerobic fitness was significantly related to shorter reaction time and superior accuracy during the flanker task, suggesting better inhibitory control and the facilitation of attention in higher-fit children. A similar result was observed for the n-back task such that higher-fit children exhibited more accurate target detection and discrimination performance when working memory demands were increased. CONCLUSIONS These findings support the positive association between aerobic fitness and multiple aspects of cognitive control in a large sample of children, using a widely implemented and reliable field estimate of aerobic capacity. Importantly, the current results suggest that this relationship is consistent across methods used to assess fitness, which may have important implications for extending this research to more representative samples of children in a variety of experimental contexts.
Proses Fonologis dan Pengkaidahannya dalam Kajian Fonologi Generatif

Tujuan penelitian ini adalah untuk mengetahui proses-proses fonologis beberapa bahasa. Pendekatan yang digunakan adalah fonologi generatif. Data penelitian ini adalah data fonologis yang berasal dari beberapa bahasa. Data penelitian ini diambil dengan menggunakan metode refleksif introspektif untuk data bahasa yang dikuasai oleh penulis. Selain bahasa yang dikuasai penulis, data diambil dari buku-buku yang memuat data yang berasal dari bahasa lain. Ada beberapa cara menganalisis data. Yang pertama, mengumpulkan data dan mengidentifikasinya. Selanjutnya adalah mengklasifikasikan data, menganalisis data, membuat kaidah fonologis, dan menjelaskan hasil temuan. Dari analisis yang dilakukan, dapat disimpulkan bahwa fonologi generatif dapat menjadi pendekatan yang relevan yang dapat digunakan untuk menjelaskan proses fonologis bahasa-bahasa yang berbeda. Dengan menggunakan fonologi generatif, ditemukan beberapa proses fonologis bahasa antara lain penambahan bunyi, pelesapan bunyi, koalisi, asimilasi, dan metatesis. Kata Kunci: proses fonologis, kaidah fonologi, fonologi generatif
A single-chip dual-band CDMA2000 receiver for cellular terminals in 0.13 µm CMOS

Keeping pace with the steady advances in the development of even finer gate length technologies, CMOS has established as preferred process for radio-frequency design that enables the integration of complex digital circuitry on the same die at reasonable costs in terms of required area and power consumption. A single-chip dual-band CDMA2000 receiver based on zero-IF architecture is presented. In addition to all required analog building blocks for reception in the North-American cellular and PCS bands (Band Class 0 and 1), the chip features a fully integrated synthesizer including VCOs for minimum external component count, analog anti-aliasing filters, a fully configurable digital-front-end (DFE), DeltaSigma ADCs, a high-speed digital serial baseband (BB) interface, and a three-wire-bus configuration interface. The DFE's functionality includes sample- rate-conversion, channel filtering, dynamic range control, and signal conditioning for data transmission via a digital interface between RFIC and baseband IC. The receiver IC with a die size of 8 mm2 has been fabricated in 0.13-mum RF-CMOS and shows an error-vector-magnitude (EVM) of 3.1 % and a Rho of 0.998 at the digital baseband interface.
Palmprint feature extraction using weight coding based non-negative sparse coding

A novel palmprint feature extraction method is proposed by using the Weight Coding Based Non-negative Sparse Coding (WCBNNSC). The WCBNNSC algorithm can model the respective field of V1 in the primary visual system of brain. And this algorithm includes more image information than the early Non-negative Sparse Coding (NNSC). Utilizing the WCBNNSC algorithm, the feature basis vectors of palmprint images can be successfully learned. These features behave locality, orientation, and spatial selection, which is similar to the respective field feature of V1 in visual cortex. Further, using the features extracted, the palmprint reconstruction task can be successfully implemented. Moreover, compared with other palmprint feature extraction methods, simulation results show that our method proposed here is indeed efficient and useful in performing the feature extraction task of palmprint images.
Who Benefits from Increased Government Spending? A State-Level Analysis

We simultaneously identify two government spending shocks: military spending shocks as defined by Ramey (2011) and federal spending shocks as defined by Perotti (2008). We analyze the effect of these shocks on state-level personal income and employment. We find regional patterns in the manner in which both shocks affect state-level variables. Moreover, we find differences in the propagation mechanisms for military versus non-military spending shocks. The former benefits economies with larger manufacturing and retail sectors and states that receive military contracts. While non-military shocks also benefit states with the proper industrial mix, they appear to stimulate economic activity in lower-income states.
Short-packet communications with multiple antennas

