bluuebunny/crossref_metadata_2025 huggingface dataset:
Metabolomic analysis of the impact of red ginseng on equine physiology
Authors: Kwak Young Beom , Stambler Ilia , Yoo Hye Hyun , Yoon Jungho
Published: September 2024

Introduction

Red ginseng (RG), a traditional herbal remedy, has garnered attention owing to its diverse health benefits resulting from its complex composition. However, extensive research is needed to substantiate the efficacy of RG and understand the underlying mechanisms supporting these benefits. This study aimed to identify potential biomarkers and investigate the impact of RG on related metabolic pathways in horse plasma using liquid chromatography–mass spectrometry (LC–MS)-based metabolomics.

Methods

Ten horses were divided into control and RG groups, with the latter administered RG at a dose of 600 mg⋅kg−1⋅day−1 for 3 weeks. Subsequently, the plasma samples were collected and analyzed using LC–MS. Multivariate statistical analysis, volcano plots, and feature-based molecular networking were employed.

Results

The analysis identified 16 metabolites that substantially decreased and 21 metabolites that substantially increased following RG consumption. Among the identified metabolites were oleanolic acid, ursolic acid, and ginsenoside Rb1, which are known for their antioxidant and anti-inflammatory properties, as well as lipid species that influence sphingolipid and glycerophospholipid metabolism. Additionally, potential biomarkers, including major RG components, demonstrated distinct group clustering in principal component analysis and partial least squares-discriminant analysis, indicating their utility in assessing the physiological effects of RG consumption.

Discussion

This study contributes to a comprehensive understanding of the effects of RG on health.
Animal welfare assessment protocol for quails reared for meat production
Authors: Dalmau Antoni , Padilla Lorena , Varvaró-Porter Aranzazu , Xercavins Aida , Velarde Antonio , Contreras-Jodar Alexandra
Published: September 2024

Introduction

It is estimated that 1.4 billion quails are reared each year for their eggs and meat, but animal welfare assessment protocols for this species have yet to be established. The objective of this study was to devise an animal welfare assessment protocol developed through a multidimensional approach that contained a number of animal-based indicators (ABIs) for quails (Coturnix japonica) reared for meat production.

Methods

During 2021 and 2022, the identical auditor visited and audited 14 Spanish farms in their initial year of integration into an animal welfare certification scheme. The protocol is categorised into 4 principles and 12 criteria. The “good feeding” principle includes 6 indicators (1 ABI), “good housing” includes 10 indicators (5 ABIs), “good health” includes 12 indicators (9 ABIs), and “appropriate behaviour” contains 8 indicators (5 ABIs). The final welfare assessment is calculated at the farm level using scores from the on-farm recordings. The assessment is a step-by-step weighted sum of the scores from the various indicators, with the final score ranging between 0 and 100.

Results and discussion

The main welfare issues found on all farms were a lack of temperature and humidity records, a poor lighting pattern, and the absence of an outdoor range or access to one. To a lesser degree, it was also found that there were excessive numbers of birds per feeder, the presence of improperly functioning drinkers (i.e., not working, inadequate water flow, or dripping water), poor litter quality, and a high prevalence of birds with dirty plumage and lameness. Despite this, the farms achieved a good overall score, being classified as “enhanced” (n = 11) and “acceptable” (n = 3). The tool proved helpful in identifying specific welfare issues at the farm level and conducting benchmarking.
Targeting ketone body metabolism to treat fatty liver disease
Authors: Kwon Sora , Jeyaratnam Reshani , Kim Kyoung-Han
Published: September 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a metabolic disorder marked by excessive accumulation of lipids within the liver. If untreated, this condition can progress to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis, and ultimately, hepatocellular carcinoma (HCC). Given the liver’s pivotal role in glucose and fatty acid metabolism, disruptions in these processes are commonly observed in MASLD. Ketone bodies, crucial energy metabolites primarily produced in the liver, are also closely related to the progression of MASLD. Recent studies have demonstrated that disrupted ketogenesis not only accompanies MASLD, but may also play a causal role in its development and progression. Moreover, activation of the ketogenic pathway has been suggested as a promising strategy for reducing excessive hepatic fat accumulation. This review focuses on the regulation of ketogenesis in MASLD, emphasizing the significance of dietary and pharmacological interventions as potential therapeutic approaches to treat fatty liver disease.
Technological Advancements and Organizational Discrimination: The Dual Impact of Industry 5.0 on Migrant Workers
Authors: Aydin Erhan , Rahman Mushfiqur , Bulut Cagri , Biloslavo Roberto
Published: September 2024

This study explores the impact of Industry 5.0 on discriminatory behaviors toward migrant employees within organizations. Through semi-structured qualitative interviews with 15 migrant workers in the UK, this research identifies key challenges faced by migrant employees amidst the integration of advanced technologies like AI and robotics in HRM systems. Thematic analysis reveals that while Industry 5.0 has the potential to mitigate human biases, it can also perpetuate existing prejudices if not managed effectively. This study highlights two main themes: the experiences of discrimination and challenges in the context of Industry 5.0, and the role of technology in HRM systems. The findings indicate that automated HR systems can both reduce and increase biases, highlighting the importance of inclusive practices and targeted support programs to help migrant workers adapt to a technologically advanced labor market. This research contributes to the literature by providing insights into the duality of technological advancements in reducing and reinforcing workplace discrimination.
Numerical Simulation of Spectral Radiation for Hypersonic Vehicles
Authors: Du Xubo , Shi Yongqiang , Yang Qingzhen , Song Dahe , Liu Xinyuan
Published: September 2024

