bluuebunny/crossref_metadata_2025 huggingface dataset:
Positioning Method for Unmanned Aerial Vehicle (UAV) Based on Airborne Two-Dimensional Laser Doppler Velocimeter: Experiment and Dead Reckoning
Authors: Chen Lanjian , Xi Chongbin , Jin Shilong , Zhou Jian
Published: December 2024

In the autonomous navigation of drones, improving positioning accuracy is of significant importance to obtain highly accurate information on flight velocity. Traditional microwave and acoustic velocity measurement methods have the disadvantages of poor precision and susceptibility to interference. In this study, an unmanned aerial vehicle (UAV)-mounted two-dimensional laser Doppler velocimeter was developed and investigated, and a relevant drone flight navigation and positioning experiment was carried out. The UAV-mounted two-dimensional laser Doppler velocimeter (LDV) prototype developed in this study applies a scheme of dual-beam measurement light, sharing a focusing lens group. After process integration, the performance of the prototype was measured. It shows that a velocity measurement effect with a high signal-to-noise ratio can be achieved by using two measurement probe beams within a working distance range of 40 m–60 m. In the flight experiment, the flight trajectory calculated using the LDV-measured velocity data was compared with the global navigation satellite system (GNSS)-recorded trajectory. The result shows that LDV can achieve an odometer accuracy of 4.8‰. This study has validated the feasibility of the laser Doppler velocimeter in drone navigation and positioning, providing a novel method for reliable and high-precision velocity measurement in autonomous drone navigation.
Limited Impact of Drone Transport of Blood on Platelet Activation
Authors: Callewaert Nico , Pareyn Inge , Acke Tessa , Desplinter Brian , Van de Pitte Kyana , Van Vooren Joke , De Meyer Mathieu , Seeldraeyers Ellen , Peeters Frank , De Meyer Simon F , Vanhoorelbeke Karen , Tersteeg Claudia
Published: December 2024

The rapid transportation of blood samples and blood products using drones has high potential in the medical sector. However, before this can be implemented, sufficient evidence that drone transportation is not affecting clinical outcomes is needed. Currently, limited data on the stability of blood, and specifically on platelet activation, after transport using drones are available. Therefore, the impact of drone transportation on platelet activation parameters was analyzed. Blood was drawn from 20 healthy volunteers and lactate dehydrogenase (LDH), potassium, free hemoglobin, PFA-100 closure time, platelet factor 4 (PF4) plasma levels and platelet activation membrane markers were determined in blood that was transported by drone and compared to non-transported samples. In addition, a control group was included where blood samples were transported by car. Transport by both drone and car increased LDH and potassium levels, but the values mostly remained within the total allowable error. Both drone and car transportation impacted platelet activation, as indicated by a small increase in the baseline P-selectin expression and increased PF4 plasma levels. To our knowledge, this is the first study assessing the impact of drone transport on platelet activation. Transportation of blood tubes from healthy individuals using drones has only minimal impacts on blood stability and platelet activation parameters, and is comparable to blood transportation by car. Therefore, the effects observed as a result of drone transportation will likely not impact clinical decision making.
Bromelain in Burn Care: Advancements in Enzymatic Debridement and Patient Outcomes
Authors: Bordeanu-Diaconescu Eliza-Maria , Grama Sabina , Grosu-Bularda Andreea , Frunza Adrian , Andrei Mihaela-Cristina , Neagu Tiberiu-Paul , Lascar Ioan
Published: December 2024

The management of severe burns is a complex process that requires a multidimensional approach to ensure optimal healing of burn wounds, minimize complications, and improve the prognosis of patients. Surgical debridement is considered the gold standard for removing necrotic tissue; however, this approach involves risks such as bleeding, the potential removal of viable tissue during excision, and technical challenges in complex anatomical areas. Recent advancements highlight the role of enzymatic debridement using NexoBrid®, which offers a less invasive alternative to surgical excision while having the ability to selectively debride necrotic tissue and preserve viable tissue. NexoBrid® has shown efficacy in reducing debridement time, minimizing the need for additional surgeries, and improving overall wound healing outcomes. This review discusses the clinical indications, advantages, and considerations for choosing between surgical and enzymatic debridement. Emerging studies suggest the potential for enzymatic debridement to be safe and effective even for larger burn areas, making it a promising option in modern burn care. However, ongoing evaluation and integration into clinical protocols will be essential to fully realize its benefits in specialized burn treatment and to establish protocols.
Ex Situ and In Situ Conservation Approaches in Species-Rich Anatolian Steppe Ecosystem: A Case Study from Ankara, Türkiye
Authors: Duman Hayri , Doğan Murat , Atlı Özge , Celep Ferhat
Published: December 2024

