Search Results (14,989)

Corporate ESG (Environmental, Social, and Governance) reporting is increasingly envisioned as evidence of accountability in the energy transition, yet persistent gaps remain between commitments and practices. This study applied the Global Reporting Initiative (GRI) framework—specifically indicators 302 (Energy) and 305 (Emissions)—to evaluate the credibility, scope, and strategic depth of disclosures by 20 Wisconsin (WI) firms in the energy, manufacturing, food, and service sectors. Guided by accountability and legitimacy theory, a comparative content analysis was conducted, complemented by Spearman correlation to examine associations between firm size and disclosure quality. Results show that while firms consistently report basic metrics such as total energy consumption and Scope 1 emissions, disclosures on Scope 3 emissions, renewable sourcing, and energy-efficiency achievements remain partial and selectively framed. Third-party assurance is inconsistently applied, and methodological transparency—such as external audit and coding protocols—is limited, weakening credibility. A statistically significant negative correlation was observed between annual revenue and disclosure quality, indicating that greater financial capacity does not necessarily translate into greater transparency. These findings highlight methodological and governance shortcomings, including reliance on generic ESG frameworks rather than climate-focused standards such as Task Force on Climate-related Financial Disclosures (TCFD). Integrated reporting approaches are recommended to improve comparability, credibility, and alignment with Wisconsin’s Clean Energy Transition Plan. Full article

Hydrogen energy is viewed as a promising green energy source because of its high energy density, abundant availability, and clean combustion results. Hydrogen storage is the critical link in a hydrogen economy. Using first-principles density functional theory calculations, this work explored the role of B and N in modulating the binding properties of transition metal-modified graphene. The hydrogen storage performance of Sc-, Ti-, and V-modified B-doped graphene was evaluated. Boron doping induces an electron-deficient state, enhancing interactions between transition metals and graphene. Sc, Ti, and V preferentially adsorbed at the carbon ring’s hollow site in B-doped graphene, with their binding energies being 1.87, 1.74, and 1.69 eV higher than those in pure graphene, respectively. These systems can stably adsorb up to 5, 4, and 4 H₂ molecules, with average adsorption energies of −0.528, −0.645, and −0.620 eV/H₂, respectively. The hydrogen adsorption mechanism was dominated by orbital interactions and polarization effects. Among the systems studied, Sc-modified B-doped graphene exhibited superior hydrogen storage characteristics, making it a promising candidate for reversible applications. Full article

Background/Objectives: Multi-bracket appliances are essential in surgical orthodontic treatment, and perioperative oral management during orthognathic surgery is critical. Thorough plaque control, appropriate use of antibiotics, and shortening of operative time have been reported to be effective in preventing postoperative infections and ensuring surgical success. As highly invasive orthognathic surgery involving osteotomy may influence the postoperative oral microbiota, this study aimed to investigate the characteristics of and clarify the changes occurring in the salivary oral microbiota after orthognathic surgery. Methods: The study included 14 patients (Group S; mean age 29.3 ± 9.8 years) who underwent surgical orthodontic treatment and 15 control patients (Group C; mean age 27.1 ± 8.7 years) who received orthodontic treatment alone. Salivary samples were analyzed via 16S rRNA gene sequencing, and the relative abundances of bacteria were evaluated using the Linear Discriminant Analysis Effect Size. Results: The prevalence of Neisseria, which is associated with early biofilm formation, decreased over time in both groups. In contrast, Streptococcus exhibited an increase in prevalence. In Group S, members of Pseudomonas, the family Saccharimonadaceae, and the order Rhizobiales showed increases at 5–8 months post-surgery. Conclusions: Surgical orthodontic treatment may influence the oral microbiota and promote colonization by opportunistic pathogens. Instructions regarding oral hygiene and appropriately timed professional cleaning interventions are critical in preventing such colonization. Longitudinal monitoring of the microbiota using metagenomic analysis may be useful for future perioperative management and guidance of oral hygiene. Full article

