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The present work aimed to investigate the effect of film-forming solution pH on characteristics of chitosan (CH) - Piper betel L. leaf extract (PBe) coating films and their potential applications in mango preservation. The coating films were fabricated from CH-PBe solutions in the pH range of 3-5 using a solvent evaporation technique. The analysis results (DSC and FTIR) demonstrate higher miscibility, better compatibility, and tighter intermolecular interactions between CH and active compounds in the film matrix prepared at low pH. The mechanical and barrier properties of the CH-PBe film significantly decreased with increasing pH value. Varying the film-forming pH insignificantly affected the antioxidant activity and antibacterial inhibition against Staphylococcus aureus (Gram-positive) of the resultant films. However, Escherichia coli (Gram-negative) was less vulnerable to the blend film prepared at the higher pH medium. The coating solution at pH 4 proved suitable for preserving 'Tu Quy' mangoes, according to the observation of color changes, accumulated decay rate, respiration rate, ripening index, and other related factors. The findings of this work reveal the importance of pH control in producing CH-PBe coating films for mango preservation and provide more insights into pH-affected interactions between CH matrix and polyphenols in PBe., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Apathy is a behavioral symptom prevalent both in neuropsychiatric pathologies and in the healthy population. However, the knowledge of the cognitive and neural mechanisms underlying apathy is still very limited, even if clinical and fMRI data support the existence of three forms of apathy (executive, emotional, initiative). These forms could be explained by the alteration of specific mechanisms. This present study's aim is to specify the cognitive and neuronal mechanisms of executive and emotional apathy. We used an EEG study conducted on 68 subjects comprising two groups of young people with specific executive or emotional phenotypes of apathy and one group with no apathy. Despite having symptom of apathy, participants were free of any neurological, metabolic, or psychiatric diagnoses and with high education. Two tasks were used: the DPX for cognitive control and the MID for motivation. Our results showed that distinct mechanisms underlie these two forms of apathy, and, for the first time, we specified these mechanisms. A deficit of the proactive control mode, reflected by a reduced probe-N2 amplitude in AY trials, underlies the executive form of apathy (p < .03), whereas liking motivational blunting, highlighted by a reduced LPP amplitude for financial loss, characterizes the emotional form (p < .04). The main limit of the results is that generalizability to the general population may be reduced since the apathetic samples were chosen for having a specific form of apathy. To conclude, better knowledge of these mechanisms informs new, more targeted treatments, both pharmacological and non-pharmacological, necessary for reducing the debilitating consequences of apathy., Competing Interests: Declaration of competing interest The authors declare no competing interests to report., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Floods occur frequently in Romania and throughout the world and are one of the most devastating natural disasters that impact people's lives. Therefore, in order to reduce the potential damages, an accurate identification of surfaces susceptible to flood phenomena is mandatory. In this regard, the quantitative calculation of flood susceptibility has become a very popular practice in the scientific research. With the development of modern computerized methods such as geographic information system and machine learning models, and as a result of the possibility of combining them, the determination of areas susceptible to floods has become increasingly accurate, and the algorithms used are increasingly varied. Some of the most used and highly accurate machine learning algorithms are the decision tree models. Therefore, in the present study focusing on flood susceptibility zonation mapping in the Trotus River basin, the following algorithms were applied: forest by penalizing attribute-weights of evidence (forest-PA-WOE), best first decision tree-WOE, alternating decision tree-WOE, and logistic regression-WOE. The best performant, characterized by a maximum accuracy of 0.981, proved to be forest-PA-WOE, whereas in terms of flood exposure, an area of over 16.22% of the Trotus basin is exposed to high and very high floods susceptibility. The performances applied models in the present work are higher than the models applied in the previous studies in the same study area. Moreover, it should be noted that the accuracy of the models is similar with the accuracies of the decision tree models achieved in the studies focused on other areas across the world. Therefore, we can state that the models applied in the present research can be successfully used in by the researchers in other case studies. The findings of this research may substantially map the flood risk areas and further aid watershed managers in limiting and remediating flood damage in the data-scarce regions. Moreover, the results of this study can be a very useful for the hazard management and planning authorities., (© 2023 Society for Risk Analysis.)