Ex situ and in situ conservation are the two most important methods for preserving and sustaining natural species. However, studies that combine in situ and ex situ studies are rather scarce. Ankara, the capital of Türkiye, is a rich biodiversity hotspot with 2353 plant species, 398 of which are endemic. Due to the rapidly growing population, agricultural areas, hobby gardens, and the urban areas of the city center, many plant species, especially local endemics, are at a high risk of extinction in the immediate vicinity of the Ankara city center. Therefore, we aimed to establish a plant protection area with both ex situ and in situ conservation approaches jointly in the Kazan Soda license area in the Kahramankazan county of Ankara. In total, 185 plant taxa belonging to 43 families, 29 of which are local or regional endemic, or rare, have been protected in the area. Although most of the taxa in the protected area grow there naturally, reproductive organs or whole plants of 11 taxa have been translocated from the immediate surroundings and habitat. Detailed information about the flora of the protected area and the license area is given. We also work in the protected area to raise awareness about biodiversity and nature conservation for local people and students.
Performance and Self-Representation of Socioemotional Competencies in Preschool Children: Implication for Adaptive Developmental Outcome
Authors: Sangiuliano Intra Francesca , Taverna Livia , Incardona Roberta Maria , Tremolada Marta , Amadori Alberto , Prestera Giulia , Brighi Antonella
Published: December 2024

Developing socioemotional competence in preschool children is essential to their growth. Numerous studies have emphasized the importance of socioemotional skills in early childhood, documenting distinct patterns in socioemotional growth and identifying distinct developmental patterns that suggest gender and self-awareness can influence developmental trajectories in this domain. This study investigates the role of gender in the relationship between children’s self-representation and socioemotional performance-based outcomes, measured through objective and quantifiable assessments of their abilities and behaviors. A sample of 145 preschool children was assessed using the Test of Emotion Comprehension and the Berkeley Puppet Interview. Results indicate no significant gender or age differences in Test of Emotion Comprehension scores, while the Berkeley Puppet Interview revealed notable gender differences across all the latent socioemotional dimensions. These findings underscore the importance of considering gender and integrating self-representation into educational programs to support adaptive development and promote psychological well-being.
Auto-Trimming-Based Designs for the Test Optimization of Mass-Produced Automotive Microcontroller Unit Chip Probing Tests
Authors: Liu Qi , Zhang David Wei
Published: December 2024

High-voltage and analog measurements occupy a large amount of automated test equipment (ATE) overhead. A method for realizing trimming automation through mixed digital and analog circuits is proposed. Taking a 40 nm 1 MB Flash chip test as an example, current high-voltage and analog quantity trimming accounts for 6.9% of the total test time. Through adding digital and analog circuits to the Built-In Self-Test (BIST) circuit, the trimming test time is reduced from 2.94 s to 0.23 s, and the ratio of the total test time is reduced to 0.58%. Compared with the original chip probing (CP) total time, the total time is reduced by 6.35%, the ATE overhead accounts for 19.35% of the total test time, and the Flash area is 0.63%. The measurement accuracy reaches 750 μV~6 mV, and the measurement error is 0.15% ± 7 mV, compared with the conventional ATE trimming method.
Enhancing Smartphone Battery Life: A Deep Learning Model Based on User-Specific Application and Network Behavior
Authors: Flores-Martin Daniel , Laso Sergio , Herrera Juan Luis
Published: December 2024

Smartphones have become a central element in modern society with their widespread adoption driven by technological advancements and their ability to facilitate everyday tasks. A critical feature influencing user satisfaction and smartphone adoption is battery life, as the intensive use of mobile devices can significantly drain battery power. This paper addresses the challenge of predicting smartphone battery consumption using artificial intelligence techniques, specifically deep learning, to optimize energy efficiency. By collecting and analyzing data from mobile devices, such as application usage, screen time, network type, network usage, and battery temperature among others, we developed a predictive model tailored to user-specific behavior. This model identifies the key variables affecting battery consumption and provides personalized energy-saving strategies. Our approach offers a solution for improving battery performance, contributing to more efficient energy management in both hardware and networking terms while adapting to individual usage patterns. The results demonstrate that our approach can significantly predict the battery to anticipate power demands based on user-specific usage. While challenges remain, such as improving the generalizability of the model across different devices, this approach provides a scalable and adaptive method to improve the energy efficiency of smartphones, which will allow efficient management solutions to be suggested, contributing to better battery and network management to improve user experience and device longevity.
Streamer-to-Leader Transition Characteristics of Long Air Gap Between Sphere and Plane with Burr Defects at High Altitudes
Authors: Liu Lei , Wang Hao , Lin Guo , Zhong Zheng , Geng Jianghai
Published: December 2024

