Perylene-diimide molecules with cyano functionalization for electron-transporting transistors

Core-cyanated perylene diimide (PDI_CY) derivatives are molecular compounds exhibiting an uncommon combination of appealing properties, including remarkable oxidative stability, high electron affinities, and excellent self-assembling properties. Such features made these compounds the subject of study for several research groups aimed at developing electron-transporting (n-type) devices with superior charge transport performances. After about fifteen years since the first report, field-effect transistors based on PDI_CY thin films are still intensely investigated by the scientific community for the attainment of n-type devices that are able to balance the performances of the best p-type ones. In this review, we summarize the main results achieved by our group in the fabrication and characterization of transistors based on PDI8-CN2 and PDIF-CN2 molecules, undoubtedly the most renowned compounds of the PDI_CY family. Our attention was mainly focused on the electrical properties, both at the micro and nanoscale, of PDI8-CN2 and PDIF-CN2 films deposited using different evaporation techniques. Specific topics, such as the contact resistance phenomenon, the bias stress effect, and the operation in liquid environment, have been also analyzed

FATIGUE ALTERS THE BIOMECHANICS OF TURNS WHILE RUNNING

This study identified the effects of fatigue on lower limb kinematics while running with repeated 180°-turns. An increased stiffness of the pivoting limb was observed in terms of a reduction of hip and knee flexion angles, and an increase of hip abduction and internal rotation. We concluded that muscle fatigue can trigger a sequence of adaptations that were previously found to expose the athlete to an increasing risk of ligament injury. These results expand the base of evidence for the development of field-based prevention programs

DECELERATION COUNTS: ESTIMATING THE ENERGY COST OF SHUlTLE RUNNING FROM MECHANICAL WORK

To estimate the energetic requirements of 5-m shuttle running based on kinematic data, we devised a modified version of existing models for the estimation of the energy cost of gait. In our approach, negative/eccentric work during deceleration phases was added to positive/concentric work in propulsive phases. Ten subjects performed two 5-rnin trials at 50% and 75% of their maximal aerobic speed. The metabolic cost estimated from 30 kinematics was compared to that measured by a portable metabolimeter. The estimation error was 1.2 J/kg/s (7.3%): results encourage to apply this method for the estimation of the workload in sports involving frequent turns and changes of direction

Correction: Space-charge accumulation and band bending at conductive P3HT/PDIF-CN₂ interfaces investigated by scanning-Kelvin probe microscopy

Correction for 'Space-charge accumulation and band bending at conductive P3HT/PDIF-CN2 interfaces investigated by scanning-Kelvin probe microscopy' by Federico Chianese et al., J. Mater. Chem. C, 2021, DOI: 10.1039/d1tc04840f

A KINEMATICALLY BASED ALGORITHM TO ESTIMATE THE ENERGY COST OF VARIABLE-SPEED SHUTTLE RUNNING

Changes of direction (CoDs) have a high metabolic and mechanical impact in field and court team sports, but the estimation of the associated workload is still inaccurate. The aim of this study is to establish a kinematic-based algorithm to determine the energy cost of running at variable speed with frequent 180° CoDs. Kinematic and metabolic data were simultaneously collected during 5-minutes 5+5 m shuttle run tests. Mechanical work computation was split into positive (eccentric) and negative (concentric) contributions. When compared to the actual energy cost, the estimation algorithm returned an error of 5%. This model constitutes the theoretical basis to extend the model from the laboratory to the field, obtaining an accurate measure of the workload of training and matches

Influence of Ambient Humidityon The Conductivity of CH3NH3SnCl3 Hybrid Films

Organic-inorganic (CnH2n+1NH3)2MX4 hybrid perovskites (M=divalent metal, X=halide) are attracting much attention, due to their unique electronic properties and excellent film processability [1]. The Sn based CH3NH3MX3 compounds are a subclass of that hybrid family, with cubic structure, where the organic component is included in the extended three-dimensional inorganic cage. Studies concerning the structural properties of these compounds [2] prove that methylammonium ions are orientationally disordered due to their polar character. On cooling the disorder is removed through one or more phase transitions, that usually determine large conductivity variations. However, the chemical instability is a major problem for accurate transport measurements on Sn hybrids. Furthermore, most of reported conductivity results refer to iodine-based hybrids, that are conductive, while Br- and Cl- compounds are semiconducting or insulating. In this communication we study the influence of ambient humidity on the electrical properties of thermally ablated CH3NH3SnCl3 films. In particular we show that conductivity increases by more than four orders of magnitude when relative humidity increases from 0 to 80%. Measurements performed in sequence give reproducible results, thus indicating that conductivity increase does not originate from irreversible reactions between hybrid and water vapour. We investigate the mechanisms responsible for the conductivity increase by studying the DC and AC characteristics of two contact planar devices as a function of the relative humidity. The results of impedance spectroscopy measurements are interpreted by suitable equivalent circuits that allow us to study the dipendence of the different circuit components on relative humidity. On this base we discuss the device characteristics and suggest novel insights into humidity sensing properties of CH3NH3SnCl3 films

Quadrato Motor Training (QMT) is associated with DNA methylation changes at DNA repeats: A pilot study

The control of non-coding repeated DNA by DNA methylation plays an important role in genomic stability, contributing to health and healthy aging. Mind-body practices can elicit psychophysical wellbeing via epigenetic mechanisms, including DNA methylation. However, in this context the effects of movement meditations have rarely been examined. Consequently, the current study investigates the effects of a specifically structured movement meditation, called the Quadrato Motor Training (QMT) on psychophysical wellbeing and on the methylation level of repeated sequences. An 8-week daily QMT program was administered to healthy women aged 40-60 years and compared with a passive control group matched for gender and age. Psychological well-being was assessed within both groups by using self-reporting scales, including the Meaning in Life Questionnaire [MLQ] and Psychological Wellbeing Scale [PWB]). DNA methylation profiles of repeated sequences (ribosomal DNA, LINE-1 and Alu) were determined in saliva samples by deep-sequencing. In contrast to controls, the QMT group exhibited increased Search for Meaning, decreased Presence of Meaning and increased Positive Relations, suggesting that QMT may lessen the automatic patterns of thinking. In the QMT group, we also found site-specific significant methylation variations in ribosomal DNA and LINE-1 repeats, consistent with increased genome stability. Finally, the correlations found between changes in methylation and psychometric indices (MLQ and PWB) suggest that the observed epigenetic and psychological changes are interrelated. Collectively, the current results indicate that QMT may improve psychophysical health trajectories by influencing the DNA methylation of specific repetitive sequences

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients