The 5th edition of the Roma-BZCAT. A short presentation

The 5th edition of the Roma-BZCAT Multifrequency Catalogue of Blazars is available in a printed version and online at the ASDC website (http://www.asdc.asi.it/bzcat); it is also in the NED database. It presents several relevant changes with respect to the past editions which are briefly described in this paper.Comment: 5 pages, 3 figures. Accepted for publication in Astrophysics and Space Scienc

Kinematics and Kinetics of Bulgarian-Bag-Overloaded Sprints in Young Athletes

Background: Eective sprinting requires large acceleration capabilities. To accelerate, large amount of force must be produced and applied eectively. The use of dierent implements such as sleds and vests can increase the amount of force produced and alter sprinting eectiveness. We propose the use of increasing overload via the Bulgarian Bag (BB) as a means to modify athletes\u2019 sprint and acutely increase force and power production. Methods: 24 young athletes performed three sprints over 20 m in three dierent conditions: unloaded (BW) and loaded with BB weighing 2.5% (BB2.5) and 5% (BB5) of the athlete\u2019s body mass. Sprint times at 2.5, 5, 10, 15, and 20 m were acquired and used to compute the force\u2013velocity relationship for the sprints. Maximal velocity (V0), peak force (F0), peak power (PP), and decrease in ratio of force (DRF) were computed. Results: the additional load caused a decrease in sprint times (p < 0.05) and V0 (p = 0.028), conversely no dierences were found for F0 (p = 0.21), PP (p = 0.50), and DRF (p = 0.83). Conclusions: Based on those findings, BB can be an alternative method to eectively overload sprint training toward improving sprinting performance

Mn- and Fe-carbonate rich layers in Meso-Cenozoic shales as proxies of environmental conditions: A case study from the southern Apennine, Italy

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Functional Connectivity Substrates for tDCS Response in Minimally Conscious State Patients

peer reviewedTranscranial direct current stimulation (tDCS) is a non-invasive technique recently employed in disorders of consciousness, and determining a transitory recovery of signs of consciousness in almost half of minimally conscious state (MCS) patients. Although the rising evidences about its possible role in the treatment of many neurological and psychiatric conditions exist, no evidences exist about brain functional connectivity substrates underlying tDCS response. We retrospectively evaluated resting state functional Magnetic Resonance Imaging (fMRI) of 16 sub-acute and chronic MCS patients (6 tDCS responders) who successively received a single left dorsolateral prefrontal cortex (DLPFC) tDCS in a double-blind randomized cross-over trial. A seed-based approach for regions of left extrinsic control network (ECN) and default-mode network (DMN) was performed. tDCS responders showed an increased left intra-network connectivity for regions co-activated with left DLPFC, and significantly with left inferior frontal gyrus. Non-responders (NR) MCS patients showed an increased connectivity between left DLPFC and midline cortical structures, including anterior cingulate cortex and precuneus. Our findings suggest that a prior high connectivity with regions belonging to ECN can facilitate transitory recovery of consciousness in a subgroup of MCS patients that underwent tDCS treatment. Therefore, resting state-fMRI could be very valuable in detecting the neuronal conditions necessary for tDCS to improve behavior in MCS

Mapping the functional connectome traits of levels of consciousness

Examining task-free functional connectivity (FC) in the human brain offers insights on how spontaneous integration and segregation of information relate to human cognition, and how this organization may be altered in different conditions, and neurological disorders. This is particularly relevant for patients in disorders of consciousness (DOC) following severe acquired brain damage and coma, one of the most devastating conditions in modern medical care. We present a novel data-driven methodology, connICA, which implements Independent Component Analysis (ICA) for the extraction of robust independent FC patterns (FC-traits) from a set of individual functional connectomes, without imposing any a priori data stratification into groups. We here apply connICA to investigate associations between network traits derived from task-free FC and cognitive/clinical features that define levels of consciousness. Three main independent FC-traits were identified and linked to consciousness-related clinical features. The first one represents the functional configuration it is associated to a sedative (sevoflurane), the overall effect of the pathology and the level of arousal. The second FC-trait reflects the disconnection of the visual and sensory-motor connectivity patterns. It also relates to the time since the insult and to the ability of communicating with the external environment. The third FC-trait isolates the connectivity pattern encompassing the fronto-parietal and the default-mode network areas as well as the interaction between left and right hemispheres, which are also associated to the awareness of the self and its surroundings. Each FC-trait represents a distinct functional process with a role in the degradation of conscious states of functional brain networks, shedding further light on the functional subcircuits that get disrupted in severe brain-damage