In the valve hall of the converter station of a UHV transmission project at high altitudes, the shielding sphere and the wall/floor form a large-size sphere–plane long air gap. Burr defects on the surface of the shielding sphere can affect its discharge characteristics. The streamer-to-leader transition is a key process in the discharge of the long air gap. The existing research is limited to the discharge characteristics of small-size electrodes at low altitudes and cannot be directly extended to those of large-size electrodes at high altitudes. Therefore, this paper constructs a discharge test platform with optical–electrical synchronous detection at an altitude of 2200 m. The instantaneous optical power, electric field intensity, high potential current, and other physical parameters during the discharge in the long air gap of a 1.3 m diameter sphere–plane system were collected for both a sphere electrode with burrs and one without burrs. The injection current of the initial streamer was used as the input variable and substituted into Gallimberti’s model to analyse the transformation process of the streamer stem’s vibrational energy into translational energy. A modified model that is more suitable for high altitudes was developed by taking into account convective diffusion and the thermal expansion of the streamer, and the influence of burr defects on the characteristics of the transition from streamer to leader was analysed and compared with the experimental results. Overall, burr defects reduced the duration of the streamer-to-leader transition and facilitated discharge. The analysis results generally agree with the experimental results. The research results are of great significance for the design of the valve hall insulation in converter stations at high altitudes.
A Fast Coding Unit Partitioning Decision Algorithm for Versatile Video Coding Based on Gradient Feedback Hierarchical Convolutional Neural Network and Light Gradient Boosting Machine Decision Tree
Authors: Liu Fangmei , Wang Jiyuan , Zhang Qiuwen
Published: December 2024

Video encoding technology is a foundational component in the advancement of modern technological applications. The latest standard in universal video coding, H.266/VVC, features a quad-tree with nested multi-type tree (QTMT) partitioning structure, which represents an improvement over its predecessor, High-Efficiency Video Coding (H.265/HEVC). This configuration facilitates adaptable block segmentation, albeit at the cost of heightened encoding complexity. In view of the aforementioned considerations, this paper puts forth a deep learning-based approach to facilitate CU partitioning, with the aim of supplanting the intricate CU partitioning process observed in the Versatile Video Coding Test Model (VTM). We begin by presenting the Gradient Feedback Hierarchical CNN (GFH-CNN) model, an advanced convolutional neural network derived from the ResNet architecture, enabling the extraction of features from 64 × 64 coding unit (CU) blocks. Following this, a hierarchical network diagram (HND) is crafted to depict the delineation of partition boundaries corresponding to the various levels of the CU block’s layered structure. This diagram maps the features extracted by the GFH-CNN model to the partitioning at each level and boundary. In conclusion, a LightGBM-based decision tree classification model (L-DT) is constructed to predict the corresponding partition structure based on the prediction vector output from the GFH-CNN model. Subsequently, any errors in the partitioning results are corrected in accordance with the encoding constraints specified by the VTM, which ultimately determines the final CU block partitioning. The experimental results demonstrate that, in comparison with VTM-10.0, the proposed algorithm achieves a 48.14% reduction in complexity with only a 0.83% increase in bitrate under the top-three configuration, which is negligible. In comparison, the top-two configuration resulted in a higher complexity reduction of 63.78%, although this was accompanied by a 2.08% increase in bitrate. These results demonstrate that, in comparison to existing solutions, our approach provides an optimal balance between encoding efficiency and computational complexity.
Secure Digital Rights Management in Gamified Personal Health Promotion Applications Using Attribute-Based Encryption
Authors: Hsu Chien-Lung , Lin Liang-Shiun , Lin Wei-Qian , Hsu Tzu-Liang
Published: December 2024

The rising prevalence of diseases linked to factors such as excessive alcohol and tobacco use, sedentary lifestyles, and poor nutrition has led to a greater focus on Personal Health Promotion (PHP) as a preventive measure. PHP emphasizes improving quality of life and well-being, driven by advances in medical technology, including virtual and augmented reality. However, as PHP systems grow in popularity, concerns over personal data security, such as account theft and information breaches, have become increasingly important. To address these concerns, this study proposes a game-based personalized health promotion system that integrates Key-Policy Attribute-Based Encryption (KP-ABE), key insulation, time-bound encryption. These methods ensure data security through hierarchical access control and dynamic time management, protecting personal health records and exercise prescriptions. The system also incorporates key insulation to enhance the security of private keys. This multi-layered security approach provides a robust solution for safeguarding sensitive data within PHP systems while accommodating dynamic subscription needs and legal access requirements.
Expanding Imaging of Satellites in Space (IoSiS): A Feasibility Study on the 3-Dimensional Imaging of Satellites Using Interferometry and Tomography
Authors: Hochberg Fabian , Jirousek Matthias , Anger Simon , Peichl Markus
Published: December 2024

