Search Results (4,319)

Background/Objectives: Scars are formed from trauma to the dermis and more specifically during the wound-healing phase. Skin needling is a technique used in scar therapy which stimulates the skin to regenerate. The aim of this study was to objectively and subjectively evaluate the degree of scar reduction after skin needling treatments based on visible changes using specialized measuring devices—ultrasound, Courage & Khazaka, and standardized questionnaires. Methods: Six patients were enrolled. Participants were given a series of three skin needling treatments. Before and after the treatment, the participants were examined for selected skin parameters with the help of specialized measuring devices such as Courage & Khazaka and skin ultrasound. Skin firmness and elasticity and MEP and HEP skin echogenicity were taken into account. Each patient completed POSAS questionnaires on satisfaction, pain, and adverse effects. Results: Based on the results of the POSAS questionnaire, a significant improvement in patients’ scar evaluation was observed after the treatment. Patients reported the most noticeable improvements in parameters such as color (p = 0.035), stiffness (p = 0.009), thickness (p = 0.041), and irregularity (0.007). An improvement in scar elasticity was observed in all subjects after treatment. Conclusions: Skin needling treatment combined with the skin needling technique and post-treatment skincare is an effective method of scar therapy, and the risk of side effects or complications after a series of treatments is low. Full article

This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and Eastern European (CEE) countries, over the period 2019–2023, were evaluated to determine the degree of convergence of the following four measurable qualitative characteristics: relevance, exact representation, comparability and understandability. The main objective is to identify consistency in the quality of accounting information based on the application of an international financial reporting framework. The applied methodology eliminates subjective variability by implementing a standardized scoring system, aligned with the criteria developed by NiCE, using libraries such as spaCy and NLTK for term extraction, respective sentiment analysis and word frequency evaluation. The results reveal significant heterogeneity in all characteristics examined, with statistical tests confirming substantial differences between countries. The investigation of relevance revealed partial convergence, with three dimensions achieving complete uniformity, while the exact representation showed the highest variability. The assessment of comparability showed a significant difference between countries’ extreme values, and in terms of comprehensibility a formalistic approach was evident, with technical dimensions outweighing user-oriented aspects. The overall quality index varied significantly across countries, with a notable average deterioration in 2023, indicating structural vulnerabilities in financial reporting systems. These findings support initial hypotheses on the lack of homogeneity in the quality of financial reporting in the selected region, despite the implementation of international standards. Full article

The windowpane oyster (Placuna placenta) is common in coastal areas of the Philippines, thriving in brackish waters. Its shells underpin the local craft industries. While its meat is edible, only small amounts are consumed locally, most going to waste. Utilization of this potential nutrient source is hindered by the lack of information concerning its organic and mineral content, the possible presence of heavy metal ions, and the risk of microbial pathogens. We report extensive analysis of the meat from Placuna placenta, harvested during three different seasons to account for potential variations. This comprises proximate analysis, mineral, antioxidant, and microbial analyses. While considerable seasonal variation was observed, the windowpane oyster was found to be a rich source of protein, fats, minerals, and carbohydrates, comparing well with the meats of other shellfish and land animals. Following pre-cooking (~90 °C, 25–30 min), the standard local method for food preparation, no viable E. coli or Salmonella sp. were detected. Mineral content was broadly similar to that reported in fish, although iron, zinc, and copper were more highly represented, nevertheless, heavy metals were below internationally acceptable levels, with the exception of one of three samples, which was slightly above the only current standard, FSANZ. Whether the arsenic was in the safer organic form, which is commonly the case for shellfish, or the more toxic inorganic form remains to be established. This and the variation of arsenic over time will need to be considered when developing food products. Overall, the meat of the windowpane oyster is a valuable food resource and its current (albeit low-level) use should lower any barriers to its acceptance, making it suitable for commercialization. The present data support its development for high-value food products in urban markets. Full article