Exercise twice-a-day potentiates markers of mitochondrial biogenesis in men

Endurance exercise begun with reduced muscle glycogen stores seems to potentiate skeletal muscle protein abundance and gene expression. However, it is unknown whether this greater signaling responses is due to performing two exercise sessions in close proximity-as a first exercise session is necessary to reduce the muscle glycogen stores. In the present study, we manipulated the recovery duration between a first muscle glycogen-depleting exercise and a second exercise session, such that the second exercise session started with reduced muscle glycogen in both approaches but was performed either 2 or 15 hours after the first exercise session (so-called twice-a-day and once-daily approaches, respectively). We found that exercise twice-a-day increased the nuclear abundance of transcription factor EB (TFEB) and nuclear factor of activated T cells (NFAT) and potentiated the transcription of peroxisome proliferator-activated receptor-ɣ coactivator 1-alpha (PGC-1α), peroxisome proliferator-activated receptor-alpha (PPARα), and peroxisome proliferator-activated receptor beta/delta (PPARβ/δ) genes, in comparison with the once-daily exercise. These results suggest that part of the elevated molecular signaling reported with previous train-low approaches might be attributed to performing two exercise sessions in close proximity. The twice-a-day approach might be an effective strategy to induce adaptations related to mitochondrial biogenesis and fat oxidation

A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures

In recent years, the field of Deep Learning has seen many disruptive and impactful advancements. Given the increasing complexity of deep neural networks, the need for efficient hardware accelerators has become more and more pressing to design heterogeneous HPC platforms. The design of Deep Learning accelerators requires a multidisciplinary approach, combining expertise from several areas, spanning from computer architecture to approximate computing, computational models, and machine learning algorithms. Several methodologies and tools have been proposed to design accelerators for Deep Learning, including hardware-software co-design approaches, high-level synthesis methods, specific customized compilers, and methodologies for design space exploration, modeling, and simulation. These methodologies aim to maximize the exploitable parallelism and minimize data movement to achieve high performance and energy efficiency. This survey provides a holistic review of the most influential design methodologies and EDA tools proposed in recent years to implement Deep Learning accelerators, offering the reader a wide perspective in this rapidly evolving field. In particular, this work complements the previous survey proposed by the same authors in [203], which focuses on Deep Learning hardware accelerators for heterogeneous HPC platforms

Equalizing the Pixel Response of the Imaging Photoelectric Polarimeter On-Board the IXPE Mission

The Gas Pixel Detector is a gas detector, sensitive to the polarization of X-rays, currently flying on-board IXPE - the first observatory dedicated to X-ray polarimetry. It detects X-rays and their polarization by imaging the ionization tracks generated by photoelectrons absorbed in the sensitive volume, and then reconstructing the initial direction of the photoelectrons. The primary ionization charge is multiplied and ultimately collected on a finely-pixellated ASIC specifically developed for X-ray polarimetry. The signal of individual pixels is processed independently and gain variations can be substantial, of the order of 20%. Such variations need to be equalized to correctly reconstruct the track shape, and therefore its polarization direction. The method to do such equalization is presented here and is based on the comparison between the mean charge of a pixel with respect to the other pixels for equivalent events. The method is shown to finely equalize the response of the detectors on board IXPE, allowing a better track reconstruction and energy resolution, and can in principle be applied to any imaging detector based on tracks.Comment: Accepted for publication in The Astronomical Journal. 10 pages, 19 figure

Impact of social determinants on antiretroviral therapy access and outcomes entering the era of universal treatment for people living with HIV in Italy

Background: Social determinants are known to be a driving force of health inequalities, even in high income countries. Aim of our study was to determine if these factors can limit antiretroviral therapy (ART) access, outcome and retention in care of people living with HIV (PLHIV) in Italy. Methods: All ART naïve HIV+ patients (pts) of Italian nationality enrolled in the ICONA Cohort from 2002 to 2016 were included. The association of socio-demographic characteristics (age, sex, risk factor for HIV infection, educational level, occupational status and residency area) with time to: ART initiation (from the first positive anti-HIV test), ART regimen discontinuation, and first HIV-RNA < 50 cp/mL, were evaluated by Cox regression analysis, Kaplan Meier method and log-rank test. Results: A total of 8023 HIV+ pts (82% males, median age at first pos anti-HIV test 36 years, IQR: 29-44) were included: 6214 (77.5%) started ART during the study period. Women, people who inject drugs (PWID) and residents in Southern Italy presented the lowest levels of education and the highest rate of unemployment compared to other groups. Females, pts aged > 50 yrs., unemployed vs employed, and people with lower educational levels presented the lowest CD4 count at ART initiation compared to other groups. The overall median time to ART initiation was 0.6 years (yrs) (IQR 0.1-3.7), with a significant decrease over time [2002-2006 = 3.3 yrs. (0.2-9.4); 2007-2011 = 1.0 yrs. (0.1-3.9); 2012-2016 = 0.2 yrs. (0.1-2.1), p < 0.001]. By multivariate analysis, females (p < 0.01) and PWID (p < 0.001), presented a longer time to ART initiation, while older people (p < 0.001), people with higher educational levels (p < 0.001), unemployed (p = 0.02) and students (p < 0.001) were more likely to initiate ART. Moreover, PWID, unemployed vs stable employed, and pts. with lower educational levels showed a lower 1-year probability of achieving HIV-RNA suppression, while females, older patients, men who have sex with men (MSM), unemployed had higher 1-year risk of first-line ART discontinuation. Conclusions: Despite median time to ART start decreased from 2002 to 2016, socio-demographic factors still contribute to disparities in ART initiation, outcome and durability

Erratum to: Cortical reorganization in an astronaut’s brain after long-duration spaceflight (Brain Struct Funct, DOI 10.1007/s00429-015-1054-3)

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