In the evolving cyberthreat landscape, a critical challenge for intrusion detection systems (IDSs) lies in defending against meticulously crafted adversarial attacks. Traditional single-view detection frameworks, constrained by their reliance on limited and unidimensional feature representations, are often inadequate for identifying maliciously manipulated samples. To address these limitations, this study proposes a key hypothesis: a detection architecture that adopts a multi-view fusion strategy can significantly enhance the system’s resilience to attacks. To validate the proposed hypothesis, this study developed a multi-view fusion architecture and conducted a series of comparative experiments. A two-pronged validation framework was employed. First, we examined whether the multi-view fusion model demonstrates superior robustness compared to a single-view model in intrusion detection tasks, thereby providing empirical evidence for the effectiveness of multi-view strategies. Second, we evaluated the generalization capability of the multi-view model under varying levels of attack intensity and coverage, assessing its stability in complex adversarial scenarios. Methodologically, a dual-axis training assessment scheme was introduced, comprising (i) continuous gradient testing of perturbation intensity, with the $\epsilon$ parameter increasing from 0.01 to 0.2, and (ii) variation in attack density, with sample contamination rates ranging from 80% to 90%. Adversarial test samples were generated using the Fast Gradient Sign Method (FGSM) on the TON_IoT and UNSW-NB15 datasets. Furthermore, we propose a validation mechanism that integrates both performance and robustness testing. The model is evaluated on clean and adversarial test sets, respectively. By analyzing performance retention and adversarial robustness, we provide a comprehensive assessment of the stability of the multi-view model under varying evaluation conditions. The experimental results provide clear support for the research hypothesis: The multi-view fusion model is more robust than the single-view model under adversarial scenarios. Even under high-intensity attack scenarios, the multi-view model consistently demonstrates superior robustness and stability. More importantly, the multi-view model, through its architectural feature diversity, effectively resists targeted attacks to which the single-view model is vulnerable, confirming the critical role of feature space redundancy in enhancing adversarial robustness. Full article

Perovskite materials have garnered significant attention in both fundamental research and practical applications owing to their exceptional light absorption coefficients, low fabrication costs, and inherent advantages for thin-film and flexible device fabrication. Nevertheless, interface defects within perovskite films induce detrimental non-radiative carrier recombination and pronounced hysteresis effects, which collectively impose substantial limitations on the photovoltaic performance and long-term operational stability of perovskite solar cells (PSCs). Conventional passivation strategies, despite their demonstrated efficacy in mitigating interface defects, often inadvertently introduce secondary defects in originally defect-free regions, thereby restricting the extent of device performance improvement. To overcome this critical limitation, we have developed a precision defect passivation methodology that employs a targeted two-step immersion–cleaning process, achieving selective defect passivation while concomitantly eliminating residual passivating agents. This approach effectively prevents the formation of new defects in unaffected regions of the perovskite films, and the resultant PSC possesses a power conversion efficiency (PCE) of 21.08%, accompanied by a substantial mitigation of hysteresis behavior. Furthermore, unencapsulated devices demonstrate remarkable stability, retaining over 81% of their initial efficiency after 20 days of atmospheric storage under 50% relative humidity, which underscores the effectiveness of our passivation strategy in simultaneously enhancing both device performance and operational stability. Full article

Achieving sustainable growth in emerging economies requires more than expanding clean energy; it also relies on the synergistic role of Artificial Intelligence, Internet Connectivity, and Knowledge Management in narrowing the digital–energy divide. Thus, this study examines the factors influencing the energy transition—both implicit and explicit—using the case of the BRICS economies with data spanning from 2000 to 2022. This study employed Driscoll–Kraay (DK) standard errors together with Lewbel IV-2SLS estimators to examine the connections. The results showed that Artificial Intelligence and economic growth hinder energy transition, while financial development and trade openness promote it. Furthermore, Knowledge Management and Internet Connectivity show threshold effects, and education remains negatively aligned with sustainability goals. Based on these findings policies are proposed. Full article

