Miracle-dz/UniFAR-FTUs huggingface dataset:
BEHAVIOURAL ROAD SAFETY MANAGEMENT

Task performance and fatigue during driving may be influenced by psychological factors since individuals differ in temperament and anxiety status. Fatigue has also been shown to be associated with changes in brain wave activity. However, research on psychophysiological associations with driver fatigue is scarce. Understanding the psychological links could provide information for educating the professional driver on fatigue management. We have in our previous research identified the psychological associations during driver fatigue for the development of fatigue management programs. Psychological profiles influence the fatigue state of a person (1,2&3). It has been found that increased anxiety, and negative mood states such as Tension-Anxiety and Fatigue-Inertia are associated with other direct indicators of fatigue such as physiological activity (2). In can be concluded from our investigations in this area that driver fatigue is influenced by psychological factors and reducing anxiety as well as increasing positive mood states may help control fatigue effects. Important psychophysiological information for educating drivers on fatigue management is now available (3,4). There are implications the for application of neurofeedback techniques to reduce and manage driver fatigue. Such driver fatigue educational programs will lead to safer road practices. INTRODUCTION Driver related sleepiness and fatigue are believed to be significant causes of traffic accidents. While numerous physiological indicators are available to measure levels of driver fatigue, the electroencephalography (EEG) signal may be one of the most predictive and reliable (1,2). However, EEG is still relatively new in the area of investigating the psychology of fatigue. Few studies have investigated the psychological associations of mood states, anxiety levels and locus of control with driver fatigue. In our recent study we found associations between psychological factors such as mood, anxiety and driver fatigue (3). Driver fatigue has been specifically defined as a state of reduced mental alertness that impairs performance of a range of cognitive and psychomotor tasks including driving (4) It generally impairs human efficiency when individuals continue working after the onset of their fatigue state. However, task performance during driving may be influenced by psychological factors because individuals differ in attention and anxiety status. An early study of sustained performance in a flight simulator by Bartlett (5) showed that as performance time on a task increased, changes in attention with an increase in errors occurred. It has been suggested that fatigue could be experienced differently by drivers with different psychological profiles and temperament (6). Other studies have indicated associations …
A Smoothed Conjugate Residual Squared Algorithm for Solving Nonsymmetric Linear Systems

Recently the conjugate residual squared (CRS) me-thod has been proposed as an attractive variant of the bi-conjugate residual method. However, in many situations, the CRS algorithm exhibits an irregular convergence behavior. To overcome the disadvantage, we apply a smoothing technique to the CRS algorithm and derived the smoothed CRS algorithm. Numerical experiments indicate that the new method give smoother convergence behavior than CRS and compete with well-known BiCGSTAB method.
EBG antenna technology for different applications

EBG technology has been shown in last years as an alternative for designer which can benefit from the different properties presented by these periodic structures. However, the number of designs which comply with specifications of tangible applications were limited. Therefore the work presented in this paper is focused in showing the advantages that can be achieved by the used of EBG technology, covering specific applications, taking advantage of diverse properties of EBG materials, i.e.: the presence of a forbidden frequency band (bandgap); the design of resonant cavities which can be used to elongate the radiation aperture of antennas, increasing consequently the directivity; or at last, the use of the property presented by EBG - AMC (Artificial Magnetic Conductor) structures to reflect incident waves with a 0° phase value at the working frequency, behaving as a perfect magnetic conductor.
Over-Education in the Labor Market

This article examines the reasons for the observed discrepancy between workers' actual and required levels of schooling and the resulting differences in returns to schooling. "Overeducated" workers are found to be younger and to have lower amounts of on-the-job training than workers with the required level of schooling. They also have higher rates of firm and occupational mobility, characterized by movement of higher-level occupations. The findings suggest that overeducation can be explained by the trade-off between schooling and other components of human capital and by the mobility patterns of overeducated workers. Copyright 1991 by University of Chicago Press. (This abstract was borrowed from another version of this item.)
Data driven consistency (working title)

