Showing papers by "University of Cagliari published in 2015"

LHCb detector performance

Abstract: The LHCb detector is a forward spectrometer at the Large Hadron Collider (LHC) at CERN. The experiment is designed for precision measurements of CP violation and rare decays of beauty and charm hadrons. In this paper the performance of the various LHCb sub-detectors and the trigger system are described, using data taken from 2010 to 2012. It is shown that the design criteria of the experiment have been met. The excellent performance of the detector has allowed the LHCb collaboration to publish a wide range of physics results, demonstrating LHCb's unique role, both as a heavy flavour experiment and as a general purpose detector in the forward region.

Estimating the impact of workplace bullying: humanistic and economic burden among workers with chronic medical conditions

Abstract: Background. Although the prevalence of work-limiting diseases is increasing, the interplay between occupational exposures and chronic medical conditions remains largely uncharacterized. Research has shown the detrimental effects of workplace bullying but very little is known about the humanistic and productivity cost in victims with chronic illnesses. We sought to assess work productivity losses and health disutility associated with bullying among subjects with chronic medical conditions. Methods. Participants () with chronic diseases answered a self-administered survey including sociodemographic and clinical data, workplace bullying experience, the SF-12 questionnaire, and the Work Productivity Activity Impairment questionnaire. Results. The prevalence of significant impairment was higher among victims of workplace bullying as compared to nonvictims (SF-12 PCS: 55.5% versus 67.9%, ; SF-12 MCS: 59.4% versus 74.3%, ). The adjusted marginal overall productivity cost of workplace bullying ranged from 13.9% to 17.4%, corresponding to Italian Purchase Power Parity (PPP) 2010 US$ 4182–5236 yearly. Association estimates were independent and not moderated by concurrent medical conditions. Conclusions. Our findings demonstrate that the burden on workers’ quality of life and productivity associated with workplace bullying is substantial. This study provides key data to inform policy-making and prioritize occupational health interventions.

Anion sensing by small molecules and molecular ensembles

Abstract: This Tutorial Review provides a short survey of anion sensing by small molecule anion receptors, molecular ensembles and chemodosimeters. The review highlights the many different mechanisms and approaches employed by supramolecular chemists for anion sensing and the wide structural variety present in these systems.

Observation of the rare B-s(0)->mu(+)mu(-) decay from the combined analysis of CMS and LHCb data

Abstract: The standard model of particle physics describes the fundamental particles and their interactions via the strong, electromagnetic and weak forces. It provides precise predictions for measurable quantities that can be tested experimentally. The probabilities, or branching fractions, of the strange B meson (B-s(0)) and the B-0 meson decaying into two oppositely charged muons (mu(+) and mu(-)) are especially interesting because of their sensitivity to theories that extend the standard model. The standard model predicts that the B-s(0)->mu(+)mu(-) and B-0 ->mu(+)mu(-) decays are very rare, with about four of the former occurring for every billion B-s(0) mesons produced, and one of the latter occurring for every ten billion B-0 mesons(1). A difference in the observed branching fractions with respect to the predictions of the standard model would provide a direction in which the standard model should be extended. Before the Large Hadron Collider (LHC) at CERN2 started operating, no evidence for either decay mode had been found. Upper limits on the branching fractions were an order of magnitude above the standard model predictions. The CMS (Compact Muon Solenoid) and LHCb(Large Hadron Collider beauty) collaborations have performed a joint analysis of the data from proton-proton collisions that they collected in 2011 at a centre-of-mass energy of seven teraelectronvolts and in 2012 at eight teraelectronvolts. Here we report the first observation of the B-s(0)->mu(+)mu(-) decay, with a statistical significance exceeding six standard deviations, and the best measurement so far of its branching fraction. Furthermore, we obtained evidence for the B-0 ->mu(+)mu(-) decay with a statistical significance of three standard deviations. Both measurements are statistically compatible with standard model predictions and allow stringent constraints to be placed on theories beyond the standard model. The LHC experiments will resume taking data in 2015, recording proton-proton collisions at a centre-of-mass energy of 13 teraelectronvolts, which will approximately double the production rates of B-s(0) and B-0 mesons and lead to further improvements in the precision of these crucial tests of the standard model.