The spectral radiation of hypersonic vehicles and surrounding flow fields is crucial for optical target detection. A novel approach combines Low-Discrepancy Sequences with the Reverse Monte Carlo Method to simulate the spectral radiation of hypersonic missiles. The effects of chemical non-equilibrium reactions and high-emissivity coating failures on the spectral radiation of a typical biconical hypersonic missile were investigated. Significant differences were found among chemical equilibrium, non-equilibrium, non-reactive, and catalytic wall models. High-emissivity coating failures occur mainly in the high-temperature regions of the nose cone and fins. The non-equilibrium model shows a transition peak distribution of NO in the head shock layer within the ultraviolet gamma band, with integrated ultraviolet radiation (200–300 nm) three times higher than the equilibrium model. In the 1–3 μm band, the non-equilibrium model’s radiation intensity at a 120° horizontal detection angle is about 1.46 times that of the equilibrium model. Using real coating emissivity, the 3–5 μm band radiation intensity is about 5% higher, and the 8–14 μm band is about 8.51% lower than the uniform emissivity model. When high-emissivity coating emissivity fails by 40%, the 3–5 μm band intensity decreases by about 15.38%, and the 8–14 μm band intensity decreases by about 12.67%.
Mathematical Modeling of the Global Engineering Process for Optimizing Product Quality in the Aerospace Industry
Authors: Titu Aurel Mihail , Pop Gheorghe Ioan , Pop Alina Bianca
Published: September 2024

The aerospace industry faces the challenge of maintaining product excellence amidst intricate processes and demands for cost and time efficiency. Mathematical modeling emerges as a valuable tool for optimizing the engineering process and enhancing quality, with potential applications extending beyond aerospace to other sectors with high quality and safety standards. This study develops and validates a mathematical model specific to the aerospace industry, aiming to assess the impact of human resource expertise on product quality. Through a case study within an aerospace organization, an IDEF0-methodology-based mathematical model, coupled with weighted averages, was constructed to depict the comprehensive engineering process and quantify knowledge’s impact on deliverable quality. Simulation data, gathered through human resource knowledge assessments and non-conformity analyses, revealed a direct correlation between technical knowledge levels and deliverable quality, consequently impacting final product quality. The proposed model serves as a tool for estimating potential deliverable error rates and pinpointing critical areas within the process that necessitate refinement. The research underscores the significance of knowledge investment and effective knowledge management strategies in upholding quality and competitiveness across industries with stringent quality requirements.
Laser Propulsion Science and Technology
Authors: Sinko John E.
Published: September 2024

Laser propulsion is an advanced technology that holds promise for use in many aerospace propulsion applications [...]
Enabling Intelligence on the Edge: Leveraging Edge Impulse to Deploy Multiple Deep Learning Models on Edge Devices for Tomato Leaf Disease Detection
Authors: Gookyi Dennis Agyemanh Nana , Wulnye Fortunatus Aabangbio , Wilson Michael , Danquah Paul , Danso Samuel Akwasi , Gariba Awudu Amadu
Published: September 2024

Tomato diseases, including Leaf blight, Leaf curl, Septoria leaf spot, and Verticillium wilt, are responsible for up to 50% of annual yield loss, significantly impacting global tomato production, valued at approximately USD 87 billion. In Ghana, there is a yield gap of about 50% in tomato production, which requires drastic measures to increase the yield of tomatoes. Conventional diagnostic methods are labor-intensive and impractical for real-time application, highlighting the need for innovative solutions. This study addresses these issues in Ghana by utilizing Edge Impulse to deploy multiple deep-learning models on a single mobile device, facilitating the rapid and precise detection of tomato leaf diseases in the field. This work compiled and rigorously prepared a comprehensive Ghanaian dataset of tomato leaf images, applying advanced preprocessing and augmentation techniques to enhance robustness. Using TensorFlow, we designed and optimized efficient convolutional neural network (CNN) architectures, including MobileNet, Inception, ShuffleNet, Squeezenet, EfficientNet, and a custom Deep Neural Network (DNN). The models were converted to TensorFlow Lite format and quantized to int8, substantially reducing the model size and improving inference speed. Deployment files were generated, and the Edge Impulse platform was configured to enable multiple model deployments on a mobile device. Performance evaluations across edge hardware provided metrics such as inference speed, accuracy, and resource utilization, demonstrating reliable real-time detection. EfficientNet achieved a high training accuracy of 97.12% with a compact 4.60 MB model size, proving its efficacy for mobile device deployment. In contrast, the custom DNN model is optimized for microcontroller unit (MCU) deployment. This edge artificial intelligence (AI) technology integration into agricultural practices offers scalable, cost-effective, and accessible solutions for disease classification, enhancing crop management, and supporting sustainable farming practices.
Advancing Persistent Character Generation: Comparative Analysis of Fine-Tuning Techniques for Diffusion Models
Authors: Martini Luca , Iacono Saverio , Zolezzi Daniele , Vercelli Gianni Viardo
Published: September 2024