As the need for new and advanced space situational awareness systems increases, new technologies for in situ observations are needed. The experimental IoSiS (Imaging of Satellites in Space) system at the German Aerospace Center (DLR) is already capable of high-resolution imaging tasks using inverse synthetic aperture radar technology. As two-dimensional radar images can be difficult to interpret, full three-dimensional imaging is desired. This paper extends the previously published simulation aspects to real ground-based experiments using a single spatially separated receiver, allowing interferometric measurements. However, as interferometry cannot fully resolve a three-dimensional object, more spatially separated receivers are also considered for the use of ISAR tomography to gain experimental insight into true three-dimensional imaging as IoSiS will eventually move toward a tomographic acquisition mode. The results shown here promise a high-resolution imaging method for the future development of IoSiS. Based on the research presented here, additional receivers can be implemented into IoSiS to establish real-world three-dimensional measurements of space objects.
RGB-Guided Depth Feature Enhancement for RGB–Depth Salient Object Detection
Authors: Zeng Zhihong , He Jiahao , Zhan Yue , Liu Haijun , Tan Xiaoheng
Published: December 2024

RGB-D (depth) Salient Object Detection (SOD) seeks to identify and segment the most visually compelling objects within a given scene. Depth data, known for their strong discriminative capability in spatial localization, provide an advantage in achieving accurate RGB-D SOD. However, recent research in this field has encountered significant challenges due to the poor visual qualities and disturbing cues in raw depth maps. This issue results in indistinct or ambiguous depth features, which consequently weaken the performance of RGB-D SOD. To address this problem, we propose a novel pseudo depth feature generation-based RGB-D SOD Network, named PDFNet, which can generate some new and more distinctive pseudo depth features as an extra supplement source to enhance the raw depth features. Specifically, we first introduce an RGB-guided pseudo depth feature generation subnet to synthesize more distinctive pseudo depth features for raw depth feature enhancement, since the discriminative power of depth features plays a pivotal role in providing effective contour and spatial cues. Then, we propose a cross-modal fusion mamba (CFM) to effectively merge RGB features, raw depth features, and generated pseudo depth features. We adopt a channel selection strategy within the CFM module to align the pseudo depth features with raw depth features, thereby enhancing the depth features. We test the proposed PDFNet on six commonly used RGB-D SOD benchmark datasets. Extensive experimental results validate that the proposed approach achieves superior performance. For example, compared to the previous cutting-edge method, AirSOD, our method improves the F-measure by 2%, 1.7%, 1.1%, and 2.2% on the STERE, DUTLF-D, NLPR, and NJU2K datasets, respectively.
Algal-Mediated Carbon Dioxide Separation in Biological Hydrogen Production
Authors: Eggers Natascha , Ramayampet Sachin Kumar , Birth-Reichert Torsten
Published: December 2024

The production of hydrogen via dark fermentation generates carbon dioxide, which needs to be separated and re-utilized to minimize the environmental impact. This research investigates the potential of utilizing algae for carbon dioxide sequestration in hydrogen production via dark fermentation. However, algae alone cannot fully use all the carbon dioxide produced, necessitating the implementation of a multistage separation process. This study proposes a purification approach that integrates membrane separation with a photobioreactor in a multistage design layout. Mathematical models were used to simulate the performance efficiency of multistage design layout using MATLAB 2015b (Version 9.3). A detailed parametric analysis and the key parameters influencing the separation efficiency were conducted for each stage. This study explores how reactor geometry, operational dynamics (such as gas transfer rates and light availability), and algae growth impact both CO2 removal and hydrogen purity. An optimization strategy was used to obtain the set of optimal operating and design parameters. Our results have shown a significant improvement in hydrogen purity, increasing from 55% to 99% using this multistage separation process, while CO2 removal efficiency rose from 35% to 85% over a week. This study highlights the potential of combining membrane technology with photobioreactors to enhance hydrogen purification, offering a more sustainable and efficient solution for hydrogen production.
Exploring the Effects of Synergistic Combustion of Alcohols and Biodiesel on Combustion Performance and Emissions of Diesel Engines: A Review
Authors: Zheng Fangyuan , Cho Haeng Muk
Published: December 2024

Diesel engines are extensively employed in transportation, agriculture, and industry due to their high thermal efficiency and fuel economy. However, the combustion of conventional diesel fuel is accompanied by substantial emissions of pollutants, including carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and carbon dioxide (CO2), posing significant threats to environmental quality. Biodiesel, as a renewable and cleaner alternative fuel, can significantly reduce emissions of CO, HC, and particulate matter (PM) due to its unique molecular structure. Nonetheless, its lower calorific value and poor cold-start performance limit its application, while its high oxygen content may contribute to increased NOx emissions. To address these limitations, researchers have proposed blending biodiesel with alcohol-based fuels such as methanol, ethanol, or butanol to create synergistic combustion systems that optimize engine performance and emission characteristics. This paper systematically reviews the effects of alcohol fuels on the performance and emission characteristics of biodiesel blends in diesel engines. Studies indicate that the addition of alcohol fuels can significantly enhance engine performance by improving fuel atomization, extending ignition delay, and increasing premixed combustion efficiency. These enhancements result in higher cylinder pressure, net heat release rate (HRR), and brake thermal efficiency (BTE), while reducing brake-specific fuel consumption (BSFC) to some extent. Moreover, most studies report that alcohol fuels help reduce CO, HC, smoke, and NOx emissions but tend to increase CO2 emissions. However, some findings suggest that in certain cases, the opposite results may occur. The impact of different types of alcohol fuels on performance and emissions varies significantly, requiring a comprehensive evaluation of their properties, such as latent heat, viscosity, and oxygen content. Although the appropriate addition of alcohol fuels demonstrates substantial potential for optimizing engine performance and reducing emissions, excessive blending may lead to adverse effects, necessitating careful control of the blending ratio. Future research should consider mixing two or more alcohol fuels with biodiesel to explore synergistic effects beyond the capabilities of single alcohols. Additionally, further studies should focus on optimizing fuel compositions and emission control strategies for varying operating conditions.
Economic Viability of Photovoltaic Systems Based on the Number of Floors in Modular Multi-Family Housing in Korea
Authors: Lee Seyeon , Jung Chanwoo , Ahn Yonghan
Published: December 2024