RAISE: a raw images dataset for digital image forensics

Abstract: Digital forensics is a relatively new research area which aims at authenticating digital media by detecting possible digital forgeries. Indeed, the ever increasing availability of multimedia data on the web, coupled with the great advances reached by computer graphical tools, makes the modification of an image and the creation of visually compelling forgeries an easy task for any user. This in turns creates the need of reliable tools to validate the trustworthiness of the represented information. In such a context, we present here RAISE, a large dataset of 8156 high-resolution raw images, depicting various subjects and scenarios, properly annotated and available together with accompanying metadata. Such a wide collection of untouched and diverse data is intended to become a powerful resource for, but not limited to, forensic researchers by providing a common benchmark for a fair comparison, testing and evaluation of existing and next generation forensic algorithms. In this paper we describe how RAISE has been collected and organized, discuss how digital image forensics and many other multimedia research areas may benefit of this new publicly available benchmark dataset and test a very recent forensic technique for JPEG compression detection.

Cognitive Training for Attention-Deficit/Hyperactivity Disorder: Meta-Analysis of Clinical and Neuropsychological Outcomes From Randomized Controlled Trials

Abstract: Objective The authors performed meta-analyses of randomized controlled trials to examine the effects of cognitive training on attention-deficit/hyperactivity disorder (ADHD) symptoms, neuropsychological deficits, and academic skills in children/adolescents with ADHD. Method The authors searched Pubmed, Ovid, Web of Science, ERIC, and CINAHAL databases through May 18, 2014. Data were aggregated using random-effects models. Studies were evaluated with the Cochrane risk of bias tool. Results Sixteen of 695 nonduplicate records were analyzed (759 children with ADHD). When all types of training were considered together, there were significant effects on total ADHD (standardized mean difference [SMD] = 0.37, 95% CI = 0.09–0.66) and inattentive symptoms (SMD = 0.47, 95% CI = 0.14–0.80) for reports by raters most proximal to the treatment setting (i.e., typically unblinded). These figures decreased substantially when the outcomes were provided by probably blinded raters (ADHD total: SMD = 0.20, 95% CI = 0.01–0.40; inattention: SMD = 0.32, 95% CI = −0.01 to 0.66). Effects on hyperactivity/impulsivity symptoms were not significant. There were significant effects on laboratory tests of working memory (verbal: SMD = 0.52, 95% CI = 0.24–0.80; visual: SMD = 0.47, 95% CI = 0.23–0.70) and parent ratings of executive function (SMD = 0.35, 95% CI = 0.08–0.61). Effects on academic performance were not statistically significant. There were no effects of working memory training, specifically on ADHD symptoms. Interventions targeting multiple neuropsychological deficits had large effects on ADHD symptoms rated by most proximal assessors (SMD = 0.79, 95% CI = 0.46–1.12). Conclusion Despite improving working memory performance, cognitive training had limited effects on ADHD symptoms according to assessments based on blinded measures. Approaches targeting multiple neuropsychological processes may optimize the transfer of effects from cognitive deficits to clinical symptoms.

Terms, definitions and measurements to describe sonographic features of myometrium and uterine masses: a consensus opinion from the Morphological Uterus Sonographic Assessment (MUSA) group

Abstract: The MUSA (Morphological Uterus Sonographic Assessment) statement is a consensus statement on terms, definitions and measurements that may be used to describe and report the sonographic features of the myometrium using gray-scale sonography, color/power Doppler and three-dimensional ultrasound imaging. The terms and definitions described may form the basis for prospective studies to predict the risk of different myometrial pathologies, based on their ultrasound appearance, and thus should be relevant for the clinician in daily practice and for clinical research. The sonographic features and use of terminology for describing the two most common myometrial lesions (fibroids and adenomyosis) and uterine smooth muscle tumors are presented. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

