Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of a Teamwork Model

INTRODUCTION For heterogeneous agents working together to achieve complex goals, teamwork (Jennings, 1995; Yen, Yin, Ioerger, Miller, Xu, & Volz, 2001; Tambe, 1997a) has emerged as the dominant coordination paradigm. For domains as diverse as rescue response, military, space, sports, and collaboration between human workmates, flexible, dynamic coordination between cooperative agents needs to be achieved despite complex, uncertain, and hostile environments. There is now emerging consensus in the multiagent arena that for flexible teamwork among agents, each team member is provided with an explicit model of teamwork, which entails commitments and responsibilities as a team member. This explicit modeling allows the coordination to be robust, despite individual failures and unpredictably changing environments. Building on the well-developed theory of joint intentions (Cohen & Levesque, 1991) and shared plans (Grosz & Kraus, 1996), the STEAM teamwork model (Tambe, 1997a) was operationalized as a set of domain independent rules that describe how teams should work together. This domain-independent teamwork model has been successfully applied to a variety of domains. From combat air missions (Hill, Chen, Gratch, Rosenbloom, & Tambe, 1997) to robot soccer (Kitano, Asada, Kuniyoshi, Noda, Osawa, & Matsubara, 1997) to teams supporting human organizations (Pynadath & Tambe, 2003) to rescue response (Scerri, Pynadath, Johnson, P., Schurr, Si, & Tambe, 2003), applying the same set of STEAM rules has resulted in successful coordination between heterogeneous agents. The successful use of the same teamwork model in a wide variety of diverse domains provides compelling evidence that it is the principles of teamwork, rather than exploitation of specific domain phenomena, that underlie the success of teamwork-based approaches.
Adaptive service differentiation for QoS provisioning in IEEE 802.11 wireless ad hoc networks

The proposed scheme IEEE 802.11e draft standard defines new MAC protocol for QoS in wireless networks, namely HCF and EDCF. EDCF is a contention based channel access scheme and is part of HCF for infrastructure networks and may be used as a separate coordination function for wireless Ad-hoc networks. In this paper we propose to enhance EDCF with a dynamic traffic class's management protocol, which allows firstly, a guarantee of QoS to the sensitive applications some as the network state. Secondly, a sliding QoS differentiation between the Traffic Classes (TC) according to the instantaneous channels fluctuations. This sliding differentiation is based on a dynamic tune of the IEEE 802.11 MAC's parameters. The performances of the proposed scheme namely AMPA (Adaptive MAC Parameters), are extensively investigated by simulations. Results obtained indicate that AMPA scheme outperforms both DCF and EDCF.
Regulatory Properties of ADP Glucose Pyrophosphorylase Are Required for Adjustment of Leaf Starch Synthesis in Different Photoperiods1[W][OPEN]

The properties of a key enzyme of starch synthesis permit adjustment of this process under different day lengths. Arabidopsis (Arabidopsis thaliana) leaves synthesize starch faster in short days than in long days, but the mechanism that adjusts the rate of starch synthesis to daylength is unknown. To understand this mechanism, we first investigated whether adjustment occurs in mutants lacking components of the circadian clock or clock output pathways. Most mutants adjusted starch synthesis to daylength, but adjustment was compromised in plants lacking the GIGANTEA or FLAVIN-BINDING, KELCH REPEAT, F BOX1 components of the photoperiod-signaling pathway involved in flowering. We then examined whether the properties of the starch synthesis enzyme adenosine 5′-diphosphate-glucose pyrophosphorylase (AGPase) are important for adjustment of starch synthesis to daylength. Modulation of AGPase activity is known to bring about short-term adjustments of photosynthate partitioning between starch and sucrose (Suc) synthesis. We found that adjustment of starch synthesis to daylength was compromised in plants expressing a deregulated bacterial AGPase in place of the endogenous AGPase and in plants containing mutant forms of the endogenous AGPase with altered allosteric regulatory properties. We suggest that the rate of starch synthesis is in part determined by growth rate at the end of the preceding night. If growth at night is low, as in short days, there is a delay before growth recovers during the next day, leading to accumulation of Suc and stimulation of starch synthesis via activation of AGPase. If growth at night is fast, photosynthate is used for growth at the start of the day, Suc does not accumulate, and starch synthesis is not up-regulated.
The Siberian High: teleconnections, extremes and association with the Icelandic Low