This study addresses a significant gap in the existing literature by introducing novel perspectives. First, it provides a comprehensive assessment of the impact of ESG sustainability and information and communication technology (ICT) on energy transition using updated quarterly data from 2002 Q3 to 2024 Q4. Second, it uniquely integrates climate policy uncertainty (CPU) and financial development (FD) as core explanatory variables, which have been largely neglected in prior research. Third, this study applies advanced quantile-based methodologies, including the Quantile Autoregressive Distributed Lag (QARDL) model and Quantile Cointegration (QC) techniques, to enhance empirical rigor and ensure policy relevance across the entire conditional distribution. The results showed that at lower quantiles (τ = 0.05–0.30), FD positively influences ET, supporting early-stage clean energy adoption. ICT shows a short-term negative effect (τ = 0.05–0.40). Based on these findings, policymakers should strengthen financial development to accelerate clean energy adoption at early stages, while addressing the short-term negative impacts of ICT by promoting supportive digital and energy policies that align technology use with sustainability goals. Full article

Advances in machine learning have improved the ability to predict critical environmental conditions, including solar radiation levels that, while essential for life, can pose serious risks to human health. In Ecuador, due to its geographical location and altitude, UV radiation reaches extreme levels. This study presents the development of a chatbot system driven by a hybrid artificial intelligence model, combining Random Forest, CatBoost, Gradient Boosting, and a 1D Convolutional Neural Network. The model was trained with meteorological data, optimized using hyperparameters (iterations: 500–1500, depth: 4–8, learning rate: 0.01–0.3), and evaluated through MAE, MSE, R², and F1-Score. The hybrid model achieved superior accuracy (MAE = 13.77 W/m², MSE = 849.96, R² = 0.98), outperforming traditional methods. A 15% error margin was observed without significantly affecting classification. The chatbot, implemented via Telegram and hosted on Heroku, provided real-time personalized alerts, demonstrating an effective, accessible, and scalable solution for health safety and environmental awareness. Furthermore, it facilitates decision-making in the efficient generation of renewable energy and supports a more sustainable energy transition. It offers a tool that strengthens the relationship between artificial intelligence and sustainability by providing a practical instrument for integrating clean energy and mitigating climate change. Full article

Organic contaminants on optical components critically impair intense laser systems. Oxygen plasma cleaning is a promising non-contact method, yet the mechanism by which the initial kinetic energy of reactive oxygen species assists chemically driven removal remains unclear. This study employs ReaxFF molecular dynamics to elucidate how reactive oxygen species chemically decompose dibutyl phthalate and how kinetic energy assists chemical reactions by enhancing transport, penetration, and energy transfer. While the core removal mechanism is chemical, kinetic energy promotes plasma-contaminant encounters and facilitates access to otherwise sluggish pathways. The results show that kinetic energy is a key promoter that enhances chemical decomposition, with the contaminant decomposition rate enhanced by up to 1310% and residues reduced by 81.13% compared to pure chemical reactions. This study identifies and quantifies two dominant reaction pathways (butyl chain cleavage & benzene ring cleavage). The analysis of diffusion and energy transfer reveals that higher kinetic energy improves reactive oxygen species transport, enables deeper penetration, and selectively activates specific reaction pathways by overcoming energy barriers. Synergy with flux, dose, and temperature is also demonstrated. This work provides atomic-level insights into kinetic promotion mechanisms, supporting optimized plasma cleaning processes and contributing to the performance stability and operational longevity of intense laser systems. Full article