In the evolving field of artificial intelligence, fine-tuning diffusion models is crucial for generating contextually coherent digital characters across various media. This paper examines four advanced fine-tuning techniques: Low-Rank Adaptation (LoRA), DreamBooth, Hypernetworks, and Textual Inversion. Each technique enhances the specificity and consistency of character generation, expanding the applications of diffusion models in digital content creation. LoRA efficiently adapts models to new tasks with minimal adjustments, making it ideal for environments with limited computational resources. It excels in low VRAM contexts due to its targeted fine-tuning of low-rank matrices within cross-attention layers, enabling faster training and efficient parameter tweaking. DreamBooth generates highly detailed, subject-specific images but is computationally intensive and suited for robust hardware environments. Hypernetworks introduce auxiliary networks that dynamically adjust the model’s behavior, allowing for flexibility during inference and on-the-fly model switching. This adaptability, however, can result in slightly lower image quality. Textual Inversion embeds new concepts directly into the model’s embedding space, allowing for rapid adaptation to novel styles or concepts, but is less effective for precise character generation. This analysis shows that LoRA is the most efficient for producing high-quality outputs with minimal computational overhead. In contrast, DreamBooth excels in high-fidelity images at the cost of longer training. Hypernetworks provide adaptability with some tradeoffs in quality, while Textual Inversion serves as a lightweight option for style integration. These techniques collectively enhance the creative capabilities of diffusion models, delivering high-quality, contextually relevant outputs.
Efficacy of a Single Injection of Stromal Vascular Fraction in Dogs with Elbow Osteoarthritis: A Clinical Prospective Study
Authors: Bruns Yvonne , Schroers Maike , Steigmeier-Raith Stephanie , Waselau Anja-Christina , Reese Sven , Meyer-Lindenberg Andrea
Published: September 2024

This study aimed to assess the efficacy of a single intra-articular injection of autologous stromal vascular fraction (SVF) in dogs with chronic lameness due to advanced elbow osteoarthritis (OA) that were unresponsive to conventional drug therapy. In this clinical, prospective, non-blinded, single-center study, twenty-three dogs received autologous SVF derived from falciform adipose tissue. Primary outcome measures over the six-month study period included clinical-orthopedic and radiographic examinations, objective gait analysis and validated owner questionnaires. In 19 of 23 joints, no progression of OA was visible radiographically. Peak vertical force improved significantly at three months and vertical impulse at six months after the injection compared to baseline. Over 33% of dogs demonstrated treatment-related improvements in lameness based on objective gait analysis. Owner questionnaires indicated significant improvement in clinical signs throughout the study period and 26% of dogs showed treatment-related improvements in pain scores according to the Canine Brief Pain Inventory. No side effects were reported. These findings suggest that autologous regenerative cell therapy may provide a promising treatment option for dogs with advanced OA that do not respond to conventional drug therapy. However, the treatment did not improve the clinical symptoms in all dogs, so it cannot be recommended for all patients.
New Insights on Chromosome Diversification in Malagasy Chameleons
Authors: Mezzasalma Marcello , Odierna Gaetano , Macirella Rachele , Brunelli Elvira
Published: September 2024

In this work, we performed a preliminary molecular analysis and a comparative cytogenetic study on 5 different species of Malagasy chameleons of the genus Brookesia (B. superciliaris) and Furcifer (F. balteautus, F. petteri, F. major and F. minor). A DNA barcoding analysis was first carried out on the study samples using a fragment of the mitochondrial gene coding for the cytochrome oxidase subunit 1 (COI) in order to assess the taxonomic identity of the available biological material. Subsequently, we performed on the studied individuals a chromosome analysis with standard karyotyping (5% Giemsa solution at pH 7) and sequential C-banding + Giemsa, + CMA3, and + DAPI. The results obtained indicate that the studied species are characterized by a different chromosome number and a variable heterochromatin content and distribution, with or without differentiated sex chromosomes. In particular, B. superciliaris (2n = 36) and F. balteatus (2n = 34) showed a similar karyotype with 6 macro- and 12–11 microchromosome pairs, without differentiated sex chromosomes. In turn, F. petteri, F. major, and F. minor showed a karyotype with a reduced chromosome number (2n = 22–24) and a differentiated sex chromosome system with female heterogamety (ZZ/ZW). Adding our newly generated data to those available from the literature, we highlight that the remarkable chromosomal diversification of the genus Furcifer was likely driven by non-homologous chromosome fusions, including autosome–autosome, Z–autosome, and W–autosome fusions. The results of this process resulted in a progressive reduction in the chromosome number and partially homologous sex chromosomes of different shapes and sizes.
Insights from Clinical Trials: Evidence-Based Recommendations for Induction Treatment of Newly Diagnosed Transplant-Eligible Multiple Myeloma
Authors: Lytvynova Olga , Jwayyed Jenna , Pastel Daniel , Prasad Rohan , Khouri Jack , Williams Louis , Mazzoni Sandra , Raza Shahzad , Anwer Faiz
Published: September 2024