CopperDroid: Automatic Reconstruction of Android Malware Behaviors

Abstract: Mobile devices and their application marketplaces drive the entire economy of the today's mobile landscape. Android platforms alone have produced staggering revenues, exceeding five billion USD, which has attracted cybercriminals and increased malware in Android markets at an alarming rate. To better understand this slew of threats, we present CopperDroid, an automatic VMI-based dynamic analysis system to reconstruct the behaviors of Android malware. The novelty of CopperDroid lies in its agnostic approach to identify interesting OS- and high-level Android-specific behaviors. It reconstructs these behaviors by observing and dissecting system calls and, therefore, is resistant to the multitude of alterations the Android runtime is subjected to over its life-cycle. CopperDroid automatically and accurately reconstructs events of interest that describe, not only well-known process-OS interactions (e.g., file and process creation), but also complex intra- and inter-process communications (e.g., SMS reception), whose semantics are typically contextualized through complex Android objects. Because CopperDroid's reconstruction mechanisms are agnostic to the underlying action invocation methods, it is able to capture actions initiated both from Java and native code execution. CopperDroid's analysis generates detailed behavioral profiles that abstract a large stream of low-level—often uninteresting—events into concise, high-level semantics, which are well-suited to provide insightful behavioral traits and open the possibility to further research directions. We carried out an extensive evaluation to assess the capabilities and performance of CopperDroid on more than 2,900 Android malware samples. Our experiments show that CopperDroid faithfully reconstructs OS- and Android-specific behaviors. Additionally, we demonstrate how CopperDroid can be leveraged to disclose additional behaviors through the use of a simple, yet effective, app stimulation technique. Using this technique, we successfully triggered and disclosed additional behaviors on more than 60% of the analyzed malware samples. This qualitatively demonstrates the versatility of CopperDroid's ability to improve dynamic-based code coverage.

Is Feature Selection Secure against Training Data Poisoning

Abstract: Learning in adversarial settings is becoming an important task for application domains where attackers may inject malicious data into the training set to subvert normal operation of data-driven technologies. Feature selection has been widely used in machine learning for security applications to improve generalization and computational efficiency, although it is not clear whether its use may be beneficial or even counterproductive when training data are poisoned by intelligent attackers. In this work, we shed light on this issue by providing a framework to investigate the robustness of popular feature selection methods, including LASSO, ridge regression and the elastic net. Our results on malware detection show that feature selection methods can be significantly compromised under attack (we can reduce LASSO to almost random choices of feature sets by careful insertion of less than 5% poisoned training samples), highlighting the need for specific countermeasures.

Exploiting XPS for the identification of sulfides and polysulfides

Abstract: The identification of surface sulfide and polysulfide species based on the curve fitting of S2p photoelectron spectra and, for the first time, of X-ray excited S KLL Auger spectra has been performed. The different sulfur chemical states present on the surface (sulfide S2−, central S and terminal S in polysulfide chains) could be unambiguously assigned in the chemical state plot. Sulfur atoms in the central or terminal position, respectively, are found on a line with slope ca. −3 irrespective of the cation indicating similar initial state effects. On the other hand, for a given polysulfide, e.g. K2Sn, sulfur atoms both in central or terminal positions are found on the same line with slope −1 indicating similar final state effects. This behavior can be rationalized with the fact that the negative charge in polysulfide chains is located mainly on sulfur atoms in the terminal position; indeed, sulfur present as central S shows a binding energy shift of −0.6 eV with respect to elemental sulfur (S8), and sulfur in terminal S a shift of −2.4 eV. An application of this approach tested on commercial alkali polysulfides is provided for the curve fitting of SKLL signals and sulfur speciation of three different sulfide minerals enargite (Cu3AsS4), chalcopyrite (CuFeS2) and arsenopyrite (FeAsS). Also for the surface of mineral sulfides, terminal S atoms and central S atoms in the polysulfide chains can successfully be identified.

