Miracle-dz/UniFAR-FTUs huggingface dataset:
Iowa Gambling Task: There is More to Consider than Long-Term Outcome. Using a Linear Equation Model to Disentangle the Impact of Outcome and Frequency of Gains and Losses

The Iowa Gambling Task (IGT) has been widely used to assess differences in decision-making under uncertainty. Recently, several studies have shown that healthy subjects do not meet the basic predictions of the task (i.e., prefer options with positive long-term outcome), hence questioning its basic assumptions. Since choice options are characterized by gain and net loss frequency in addition to long-term outcome, we hypothesized that a combination of features rather than a single feature would influence participants’ choices. Offering an alternative way of modeling IGT data, we propose to use a system of linear equations to estimate weights that quantify the influence of each individual feature on decision-making in the IGT. With our proposed model it is possible to disentangle and quantify the impact of each of these features. Results from 119 healthy young subjects suggest that choice behavior is predominantly influenced by gain and loss frequency. Subjects preferred choices associated with high-frequency gains to those with low-frequency gains, regardless of long-term outcome. However, among options with low-frequency gains, subjects learned to distinguish between choices that led to advantageous and disadvantageous long-term consequences. This is reflected in the relationship between the weights for gain frequency (highest), loss frequency (intermediate), and long-term outcome (lowest). Further, cluster analysis of estimated feature weights revealed sub-groups of participants with distinct weight patterns and associated advantageous decision behavior. However, subjects in general do not learn to solely base their preference for particular decks on expected long-term outcome. Consequently, long-term outcome alone is not able to drive choice behavior on the IGT. In sum, our model facilitates a more focused conclusion about the factors guiding decision-making in the IGT. In addition, differences between clinical groups can be assessed for each factor individually.
Indoor MIMO Visible Light Communications: Novel Angle Diversity Receivers for Mobile Users

This paper proposes two novel and practical designs of angle diversity receivers to achieve multiple-input-multiple-output (MIMO) capacity for indoor visible light communications (VLC). Both designs are easy to construct and suitable for small mobile devices. By using light emitting diodes for both illumination and data transmission, our receiver designs consist of multiple photodetectors (PDs), which are oriented with different inclination angles to achieve high-rank MIMO channels and can be closely packed without the requirement of spatial separation. Due to the orientations of the PDs, the proposed receiver designs are named pyramid receiver (PR) and hemispheric receiver (HR). In a PR, the normal vectors of PDs are chosen the same as the normal vectors of the triangle faces of a pyramid with equilateral N-gon base. On the other hand, the idea behind HR is to evenly distribute the PDs on a hemisphere. Through analytical investigation, simulations and experiments, the channel capacity and bit-error-rate (BER) performance under various settings are presented to show that our receiver designs are practical and promising for enabling VLC-MIMO. In comparison to induced link-blocked receiver, our designs do not require any hardware adjustment at the receiver from location to location so that they can support user mobility. Besides, their channel capacities and BER performance are quite close to that of link-blocked receiver. Meanwhile, they substantially outperform spatially-separated receiver. This study reveals that using angle diversity to build VLC-MIMO system is very promising.
Sleep patterns and disorders among university students in Lebanon.

BACKGROUND Insufficient sleep is a significant public health issue with adverse medical consequences. Sleep disturbances are common among university students and have an effect on this group's overall health and functioning. The aim of this study was to investigate sleep habits and disorders in a population of university students across Lebanon. METHODS This was a cross-sectional study carried out in 2012 among 735 students aged 18-25 yrs. old, enrolled at six universities across Lebanon. The Pittsburg Sleep Quality Index (PSQI) was used to assess sleep quality and habits. RESULTS Less than half of the total study population (47.3%) were good sleepers (PSQI<5). Upon bivariate analysis, males experienced more sleep difficulties than females (57.8% vs. 40.8%). The majority (60%) of males vs. 40% of females had trouble performing daily activities more than once per week (P=0.02). Results of the multivariate analysis revealed that reporting poor sleep quality was strongly associated with daytime dysfunction and sleep- enhancing medication use especially more than once per week. CONCLUSIONS This is the first study to describe the nature of sleep problems among university students in Lebanon. This study suggests that sleep problems among Lebanese college students were common and such problems may interfere with daily performance. Findings from this study have important implications for programs intended to improve academic performance by targeting sleep habits of students.
Experimental Manipulation of Death Anxiety.

