Sequential Extraction and Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy Monitoring in the Biorefining of Brewer's Spent Grain.

The brewing industry plays a significant role in producing a substantial annual volume of by-products, which contributes to the global accumulation of food waste. The primary by-product generated is brewer's spent grain (BSG), a lignocellulosic biomass rich in proteins, fiber, and moisture content. Leveraging biorefining and valorization techniques for BSG represents a promising strategy to enhance sustainability, resilience, and circularity within the brewing chain.

Orthodontic patients and the information found on the web: a cross-sectional study.

Background: In recent years, the Web has become a source of medical information for patients, even though the information available online may be incorrect or qualitatively inadequate. Younger generations, immersed in a digital environment since a very tender age, are more likely to get informed online. This study aims to understand the relevance of online information for prospective orthodontic patients and to investigate the effects of digital research on patients' decision-making process, and it also aims to investigate potential generational differences between digital natives and digital immigrants.

Borderline shades: Morphometric features predict borderline personality traits but not histrionic traits.

Borderline personality disorder (BPD) is one of the most diagnosed disorders in clinical settings. Besides the fully diagnosed disorder, borderline personality traits (BPT) are quite common in the general population. Prior studies have investigated the neural correlates of BPD but not of BPT.

Exploring the Role of Birth Environment on Italian Mothers' Emotional Experience during Childbirth.

The physical environment is one of the factors that affect mother's experience of childbirth and psychological health. A woman's childbirth experience has been found to influence not only the mother's own health and future births but also the well-being of her child and family. The present study's objective was to investigate mothers' perceptions of spatial-physical humanization, affective quality of place, and emotions during childbirth.

Comparing reappraisal and acceptance strategies to understand the neural architecture of emotion regulation: a meta-analytic approach.

Introduction: In the emotion regulation literature, the amount of neuroimaging studies on cognitive reappraisal led the impression that the same top-down, control-related neural mechanisms characterize all emotion regulation strategies. However, top-down processes may coexist with more bottom-up and emotion-focused processes that partially bypass the recruitment of executive functions. A case in point is acceptance-based strategies.

Thermoplastic Pultrusion Process of Polypropylene/Glass Tapes.

The present work focuses on the pultrusion of pre-impregnated glass-reinforced polypropylene tapes. An appositely designed laboratory-scale pultrusion line, consisting of a heating/forming die and a cooling die, was used. The temperature of the advancing materials and the pulling force resistance were measured by using thermocouples embedded in the pre-preg tapes and a load cell.

Cytotoxicity and Antibiofilm Activity of Silver-Polypropylene Nanocomposites.

The development of biocompatible nanomaterials that interface with human skin and tissue is critical for advancing prosthetics and other therapeutic medical needs. In this perspective, the development of nanoparticles with cytotoxicity and antibiofilm properties and biocompatibility characteristics are important. Metallic silver (Ag) exhibits good biocompatibility, but it is often challenging to integrate it into a nanocomposite without compromising its antibiofilm properties for optimal applications.

On the Generalization of Deep Learning Models in Video Deepfake Detection.

The increasing use of deep learning techniques to manipulate images and videos, commonly referred to as "deepfakes", is making it more challenging to differentiate between real and fake content, while various deepfake detection systems have been developed, they often struggle to detect deepfakes in real-world situations. In particular, these methods are often unable to effectively distinguish images or videos when these are modified using novel techniques which have not been used in the training set. In this study, we carry out an analysis of different deep learning architectures in an attempt to understand which is more capable of better generalizing the concept of deepfake.

Trust in science and belief in misinformation mediate the effects of political orientation on vaccine hesitancy and intention to be vaccinated.

In previous studies, anti-vaccination attitudes have been attributed either to far-right voters or to both far-left and far-right voters. The present study investigated the associations of political orientation with vaccine hesitancy and intention to be vaccinated against COVID-19, and the potential mediating roles of trust in science and belief in misinformation. A total of 750 Italian respondents completed an online questionnaire in the period between the second and the third wave of COVID-19 (from 9th March to 9th May 2021).

"Fare male farsi male" project - Are cyberbullying and cyber victimisation associated with physical activity levels? a cross sectional study in a sample of Italian adolescents.