Multiple myeloma (MM) is a hematological malignancy and poses significant therapeutic challenges. This review synthesizes evidence from pivotal clinical trials to guide induction treatment for transplant-eligible (TE), newly diagnosed MM (NDMM) patients. Emphasizing the evolution from three-drug to four-drug induction therapies, we highlight the integration of monoclonal antibodies, particularly CD38 recombinant monoclonal antibody agents, into treatment regimens. This analysis includes a comprehensive literature review of research from major databases and conferences conducted between 2010 and 2023, culminating in the detailed evaluation of 47 studies. The findings underscore the superiority of quadruple regimens in TE NDMM, notably those incorporating daratumumab, in achieving superior responses including progression-free survival (PFS), minimal residual disease (MRD) negativity, objective response rate (ORR), and overall survival (OS) when compared to triple-drug regimens. As treatment regimens evolve with additional agents, the improved outcomes with treatment-related adverse events should be carefully balanced. This review advocates for a paradigm shift towards quadruple induction therapies for TE NDMM, offers a detailed insight into the current landscape of MM treatment, and reinforces a new standard of care.
Target Attainment and Population Pharmacokinetics of Cefazolin in Patients with Invasive Staphylococcus aureus Infections: A Prospective Cohort Study
Authors: Bausch Severin , Dräger Sarah , Charitos-Fragkakis Panteleimon , Egli Adrian , Moser Stephan , Hinic Vladimira , Kuehl Richard , Bassetti Stefano , Siegemund Martin , Rentsch Katharina M. , Hermann Laura , Schöning Verena , Hammann Felix , Sendi Parham , Osthoff Michael
Published: September 2024

This study aimed to determine cefazolin target attainment in patients with invasive Staphylococcus aureus (S. aureus) infections and to develop a population pharmacokinetic (PK) model. Adult patients with invasive S. aureus infections treated with cefazolin bolus infusions were included. Unbound and total trough and mid-dose cefazolin concentrations were measured, and strain-specific MICs were determined. The primary outcome was the proportion of patients attaining 100% fT>MIC at all time points evaluated. A population PK model was developed, using non-linear mixed-effects modelling. Overall, 51 patients were included, with a total of 226 unbound and total cefazolin concentrations measured (mean: 4.4 per patient). The median daily dosage in patients with an estimated glomerular filtration rate of >60 mL/min/m2 was 8 g. The median age was 74 years (interquartile range (IQR) 57–82) and 26% were female. A history of chronic kidney disease and acute kidney injury were present in 10/51 (19.6%) and 6/51 (11.7%), respectively. Achievement of 100% fT>MIC occurred in 86% of the patients and decreased to 45% when a target of 100% fT>4xMIC was evaluated. The mean unbound cefazolin fraction was 27.0% (standard deviation (SD) 13.4). Measured and estimated mean cefazolin trough concentrations differed significantly [13.1 mg/L (SD 23.5) vs. 7.4 mg/L (SD 7.9), p < 0.001]. In the population PK model, elevated estimated creatinine clearance and bolus instead of continuous application were covariates for target non-attainment. In conclusion, cefazolin target achievement was high, and the measurement of the unbound cefazolin concentration may be favored. The Monte Carlo simulations indicated that target attainment was significantly improved with continuous infusion.
Processing Hemp Shiv Particles for Building Applications: Alkaline Extraction for Concrete and Hot Water Treatment for Binderless Particle Board
Authors: Diakité Maya-Sétan , Lequart Vincent , Hérisson Alexandre , Chenot Élise , Potel Sébastien , Leblanc Nathalie , Martin Patrick , Lenormand Hélène
Published: September 2024

The building and construction sector is the largest emitter of greenhouse gases, accounting for 37% of global emissions. The production and use of materials such as cement, steel, and aluminum contribute significantly to this carbon footprint. Utilizing valorized agricultural by-products, such as hemp shiv and sunflower pith, in construction can enhance the insulating properties of materials and reduce their environmental impact by capturing CO2. Additionally, during the formulation process, molecules such as polyphenols and sugars are released, depending on process parameters like pH and temperature. In some cases, these releases can cause issues, such as delaying the hardening of agro-based concrete or serving as binding agents in binderless particle boards. This study focuses on the molecules released during the processing of these materials, with particular attention to the effects of pH and temperature, and the modifications to the plant particles resulting from these conditions. Physical, chemical, and morphological analyses were conducted on the treated hemp shiv particles (HS1 and HS2). No physical or morphological differences were observed between the samples. However, chemical differences, particularly in the lignin and soluble compound content, were noted and were linked to the release of plant substances during the process.
Local Ecological Knowledge (LEK) Can Guide Decision-Making in Inland Fisheries Management
Authors: Petriki Olga , Kouletsos Athanasios , Ntislidou Chrysoula , Bobori Dimitra C.
Published: September 2024