We are motivated by applications that need rich model classes to represent them. Examples of rich model classes include distributions over large, countably infinite supports, slow mixing Markov processes, etc. But such rich classes may be too complex to admit estimators that converge to the truth with convergence rates that can be uniformly bounded over the entire model class as the sample size increases (uniform consistency). However, these rich classes may still allow for estimators with pointwise guarantees whose performance can be bounded in a model dependent way. The pointwise angle of course has the drawback that the estimator performance is a function of the very unknown model that is being estimated, and is therefore unknown. Therefore, even if the estimator is consistent, how well it is doing may not be clear no matter what the sample size is. Departing from the dichotomy of uniform and pointwise consistency, a new analysis framework is explored by characterizing rich model classes that may only admit pointwise guarantees, yet all the information about the model needed to guage estimator accuracy can be inferred from the sample at hand. To retain focus, we analyze the universal compression problem in this data driven pointwise consistency framework.
Functional and Probiotic Attributes of an Indigenous Isolate of Lactobacillus plantarum

Background Probiotic microorganisms favorably alter the intestinal microflora balance, promote intestinal integrity and mobility, inhibit the growth of harmful bacteria and increase resistance to infection. Probiotics are increasingly used in nutraceuticals, functional foods or in microbial interference treatment. However, the effectiveness of probiotic organism is considered to be population-specific due to variation in gut microflora, food habits and specific host-microbial interactions. Most of the probiotic strains available in the market are of western or European origin, and a strong need for exploring new indigenous probiotic organisms is felt. Methods and Findings An indigenous isolate Lp9 identified as Lactobacillus plantarum by molecular-typing methods was studied extensively for its functional and probiotic attributes, viz., acid and bile salt tolerance, cell surface hydrophobicity, autoaggregation and Caco-2 cell-binding as well as antibacterial and antioxidative activities. Lp9 isolate could survive 2 h incubation at pH 1.5–2.0 and toxicity of 1.5–2.0% oxgall bile. Lp9 could deconjugate major bile salts like glycocholate and deoxytaurocholate, indicating its potential to cause hypocholesterolemia. The isolate exhibited cell-surface hydrophobicity of ∼37% and autoaggregation of ∼31%. Presence of putative probiotic marker genes like mucus-binding protein (mub), fibronectin-binding protein (fbp) and bile salt hydrolase (bsh) were confirmed by PCR. Presence of these genes suggested the possibility of specific interaction and colonization potential of Lp9 isolate in the gut, which was also suggested by a good adhesion ratio of 7.4±1.3% with Caco-2 cell line. The isolate demonstrated higher free radical scavenging activity than standard probiotics L. johnsonii LA1 and L. acidophilus LA7. Lp9 also exhibited antibacterial activity against E. coli, L. monocytogenes, S. typhi, S. aureus and B. cereus. Conclusion The indigenous Lactobacillus plantarum Lp9 exhibited high resistance against low pH and bile and possessed antibacterial, antioxidative and cholesterol lowering properties with a potential for exploitation in the development of indigenous functional food or nutraceuticals.
Serendipitous VLBI detection of rapid, large-amplitude, intraday variability in QSO 1156+295

Aims. We report a serendipitous detection of rapid, large amplitude flux density variations in the highly core-dominated, flat-spectrum radio quasar 1156+295 during an observing session at the Very Long Baseline Array (VLBA). Methods. The source was observed as a part of the MOJAVE survey programme with the VLBA at 15 GHz on February 5, 2007. Large amplitude variability in the correlated flux density, unexplainable in terms of the source structure, was first discovered while processing the data, and later confirmed by calibrating the antenna gains using 24 other sources observed in the experiment. Results. The source shows variations in the correlated flux density as high as 40% on a timescale of only 2.7 h. This places 1156+295 between the classical IDV sources and the so-called intra-hour variables. The observed variability timescale and the modulation index of 13% are consistent with interstellar scintillation by a nearby, highly turbulent scattering screen. The large modulation index at 15 GHz implies a scattering measure that is atypically high for a high galactic latitude source such as 1156+295.
Target perceivability for multi-frame multi-target tracking