Search for the decay B-s(0) -> (D)over-bar(0) f(0)(980)

Abstract: A search for $B_s^0 \to \overline{D}^{0} f_{0}(980)$ decays is performed using $3.0\, {\rm fb}^{-1}$ of $pp$ collision data recorded by the LHCb experiment during 2011 and 2012. The $f_{0}(980)$ meson is reconstructed through its decay to the $\pi^{+}\pi^{-}$ final state in the mass window $900\, {\rm MeV}/c^{2} < m(\pi^{+}\pi^{-}) < 1080\, {\rm MeV}/c^{2}$. No significant signal is observed. The first upper limits on the branching fraction of $\mathcal{B}(B_s^0 \to \overline{D}^{0} f_{0}(980)) < 3.1\,(3.4) \times 10^{-6}$ are set at $90\,\%$ ($95\,\%$) confidence level.

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: The challenge ahead

Abstract: Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology.

Risk factors for neurodegeneration in idiopathic rapid eye movement sleep behavior disorder: A multicenter study

Abstract: Objective To assess whether risk factors for Parkinson disease and dementia with Lewy bodies increase rate of defined neurodegenerative disease in idiopathic rapid eye movement (REM) sleep behavior disorder (RBD). Methods Twelve centers administered a detailed questionnaire assessing risk factors for neurodegenerative synucleinopathy to patients with idiopathic RBD. Variables included demographics, lifestyle factors, pesticide exposures, occupation, comorbid conditions, medication use, family history, and autonomic/motor symptoms. After 4 years of follow-up, patients were assessed for dementia or parkinsonism. Disease risk was assessed with Kaplan–Meier analysis, and epidemiologic variables were compared between convertors and those still idiopathic using logistic regression. Results Of 305 patients, follow-up information was available for 279, of whom 93 (33.3%) developed defined neurodegenerative disease. Disease risk was 25% at 3 years and 41% after 5 years. Patients who converted were older (difference = 4.5 years, p < 0.001), with similar sex distribution. Neither caffeine, smoking, nor alcohol exposure predicted conversion. Although occupation was similar between groups, those who converted had a lower likelihood of pesticide exposure (occupational insecticide = 2.3% vs 9.0%). Convertors were more likely to report family history of dementia (odds ratio [OR] = 2.09), without significant differences in Parkinson disease or sleep disorders. Medication exposures and medical history were similar between groups. Autonomic and motor symptoms were more common among those who converted. Risk factors for primary dementia and parkinsonism were generally similar, except for a notably higher clonazepam use in dementia convertors (OR = 2.6). Interpretation Patients with idiopathic RBD are at very high risk of neurodegenerative synucleinopathy. Risk factor profiles between convertors and nonconvertors have both important commonalities and differences. Ann Neurol 2015;77:830–839

Measurement of the track reconstruction efficiency at LHCb

Abstract: The determination of track reconstruction efficiencies at LHCb using J/psi -> mu(+)mu(-) decays is presented. Efficiencies above 95% are found for the data taking periods in 2010, 2011, and 2012. The ratio of the track reconstruction efficiency of muons in data and simulation is compatible with unity and measured with an uncertainty of 0.8% for data taking in 2010, and at a precision of 0.4% for data taking in 2011 and 2012. For hadrons an additional 1.4% uncertainty due to material interactions is assumed. This result is crucial for accurate cross section and branching fraction measurements in LHCb.

Angular analysis and differential branching fraction of the decay B s 0 → ϕμ + μ −

Abstract: An angular analysis and a measurement of the differential branching fraction of the decay B0s→ϕμ+μ− are presented, using data corresponding to an integrated luminosity of 3.0fb−1 of pp collisions recorded by the LHCb experiment at s√=7 and 8TeV. Measurements are reported as a function of q2, the square of the dimuon invariant mass and results of the angular analysis are found to be consistent with the Standard Model. In the range 1

