Miracle-dz/UniFAR-FTUs huggingface dataset:
Response actions influence the categorization of directions in auditory space

Spatial region concepts such as “front,” “back,” “left,” and “right” reflect our typical interaction with space, and the corresponding surrounding regions have different statuses in memory. We examined the representation of spatial directions in the auditory space, specifically in how far natural response actions, such as orientation movements toward a sound source, would affect the categorization of egocentric auditory space. While standing in the middle of a circle with 16 loudspeakers, participants were presented acoustic stimuli coming from the loudspeakers in randomized order, and verbally described their directions by using the concept labels “front,” “back,” “left,” “right,” “front-right,” “front-left,” “back-right,” and “back-left. ” Response actions varied in three blocked conditions: (1) facing front, (2) turning the head and upper body to face the stimulus, and (3) turning the head and upper body plus pointing with the hand and outstretched arm toward the stimulus. In addition to a protocol of the verbal utterances, motion capture and video recording generated a detailed corpus for subsequent analysis of the participants’ behavior. Chi-square tests revealed an effect of response condition for directions within the left and right sides. We conclude that movement-based response actions influence the representation of auditory space, especially within the sides’ regions. Moreover, the representation of auditory space favors the front and the back regions in terms of resolution, which is possibly related to the physiological characteristics of the human auditory system, as well as to the ecological requirements of action control in the different regions.
Probabilistic Exploration in Planning while Learning

Sequential decision tasks with incomplete information are characterized by the exploration problem; namely the trade-off between further exploration for learning more about the environment and immediate exploitation of the accrued information for decision-making. Within artificial intelligence, there has been an increasing interest in studying planning-while-learning algorithms for these decision tasks. In this paper we focus on the exploration problem in reinforcement learning and Q-learning in particular. The existing exploration strategies for Q-learning are of a heuristic nature and they exhibit limited scaleability in tasks with large (or infinite) state and action spaces. Efficient experimentation is needed for resolving uncertainties when possible plans are compared (i.e. exploration). The experimentation should be sufficient for selecting with statistical significance a locally optimal plan (i.e. exploitation). For this purpose, we develop a probabilistic hill-climbing algorithm that uses a statistical selection procedure to decide how much exploration is needed for selecting a plan which is, with arbitrarily high probabiiity, arbitrarily close to a locally optimal one. Due to its generality the algorithm can be employed for the exploration strategy of robust Q-learning. An experiment on a relatively complex control task shows that the proposed exploration strategy performs better than a typical exploration strategy.
Molecular Mechanisms of Aging and Immune System Regulation in Drosophila

Aging is a complex process that involves the accumulation of deleterious changes resulting in overall decline in several vital functions, leading to the progressive deterioration in physiological condition of the organism and eventually causing disease and death. The immune system is the most important host-defense mechanism in humans and is also highly conserved in insects. Extensive research in vertebrates has concluded that aging of the immune function results in increased susceptibility to infectious disease and chronic inflammation. Over the years, interest has grown in studying the molecular interaction between aging and the immune response to pathogenic infections. The fruit fly Drosophila melanogaster is an excellent model system for dissecting the genetic and genomic basis of important biological processes, such as aging and the innate immune system, and deciphering parallel mechanisms in vertebrate animals. Here, we review the recent advances in the identification of key players modulating the relationship between molecular aging networks and immune signal transduction pathways in the fly. Understanding the details of the molecular events involved in aging and immune system regulation will potentially lead to the development of strategies for decreasing the impact of age-related diseases, thus improving human health and life span.
Word equations in linear space

Satisfiability of word equations is an important problem in the intersection of formal languages and algebra: Given two sequences consisting of letters and variables we are to decide whether there is a substitution for the variables that turns this equation into true equality of strings. The exact computational complexity of this problem remains unknown, with the best lower and upper bounds being, respectively, NP and PSPACE. Recently, the novel technique of recompression was applied to this problem, simplifying the known proofs and lowering the space complexity to (nondeterministic) O(n log n). In this paper we show that satisfiability of word equations is in nondeterministic linear space, thus the language of satisfiable word equations is context-sensitive, and by the famous Immerman-Szelepcsenyi theorem: the language of unsatisfiable word equations is also context-sensitive. We use the known recompression-based algorithm and additionally employ Huffman coding for letters. The proof, however, uses analysis of how the fragments of the equation depend on each other as well as a new strategy for nondeterministic choices of the algorithm, which uses several new ideas to limit the space occupied by the letters.
Mid-air modeling with Boolean operations in VR