Korea is making efforts to reduce carbon emissions from buildings and, as part of this initiative, the government is promoting the expansion of modular housing. This study analyzed the feasibility of achieving zero-energy certification and the economic viability of applying photovoltaic (PV) systems to modular housing in Korea. Energy consumption and self-sufficiency were calculated for low-rise (4 floors), mid-rise (13 floors), and high-rise (30 floors) buildings. Economic viability was assessed according to the payback period, net present value (NPV), and benefit–cost ratio (B/C ratio). Construction costs of modular buildings are higher than those of reinforced concrete (RC) buildings, and when only PV systems are applied, it is not possible to achieve a high grade in high-rise buildings. The results indicate that economic feasibility is lacking across all building heights, leading to the conclusion that further research on cost reduction and expanded government support are necessary. This study presents a sustainable building model for Korea that is expected to contribute to future policy decisions.
Photochemical Degradation of Some Halogenated Anesthetics in Air
Authors: Srinivasan Shruthi , Kaur Amandeep , Moralejo Carol , Anderson William A.
Published: December 2024

Anesthetic gases enter the environment primarily through patient exhalation and venting from scavenging systems directly into the atmosphere. Emissions of halogenated anesthetic gases like halothane, isoflurane and sevoflurane are of concern due to their high global warming potential, highlighting the need to mitigate their environmental impact. Photocatalytic oxidation has been proposed as a potential option for emission control and indoor air treatment, but data on its use for various halogenated anesthetics is very limited. In this work, photocatalytic oxidation efficiency for the degradation of halothane was studied by varying the method for catalyst support and catalyst mass loading. Approximately 99.9% of halothane (1296 mg/m3) in air was degraded with a TiO2 photocatalyst under UVC light (254 nm) in 35 min in a recirculating batch photoreactor. The optimized conditions for halothane demonstrated a similar although faster photocatalytic degradation efficiency for isoflurane (99.8% in 20 min, 911 mg/m3) and sevoflurane (>98% in 10 min, 847 mg/m3). The results presented here suggest that a UV–photocatalysis is a promising technique to treat such anesthetic gases before being released into the environment by scavenging systems, although significant work remains to identify the potential by-products and optimal photoreactor designs for efficient long-term operation.
Effects of Downed Log Decomposition on Soil Properties and Enzyme Activities in Southwest China
Authors: Liu Tingting , Xu Chenzhan , Lu Zhiyun , Wang Hang , Guo Huijun
Published: December 2024

Downed logs play crucial roles in carbon and nutrient cycling within forest ecosystems, influencing soil nutrients and revealing their functional roles in these environments. This study focuses on an evergreen broadleaf forest at Ailaoshan Station for Subtropical Forest Ecosystem Studies, Yunnan, and specifically examines three dominant tree species whose logs are heavily decayed: Lithocarpus xylocarpus (L. xylocarpus), Lithocarpus hancei (L. hancei), and Castanopsis wattii (C. wattii). Soil samples were collected from three depths (0–10 cm, 10–20 cm, and 20–30 cm) beneath the downed logs and from control plots without downed logs. The physicochemical properties and enzyme activities of these soils were analyzed to explore the effects of downed log decomposition on the soil properties. The results revealed several key findings: (1) Downed logs significantly increased the soil organic carbon (SOC) and total nitrogen (TN) content in the surface soil (0–10 cm), with the SOC and TN contents under L. xylocarpus logs being 368.20% and 65.32% higher than those in the CK plots, respectively, substantially increasing soil nutrient accumulation. (2) Downed log decomposition significantly increased the soil enzyme activities, with the highest activities observed in the surface soil (0–10 cm) under L. xylocarpus. In deeper soil layers (20–30 cm), L. xylocarpus and C. wattii still presented higher enzyme activities than those in the CK plots did (p < 0.05). (3) The SOC, TN, and C/N were significantly positively correlated (r > 0.95 and p < 0.01), whereas the correlations were weak or nonexistent in the CK plots. The release of organic acids from downed logs enhanced the microbial activity, significantly reducing the soil pH (p < 0.05). (4) Different tree species exhibited distinct effects during downlog decomposition, with L. xylocarpus showing the most significant improvements in the SOC, TN, and enzyme activities, followed by C. wattii, whereas L. hancei limited carbon accumulation due to faster nitrogen release, resulting in a relatively lower C/N. Overall, this study demonstrated that the interaction between downed log decomposition and soil enzyme activity plays a key role in improving soil fertility and promoting nutrient cycling. This research provides evidence for understanding the impact of downed logs on forest soil ecological functions and microbial functional activity and their role, thereby contributing valuable insights into carbon cycling in subtropical forest ecosystems.
Geography and the Environment Shape the Landscape Genetics of the Vulnerable Species Ulmus lamellosa in Northern China
Authors: Liu Li , Shen Yuexin , Zhang Yimeng , Gao Ting , Wang Yiling
Published: December 2024

