Search Results (8,106)

The Mapleton Falls National Park transmission line corridor in Queensland, Australia, has received a number of vegetation management treatments over the last decade to maintain and protect the infrastructure and to ensure continuous electricity supply. Recent treatments have included ‘mega-mulching’ (mechanical mastication of vegetation to a mulch layer) in 2020 and targeted herbicide treatment of woody vegetation, with the aim of reducing vegetation height by encouraging a native herbaceous groundcover beneath the transmission lines. We measured vegetation structure (cover and height) and composition (species presence in 15 × 2 m plots), at 12 transects, 90 m in length on the transmission line corridor, to determine if management goals were being achieved and to determine how the vegetation and fire hazard (based on the overall fuel hazard assessment method) varied among the treated corridor, the forest edge environment, and the natural forest. The results showed that vegetation structure and composition in the treated zones had been modified to a state where herbaceous plant species were dominant; there was a significantly (p < 0.05) higher native grass cover and cover of herbs, sedges, and ferns in the treated zones, and a lower cover of trees and tall woody plants (>1 m in height) in these areas. For example, mean native grass cover and the cover of herbs and sedges in the treated areas was 10.2 and 2.8 times higher, respectively, than in the natural forest. The changes in the vegetation structure (particularly removal of tall woody vegetation) resulted in a lower overall fuel hazard in the treated zones, relative to the edge zones and natural forest. The overall fuel hazard was classified as ‘high’ in 83% of the transects in the treated areas, but it was classified as ‘extreme’ in 75% of the transects in the adjacent forest zone. Importantly, there were few introduced species recorded. The results suggest that fuel management has been successful in reducing wildfire risk in the transmission corridor. Temporal monitoring is recommended to determine the frequency of ongoing fuel management. Full article

Aiming to address the problems of asynchronous acquisition time of multiple sensors in the crop phenotype acquisition system and high cost of the acquisition equipment, this paper developed a low-cost crop phenotype synchronous acquisition system based on the PTP synchronization protocol, realizing the synchronous acquisition of three types of crop data: visible light images, thermal infrared images, and laser point clouds. The paper innovatively proposed the Difference Structural Similarity Index Measure (DSSIM) index, combined with statistical indicators (average point number difference, average coordinate error), distribution characteristic indicators (Charm distance), and Hausdorff distance to characterize the stability of the system. After 72 consecutive hours of synchronization testing on the timing boards, it was verified that the root mean square error of the synchronization time for each timing board reached the ns level. The synchronous trigger acquisition time for crop parameters under time synchronization was controlled at the microsecond level. Using pepper as the crop sample, 133 consecutive acquisitions were conducted. The acquisition success rate for the three phenotypic data types of pepper samples was 100%, with a DSSIM of approximately 0.96. The average point number difference and average coordinate error were both about 3%, while the Charm distance and Hausdorff distance were only 1.14 mm and 5 mm. This system can provide hardware support for multi-parameter acquisition and data registration in the fast mobile crop phenotype platform, laying a reliable data foundation for crop growth monitoring, intelligent yield analysis, and prediction. Full article

Direct seeding has gained prominence as a labor-efficient and environmentally sustainable alternative to conventional transplanting in rice cultivation. In direct seeding systems, early-stage management is crucial for stable seedling establishment, with sowing uniformity measured by seed counts being a critical indicator of success. However, conventional manual seed counting methods are time-consuming, prone to human error, and impractical for large-scale or repetitive tasks, necessitating advanced automated solutions. Recent advances in computer vision technologies and precision agriculture tools, offer the potential to automate seed counting tasks. Nevertheless, challenges such as domain discrepancies and limited labeled data restrict robust real-world deployment. To address these issues, we propose a density estimation-based seed counting framework integrating semi-supervised learning and background augmentation. This framework includes a cost-effective data acquisition system enabling diverse domain data collection through indoor background augmentation, combined with semi-supervised learning to utilize augmented data effectively while minimizing labeling costs. The experimental results on field data from unknown domains show that our approach reduces seed counting errors by up to 58.5% compared to conventional methods, highlighting its potential as a scalable and effective solution for agricultural applications in real-world environments. Full article

This paper presents field investigations of a corrugated steel soil–steel arch structure with a span of 25.7 m and a rise of 9.0 m—currently the largest single-span structure of its kind in Europe. The structure, serving as a wildlife crossing along the DK16 expressway in northeastern Poland, was constructed using deep corrugated steel plates (500 mm× 237 mm) made from S315MC steel, without additional reinforcements such as stiffening ribs or geosynthetics. The study focused on monitoring the structural behavior during the critical backfilling phase. Displacements and strains were recorded using 34 electro-resistant strain gauges and a geodetic laser system at successive backfill levels, with particular attention to the loading stage at the crown. The measured results were compared with predictions based on the Swedish Design Method (SDM). The SDM equations did not accurately predict internal forces during backfilling. At the crown level, bending moments and axial forces were overestimated by approximately 69% and 152%, respectively. At the final backfill level, the SDM underestimated bending moments by 55% and overestimated axial forces by 90%. These findings highlight limitations of current design standards and emphasize the need for revised analytical models and long-term monitoring of large-span soil–steel structures. Full article

