Nonextensive Thermostatistical Approach to the Thermoluminescence Decay

In this study, thermoluminescence decay is investigated within Tsallis thermostatistics (TT). We belive that this is the first attempt to handle themoluminescence decay process within TT

Smart Textiles for Soldier of the Future

The textile-based materials, equipped with nanotechnology and electronics, have a majorrole in the development of high-tech milltary uniforms and materials. Active intelligent textilesystems, integrated to electronics, have the capacity of improving the combat soldiers performanceby sensing, adopting themselves and responding to a situational combat need allowing thecombat soldiers to continue their mission. Meantime, smart technologies aim to help soldiersdo everyth~ngth ey need to do with a less number of equipment and a lighter load. In this study,recent developments on smart garments, especially designed for military usage owing to theirelectronic functions, and intelligent textlle-based materials that can be used in battlefield, areintroduced

The effects of the nonextensivity on the dimerization process and nematic ordering

The influence of the dimerization process on the nematic ordering is investigated by using a nonextensive thermostatistics, namely Tsallis thermostatistics(TT). A theoretical model taking into account the dimerization influence on the nematic scalar order parameter has been recently presented[1]. Our study considers this model and the theoretical predictions for the nematic order parameter are improved by using TT

OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics

Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their relatively steep learning curve and the different methodologies employed by DL compared to traditional approaches, along with the high complexity of DL models, which often leads to the need of employing specialized hardware accelerators, further increase the effort and cost needed to employ DL models in robotics. Also, most of the existing DL methods follow a static inference paradigm, as inherited by the traditional computer vision pipelines, ignoring active perception, which can be employed to actively interact with the environment in order to increase perception accuracy. In this paper, we present the Open Deep Learning Toolkit for Robotics (OpenDR). OpenDR aims at developing an open, non-proprietary, efficient, and modular toolkit that can be easily used by robotics companies and research institutions to efficiently develop and deploy AI and cognition technologies to robotics applications, providing a solid step towards addressing the aforementioned challenges. We also detail the design choices, along with an abstract interface that was created to overcome these challenges. This interface can describe various robotic tasks, spanning beyond traditional DL cognition and inference, as known by existing frameworks, incorporating openness, homogeneity and robotics-oriented perception e.g., through active perception, as its core design principles.acceptedVersionPeer reviewe

Cytokine Plasma Levels: Reliable Predictors for Radiation Pneumonitis?

BACKGROUND: Radiotherapy (RT) is the primary treatment modality for inoperable, locally advanced non-small-cell lung cancer (NSCLC), but even with highly conformal treatment planning, radiation pneumonitis (RP) remains the most serious, dose-limiting complication. Previous clinical reports proposed that cytokine plasma levels measured during RT allow to estimate the individual risk of patients to develop RP. The identification of such cytokine risk profiles would facilitate tailoring radiotherapy to maximize treatment efficacy and to minimize radiation toxicity. However, cytokines are produced not only in normal lung tissue after irradiation, but are also over-expressed in tumour cells of NSCLC specimens. This tumour-derived cytokine production may influence circulating plasma levels in NSCLC patients. The aim of the present study was to investigate the prognostic value of TNF-alpha, IL-1beta, IL-6 and TGF-beta1 plasma levels to predict radiation pneumonitis and to evaluate the impact of tumour-derived cytokine production on circulating plasma levels in patients irradiated for NSCLC. METHODOLOGY/PRINCIPAL FINDINGS: In 52 NSCLC patients (stage I-III) cytokine plasma levels were investigated by ELISA before and weekly during RT, during follow-up (1/3/6/9 months after RT), and at the onset of RP. Tumour biopsies were immunohistochemically stained for IL-6 and TGF-beta1, and immunoreactivity was quantified (grade 1-4). RP was evaluated according to LENT-SOMA scale. Tumour response was assessed according to RECIST criteria by chest-CT during follow-up. In our clinical study 21 out of 52 patients developed RP (grade I/II/III/IV: 11/3/6/1 patients). Unexpectedly, cytokine plasma levels measured before and during RT did not correlate with RP incidence. In most patients IL-6 and TGF-beta1 plasma levels were already elevated before RT and correlated significantly with the IL-6 and TGF-beta1 production in corresponding tumour biopsies. Moreover, IL-6 and TGF-beta1 plasma levels measured during follow-up were significantly associated with the individual tumour responses of these patients. CONCLUSIONS/SIGNIFICANCE: The results of this study did not confirm that cytokine plasma levels, neither their absolute nor any relative values, may identify patients at risk for RP. In contrast, the clear correlations of IL-6 and TGF-beta1 plasma levels with the cytokine production in corresponding tumour biopsies and with the individual tumour responses suggest that the tumour is the major source of circulating cytokines in patients receiving RT for advanced NSCLC