A 60 year minimum temperature record of 11 stations in inner Eurasia enabled the characterization of the Siberian High (SH) intensity. The decline in the SH intensity is observed in tandem with the positive mode of the Arctic Oscillation (AO), both increasing in recent years. The coldest 1968–1969 winter in the 60 year period corresponds with the lowest AO annual index value. Spatial correlation analyses indicate that enhanced cyclogenetic conditions over the eastern flank of the Icelandic Low (IL) are associated with a milder SH. Seasonal composite analyses of the circulation pattern during the coldest 1968–1969 winter are characterized by a retreat of the IL, allowing a westward expansion of the SH cold core. A robust methodology, assuring an adequate representation of extremely cold spells in both their extent and duration, was developed. This methodology yielded three exceptional events, the most severe one lasting 10 days and affecting all stations in the SH domain. Analysing this event on a fine temporal resolution enabled the detection of short‐term synoptic scale processes, such as the polar air mass penetration, resulting in a mean minimum temperature of − 40 °C over the whole domain. This short‐term polar air incursion and its termination featuring this spell, as modulated by the location of the IL, point at its important role in modifying the SH. Copyright © 2012 Royal Meteorological Society
The role of GABRA2 in alcohol dependence, smoking, and illicit drug use in an Australian population sample.

BACKGROUND Multiple studies have shown that genetic variation in the alpha-2 subunit of the gamma-aminobutyric acid type A (GABA(A)) receptor (GABRA2) is associated with risk for alcohol dependence. Recent reports have suggested that GABRA2 may exert its influence on dependence through factors such as sensitivity to alcohol's intoxicating effects and that GABRA2 may also contribute to a common underlying genetic vulnerability to both alcohol and drug dependence. The present study tested for association between GABRA2 and alcohol dependence, smoking, and illicit drug use within the Australian population. METHODS We genotyped 11 single nucleotide polymorphisms (SNPs) within or flanking GABRA2 in 4597 subjects (34.6% males) from 2618 families comprising 814 monozygotic pairs, 1177 dizygotic pairs, and 627 twins whose co-twin did not participate. Family-based association tests were conducted for binary and quantitative measures of alcohol dependence, smoking, and cannabis and other illicit drug use. RESULTS We observed evidence of association (p < 0.05) between multiple GABRA2 SNPs and quantitative measures of alcohol dependence, including symptom scores and principal component factor scores from the 9 criteria for DSM-IV alcohol dependence, in the opposite direction to that previously reported. In contrast, GABRA2 was not associated overall with dichotomous measure of alcohol dependence nor with smoking, cannabis, or illicit drug use. CONCLUSIONS The GABRA2 allelic associations found in clinical case-control studies have detectable but minor effects on DSM-defined alcohol dependence in the general community. Systematic comparisons of allelic effects on alcohol dependence in clinical cases and in the general community are required.
Importance-driven visualization layouts for large time series data

Time series are an important type of data with applications in virtually every aspect of the real world. Often a large number of time series have to be monitored and analyzed in parallel. Sets of time series may show intrinsic hierarchical relationships and varying degrees of importance among the individual time series. Effective techniques for visually analyzing large sets of time series should encode the relative importance and hierarchical ordering of the time series data by size and position, and should also provide a high degree of regularity in order to support comparability by the analyst. In this paper, we present a framework for visualizing large sets of time series. Based on the notion of inter time series importance relationships, we define a set of objective functions that space-filling layout schemes for time series data should obey. We develop an efficient algorithm addressing the identified problems by generating layouts that reflect hierarchy and importance based relationships in a regular layout with favorable aspect ratios. We apply our technique to a number of real world data sets including sales and stock data, and we compare our technique with an aspect ratio aware variant of the well known TreeMap algorithm. The examples show the advantages and practical usefulness of our layout algorithm.
Effect of pomegranate seed oil on serum TNF-α level in dyslipidemic patients

Pomegranate punicic acid and pomegranate fruit extracts have the potential effects in inhibiting tumour necrosis factor-α (TNF-α) and inflammatory diseases. The aim of this study was to evaluate the effect of pomegranate seed oil (PSO) consumption on serum TNF-α level in dyslipidemic patients. Fifty-one subjects with serum total cholesterol concentration >200 mg/dl and serum triglyceride concentrations >150 mg/dl were randomly assigned into the PSO (n = 25) and placebo (n = 26) groups. Subjects were given 400 mg PSO or placebo capsules twice daily for 4 weeks. Six patients were excluded because of complications or lack of compliance. Serum TNF-α level was measured at baseline and after 4 weeks. Mean (SD) serum concentration of TNF-α decreased from 14.73 ± 5.25 to 13.28 ± 3.79 pg/ml in the PSO group (P = NS). Corresponding values in the placebo group were 12.46 ± 1.67 versus 13.14 ± 1.67 pg/ml (P = NS). In conclusion, administration of PSO in dyslipidemic patients does not affect the serum TNF-α.
An in vitro nuclear disassembly system reveals a role for the RanGTPase system and microtubule-dependent steps in nuclear envelope breakdown

