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Abstract Background An intronic deletion within intron 2 of the DCDC2 gene encompassing the entire READ1 (hereafter, READ1d) has been associated in both children with developmental dyslexia (DD) and typical readers (TRs), with interindividual variation in reading performance and motion perception as well as with structural and functional brain alterations. Visual motion perception -- specifically processed by the magnocellular (M) stream -- has been reported to be a solid and reliable endophenotype of DD. Hence, we predicted that READ1d should affect neural activations in brain regions sensitive to M stream demands as reading proficiency changes. Methods We investigated neural activations during two M-eliciting fMRI visual tasks (full-field sinusoidal gratings controlled for spatial and temporal frequencies and luminance contrast, and sensitivity to motion coherence at 6%, 15% and 40% dot coherence levels) in four subject groups: children with DD with/without READ1d, and TRs with/without READ1d. Results At the Bonferroni-corrected level of significance, reading skills showed a significant effect in the right polar frontal cortex during the full-field sinusoidal gratings-M task. Regardless of the presence/absence of the READ1d, subjects with poor reading proficiency showed hyperactivation in this region of interest (ROI) compared to subjects with better reading scores. Moreover, a significant interaction was found between READ1d and reading performance in the left frontal opercular area 4 during the 15% coherent motion sensitivity task. Among subjects with poor reading performance, neural activation in this ROI during this specific task was higher for subjects without READ1d than for READ1d carriers. The difference vanished as reading skills increased. Conclusions Our findings showed a READ1d-moderated genetic vulnerability to alterations in neural activation in the ventral attentive and salient networks during the processing of relevant stimuli in subjects with poor reading proficiency.

Matteo Chiappedi,1 Alessio Toraldo,2 Silvia Mandrini,3 Federica Scarpina,2 Melissa Aquino,2 Francesca Giulia Magnani,2 Maurizio Bejor31Don Carlo Gnocchi ONLUS Foundation, Milan, Italy; 2University of Pavia, Department of Psychology, Pavia, Italy; 3University of Pavia, Department of Surgical, Resuscitative, Rehabilitative and Transplant Sciences, Pavia, ItalyIntroduction: Visual-motor skills are the basis for a great number of daily activities. To define a correct rehabilitation program for neurological patients who have impairment in these skills, there is a need for simple and cost-effective tools to determine which of the visual-motor system levels of organization are compromised by neurological lesions. In their 1995 book, The Visual Brain in Action (Oxford: Oxford University Press), AD Milner and MA Goodale proposed the existence of two pathways for the processing of visual information, the “ventral stream” and “dorsal stream,” that interact in movement planning and programming. Beginning with this model, our study aimed to validate a method to quantify the role of the ventral and dorsal streams in perceptual and visual-motor skills.Subjects and methods: Nineteen right-handed healthy subjects (mean age 22.8 years ± 3.18) with normal or corrected-to-normal vision were recruited. We proposed that a delayed pointing task, a distance reproduction task, and a delayed anti-pointing task could be used to assess the ventral stream, while the dorsal stream could be evaluated with a grasping task and an immediate pointing task. Performance was recorded and processed with the video-analysis software Dartfish ProSuite.Results: Results showed the expected pattern of predominance of attention for the superior left visual field, predominance of the flexor tone in proximal peri-personal space arm movements, tendency toward overestimation of short distances, and underestimation of long distances.Conclusion: We believe that our method is advantageous as it is simple and easily transported, but needs further testing in neurologically compromised patients.Keywords: dorsal stream, ventral stream, visual-motor skills, rehabilitation, neurological disorders