The multi-timescale optimization dispatch method for integrated energy systems proposed in this paper balances sustainability and low-carbon characteristics. It first incorporates shared energy storage resources such as electric vehicles into system dispatch, fully leveraging their spatiotemporal properties to enhance dispatch flexibility and rapid response capabilities for integrating renewable energy and enabling clean power generation. Second, an incentive-penalty mechanism enables effective interaction between the system and the green certificate–carbon joint trading market. Penalties are imposed for failing to meet renewable energy consumption targets or exceeding carbon quotas, while rewards are granted for meeting or exceeding targets. This regulates the system’s renewable energy consumption level and carbon emissions, ensuring robust low-carbon performance. Third, this strategy considers the close coordination between heating, cooling, and electricity demand response measures with the integrated energy system, smoothing load fluctuations to achieve peak shaving and valley filling. Finally, through case study simulations and analysis, the advantages of the multi-timescale dispatch strategy proposed in this paper, in terms of economic feasibility, low-carbon characteristics, and sustainability, are verified. Full article

This research details the development and evaluation of a Modern Ultrasonic Cleaning Tank (MUCT) designed to enhance cleaning efficiency in jewelry manufacturing, particularly for silver jewelry, replacing the traditional method, which was less efficient and had higher operating costs. The MUCT offers capabilities of single- or dual-frequency ultrasonic operation (28 kHz and 40 kHz) and adjustable transducer positioning. An advanced method involving computer simulations, utilizing harmonic response analysis and transient dynamic analysis, was employed to determine the acoustic pressure inside the MUCT, thereby indicating the cavitation intensity required to achieve high cleaning efficiency. Simulation results confirm that this design can distribute acoustic pressure throughout the MUCT, as intended. A prototype MUCT was assembled, and its operation was validated through foil corrosion tests, ultrasonic power concentration (UPC) measurements, and jewelry cleaning tests. The results revealed that the MUCT’s center provided the maximum UPC of 28 W/L and an acoustic pressure of 30.43 MPa, effectively operating at single and dual frequencies, and achieving superior dirt removal. The highest cleaning efficiency of 100% was achieved using dual frequency with a 97% water and 3% dishwashing liquid mixture at 60 °C, exceeding the 23.52% obtained with water at 27 °C without ultrasonic treatment. The MUCT, successfully integrated into the manufacturing process, offers customizable features to meet various cleaning needs, providing flexibility, improved performance, and cost savings. Full article

Oleosomes are submicron oil bodies of a triacylglycerol core enveloped by a phospholipid monolayer and embedded proteins, forming a naturally assembled nanocarrier with exceptional oxidative resilience, interfacial stability, and biocompatibility. Their unique architecture supports solvent-free extraction, self-emulsification, and near-complete encapsulation of highly lipophilic compounds (log P > 4), including curcumin and cannabidiol, with reported efficiencies exceeding 95%. These plant-derived droplets enhance oral bioavailability through lymphatic uptake and enable targeted delivery strategies such as magnetically guided chemotherapy, which has reduced tumor burden by approximately 70% in vivo. The review critically examines recent advances in oleosome research, spanning botanical sourcing, green extraction technologies, interfacial engineering, xenobiotic encapsulation, pharmacokinetics, and therapeutic applications across oncology, dermatology, metabolic disease, and regenerative medicine. Comparative analyses demonstrate that oleosomes rival or surpass synthetic lipid nanocarriers in encapsulation efficiency, oxidative stability, and cost efficiency while offering a sustainable, clean-label alternative. Remaining challenges, including low loading of hydrophilic drugs, allergenicity, and regulatory standardization, are addressed through emerging strategies such as hybrid oleosome–liposome systems, recombinant oleosin engineering, and stimulus-responsive coatings. These advances position oleosomes as a versatile and scalable platform with significant potential for food, cosmetic, and pharmaceutical applications. Full article