Motivated by the current interest in ultra-reliable, low-latency, machine-type communication systems, we investigate the tradeoff between reliability, throughput, and latency in the transmission of information over multiple-antenna Rayleigh blockfading channels. Specifically, we obtain finite-blocklength, finiteSNR upper and lower bounds on the maximum coding rate achievable over such channels for a given constraint on the packet error probability. Numerical evidence suggests that our bounds delimit tightly the maximum coding rate already for short blocklengths (packets of about 100 symbols). Furthermore, our bounds reveal the existence of a tradeoff between the rate gain obtainable by spreading each codeword over all available time-frequency-spatial degrees of freedom, and the rate loss caused by the need of estimating the fading coefficients over these degrees of freedom. In particular, our bounds allow us to determine the optimal number of transmit antennas and the optimal number of time-frequency diversity branches that maximize the rate. Finally, we show that infinite-blocklength performance metrics such as the ergodic capacity and the outage capacity yield inaccurate throughput estimates.
Modeling the fifth dimension with scalars and gravity

A method for obtaining solutions to the classical equations for scalars plus gravity in five dimensions is applied to some recent suggestions for brane-world phenomenology. The method involves only first order differential equations. It is inspired by gauged supergravity but does not require supersymmetry. Our first application is a full nonlinear treatment of a recently studied stabilization mechanism for interbrane spacing. The spacing is uniquely determined after conventional fine-tuning to achieve a zero four-dimensional cosmological constant. If the fine-tuning is imperfect, there are solutions in which the four-dimensional branes are de Sitter or anti-de Sitter spacetimes. Our second application is a construction of smooth domain wall solutions which in a well-defined limit approach any desired array of sharply localized positive-tension branes. As an offshoot of the analysis we suggest a construction of a supergravity c function for nonsupersymmetric four-dimensional renormalization group flows. The equations for fluctuations about an arbitrary scalar-gravity background are also studied. It is shown that all models in which the fifth dimension is effectively compactified contain a massless graviton. The graviton is the constant mode in the fifth dimension. The separated wave equation can be recast into the form of supersymmetric quantum mechanics. The graviton wave functionmore » is then the supersymmetric ground state, and there are no tachyons. (c) 2000 The American Physical Society. « less
Kinesthetic Learning Style Preferences: A Survey of Indonesian EFL Learners by Gender

This study investigated predominant learning style of 3 rd semester students of English Language Education Program in Faculty of Cultural Studies at Universitas Brawijaya according to gender. Purposive sampling was used for this research and the sampling in this research was 100 students consist of 34 male students and 66 female students taken from 3 rd semester English Department students of Faculty of Cultural Studies at Universitas Brawijaya. All participants were administered an Indonesian translated version of Reid’s (1984) Perceptual Learning Style Preference Questionnaire consisting of Visual, Auditory, Kinesthetic, Tactile, Group, and Individual, included 30 items. This study used quantitative survey design and Microsoft Excel 2007 as the analysis software. The validity and the reliability of this research were calculated by SPSS v.21. The result indicated that predominant male’s learning style was Kinesthetic and estimated by 14 male students (41%) while female students become Kinesthetic and Group and estimated the same percentage, 21 students (332%) for Kinesthetic and 21 (32%) students for Group. The result of the study also shows that both male and female tend to be Kinesthetic. It is suggested that to the English department to adjust the academic activities with the learning styles to enhance educational achievement and encouraging students take responsibility in their whole learning.
Mutation of the Drosophila vesicular GABA transporter disrupts visual figure detection

SUMMARY The role of gamma amino butyric acid (GABA) release and inhibitory neurotransmission in regulating most behaviors remains unclear. The vesicular GABA transporter (VGAT) is required for the storage of GABA in synaptic vesicles and provides a potentially useful probe for inhibitory circuits. However, specific pharmacologic agents for VGAT are not available, and VGAT knockout mice are embryonically lethal, thus precluding behavioral studies. We have identified the Drosophila ortholog of the vesicular GABA transporter gene (which we refer to as dVGAT), immunocytologically mapped dVGAT protein expression in the larva and adult and characterized a dVGATminos mutant allele. dVGAT is embryonically lethal and we do not detect residual dVGAT expression, suggesting that it is either a strong hypomorph or a null. To investigate the function of VGAT and GABA signaling in adult visual flight behavior, we have selectively rescued the dVGAT mutant during development. We show that reduced GABA release does not compromise the active optomotor control of wide-field pattern motion. Conversely, reduced dVGAT expression disrupts normal object tracking and figure–ground discrimination. These results demonstrate that visual behaviors are segregated by the level of GABA signaling in flies, and more generally establish dVGAT as a model to study the contribution of GABA release to other complex behaviors.
Coarse and fine learning in deep networks

