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05 and 0.01) on all plant variables and nearly all indices. Almost all indices within each SRI type performed favorably in estimating the plant variables under both salinity levels (6.0 and 12.0 dS m-1) and for the salt-sensitive genotype Sakha 61. The most effective indices extracted from each SRI type by SMLR explained 60%-81% of the total variability in four plant variables. The various predictive models provided a more accurate estimation of Chla and Chlt content than of SDW and Chlb under both salinity levels. They also provided a more accurate estimation of SDW than of Chl content for salt-tolerant genotype Sakha 93, exhibited strong performance for predicting the four variables for Sakha 61, and failed to predict any variables under control and Chlb for Sakha 93. The overall results indicate that the simple form of indices can be used in practice to remotely assess the growth and chlorophyll content of distinct wheat genotypes under saline field conditions.Geosynthetics are extensively utilized to improve the stability of geotechnical structures and slopes in urban areas. Among all existing geosynthetics, geotextiles are widely used to reinforce unstable slopes due to their capabilities in facilitating reinforcement and drainage. To reduce settlement and increase the bearing capacity and slope stability, the classical use of geotextiles in embankments has been suggested. However, several catastrophic events have been reported, including failures in slopes in the absence of geotextiles. Many researchers have studied the stability of geotextile-reinforced slopes (GRSs) by employing different methods (analytical models, numerical simulation, etc.). The presence of source-to-source uncertainty in the gathered data increases the complexity of evaluating the failure risk in GRSs since the uncertainty varies among them. Consequently, developing a sound methodology is necessary to alleviate the risk complexity. Our study sought to develop an advanced risk-based maintenance (RBM) methodology for prioritizing maintenance operations by addressing fluctuations that accompany event data. For this purpose, a hierarchical Bayesian approach (HBA) was applied to estimate the failure probabilities of GRSs. Using Markov chain Monte Carlo simulations of likelihood function and prior distribution, the HBA can incorporate the aforementioned uncertainties. The proposed method can be exploited by urban designers, asset managers, and policymakers to predict the mean time to failures, thus directly avoiding unnecessary maintenance and safety consequences. To demonstrate the application of the proposed methodology, the performance of nine reinforced slopes was considered. The results indicate that the average failure probability of the system in an hour is 2.8×10-5 during its lifespan, which shows that the proposed evaluation method is more realistic than the traditional methods.Lithium cobalt oxide (LiCoO2), which has been successfully applied in commercial lithium-ion batteries for portable devices, possesses a theoretical specific capacity of 274 mAh g-1. However, its actual capacity is only half of the theoretical specific capacity, because the charging voltage is restricted below 4.2 V. If a higher charging voltage is applied, an irreversible phase transition of LiCoO2 during delithiation would occur, resulting in severe capacity fading. Therefore, it is essential to investigate the electrochemically driven phase transition of LiCoO2 cathode material to approach its theoretical capacity. In this work, it was observed that LiCoO2 partially degraded to Co3O4 after 150 charging-discharging cycles. From the perspective of crystallography, the conventional cell of LiCoO2 was rebuilt to an orthonormal coordinate, and the transition path from layered LiCoO2 to cubic Co3O4 proposed. The theoretical analysis indicated that the electrochemically driven phase transition from LiCoO2 to Co3O4 underwent several stages. Based on this, an experimental verification was made by doping LiCoO2 with Al, In, Mg, and Zr, respectively. The doped samples theoretically predicted behavior. The findings in this study provide insights into the electrochemically driven phase transition in LiCoO2, and the phase transition can be eliminated to improve the capacity of LiCoO2 to its theoretical value.Chronic diseases represent one of the main causes of death worldwide. The integration of digital solutions in clinical interventions is broadly diffused today; however, evidence on their efficacy in addressing psychological comorbidities of chronic diseases is sparse. This systematic review analyzes and synthesizes the evidence about the efficacy of digital interventions on psychological comorbidities outcomes of specific chronic diseases. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic search of PubMed, PsycInfo, Scopus and Web of Science databases was conducted. Only Randomized Controlled Trials (RCTs) were considered and either depression or anxiety had to be assessed to match the selection criteria. Of the 7636 identified records, 17 matched the inclusion criteria 9 digital interventions on diabetes, 4 on cardiovascular diseases, 3 on Chronic Obstructive Pulmonary Disease (COPD) and one on stroke. Of the 17 studies reviewed, 14 found digital interventions to be effective. Quantitative synthesis highlighted a moderate and significant overall effect of interventions on depression, while the effect on anxiety was small and non-significant. Design elements making digital interventions effective for psychological comorbidities of chronic diseases were singled out (a) implementing a communication loop with patients and (b) providing disease-specific digital contents. This focus on "how" to design technologies can facilitate the translation of evidence into practice.Aspergillus is one of the most common fungal genera found indoors; it is important because it can cause a wide range of diseases in humans. Aspergillus species identification is based on a combination of morphological, physiological, and molecular methods. However, molecular methodologies have rarely been used for the identification of environmental isolates of Aspergillus in Cuba. Therefore, the objective of this work was to identify the species of the genus Aspergillus obtained from houses in Havana, Cuba, through the construction of phylogeny from a partial sequence of the benA gene region, and to analyze the diversity and richness of Aspergillus in the studied municipalities. Isolates of Aspergillus spp. included in this study presented the typical macro- and micromorphology described for the genus. According to this polyphasic characterization, A. niger, A. flavus, A. welwitschiae, A. heteromorphus, A. sydowii, A. tamarii, A. fumigatus, A. clavatus, and A. learn more tubingensis were the most abundant species. Most of the identified species constitute new records for outdoor and indoor environments in Cuba and contribute to the knowledge of fungal biodiversity in the country.