While horizontal roughing filters (HRFs) remain widely acclaimed for their exceptional efficiency in water treatment, especially in developing countries, they are inherently susceptible to clogging, which necessitates timely maintenance interventions. Conventional methods for managing clogging in HRFs typically involve evaluating filter head loss coefficients against established water quality standards. This study utilizes artificial neural network (ANN) for the prediction of clogging duration and effluent turbidity in HRF equipment. The ANN was configured with two outputs, the clogging duration and effluent turbidity, which were predicted concurrently. Effluent turbidity was modeled to enhance the network’s learning process and improve the accuracy of clogging prediction. The network steps of the iterative training process of ANN used different types of input parameters, such as influent turbidity, filtration rate, pH, conductivity, and effluent turbidity. The training, in addition, optimized network parameters such as learning rate, momentum, and calibration of neurons in the hidden layer. The quantities of the dataset accounted for up to 70% for training and 30% for testing and validation. The optimized structure of ANN configured in a 4-8-2 topology and trained using the Levenberg–Marquardt (LM) algorithm achieved a mean square error (MSE) of less than 0.001 and R-coefficients exceeding 0.999 across training, validation, testing, and the entire dataset. This ANN surpassed models of scaled conjugate gradient (SCG) and obtained a percentage of average absolute deviation (%AAD) of 9.5. This optimal structure of ANN proved to be a robust tool for tracking the filter clogging duration in HRF equipment. This approach supports proactive maintenance and operational planning in HRFs, including data-driven scheduling of backwashing based on predicted clogging trends. Full article

Objective: Cervical pregnancy (CP) accounts for less than 1% of all ectopic pregnancies. The standard of management for CP is still under detailed investigation; however, among the known treatment methods, super-selective uterine artery embolization (UAE) and the use of methotrexate (MTX) have emerged as effective and minimally invasive options in recent years. Our aim is to present our center’s experience and provide available evidence evaluating the efficacy of UAE in the treatment of CP. Materials and Methods: This single-center and retrospective study evaluated the procedural and clinical outcomes of patients with CP who underwent endovascular uterine embolization with MTX between 2017 and 2024. Both procedural and clinical efficacy and safety, as well as the rate of complications and long-term outcomes, were noted. Results: A total of nine patients were diagnosed with CP (imaging examination included transvaginal ultrasound and/or magnetic resonance imaging) and referred for endovascular treatment. The mean age of the patients was 36.7 years, and the mean gestational age on admission was 9 weeks. In all cases, selective catheterization of supplying vessels and subsequent embolization with a mixture of methotrexate and gel sponge was carried out. The technical success rate was 100% with no complications. Follow-up ultrasound confirmed the disappearance of the flow signal around the intracervical gestational sac in all cases. Conclusions: In conclusion, this retrospective study demonstrated the procedural and clinical safety and efficacy of uterine artery embolization in patients with cervical pregnancy. This is why endovascular therapy should be proposed to these individuals and be included in treatment options discussed during multidisciplinary boards. Full article

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

The Research Integrity Risk Index (RI²), introduced as a tool to identify universities at risk of compromised research integrity, adopts an overly reductive methodology by combining retraction rates and delisted journal proportions into a single, equally weighted composite score. While its stated aim is to promote accountability, this commentary critiques the RI² index for its flawed assumptions, lack of empirical validation, and disproportionate penalization of institutions in low- and middle-income countries. We examine how RI² misinterprets retractions, misuses delisting data, and fails to account for diverse academic publishing environments, particularly in Indonesia, where many high-performing universities are unfairly categorized as “high risk” or “red flag.” The index’s uncritical reliance on opaque delisting decisions, combined with its fixed equal-weighting formula, produces volatile and context-insensitive scores that do not accurately reflect the presence or severity of research misconduct. Moreover, RI² has gained significant media attention and policy influence despite being based on an unreviewed preprint, with no transparent mechanism for institutional rebuttal or contextual adjustment. By comparing RI² classifications with established benchmarks such as the Scimago Institution Rankings and drawing from lessons in global development metrics, we argue that RI², although conceptually innovative, should remain an exploratory framework. It requires rigorous scientific validation before being adopted as a global standard. We also propose flexible weighting schemes, regional calibration, and transparent engagement processes to improve the fairness and reliability of institutional research integrity assessments. Full article