Relative effects of hypnosis, alpha biofeedback, prestige sug­ gestion, and silence in attenuating experimentally induced increases in death anxiety were investigated. Forty female undergraduate Ss at Louisiana State University were tested on four measures of death anxiety: "emotional" associations to "death" words, association response latencies to "death" versus "neutral" words, Death Anxiety Scale, and Death Concern Scale. Ss were then assigned to four treatments: 1) hypnosis, with anxiolytic post-hypnotic relaxation suggestions; 2) non-hypnotic anxiolytic prestige suggestions; 3) EEG alpha-contingent biofeedback; and 4) a 15 minute waiting period. Hypnotic Ss scoring 7 or lower on the modified Stanford Scale of Hypnotic Susceptibility were replaced, as were biofeedback Ss who failed to increase percent-time alpha and/or alpha amplitude. Following treatments, Ss viewed a tape-slide presentation empha­ sizing personal death and overestimating its probability from various causes. Ss were then retested on death anxiety measures, forms of which were counterbalanced within groups, hypothesizing that hypnosis and biofeedback Ss would increase death anxiety less than silence or sugges­ tion control Ss. Analysis of variance (at .05 and .01 confidence levels) did not significantly differentiate groups on either increases or decreases of death anxiety.
A Declarative Optimization Engine for Resource Provisioning of Scientific Workflows in IaaS Clouds

Resource provisioning for scientific workflows in Infrastructure-as-a-service (IaaS) clouds is an important and complicated problem for budget and performance optimizations of workflows. Scientists are facing the complexities resulting from severe cloud performance dynamics and various user requirements on performance and cost. To address those complexity issues, we propose a declarative optimization engine named Deco for resource provisioning of scientific workflows in IaaS clouds. Deco allows users to specify their workflow optimization goals and constraints of specific problems with an extended declarative language. We propose a novel probabilistic optimization approach for evaluating the declarative optimization goals and constraints in dynamic clouds. To accelerate the solution finding, Deco leverages the available power of GPUs to find the solution in a fast and timely manner. We evaluate Deco with several common provisioning problems. We integrate Deco into a popular workflow management system (Pegasus) and show that Deco can achieve more effective performance/cost optimizations than the state-of-the-art approaches.
Condition‐independent sensitization of locomotor stimulation and mesocortical dopamine release following chronic nicotine treatment in the rat

Chronic nicotine (NIC) pretreatment has been shown to enhance NIC‐induced locomotor stimulation, an effect that seems critically dependent on activation of brain dopamine (DA) systems. In the present study the effects of chronic, intermittent NIC treatment were examined in the rat to establish whether such behavioral sensitization is associated with specific, regional changes in brain dopaminergic activity. Male rats received daily injections in their home cage with either saline (SAL) or NIC (0.5 mg/kg, s.c.) for 12 days. Twenty‐four hours later, the locomotor activity of the animals subjected to NIC challenge as well as the functional responsiveness of the mesolimbocortical dopaminergic system were assessed. To this end, microdialysis experiments were performed in awake animals, measuring extracellular concentrations of DA and its metabolites in the prefrontal cortex (PFC) and the nucleus accumbens (NAC). Extracellular single cell recordings from DA neurons in the ventral tegmental area (VTA) were also performed in anesthetized animals. NIC (0.5 mg/kg, s.c.) increased all measured parameters of locomotor activity, with the exception of rearing, in SAL‐pretreated animals; these effects were substantially enhanced after pretreatment with NIC. Nicotine (0.5 mg/kg, s.c.) increased DA release in both the PFC and the NAC in SAL‐treated animals. Nicotine pretreatment significantly enhanced this effect in the PFC, whereas it did not affect the response in the NAC. Low doses of intravenously administered NIC dose‐dependently increased burst activity, starting at 12 μg/kg in the SAL pretreated animals and at 6 μg/kg in the NIC‐pretreated animals, and also dose‐dependently increased firing rate in SAL as well as NIC‐pretreated animals, although starting at a higher dose level, i.e., 25 μg/kg. These results demonstrate that behavioral sensitization after chronic NIC treatment is accompanied by an enhanced dopamine release specifically within the PFC. This phenomenon may be highly significant for the dependence‐producing effects of NIC, particularly in association with major psychiatric disorder, such as schizophrenia. © 1996 Wiley‐Liss, Inc.
Asymptotics of eigenbased collaborative sensing