The present study investigates the adoption of predictive methods for road safety in the Italian context. The main goal of predictive methods is to describe safety performances of a road infrastructure according to the real number of occurred crashes and the actual infrastructure characteristics. Currently, the most reliable and widely used model is reported in the Highway Safety Manual (HSM), initially developed for the United States. In order to adapt the HSM existing model to the Italian context a calibration procedure is required. The main purpose of this study is to conduct the sensitivity analysis of the calibration factor, to evaluate the influence of various road characteristics (expressed in terms of Crash Modification Factors – CMFs) on the reliability of the model. Results show that the most influential factors are represented by planimetric curve radius, followed by shoulder type and width and Roadside Hazard Rating (RHR). In addition, the Italian roads taken into account for the present case study, which are single carriageway rural roads located in Emilia Romagna region, have generally exhibited more critical conditions compared to American roads. As a consequence, CMFs expressing the aforementioned infrastructure characteristics are typically greater than 1. Furthermore, road features and driving habits vary significantly with the orographic context (mountain, hill, or valley) and geographical area, factors that cannot be neglected when calibrating predictive models. As a result, a layered calibration would bring to the most reliable solution and, in specific situations, alternative predictive models to HSM could be developed.

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.

The adhesive properties of tack coats between asphalt pavement layers are crucial for the pavement’s structural behavior. This study first involved numerical analyses to compare stress patterns, deformations, and displacements in the pavement structure under various geometric and mechanical conditions. A rational calculation method based on the theory of elastic multilayer systems was used to quantify the impact of layer properties such as thickness, stiffness modulus, and Poisson’s ratio on interlayer bonding. Three bonding conditions—Full Friction, Partial Bonding, and Full Debonding—were analyzed to understand the tack coat’s effect between the top two layers. The second phase involved characterizing the mechanical behavior of the interface through shear strength tests (Leutner shear test) on both laboratory-prepared specimens and samples from a 10-year-old highway. Specimens were prepared using a Roller Compactor and tested under different interface conditions: hot-on-hot (H/H), residual bitumen 200 g/m2 (RB 200), and residual bitumen 400 g/m2 (RB 400). The tests examined the bonding effects in terms of tangential force and shear displacement at failure, as well as the impact of vehicular traffic on rutting and fatigue failure. Finally, this study investigated the long-term aging effects of the binder on interlayer bonding and sought to correlate the results of numerical calculations with those of the laboratory tests.

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.

A deficit in short-term memory (STM) functions characterizes many neurodevelopmental disorders, in particular, specific learning disorders. Hence, there is a need to develop a web-based platform capable of testing specific variables and administration conditions in a controlled manner. The platform herein presented allows for the assessment of short-term memory (STM) items and order components in a series of different conditions. Stimulus types, presentation, and response modalities were appropriately selected to assess the impact of those variables on memory performances. The usefulness of such a systematic, fine-grained analysis of STM functions was tested by applying the complete assessment in a group of 100 school-age children (47 Typically Developing children and 53 children with learning disorders) and evaluating the capacity of the software to highlight different specific memory processes activated during reading, writing, and calculation. A cluster analysis was applied to the learning performances of the whole group, and a four-cluster solution representing the best division into subgroups of learning disorders (affecting reading, writing, and mathematical skills, variously combined) also showed clear-cut differences in the children’s STM profiles. This confirms the potential and the usefulness of the tool for the characterization of STM in school-age children.

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.