Floating photovoltaic (FPV) systems are promising for coastal aquaculture where reliable electricity is essential for pumping, oxygenation, sensing, and control. A sustainable FPV–storage hybrid tailored to monsoon-prone sites is developed, with emphasis on energy efficiency and structural resilience. The prototype combines dual-axis solar tracking with a spray-cooling and cleaning subsystem and an active wind-protection strategy that automatically flattens the array when wind speed exceeds 8.0 m/s. Temperature, wind speed, and irradiance sensors are coordinated by an Arduino-based supervisor to optimize tracking, thermal management, and tilt control. A 10 W floating module and a fixed-tilt reference were fabricated and tested outdoors in Penghu, Taiwan. The FPV achieved a 25.17% energy gain on a sunny day and a 40.29% gain under overcast and windy conditions, while module temperature remained below 45 °C through on-demand spraying, reducing thermal losses. In addition, a hybrid energy storage system (HESS), integrating a 12 V/10 Ah lithium-ion battery and a 12 V/24 Ah lead-acid battery, was validated using a priority charging strategy. During testing, the lithium-ion unit was first charged to stabilize the control circuits, after which excess solar energy was redirected to the lead-acid battery for long-term storage. This hierarchical design ensured both immediate power stability and extended endurance under cloudy or low-irradiance conditions. The results demonstrate a practical, low-cost, and modular pathway to couple FPV with hybrid storage for coastal energy resilience, improving yield and maintaining safe operation during adverse weather, and enabling scalable deployment across cage-aquaculture facilities. Full article

This paper aims to conduct a gap analysis and explore the potential for greenhouse gas (GHG) emissions reduction in the tourism sector of Chiang Mai province, with the goal of promoting sustainable tourism. Chiang Mai is a major tourism hub in Thailand, located in the Northern Economic Corridor (NEC). The gap analysis of small- and medium-sized tourism enterprises will be examined across four dimensions: (1) management, (2) socio-economy, (3) cultural, and (4) environmental. In 2024, Chiang Mai’s tourism revenue accounted for 46.97% of the northern region’s total tourism revenue and 3.73% of Thailand’s total tourism revenue. Given this economic significance, the development of sustainable tourism should be accelerated to meet the expectations of new tourists who are increasingly concerned about the environment. To address this need, this study analyzes the gaps in small- and medium-sized tourism enterprises and assesses GHG emissions through interviews and surveys of 90 tourism-related establishments across nine sectors: hotels, restaurants and beverages, tour agencies, transportation, souvenirs, attractions and activities, spas and wellness, community-based tourism, and farm tourism. The total GHG emissions from these establishments were found to be 15,303.72 tCO₂eq. Moreover, if renewable energy from solar power were adopted, an installation capacity of 21,866.84 kWp would be required. Such a transition would not only reduce emissions, but also support low-carbon development in small- and medium-sized tourism enterprises and ultimately contribute to achieving net-zero tourism. Finally, this study contributes to the advancement of STGs 1–17, adapted from the SDGs 1–17, with particular emphasis on SDG 7 on clean energy and SDG 13 on climate change. Full article

This work analyses what the systematic effect of public awareness on domestic water consumption is. In some parts of the world, the availability of water is continually decreasing, mainly due to reduced rainfall, so it is of paramount importance to raise awareness among the population. We conducted an experiment on a large sample of participating units located in urban areas of Italy, mainly in the central portion of the country. Approximately 750 people participated, belonging to 250 buildings, mainly domestic residences, but also professional offices, small companies, and student residences. In the first phase, lasting three weeks, normal per capita water consumption was quantified. Subsequently, instructions were given on how to save water during various uses in the household (showers, cleaning hands, use of water in toilets and in the kitchen, watering small green areas, use of water in the kitchen, and so on), and small visual messages conveyed through stickers were posted on water dispensers to remind users to behave properly. Finally, household consumption was assessed again during a further 3-week period. An average water-saving ($WS$) rate of +17.20% was found, in line with results obtained from a previous similar experiment involving a much smaller sample. Higher $WS$ rates were recorded for buildings with less inhabitants. This experiment enabled us to quantify the significant effect of the awareness-raising action on the reduction in water consumption, without the use of any structural action (e.g., replacement of dispensers, improvement of the water system, realization of recycling systems). Moreover, the simplicity of the proposed methodology makes it suitable for implementation in other regions worldwide, thus promoting a step forward towards more sustainable use of water. Full article