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Abstract Examining a large number of specific college majors and their association with mental health literacy (MHL) is an important step towards identifying at-risk groups at the college level. Though prior research has investigated MHL across student demographics such as gender, age, ethnicity, and level of education, the present study was the first to compare the MHL of undergraduate students across 19 different college majors. A total of 617 demographically and ethnically diverse undergraduate students (62.1% female; 69.3% non-white; mean age = 22.2 years; mean year in college = 2.8) reported their demographics, college experience, and college major, and completed an MHL measure that assessed knowledge of more than 20 psychological disorders and the application of that knowledge to real life scenarios. After controlling for gender, data were analyzed using ANOVA and post hoc comparisons to determine if differences in mental health literacy level were related to specific college majors. Results revealed that mental health literacy significantly differed across majors, F(18, 598) = 5.09, p

Abstract Background Surfactant is a well-established therapy for preterm neonates affected by respiratory distress syndrome (RDS). The goals of different methods of surfactant administration are to reduce the duration of mechanical ventilation and the severity of bronchopulmonary dysplasia (BPD); however, the optimal administration method remains unknown. This study compares the effectiveness of the INtubate-RECruit-SURfactant-Extubate (IN-REC-SUR-E) technique with the less-invasive surfactant administration (LISA) technique, in increasing BPD-free survival of preterm infants. This is an international unblinded multicenter randomized controlled study in which preterm infants will be randomized into two groups to receive IN-REC-SUR-E or LISA surfactant administration. Methods In this study, 382 infants born at 24+0–27+6 weeks’ gestation, not intubated in the delivery room and failing nasal continuous positive airway pressure (nCPAP) or nasal intermittent positive pressure ventilation (NIPPV) during the first 24 h of life, will be randomized 1:1 to receive IN-REC-SUR-E or LISA surfactant administration. The primary outcome is a composite outcome of death or BPD at 36 weeks’ postmenstrual age. The secondary outcomes are BPD at 36 weeks’ postmenstrual age; death; pulse oximetry/fraction of inspired oxygen; severe intraventricular hemorrhage; pneumothorax; duration of respiratory support and oxygen therapy; pulmonary hemorrhage; patent ductus arteriosus undergoing treatment; percentage of infants receiving more doses of surfactant; periventricular leukomalacia, severe retinopathy of prematurity, necrotizing enterocolitis, sepsis; total in-hospital stay; systemic postnatal steroids; neurodevelopmental outcomes; and respiratory function testing at 24 months of age. Randomization will be centrally provided using both stratification and permuted blocks with random block sizes and block order. Stratification factors will include center and gestational age (24+0 to 25+6 weeks or 26+0 to 27+6 weeks). Analyses will be conducted in both intention-to-treat and per-protocol populations, utilizing a log-binomial regression model that corrects for stratification factors to estimate the adjusted relative risk (RR). Discussion This trial is designed to provide robust data on the best method of surfactant administration in spontaneously breathing preterm infants born at 24+0–27+6 weeks’ gestation affected by RDS and failing nCPAP or NIPPV during the first 24 h of life, comparing IN-REC-SUR-E to LISA technique, in increasing BPD-free survival at 36 weeks’ postmenstrual age of life. Trial registration ClinicalTrials.gov NCT05711966. Registered on February 3, 2023.

In the current study, we introduced a unique method for identifying and segmenting oral squamous cell carcinoma (OSCC) nuclei, concentrating on those predicted to have significant CAF-1/p60 protein expression. Our suggested model uses the StarDist architecture, a deep-learning framework designed for biomedical image segmentation tasks. The training dataset comprises painstakingly annotated masks created from tissue sections previously stained with hematoxylin and eosin (H&E) and then restained with immunohistochemistry (IHC) for p60 protein. Our algorithm uses subtle morphological and colorimetric H&E cellular characteristics to predict CAF-1/p60 IHC expression in OSCC nuclei. The StarDist-based architecture performs exceptionally well in localizing and segmenting H&E nuclei, previously identified by IHC-based ground truth. In summary, our innovative approach harnesses deep learning and multimodal information to advance the automated analysis of OSCC nuclei exhibiting specific protein expression patterns. This methodology holds promise for expediting accurate pathological assessment and gaining deeper insights into the role of CAF-1/p60 protein within the context of oral cancer progression.