This paper focuses on the gut-lung axis in the context of Inflammatory Bowel Disease (IBD) and Chronic Obstructive Pulmonary Disease (COPD), highlighting the key role played by microbial dysbiosis and the impact of environmental and genetic factors on the innate and acquired immune system and on chronic inflammation in the intestinal and pulmonary tracts. Recent evidence indicates that Antigen-Presenting Cells (APCs) perform regulatory activity influencing the composition of the microbiota. APCs (macrophages, dendritic cells, B cells) possess membrane receptors known as Pattern Recognition Receptors (PRRs), a category of toll-like receptors (TLRs). PRRs recognise distinct microbial structures and microbial metabolites called Signals, which modulate the saprophytic microbial equilibrium of the healthy microbiota by recognising molecular profiles associated with commensal microbes (Microbe-Associated Molecular Patterns, MAMPs). During dysbiosis, pathogenic bacteria can prompt an inflammatory response, producing PAMPs (Pathogen-Associated Molecular Patterns) thereby activating the proliferation of inflammatory response cells, both local and systemic. This series of regulatory and immune-response events is responsible (together with chronic infection, incorrect diet, obesity, etc.) for the systemic chronic inflammation (SCI) known as 'low-grade inflammation' typical of COPD and IBD. This review looks at immunological research and explores the role of the microbiota, looking at two recent clinical studies, SPIROMICS and AERIS. There is a need for further clinical studies to characterize the pulmonary microbiota and to obtain new information about the pathogenesis of lung disease to improve our knowledge and treatment strategies and identify new therapeutic targets., Author(s): Francesco De Nuccio [sup.1], Prisco Piscitelli [sup.2], Domenico Maurizio Toraldo [sup.3] Author Affiliations: (1) grid.9906.6, 0000 0001 2289 7785, Laboratory Human Anatomy, Department of Biological and Environmental Sciences and [...]

The use of Electric Vehicles (EV) seems to be a promising solution to achieve a sustainable road transport system. Among the contactless dynamic vehicle charging technologies, the use of Charging Units (CUs)—cement concrete box—embedded into the road pavement seems to be a favorable option. The available scientific papers related to the structural effects of embedding CUs in road pavements consider the CU as a solid box, even if a cavity is needed for the electrical technologies’ accommodation. This is why the current research is aimed at studying electrified roads (e-road) with different CU cavity shapes and dimensions. In detail, pavement structural responses are investigated, as a first step, adopting a Finite Element Model (FEM), and, as a second step, the long-term performances (fatigue cracking/rutting proneness) are evaluated. The study is divided into two phases: the theoretical fatigue/rutting assessment, which allows to calculate the critical load repetitions leading to pavement failure, and an urban case study with the goals of both assessing the theoretical results and computing fatigue/rutting performance with real scale traffic conditions. The outcomes demonstrate that CUs can be used with no significant impacts on the long-term road pavement structural performance, laying the foundation for a future upgrading of the existing urban road networks.

Objective: Aberrant activity of androgen receptor (AR) is the primary cause underlying development and progression of prostate cancer (PCa) and castration-resistant PCa (CRPC). Androgen signaling regulates gene transcription and lipid metabolism, facilitating tumor growth and therapy resistance in early and advanced PCa. Although direct AR signaling inhibitors exist, AR expression and function can also be epigenetically regulated. Specifically, lysine (K)-specific demethylases (KDMs), which are often overexpressed in PCa and CRPC phenotypes, regulate the AR transcriptional program. Methods: We investigated LSD1/UTX inhibition, two KDMs, in PCa and CRPC using a multi-omics approach. We first performed a mitochondrial stress test to evaluate respiratory capacity after treatment with MC3324, a dual KDM-inhibitor, and then carried out lipidomic, proteomic, and metabolic analyses. We also investigated mechanical cellular properties with acoustic force spectroscopy. Results: MC3324 induced a global increase in H3K4me2 and H3K27me3 accompanied by significant growth arrest and apoptosis in androgen-responsive and -unresponsive PCa systems. LSD1/UTX inhibition downregulated AR at both transcriptional and non-transcriptional level, showing cancer selectivity, indicating its potential use in resistance to androgen deprivation therapy. Since MC3324 impaired metabolic activity, by modifying the protein and lipid content in PCa and CRPC cell lines. Epigenetic inhibition of LSD1/UTX disrupted mitochondrial ATP production and mediated lipid plasticity, which affected the phosphocholine class, an important structural element for the cell membrane in PCa and CRPC associated with changes in physical and mechanical properties of cancer cells. Conclusions: Our data suggest a network in which epigenetics, hormone signaling, metabolite availability, lipid content, and mechano-metabolic process are closely related. This network may be able to identify additional hotspots for pharmacological intervention and underscores the key role of KDM-mediated epigenetic modulation in PCa and CRPC.