A comprehensive understanding of the pattern of genetic variation among populations and adaptations to environmental heterogeneity is very important for conservation and genetic improvement. Forest tree species are ideal resources for understanding population genetic differentiation and detecting signatures of selection due to their adaptations to heterogeneous landscapes. Ulmus lamellosa is a tree species that is endemic to northern China. In this study, using restriction-site-associated DNA sequencing (RAD-seq) data, 12,179 single-nucleotide polymorphisms were identified across 51 individuals from seven populations. There was a high level of genetic diversity and population differentiation in U. lamellosa. Population genetic structure analyses revealed a significant genetic structure related to the configuration of the mountains. Additionally, we found that the isolation-by-distance pattern explained the genetic differentiation best, and environmental heterogeneity also played a role in shaping the landscape genetics of this species inhabiting mountain ecosystems. The FST-based outlier and genotype–environment association approaches were used to explore the genomic signatures of selection and local adaptation and detected 317 candidate outlier loci. Precipitation seasonality (coefficient of variation), precipitation in the driest month, and enhanced vegetation index were important determinants of adaptive genetic variation. This study provides abundant genetic resources for U. lamellosa and insights into the genetic variation patterns among populations.
Evaluation of Correction Algorithms for Sentinel-2 Images Implemented in Google Earth Engine for Use in Land Cover Classification in Northern Spain
Authors: Teijido-Murias Iyán , Barrio-Anta Marcos , López-Sánchez Carlos A.
Published: December 2024

This study examined the effect of atmospheric, topographic, and Bidirectional Reflectance Distribution Function (BRDF) corrections of Sentinel-2 images implemented in Google Earth Engine (GEE) for use in land cover classification. The study was carried out in an area of complex orography in northern Spain and made use of the Spanish National Forest Inventory plots and other systematically located plots to cover non-forest classes. A total of 2991 photo-interpreted ground plots and 15 Sentinel-2 images, acquired in summer at a spatial resolution of 10–20 m per pixel, were used for this purpose. The overall goal was to determine the optimal level of image correction in GEE for subsequent use in time series analysis of images for accurate forest cover classification. Particular attention was given to the classification of cover by the major commercial forest species: Eucalyptus globulus, Eucalyptus nitens, Pinus pinaster, and Pinus radiata. The Second Simulation of the Satellite Signal in the Solar Spectrum (Py6S) algorithm, used for atmospheric correction, provided the best compromise between execution time and image size, in comparison with other algorithms such as Sentinel-2 Level 2A Processor (Sen2Cor) and Sensor Invariant Atmospheric Correction (SIAC). To correct the topographic effect, we tested the modified Sun-canopy-sensor topographic correction (SCS + C) algorithm with digital elevation models (DEMs) of three different spatial resolutions (90, 30, and 10 m per pixel). The combination of Py6S, the SCS + C algorithm and the high-spatial resolution DEM (10 m per pixel) yielded the greatest precision, which demonstrated the need to match the pixel size of the image and the spatial resolution of the DEM used for topographic correction. We used the Ross-Thick/Li-Sparse-Reciprocal BRDF to correct the variation in reflectivity captured by the sensor. The BRDF corrections did not significantly improve the accuracy of the land cover classification with the Sentinel-2 images acquired in summer; however, we retained this correction for subsequent time series analysis of the images, as we expected it to be of much greater importance in images with larger solar incidence angles. Our final proposed dataset, with image correction for atmospheric (Py6S), topographic (SCS + C), and BRDF (Ross-Thick/Li-Sparse-Reciprocal BRDF) effects and a DEM of spatial resolution 10 m per pixel, yielded better goodness-of-fit statistics than other datasets available in the GEE catalogue. The Sentinel-2 images currently available in GEE are therefore not the most accurate for constructing land cover classification maps in areas with complex orography, such as northern Spain.
Beat the Heat: Stay or Stray? Exploring the Connection of Extreme Temperature Events, Green Space, and Impervious Surfaces in European Cities
Authors: Halecki Wiktor
Published: December 2024