Evaluating and integrating local ecological knowledge held by fishers into decision-making processes has the potential to significantly enhance fisheries management. The present study aimed to collect information on fishery practices and to assess the ecological knowledge of local professional fishers through interviews, evaluating its importance in managerial design. As a case study, Polyphytos Reservoir in Greece, which supports substantial fisheries, was selected. During the summer of 2023, thirty-seven interviews were conducted to document fishing efforts, methods, catches, biological information, and fishers’ perspectives on lake management, and economic/demographic details. In addition to gathering data on fishing activities, the study seeks to understand fishers’ perspectives on managerial deficiencies and necessities, thereby revealing their valuable ecological knowledge. The integration of this knowledge into decision-making processes can empower stakeholders and enhance local participation in fishery management. Ultimately, this approach has the potential to address long-standing conflicts, foster inclusive processes, and ensure better collective outcomes.
Modeling Brittle-to-Ductile Transitions in Rock Masses: Integrating the Geological Strength Index with the Hoek–Brown Criterion
Authors: Vásárhelyi Balázs , Narimani Samad , Davarpanah Seyed Morteza , Mocsár Gábor
Published: September 2024

Many studies focus on brittle–ductile transition stress in intact rocks; however, in real life, we deal with rock mass which contains many discontinuities. To fill this gap, this research focuses on the brittle–ductile transition stress of rock mass by considering the influence of different Geological Strength Index (GSI) values on the brittle–ductile transition stress of rock mass. In other words, the Hoek–Brown failure criteria for rock mass were reformulated mathematically including the ductility parameter (d), which is defined as the ratio of differential stress to minor stress. Then, the results were analyzed and plotted between σ3*σc and GSI, considering different (d) and Hoek–Brown material constant (mi) values. The brittle–ductile transition stress, σ3*, was determined by intersecting the Hoek–Brown failure envelope with Mogi’s line, with ductility parameters d ranging from 3.4 (silicate rocks) to 5.0 (carbonate rocks). Numerical solutions were derived for σ3*σc as a function of GSI using Matlab, and the results were fitted with an exponential model. The analysis revealed an exponential relationship between σ3*σc and GSI for values above 32, with accuracy better than 3%. Increased ductility reduces rock mass strength, with higher d values leading to lower σ3*σc. The diminishing returns in confinement strength at higher GSI values suggest that rock masses with higher GSI can sustain more confinement but with reduced effectiveness as GSI increases. These findings provide a framework for predicting brittle–ductile transitions in rock engineering.
Between Tradition and Modernity: The Sociospatial Dynamics of Japanese Residential Architecture from Pre-War to Present
Authors: Tamura Junko
Published: September 2024

This research examines the evolution of Japanese residential architecture throughout the 20th century, focusing on the transformation of house plans in response to changing societal needs. This study specifically examines how traditional spatial configurations adapted to urbanization, modernisation, and shifts in the family structure. By analysing house plans across three distinct periods—the pre-war and post-Kanto earthquake period, the post-war period, and the post-oil shock period to the present—this research illustrates the transition from detached houses to modern collective housing. Utilising a space syntax methodology, this research quantitatively analyses threshold spaces, circulation, and family gathering spaces to understand their social and architectural implications. Historical analyses are paired with a network analysis of selected house plans, highlighting the persistent significance of traditional elements such as the doma (vestibule) and the en-gawa (verandah) in contemporary designs. The findings demonstrate a significant reduction in the size and complexity of living spaces over time, reflecting broader trends towards efficiency and modernisation in public housing. This research contributes to architectural scholarship by providing a detailed account of how Japanese customary spaces have been reconfigured to accommodate evolving lifestyles, offering insights into the balance between tradition and modern living.
The Distributed Authorship of Art in the Age of AI
Authors: Goodfellow Paul
Published: September 2024

The distribution of authorship in the age of machine learning or artificial intelligence (AI) suggests a taxonomic system that places art objects along a spectrum in terms of authorship: from pure human creation, which draws directly from the interior world of affect, emotions and ideas, through to co-evolved works created with tools and collective production and finally to works that are largely devoid of human involvement. Human and machine production can be distinguished in terms of motivation, with human production being driven by consciousness and the processing of subjective experience and machinic production being driven by algorithms and the processing of data. However, the expansion of AI entangles the artist in ever more complex webs of production and dissemination, whereby the boundaries between the work of the artist and the work of the networked technologies are increasingly distributed and obscured. From this perspective, AI-generated works are not solely the products of an independent machinic agency but operate in the middle of the spectrum of authorship between human and machine, as they are the consequences of a highly distributed model of production that sit across the algorithms and the underlying information systems and data that support them and the artists who both contribute and extract value. This highly distributed state further transforms the role of the artist from the creator of objects containing aesthetic and conceptual potential to the translator and curator of such objects.
Pedestrian Behavior in Static and Dynamic Virtual Road Crossing Experiments
Authors: Soares Francisco , Pereira Frederico , Faria Susana , Sousa Emanuel , Almeida Raul , Freitas Elisabete F.
Published: September 2024

