The present study analyzed the relationship between the average annual temperature and the area of Amazonian forest in the departments of Peru during the period 2013-2021, using a panel data model with random effects. The data used come from the National Institute of Statistics and Informatics (INEI) and include the average annual temperature in degrees Celsius and the area of Amazonian rainforest in thousands of hectares, both disaggregated by department. Additionally, CO2 emissions resulting from the loss of tree cover, measured in megatons (Mt) of carbon dioxide equivalent (CO₂e), were considered as a control variable. The results revealed a positive and statistically significant relationship between the area of Amazonian forest and the average annual temperature, denoting that an increase of one thousand hectares in the extension of the forest corresponds to an increase of 0.0004 °C in temperature. In this sense, the finding contradicts the climate-regulating role played by forests, however, this is attributed to the influence of unobserved confounding variables that are linked to both forest area and temperature.

Job satisfaction and digital talent are topics of growing interest in the context of digital transformation. Digitalization is changing the way organizations operate and how employees perceive their work. The state and its administrative staff is no exception, as these capabilities are essential to perform operational tasks that underpin the public institution's documentary processes. This study investigates the influence of digital talent (independent variable) on job satisfaction (dependent variable), employing structural equation modeling (SEM) using WarpPLS software. Digital Talent is broken down into three sub-variables: Digital Competencies of Employees (DCE), Capacity for Digital Innovation and Creativity (CIDC) and Adaptability and Continuous Learning (ACL), while Job Satisfaction is measured through two sub-variables: Work Environment (WE) and Professional Development Opportunities (PDO). The analyses revealed that Capacity for Innovation and Digital Creativity (CIDC) has a significant impact on Work Environment, with a path coefficient (β) of 0.13 (p = 0.01). Similarly, adaptability and continuous learning (ACL) positively influence the work environment, with a path coefficient (β) of 0.10 (p = 0.04). In addition, a strong relationship was found between professional development opportunities (PDO) and work environment, with a path coefficient (β) of 0.68 (p < 0.001). For the relationship between digital competencies (DCE) and career development opportunities, the path coefficient was 0.10 (p = 0.04). Digital talent is a key predictor of job satisfaction in administrative staff. The results suggest that investing in the development of digital capabilities, especially innovation and creativity, as well as adaptability, is essential to improve the work environment and career development opportunities.

The current work involves the synthesis of amalgamated heterocyclic scaffolds embracing pyrazolone and triazole nuclei. The suggested methodology leads to streaming in the targeted synthesis in a multicomponent reaction manner resulting in 91% yield of the structural motifs. This strategy makes use of the click reaction mechanism of copper-catalyzed azide-alkyne (CuAAC) cycloaddition. The structures of all the synthesized compounds were ascertained considering spectro-analytical data from 1H NMR, ¹³C NMR, and FTIR and Mass studies. Subsequently, molecular docking studies were performed taking into account the P. gingivalis as the heme binding targeted protein.

This study investigates the factors influencing the actual usage of freight forwarding services in Indonesia, focusing on the roles of desire, outcome expectancy, and perceived self-efficacy, with delivery risk and perceived trust acting as moderating factors. Grounded in Social Cognitive Theory (SCT), this study examines how personal cognitive factors and external risks influence users' attitudes and behaviors toward freight forwarding services. Data were collected from 616 respondents across Jakarta, Surabaya, and Makassar utilizing a structured questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized relationships. The findings reveal that desire significantly influences both attitude and delivery risk, while attitude has a strong direct effect on actual usage. Outcome expectancy and perceived self-efficacy demonstrated weaker effects, particularly on attitudes, suggesting that other factors, such as trust and risk perceptions, play a more significant role in this context. Additionally, delivery risk was found to moderate the relationship between desire and attitude, while perceived trust did not moderate the link between attitude and actual usage. The research underscores the importance of trust-building and risk mitigation strategies for freight forwarding service providers in Indonesia. The study also provides theoretical contributions by applying SCT to the logistics sector and offers practical implications for enhancing service adoption in emerging markets.

The mechanism and regioselectivity of 1,3-dipolar reaction of 2-azido-N-(4-diazenylphenyl) acetamide and an alkyne have been studied in gas phase and in DMSO using the B3LYP-GD3 functional and 6-31G(d,p) basis set. The reaction followed a one-step mechanism with asynchronous TSs. The calculated global reactivity indices calculated revealed, among other things, the nucleophile character of the 2-azido-N-(4-diazenylphenyl)acetamide and the electrophile character of the alkyne (4-bromo-2-chloro-1-ethynylbenzene), in addition to an electron transfer from the 4-bromo-2-chloro-1-ethynylbenzene towards the 2-azido-N-(4-diazenylphenyl) acetamide. The calculated local reactivity indices predicted the formation of the 1,4-triazole, with the most nucleophilic nitrogen and the most electrophilic carbon favoring its formation. However, analysis of the activation energies and thermochemistry parameters showed that the 1,5 triazole is energetically favorable and more stable under thermodynamic control. Bond order analysis coupled with bond formation evolution and the solvent effect was further investigated to support and highlight the asynchronicity in bond formation and the regioselectivity of the reaction, respectively.