This paper presents a novel weight assignment model for a rank constrained continuous formulation of multiframe multi-target data association problem. The new weight assignment model explicitly estimates the joint probability of the target perceivability, the target state and measurement, within a Bayesian framework with continuous update when new measurements are available. The knowledge on target perceivability state at every time step also provides a new pruning criterion for reducing the space of all possible track associations. Experiments on synthetic data under different operating conditions demonstrate the effectiveness of the proposed weight assignment model for multi-target tracking problem. It also presents good qualitative tracking performance on real-world video data.
Co-design of an active suspension using simultaneous dynamic optimization

Design of physical systems and associated control systems are coupled tasks; design methods that manage this interaction explicitly can produce system-optimal designs, whereas conventional sequential processes may not. Here we explore a new technique for combined physical system and control design (co-design) based on a simultaneous dynamic optimization approach known as direct transcription, which transforms infinite-dimensional control design problems into finite dimensional nonlinear programming problems. While direct transcription problem dimension is often large, sparse problem structures and fine-grained parallelism (among other advantageous properties) can be exploited to yield computationally efficient implementations. Extension of direct transcription to co-design gives rise to a new problem structures and new challenges. Here we illustrate direct transcription for co-design using a new automotive active suspension design example developed specifically for testing co-design methods. This example builds on prior active suspension problems by incorporating a more realistic physical design component that includes independent design variables and a broad set of physical design constraints, while maintaining linearity of the associated differential equations. © 2011 ASME
Impact of reduction in early- and late-systolic functional mitral regurgitation on reverse remodelling after cardiac resynchronization therapy.

AIMS To examine whether the presence of pre-pacing functional mitral regurgitation (MR) and its improvement would affect the extent of left ventricular (LV) reverse remodelling after cardiac resynchronization therapy (CRT). METHODS AND RESULTS Echocardiographic assessment was performed in 83 patients before and 3 months after CRT. Total MR volume and the early- and late-systolic MR flow rate were assessed. At 3 months, there was reduction in total MR volume (38 ± 20 vs. 33 ± 21 mL) with decrease in both early- (71 ± 52 vs. 60 ± 51 mL/s) and late-systolic (49 ± 46 vs. 42 ± 46 mL/s) MR flow rate (all P < 0.05). Receiver-operating characteristic curve found that an 11% decrease in total MR volume was associated with LV reverse remodelling [defined by the reduction in LV end-systolic volume (LVESV) of ≥15%] [sensitivity, 90%; specificity, 80%; area under the curve (AUC), 0.85; P < 0.001]. The improvement in early- and late-systolic MR was also associated with LV reverse remodelling, in which improvement in early-systolic MR had higher sensitivity, specificity, and AUC than late-systolic MR. The extent of reverse remodelling with gain in LV ejection fraction and forward stroke volume was greatest in patients with improvement in total MR, intermediate in those with mild or no MR at baseline, and the least in those without improvement in total MR (LVESV, -29.8 ± 12.0 vs. -18.6 ± 16.6 vs. -5.5 ± 8.6%; ejection fraction, 11.8 ± 6.2 vs. 7.0 ± 6.8 vs. 3.0 ± 5.0%; forward stroke volume, 43.1 ± 37.9 vs. 21.1 ± 26.1 vs. 6.8 ± 34.6%; all P < 0.05). CONCLUSION Improvement of functional MR contributes to LV reverse remodelling after CRT, whereas reduction of early-systolic MR is more powerful than late-systolic MR.
A SCALABLE ARCHITECTURE FOR DISCOVERY AND COMPOSITION IN P 2 P SERVICE NETWORKS