Internet of multimedia things

Abstract: Internet of Things (IoT) systems cannot successfully realize the notion of ubiquitous connectivity of everything if they are not capable to truly include 'multimedia things'. However, the current research and development activities in the field do not mandate the features of multimedia objects, thus leaving a gap to benefit from multimedia content based services and applications. In this paper, we analyze this issue by contemplating the concept of IoT and drawing an inspiration towards the perspective vision of 'Internet of Multimedia Things' (IoMT). Therein, we introduce IoMT as a novel paradigm in which smart heterogeneous multimedia things can interact and cooperate with one another and with other things connected to the Internet to facilitate multimedia based services and applications that are globally available to the users. Some applications and use-cases for IoMT are presented to reflect the possibilities enabled by this new paradigm. An IoMT architecture is then presented which is segregated into four distinct stages; (i) multimedia sensing, (ii) reporting and addressability, (iii) multimedia-aware cloud, and (iv) multi-agent systems. Instead of proposing specific technical solutions for each individual stage of the presented architecture, we survey the already existing technologies, providing a synthesis for the realization of the vision of IoMT. Subsequently, various requirements and challenges as well as the feasibility of existing solutions for each stage of proposed IoMT architecture are comprehensively discussed.

Monitoring the modifications of the vitreous humor metabolite profile after death: an animal model.

Abstract: We applied a metabolomic approach to monitor the modifications occurring in goat vitreous humor (VH) metabolite composition at different times (0, 6, 12, 18, and 24 hours) after death. The 1H-NMR analysis of the VH samples was performed for the simultaneous determination of several metabolites (i.e., the metabolite profile) representative of the VH status at different times. Spectral data were analyzed by Principal Component Analysis (PCA) and by Orthogonal Projection to Latent Structures (OPLS) regression technique. PCA and OPLS suggested that different spectral regions were involved in time-related changes. The major time-related compositional changes, here detected, were the increase of lactate, hypoxanthine, alanine, total glutathione, choline/phosphocholine, creatine, and myo-inositol and the decrease of glucose and 3-hydroxybutyrate. We attempted a speculative interpretation of the biological mechanisms underlying these changes. These results show that multivariate statistical approach, based on 1H NMR metabolite profiling, is a powerful tool for detecting ongoing differences in VH composition and may be applied to investigate several physiological and pathological conditions.

Cell-specific STORM super-resolution imaging reveals nanoscale organization of cannabinoid signaling

Abstract: A major challenge in neuroscience is to determine the nanoscale position and quantity of signaling molecules in a cell type- and subcellular compartment-specific manner. We developed a new approach to this problem by combining cell-specific physiological and anatomical characterization with super-resolution imaging and studied the molecular and structural parameters shaping the physiological properties of synaptic endocannabinoid signaling in the mouse hippocampus. We found that axon terminals of perisomatically projecting GABAergic interneurons possessed increased CB1 receptor number, active-zone complexity and receptor/effector ratio compared with dendritically projecting interneurons, consistent with higher efficiency of cannabinoid signaling at somatic versus dendritic synapses. Furthermore, chronic Δ(9)-tetrahydrocannabinol administration, which reduces cannabinoid efficacy on GABA release, evoked marked CB1 downregulation in a dose-dependent manner. Full receptor recovery required several weeks after the cessation of Δ(9)-tetrahydrocannabinol treatment. These findings indicate that cell type-specific nanoscale analysis of endogenous protein distribution is possible in brain circuits and identify previously unknown molecular properties controlling endocannabinoid signaling and cannabis-induced cognitive dysfunction.

Measurement of the $B_s^0 \to \phi \phi$ branching fraction and search for the decay $B^0 \to \phi \phi$