Evaluating the renewable energy potential, such as that of solar photovoltaics (PV), is important for developing renewable energy policies. This study investigated rooftop solar PV potential in Thailand based on open-source geographic information system (GIS) building footprints, solar PV power output, and the most recent land use data (2022). GIS-based overlay analysis, buffering, fishnet modeling, and spatial join operations were applied to assess rooftop availability across various building types, taking into account PV module installation parameters and optimal panel orientation. Economic feasibility and sensitivity analyses were conducted using standard economic metrics, including net present value (NPV), internal rate of return (IRR), payback period, and benefit–cost ratio (BCR). The findings showed a total rooftop solar PV power generation potential of 50.32 TWh/year, equivalent to 25.5% of Thailand’s total electricity demand in 2022. The Central region contributed the highest potential (19.59 TWh/year, 38.94%), followed by the Northeastern (10.49 TWh/year, 20.84%), Eastern (8.16 TWh/year, 16.22%), Northern (8.09 TWh/year, 16.09%), and Southern regions (3.99 TWh/year, 7.92%). Both commercial and industrial sectors reflect the financial viability of rooftop PV installations and significantly contribute to the overall energy output. These results demonstrate the importance of incorporating rooftop solar PV in renewable energy policy development in regions with similar data infrastructure, particularly the availability of detailed and standardized land use data for building type classification. Full article

Ensuring the safe operation of Unmanned Aerial Vehicles (UAVs) is crucial for both mission-critical and safety-critical tasks. In scenarios where UAVs must track airborne targets, they need to follow the target’s path while maintaining a safe distance, even in the presence of unmodeled dynamics and environmental disturbances. This paper presents a novel collision avoidance strategy for dynamic quadrotor UAVs during target-tracking missions. We propose a safety controller that combines a learning-based Control Barrier Function (CBF) with standard sliding mode feedback. Our approach employs a neural network that learns the true CBF constraint, accounting for wind disturbances, while the sliding mode controller addresses unmodeled dynamics. This unified control law ensures safe leader-following behavior and precise trajectory tracking. By leveraging a learned CBF, the controller offers improved adaptability to complex and unpredictable environments, enhancing both the safety and robustness of the system. The effectiveness of our proposed method is demonstrated through the AirSim platform using the PX4 flight controller. Full article

The countries and regions along the Belt and Road are rich in wetland carbon sink resources, crucial for mitigating greenhouse gas emissions and achieving global emission reduction. This paper uses policy analysis and desk research to analyze the overview of wetland carbon sinks in these countries. It explores the necessity of legal system construction for their carbon sink trading. This study finds that smooth trading requires clear property rights definition rules, efficient market trading entities, definite carbon sink trading price rules, financial support aligned with the Equator Principles, and support from biodiversity-compatible environmental regulatory principles. Currently, there are still obstacles in wetland carbon sink trading in the Belt and Road, such as property rights confirmation, an accounting system, an imperfect market trading mechanism, and the coexistence of multiple trading risks. Therefore, this paper first proposes to clarify the goal of the legal guarantee mechanism. Efforts should focus on promoting a consensus on wetland carbon sink ownership and establishing a unified accounting standard system; simultaneously, the relevant departments should conduct field investigations and monitoring, standardize the market order, and strengthen government financial support and funding guarantees. Full article

The Surface Water and Ocean Topography (SWOT) mission provides unprecedented high-resolution observations of sea-surface height. However, their direct use in ocean circulation studies is complicated by the presence of small-scale unbalanced motion signals and instrumental noise, which hinder accurate estimation of geostrophic velocities. To address these limitations, we developed an adaptive convolutional neural network (CNN)-based filtering technique that refines SWOT-derived sea-level observations. The network includes multi-head attention layers to exploit information on concurrent wind fields and standard altimetry interpolation errors. We train the model with a custom loss function that accounts for the differences between geostrophic velocities computed from SWOT sea-surface topography and simultaneous in-situ drifter velocities. We compare our method to existing filtering techniques, including a U-Net-based model and a variational noise-reduction filter. Our adaptive-filtering CNN produces accurate velocity estimates while preserving small-scale features and achieving a substantial noise reduction in the spectral domain. By combining satellite and in-situ data with machine learning, this work demonstrates the potential of an adaptive CNN-based filtering approach to enhance the accuracy and reliability of SWOT-derived sea-level and velocity estimates, providing a valuable tool for global oceanographic applications. Full article