Virtual Reality (VR) is again in the spotlight. However, interactions and modeling operations are still major hurdles to its complete success. To make VR Interaction viable, many have proposed mid-air techniques because of their naturalness and resemblance to physical world operations. Still, natural mid-air metaphors for Constructive Solid Geometry (CSG) are still elusive. This is unfortunate, because CSG is a powerful enabler for more complex modeling tasks, allowing to create complex objects from simple ones via Boolean operations. Moreover, Head-Mounted Displays occlude the real self, and make it difficult for users to be aware of their relationship to the virtual environment. In this paper we propose two new techniques to achieve Boolean operations between two objects in VR. One is based on direct-manipulation via gestures while the other uses menus. We conducted a preliminary evaluation of these techniques. Due to tracking limitations, results allowed no significant conclusions to be drawn. To account for self-representation, we compared full-body avatar against an iconic cursor depiction of users' hands. In this matter, the simplified hands-only representation improved efficiency in CSG modelling tasks.
Structured clustering with automatic kernel adaptation

Clustering is an invaluable data analysis tool in a variety of applications. However, existing algorithms often assume that the clusters do not have any structural relationship. Hence, they may not work well in situations where such structural relationships are present (e.g., it may be given that the document clusters are residing in a hierarchy). Recently, the development of the kernel-based structured clustering algorithm CLUHSIC [9] tries to alleviate this problem. But since the input kernel matrix is defined purely based on the feature vectors of the input data, it does not take the output clustering structure into account. Consequently, a direct alignment of the input and output kernel matrices may not assure good performance. In this paper, we reduce this mismatch by learning a better input kernel matrix using techniques from semi-supervised kernel learning. We combine manifold information and output structure information with pairwise clustering constraints that are automatically generated during the clustering process. Experiments on a number of data sets show that the proposed method outperforms existing structured clustering algorithms.
Sexual behaviour and risk of sexually transmitted infections in young female healthcare students in Spain

Background. Several authors have examined the risk for sexually transmitted infections (STI), but no study has yet analyzed it solely in relation with sexual behaviour in women. We analyzed the association of sexual behaviour with STI risk in female university students of healthcare sciences. Methods. We designed a cross-sectional study assessing over three months vaginal intercourse with a man. The study involved 175 female university students, without a stable partner, studying healthcare sciences in Spain. Main outcome variable: STI risk (not always using male condoms). Secondary variables: sexual behaviour, method of orgasm, desire to increase the frequency of sexual relations, desire to have more variety in sexual relations, frequency of sexual intercourse with the partner, and age. The information was collected with an original questionnaire. A logistic regression model was used to estimate the adjusted odds ratios (ORs) in order to analyze the association between the STI risk and the study variables. Results. Of the 175 women, 52 were positive for STI risk (29.7%, 95% CI [22.9–36.5%]). Factors significantly associated with STI risk (p < 0.05) included: orgasm (not having orgasms →OR = 7.01, 95% CI [1.49–33.00]; several methods →OR = 0.77, 95% CI [0.31–1.90]; one single method →OR = 1; p = 0.008) and desiring an increased frequency of sexual activities (OR = 0.27, 95% CI [0.13–0.59], p < 0.001). Conclusions. Women’s desire for sexual activities and their sexual function were significant predictors of their risk for STI. Information about sexual function is an intrinsic aspect of sexual behaviour and should be taken into consideration when seeking approaches to reduce risks for STI.
Inhibition of the High‐Affinity Brain Glutamate Transporter GLAST‐1 via Direct Phosphorylation

Abstract: Neurotransmission at excitatory glutamatergic synapses is terminated by the reuptake of the neurotransmitter by high‐affinity transporters, which keep the extracellular glutamate concentration below excitotoxic levels. The amino acid sequence of the recently isolated and cloned brain‐specific glutamate/aspartate transporter (GLAST‐1) of the rat reveals three consensus sequences of putative phosphorylation sites for protein kinase C (PKC). The PKC activator phorbol 12‐myristate 13‐acetate (PMA) decreased glutamate transport activity in Xenopus oocytes and human embryonic kidney cells (HEK293) expressing the cloned GLAST‐1 cDNA, within 20 min, to 25% of the initial transport activity. This down‐regulation was blocked by the PKC inhibitor staurosporine. GLAST‐1 transport activity remains unimpaired by phorbol 12‐monomyristate. Removal of all putative PKC sites of wild‐type GLAST‐1 by site‐directed mutagenesis did not abolish inhibition of glutamate transport. [32P]Phosphate‐labeled wild‐type and mutant transport proteins devoid of all predicted PKC sites were detected by immunoprecipitation after stimulation with PMA. Immunoprecipitation of [35S]methionine‐labeled transporter molecules indicates a similar stability of phosphorylated and nonphosphorylated GLAST‐1 protein. Immunofluorescence staining did not differentiate surface staining of HEK293 cells expressing GLAST‐1 with and without PMA treatment. These data suggest that the neurotransmitter transporter activity of GLAST‐1 is inhibited by phosphorylation at a non‐PKC consensus site.
Physician Financial Incentives and Cesarean Section Delivery