Evolutionary systems such as Learning Classifier Systems (LCS) are able to learn reliably in irregular domains, while Artificial Neural Networks (ANNs) are very successful on problems with an appropriate gradient. This study introduces a novel method for discovering coarse structure, using a technique related to LCS, in combination with gradient descent. The structure used is a deep feature network, with a number of properties of a higher level of abstraction than existing ANNs, for example the network is constructed based on co-occurrence relationships, and maintained as a dynamic population of features. The feature creation technique can be considered a coarse or rapid initialization technique, that constructs a network before subsequent fine-tuning using gradient descent. The process is comparable with, but distinct from, layer-wise pretraining methods that construct and initialize a deep network prior to fine-tuning. The approach we introduce is a general learning technique, with assumptions of the dimensionality of input, and the described method uses convolved features. Results of classification of MNIST images show an average error rate of 0.79% without pre-processing or pretraining, comparable to the benchmark result provided by Restricted Boltzmann Machines of 0.95%, and 0.79% using dropout, however based on a convolutional topology, and as such our system is less general than RBM techniques, but more general than existing convolutional systems because it does not require the same domain assumptions and pre-defined topology. Use of a randomly initialized network provides a much poorer result (1.25%) indicating the coarse learning process plays a significant role. Classification of NORB images is examined, with results comparable to SVM approaches. Development of higher level relationships between features using this approach offers a distinct method of learning using a deep network of features, that can be used in combination with existing techniques.
Effects of Preload on the Transmural Distribution of Perfusion and Pressure‐Flow Relationships in the Canine Coronary Vascular Bed

We studied the effects of preload on transmural myocardial perfusion and coronary pressure-flow relationships in mongrel dogs. The left circumflex (LC) artery was cannulated and perfused through an external circuit of rigid tubing originating in the left subclavian artery and containing an electromagnetic flowmeter (EMF), a solenoid, and a short segment of soft tubing which could be occluded. The solenoid, triggered by the R-wave of the ECG, was adjusted so that perfusion occurred only during diastole. Autoregulation was abolished by maximal vasodilation with carbocromen. In 16 dogs, overall radioactive microsphere flow in the perfused LC segment was 1.67 ± 0.17 (SKM) ml/min per g at normal preload and 1.54 ± 0.19 ml/min per g at elevated preload. The endocardial: epicardial flow ratio decreased from 0.76 ± 0.03 at normal preload to 0.55 ± 0.04 at elevated preload (P < 0.01). EMF pressure-flow curves, determined by stepwise constriction of the perfusion circuit in the same dogs, showed a rightward shift with increased preload and an increase in PZF, the pressure at which inflow became zero (12 ± 0.9 nun Hg at normal preload vs. 19 ± 1.0 mm Hg at elevated preload, P < 0.01). Microsphere pressure-flow curves in eight additional dogs suggested that a small endocardial: epicardial difference in diastolic PZF at normal preload is accentuated at elevated preload. We conclude that effects of increased preload produced by volume expansion are 2-fold: (1) a selective reduction of flow in the inner layers of the heart, and (2) a shift to the right of the diastolic pressure-flow relationship. The former seems reasonably related to direct effects of preload on intramyocardial tissue pressure, whereas the latter suggests additional effects of local reflex, myogenic or mechanical phenomena. Circ Res 46: 68-77, 1979
Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure

MOTIVATION Drawing inferences from large, heterogeneous sets of biological data requires a theoretical framework that is capable of representing, e.g. DNA and protein sequences, protein structures, microarray expression data, various types of interaction networks, etc. Recently, a class of algorithms known as kernel methods has emerged as a powerful framework for combining diverse types of data. The support vector machine (SVM) algorithm is the most popular kernel method, due to its theoretical underpinnings and strong empirical performance on a wide variety of classification tasks. Furthermore, several recently described extensions allow the SVM to assign relative weights to various datasets, depending upon their utilities in performing a given classification task. RESULTS In this work, we empirically investigate the performance of the SVM on the task of inferring gene functional annotations from a combination of protein sequence and structure data. Our results suggest that the SVM is quite robust to noise in the input datasets. Consequently, in the presence of only two types of data, an SVM trained from an unweighted combination of datasets performs as well or better than a more sophisticated algorithm that assigns weights to individual data types. Indeed, for this simple case, we can demonstrate empirically that no solution is significantly better than the naive, unweighted average of the two datasets. On the other hand, when multiple noisy datasets are included in the experiment, then the naive approach fares worse than the weighted approach. Our results suggest that for many applications, a naive unweighted sum of kernels may be sufficient. AVAILABILITY http://noble.gs. washington.edu/proj/seqstruct
Impact of psychological contract fulfillment on organizational citizenship behavior: mediating role of perceived organizational support