A runway pavement during its useful life is subject to a series of deteriorations because of repeated load cycles and environmental conditions. One of the most common deteriorations is the formation of rutting (surface depression in the wheel path) on the runway surface. Rutting negatively affects aircraft performance during landings and will behave even worse during precipitation or with the existence of fluid contaminations on the surface. This paper aims to develop a model for calculating aircraft braking distance during landing on wet-pavement runways affected by rutting based on dynamic skid resistances generated by tire–fluid–pavement interactions. Intense precipitation, variable rutting depths for a 100 m length step, water film depths (e.g., 1 to 26 mm), and aircraft wheel loads (e.g., 10 to 140 kN) are considered as the boundary conditions of the developed model. The output is a model that can estimate aircraft braking distance as a function of rutting depth and can perform further assessment of the probability of the occurrence of landing overrun. After validating the model with existing methodologies and calibrating it according to the actual landing distance required for each type of aircraft, an Italian airport is simulated using a model with real data regarding the level of service of its pavement surface characteristics.

Background: There is a lack of data regarding patients aged 90 years or older undergoing mechanical thrombectomy and their predictors of futile recanalization. Aims: We sought to evaluate the predictors of futile recanalization in patients ≥ 90 years with large vessel occlusion undergoing mechanical thrombectomy. Methods: This multi-center observational retrospective study included patients ≥ 90 years consecutively treated with mechanical thrombectomy in four thrombectomy capable centers between January 1st, 2016 and 30th March 2023. Futile recanalization was defined as large vessel occlusion patients experiencing a 90-day poor outcome (mRS 3–6) despite successful recanalization (mTICI ≥ 2b) after mechanical thrombectomy. Results: Our cohort included 139 patients ≥ 90 years with acute ischemic stroke due to anterior circulation large vessel occlusion treated with mechanical thrombectomy. One hundred seventeen of one hundred thirty-nine patients ≥ 90 years who achieved successful recanalization were included in the analysis (seventy-six female (64.9%)), of whom thirty-one (26.49%) experienced effective recanalization and eighty-six (73.51%) experienced futile recanalization. Patients with futile recanalization had higher NIHSS on admission (p < 0.001); they were less frequently treated with intravenous thrombolysis (p = 0.048), had more often general anesthesia (p = 0.011), and longer door to groin puncture delay (p = 0.002). Univariable regression analysis showed that use of intravenous thrombolysis (0.29, 95% CI 0.02–0.79, p = 0.034) and site of occlusion distal vs proximal (0.34, 95% CI 0.11–0.97, p = 0.044) were associated with reduced probability of futile recanalization while NIHSS on admission (1.29, 95% CI 1.16–1.45, p < 0.001), NIHSS at 24 h (1.15, 95% CI 1.07–1.25, p = 0.002), type of anesthesia used (4.18, 95% CI 1.57–11.08, p = 0.004), and door to groin puncture time (1.02, 95% CI 1.00–1.05, p = 0.005) were associated with increased probability of futile recanalization. Multivariable regression analysis showed that use of intravenous thrombolysis (0.44, 95% CI 0.09–0.88, p = 0.039) was associated with reduced probability of futile recanalization. Conclusion: Our study seems to suggest that mechanical thrombectomy with intravenous thrombolysis is associated with reduced probability of futile recanalization in a multi-center cohort of patients aged 90 years or older. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The adhesive properties of tack coats between asphalt pavement layers are crucial for the pavement's structural behavior. This study first involved numerical analyses to compare stress patterns, deformations, and displacements in the pavement structure under various geometric and mechanical conditions. A rational calculation method based on the theory of elastic multilayer systems was used to quantify the impact of layer properties such as thickness, stiffness modulus, and Poisson's ratio on interlayer bonding. Three bonding conditions—Full Friction, Partial Bonding, and Full Debonding—were analyzed to understand the tack coat's effect between the top two layers. The second phase involved characterizing the mechanical behavior of the interface through shear strength tests (Leutner shear test) on both laboratory-prepared specimens and samples from a 10-year-old highway. Specimens were prepared using a Roller Compactor and tested under different interface conditions: hot-on-hot (H/H), residual bitumen 200 g/m2 (RB 200), and residual bitumen 400 g/m2 (RB 400). The tests examined the bonding effects in terms of tangential force and shear displacement at failure, as well as the impact of vehicular traffic on rutting and fatigue failure. Finally, this study investigated the long-term aging effects of the binder on interlayer bonding and sought to correlate the results of numerical calculations with those of the laboratory tests. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Fractional calculus expands the idea of differentiation to fractional/non‐integer orders of the derivatives. It includes the memory‐dependent and non‐local system's behaviors while fractal–fractional derivatives is the generalization of fractional‐order derivatives which refers to a combination of fractional calculus and fractal geometry. In this article, we have considered the magnetohydrodynamic (MHD) flow of Casson hybrid nanofluid through a vertical open channel with the effect of viscous dissipation and Newtonian heating. The problem is modeled in terms of non‐linear and coupled integer‐order PDEs which is further generalized through fractal–fractional derivative of power law kernel. Due to non‐linearity and complexities, we have adopted the numerical procedure as it is used when the analytical solutions of PDEs are frequently difficult or impossible for complicated situations. We have established the numerical algorithms for both the classical and fractal–fractional‐order model and compared the results. The existence and uniqueness of the model's solution has been shown theoretically. The effect of various embedded parameters on the heat transfer and fluid flow has been simulated and presented through various figures while skin friction and Nusselt number are tabulated. The effect of fractional and fractal parameter is also shown. As the present model is taken for the hybrid nanofluid flow and for the heat transfer applications, we have considered mineral transformer oil as a base fluid while titania and cadmium telluride nanoparticles are dispersed in it. From the results, it is observed that hybrid nanofluid have a better heat transfer enhancement up to 19.71% while the unitary nanofluids are only capable to enhance the heat transfer up to 9%. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We propose a novel steplength selection rule in proximal gradient methods for minimizing the sum of a differentiable function plus an $ \def\bigtimes{{\Huge \times}} \def\operatornamewithlimits#1{\mathop{\rm #1}\limits} \ell _1 $ ℓ 1 -norm penalty term. The proposed rule modifies one of the classical Barzilai–Borwein steplength, extending analogous results obtained in the context of gradient projection methods for constrained optimization. We analyse the spectral properties of the Barzilai–Borwein-like steplength when the differentiable part is quadratic, showing that its reciprocal lies in the spectrum of the submatrix of the Hessian that depends on both the nonzero and the nonoptimal zero components of the current iterate, allowing for acceleration effects when the optimal zero components start to be identified. Furthermore, we insert the modified rule into a proximal gradient method with a nonmonotone line search, for which we prove global convergence towards a stationary point. Numerical experiments show the ability of the proposed rule to sweep the spectrum of the reduced Hessian on a series of quadratic $ \ell _1 $ ℓ 1 -regularized problems, as well as its effectiveness in recovering the ground truth in a least squares regularized problem arising in image restoration. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea (OSA) syndrome is a condition characterized by the presence of repeated complete or partial collapse of the upper airways during sleep associated with episodes of intermittent hypoxia, leading to fragmentation of sleep, sympathetic nervous system activation, and oxidative stress. To date, one of the major aims of research is to find out a simplified non-invasive screening system for this still underdiagnosed disease. The Berlin questionnaire (BQ) is the most widely used questionnaire for OSA and is a beneficial screening tool devised to select subjects with a high likelihood of having OSA. We administered the original ten-question Berlin questionnaire, enriched with a set of questions purposely prepared by our team and completing the socio-demographic, clinical, and anamnestic picture, to a sample of Italian professional nurses in order to investigate the possible impact of OSA disease on healthcare systems. According to the Berlin questionnaire, respondents were categorized as high-risk and low-risk of having OSA. For both risk groups, baseline characteristics, work information, clinical factors, and symptoms were assessed. Anthropometric data, work information, health status, and symptoms were significantly different between OSA high-risk and low-risk groups. Through supervised feature selection and Machine Learning, we also reduced the original BQ to a very limited set of items which seem capable of reproducing the outcome of the full BQ: this reduced group of questions may be useful to determine the risk of sleep apnea in screening cases where questionnaire compilation time must be kept as short as possible.