The "induced-demand" model states that in the face of negative income shocks, physicians may exploit their agency relationship with patients by providing excessive care. We test this model using an exogenous change in the financial environment facing obstetrician/gynecologists: declining fertility in the United States. We argue that the 13.5% fall in fertility over the 1970-1982 period led ob/gyns to substitute from normal childbirth toward a more highly reimbursed alternative, cesarean delivery. Using a nationally representative microdata set for this period, we show that there is a strong correlation between within-state declines in fertility and within-state increases in cesarean utilization.
A Difference of Convex Functions Approach to Large-Scale Log-Linear Model Estimation

We introduce a new class of parameter estimation methods for log-linear models. Our approach relies on the fact that minimizing a rational function of mixtures of exponentials is equivalent to minimizing a difference of convex functions. This allows us to construct convex auxiliary functions by applying the concave-convex procedure (CCCP). We consider a modification of CCCP where a proximal term is added (ProxCCCP), and extend it further by introducing an ℓ1 penalty. For solving the ` convex + ℓ1' auxiliary problem, we propose an approach called SeqGPSR that is based on sequential application of the GPSR procedure. We present convergence analysis of the algorithms, including sufficient conditions for convergence to a critical point of the objective function. We propose an adaptive procedure for varying the strength of the proximal regularization term in each ProxCCCP iteration, and show this procedure (AProxCCCP) is effective in practice and stable under some mild conditions. The CCCP procedure and proposed variants are applied to the task of optimizing the cross-entropy objective function for an audio frame classification problem. Class posteriors are modeled using log-linear models consisting of approximately 6 million parameters. Our results show that CCCP variants achieve a much better cross-entropy objective value as compared to direct optimization of the objective function by a first order gradient based approach, stochastic gradient descent or the L-BFGS procedure.
Ten-year diabetes incidence in 1046 HIV-infected patients started on a combination antiretroviral treatment

Objective:To evaluate the incidence and determinants of diabetes in a cohort of HIV-infected adults initiated with combination antiretroviral treatment (cART) in 1997–1999 and followed up to 2009. Design:Prospective study of 1046 patients at 47 French clinical sites. Methods:Potential determinants of diabetes occurrence, defined by confirmed increased glycemia and/or initiation of antidiabetic treatment, were assessed by a proportional hazards model, including time-updated metabolic parameters and ART exposure. Results:Among the cohort, representing 7846 person-years of follow-up (PYFU), 54% received indinavir, 75% stavudine and 52% didanosine. Overall, 111 patients developed diabetes, with an incidence of 14.1/1000 PYFU (14.6 in men, 12.6 in women). Incidence peaked in 1999–2000 (23.2/1000 PYFU) and decreased thereafter. The incidence of diabetes was associated [adjusted hazard ratio (aHR), all P < 0.02] with older age (hazard ratio = 2.13 when 40–49 years, hazard ratio = 3.63 when ≥50 years), overweight (hazard ratio = 1.91 for a BMI 25–29 kg/m2, hazard ratio = 2.85 >30 kg/m2), waist-to-hip ratio (hazard ratio = 3.87 for ≥0.97 male/0.92 female), time-updated lipoatrophy (hazard ratio = 2.14) and short-term exposure to indinavir (0–1year: hazard ratio = 2.53), stavudine (0–1year: hazard ratio = 2.56, 1–2years: hazard ratio = 2.65) or didanosine (2–3years: hazard ratio = 3.16). Occurrence of diabetes was not associated with HIV-related markers, hepatitis C, hypertension or family history of diabetes. Insulin resistance was predictive for incident diabetes. Conclusions:In this nationwide cohort, followed for 10 years after cART initiation, diabetes incidence peaked in 1990–2000, was markedly higher than that reported for European uninfected or other HIV-infected populations (4–6/1000 PYFU) and linked with age and adiposity. Adiposity and glycemic markers should be monitored in aging HIV-infected patients.
Reconstructing the initial global spread of a human influenza pandemic