Translational toxicology in setting occupational exposure limits for dusts and hazard classification – a critical evaluation of a recent approach to translate dust overload findings from rats to humans

Background We analyze the scientific basis and methodology used by the German MAK Commission in their recommendations for exposure limits and carcinogen classification of “granular biopersistent particles without known specific toxicity” (GBS). These recommendations are under review at the European Union level. We examine the scientific assumptions in an attempt to reproduce the results. MAK’s human equivalent concentrations (HECs) are based on a particle mass and on a volumetric model in which results from rat inhalation studies are translated to derive occupational exposure limits (OELs) and a carcinogen classification. Methods We followed the methods as proposed by the MAK Commission and Pauluhn 2011. We also examined key assumptions in the metrics, such as surface area of the human lung, deposition fractions of inhaled dusts, human clearance rates; and risk of lung cancer among workers, presumed to have some potential for lung overload, the physiological condition in rats associated with an increase in lung cancer risk. Results The MAK recommendations on exposure limits for GBS have numerous incorrect assumptions that adversely affect the final results. The procedures to derive the respirable occupational exposure limit (OEL) could not be reproduced, a finding raising considerable scientific uncertainty about the reliability of the recommendations. Moreover, the scientific basis of using the rat model is confounded by the fact that rats and humans show different cellular responses to inhaled particles as demonstrated by bronchoalveolar lavage (BAL) studies in both species. Conclusion Classifying all GBS as carcinogenic to humans based on rat inhalation studies in which lung overload leads to chronic inflammation and cancer is inappropriate. Studies of workers, who have been exposed to relevant levels of dust, have not indicated an increase in lung cancer risk. Using the methods proposed by the MAK, we were unable to reproduce the OEL for GBS recommended by the Commission, but identified substantial errors in the models. Considerable shortcomings in the use of lung surface area, clearance rates, deposition fractions; as well as using the mass and volumetric metrics as opposed to the particle surface area metric limit the scientific reliability of the proposed GBS OEL and carcinogen classification.International Carbon Black Associatio

Intraperitoneal drain placement and outcomes after elective colorectal surgery: international matched, prospective, cohort study

Despite current guidelines, intraperitoneal drain placement after elective colorectal surgery remains widespread. Drains were not associated with earlier detection of intraperitoneal collections, but were associated with prolonged hospital stay and increased risk of surgical-site infections.Background Many surgeons routinely place intraperitoneal drains after elective colorectal surgery. However, enhanced recovery after surgery guidelines recommend against their routine use owing to a lack of clear clinical benefit. This study aimed to describe international variation in intraperitoneal drain placement and the safety of this practice. Methods COMPASS (COMPlicAted intra-abdominal collectionS after colorectal Surgery) was a prospective, international, cohort study which enrolled consecutive adults undergoing elective colorectal surgery (February to March 2020). The primary outcome was the rate of intraperitoneal drain placement. Secondary outcomes included: rate and time to diagnosis of postoperative intraperitoneal collections; rate of surgical site infections (SSIs); time to discharge; and 30-day major postoperative complications (Clavien-Dindo grade at least III). After propensity score matching, multivariable logistic regression and Cox proportional hazards regression were used to estimate the independent association of the secondary outcomes with drain placement. Results Overall, 1805 patients from 22 countries were included (798 women, 44.2 per cent; median age 67.0 years). The drain insertion rate was 51.9 per cent (937 patients). After matching, drains were not associated with reduced rates (odds ratio (OR) 1.33, 95 per cent c.i. 0.79 to 2.23; P = 0.287) or earlier detection (hazard ratio (HR) 0.87, 0.33 to 2.31; P = 0.780) of collections. Although not associated with worse major postoperative complications (OR 1.09, 0.68 to 1.75; P = 0.709), drains were associated with delayed hospital discharge (HR 0.58, 0.52 to 0.66; P < 0.001) and an increased risk of SSIs (OR 2.47, 1.50 to 4.05; P < 0.001). Conclusion Intraperitoneal drain placement after elective colorectal surgery is not associated with earlier detection of postoperative collections, but prolongs hospital stay and increases SSI risk