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As the sustainability of the environment is a very much concerning issue for developed countries, the drive of the paper is to reveal the effects of nuclear, environment-friendly, and non-friendly energy, population, and GDP on CO2 emission for Italy, a developed country. Using the extended Stochastic Regression on Population, Affluence, and Technology (STIRPAT) framework, the yearly data from 1972 to 2021 are analyzed in this paper through an Autoregressive Distributed Lag (ARDL) framework. The reliability of the study is also examined by employing Fully Modified Ordinary Least Square (FMOLS), Dynamic Ordinary Least Square (DOLS), and Canonical Cointegration Regression (CCR) estimators and also the Granger causality method which is used to see the directional relationship among the indicators. The investigation confirms the findings of previous studies by showing that in the longer period, rising Italian GDP and non-green energy by 1% can lead to higher CO2 emissions by 8.08% and 1.505%, respectively, while rising alternative and nuclear energy by 1% can lead to falling in CO2 emission by 0.624%. Although population and green energy adversely influence the upsurge of CO2, they seem insignificant. Robustness tests confirm these longer-period impacts. This analysis may be helpful in planning and developing strategies for future financial funding in the energy sector in Italy, which is essential if the country is to achieve its goals of sustainable development.

Due to limited motor capabilities, people with upper limb disabilities have trouble utilizing a typical mouse while operating a computer. Different wearable Assistive Mouse Controllers (AMCs) have been developed to overcome their challenges. However, these people may not be able to realize the importance, ease of use, and social approval of these AMCs due to their fear of new technology, lack of confidence, and lack of ingenuity. These may negatively affect their attitude and intention toward accepting AMCs for equitable human-computer interaction. This study presents the development of a sensor-based head-mounted AMC, followed by an empirical analysis of its acceptance using the Technology Acceptance Model (TAM) from the socioeconomic perspective of Bangladesh. In a similar vein, we examined the effects of three additional psychological constructs—technology anxiety, confidence, and innovation, on its acceptance along with the original components of the TAM. A total of 150 individuals with stroke-induced upper limb disability participated in an online survey, and their responses were analyzed using confirmatory factor analysis and structural equation modeling, following the general least square method. Analysis revealed, about 96.44% of the participants had positive attitude towards the AMC, and almost 88.56% of them had positive intentions to accept it. Furthermore, about 68.61% of them expressed signs of anxiety, 96.35% were confident, and 94.16% of them had an innovative mindset in terms of device usage. The findings imply that individuals with an innovative mentality are more capable of comprehending the practical implications of a new technology than those without one. It is also feasible to reduce technological anxiety and boost a user’s confidence while using an AMC by combining an innovative mentality with straightforward device interaction techniques. Additionally, peer encouragement and motivation can significantly enhance their positive attitude towards accepting the AMC for facilitating their interaction with a computer.

Energy-intensive sectors in emerging nations have the simultaneous difficulties of trying to diminish greenhouse gas emissions while maintaining a stable and cost-effective energy supply. Rooftop solar photovoltaic (PV) systems offer a viable solution, especially in tropical areas like Indonesia that have elevated solar irradiance. This study employs a comprehensive methodology to evaluate the structural, economic, and safety viability of rooftop photovoltaic adoption in the Fast-Moving Consumer Goods (FMCG) sector. Structural analysis utilizing the PMM Ratio verified that industrial rooftops can support a 599 kWp photovoltaic system with minimal reinforcements. The economic assessment revealed substantial feasibility, featuring a Levelized Cost of Energy (LCOE) of Rp 261.40/kWh (about USD 0.016/kWh), yearly savings of Rp 1.36 billion (approximately USD 89,000), a Return on Investment (ROI) of 570%, and a payback duration of 3.73 years. The safety evaluation utilizing the Hazard Identification and Risk evaluation (HIRA) technique found significant hazards—working at height, electrical faults, and fire risks—and recommended mitigation measures in accordance with IEC and Indonesian standards. The findings establish a replicable paradigm for assessing rooftop photovoltaic systems in energy-intensive sectors and furnish actionable recommendations for policymakers and industry executives to expedite the adoption of renewable energy in tropical emerging economies.