In urban areas prone to extreme weather, it has become crucial to implement effective strategies to improve living conditions for residents reliant on medical and educational facilities. This research highlighted the importance of urban green spaces in cooling European cities and examined the planning and maintenance of these areas alongside economic losses due to water consumption during heatwaves. Key findings using an SEM (structural equation model) showed that hot summer days indirectly impacted water prices by increasing cumulative temperature days. The confidence interval (0.015, 0.038) confirmed this effect. Additionally, tropical nights indirectly impacted water prices, as shown by the cooling degree days, which indicated the need for air conditioning. The increased use of energy for cooling resulted in higher water prices due to the water required for power generation. This effect was statistically significant, with an estimated value of 0.029 (p < 0.001). A generalized linear model (GLM) indicated an inverse relationship between urban green space and impervious surfaces (slope: −0.69996 ± 0.025561, intercept: 53.675 ± 0.97709, p < 0.01), which was important for reducing impervious surfaces and improving water management, ultimately leading to cooler urban temperatures. Practical recommendations for decision-makers, urban planners, and residents are provided to adapt to changing extreme weather conditions. These include improving the soil environment in current locations and increasing access to green spaces, which can enhance well-being and address health issues.
An International Perspective on the Status of Wildlife in Türkiye’s Sustainable Forest Management Processes
Authors: Uyar Çağdan , Perkumienė Dalia , Škėma Mindaugas , Aleinikovas Marius
Published: December 2024

Ensuring the sustainability of forests is among the priority measures to be taken against the decline in biodiversity, which is among the world’s increasingly common concerns. This study investigated whether sustainable forest management processes are considering wildlife conservation objectives. Ten forest management processes were categorized and then analyzed for whether wildlife conservation is adequately considered. The wildlife data were grouped into four categories, with the most common being the protection of biodiversity and wildlife trade. The satisfaction level obtained according to the scoring method used was determined as the criterion of success in wildlife conservation. According to the scoring method applied, the overall success was found to be 50%. It was determined that a standard should be developed regarding the economic value of wildlife fauna and flora species and that this issue should be included in sustainable forest management strategies. Only 20 of 116 total sustainable forest management criteria considered wildlife. The African Timber Organization process, which has the most member countries, was identified as the process with the lowest number of wildlife criteria, at 2%, while the International Tropical Timber Organization process was found to have the most wildlife protection criteria at 20%. The conservation success rates for the two processes of which Türkiye is a member were also found to be quite low. It is concluded that there is a need to strengthen the place of wildlife, one of the most important living components for forests, in SFM processes both for Türkiye and internationally. The results obtained were evaluated both in terms of international criteria and practices in Türkiye. It is also recommended that future international meetings include wildlife health and diversity as a separate criterion when determining sustainable methods.
Continuous Production of Chitin Oligosaccharides Utilizing an Optimized Enzyme Production-Adsorption-Enzymolysis-Product Separation (EAES) System
Authors: Zhou Xiuling , Huang Yang , Liu Yuying , Pan Delong , Zhang Yang
Published: December 2024

Chitin oligosaccharide (CHOS) is a chitin derivative with excellent biological activities. Enzymatic hydrolysis of chitin-rich biomass into CHOS is a hot topic in research on the high-value utilization of chitin resources. The disadvantages of complex preparation and purification processes and the high cost of chitin-degrading enzymes limit large-scale enzymatic production and application of CHOS. In this study, the activity of chitinase increased from 1.8 U/mL to 3.52 U/mL by 94.4% after optimizing the carbon and nitrogen source of Chitiniphilus sp. LZ32 fermentation. An enzyme production-adsorption-enzymolysis-product separation (EAES) system was constructed using fermentation, an adsorption purification module, and a product ultrafiltration module of a chitin-degrading enzyme. CHOS production by continuous enzymatic hydrolysis was performed in an EAES system using housefly larval powder (HLP) as the substrate. After the C. sp. LZ32 fermentation broth was circulated in the adsorption module for 90 min, the adsorption rate of the chitin-degrading enzyme reached more than 90%. The ultrafiltration module effectively separated CHOS at an operating pressure of 2 bar. Four batches of CHOS were produced in the EAES system using repeated batch fermentation. The running time of a single batch decreased from 115 h in the first batch to 48 h, and the CHOS output of each batch gradually increased. The total CHOS output was 61 g, and the production efficiency was 0.24 g/h. The CHOS produced by the EAES system (ECHOS) has high antioxidant activity. In this study, the EAES system was used to simplify the purification and separation steps of CHOS preparation, and the continuous production of CHOS was realized, which has potential application prospects in the field of green CHOS production.
Advances in Research on Beverages, Food, Yeast and Brewing
Authors: Nwaiwu Ogueri
Published: December 2024

