Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychological Adjustment after Combat Deployment: Decompression at Home Versus at Sea

ABSTRACT The present quasi-experimental study examined the psychological health of one group of U.S. Marines returning home by 12-day sea voyage to another comparable group returning within 24 hr by air following a 6-month combat deployment to Iraq. Few significant group differences were seen in the 11 assessed self-report outcomes at 3 (n = 631) or at 6 months postdeployment (n = 437). The few significant differences were largely small and somewhat inconsistent. For example, the prevalence of PTSD in Marines returning by sea was higher at 3 months (13% vs 7%) but lower at 6 months (12% vs. 18%), though only the former difference was statistically significant. We conclude that decompression done at sea or at home after return by air have ultimately similar enough outcomes that either approach is appropriate. Future research is needed to explore the potential for time-dependent impacts of various approaches to decompression and to possible heterogeneity of affects across relevant outcomes.
FROM COMPRESSIVE CLUSTERING TO COMPRESSIVE LEARNING Supervisor : Rémi Gribonval

It is often useful to fit a probability model to a data collection, in order to concisely represent the data, to feed learning algorithms that work on densities, to extract features or, simply, to uncover underlying structures. A particularly popular probability model is the Gaussian Mixture Model (GMM). Among many other applications , GMM form a central tool to build time-frequency models of audio data that are used for audio source separation [2], and is traditionally fitted through the Expectation-Maximization (EM) algorithm [3]. However, when the collection is voluminous, memory and computation time can be prohibitive. In a recent paper [1], we proposed a framework to fit a Gaussian Mixture Model (GMM) using only a low-dimensional sketch of the data which represents a limited number empirical moments of the underlying probability distribution. The framework is inspired by compressive sensing [4], an approach that leverages sparsity and random projections to characterize and reconstruct high-dimensional vectors through a limited set of random linear projections, under a sparsity assumption. Compressive sensing allows drastic dimension reduction with controlled loss of information, and is associated to reconstruction algorithms of bounded complexity. By analogy with the algorithms developed for compressive sensing [5,6], we derived a reconstruction algorithm and experimentally showed that it is possible to precisely estimate the mixture parameters of a on GMM with isotropic Gaussians, provided that the sketch is large enough [1]. This resulted in a compressive clustering algorithm, in the sense that the centroids of the main clusters of the training collection can be identified from the sketch. Unlike the classical EM approach to GMM estimation, the proposed compressive clustering algorithm consumes an amount of memory independent of the volume of the training collection. It also provides a privacy-preserving data analysis tool, since the sketch doesnt disclose information about individual elements of the training collection. The goal of this internship is to extend and validate the compressive clustering algorithm [1] to handle GMMs with non-isotropic Gaussians. After an implementation and testing stage where the main computational bottlenecks will be identified and addressed, if time allows, comparisons with EM approaches for audio source separation [2,3] will be performed.
Autophagy Limits Endotoxemic Acute Kidney Injury and Alters Renal Tubular Epithelial Cell Cytokine Expression

Sepsis related acute kidney injury (AKI) is a common in-hospital complication with a dismal prognosis. Our incomplete understanding of disease pathogenesis has prevented the identification of hypothesis-driven preventive or therapeutic interventions. Increasing evidence in ischemia-reperfusion and nephrotoxic mouse models of AKI support the theory that autophagy protects renal tubular epithelial cells (RTEC) from injury. However, the role of RTEC autophagy in septic AKI remains unclear. We observed that lipopolysaccharide (LPS), a mediator of gram-negative bacterial sepsis, induces RTEC autophagy in vivo and in vitro through TLR4-initiated signaling. We modeled septic AKI through intraperitoneal LPS injection in mice in which autophagy-related protein 7 was specifically knocked out in the renal proximal tubules (ATG7KO). Compared to control littermates, ATG7KO mice developed more severe renal dysfunction (24hr BUN 100.1mg/dl +/- 14.8 vs 54.6mg/dl +/- 11.3) and parenchymal injury. After injection with LPS, analysis of kidney lysates identified higher IL-6 expression and increased STAT3 activation in kidney lysates from ATG7KO mice compared to controls. In vitro experiments confirmed an altered response to LPS in RTEC with genetic or pharmacological impairment of autophagy. In conclusion, RTEC autophagy protects against endotoxin induced injury and regulates downstream effects of RTEC TLR4 signaling.
A Secure Oblivious Transfer Protocol from Indistinguishing Obfuscation

We proposed a new secure oblivious transfer protocol from indistinguishability obfuscation in this paper. Our main technical tool is the candidate indistinguishability obfuscation introduced in [1] and a dual-mode cryptosystem proposed in [2]. Following their steps, we presents a new k-out-of-l oblivious transfer protocol, its realization from DDH is described in this paper, in which we combined indistinguishability obfuscation with the dual-mode cryptosystem. The security of our scheme mainly relies on the indistinguishability of the obf-branches ( corresponding to the two modes in dual-mode model). Our paper explores a new way for the application of indistinguishability obfuscation.
A belief-propagation approach for multicast scheduling in input-queued switches

Scheduling multicast traffic in input-queued switches requires solving a hard combinatorial optimization problem in a very short time. This task advocates the design of algorithms that are simple to implement and efficient in terms of performance. We propose a new scheduling algorithm, based on message passing and inspired by the belief propagation paradigm, meant to approximate the provably optimal scheduling policy. Our main finding is that our algorithm outperforms other centralized greedy scheduling policies, achieving a better tradeoff between complexity and performance.
An Absration Layer for Neighborhood Discovery and Cross-Layer Metrics

Topology-awareness is an important feature of communication algorithms and protocols for wireless multi-hop networks. In its basic form, topology-awareness requires nodes to know their immediate neighbors and, if possible, the quality of the links between them. In general, neighborhood discovery is done by routing protocols; the problem with such an approach is that fundamental changes in node characteristics require revisiting the routing protocol, especially if this latter relies on cross-layer metrics. In this paper, we propose an abstraction layer that performs neighborhood discovery and link quality assessment. In this way, neighborhood discovery is decoupled from the upper layers. Our abstraction layer stands as an active building block for the implementation of routing protocols or any other IEEE 802.11 communication algorithm for wireless multi-hop networks. It provides an updated list of neighbors, along with several statistics about link quality that can be used, for instance, to compute cross-layer metrics.
Neonatal representation of odour objects: distinct memories of the whole and its parts

Extraction of relevant information from highly complex environments is a prerequisite to survival. Within odour mixtures, such information is contained in the odours of specific elements or in the mixture configuration perceived as a whole unique odour. For instance, an AB mixture of the element A (ethyl isobutyrate) and the element B (ethyl maltol) generates a configural AB percept in humans and apparently in another species, the rabbit. Here, we examined whether the memory of such a configuration is distinct from the memory of the individual odorants. Taking advantage of the newborn rabbit's ability to learn odour mixtures, we combined behavioural and pharmacological tools to specifically eliminate elemental memory of A and B after conditioning to the AB mixture and evaluate consequences on configural memory of AB. The amnesic treatment suppressed responsiveness to A and B but not to AB. Two other experiments confirmed the specific perception and particular memory of the AB mixture. These data demonstrate the existence of configurations in certain odour mixtures and their representation as unique objects: after learning, animals form a configural memory of these mixtures, which coexists with, but is relatively dissociated from, memory of their elements. This capability emerges very early in life.
Microlensing towards the Large Magellanic Cloud: a study of the LMC halo contribution