Virtual studies involving pedestrians have gained relevance due to the advantage of not exposing them to actual risk, and simulation setups have benefitted from rapid technical advancements, becoming increasingly complex and immersive. However, it remains unclear whether complex setups affecting participants’ freedom of movement impact their decision-making. This research evaluated the effects of a more realistic approach to studying pedestrian crossing behavior by comparing a perception-action task requiring participants to walk effectively along a semi-virtual crosswalk with a similar experiment using static crossing conditions. Using a CAVE system, two real-world streets were modeled in two different virtual scenarios, varying vehicle speed patterns and distance from the crosswalk. Visual stimuli were presented to two groups of 30 participants, with auditory stimuli adapted accordingly. The impact of various factors on participants’ crossing decisions was evaluated by examining the percentage of crossings, crossing start time, and time-to-passage. Overall, the experimental approach did not significantly affect participants’ crossing decisions.
Characterization and Sources of VOCs during PM2.5 Pollution Periods in a Typical City of the Yangtze River Delta
Authors: Zhang Dan , Huang Xiaoqing , Xiao Shaoxuan , Zhang Zhou , Zhang Yanli , Wang Xinming
Published: September 2024

To investigate the characteristics and sources of volatile organic compounds (VOCs) as well as their impacts on secondary organic aerosols (SOAs) formation during high-incidence periods of PM2.5 pollution, a field measurement was conducted in December 2019 in Hefei, a typical city of the Yangtze River Delta (YRD). During the whole process, the mixing ratios of VOCs were averaged as 21.1 ± 15.9 ppb, with alkanes, alkenes, alkyne, and aromatics accounting for 59.9%, 15.3%, 15.0%, and 9.8% of the total VOCs, respectively. It is worth noting that the contributions of alkenes and alkyne increased significantly during PM2.5 pollution periods. Based on source apportionment via the positive matrix factorization (PMF) model, vehicle emissions, liquefied petroleum gas/natural gas (LPG/NG), and biomass/coal burning were the main sources of VOCs during the research in Hefei. During pollution periods, however, the contribution of biomass/coal burning to VOCs increased significantly, reaching as much as 47.6%. The calculated SOA formation potential (SOAFP) of VOCs was 0.38 ± 1.04 µg m−3 (range: 0.04–7.30 µg m−3), and aromatics were the dominant contributors, with a percentage of 96.8%. The source contributions showed that industrial emissions (49.1%) and vehicle emissions (28.3%) contributed the most to SOAFP during non-pollution periods, whereas the contribution of biomass/coal burning to SOA formation increased significantly (32.8%) during PM2.5 pollution periods. These findings suggest that reducing VOCs emissions from biomass/coal burning, vehicle, and industrial sources is a crucial approach for the effective control of SOA formation in Hefei, which provides a scientific basis for controlling PM2.5 pollution and improving air quality in the YRD region.
SO2 Diffusion Features of the 2022 Hunga Tonga–Hunga Ha’apai Volcanic Eruptions from DSCOVR/EPIC Observations
Authors: Huang Yi , Duan Wentao
Published: September 2024

Understanding the volcanic SO2 diffusive characteristics can enhance our knowledge of the impact of volcanic eruptions on climate change. In this study, the SO2 diffusion features of the Hunga Tonga–Hunga Ha’apai underwater volcano (HTHH) 2022 eruptions are investigated based on the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) dataset, which could provide longer term, more consistent, and higher temporal sampling rate observations to complement current low-orbit satellite-based research. SO2 plume major-direction profile analysis indicates that the SO2 diffusion extent of subaerial eruption initiating at 15:20/13 January 2022 was approximately 1500 km in the Southeast–Northwest major diffusive direction by 20:15/14 January 2022 (about 29 h after the HTHH subaerial eruption). All-direction SO2 plume analysis shows that the HTHH subaerial eruption-emitted SO2 plume could diffuse as far as 6242 km by 02:20/15 January 2022. Furthermore, these two analyses in terms of the HTHH major eruption initiating at 04:00/15 January 2022 imply that HTHH major eruption-emitted SO2 plume could diffuse as far as 8600 km in the Southeast–Northwest major diffusive direction by 02:24/18 January 2022 (about 70 h after the HTHH major eruption). It is also implied that HTHH major eruption-emitted SO2 plume could extend to approximately 14,729 km away from the crater by 13:12/18 January 2022. We believe that these findings could provide certain guidance for volcanic gas estimations, thus helping to deepen our understanding of volcanic impacts on climate change.
Occurrences of Deposited Polycyclic Aromatic Hydrocarbons in Wax of Plant Leaves Using Laser Scanning Microscopy and Gas Chromatography–Mass Spectrometry
Authors: Yang Ming , Liu Qingyang , Tian Shili , Yang Zheng , Yang Yifan , Shao Peng , Liu Yanju
Published: September 2024

The knowledge of the deposition fate of ambient polycyclic aromatic hydrocarbons (PAHs) on plant leaves is limited. To fill in this knowledge gap, this study strives to observe the intermolecular complex between the polycyclic aromatic hydrocarbons and epicuticular wax of plant leaves using laser scanning microscopy. Epicuticular wax refers to a type of organic mixture that covers the outermost layer of leaves. The leaves of 20 tree species were collected in Beijing in July 2023. The concentrations of 31 PAHs were quantified by gas chromatography–mass spectrometry. Furthermore, the intermolecular complexes of polycyclic aromatic hydrocarbons and epicuticular wax were found with a fluorescence spectrofluorometer and laser scanning microscopy. The levels of total PAHs across 20 tree species ranged from 12.4 ng g−1 to 68.4 ng g−1. Differences in the amounts of total PAHs across tree leaves were observed, which may be ascribed to the differences in leaf surface across tree types. The higher concentration of low-molecular-weight PAHs was found in leaves compared to high-molecular-weight PAHs. The fluorescence spectrofluorometer identified the formation of a new intermolecular complex with fluorescence emission at an excitation wavelength of 340 nm between PAHs and epicuticular wax relative to PAHs. We used laser scanning microscopy with a 405 nm laser for excitation to observe the new intermolecular complex of PAHs and epicuticular wax on the stomata and epicuticular wax of leaves. This study found the intermolecular complex of PAHs on the surface of leaves in situ, which provides important information about the deposition fate of ambient PAHs.
The Development and Optimization of a New Wind Tunnel Design for Odour Sampling
Authors: Tagliaferri Francesca , Carrera Luca , Albertini Anna , Invernizzi Marzio , Sironi Selena
Published: September 2024