Developmental dyslexia can be viewed as the result of the effects of single deficits or multiple deficits. This study presents a test of the applicability of a multifactor-interactive model (MFi-M) with a preliminary set of five variables corresponding to different neuropsychological functions involved in the reading process. The model has been tested on a sample of 55 school-age children with developmental dyslexia. The results show that the data fit a model in which each variable contributes to the reading ability in a non-additive but rather interactive way. These findings constitute a preliminary validation of the plausibility of the MFi-M, and encourage further research to add relevant factors and specify their relative weights. It is further discussed how subtype-based intervention approaches can be a suitable and advantageous framework for clinical intervention in a MFi-M perspective.

There is strong evidence that homocysteine is a risk factor not only for cerebrovascular diseases but also for degenerative dementias. A recent consensus statement renewed the importance and the role of high levels of homocysteine in cognitive decline in several forms of degenerative dementia, such as Alzheimer’s disease. Although the molecular mechanisms by which homocysteine causes cell dysfunction are known, both the impact of homocysteine on specific cognitive functions and the relationship between homocysteine level and non-Alzheimer dementias have been poorly investigated. Most of the studies addressing the impact of hyperhomocysteinemia on dementias have not examined the profile of performance across different cognitive domains, and have only relied on screening tests, which provide a very general and coarse-grained picture of the cognitive status of the patients. Yet, trying to understand whether hyperhomocysteinemia is associated with the impairment of specific cognitive functions would be crucial, as it would be, in parallel, learning whether some brain circuits are particularly susceptible to the damage caused by hyperhomocysteinemia. These steps would allow one to (i) understand the actual role of homocysteine in the pathogenesis of cognitive decline and (ii) improve the diagnostic accuracy, differential diagnosis and prognostic implications. This review is aimed at exploring and revising the state of the art of these two strictly related domains. Suggestions for future research are provided.

Objective: The COVID‐19 pandemic had a profound negative impact on the psychological wellbeing of healthcare providers (HPs), but little is known about the factors that positively predict mental health of primary care staff during these dire situations. Methods: We conducted an online questionnaire survey among 702 emergency department workers across 10 hospitals in Switzerland and Belgium following the first COVID‐19 wave in 2020, to explore their psychological vulnerability, perceived concerns, self‐reported impact and level of pandemic workplace preparedness. Participants included physicians, nurses, psychologists and nondirect care employees (administrative staff). We tested for predictors of psychological vulnerability through both an exploratory cross‐correlation with rigorous correction for multiple comparisons and model‐based path modelling. Results: Findings showed that the self‐reported impact of COVID‐19 at work, concerns about contracting COVID‐19 at work, and a lack of personal protective equipment were strong positive predictors of Depression, Anxiety, and Stress, and low Resilience. Instead, knowledge of the degree of preparedness of the hospital/department, especially in the presence of a predetermined contingency plan for an epidemic and training sessions about protective measures, showed the opposite effect, and were associated with lower psychological vulnerability. All effects were confirmed after accounting for confounding factors related to gender, age, geographical location and the role played by HPs in the hospital/department. Conclusions: Difficult working conditions during the pandemic had a major impact on the psychological wellbeing of emergency department HPs, but this effect might have been lessened if they had been informed about adequate measures for minimizing the risk of exposure. [ABSTRACT FROM AUTHOR]