Solar cell cover glass development Final report

High vacuum ion beam sputtering of integral coverslips for solar cell utilizatio

Теоретичні аспекти та проблеми вивчення давньоруських бібліотек

У статті відбито сучасну тенденцію в гуманітарній науці, де відбувається подальша міждисциплінарна інтеграція, спостерігається застосування різних методологічних підходів, які доповнюють та збагачують один одного; інтеграція спеціальних історичних дисциплін, їх поступова трансформація в замкнену галузь знання. У нашому випадку це – історичне бібліотекознавство і його новий напрям, який пропонує автор статті, – бібліотечне пам’яткознавство.В статье отображена современная тенденция в гуманитарной науке, где происходит дальнейшая междисциплинарная интеграция, наблюдается применение различных методологических подходов, которые дополняют и обогащают друг друга: интеграция специальных исторических дисциплин, их постепенная трансформация в замкнутую отрасль знаний. В нашем случае это историческое библиотековедение и его новое направление, которое предлага- ет автор статьи, – библиотечное памятниковедение.The article reflects the modern trends in humanitarian science for further interdisciplinary integration, and the use of different methodological approaches that complement each other, as well as describes an integration of special historical disciplines, and graduate transformation into the sphere of the general knowledge. In our case we look at the historical librarian studies and specifically at the branch offered by the author, – librarian study of monuments

Latent burnout profiles in a sample of frontline healthcare professionals after the peak of the Italian COVID-19 pandemic

Background: In Italy since February 2020, the unexpected massive afflux of COVID-19 patients exposed healthcare professionals to high work-related stress, high time pressure and increased the risk of being infected. This is the first study that aimed to investigate the psychological impact of COVID-pandemic at the end of the peak, by identifying latent burnout profiles in a sample of front-line healthcare professionals that worked in Italy during the peak of the pandemic. Methods: A total of 589 subjects filled in an online ad-hoc questionnaire and the Italian version of Maslach Burnout Inventory - Human Services Survey. Results: A higher presence of burnout profile in healthcare professionals who worked in frontline during the peak of the COVID-19 pandemic was highlighted. Furthermore, those professionals showed significantly higher perceived stress levels, increase of worries, and sleep problems, they were more likely to underline the importance of team spirit and to consider asking for psychological support. A multiple regression analysis revealed that age, managing COVID-19 patients, perceived stress levels, adequacy of training, and considering to ask for psychological support significantly predicted latent burnout profiles. Moreover, perceived stress levels mediate the relationship between those profiles and managing COVID-19 patients. Conclusions: These findings highlight how stressful and damaging the pandemic has been, especially for people directly involved in the care of patients tested positive for COVID-19. Furthermore, it provides evidence for the importance of investing in wellness for healthcare professionals, in order to avoid shortage due to burnout and to guarantee optimal standards of care to all patient

Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples

Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-validation strategies (CV) for evaluating the ML predictive model performances with not so large datasets. We carried out two classification tasks: histology classification (3 classes) and overall stage classification (two classes: stage I and II). In the first task, the best performance was obtained by a Random Forest classifier, once the analysis has been restricted to stage I and II tumors of the Lung1 and L-RT merged dataset (AUC = 0.72 ± 0.11). For the overall stage classification, the best results were obtained when training on Lung1 and testing of L-RT dataset (AUC = 0.72 ± 0.04 for Random Forest and AUC = 0.84 ± 0.03 for linear-kernel Support Vector Machine). According to the classification task to be accomplished and to the heterogeneity of the available dataset(s), different CV strategies have to be explored and compared to make a robust assessment of the potential of a predictive model based on radiomics and ML

Working Memory, Jumping to Conclusions and Emotion Recognition: a Possible Link in First Episode Psychosis (Fep)

Introduction A large body of literature has demonstrated that people affected by psychotic disorders show deficits in working memory, in Emotion Recognition (ER) and in data-gathering to reach a decision (Jumping To Conclusions - JTC). Aims To investigate a possible correlation between working memory, JTC and ER in FEP. Methods 41 patients and 89 healthy controls completed assessments of working memory using WAIS shortened version, JTC using the 60:40 Beads Task and ER using Degraded Facial Affect Recognition Task. Results According to the literature, cases had poorer performance in working memory tasks (Digit Span: \u3bc7,72 [ds=2,98] vs \u3bc10,14 [ds=3,10], U=865,00, p=0,00; Digit Symbol: \u3bc5,36 [ds=2,43] vs \u3bc10,05 [ds=3,10], U=455,50, p=0,00; Arithmetic: \u3bc5,46 [ds=2,76] vs \u3bc8,74 [ds=3,24], U=865,50, p=0,00; Block Design: \u3bc4,82 [ds=2,72] vs \u3bc7,60 [ds=3,18], U=912,00, p=0,00), in Beads Task (81,6% vs 51,1%, \u3c72=10,27, p=0,001, \u3bc2,53 [ds=3,57] vs \u3bc4,23 [ds=4,77], U=1171,00, p=0,006) and in DFAR (total errors: \u3bc21,62 [ds=7,43] vs \u3bc16,58 [ds=8,69], U=554,50, p=0,002). Furthermore working memory tasks in cases group correlated significantly with JTC (Digit Span: rrho=0,276, p=0,003; Digit Symbol: rrho=0,275, p=0,002; Arithmetic: rrho=0,265, p=0,003; Block Design: rrho=0,292, p=0,001), but only Digit Span with ER (rrho=-0,239; p=0,021). In addition, we found that JTC and ER were significantly associated (rrho=-0,281; p=0,004). Conclusions Data show that working memory impairments, JTC style and dysfunctions in the facial emotions recognition are phenomena strongly correlated in the group of patients. Preliminary results suggest the importance of early rehabilitation as the impairments detected may lead to difficulties in social and relational adaptation in psychotic patients