We carry out a new analysis of the sample of MACHO microlensing candidates towards the LMC. Our main purpose is to determine the lens population to which the events may belong. We give particular emphasis to the possibility of characterising the Milky Way dark matter halo population with respect to the LMC one. Indeed, we show that only a fraction of the events have characteristics that match those expected for lenses belonging to the MACHO population of the Galactic halo. This suggests that this component cannot explain all the candidates. Accordingly, we challenge the view that the dark matter halo fraction of both the Galaxy and the LMC halos are equal, and indeed we show that, for a MACHO mass in the range 0.1–0.3 $M_\odot$, the LMC halo fraction can be significantly larger than the Milky Way's. In this perspective, our main conclusion is that up to about half of the observed events could be attributed to the LMC MACHO dark matter halo.
Interferometric observations of R Leonis in the K band First direct detection of the photospheric pulsation and study of the atmospheric intensity distribution

The Mira-type star R Leonis was observed at two different epochs in the K band with the FLUOR beam combiner on the IOTA interferometer. A variation of diameter is clearly detected for the very first time at this wavelength revealing an apparent pulsation of atmospheric layers very close to the stellar photosphere. We discuss the excess of visibility measured at high spatial frequencies and show that they very likely reveal smaller diameters of the photosphere (22-24 mas) than those deduced on the basis of shorter frequency components. This smaller diameter makes R Leonis a fundamental pulsator. Mira models are compared to our data and a disagreement with spatial intensity distribution and dynamical behaviour is found.
Two loop partition function for large N pure Yang-Mills theory on a small S**3

We give a direct path-integral calculation of the partition function for pure 3+1 dimensional U(N) Yang-Mills theory at large N on a small S{sup 3}, up to two loop order in perturbation theory. From this, we calculate the one loop shift in the Hagedorn/deconfinement temperature for the theory at small volume, finding that it increases (in units of the inverse sphere radius) as we go to larger coupling (larger volume). Our results also allow us to read off the sum of one loop anomalous dimensions for all operators with a given engineering dimension in planar Yang-Mills theory on R{sup 4}. As checks on our calculation, we reproduce both the Hagedorn shift and some of the anomalous dimension sums by independent methods using the results of Beisert et al. [Nucl. Phys. B 717, 137 (2005)] and Spradlin and Volovich [Nucl. Phys. B 711, 199 (2005)]. The success of our calculation provides a significant check of methods used by Aharony et al. [Phys. Rev. D 71, 125018 (2005)] to establish a first-order deconfinement transition for pure Yang-Mills theory on a small S{sup 3}.
Affine General Equilibrium Models

No-arbitrage models are extremely flexible modelling tools but often lack economic motivation. This paper describes an equilibrium consumption-based CAPM framework based on Epstein-Zin preferences, which produces analytic pricing formulas for stocks and bonds under the assumption that macro growth rates follow affine processes. This allows the construction of equilibrium pricing formulas while maintaining the same flexibility of state dynamics as in no-arbitrage models. In demonstrating the approach, the paper presents a model that incorporates inflation such that asset prices are nominal. The model takes advantage of the possibility of non-Gaussian shocks and model macroeconomic uncertainty as a jump-diffusion process. This leads to endogenous stock market crashes as stock prices drop to reflect a higher expected rate of return in response to sudden increases in risk. The nominal yield curve in this model has a positive slope if expected inflation growth negatively impacts real growth. This model also produces asset prices that are consistent with observed data, including a substantial equity premium at moderate levels of risk aversion.
CLIPS, a Multi-level Italian Computational Lexicon: a Glimpse to Data

CLIPS is a multi-layered Italian computational lexicon based on the PAROLE-SIMPLE model. In this paper we briefly recall the main characteristics of the model and devote our attention to issues emerging from the encoding of large quantities of data, especially in relation to those types of syntactic and semantic information specific to our lexicon and that reflect innovative features of the underlying model. At syntactic level, we show how alternating structures may be encoded in a linguistically more elegant way by using framesets. We illustrate the connection between syntactic and semantic information, and show how the SIMPLE Italian lexicon approach to predicate selection has been refined in CLIPS. At semantic level, we illustrate the richness of information types encoded in a word sense description and the way such a wealth of data can be exploited. We stress in particular the expressive power of the Extended Qualia Structure yet mentioning some of its problematic aspects. We show that queries on qualia relations allow to retrieve lexical collocates, to extract domain specific information, semantic networks, and help interpreting modifying PPs in complex nominals. Finally, we show that features, which cut across the type hierarchy, have a stronger expressive power with respect to semantic types in identifying selectional preferences.
Effect of a diabetes counseling programme on knowledge, attitude and practice among diabetic patients in Erode district of South India