The desirable global scalability of Grid systems has steered the research towards the employment of the peer-to-peer (P2P) paradigm for the development of new resource discovery systems. As Grid systems mature, the requirements for such a mechanism have grown from simply locating the desired service to compose more than one service to achieve a goal. In Semantic Grid, resource discovery systems should also be able to automatically construct any desired service if it is not already present in the system, by using other, already existing services. In this paper, we present a novel system for the automatic discovery and composition of services, based on the P2P paradigm, having in mind (but not limited to) a Grid environment for the application. The paper improves composition and discovery by exploiting a novel network partitioning scheme for the decoupling of services that belong to different domains and an ant-inspired algorithm that places co-used services in neighbouring peers.
Efficiency of Compact Organic Rankine Cycle System with Rotary-Vane-Type Expander for Low-Temperature Waste Heat Recovery

This paper describes the experimental efficiency of a compact organic Rankine cycle (ORC) system with a compact rotary-vane-type expander. The compact ORC system can be used for power generation from low-temperature heat sources such as waste heat from various small-scale heat engines, fuel cells, electric devices, and solar thermal energy. The purpose of this study is to develop an ORC system with a low power output of less than 1 kW with a hot temperature source ranging from 60°C to 100°C and a cold temperature source ranging from 10°C to 30°C. The power output of the system is rather less due to limited heat efficiency. Therefore, the system should have an economically optimal efficiency. In order to realize such a system, an efficient and low-cost expander is indispensable. An experimental ORC system was developed using the rotary-vane-type expander which is one of possible candidates of the expander. The experimental results revealed the expander performance for various rotation speeds, expander efficiencies, and thermal efficiencies. Approximately 30 W of expander power output with 48% expander efficiency and 4% thermal efficiency with a temperature difference between the hot and cold sources of 80°C was achieved.
Hierarchical label partitioning for large scale classification

Extreme classification task where the number of classes is very large has received important focus over the last decade. Usual efficient multi-class classification approaches have not been designed to deal with such large number of classes. A particular issue in the context of large scale problems concerns the computational classification complexity : best multi-class approaches have generally a linear complexity with respect to the number of classes which does not allow these approaches to scale up. Recent works have put their focus on using hierarchical classification process in order to speed-up the classification of new instances. Using a priori information on labels such as a label hierarchy allows to build an efficient hierarchical structure over the labels in order to decrease logarithmically the classification time. However such information on labels is not always available nor useful. Finding a suitable hierarchical organization of the labels is thus a crucial issue as the accuracy of the model depends highly on the label assignment through the label tree. We propose in this work a new algorithm to build iteratively a hierarchical label structure by proposing a partitioning algorithm which optimizes simultaneously the structure in terms of classification complexity and the label partitioning problem in order to achieve high classification performances. Beginning from a flat tree structure, our algorithm selects iteratively a node to expand by adding a new level of nodes between the considered node and its children. This operation increases the speed-up of the classification process. Once the node is selected, best partitioning of the classes has to be computed. We propose to consider a measure based on the maximization of the expected loss of the sub-levels in order to minimize the global error of the structure. This choice enforces hardly separable classes to be group together in same partitions at the first levels of the tree structure and it delays errors at a deep level of the structure where there is no incidence on the accuracy of other classes. Experiments on real big text data from recent challenge assess the performances of our model.
Mixing and its effects on biogeochemistry in the persistently stratified, deep, tropical Lake Matano, Indonesia

