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Human Factors are stable psychological, psychophysical, and physiological limits that influence the performance and safety of technical systems managed by humans. Roads are made for human use, but nowadays not completely on a human scale. Many studies demonstrate that Human Factors are a key factor in accident occurrence and thus it is mandatory to consider them in the definition of design standards. This research provides a methodological approach to reviewing design standards based on Human Factors. The methodology identifies which Human Factors aspects are relevant for each specific design feature. The reviewer is then able to judge if those aspects are considered using checklists. Moreover, the paper presents a review of the Italian design standards using the proposed methodology. This identifies to what extent Human Factors are considered in the Italian design standards, analyzing if they match the requirements of the three rules of Human Factors proposed by PIARC (Permanent International Association of Road Congresses). The results identify where Italian design standards consider Human Factors and where they do not. This is where further improvements should be made so that engineering solutions could match psychological requirements, for safer and ergonomic road infrastructures. The proposed approach provides a structured and systematic procedure for the analysis which has been found to be suitable also for road safety audits procedures.

Chirality in inorganic nanostructures has recently stimulated the attention of many researchers, both to unravel fundamental questions on the origin of chirality in inorganic and hybrid materials, as well as to introduce novel promising properties that are originated by the symmetry breaking. MoS2 is one of the most investigated among the large family of layered transition metal dichalcogenides. In particular, the metastable metallic 1T−MoS2 phase is of large interest for potential applications. However, due to thermodynamic reasons, the synthesis of 1T−MoS2 phase is quite challenging. Herein, we present the first synthesis of chiral 1T−MoS2 phase which shows remarkably high chiroptical activity with a g‐factor up to 0.01. Chiral 1T−MoS2 was produced using tartaric acid as a chiral ligand to induce symmetry breaking during the material's growth under hydrothermal conditions, leading to the formation of distorted hierarchical nanosheet assemblies exhibiting chiral morphology. Thorough optimization of the synthetic conditions was carried out to maximize chiroptical activity, which is strongly related to the nanostructures' morphology. Finally, the formation mechanism of the chiral 1T−MoS2 nanosheet assemblies was investigated, focusing on the role of molecular intermediates in the growth of the nanosheets and the transfer of chirality. [ABSTRACT FROM AUTHOR]

The development of multimodal nano- and micro-structures has become an increasingly popular area of research in recent years. In particular, the combination of two or more desirable properties within a single structure opens multiple opportunities from biomedicine, sensing, and catalysis, to a variety of optical applications. Here, for the first time, we report the synthesis and characterization of multimodal chiroptically active CaCO3 nanocomposites. These composites have been prepared by a modified microemulsion method in the presence of an amino acid (cysteine). Following this, additional modalities have been introduced by loading the composites with luminescent nanoparticles or doping with Eu3+ ions. The luminescent composites have been produced by the incorporation of CuInZnS/ZnS or CdSe@ZnS/ZnS core/shell quantum dots, or via doping with trivalent europium. In this manner, we have produced chiroptically active composites with orange, green, and red luminescence. Overall, this work demonstrates the unique advantage and potential of our approach and new class of chiroptically active CaCO3 nanocomposites, which display tunable functionality to specific requirements via the incorporation of desired ions, nanoparticles, and chirality of the structure.

Piezoelectric materials are a class of compounds that is gaining increasing interest in various applications such as energy harvesting. During the last decade, lead-free ZnSnO3 perovskite ceramic has gained attention among the scientific community thanks to its unique symmetry-dependent and spontaneous polarization properties such as piezoelectricity and ferroelectricity. Nevertheless, only a few studies successfully prepared pure ZnSnO3, while most seem to mislead the product for its hydroxide precursor (ZnSn(OH)6) or a mixture of Zn2SnO4 and SnO2. In our work, we investigated the conversion of ZnSn(OH)6 at different temperatures (500, 600, 700, 750 and 800 °C) by X-ray powder diffraction analysis, and in-situ using synchrotron radiation up to 950 °C under ambient atmosphere and in a vacuum, to reproduce conventional reaction conditions. SEM and TEM have been used to understand the evolution of the particle shape and surface structure before and after the thermal treatments. Our results show the instability of the ZnSn(OH)6 phase, which converts into an amorphous structure at low temperature. Above 750 °C, the material segregates into Zn2SnO4 and SnO2, supporting the hypothesis that the thermal treatment of the hydroxide phase under typical conditions results in the formation of an oxide mixture rather than the phase pure ZnSnO3.

A significant percentage of road fatalities and injuries occur in the nonmotorway rural road network. One of the main causes of accidents on these roads is represented by overtaking, as, by its nature, it involves a risk of a head-on collision with oncoming traffic. The paper describes a combined simulation approach (driving simulator and traffic microsimulation) designed to examine the influence of different traffic conditions on passing manoeuvres on two-lane two-way rural roads. The main focus was the evaluation of the end of the passing manoeuvre because it reflects the risk of a head-on collision. In addition, the study aimed to assess the usefulness of the proposed combined approach in the ability to proactively and quickly diagnose traffic safety problems and consequently to evaluate appropriate solutions. The data collected with an interactive driving simulator on a sample of 54 participants have been used to adjust some input data of the traffic microsimulation software. A specific situation consisting of a stationary heavy vehicle obstructing the entire lane was repeated in both experiments. The analyses focused on time-to-collision (TTC), defined as the remaining gap between the passing vehicle and the oncoming vehicle at the end of the passing manoeuvre. The results showed that the type of manoeuvre performed is significantly influenced by the traffic condition. Furthermore, the manoeuvre is influenced by the gap between two successive vehicles in the opposite lanes. Focusing on the end of the manoeuvre, it was found how a traffic increase leads to a significant reduction of the TTC values. Furthermore, the comparative analysis conducted between the data recorded following the combined approach and those obtained using exclusively the input data of the microsimulation software supports the usefulness of the proposed methodology for conducting road safety analyses, especially in complex traffic environments where drivers’ behaviour plays a decisive role.