Ocean energy is an abundant, eco-friendly, and renewable energy resource that is useful for powering sensor networks connected to the maritime Internet of Things (MIoT). These sensor networks can be used to measure different marine environmental parameters that affect ocean infrastructure integrity and harm marine ecosystems. This ocean energy can be harnessed through hybrid nanogenerators that combine triboelectric nanogenerators, electromagnetic generators, piezoelectric nanogenerators, and pyroelectric generators. These nanogenerators have advantages such as high-power density, robust design, easy operating principle, and cost-effective fabrication. However, the performance of these nanogenerators can be affected by the wear of their main components, reduction of wave frequency and amplitude, extreme corrosion, and sea storms. To address these challenges, future research on hybrid nanogenerators must improve their mechanical strength, including materials and packages with anti-corrosion coatings. Herein, we present recent advances in the performance of different hybrid nanogenerators to harvest ocean energy, including various transduction mechanisms. Furthermore, this review reports potential applications of hybrid nanogenerators to power devices in marine infrastructure or serve as self-powered MIoT monitoring sensor networks. This review discusses key challenges that must be addressed to achieve the commercial success of these nanogenerators, regarding design strategies with advanced simulation models or digital twins. Also, these strategies must incorporate new materials that improve the performance, reliability, and integration of future nanogenerator array systems. Thus, optimized hybrid nanogenerators can represent a promising technology for ocean energy harvesting with application in the maritime industry. Full article

A facile and versatile strategy to obtain NPs@ZnAlO nanocomposite materials, comprising controlled-size nanoparticles (NPs) within a ZnAlO matrix is reported. The mono-(Au, Ni) and bimetallic (Ni-Au) NPs serving as an active phase were prepared by the polyol-alkaline method, while the ZnAlO support was obtained via the thermal decomposition of its corresponding layered double hydroxide (LDH) precursors. X-ray diffraction (XRD) patterns confirmed the successful fabrication of the nanocomposites, including the synthesis of the metallic NPs, the formation of LDH-like structure, and the subsequent transformation to ZnO phase upon LDH calcination. The obtained nanostructures confirmed the nanoplate-like morphology inherited from the original LDH precursors, which tended to aggregate after the addition of gold NPs. According to the UV-Vis spectroscopy, loading NPs onto the ZnAlO support enhanced the light absorption and reduced the band gap energy. ATR-DRIFT spectroscopy, H₂-TPR measurements, and XPS analysis provided information about the functional groups, surface composition, and reducibility of the materials. The catalytic performance of the developed nanostructures was evaluated by the photodegradation of bisphenol A (BPA), under simulated solar irradiation. The conversion of BPA over the bimetallic Ni-Au@ZnAlO reached up to 95% after 180 min of irradiation, exceeding the monometallic Ni@ZnAlO and Au@ZnAlO catalysts. Its enhanced activity was correlated with good dispersion of the bimetals, narrower band gap, and efficient charge carrier separation of the photo-induced e⁻/h⁺ pairs. Full article

Background/Objectives: This study investigated the association between cochlear implant (CI) users’ assessed perception of musical sound quality and their subjective music perception and music-related quality of life (QoL). The aim was to provide a comprehensive evaluation by integrating a relatively objective Turkish Multiple Stimulus with Hidden Reference and Anchor (TR-MUSHRA) test and a subjective music questionnaire. Methods: Thirty CI users and thirty normal-hearing (NH) adults were assessed. Perception of sound quality was measured using the TR-MUSHRA test. Subjective assessments were conducted with the Music-Related Quality of Life Questionnaire (MuRQoL). Results: TR-MUSHRA results showed that while NH participants rated all filtered stimuli as perceptually different from the original, CI users provided similar ratings for stimuli with adjacent high-pass filter settings, indicating less differentiation in perceived sound quality. On the MuRQoL, groups differed on the Frequency subscale but not the Importance subscale. Critically, no significant correlation was found between the TR-MUSHRA scores and the MuRQoL subscale scores in either group. Conclusions: The findings demonstrate that TR-MUSHRA is an effective tool for assessing perceived sound quality relatively objectively, but there is no relationship between perceiving sound quality differences and measures of self-reported musical engagement and its importance. Subjective music experience may represent different domains beyond the perception of sound quality. Therefore, successful auditory rehabilitation requires personalized strategies that consider the multifaceted nature of music perception beyond simple perceptual judgments. Full article