Here, we present an analysis of the H1N1pdm genetic data sampled over the initial stages in the epidemic. To infer phylodynamic spread in time and space we employ a recently developed Bayesian statistical inference framework (Lemey et al., in press). We model spatial diffusion as a continuous-time Markov chain process along time-measured genealogies. In this analysis, we consider 40 locations for which sequence data were available on 06-Aug-2009. The sampling time interval of the 242 sequences spans from 30-Mar-2009 to 12-Jul-2009. The Bayesian inference typically results in a posterior distribution of phylogenetic trees, each having an estimate of the epidemic locations at the ancestral nodes in the tree. We summarize these trees using the most representative clustering pattern and annotate these clusters with the most probable location states. We can visualize this information as tree that grows over time, seeding locations each time an ancestral node is inferred to exist at a different location. A Bayes factor test provides statistical support for epidemiological linkage throughout the evolutionary history. We demonstrate how our full probabilistic approach efficiently tracks an epidemic based on viral genetic data as it unfolds across the globe.
Quota Restriction and Goldbricking in a Machine Shop

When the production behavior of industrial workers is examined by participant observation, it is seen that loafing on the job may not be the simple line of inactivity that some students of the subject have thought it. Close scrutiny of the particulars of "soldiering" in one piecework machine shop revealed that group adherence to a "bogey" was but one of several kinds of output restriction in the repertoire of machine operatives and that the work group was restricting production day in and day out.
End-to-end TCP performance in Ethernet/ATM networks

Enterprise networks using Ethernet switches at the edge of the network and ATM switches in the core of the network have become a common model in the industry. In such networking environment, TCP is used as the end-to-end flow control mechanism (transport layer) and ABR as the edge-to-edge flow control mechanism (link layer). It is well known that ABR pushes congestion to the edge of the network, thereby alleviating congestion in the ATM network but resulting in buffer overflows and packet losses at the interworking Ethernet/ATM unit, thus degrading end-to-end performance. We investigate the interworking behavior between the TCP flow control mechanism and ABR flow control mechanism, and show that appropriate buffer provisioning in the edge devices results in acceptable TCP performance. However, fairness between competing connections is not perfectly achieved. We also show that different TCP flavors exhibit distinctive performance behavior.
Ion transport in cortical collecting tubule; effect of amiloride.

STONER, L. C. , M. B. BURG, AND J. ORLOFF. Ion transport in cortical collecting tubule; effect of amiloride. Am. J. Physiol. 227(2) : 453-459. 1974. -T b 1 u u es were dissected from rabbit kidneys and perfused in vitro. In cortical collecting tubules the transepithelial electrical potential difference (PD) was 35 mV (lumen negative). There was net active sodium reabsorption from the lumen and net active potassium secretion into the lumen. There was net chloride reabsorption that was probably passive, but the analysis of the mechanism of chloride transport was complicated by the presence of chloride exchange diffusion. Amiloride (10-j M) in the lumen inhibited sodium and potassium transport and caused a reversal of the polarity of the PD; 10B4 M amiloride in the bath had no effect. The positive PD was most likely caused by urinary acidification and decreased toward zero when acetazolamide was added to the bath, or when CO2 was eliminated from the bathing solutions. In the thick ascending limb of Henle’s loop the PD was +5.8 mV, which is attributed to active chloride reabsorption. Amiloride had no effect on either the PD or the net chloride transport. We conclude that amiloride inhibits active sodium and potassium transport in the cortical collecting tubule, but does not inhibit active chloride transport in the thick ascending limb, and that these effects account for the action of the drug previously observed in the intact kidney.
A DISCRETE-TIME MODEL OF TCP WITH ACTIVE QUEUE MANAGEMENT

The interaction between Transmission Control Protocol (TCP) and Active Queue Management (AQM) can be captured using dynamical models. The communication network is viewed as a discrete-time feedback control system, where TCP adjusts its window size based on packet loss detection during the previous Round Trip Time (RTT) interval. In this research, a discrete-time dynamical model is proposed for the interaction between TCP and Random Early Detection (RED), one of the most widely used AQM schemes in today's Internet. The model, constructed using an iterative map, captures the detailed dynamical behaviour of TCP/RED, including the slow start and fast retransmit phases, as well as the timeout event in TCP. Model performance for various RED parameters is evaluated using the ns-2 network simulator. The results are then compared with other existing models. Based on evaluations and comparisons of our results, we can conclude that the proposed model captures the dynamical behaviour of the TCP/RED system. In addition, the model provides reasonable predictions for system parameters such as RTT, packet sending rate, and packet drop rate. An extension of the proposed model is also presented, which is a dynamical model of TCP with Adaptive RED (ARED), a modified AQM algorithm based on RED.