The characterization of passive area sources, emitting odours due to wind-driven convection, poses significant challenges. The present experimental study aims to evaluate the performance, in terms of fluid dynamics and mass transfer, of a recently developed wind tunnel, with a more compact design and reduced weight, compared to the one proposed by the Italian regulations. The results show that the new design outperforms the Italian standard in several aspects. From a fluid dynamic point of view, the new wind tunnel exhibits a slightly more homogenous and uniform velocity distribution, and it does not reveal airflow preferential channels inside the central body. The pressure tests highlight that the presence of fillers in the new wind tunnel does not significantly alter the pressure inside the hood and therefore the gas–liquid equilibrium conditions; actually, the slight overpressure may help to prevent the infiltration of external air. Finally, mass transfer tests on the standard device show a vertical concentration gradient along the outlet duct, highlighting concentration values that differ up to a factor of two depending on the measurement point. The new design has almost completely solved this issue, thanks to the use of fillers that promote mixing of the outlet flow.
Biologically Relevant Methods to Test How Microbes Colonize Maize Styles (Silks): Case Study of a Pantoea Strain
Authors: Thompson Michelle E. H. , Raizada Manish N.
Published: September 2024

Maize silks (style) receive wind-transmitted pollen. Thereafter, male gametes travel through the silks to reach ovules. Pollinated silks contain a microbiome, members of which are predicted to promote host reproduction and abiotic/biotic stress tolerance during fertilization. It is unknown whether pollinated silk bacteria originate environmentally (air/pollen) or from maternal tissue. Methods are lacking to test microbial colonization of silks in their native habitat [on intact maize inflorescences (cobs) encased by husk leaves]. Current methods focus on naked silks attached to dehusked cob pieces. Here, two novel methods are presented to enable research on silk microbes in their native habitat. Method 1 tests whether silk-associated bacteria with potential environmental origins are attracted toward ovules. Method 2 distinguishes whether a microbe colonizes silks from the environment or maternal parent. Biosafety containment was enabled by housing microbe-treated cobs in large jars. Using these methods, a model bacterial isolate from fertilization-stage silks (DsRed-tagged Pantoea-E04) was shown to colonize husk-covered silks after inoculating exposed silk tips; E04 could not colonize from the cob base, suggesting an environmental origin. In support, E04 colonized silks more frequently when cobs were uncut and oriented vertically. These protocols will enable more biologically relevant investigation of silk microbiomes and pathogens.
Proteomic Analysis of Thermus thermophilus Cells after Treatment with Antimicrobial Peptide
Authors: Surin Alexey K. , Malykhina Anna I. , Slizen Michail V. , Kochetov Alexey P. , Suvorina Mariya Yu. , Biryulyov Vadim E. , Grishin Sergei Y. , Galzitskaya Oxana V.
Published: September 2024

In recent years, the study of antimicrobial peptides (AMPs) has garnered considerable attention due to their potential in combating antibiotic-resistant pathogens. Mass spectrometry-based proteomics provides valuable information on microbial stress responses induced by AMPs. This work aims to unravel the proteomic alterations induced by the amyloidogenic antimicrobial peptide R23I, encompassing both inhibitory and non-inhibitory concentrations. This study investigates the effects of the R23I peptide on the protein abundance of Thermus thermophilus (T. thermophilus) at different concentrations (20, 50, and 100 μg/mL). We found 82 differentially expressed proteins, including 15 upregulated and 67 downregulated proteins. We also compared the protein identification results between the PEAKS and IdentiPy programs. Our proteomic analysis revealed distinct patterns of protein expression, suggesting compensatory mechanisms in response to the R23I peptide. Notably, the alterations predominantly affected membrane and cytoplasmic proteins that play a central role in critical cellular processes such as transcription, translation, and energy conversion. This study sheds light on the complex interactions between antimicrobial peptides and bacterial responses, offering insights into microbial adaptability and potential implications for antimicrobial strategies and the understanding of microbial physiology.
Identification of Anomalies in Lung and Colon Cancer Using Computer Vision-Based Swin Transformer with Ensemble Model on Histopathological Images
Authors: Alsulami Abdulkream A. , Albarakati Aishah , AL-Ghamdi Abdullah AL-Malaise , Ragab Mahmoud
Published: September 2024