During prophase, vertebrate cells disassemble their nuclear envelope (NE) in the process of NE breakdown (NEBD). We have established an in vitro assay that uses mitotic Xenopus laevis egg extracts and semipermeabilized somatic cells bearing a green fluorescent protein–tagged NE marker to study the molecular requirements underlying the dynamic changes of the NE during NEBD by live microscopy. We applied our in vitro system to analyze the role of the Ran guanosine triphosphatase (GTPase) system in NEBD. Our study shows that high levels of RanGTP affect the dynamics of late steps of NEBD in vitro. Also, inhibition of RanGTP production by RanT24N blocks the dynamic rupture of nuclei, suggesting that the local generation of RanGTP around chromatin may serve as a spatial cue in NEBD. Furthermore, the microtubule-depolymerizing drug nocodazole interferes with late steps of nuclear disassembly in vitro. High resolution live cell imaging reveals that microtubules are involved in the completion of NEBD in vivo by facilitating the efficient removal of membranes from chromatin.
Distributed Power-law Graph Computing: Theoretical and Empirical Analysis

With the emergence of big graphs in a variety of real applications like social networks, machine learning based on distributed graph-computing (DGC) frameworks has attracted much attention from big data machine learning community. In DGC frameworks, the graph partitioning (GP) strategy plays a key role to affect the performance, including the workload balance and communication cost. Typically, the degree distributions of natural graphs from real applications follow skewed power laws, which makes GP a challenging task. Recently, many methods have been proposed to solve the GP problem. However, the existing GP methods cannot achieve satisfactory performance for applications with power-law graphs. In this paper, we propose a novel vertex-cut method, called degree-based hashing (DBH), for GP. DBH makes effective use of the skewed degree distributions for GP. We theoretically prove that DBH can achieve lower communication cost than existing methods and can simultaneously guarantee good workload balance. Furthermore, empirical results on several large power-law graphs also show that DBH can outperform the state of the art.
FinFET-Based Power Management for Improved DPA Resistance with Low Overhead

Differential power analysis (DPA) is a side-channel attack that statistically analyzes the power consumption of a cryptographic system to obtain secret information. This type of attack is well known as a major threat to information security. Effective solutions with low energy and area cost for improved DPA resistance are urgently needed, especially for energy-constrained modern devices that are often in the physical proximity of attackers. This article presents a novel countermeasure against DPA attacks on smart cards and other digital ICs based on FinFETs, an emerging substitute for bulk CMOS at the 22nm technology node and beyond. We exploit the adaptive power management characteristic of FinFETs to generate a high level of noise at critical moments in the execution of a cryptosystem to thwart DPA attacks. We demonstrate the effectiveness of the proposed countermeasure by developing a simple power model for estimating DPA spikes. We then validate the model by carrying out DPA attacks on an ASIC implementation of the advanced encryption standard system via gate-level simulation. Both modeling and simulation-based experiment indicate that with the proposed countermeasure, even 8,000,000 power acquisitions are not sufficient to reveal the secret key. As opposed to other countermeasures presented in the literature, the proposed hardware design requires less than 1% increase in area and 15% increase in total energy consumption without any extra delay in the critical path. The proposed method is generic and can be applied to other encryption algorithms as well.
Detection of Correlations in tRNA Sequences with Structural Implications

Using an flexible representation of biological sequences, we have performed a comparative analysis of 1208 known tRNA sequences. We believe we our technique is a more sensitive method for detecting structural and functional relationships in sets of aligned sequences because we use a flexible representation (for sequences), as well as a general statistical method that can detect a wide range of relationships between positions in a sequence. Our method utilizes functional classifications of the sequence building-blocks (nucleotide bases and amino acids) based on physical or chemical properties. This flexibility in sequence representation improves the significance of finding sequence relationships mediated by the defining property. For example, using a purine/pyrimidine classification, we can detect base-stacking interactions in sets of nucleotide sequences that form base-paired helices. We use several statistical measures, including chi 2-tests, Monte Carlo simulations and an information measure to detect significant correlations in sequences. In this paper we illustrate our method by analyzing a set of tRNA sequences and showing that the correlations our program discovers, in each case, correspond to the known base-pairing and higher order interactions observed in tRNA crystal structures. Furthermore, we show that novel and interesting features of tRNAs are detected when sequence correlations with the charged amino acid (and anticodon) are evaluated. This technique is a powerful method for predicting the structure of RNAs and for analyzing specific functional characteristics.
EFFECTS OF FOREST FERTILIZATION ON STREAM WATER CHEMISTRY IN THE APPALACHIANS1