Purpose This study aimed to investigate the impact of psychological contract fulfillment (independent) on organizational citizenship behavior (dependent) with mediating role of perceived organizational support. Design/methodology/approach Quantitative methodology was adopted to achieve the aim of this study and data were collected via questionnaire through employee-supervisor/colleague dyed. Various five and four star hotel staff members in Pakistan were the target population, eliciting a recorded sample of 418 employees and 105 supervisors/colleagues. Findings The study revealed that psychological contract fulfillment has a positive impact on perceived organizational support and organizational citizenship behavior. The partial mediating role of perceived organizational support between the dependent and independent variables was also confirmed. Research limitations/implications Among the implications, novel theoretical underpinning of organizational support theory was established in psychological contract.
The effects of cooperative learning on enhancing Hong Kong fifth graders' achievement goals, autonomous motivation and reading proficiency

Research indicates that cooperative learning with teacher-guided instruction is more effective in helping young children to learn than cooperative learning with minimal guidance. In the present study, two different cooperative learning activities (jigsaw and drama) and a control condition (a traditional teacher-led approach) were compared. The participants were 279 Grade 5 Hong Kong students located in nine classrooms. The two experimental conditions emphasised teachers' cognitive support in helping students to understand a text through both teacher-led and student-led activities. Post-test data included a reading comprehension test and three questionnaires that investigated students' goal orientations, initial level of relative autonomy and perceptions of instructional practices. Findings indicate that students in the jigsaw group outperformed students in both the drama group and the control group in the reading comprehension test. The implications of conducting cooperative learning activities with well-planned teacher guidance are discussed.
Effective connectivity of the subthalamic nucleus–globus pallidus network during Parkinsonian oscillations

The firing of subthalamic nucleus (STN) neurons and two types of external globus pallidus (GP) neuron becomes excessively and rhythmically synchronised in Parkinsonism, but the substrates for this are unknown. We recorded abnormal oscillatory firing of STN and GP neurons in vivo after chronic dopamine loss, and then used computational models to explore the underlying effective connections and physiological parameters. The best candidate model accurately reproduced our electrophysiological data and predicted that the input and output connections of the two types of GP neuron are quantitatively different, including inhibitory connections from striatum and excitatory connections from thalamus and STN. The two types of GP neuron were also predicted to have different intrinsic physiological properties, reflected in distinct autonomous firing rates. Our results elucidate potential substrates of GP functional dichotomy, and suggest that rhythmic inputs from striatum, thalamus and cortex orchestrate STN–GP network activity during Parkinsonian oscillations.
Adolescent Maturation of Dopamine D1 and D2 Receptor Function and Interactions in Rodents

Adolescence is a developmental period characterized by heightened vulnerability to illicit drug use and the onset of neuropsychiatric disorders. These clinical phenomena likely share common neurobiological substrates, as mesocorticolimbic dopamine systems actively mature during this period. Whereas prior studies have examined age-dependent changes in dopamine receptor binding, there have been fewer functional analyses. The aim of the present study was therefore to determine whether the functional consequences of D1 and D2-like activation are age-dependent. Adolescent and adult rats were given direct D1 and D2 agonists, alone and in combination. Locomotor and stereotypic behaviors were measured, and brains were collected for analysis of mRNA expression for the immediate early genes (IEGs), cfos and arc. Adolescents showed enhanced D2-like receptor control of locomotor and repetitive behaviors, which transitioned to dominant D1-like mechanisms in adulthood. When low doses of agonists were co-administered, adults showed supra-additive behavioral responses to D1/D2 combinations, whereas adolescents did not, which may suggest age differences in D1/D2 synergy. D1/D2-stimulated IEG expression was particularly prominent in the bed nucleus of the stria terminalis (BNST). Given the BNST’s function as an integrator of corticostriatal, hippocampal, and stress-related circuitry, and the importance of neural network dynamics in producing behavior, an exploratory functional network analysis of regional IEG expression was performed. This data-driven analysis demonstrated similar developmental trajectories as those described in humans and suggested that dopaminergic drugs alter forebrain coordinated gene expression age dependently. D1/D2 recruitment of stress nuclei into functional networks was associated with low behavioral output in adolescents. Network analysis presents a novel tool to assess pharmacological action, and highlights critical developmental changes in functional neural circuitry. Immature D1/D2 interactions in adolescents may underlie their unique responses to drugs of abuse and vulnerability to psychopathology. These data highlight the need for age-specific pharmacotherapy design and clinical application in adolescence.