Lung and colon cancer (LCC) is a dominant life-threatening disease that needs timely attention and precise diagnosis for efficient treatment. The conventional diagnostic techniques for LCC regularly encounter constraints in terms of efficiency and accuracy, thus causing challenges in primary recognition and treatment. Early diagnosis of the disease can immensely reduce the probability of death. In medical practice, the histopathological study of the tissue samples generally uses a classical model. Still, the automated devices that exploit artificial intelligence (AI) techniques produce efficient results in disease diagnosis. In histopathology, both machine learning (ML) and deep learning (DL) approaches can be deployed owing to their latent ability in analyzing and predicting physically accurate molecular phenotypes and microsatellite uncertainty. In this background, this study presents a novel technique called Lung and Colon Cancer using a Swin Transformer with an Ensemble Model on the Histopathological Images (LCCST-EMHI). The proposed LCCST-EMHI method focuses on designing a DL model for the diagnosis and classification of the LCC using histopathological images (HI). In order to achieve this, the LCCST-EMHI model utilizes the bilateral filtering (BF) technique to get rid of the noise. Further, the Swin Transformer (ST) model is also employed for the purpose of feature extraction. For the LCC detection and classification process, an ensemble deep learning classifier is used with three techniques: bidirectional long short-term memory with multi-head attention (BiLSTM-MHA), Double Deep Q-Network (DDQN), and sparse stacked autoencoder (SSAE). Eventually, the hyperparameter selection of the three DL models can be implemented utilizing the walrus optimization algorithm (WaOA) method. In order to illustrate the promising performance of the LCCST-EMHI approach, an extensive range of simulation analyses was conducted on a benchmark dataset. The experimentation results demonstrated the promising performance of the LCCST-EMHI approach over other recent methods.
Evolution and Innovations in Bone Marrow Cellular Therapy for Musculoskeletal Disorders: Tracing the Historical Trajectory and Contemporary Advances
Authors: Lana José Fábio , de Brito Gabriela Caponero , Kruel André , Brito Benjamim , Santos Gabriel Silva , Caliari Carolina , Salamanna Francesca , Sartori Maria , Barbanti Brodano Giovanni , Costa Fábio Ramos , Jeyaraman Madhan , Dallo Ignácio , Bernaldez Pedro , Purita Joseph , Andrade Marco Antonio Percope de , Everts Peter Albert
Published: September 2024

Bone marrow cellular therapy has undergone a remarkable evolution, significantly impacting the treatment of musculoskeletal disorders. This review traces the historical trajectory from early mythological references to contemporary scientific advancements. The groundbreaking work of Friedenstein in 1968, identifying fibroblast colony-forming cells in bone marrow, laid the foundation for future studies. Caplan’s subsequent identification of mesenchymal stem cells (MSCs) in 1991 highlighted their differentiation potential and immunomodulatory properties, establishing them as key players in regenerative medicine. Contemporary research has focused on refining techniques for isolating and applying bone marrow-derived MSCs. These cells have shown promise in treating conditions like osteonecrosis, osteoarthritis, and tendon injuries thanks to their ability to promote tissue repair, modulate immune responses, and enhance angiogenesis. Clinical studies have demonstrated significant improvements in pain relief, functional recovery, and tissue regeneration. Innovations such as the ACH classification system and advancements in bone marrow aspiration methods have standardized practices, improving the consistency and efficacy of these therapies. Recent clinical trials have validated the therapeutic potential of bone marrow-derived products, highlighting their advantages in both surgical and non-surgical applications. Studies have shown that MSCs can reduce inflammation, support bone healing, and enhance cartilage repair. However, challenges remain, including the need for rigorous characterization of cell populations and standardized reporting in clinical trials. Addressing these issues is crucial for advancing the field and ensuring the reliable application of these therapies. Looking ahead, future research should focus on integrating bone marrow-derived products with other regenerative techniques and exploring non-surgical interventions. The continued innovation and refinement of these therapies hold promise for revolutionizing the treatment of musculoskeletal disorders, offering improved patient outcomes, and advancing the boundaries of medical science.
Prospective Randomized Controlled Clinical Trial to Evaluate the Safety and Efficacy of ACTLINK Plasma Treatment for Promoting Osseointegration and Bone Regeneration in Dental Implants
Authors: Kwon Jin-Seon , Cho Won-Tak , Lee Jong-Ho , Joo Ji-Young , Lee Jae-Yeol , Lim Youbong , Jeon Hyun-Jeong , Huh Jung-Bo
Published: September 2024

Recent studies have explored surface treatments, such as increasing the hydrophilicity of implant fixtures, to enhance the osseointegration of implants. This prospective clinical study aimed to assess the clinical stability and efficacy of plasma treatment applied to implants with sandblast−acid etching (SLA) surfaces before placement. Twenty-eight patients requiring implant placement provided consent and were assigned randomly to either the SLA group without plasma treatment or the SLA/plasma group with plasma treatment. Recall checks were conducted one and three months after the first-stage surgery, followed by a second surgery at four months. Although no significant differences in buccal bone defects or implant stability were observed between the groups, the SLA/plasma group showed significant increases in marginal bone changes on the mesial and distal sides, as assessed using periapical radiographs. This study underscores the potential of pre-implantation plasma treatment to enhance bone regeneration around implants.