In this contribution, we propose a new technique for collaborative sensing based on the analysis of the normalized (by the trace) largest eigenvalues of the sample covariance matrix. Assuming that several base stations are cooperating and without the knowledge of the noise variance, the test is able to determine the presence of mobile users in a network when only few samples are available. Unlike previous heuristic techniques, we show that the test has roots within the generalized likelihood ratio test and provide an asymptotic random matrix analysis enabling to determine adequate threshold detection values (probability of false alarm). Simulations sustain our theoretical claims.
From Molecule to Metaphor - A Neural Theory of Language

Over the last decade or so, it has become increasingly clear to many cognitive scientists that research into human language (and cognition in general, for that matter) has largely neglected how language and thought are embedded in the body and the world. As argued by, for instance, Clark (1997), cognition is fundamentally embodied, that is, it can only be studied in relation to human action, perception, thought, and experience. As Feldman puts it: “Human language and thought are crucially shaped by the properties of our bodies and the structure of our physical and social environment. Language and thought are not best studied as formal mathematics and logic, but as adaptations that enable creatures like us to thrive in a wide range of situations” (p. 7). Although it may seem paradoxical to try formalizing this view in a computational theory of language comprehension, this is exactly what From Molecule to Metaphor does. Starting from the assumption that human thought is neural computation, Feldman develops a computational theory that takes the embodied nature of language into account: the neural theory of language. The book comprises 27 short chapters, distributed over nine parts. Part I presents the basic ideas behind embodied language and cognition and explains how the embodiment of language is apparent in the brain: The neural circuits involved in a particular experience or action are, for a large part, the same circuits involved in processing language about this experience or action. Part II discusses neural computation, starting from the molecules that take part in information processing by neurons. This detailed exposition is followed by a description of neuronal networks in the human body, in particular in the brain. The description of the neural theory of language begins in Part III, where it is explained how localist neural networks, often used as psycholinguistic models, can represent the meaning of concepts. This is done by introducing triangle nodes into the network. Each triangle node connects the nodes representing a concept, a role, and a filler—for example, “pea,” “has-color,” and “green. ” Such networks are trained by a process called recruitment learning, which is described only very informally. This is certainly an interesting idea for combining propositional and connectionist models, but it does leave the reader with a number of questions. For instance, how is the concept distinguished from the filler when they can be interchanged, as in “cats, feed-on, mice” versus “mice, feed-on, cats. ” And on a more philosophical note: Where does this leave embodiment? The idea that there exists a node representing the concept “pea,” neurally distinct from its properties and from experiences with peas, seems to introduce abstract and arbitrary symbols. These are quite alien to embodied theories of cognition, which generally assume modal and analogical perceptual symbols (Barsalou 1999) or even no symbols at all (Brooks 1991).
Sensitization of Dictyostelium chemotaxis by phosphoinositide-3-kinase-mediated self-organizing signalling patches