The swift growth of online commerce has significantly impacted the expedition service industry. As online shopping becomes increasingly prevalent, reliable shipping service has become crucial. Therefore, this study aims to determine the correlation between service quality, customer perceived value, and trust, as well as their impact on customer satisfaction within the expedition service industry. A survey was carried out through various messaging platforms, such as WhatsApp and Telegram, to reach users. Data were then obtained from 165 respondents, who were users of the 8 most popular expedition services in Indonesia (including J&T, JNE, SiCepat, Ninja Express, SAP, and others), followed by PLS-SEM analysis. The results showed that the three independent variables positively influenced customer satisfaction. In addition, trust acted as a mediator, indirectly affecting both service quality and customer perceived value. These results are expected to serve as a foundation for developing more efficient and contextually relevant strategies for expedition companies in the future.

Artemisia herba-alba is a perennial herbaceous plant belonging to the Asteraceae family. It is used in folk medicine to treat many nervous and digestive disorders, as well as diabetes. It possesses antioxidant, antifungal and anti-inflammatory properties. The chemical composition of the organic extracts obtained from the leaves of the Syrian Artemisia herba-alba plant was analysed using a Soxhlet extraction device and three solvents with varying degrees of polarity (petroleum ether, chloroform and ethyl acetate). The chemical constituents of the three extracts were determined using GC/MS technology. In the petroleum ether extract (Ah1), 38 compounds were identified, while the chloroform extract (Ah2) contained 39 compounds, and the ethyl acetate extract (Ah3) contained 45 compounds. The most significant compounds in the Ah1 extract were longiverbenone (23.9%), heneicosane (18.2%), 3,3,6-trimethyl-1,5-heptadien-4-one (16.5%), caryophyllene oxide (5.8%), and octacosane (4.6%). In the Ah2 extract, the main constituents were dioctyl hexanedioate (13.2%), (Z,Z) 9,12-octadecadienoyl chloride (7.3%), and (-)-spathulenol (7.1%). The primary compounds in the Ah3 extract were pentanoic acid (9.5%), geranyl isovalerate (9.3%), 2-butyl-1-octanol (7.5%), and 1-heptadecene (6.4%).

This paper analyses the possible determinants that induced Silicon Valley and First Republic Bank to Bankruptcy. We employ financial statements for a sample of Banks in line with the business core of Silicon Valley Bank. The period under assessment ranges from 2006-2022. We estimate an indicator of Bank Efficiency using the technique Data Envelopment Analysis (DEA). The latter indicator is used as the primary step to analyze failure within sample banks. According to the CAMEL model, macroeconomic variables are non-significant but relevant variables that drive failure were: Bank Efficiency, Capital adequacy, Earning ability, and Liquidity position ratio. Our study is relevant for any policy making to prevent any future bank failure.

While the number of AIDS-related deaths continues to rise, efforts have been made to transform the disease into a manageable chronic condition. HIV protease inhibitors have become central to combination therapy. As a result, these inhibitors have become a major focus of anti-HIV drug development. This research takes a data-driven approach to drug development through the use of quantitative structure-activity relationship (QSAR) analysis. A dataset of 450 anti-HIV drugs was used to construct and validate models. Using extensive validation methods and various machine learning algorithms, the results clearly showed that the "ET" regression outperformed the other models (“XGB”, “LGBM”, “DT”, “RF”, “GB”, “Bag”, and “HGB”) in terms of goodness of fit, predictivity, generalizability, and model robustness. Promising compounds were subjected to molecular docking and molecular dynamics simulation, resulting in drugs with favourable pharmacokinetic and pharmacodynamic properties that consistently interact with the therapeutic target.

This study sought to determine how CAATS, corporate governance (CG), and EIAF positively and directly influence the quality of financial reports (QFR). In addition to identifying the moderating effect of EIAF on the links between CAATS, CG and QFR in Saudi commercial banks. To this end, data was collected from 293 participants, including administrative managers, board members, internal auditors, certified public accountants, and staff members from the audit and internal audit departments as well as the accounting departments. Using structural equation modelling (SEM) via SmartPls, data was analyzed. The study showed that QFR is positively and significantly affected by CAATS, CG, and EIAF. Moreover, EIAF does not moderate the effect of CAATS and CG on QFR. Hence, this study enriches accounting literature and has implications for both practitioners and policymakers.