This closing Editorial marks the end of three volumes of this Special Issue (SI), which covered themes like changes in reactants and products, chemistry, sensory properties, microbiology, transcriptomics, proteomics and metabolomics, food safety, and nutrition [...]
The Care of Appendicular Peritonitis in the Era of Antibiotic Resistance: The Role of Surgery and the Appropriate Antibiotic Choice
Authors: Di Mitri Marco , Collautti Edoardo , Thomas Eduje , Di Carmine Annalisa , Veronesi Giulio , Cravano Sara Maria , D’Antonio Simone , Ambretti Simone , Campoli Caterina , Bisanti Cristian , Ruspi Francesca , Manghi Ilaria , Parente Giovanni , Libri Michele , Gargano Tommaso , Lima Mario
Published: December 2024

Purpose: Acute appendicitis (AA), classified as non-complicated acute appendicitis (NCAA) and complicated acute appendicitis (CAA), is the most common cause of abdominal pain in children requiring surgical treatment. If the first-line treatment for NCAA is to be debated between conservative management and surgery, authors find a consensus in choosing surgery as the first step for CAA in children. In the case of patients with CAA undergoing surgery, a broad-spectrum antibiotic therapy should be administered to reduce the risk of post-operative complications (POC). The rise in antibiotic resistance requires a review of recent data regarding bacterial species involved in AA. The primary aim of our study was to investigate the clinical effectiveness of different antibiotic protocols in patients undergoing surgery for CAA. The secondary aim was to verify the antibiotic’s in vitro effectiveness based on cultural examinations. Methods: A retrospective and prospective study was conducted on all patients operated on at our pediatric surgery department for CAA from January 2017 to January 2023. The following data were collected: age at surgery, sex, surgical technique, duration of the procedure, antibiotic therapy, duration of the hospital stay, cultural examination of peritoneal effusion, and POC. Results: We divided the patients enrolled (n = 182) into three groups of antibiotic protocols; only one group resulted in a statistically significant lower rate of POC. Different pathogens were isolated (Enterobacteriaceae, non-fermentative Gram-negative bacilli, anaerobes, Gram-positive cocci), and the in vitro rate of antimicrobial sensitivity varied from 40% to 94% in the three groups of patients. Conclusions: Based on cultural examinations, our study showed a high rate of inadequacy regarding the therapy with amoxicillin + clavulanic acid despite a low rate of complications. Radical surgery seems to be the best way to reduce complications in children with CAA.
Influence of Animal Manure Extracts on Physico-Chemical and Nutritional Quality of Tomatoes Grown in Soilless Cultivation
Authors: Luthuli Ayanda , Magwaza Lembe , Tesfay Samson , Magwaza Shirly , Mditshwa Asanda
Published: December 2024

In response to environmental challenges facing the agricultural sector, growers are moving toward innovative and sustainable cultivation methods such as the hydroponic production system. This study evaluated the effect of different sources of manure on the physico-chemical and nutritional qualities of tomatoes (cv. CLX 532) grown under a hydroponic system. The experiment was set up in a completely randomized design with four treatments, which included three types of animal manure-derived hydroponic nutrient extracts, namely, chicken (CHME), cow (CME) and goat (GME), and a commercial fertilizer as a control. Tomato fruit from each treatment were harvested and analysed for macro- and micronutrients, physicochemical attributes such as total soluble solids (TSS), titratable acidity (TA), total soluble solid to titratable acidity ratio (TSS/TA), BrimA, colour index and firmness. The total phenolics and ascorbic acid content were also assessed. The results showed significant differences in physico-chemical and nutritional quality among different treatments. TSS was higher in CHME (6.47 °Brix) compared to other treatments. The TA was higher in both commercial fertilizer and CHME (0.62% and 0.61%) than in GME and CME (0.44% and 0.39%). Both TSS/TA and BrimA were lower in commercial fertilizer and than in animal manure extracts (AME). CHME had a higher colour index (30.32) while GME had higher firmness (316.9 N) than other treatments. The phenolic content was notably higher in GME compared to the commercial fertilizer and AME. Fruit fertigated with commercial fertilizer had more macronutrient content while fruit fertigated with animal manure-based nutrient solutions had high micronutrients. Based on these findings, animal manure extracts, specifically CHME and GME, can be used as a nutrient source in the production of tomatoes as it produces good fruit quality which is comparable to commercial fertilizers.
Revolutionizing Patient Safety: The Economic and Clinical Impact of Artificial Intelligence in Hospitals
Authors: Epelde Francisco
Published: December 2024

Artificial intelligence (AI) has emerged as a transformative force in enhancing patient safety within hospital settings. This perspective explores the various applications of AI in improving patient outcomes, including early warning systems, predictive analytics, process automation, and personalized treatment. We also highlight the economic benefits associated with AI implementation, such as cost savings through reduced adverse events and improved operational efficiency. Moreover, the perspective addresses how AI can enhance pharmacological treatments, optimize diagnostic testing, and mitigate hospital-acquired infections. Despite the promising advancements, challenges related to data quality, ethical concerns, and clinical integration remain. Future research directions are proposed to address these challenges and harness the full potential of AI in healthcare.