In the > 590‐m deep, tropical Lake Matano (Indonesia), stratification is characterized by weak thermal gradients (< 2°C per 500 m) and weak salinity gradients (< 0.14% per 500 m). These gradients persist over seasons, decades, and possibly centuries. Under these nearly steady‐state conditions, vertical eddy diffusion coefficients (Kz) cannot be estimated by conventional methods that rely on time derivatives of temperature distributions. We use and compare several alternative methods: one‐dimensional k‐ε modeling, three‐dimensional hydrodynamic modeling, correlation with the size of Thorpe instabilities, and correlation with the stability frequency. In the thermocline region, at 100‐m depth, the Kz is ~ 5 × 10−6 m2 s−1, but, below 300 m, the small density gradient results in large (20 m) vertical eddies and high mixing rates (Kz ~ 10−2 m2 s−1). The estimated timescale of water renewal in the monimolimnion is several hundred years. Intense evaporation depletes the surface mixed layer of 16O and 1H isotopes, making it isotopically heavier. The lake waters become progressively isotopically lighter with depth, and the isotopic composition in the deep waters is close to those of the ground and tributary waters. The vertical distribution of Kz is used in a biogeochemical reaction‐transport model. We show that, outside of a narrow thermocline region, the vertical distributions of dissolved oxygen, iron, methane, and phosphorus are shaped by vertical variations in transport rates, rather than by sources or sinks.
Capsular polysaccharides are an important immune evasion mechanism for Staphylococcus aureus

Staphylococcus aureus can cause severe life threatening invasive diseases. The principal immune effector mechanism by which humans are protected from Gram positive bacteria such as S. aureus is antigen specific antibody- and complement-dependent opsonophagocytosis. This process can be measured in vitro using the opsonophagocytic antibody assay (OPA), which is a complex assay composed of live S. aureus bacteria, a complement source, phagocytic effector cells such as differentiated HL-60 cells, and test serum. In this report, we investigated the impact on the OPA of S. aureus surface antigens capsular polysaccharides (CP) and protein A (SpA). We demonstrated that higher CP expression renders bacteria more resistant to non-specific opsonophagocytic killing than increased SpA expression, suggesting that the expression of capsular polysaccharides may be the more important immune evasion strategy for S. aureus. Bacteria that were not fully encapsulated were highly susceptible to non-specific killing in the assay in the absence of immune serum. This non-specific killing was prevented by growing the bacteria under conditions that increased capsular polysaccharide levels on the surface of the bacteria. In contrast, the level of SpA expression had no detectable effect on non-specific killing in OPA. Using anti-CP antibodies we demonstrated type-specific killing in OPA of both MRSA and MSSA clinical isolates. SpA expression on the cell surface did not interfere with OPA activity, providing evidence that despite the role of SpA in sequestering antibodies by their Fc region, killing is easily accomplished in the presence of high titered anti-capsular polysaccharide antibodies. This highlights the role of CP as an important immune evasion mechanism and supports the inclusion of capsular polysaccharide antigens in the formulation of multi-component prophylactic vaccines against S. aureus.
Surcharges plus Unhealthy Labels Reduce Demand for Unhealthy Menu Items

Three laboratory experiments and a field experiment in a restaurant demonstrate that neither a price surcharge nor an unhealthy label is enough on its own to curtail the demand for unhealthy food. However, when the two are combined as an unhealthy label surcharge, they reduce demand for unhealthy food. The authors also show that the unhealthy label is as effective for women as the unhealthy label surcharge, whereas it backfires for men, who order more unhealthy food when there is an unhealthy label alone. The authors demonstrate that an unhealthy surcharge, which highlights both the financial disincentive and potential health costs, can significantly drive healthier consumption choices. From a policy and government perspective, if the goal is to reduce demand for unhealthy food, increasing the transparency of the health rationale for any financial disincentive is necessary to effectively lower unhealthy food consumption.
An improved TF-IDF weights function based on information theory

Vector Space Model (VSM) is a typical method to describe the text feature in text classification at present. It adopts TF-IDF weights to compute the term weighting in each dimension of the text feature. However, it only considers the relationship between the term and the whole text but neglects the relationship between different terms. Aiming at this problem an improved TF-IDF weights function is proposed which uses the distribution information among classes and inside a class. The experience shows that the improved method is feasible and effective. In addition, it greatly improves the accuracy of text category.