The increase in the penetration of inverter based renewable energy resources comes with several challenges. For one, the power quality can be cited as an issue due to the impact of the electronic devices in the grid voltage profile, which can cause harmonic disturbances and then affect all other installations nearby. Considering the issue previously described,} this paper analyzes the effects of grid voltage harmonic disturbances in the operation of a grid-connected Voltage Source Converter (VSC) with current control in the stationary reference frame. A mathematical model is derived and validated both through simulations and experiments in order to associate the voltage harmonic magnitude disturbance with the respective current harmonic magnitude response from the grid-connected VSC. The model is also utilized to tune paralleled resonant controllers to mitigate the effect. Furthermore, the results and analyses highlight not only the effectiveness but also the limitations from the proposal.

The Stochastic Shortest Path (SSP) is a formalism widely used for modeling goal-oriented probabilistic planning problems. When dead ends, which are states from which goal states cannot be reached, are present in the problem and cannot be avoided, the standard criterion for solving SSPs is not well defined in these scenarios. Because of that, several alternate criteria for solving SSPs with unavoidable dead ends have been proposed in the literature. One of these criteria is GUBS (Goals with Utility-Based Semantics), a criterion that makes trade-offs between probability-to-goal and cost by combining goal prioritization with Expected Utility Theory. GUBS is a good choice for these problems because it is one of the only criteria that are known to maintain the ?-strong probability-to-goal priority property, a property that provides guarantees on how a decision criterion can choose policies without having to preprocess any specific SSP problem. Although there already exist two exact algorithms for solving GUBS, eGUBS-VI and eGUBS-AO*, both are offline and there is no algorithm for solving GUBS in an online manner. In this paper we propose UCT-GUBS, an online approximate algorithm based on UCT (a Monte Carlo tree search algorithm) that solves SSPs under the GUBS criterion. We provide an analysis of an empirical evaluation performed on two probabilistic planning domains (Triangle Tireworld and Navigation) to observe how the probability-to-goal and utility values of the resulting policies compare to the optimal values, and also how the time performance of UCT-GUBS compares to the ones of eGUBS-VI and eGUBS-AO*. Our conclusion is that, like other algorithms, the usage of UCT-GUBS has to be evaluated considering the application requirements and of the problem being solved. Depending on these factors, it can be a good alternative for obtaining policies in an online fashion while, for some problems, also being able to have better time performance than other algorithms

Abstract Using Amazonian fruits to flavor kombuchas is a promising proposal, as it adds nutritional value to the drink. This work sought to develop kombucha flavored with Amazonian fruits and evaluate the bioactive compounds and antioxidant capacity of the formulations. Three kombucha formulations were prepared using green tea (Camellia sinensis) and three Amazonian fruits: cupuassu (Theobroma grandiflorum), tapereba (Spondias lutea L.) and bacuri (Platonia insignis). Kombucha fermentations were evaluated before and after the insertion of nectars through the analysis of phenolic compounds, vitamin C and antioxidant capacity. Analyzes of pH, total sugars, acetic acid, ethanol, and microbiological characterization of final formulations were also carried out. For the first fermentation, were found values of phenolic compounds and antioxidant capacity of 30.60 ± 0.93 mg EAG/L and 295.02 ± 5.59 µmol ET/mL, and the formulation with tapereba showed the highest values for total phenolic compounds (34.92 ± 12.25 mg EAG/L), antioxidant capacity (320.57 ± 9.53 µmol ET/mL) and vitamin C (198.25 mg/100g). Thus, the formulations developed had a crucial nutritional appeal to stimulate consumption by the population, in addition to enabling the valorization and addition of commercial value to the Amazonian fruits used.

Abstract Background Crime scene investigation (CSI) in general means the standard procedures and techniques used for processing and reconstructing of scene of crime. In Palestine, the competent authorities delegated by law to carry out the task of research and investigation of crimes and inspection at the crime scene are the officers granted by law the status of the judicial police. CSIs face numerous challenges that affect every worker involved. These challenges arise from legal, administrative, security, and technical aspects. This study aimed to point out the challenges faced by field police personnel during CSI in Palestine. To achieve the aims of this study, a validated and reliable questionnaire was developed. The study sample consisted of 354 crime scene investigators and officers affiliated with the Palestinian Civil Police (PCP) across all governorates of the West Bank. Results In addition to the training of CSI officers, and shortage of equipment, the findings of this study indicate that there are many challenges amplified by the Israeli occupation facing PCP officers concerning crime scene management and technical procedures during CSIs such as the collection, transportation, and storage of forensic evidence. Overlapping responsibilities and difficulties in coordinating specialized agencies working at the crime scene are also factors that should be better studied. Conclusion This study invites decision-makers within the Palestinian police agencies to prioritize efforts to address the significant challenges encountered by workers at crime scenes. They should give special attention on enhancing training programs and providing the necessary tools and devices for effective crime scene work. It also recommends Palestinian representatives at international stage to highlight the obstacles facing workers at crime scenes due to the occupation.

Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, accounting for over 9 million deaths annually. The prevalence of CAD continues to rise, driven by ageing and the increasing prevalence of risk factors such as hypertension, diabetes, and obesity. Current clinical guidelines emphasize the importance of functional tests in the diagnostic pathway, particularly for assessing the presence and severity of ischemia. While recommended tests are valuable, they may not fully capture the complex physiological responses to exercise or provide the necessary detail to tailor personalized treatment plans. Cardiopulmonary exercise testing (CPET) offers a comprehensive assessment of the cardiovascular, pulmonary, and muscular systems under stress, potentially addressing these gaps and providing a more precise understanding of CAD, particularly in settings where traditional diagnostics may be insufficient. By enabling more personalized and precise treatment strategies, CPET could play a central role in the future of CAD management. This narrative review examines the current evidence supporting the use of CPET in CAD diagnosis and management and explores the potential for integrating CPET into existing clinical guidelines, considering its diagnostic and prognostic capabilities, cost-effectiveness, and the challenges associated with its adoption.

Electrocardiogram modifications in athletes are common and usually reflect structural and electrical heart adaptations to regular physical training, known as the athlete’s heart. However, these electrical modifications sometimes overlap with electrocardiogram findings that are characteristic of various heart diseases. A missed or incorrect diagnosis can significantly impact a young athlete’s life and potentially have fatal consequences during exercise, such as sudden cardiac death, which is the leading cause of death in athletes. Therefore, it is crucial to correctly distinguish between expected exercise-related electrocardiogram changes in an athlete and several electrocardiogram abnormalities that may indicate underlying heart disease. This review aims to serve as a practical guide for cardiologists and sports clinicians, helping to define normal and physiology-induced electrocardiogram findings from those borderlines or pathological, and indicating when further investigations are necessary. Therefore, the possible athlete’s electrocardiogram findings, including rhythm or myocardial adaptation, will be analyzed here, focusing mainly on the differentiation from pathological findings.

Milk and its derivatives are included in a balanced diet of humans as excellent sources of proteins, vitamins, and essential minerals that are functional nutrients. Knowledge about the nutritional benefits or harms due to milk consumption has been expanding in recent years. We previously explored, in rodent models, the metabolic effects of isoenergetic intake of milk derived from cows, donkeys, or humans, while the impact of goat’s milk intake has remained unexplored. The aim of this work was to investigate, in an animal model, the effects of dietary supplementation with goat’s milk on energy homeostasis and inflammatory state, focusing on the modulation of mitochondrial functions in most metabolically active organs, such as skeletal muscle and the liver. In addition, we highlighted a link between nutrient intake, substrate metabolism, and the orexinergic system. Our results indicate that goat milk improves mitochondrial oxidative capacity and reduces inflammation and oxidative stress in both organs. Notably, goat milk lowers the circulating levels of Orexin-A, a neuropeptide that plays a crucial role in regulating peripheral energy balance and central nervous system mechanisms. These data provide the first evidence that the anti-inflammatory and antioxidant effects of goat milk are mediated by the modulation of mitochondrial functions and orexinergic signaling.

In this paper, the effectiveness of reinforcements for flexible pavements is evaluated through an analysis of reflective cracking. Different stiffness and thickness reinforcements are considered for the rehabilitation of an already cracked pavement. The effect of the reinforcement is assessed from two different perspectives: (i) the ability to reduce stresses in the rehabilitated pavement layers, and (ii) the capacity to mitigate the crack propagation from deeper layers. A finite element model (FEM) is adopted to study the stress and strain state of the pavement layers. The pavement model has been properly validated, transitioning from a simply supported beam scheme to an elastic multilayer model. In addition, to represent crack propagation, fracture evolution is analyzed using Linear Elastic Fracture Mechanics (LEFMs) and Paris’ law. The effect of different reinforcements on the pavement is then simulated. The results show that the reinforcement performance is strictly dependent on the interlayer thickness and stiffness. In particular, high stiffness reinforcements (geomembranes) show increasing effectiveness with stiffness, both in terms of reflective cracking and stress reduction. Conversely, low stiffness reinforcements (SAMIs) show a variable trend with the stiffness modulus. In fact, extremely low stiffness is effective in slowing down crack propagation but is detrimental to the wearing course’s stress condition. However, as the stiffness increases, the likelihood of cracking in the wearing course decreases, though only a small beneficial effect is registered for crack propagation in the base layer.