The prevalence of diabetes in India has grown over the past decade. Diabetic patients develop complications due to poor awareness regarding the disease and inadequate glycemic control. Patient education is the most effective way to lessen the complications of diabetes and its management. A total of 207 (85 males and 122 females) type 2 diabetes mellitus patients were enrolled and randomized into test and control groups. Patients in the test group received counseling at each visit and information leaflets from the pharmacist; the control group patients received counseling and information leaflets only at the end of the study. A validated knowledge, attitude, and practice (KAP) questionnaire was administered to both test and control group patients at baseline and at final follow-up to assess awareness regarding disease management. Glucose and lipid levels were also evaluated at baseline and final follow-up in both the groups. At the end of the study, the KAP score of test group patients improved significantly (P<0.0001), whereas no significant changes were observed in control group patients. The postprandial blood glucose (PPBG) levels decreased significantly in the test group. Total cholesterol (TC), triglycerides (TGL), and low density lipoprotein levels (LDL) also showed a decrease in the test group. Thus, our study reveals that pharmacist counseling might be an important element in diabetes management programs.
GC-Rich Sequence Elements Recruit PRC2 in Mammalian ES Cells

Polycomb proteins are epigenetic regulators that localize to developmental loci in the early embryo where they mediate lineage-specific gene repression. In Drosophila, these repressors are recruited to sequence elements by DNA binding proteins associated with Polycomb repressive complex 2 (PRC2). However, the sequences that recruit PRC2 in mammalian cells have remained obscure. To address this, we integrated a series of engineered bacterial artificial chromosomes into embryonic stem (ES) cells and examined their chromatin. We found that a 44 kb region corresponding to the Zfpm2 locus initiates de novo recruitment of PRC2. We then pinpointed a CpG island within this locus as both necessary and sufficient for PRC2 recruitment. Based on this causal demonstration and prior genomic analyses, we hypothesized that large GC-rich elements depleted of activating transcription factor motifs mediate PRC2 recruitment in mammals. We validated this model in two ways. First, we showed that a constitutively active CpG island is able to recruit PRC2 after excision of a cluster of activating motifs. Second, we showed that two 1 kb sequence intervals from the Escherichia coli genome with GC-contents comparable to a mammalian CpG island are both capable of recruiting PRC2 when integrated into the ES cell genome. Our findings demonstrate a causal role for GC-rich sequences in PRC2 recruitment and implicate a specific subset of CpG islands depleted of activating motifs as instrumental for the initial localization of this key regulator in mammalian genomes.
American Thoracic Society Documents an Official American Thoracic Society Clinical Practice Guideline: the Diagnosis of Intensive Care Unit–acquired Weakness in Adults on Behalf of the Ats Committee on Icu-acquired Weakness in Adults Overview Introduction Methods Guideline Panel Formulation of Quest