Reading a book, understanding the news reports or any other behaviour involving the processing of meaningful stimuli requires the semantic system to have two main features: being active during an extended period of time and flexibly adapting the internal representation according to the changing environment. Despite being key features of many everyday tasks, formation and updating of the semantic “gestalt” are still poorly understood. In this fMRI study we used naturalistic stimuli and task manipulations to identify the neural network that forms and updates conceptual gestalts during time-extended integration of meaningful stimuli. Univariate and multivariate techniques allowed us to draw a distinction between networks that are crucial for the formation of a semantic gestalt (meaning integration) and those that instead are important for linking incoming cues about the current context (e.g., time and space cues) into a schema representation. Specifically, we revealed that time-extended formation of the conceptual gestalt was reflected in the neuro-computations of the anterior temporal lobe accompanied by multi-demand areas and hippocampus, with a key role of brain structures in the right hemisphere. This “semantic gestalt network” was strongly recruited when an update of the current semantic representation was required during narrative processing. A distinct fronto-parietal network, instead, was recruited for context integration, independently from the meaning associations between words (semantic coherence). Finally, in contrast with accounts positing that the default mode network (DMN) may have a crucial role in semantic cognition, our findings revealed that DMN activity was sensitive to task difficulty, but not to semantic integration. The implications of these findings for neurocognitive models of semantic cognition and the literature on narrative processing are discussed.

Every year in Italy, there are about 20,000 road accidents involving pedestrians, with a significant number of injuries and deaths. Out of these, about 30% occur at pedestrian crossings, where pedestrians should be protected the most. Here, we propose a new accident prediction model to improve pedestrian safety assessments that allows us to accurately identify the sites with the largest potential safety improvements and define the best treatments to be applied. The accident prediction model was developed using the ISTAT dataset, including information about the fatal and injurious crashes that occurred in Italy in a 5-year period. The model allowed us to estimate the risk level of a road section through a machine-learning approach. Gradient Boosting seems to be an appropriate tool to fit classification models for its flexibility that allows us to capture non-linear relationships that would be difficult to detect via a classical approach. The results show the ability of the model to perform an accurate analysis of the sites included in the dataset. The locations analyzed have been classified based on the potential risk in the following three classes: High, medium, and low. The proposed model represents a solid and reliable tool for practitioners to perform accident analysis with pedestrian involvement.

The development of multimodal nano- and micro-structures has become an increasingly popular area of research in recent years. In particular, the combination of two or more desirable properties within a single structure opens multiple opportunities from biomedicine, sensing, and catalysis, to a variety of optical applications. Here, for the first time, we report the synthesis and characterization of multimodal chiroptically active CaCO3 nanocomposites. These composites have been prepared by a modified microemulsion method in the presence of an amino acid (cysteine). Following this, additional modalities have been introduced by loading the composites with luminescent nanoparticles or doping with Eu3+ ions. The luminescent composites have been produced by the incorporation of CuInZnS/ZnS or CdSe@ZnS/ZnS core/shell quantum dots, or via doping with trivalent europium. In this manner, we have produced chiroptically active composites with orange, green, and red luminescence. Overall, this work demonstrates the unique advantage and potential of our approach and new class of chiroptically active CaCO3 nanocomposites, which display tunable functionality to specific requirements via the incorporation of desired ions, nanoparticles, and chirality of the structure. [ABSTRACT FROM AUTHOR]

A significant percentage of road fatalities and injuries occur in the nonmotorway rural road network. One of the main causes of accidents on these roads is represented by overtaking, as, by its nature, it involves a risk of a head-on collision with oncoming traffic. The paper describes a combined simulation approach (driving simulator and traffic microsimulation) designed to examine the influence of different traffic conditions on passing manoeuvres on two-lane two-way rural roads. The main focus was the evaluation of the end of the passing manoeuvre because it reflects the risk of a head-on collision. In addition, the study aimed to assess the usefulness of the proposed combined approach in the ability to proactively and quickly diagnose traffic safety problems and consequently to evaluate appropriate solutions. The data collected with an interactive driving simulator on a sample of 54 participants have been used to adjust some input data of the traffic microsimulation software. A specific situation consisting of a stationary heavy vehicle obstructing the entire lane was repeated in both experiments. The analyses focused on time-to-collision (TTC), defined as the remaining gap between the passing vehicle and the oncoming vehicle at the end of the passing manoeuvre. The results showed that the type of manoeuvre performed is significantly influenced by the traffic condition. Furthermore, the manoeuvre is influenced by the gap between two successive vehicles in the opposite lanes. Focusing on the end of the manoeuvre, it was found how a traffic increase leads to a significant reduction of the TTC values. Furthermore, the comparative analysis conducted between the data recorded following the combined approach and those obtained using exclusively the input data of the microsimulation software supports the usefulness of the proposed methodology for conducting road safety analyses, especially in complex traffic environments where drivers' behaviour plays a decisive role., Author(s): Valentina Branzi [1]; Monica Meocci (corresponding author) [1]; Lorenzo Domenichini [1]; Margherita Calcinai [2] 1. Introduction Most road accidents worldwide occur on rural roads. They are associated with the [...]