: Stream water chemistry was monitored on two watersheds on the Fernow Experimental Forest in north-central West Virginia to determine the effects of forest fertilization on annual nutrient exports. Ammonium nitrate and triple superphosphate were applied simultaneously at rates of 336 kg ha−1 N and 224 kg ha−1 P2O5, respectively, which are similar to rates used in commercial forest operations. The treatment significantly increased outputs of several ions. Annual outputs of nitrate N increased as much as 18 times over pretreatment levels, and calcium and magnesium increased as much as three times over pretreatment levels the first year after fertilization. Outputs for these nutrients were elevated for all three post-treatment years. Although nitrate N increased significantly, only about 20 percent of the applied fertilizer was accounted for in stream water exports. Outputs of phosphate P declined following fertilization, probably because the watersheds are phosphorus deficient, but by the third year, they slightly exceeded predicted values. Estimated nutrient losses to deep seepage were substantial, especially on the leakier south-facing catchmeat, on which some nutrient losses were equal to or greater than those in stream water. When the nutrient exports associated with both stream discharge and ground water recharge were combined, the percentages of applied N that were lost were similar on the two watersheds, averaging 27.5 percent. Less than 1 percent of the applied P was lost from either watershed in the combination of streamflow and deep seepage.
Social Network Clustering and Visualization using Hierarchical Edge Bundles

The hierarchical edge bundle (HEB) method generates useful visualizations of dense graphs, such as social networks, but requires a predefined clustering hierarchy, and does not easily benefit from existing straight‐line visualization improvements. This paper proposes a new clustering approach that extracts the community structure of a network and organizes it into a hierarchy that is flatter than existing community‐based clustering approaches and maps better to HEB visualization. Our method not only discovers communities and generates clusters with better modularization qualities, but also creates a balanced hierarchy that allows HEB visualization of unstructured social networks without predefined hierarchies. Results on several data sets demonstrate that this approach clarifies real‐world communication, collaboration and competition network structure and reveals information missed in previous visualizations. We further implemented our techniques into a social network visualization application on facebook.com and let users explore the visualization and community clustering of their own social networks.
Bessel inequality for robust stability analysis of time-delay system

This paper addresses the problem of the stability analysis for a linear time-delay systems via a robust analysis approach and especially the quadratic separation framework. To this end, we use the Bessel inequality for building operators that depend on the delay. They not only allow us to model the system as an uncertain feedback system but also to control the accuracy of the approximations made. Then, a set of LMIs conditions are proposed which tends on examples to the analytical bounds for both delay dependent stability and delay range stability.
A new sliding-mode current controller for field oriented controlled induction motor drives

Accurate and fast current control is essential in high performance field oriented controlled induction motor drives. In this paper, a new sliding-mode current controller is presented for induction motor drives. This scheme uses two sliding-mode controllers to regulate the d-axis and q-axis stator currents respectively, and adopts space vector modulation (SVM) technique as the voltage modulation strategy. This new current controller exhibits several advantages such as fast dynamic response, perfect decoupling and robustness to parameter variations. Simulation results are provided to verify the performance of the proposed current control scheme
Evapotranspiration monitoring in a vineyard using satellite-based thermal remote sensing

A two-source energy balance model that separates surface fluxes of the soil and canopy was applied to a drip-irrigated vineyard in central Spain, using a series of nine Landsat-5 images acquired during the summer of 2007. The model partitions the available energy, using surface radiometric temperatures to constrain the sensible heat flux, and computing ET as a residual of the energy balance. Flux estimations from the model are compared with half-hourly and daily values obtained by an eddy covariance flux tower installed on the site during the experiment. The performance of the twosource model to estimate ET under the low vegetation cover and semiarid conditions of the experiment, with RMSD between observed and model data equal to 49 W m-2 for half-hourly estimations and RMSD=0.5 mm day-1 at daily scale, is regarded as acceptable for irrigation management purposes. Model results in the separation of the beneficial (transpiration) and non-beneficial (evaporation from the soil) fractions, which is key information for the quest to improve water productivity, are also reported. However, the lack of measures of these components makes it difficult to draw conclusions about the final use of the water.
An artificial nerve fiber for evaluation of nerve cuff electrodes

The different applications of natural sensors for feedback in rehabilitation systems using functional electrical stimulation (FES) require specialised and optimised designs of nerve cuff electrodes for recording of the sensory information. This paper describes a simple artificial nerve fiber for evaluation of nerve cuff electrode designs, cuff recording configurations and noise reduction methods in a controlled environment. The idea is to experimentally identify the transfer function from a nerve fiber to the cuff electrode and make a computed construction of a single fiber action potential. This is done using an action current template as input to the identified transfer functions. The artificial nerve was tested on three cuffs of different lengths and the results showed good agreement with the results from a nerve conduction model of a single fiber action potential in an inhomogeneous volume conductor.