Rationale: Profound muscle weakness during and after critical illness is termed intensive care unit–acquired weakness (ICUAW). Objectives: To develop diagnostic recommendations for ICUAW. Measurement and Main Results: Severe sepsis, difficult ventilator liberation, and prolonged mechanical ventilation are associated with ICUAW. Physical rehabilitation improves outcomes in heterogeneous populations of ICU patients. Because it may not be feasible to provide universal physical rehabilitation, an alternative approach is to identify patients most likely to benefit. Patients with ICUAW may be such a group. Our review identified only one case series of patients with ICUAW who received physical therapy. When compared with a case series of patients with ICUAW who did not receive structured physical therapy, evidence suggested those who receive physical rehabilitation were more frequently discharged home rather than to a rehabilitative facility, although confidence intervals included no difference. Other interventions show promise, but fewer data proving patient benefit existed, thus precluding specific comment. Additionally, prior comorbidity was insufficiently defined to determine its influence on outcome, treatment response, or patient preferences for diagnostic efforts. We recommend controlled clinical trials in patients with ICUAW that compare physical rehabilitation with usual care and further research in understanding risk and patient preferences. Conclusions: Research that identifies treatments that benefit patients with ICUAW is necessary to determine whether the benefits of diagnostic testing for ICUAW outweigh its burdens. Overview Severe muscle weakness is common among critically ill patients, yet there is no consensus on whether or how to systematically identify patients with intensive care unit–acquired weakness (ICUAW). The guideline development committee began with a systematic review that identified that ICUAW may be more common among ICU patients with severe sepsis as well as those having difficulty being liberated from mechanical ventilation or requiring prolonged mechanical ventilation. Literature review failed to identify evidence comparing the effects of diagnostic testing versus no diagnostic testing on clinical outcomes. A small case series of patients with ICUAW who received physical therapy was identified, and when compared with a similar series of patients with ICUAW who did not receive physical therapy, it appeared that therapy patients might be discharged home rather than to a rehabilitative facility more frequently. However, the confidence intervals did not exclude no effect. As such, the evidence provides very little confidence in the estimated effects of physical therapy on clinical outcomes in patients with ICUAW. The guideline development committee is certain that additional research is necessary to determine …
Revised terminology and concepts for organization of seizures and epilepsies: Report of the ILAE Commission on Classification and Terminology, 2005–2009

The International League Against Epilepsy (ILAE) Commission on Classification and Terminology has revised concepts, terminology, and approaches for classifying seizures and forms of epilepsy. Generalized and focal are redefined for seizures as occurring in and rapidly engaging bilaterally distributed networks (generalized) and within networks limited to one hemisphere and either discretely localized or more widely distributed (focal). Classification of generalized seizures is simplified. No natural classification for focal seizures exists; focal seizures should be described according to their manifestations (e.g., dyscognitive, focal motor). The concepts of generalized and focal do not apply to electroclinical syndromes. Genetic, structural–metabolic, and unknown represent modified concepts to replace idiopathic, symptomatic, and cryptogenic. Not all epilepsies are recognized as electroclinical syndromes. Organization of forms of epilepsy is first by specificity: electroclinical syndromes, nonsyndromic epilepsies with structural–metabolic causes, and epilepsies of unknown cause. Further organization within these divisions can be accomplished in a flexible manner depending on purpose. Natural classes (e.g., specific underlying cause, age at onset, associated seizure type), or pragmatic groupings (e.g., epileptic encephalopathies, self‐limited electroclinical syndromes) may serve as the basis for organizing knowledge about recognized forms of epilepsy and facilitate identification of new forms.
The CORE system: Animation and functional correctness of pointer programs

Pointers are a powerful and widely used programming mechanism, but developing and maintaining correct pointer programs is notoriously hard. Here we describe the CORE1 system, which supports the development of provably correct pointer programs. The CORE system combines data structure animation with functional correctness. While the animation component allows a programmer to explore and debug their algorithms, the functional correctness component provides a stronger guarantee via formal proof. CORE builds upon two external reasoning tools, i.e. the Smallfoot family of static analysers and the IsaPlanner proof planner. At the heart of the CORE functional correctness capability lies an integration of planning and term synthesis. The planning subsystem bridges the gap between shape analysis, provided by Smallfoot, and functional correctness. Key to this process is the generation of functional invariants, i.e. both loop and frame invariants. We use term synthesis, coupled with IsaPlanner's capability for reasoning about inductively defined structures, to automate the generation of functional invariants. The formal guarantees constructed by the CORE system take the form of proof tactics.