Background: The aim of this project is to study the prevalence of cyberbullies (CB) and cybervictims (CV) and cyberbully-victims(CBV) in Italian adolescent students and a possible correlation with physical activity (PA) levels and as potential protective factor.

Methods: The Italian version of the European Cyberbullying Intervention Project Questionnaire (ECIPQ) was used for categorized cyberbullies (CB) and cybervictims (CV). Six items of the IPAQ-A Italian version were considered to measure the PA levels.

A new governance model for the conservation and enhancement of Italian ancient transhumance routes.

Transhumance routes mark the natural path followed by herds during their seasonal movements. These routes are disappearing in many European countries. In Italy, a few fragments survive in Molise, in southern Italy, called Tratturi and run along grassy paths.

The binding of negative emotional stimuli with spatial information in working memory: A possible role for the episodic buffer.

Introduction: Remembering where negative events occur has undeniable adaptive value, however, how these memories are formed remains elusive. We investigated the role of working memory subcomponents in binding emotional and visuo-spatial information using an emotional version of the object relocation task (EORT).

Methods: After displaying black rectangles simultaneously, emotional pictures (from the International Affective Pictures System) appeared sequentially over each rectangle.

Ventricular tachycardia ablation through radiation therapy (VT-ART) consortium: Concept description of an observational multicentric trial matched pair analysis.

Introduction: Monomorphic ventricular tachycardia (VT) is a life-threatening condition often observed in patients with structural heart disease. Ventricular tachycardia ablation through radiation therapy (VT-ART) for sustained monomorphic ventricular tachycardia seems promising, effective, and safe. VT-ART delivers focused, high-dose radiation, usually in a single fraction of 25 Gy, allowing ablation of VT by inducing myocardial scars.

Abnormal Brain Circuits Characterize Borderline Personality and Mediate the Relationship between Childhood Traumas and Symptoms: A mCCA+jICA and Random Forest Approach.

Borderline personality disorder (BPD) is a severe personality disorder whose neural bases are still unclear. Indeed, previous studies reported inconsistent findings concerning alterations in cortical and subcortical areas. In the present study, we applied for the first time a combination of an unsupervised machine learning approach known as multimodal canonical correlation analysis plus joint independent component analysis (mCCA+jICA), in combination with a supervised machine learning approach known as random forest, to possibly find covarying gray matter and white matter (GM-WM) circuits that separate BPD from controls and that are also predictive of this diagnosis.

The challenges of open data for future epidemic preparedness: The experience of the 2022 Ebolavirus outbreak in Uganda.

On 20 September 2022, the Ministry of Health in Uganda, together with the World Health Organization-Regional Office for Africa (WHO AFRO) confirmed an outbreak of EVD due to Sudan ebolavirus in Mubende District, after one fatal case was confirmed. Real-time information are needed to provide crucial information to understand transmissibility, risk of geographical spread, routes of transmission, risk factors of infection, and provide the basis for epidemiological modelling that can inform response and containment planning to reduce the burden of disease. We made an effort to build a centralized repository of the Ebola virus cases from verified sources, providing information on dates of symptom onset, locations (aggregated to the district level), and when available, the gender and status of hospitals, reporting bed capacity and isolation unit occupancy rate according to the severity status of the patient.

Authentic leadership and employee resilience during the COVID-19: The role of flow, organizational identification, and trust.

The present work investigated fundamental mediating mechanisms (i.e., flow experience, organizational identification, and trust), underlining the impact of authentic leadership on employee resilience during the turbulent COVID-19 pandemic.

Anxious Brains: A Combined Data Fusion Machine Learning Approach to Predict Trait Anxiety from Morphometric Features.

Trait anxiety relates to the steady propensity to experience and report negative emotions and thoughts such as fear and worries across different situations, along with a stable perception of the environment as characterized by threatening stimuli. Previous studies have tried to investigate neuroanatomical features related to anxiety mostly using univariate analyses and thus giving rise to contrasting results. The aim of this study is to build a predictive model of individual differences in trait anxiety from brain morphometric features, by taking advantage of a combined data fusion machine learning approach to allow generalization to new cases.