The leading edge of Dictyostelium cells in chemoattractant gradients can be visualized using green fluorescent protein (GFP) tagged to the pleckstrin-homology (PH) domain of cytosolic regulator of adenylyl cyclase (CRAC), which presumable binds phosphatidylinositol-(3,4,5)triphosphate [PtdIns(3,4,5)P3]. Uniform cyclic AMP (cAMP) concentrations induce persistent translocation of PHCrac-GFP from the cytosol to multiple patches, which are similar to the single patch of PHCrac-GFP at the leading edge in a cAMP gradient. We show that cAMP determines the probability of patch formation (half-maximal effect at 0.5 nM cAMP) but not the size, lifetime or intensity of patches, indicating that patches are self-organizing structures. A pseudopod is extended from the area of the cell with a PHCrac-GFP patch at about 10 seconds after patch formation. Cells treated with the F-actin inhibitor latrunculin A are round without pseudopodia; uniform cAMP still induces localized patches of PHCrac-GFP. Inhibition of phosphoinositide-3-kinase (PI3K) activity with LY294002 inhibits PHCrac-GFP patches and inhibits chemotaxis towards nanomolar cAMP but has no effect at higher cAMP concentrations. Thus, very low cAMP concentrations induce self-organizing PHCrac-GFP patches that serve as a spatial cue for pseudopod formation, which enhances the sensitivity and amplitude of chemotactic movement.
Fluoride Sorption Efficiency of Vermiculite Functionalised with Cationic Surfactant: Isotherm and Kinetics

Groundwater is a major source of water, especially in rural communities. The presence of excess fluoride in groundwater has been a health concern for many decades because it causes fluorosis. The persistence of this problem led to the development of several approaches for reducing fluoride in groundwater to ≤1.5 mg/L, which is the World Health Organization’s (WHO) permissible limit. Despite recorded success in fluoride reduction, drawbacks such as cost and efficiency have remained apparent, thus necessitating further research on defluoridation. This paper aims at assessing the defluoridation capacity of a clay mineral, vermiculite, when modified with the cationic surfactant hexadecyltrimethylammonium bromide. The effects of experimental parameters such as pH, agitation time, mass of adsorbent, and temperature were examined to determine the most favourable adsorption conditions. Using batch technique, the results showed a fluoride sorption of 51% from an 8 mg/L fluoride solution. The adsorption conformed more to Freundlich than Langmuir isotherm with an adsorption capacity of 2.36 mg/g, while the kinetics conformed to a pseudo-second-order reaction. pH emerged as the most influential factor in optimisation. The findings of this study indicated that modified vermiculite could be efficient in reducing fluoride in groundwater to more tolerable limits, but requires adequate pH control.
The relationship between the carcass characteristics and meat composition of young Simmental beef cattle

The objective was to study the relationships between the carcass characteristics and meat composition of young Simmental beef, classified with regard to conformation and degree of fatness scores, and total lipid content, depending on gender. For this purpose, 90 animals (60 male and 30 female Simmental beef cattle) were analysed. The results of the study showed that gender affected carcass measurement scores and chemical composition of meat through its important effect on overall animal fatness. Referring to correlations, male carcass conformation score was negatively related to slaughter weight, total lipid content and fatness score. On the other hand, slaughter weight, hot and cold carcass weight, dressing percentage and carcass conformation was positively related to fatness score, all of them being significant. However, female carcass conformation score was positively related to slaughter weight, total lipid content and fatness score. Hot and cold carcass weights of female Simmental beef cattle were positively correlated to slaughter weight, total lipid content and carcass conformation score. Carcass conformation score and fatness score were affected by gender of young Simmental beef cattle.
A Cultural Immune Quantum Evolutionary Algorithm and Its Application

This paper proposes to integrate immune quantum evolutionary algorithm into cultural algorithms frame to develop a more efficient cultural immune quantum evolutionary algorithm (CIQEA). The computing model consists of a population space based on quantum-inspired evolutionary algorithm and a belief space based on immune vaccination, the population space and belief space have their own population evolved independently and parallel. The population space contributes vaccines to the belief population periodically, and the belief space continually evolve these vaccines which are used to provide better evolutionary direction to the population space, to constitute the dual-evolution and dual-improvement mechanism that can improve the global optimization abilities and convergence speed greatly. The convergence of CIQEA is proved based on markov random process and its superiority is shown by the experimental results on the knapsack problem.
The Neuropeptide Y Y1 Receptor: A Diagnostic Marker? Expression in MCF-7 Breast Cancer Cells Is Down-Regulated by Antiestrogens In Vitro and in Xenografts

The neuropeptide Y (NPY) Y1 receptor (Y1R) has been suggested as a tumor marker for in vivo imaging and as a therapeutic target. In view of the assumed link between estrogen receptor (ER) and Y1R in mammary carcinoma and with respect to the development of new diagnostic tools, we investigated the Y1R protein expression in human MCF-7 cell variants differing in ER content and sensitivity against antiestrogens. ER and Y1R expression were quantified by radioligand binding using [3H]-17β-estradiol and the Y1R selective antagonist [3H]-UR-MK114, respectively. The latter was used for cellular binding studies and for autoradiography of MCF-7 xenografts. The fluorescent ligands Cy5-pNPY (universal Y1R, Y2R and Y5R agonist) and UR-MK22 (selective Y1R antagonist), as well as the selective antagonists BIBP3226 (Y1R), BIIE0246 (Y2R) and CGP71683 (Y5R) were used to identify the NPY receptor subtype(s) by confocal microscopy. Y1R functionality was determined by mobilization of intracellular Ca2+. Sensitivity of MCF-7 cells against antiestrogen 4-hydroxytamoxifen correlated directly with the ER content. The exclusive expression of Y1Rs was confirmed by confocal microscopy. The Y1R protein was up-regulated (100%) by 17β-estradiol (EC50 20 pM) and the predominant role of ERα was demonstrated by using the ERα-selective agonist “propylpyrazole triol”. 17β-Estradiol-induced over-expression of functional Y1R protein was reverted by the antiestrogen fulvestrant (IC50 5 nM) in vitro. Furthermore, tamoxifen treatment of nude mice resulted in an almost total loss of Y1Rs in MCF-7 xenografts. In conclusion, the value of the Y1R as a target for therapy and imaging in breast cancer patients may be compromised due to Y1R down-regulation induced by hormonal (antiestrogen) treatment.
Photo Retrieval Based on Spatial Layout with Hardware Acceleration for Mobile Devices

A new photo retrieval system for mobile devices is proposed. The system can be used to search for photos with similar spatial layouts efficiently, and it adopts an image segmentation algorithm that extracts features of image regions based on K-Means clustering. Since K-Means is computationally intensive for real-time applications and prone to generate clustering results with local optima, parallel hardware architectures are designed to meet the real-time requirement of the retrieval process. Experiments show that the proposed algorithm in the photo retrieval system obtains better mean average precision than other methods, and it is tested with image recognition problems. The robustness of the algorithm is also evaluated with noise and image blurring. Besides, the proposed K-Means hardware can provide a trade-off between the execution time and the retrieval performance on the software and hardware cosimulation platform. The contribution of this work is twofold. The first is the development of a photo retrieval framework for mobile devices, where a new texture feature is employed in the algorithm to enhance the retrieval performance. The other is the integration of the K-Means hardware accelerator and the photo retrieval system. The hardware architecture is analyzed, and the specifications are compared with previous works.
H ∞ consensus control of multi-agent systems with input delay and directed topology

In this study, the consensus problem for linear multi-agent systems with general directed graph in the presence of constant input delay and external disturbances is addressed. To deal with input delay, a truncated prediction of the agent state over the delay period is approximated by the finite-dimensional term of the classical state predictor. The truncated predictor feedback method is used for the consensus protocol design. By exploring certain features of the Laplacian matrix, the H ∞ consensus analysis is put in the framework of Lyapunov analysis. The integral terms that remain in the transformed systems are carefully analysed using Krasovskii functional. Sufficient conditions are derived for the multi-agent systems to guarantee the H ∞ consensus in the time domain. The feedback gain is then designed by solving these conditions with an iterative linear matrix inequality procedure. A simulation study is carried out to validate the proposed control design.