Background: Diabetes mellitus is associated with worse outcomes after cardiac arrest. Hyperglycemia, diabetes treatments and other long-term sequalae may contribute to this association. We sought to determine the acute effect of diabetes on the return of spontaneous circulation (ROSC) and post-arrest cardiac function in a rat cardiac arrest model. Methods: Eighteen male Wistar rats were utilized, and 12 underwent the induction of type II diabetes for 10 weeks through a high-fat diet and the injection of streptozotocin. The carotid artery flow and femoral arterial pressure were measured. Seven minutes of asphyxial cardiac arrest was induced. An external cardiac compression was performed via an automated piston. Post-ROSC, epinephrine was titrated to a mean arterial pressure (MAP) of 70 mmHg. Data was analyzed using the Mann–Whitney test. The significance was set at p ≤ 0.05. Results: The rate of the ROSC was significantly lower in animals with diabetes, 50% compared to 100% in non-diabetics. Additionally, it took significantly longer to achieve the ROSC in diabetics, p = 0.034. In animals who survived, the cardiac function was reduced, as indicated by an increased epinephrine requirement, p = 0.041, and a decreased cardiac output at the end of the experiment, p = 0.017. The lactate, venous and arterial pressures, heart rate and carotid flow did not differ between groups at 2 h. Conclusions: Diabetes negatively affects the survival from cardiac arrest. Here, the critical difference was the rate of the conversion to a life-sustaining rhythm and the achievement of the ROSC. The post-ROSC cardiac function was depressed in diabetic animals. Interventions targeted at improving defibrillation success may be important in diabetics. Full article

Background and Objectives: Depression is a leading cause of disability globally, with treatment challenges including limited access, stigma, and poor adherence. Gamification, which applies game elements such as points, levels, and storytelling into non-game contexts, offers a promising strategy to enhance engagement and augment traditional treatments. Our research is the first study designed to explore the implementation of gamification within the Malaysian context. The objective was to explore the feasibility of implementation of gamification as an adjunctive treatment for adults with depression. Materials and Methods: Focus group discussions were held with five mental health professionals and ten patients diagnosed with moderate depression. The qualitative component assessed perceptions of gamified interventions, while quantitative measures evaluated participants’ depressive and anxiety symptomatology. Results: Three key themes were identified: (1) understanding of gamification as a treatment option, (2) factors influencing its acceptance, and (3) characteristics of a practical and feasible intervention. Clinicians saw potential in gamification to boost motivation, support psychoeducation, and encourage self-paced learning, but they expressed concerns about possible addiction, stigma, and the complexity of gameplay for some patients. Patients spoke of gaming as a source of comfort, escapism, and social connection. Acceptance was shaped by engaging storylines, intuitive design, balanced difficulty, therapist guidance, and clear safety measures. Both groups agreed that gamification should be used in conjunction with standard treatments, be culturally sensitive, and be presented as a meaningful therapeutic approach rather than merely as entertainment. Conclusions: Gamification emerges as an acceptable and feasible supplementary approach for managing depression in Malaysia. Its success depends on culturally sensitive design, robust clinical oversight, and seamless integration with existing care pathways. Future studies should investigate long-term outcomes and establish guidelines for the safe and effective implementation of this approach. We recommend targeted investment into culturally adapted gamified tools, including training, policy development, and collaboration with key stakeholders to realistically implement gamification as a mental health intervention in Malaysia. Full article

This study examined data from participants who completed the SLeep Education for Everyone Program (SLEEP) to explore how various demographic variables affected sleep outcomes and to determine which participant characteristics predicted success. A total of 104 individuals participated. The Sleep Hygiene Index (SHI) measured undesirable sleep behaviors; the Pittsburgh Sleep Quality Index (PSQI) assessed sleep quality and self-reported sleep duration. Participant demographic information was collected at baseline. A mixed ANOVA evaluated group differences, and a multiple linear regression model identified predictors of sleep improvements. Change in SHI scores from pre- to post-intervention demonstrated a significant time × group interaction between Black and white participants (p = 0.024); further analysis indicated Black participants improved more. Better baseline scores predicted more favorable post-intervention outcomes for SHI, PSQI, and sleep duration. Fewer chronic conditions predicted better post-intervention SHI and PSQI scores. Older age also predicted better SHI scores. More favorable initial scores, fewer chronic conditions, and older age were the strongest predictors of positive outcomes following SLEEP. Improved sleep hygiene, sleep quality, and sleep duration were observed over time within subjects across all groups. In summary, SLEEP appears to be effective. Further work exploring challenges experienced by younger participants or those with multiple co-morbidities is warranted. Full article