This study explores how corporate governance reforms can enhance financial reporting quality and organizational transparency, focusing on Greece’s transition from Law 3016/2002 to Law 4706/2020. The legislative reform aimed to modernize governance structures, align national practices with international standards, and strengthen investor protection in a post-crisis economic environment. Moving beyond a simple legal comparison, the study examines how Law 3016/2002’s formal compliance model contrasts with Law 4706/2020’s more substantive accountability framework. We hypothesize that Law 4706/2020 introduces substantively stronger governance mechanisms than its predecessor, thereby improving transparency and investor protection, while compliance with the new law imposes materially greater administrative and financial burdens, especially on small- and mid-cap firms. Methodologically, the research employs a narrative literature review and a structured comparative legal analysis to assess the administrative and financial implications of the new law for publicly listed companies, focusing on board composition and diversity, internal controls, suitability policies, and disclosure requirements. Drawing on prior comparative evidence, we posit that Law 4706/2020 will foster governance and disclosure improvements, enhanced oversight, and clearer board roles. However, these measures also impose compliance burdens. Due to the heterogeneity of listed companies and the lack of firm-level data following Law 4706/2020’s implementation, the findings are neither fully generalizable nor quantifiable; future quantitative research using event studies or panel data is required to validate the hypotheses. We conclude that Greece’s new framework is a critical step toward sustainable corporate governance and more transparent financial reporting, offering regulators, practitioners, and scholars examining legal reform’s impact on governance effectiveness and financial reporting integrity. Full article

Articulated arm coordinate measuring machines are designed for in situ use directly in manufacturing environments, enabling efficient dimensional control outside of climate-controlled laboratories. This study investigates the influence of ambient temperature variation on the accuracy of length measurements performed with the Hexagon Absolute Arm 8312. The experiment was carried out in a laboratory setting simulating typical shop floor conditions through controlled temperature changes in the range of approximately 20–31 °C. A calibrated steel gauge block was used as a reference standard, allowing separation of the influence of the measuring system from that of the measured object. The results showed that the gauge block length changed in line with the expected thermal expansion, while the articulated arm coordinate measuring machine exhibited only a minor residual thermal drift and stable performance. The experiment also revealed a constant measurement offset of approximately 22 µm, likely due to calibration deviation. As part of the study, an uncertainty budget was developed, taking into account all relevant sources of influence and enabling a more realistic estimation of accuracy under operational conditions. The study confirms that modern carbon composite articulated arm coordinate measuring machines with integrated compensation can maintain stable measurement behavior even under fluctuating temperatures in controlled environments. Full article

Aiming at the problems of the high multiple- and missed-seeding index and low operation efficiency of current mechanical potato seed-meters in minituber sowing, this study designed an air-suction roller-type minituber seed-metering device for minitubers (mass between 2 and 4 g) in accordance with the agronomic standards for potato cultivation in the single-cropping area of northern China. An account of the device’s structure and operational principle was made, its working process was theoretically analysed, and the three main factors affecting the airflow suction were determined: the seed roller speed, the suction seeding hole diameter, and the air inlet negative pressure. This study adopted the fluid dynamics simulation method and determined that the ideal location of the air inlet was 30° for horizontal inclination and 60° for vertical inclination. Then, based on the CFD-DEM fluid-structure coupling simulation method, the impact of a range of factors on the functionality of the seed-metering device under different conditions was studied and verification tests were carried out. Design-Expert was used to analyse test results. The results showed that when the pressure at the air inlet was −7000 Pa, the speed of the seeding roller was 40.2 r·min⁻¹, the suction seeding hole diameter was 10.37 mm, and the performance was optimal: the qualified index was 92.95%, the multiple-seeding index was 4.16%, and the missed-seeding index was 2.89%. The research results show that the seed-metering device developed under this scheme exhibited satisfactory seeding performance during operation and was able to meet the demands of minituber sowing. Full article

To date, few studies have been published for cities in Germany that take into account climate change and changing hydrologic patterns due to increases in building density. This study investigates the efficiency of LID for past and future climate in the polycentric agglomeration area Frankfurt, Main (Central Germany) using observed and projected climate (model) data for a standard reference period (1961–1990) and a high emission scenario (RCP 8.5) as well as a climate protection scenario (RCP 2.6), under 40 to 75 percent building density. LID elements included green roofs, permeable pavement and bioretention cells. SWMM₅ was used as model for simulation purposes. A holistic evaluation of simulation results showed that effectiveness increases incrementally with LID implementation percentage and inverse to building density if implemented onto at least 50 percent of available impervious area. Building density had a higher adverse effect on LID efficiency than climate change. The results contribute to the understanding of localized effects of climate change and the implementation of adaption strategies to that end. The results of this study can be helpful for the scientific community regarding future investigations of LID implementation efficiency in dense residential areas and used by local governments to provide suggestions for urban water balance revaluation. Full article