This study, based on the Neo-Malthusian framework, examines the association between population growth, resource scarcity, and political instability in 128 developing countries from 1960 to 2022. Results show that rapid population growth is associated with higher levels of political instability. This association appears stronger in low-income countries, which generally exhibit weaker institutions, limited fiscal capacity, and lower carrying capacity that coincide with greater sociopolitical tensions and inequalities. In contrast, high-income developing countries tend to show greater resilience, associated with stronger governance and technological adaptability. The findings highlight the importance of policies that strengthen governance, enhance resource management, and promote sustainable development to address potential instability risks associated with demographic pressures.

Background Anxious depression, which is a common subtype of major depressive disorder, has distinct clinical features from nonanxious depression. However, little is known about the neurobiological characteristics of anxious depression. In this study, we explored resting-state regional brain activity changes between anxious depression and nonanxious depression. Method Resting-state functional magnetic resonance (rs-fMRI) imaging data were collected from 60 patients with anxious depression, 38 patients with nonanxious depression, and 60 matched healthy controls (HCs). One-way analysis of variance was performed to compare the whole-brain fractional amplitude of low-frequency fluctuation (fALFF) in the three groups. The correlation between the fALFF values and the clinical measures was examined. Results Compared with those of HCs, the fALFF values in the left superior temporal gyrus (STG) in patients with anxious depression were significantly increased, while the fALFF values in the left middle temporal gyrus (MTG), left STG, and right STG in patients with nonanxious depression were significantly increased. Patients with anxious depression showed reduced fALFF values in the right STG compared with patients with nonanxious depression ( p  < 0.001, corrected). Within the anxious depression group, fALFF value in the right STG was positively correlated with the cognitive disturbance score ( r  = 0.36, p  = 0.005 corrected). Conclusion The bilateral STG and left MTG, which are related to the default mode network, appear to be key brain regions in nonanxious depression, while the right STG plays an essential role in the neuropathological mechanism of anxious depression.

Sustainable mineral resource management is critical amid escalating environmental concerns and growing demand for minerals in digital and clean energy technologies. While financial technology (FinTech) has been widely recognized for enhancing financial inclusion and economic efficiency, its role in environmental governance—particularly in the mining sector—remains underexplored, especially within developed economies like the United States. This study addresses this gap by examining how FinTech adoption influences mineral sustainability, using time series data from 1998 to 2023. Four FinTech proxies—mobile cellular subscriptions, Internet usage, fixed broadband access, and financial inclusion—were analyzed alongside environmental compliance and investment in sustainable mining technologies. Using the Autoregressive Distributed Lag (ARDL) model and Frequency Domain Causality (FDC) analysis, the results show that greater FinTech adoption significantly reduces mineral depletion rates, indicating improved sustainability. Internet and broadband access exhibit strong long-term impacts, while mobile connectivity and credit access show notable short- and medium-term effects. Investment in sustainable mining technologies further enhances these outcomes. Our findings suggest that FinTech serves as a multidimensional enabler of sustainability through digital inclusion, transparency, and access to green financing. This study provides empirical evidence to guide policymakers in integrating digital financial infrastructure into strategies for sustainable mineral resource governance.

Major depressive disorder (MDD), characterized by low mood or anhedonia, is commonly associated with a greater suicidal susceptibility. There are numerous suicide-related findings pertaining to the dorsolateral prefrontal cortex (DLPFC), caudate nucleus and thalamus, which form a cortico-striato-thalamo-cortical (CSTC) circuit responsible for executive function and working memory. An aberrant CSTC circuitry is hypothesized to be implicated in depressed patients with a high suicidal risk. 27 MDD patients were assessed with the Nurses Global Assessment of Suicide Risk (NGASR), following which 14 patients were classified into a high suicide risk group (NGASR ≥ 12) and 13 patients were assigned to a low suicide risk group (NGASR < 6). All 27 patients were enrolled with 25 healthy controls for resting-state magnetoencephalography (MEG). Cross-frequency coupling (CFC) measured the phase of alpha-band (8–13 Hz) as it modulated to cortical gamma-band (30–48 Hz). There was a significantly lower alpha-to-gamma phase-amplitude coupling (PAC) between the right caudate and left thalamus in high-risk suicide group compared to both the low-risk suicide group and healthy controls. The presence of a weaker coupling between the right caudate and left thalamus is indicative of a caudothalamic abnormality in suicidally depressed patients. This implies that a disruption of CSTC loop could result in executive dysfunction and working memory impairment, leading to an increased suicidal risk in MDD patients. In the future, this preliminary study has the possibility of being replicated on a larger scale, and hence validates caudothalamic dysfunction as a reliable neuroimaging biomarker for suicide in depression.