This study aims to establish an effective approach for evaluating the safety performance of road infrastructure. Road safety levels are typically quantified using safety performance indicators. However, due to the stochastic nature of accidents, many safety performance indicators cannot adequately and completely describe reality. Therefore, predictive methods based on regression models are widely used. This approach also allows for the identification of latent risk conditions in the infrastructure, even in the absence of accidents. Among available approaches, the Highway Safety Manual (HSM) methodology is chosen for its synthesis of validated highway research and best practices for incorporating safety into both new design and rehabilitation. For this study, a preliminary new version of HSM is used. The application of this method, which combines a predictive model with observed accidents through an empirical Bayesian approach, requires a calibration process that is crucial to tailoring this method to the specific study context. In this research, the predictive model is calibrated for single carriageway roads with one lane per direction across the Italian national network. Following calibration, the safety indicators are evaluated. The results obtained according to different indicators are compared to show the importance of adopting this method to counteract the regression to the mean of observed crashes. In fact, the method, supported by empirical Bayesian analysis, enables the identification of high-risk sections of the road network, selecting more sections that would be neglected by traditional indicators based solely on observed crashes. Finally, a possible approach to prioritizing sites for inspection based both on the excess of crashes and the Safety Potential (SAPO) is proposed. In addition, SAPO is adjusted to local conditions to account for the specific context and the decreasing trend of accidents over the years.

Due to repeated load cycles and climate impacts, road pavement deteriorates. One of the primary causes of pavement degradation is the formation of rutting under the wheel path on the road surface. Rutting's impact on vehicle performance, especially on rainy days (since the rain would fill the rutting depression), leads to longer braking distances compared to dry conditions. This study developed a MATLAB-based model for calculating vehicle braking distance on wet asphalt pavement affected by rutting, using dynamic skid resistances generated through Back-Propagation Neural Network (BPNN) analysis. This study addresses the worst-case scenario in which rutting is filled with water, then calculates the required vehicle braking distance under various Water Film Thickness (WFT) conditions. The developed model can perform these evaluations for different operational conditions across various input ranges, such as precipitation intensity, number of lanes, lane width, cross slope, average texture depth, rutting depths, and accumulated WFT. As an outcome, the vehicle braking distance can be estimated as a function of Rutting Depth (RD) within a known vehicle speed interval. After validating the proposed model against existing approaches from the literature, several sensitivity analyses are conducted to assess the impact of influencing parameters on the results. Moreover, the study examines the relationship between AASHTO braking distance requirements and the RD threshold levels adopted by several highway agencies. Furthermore, this model is also applicable to real-world case studies, enabling the calculation of vehicle braking distances with varying RDs in the presence of various WFTs on the pavement surface.

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BackgroundThe 10-item Perceived Stress Scale is a widely used questionnaire for measuring perceived stress.AimThis study aimed to assess the psychometric properties of the Italian version of the 10-item Perceived Stress Scale in a sample of Italian teachers during the COVID-19 pandemic.MethodsA cross-sectional study was performed. A sample of 1,179 teachers of pre-primary, primary, and secondary schools anonymously completed an online questionnaire. A Confirmatory Factor Analysis was performed to compare the fit of a two-factor model against a one-factor solution of the scale. Multigroup CFA was run to test the measurement invariance of the two-factor PSS-10 solution across gender. The internal reliability of the scale was evaluated using Cronbach’s alpha and McDonald’ omega coefficients. Convergent validity with measures of subjective well-being and self-reported health was evaluated.ResultsThe results of the Confirmatory Factor Analysis showed that the two-factor structure of the 10-items Perceived Stress Scale provided a better fit to the data and supported the adequacy of the Italian version of the scale. The two-factor model showed measurement invariance across female and male groups, as result of the multigroup CFA. The scale proved to have good internal reliability. Correlation analyses with measures of the Positive Affect and Negative Affect Schedule and self-reported health supported convergent validity.ConclusionThese results suggest that the Italian version of the 10-item Perceived Stress Scale has good psychometric properties and can be considered a valid and reliable instrument to assess perceived stress.

The purpose of this study is to determine the safety effectiveness of an intervention on an existing road by using predictive methods. Predictive methods allow the benefit of the intervention to be quantified in terms of crash reduction. Currently, the most widely used model is reported in the Highway Safety Manual, developed in the US. The HSM model is adapted to the Italian context through a calibration procedure. The model is then applied to two future scenarios: in the absence and presence of intervention. The redesign intervention consists of rehabilitating some road sections and constructing five tunnel bypasses to avoid crossing residential areas. The comparison between the ‘with’ and ‘without’ scenario estimated an overall reduction in the number of accidents of around 45%. The variant scenario is based on reasonable assumptions that allowed the determination of the proportion of traffic that will be diverted to the variant. In addition, several alternative future scenarios are considered to assess a possible different trend in assumed traffic distribution. Moreover, a possible overall increase or reduction in total traffic affecting the road is taken into account. The results showed that the intervention provided significant benefits even with increased traffic, proving the resilience of the intervention.