Current work investigates the fabrication and performance of nanocomposite membranes, modified with varying concentrations of hybrid nanostructures comprising titanium nanowires coated with iron nanoparticles (TiO₂ NWs-Fe₂O₃), for the removal of Naphthol Blue Black (NBB) dye from industrial wastewater. A series of analytical tools were employed to confirm the successful modification including scanning electron microscopy and EDX analysis, porosity and hydrophilicity measurements, Fourier-transform infrared spectroscopy, and X-Ray Diffraction. The incorporation of TiO₂ NWs-Fe₂O₃ has enhanced membrane performance significantly by increasing the PWF and improving dye retention rates of nanocomposite membranes. At 0.7 g of nanostructure content, the modified membrane (M8) achieved a PWF of 93 L/m²·h and NBB dye rejection of over 98%. The flux recovery ratio (FRR) analysis disclosed improved antifouling properties, with the M8 membrane demonstrating a 73.4% FRR. This study confirms the potential of TiO₂ NWs-Fe₂O₃-modified membranes in enhancing water treatment processes, offering a promising solution for industrial wastewater treatment. These outstanding results highlight the potential of the novel PES-TiO₂ NWs-Fe₂O₃ membranes for dye removal and present adequate guidance for the modification of membrane physical properties in the field of wastewater treatment. Full article

The transition to efficient production requires innovative water control techniques to maximize irrigation efficiency and minimize waste. Analyzing and optimizing irrigation practices is essential to improve water use and reduce environmental impact. The aim of the research was to identify a discrimination method to analyze the different hydration levels in baby-leaf products. The species being researched was spinach, harvested at the baby leaf stage. Utilizing a large dataset of 261 wavelengths from the hyperspectral imaging system, the feature selection minimum redundancy maximum relevance (FS-MRMR) algorithm was applied, leading to the development of a neural network-based prediction model. Finally, a mathematical classification model K-NN (k-nearest neighbors type) was developed in order to identify a transfer function capable of discriminating the hyperspectral data based on a threshold value of absolute leaf humidity. Five significant wavelengths were identified for estimating the moisture content of baby leaves. The resulting model demonstrated a high generalization capability and excellent correlation between predicted and measured data, further confirmed by the successful training, validation, and testing of a K-NN-based statistical classifier. The construction phase of the statistical classifier involved the use of the experimental dataset and the critical humidity threshold value of 0.83 (83% of leaf humidity) was considered, below which the baby-leaf crop requires the irrigation intervention. High percentages of correct classification were achieved for data within two humidity classes. Specifically, the statistical classifier demonstrated excellent performance, with 81.3% correct classification for samples below the threshold and 99.4% for those above it. The application of advanced spectral analysis and artificial intelligence methods has led to significant progress in leaf moisture analysis and prediction, yielding substantial implications for both agriculture and biological research. Full article

Ongoing interest in the intersection of spirituality and health has prompted a need for integrated research. This report proposes a distinct approach in a model that allows for successful and harmonious cross-fertilization within these latter two areas of interest. Our work is especially pertinent to inquiries around the role of spirituality in mental health, with special attention to chronic pain conditions. The latter have become an open channel for novel avenues to explore the field of spirituality-based interventions within the arena of psychological inquiry. To address this, the authors developed and implemented the Church and Academia Model, a prototype for an innovative collaborative research project, with the aim of exploring the role of devotional practices, and their potential to be used as therapeutic co-adjuvants or tools to enhance the coping skills of patients with chronic pain. Keeping in mind that the church presents a rich landscape for clinical inquiry with broad relevance for clinicians and society at large, we created a unique hybrid research model. This is a new paradigm that focuses on distinct and well-defined studies where the funding, protocol writing, study design, and implementation are shared by experts from both the pastoral and clinical spaces. A team of theologians, researchers, and healthcare providers, including clinical pain psychologists, built a coalition leveraging their respective skill sets. Each expert is housed in their own environs, creating a functional network that has proven academically productive and pastorally effective. Key outputs include the creation and validation of a new psychometric measure, the Pain-related PRAYER Scale (PPRAYERS), an associated bedside prayer tool and a full-scale dissemination strategy through journal publications and specialty society conferences. This collaborative prototype is also an ideal fit for integrated knowledge translation platforms, and it is a promising paradigm for future collaborative projects focused on spirituality and mental health. Full article

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article

Traditional energy conservation policies have primarily relied on economic incentives and informational campaigns. However, recent insights from behavioral and social sciences indicate that subtle behavioral interventions, particularly social nudges, can significantly influence household electricity use. This paper presents a structured review of 23 recent field studies examining how social nudging strategies, such as peer comparison, group identity, and normative messaging, have contributed to measurable reductions in electricity consumption. By analyzing intervention outcomes across different regions and formats, we identify key success factors, limitations, and policy implications. Special attention is given to ethical considerations, fairness in implementation, and potential challenges in sustaining behavior change. This study offers a framework for integrating social nudges into future energy policies, emphasizing their role as low-cost, scalable tools for promoting sustainable energy behavior. Full article