Abstract: Using a dataset corresponding to an integrated luminosity of 3.0 fb$^{-1}$ collected in $pp$ collisions at centre-of-mass energies of 7 and 8 TeV, the $B_s^0 \to \phi \phi$ branching fraction is measured to be \[ \mathcal{B}(B_s^0 \to \phi \phi) = ( 1.84 \pm 0.05 (\text{stat}) \pm 0.07 (\text{syst}) \pm 0.11 (f_s/f_d) \pm 0.12 (\text{norm}) ) \times 10^{-5}, \] where $f_s/f_d$ represents the ratio of the $B_s^0$ to $B^0$ production cross-sections, and the $B^0 \to \phi K^*(892)^0$ decay mode is used for normalization. This is the most precise measurement of this branching fraction to date, representing a factor five reduction in the statistical uncertainty compared with the previous best measurement. A search for the decay $B^0 \to \phi \phi$ is also made. No signal is observed, and an upper limit on the branching fraction is set as \[ \mathcal{B}(B^0 \to \phi \phi) < 2.8 \times 10^{-8} \] at 90% confidence level. This is a factor of seven improvement compared to the previous best limit.

Diversified Sensitivity-Based Undersampling for Imbalance Classification Problems

Abstract: Undersampling is a widely adopted method to deal with imbalance pattern classification problems. Current methods mainly depend on either random resampling on the majority class or resampling at the decision boundary. Random-based undersampling fails to take into consideration informative samples in the data while resampling at the decision boundary is sensitive to class overlapping. Both techniques ignore the distribution information of the training dataset. In this paper, we propose a diversified sensitivity-based undersampling method. Samples of the majority class are clustered to capture the distribution information and enhance the diversity of the resampling. A stochastic sensitivity measure is applied to select samples from both clusters of the majority class and the minority class. By iteratively clustering and sampling, a balanced set of samples yielding high classifier sensitivity is selected. The proposed method yields a good generalization capability for 14 UCI datasets.

World Input-Output Network.

Abstract: Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the global multi-regional input-output (GMRIO) tables By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION) and document its evolution over time At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries

Centrality dependence of particle production in p-Pb collisions at root s(NN)=5.02 TeV

Abstract: We report measurements of the primary charged-particle pseudorapidity density and transverse momentum distributions in p-Pb collisions at root s(NN) = 5.02 TeV and investigate their correlation with experimental observables sensitive to the centrality of the collision. Centrality classes are defined by using different event-activity estimators, i.e., charged-particle multiplicities measured in three different pseudorapidity regions as well as the energy measured at beam rapidity (zero degree). The procedures to determine the centrality, quantified by the number of participants (N-part) or the number of nucleon-nucleon binary collisions (N-coll) are described. We show that, in contrast to Pb-Pb collisions, in p-Pb collisions large multiplicity fluctuations together with the small range of participants available generate a dynamical bias in centrality classes based on particle multiplicity. We propose to use the zero-degree energy, which we expect not to introduce a dynamical bias, as an alternative event-centrality estimator. Based on zero-degree energy-centrality classes, the N-part dependence of particle production is studied. Under the assumption that the multiplicity measured in the Pb-going rapidity region scales with the number of Pb participants, an approximate independence of the multiplicity per participating nucleon measured at mid-rapidity of the number of participating nucleons is observed. Furthermore, at high-pT the p-Pb spectra are found to be consistent with the pp spectra scaled by N-coll for all centrality classes. Our results represent valuable input for the study of the event-activity dependence of hard probes in p-Pb collisions and, hence, help to establish baselines for the interpretation of the Pb-Pb data.

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Abstract: Background Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response ( P = 3.27 × 10 −12 after multiple testing correction for pathways), regulation of endocytosis ( P = 1.31 × 10 −11 ), cholesterol transport ( P = 2.96 × 10 −9 ), and proteasome-ubiquitin activity ( P = 1.34 × 10 −6 ). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002–.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.

Search for the Lambda(0)(b) -> Lambda eta ' and Lambda(0)(b) -> Lambda eta decays with the LHCb detector

Abstract: A search is performed for the as yet unobserved baryonic Lambda(0)(b) -> Lambda eta' and Lambda(0)(b) -> Lambda eta decays with 3 fb(-1) of proton-proton collision data recorded by the LHCb experiment. The B-0 -> K-s(0)eta' decay is used as a normalisation channel. No significant signal is observed for the Lambda(0)(b) -> Lambda eta' decay. An upper limit is found on the branching fraction of B(Lambda(0)(b) -> Lambda eta') Lambda eta 0 decay at the level of 3 sigma significance, with a branching fraction B(Lambda(0)(b) -> Lambda eta) = (9.3(-5.3)(+7.3)) x 10(-6).