Cannabis consumption and the risk of psychosis

Summary Objectives: Cannabis is the most widely used illicit drug globally and its use has been linked to an increased risk for psychotic disorders. An association between cannabis consumption and psychotic symptoms was consistently reported by several studies. This case-control study aimed to widen the current findings about the impact of cannabis exposure on the risk of psychosis, by investigating the pattern of cannabis consumption in a sample of first-episode of psychosis (FEP) patients compared to healthy controls. Material and methods: 68 individuals who presented for the first time to mental health services of Palermo (Italy) with an ICD-10 diagnosis of psychotic disorders and 74 healthy were enrolled as part of the Sicilian Genetics and Psychosis study. Psychopathological assessment and diagnosis were carried out by the Schedule for Clinical Assessment in Neuropsychiatry (SCAN). Socio-demographic data were collected by the modified version of the Medical Research Council (MRC) socio-demographic scale. All participants were interviewed using the Cannabis Experience Questionnaire \u2013 Modified Version to obtain a detailed assessment of lifetime patterns of cannabis and other illicit drug consumption. Logistic regression was applied to investigate the relationships between various aspects of cannabis use (lifetime use, age at first use, duration, and frequency of use) and case-control status while controlling for potential confounders. Results: Patients started cannabis consumption about 3 years earlier than the control group (t = 3.1, p = 0.002) and were 8 times more likely to having started using cannabis before 15 years (adjusted OR = 8.0, 95% CI 2.4-27) than controls. Furthermore cases were more likely to smoke more frequently than controls (adjusted OR = 4.4, 95% CI 1.08-18). We did not find a difference in duration of cannabis use between cases and controls. Conclusions: The findings suggest that cannabis exposure, and especially daily cannabis consumption, is associated with the risk for psychosis; however, the retrospective study design does not allow drawing firm conclusions about causality

Comparing microphysical/dynamical outputs by different cloud resolving models: impact on passive microwave precipitation retrieval from satellite

International audienceMesoscale cloud resolving models (CRM's) are often utilized to generate consistent descriptions of the microphysical structure of precipitating clouds, which are then used by physically-based algorithms for retrieving precipitation from satellite-borne microwave radiometers. However, in principle, the simulated upwelling brightness temperatures (TB's) and derived precipitation retrievals generated by means of different CRM's with different microphysical assumptions, may be significantly different even when the models simulate well the storm dynamical and rainfall characteristics. In this paper, we investigate this issue for two well-known models having different treatment of the bulk microphysics, i.e. the UW-NMS and the MM5. To this end, the models are used to simulate the same 24-26 November 2002 flood-producing storm over northern Italy. The model outputs that best reproduce the structure of the storm, as it was observed by the Advanced Microwave Scanning Radiometer (AMSR) onboard the EOS-Aqua satellite, have been used in order to compute the upwelling TB's. Then, these TB's have been utilized for retrieving the precipitation fields from the AMSR observations. Finally, these results are compared in order to provide an indication of the CRM-effect on precipitation retrieval

A microfabricated physical sensor for atmospheric mercury monitoring,”

Abstract A new microfabricated physical sensor for elemental gaseous mercury (Hg 0 ) determinations has been developed and experimentally tested by the authors. Hg 0 represents 90-99% of atmospheric mercury forms. The sensor is based on the technique of resistivity variation of thin gold film, characterised by high selectivity and absence of optical parts. The sensor consists of four identical thin gold film resistors mounted in Wheatstone bridge configuration. Two resistors work as sensitive elements and the others as reference, in order to minimise the influence of temperature variation. The absorption of Hg 0 on the gold film produces a change in the resistivity of the amalgam. Far from the saturation, this change is proportional to the amount of the absorbed Hg 0 . The adsorption behaviour of the sensor deposited by sputtering on two different substrates (glass and Printed Circuit Board (PCB)) have been investigated. The sensors showed to work in a large range of linearity and need a low power during the regeneration process. Sensors on glass and PCB substrates underwent numerous regeneration cycles without inflicting any mechanical or electrical damages to the resistors. The presented experimental results describe the features of both sensors pointing out advantages and drawbacks of the used substrates. The PCB substrate seems to have more suitable characteristics for developing a new mercury 'smart' sensor

The Antioxidant Potential of the Mediterranean Diet in Patients at High Cardiovascular Risk: An In-Depth Review of the PREDIMED

Cardiovascular disease (CVD) is the leading global cause of death. Diet is known to be important in the prevention of CVD. The PREDIMED trial tested a relatively low-fat diet versus a high-fat Mediterranean diet (MedDiet) for the primary prevention of CVD. The resulting reduction of the CV composite outcome resulted in a paradigm shift in CV nutrition. Though many dietary factors likely contributed to this effect, this review focuses on the influence of the MedDiet on endogenous antioxidant systems and the effect of dietary polyphenols. Subgroup analysis of the PREDIMED trial revealed increased endogenous antioxidant and decreased pro-oxidant activity in the MedDiet groups. Moreover, higher polyphenol intake was associated with lower incidence of the primary outcome, overall mortality, blood pressure, inflammatory biomarkers, onset of new-onset type 2 diabetes mellitus (T2DM), and obesity. This suggests that polyphenols likely contributed to the lower incidence of the primary event in the MedDiet groups. In this article, we summarize the potential benefits of polyphenols found in the MedDiet, specifically the PREDIMED cohort. We also discuss the need for further research to confirm and expand the findings of the PREDIMED in a non-Mediterranean population and to determine the exact mechanisms of action of polyphenols