Modelers often create diverse system dynamics models for the same issue, depending on their viewpoints, which can decrease stakeholder assurance. Validating system dynamics may enhance stakeholder confidence. This study suggests using fuzzy‐set qualitative comparative analysis (fsQCA) as a technique based on a set theory approach to validate the causal connections between entities in causal loop diagram (CLD) models. This case study analyzed the issue of Indonesian mobile network operators with limited sample data, utilizing the fsQCA method to test causal connections between entities in the CLD model that require validation. Following the creation of the CLD model through the system dynamics methodology, fsQCA was employed to enhance the previously formed model. The fsQCA method fuses qualitative comparative analysis (QCA) with fuzzy set theory, permitting partial membership, and can identify causal links among entities in the CLD model. It assists in testing causal relationships using limited sample data and boosts stakeholder confidence in the CLD model. Modelers typically produce different system dynamics models for the same problem, depending on each modeler's perspective, leading to reduced stakeholder confidence. Validation of system dynamics can increase stakeholder confidence. The fsQCA method can be used to test causal relationships between entities in the CLD model with small sample data and increase stakeholder confidence in the CLD model.

Background and Hypothesis Antipsychotics (APs), the cornerstone of schizophrenia treatment, confer a relatively high risk of constipation. However, the mechanisms underpinning AP-induced constipation are poorly understood. Thus, we hypothesized that (1) schizophrenia patients with AP-induced constipation have distinct metabolic patterns; (2) there is more than one mechanism at play in producing this adverse drug effect; and (3) AP-associated changes in the gut microbiome are related to the altered metabolic profiles. Study Design Eighty-eight schizophrenia patients, including 44 with constipation (C) and 44 matched patients without constipation (NC), were enrolled in this study. Constipation was diagnosed by Rome IV criteria for constipation and colonic transit time using radiopaque markers (ROMs) while severity was evaluated with the Bristol Stool Form Scale (BSS) and Constipation Assessment Scale (CAS). Fasting blood samples were drawn from all participants and were subjected to non-targeted liquid chromatography-mass spectrometry (LC-MS) metabolomic analysis. Study Results Eleven metabolites were significantly altered in AP-induced constipation which primarily disturbed sphingolipid metabolism, choline metabolism, and sphingolipid signaling pathway (P value < .05, FDR < 0.05). In the C group, changes in the gut bacteria showed a certain degree of correlation with 2 of the significantly altered serum metabolites and were associated with alterations in choline metabolism. Conclusions Our findings indicated that there were disturbances in distinct metabolic pathways that were associated with AP-induced constipation. In addition, this study presents evidence of a link between alterations in the gut microbiome and host metabolism which provides additional mechanistic insights on AP-induced constipation.

In this study, the physicochemical properties, composition, thermal properties, and crystal microstructure of fractionated bambangan kernel fat stearin and palm oil mid-fraction blends were investigated with respect to a potential cocoa butter equivalent. The blends were prepared in five ratios, and all of the blends exhibited similar physicochemical properties to cocoa butter. Although all of the blends had similar physicochemical properties, the blend containing 70% bambangan kernel fat stearin and 30% palm oil mid-fraction showed remarkable similarity to cocoa butter. The blend had similar fatty acid and triacylglycerol content to cocoa butter with 18.74% palmitic acids, 38.26% stearic acids, 34.05% oleic acids, 15.20% 1,3-dipalmitoyl-2-oleoyl glycerol, and 29.74% 1,3-disteroyl-2-oleoyl glycerol with improved thermostability (high solid fat content at 30 °C but reaching 0% at 40 °C). It also exhibited spherulite crystals with a needle-like crystal structure of 50 µm. This mixture showed good compatibility with cocoa butter at all mixing ratios; hence, it is suggested as a potential cocoa butter equivalent.