Accuracy of transvaginal ultrasound for diagnosis of deep endometriosis in uterosacral ligaments, rectovaginal septum, vagina and bladder: systematic review and meta-analysis.

Abstract: Objective To review the diagnostic accuracy of transvaginal ultrasound (TVS) in the preoperative detection of endometriosis in the uterosacral ligaments (USL), rectovaginal septum (RVS), vagina and bladder in patients with clinical suspicion of deep infiltrating endometriosis (DIE). Methods An extensive search was performed in MEDLINE (PubMed) and EMBASE for studies published between January 1989 and December 2014. Studies were considered eligible if they reported on the use of TVS for the preoperative detection of endometriosis in the USL, RVS, vagina and bladder in women with clinical suspicion of DIE using the surgical data as a reference standard. Study quality was assessed using the PRISMA guidelines and QUADAS-2 tool. Results Of the 801 citations identified, 11 studies (n = 1583) were considered eligible and were included in the meta-analysis. For detection of endometriosis in the USL, the overall pooled sensitivity and specificity of TVS were 53% (95%CI, 35–70%) and 93% (95%CI, 83–97%), respectively. The pretest probability of USL endometriosis was 54%, which increased to 90% when suspicion of endometriosis was present after TVS examination. For detection of endometriosis in the RVS, the overall pooled sensitivity and specificity were 49% (95%CI, 36–62%) and 98% (95%CI, 95–99%), respectively. The pretest probability of RVS endometriosis was 24%, which increased to 89% when suspicion of endometriosis was present after TVS examination. For detection of vaginal endometriosis, the overall pooled sensitivity and specificity were 58% (95%CI, 40–74%) and 96% (95%CI, 87–99%), respectively. The pretest probability of vaginal endometriosis was 17%, which increased to 76% when suspicion of endometriosis was present after TVS assessment. Substantial heterogeneity was found for sensitivity and specificity for all these locations. For detection of bladder endometriosis, the overall pooled sensitivity and specificity were 62% (95%CI, 40–80%) and 100% (95%CI, 97–100%), respectively. Moderate heterogeneity was found for sensitivity and specificity for bladder endometriosis. The pretest probability of bladder endometriosis was 5%, which increased to 92% when suspicion of endometriosis was present after TVS assessment. Conclusion Overall diagnostic performance of TVS for detecting DIE in uterosacral ligaments, rectovaginal septum, vagina and bladder is fair with high specificity. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

A spectral-timing model for ULXs in the supercritical regime

Abstract: Ultraluminous X-ray sources (ULXs) with luminosities lying between ∼3 × 1039 and 2 × 1040 erg s−1 represent a contentious sample of objects as their brightness, together with a lack of unambiguous mass estimates for the vast majority of the central objects, leads to a degenerate scenario where the accretor could be a stellar remnant (black hole or neutron star) or intermediate-mass black hole (IMBH). Recent, high-quality observations imply that the presence of IMBHs in the majority of these objects is unlikely unless the accretion flow somehow deviates strongly from expectation based on objects with known masses. On the other hand, physically motivated models for supercritical inflows can re-create the observed X-ray spectra and their evolution, although have been lacking a robust explanation for their variability properties. In this paper, we include the effect of a partially inhomogeneous wind that imprints variability on to the X-ray emission via two distinct methods. The model is heavily dependent on both inclination to the line of sight and mass accretion rate, resulting in a series of qualitative and semiquantitative predictions. We study the time-averaged spectra and variability of a sample of well-observed ULXs, finding that the source behaviours can be explained by our model in both individual cases as well as across the entire sample, specifically in the trend of hardness-variability power. We present the covariance spectra for these sources for the first time, which shed light on the correlated variability and issues associated with modelling broad ULX spectra.