In recent years, biomonitoring has gained more attention, particularly when assessing the environmental health of significant areas, such as those near waste-to-energy facilities. These requirements coincide with the chance to detect environmental pollutants using sensitive organisms. Bees were shown to be quite effective in evaluating the presence of certain compounds by analyzing their associated matrices, such as pollen, honey, or wax. In our study, we employed the honey bee (Apis mellifera) as an indicator to initially monitor the vicinity of the waste-to-energy plant in Acerra, which is situated in the Campania region of Italy. The primary aim was to determine whether the facility was accountable for any environmental releases of dioxins or dioxin-like compounds. Then, we assessed the presence of additional pollutants in the same area, including trace elements, polycyclic aromatic hydrocarbons, and pesticides, released by human activities. To obtain further information about environmental quality, a second biomonitoring station was installed near the Caivano S.T.I.R. (Waste Shredding, Sifting, and Packaging Plant). The results showed the dioxin levels did not exceed predetermined limitations at the Acerra site, thus demonstrating the efficacy of the waste-to-energy facility and the bees’ ability to detect the presence of other pollutants. Additionally, this biomonitoring system exhibited sensitivity to environmental variations, thereby enabling the evaluation of xenobiotic flux between two proximate zones and across temporal scales. This pioneering study suggests the advantages of utilizing bees to detect a wide range of contaminants, thereby providing valuable insights into environmental quality and potential health risks for both ecosystems and human populations.

The therapeutic management of atherosclerosis focuses almost exclusively on the reduction of plasma cholesterol levels. An important role in the genesis and evolution of atherosclerosis is played by chronic inflammation in promoting thrombosis phenomena after atheroma rupture. This review aims to take stock of the knowledge so far accumulated on the role of endemic HP infection in atherosclerosis. The studies produced so far have demonstrated a causal relationship between Helicobacter pylori (HP) and CVD. In a previous study, we demonstrated in HP-positive patients that thrombin and plasma fragment 1 + 2 production was proportionally related to tumor necrosis factor-alpha levels and that eradication of the infection resulted in a reduction of inflammation. At the end of our review, we can state that HP slightly affects the risk of CVD, particularly if the infection is associated with cytotoxic damage, and HP screening could have a clinically significant role in patients with a high risk of CVD. Considering the high prevalence of HP infection, an infection screening could be of great clinical utility in patients at high risk of CVD.

Joint visco-supplementation is an effective therapeutic approach against the degenerative signs and symptoms of osteoarthrosis/osteoarthritis of the mandibular condyle. Supplements of choice are usually delivered inside the temporomandibular joint (TMJ) by intra-articular infiltration. The present study aimed to assess the clinical effectiveness of pericapsular injection of polinucleotides (PN) and hyaluronic acid (HA). Sixty patients suffering from TMJ osteoarthrosis were recruited and divided into two groups (test group: n = 30, pericapsular injection; control group: n = 30, self-delivered physiotherapeutic exercises). For each patient, maximum opening, right and left lateral excursion, and visual analogue scale (VAS) scores were recorded at four different timepoints by a blinded investigator. Paired Student's t tests were used to compare consecutive measurements of the parameters evaluated within the groups, and unpaired Student's t tests were used for between-group comparisons. All investigated parameters displayed a progressive clinical improvement in both groups, which was more accentuated in the test group. The decrease in VAS score differed significantly between groups (p < 0.0001). Maximum opening showed a continuous increase from baseline (mean (SD) 37.70 (8.33) mm) to T3 (39.68 (7.64) mm), reflecting a progressive improvement, but it was not statistically significant (p = 0.089 at T3 with respect to T0). PN HA pericapsular injection is a minimally invasive treatment that effectively reduces pain and improves mandibular kinematics. [ABSTRACT FROM AUTHOR]

This paper describes the methodology underlying the matching between extra-EU counterparts in the Italian Customs and Monopolies Agency data with firms in the Bureau van Dijk Orbis database. Through different validation exercises, we show that the matches stemming from our proposed procedure are largely correct regarding both records and transaction values. The resulting corresponding tables can serve as a useful tool to shed light on the features of the counterparts of Italian firms active in international trade. [ABSTRACT FROM AUTHOR]