bluuebunny/crossref_metadata_2025 huggingface dataset:
A hypothetical model: Chromatin remodelers couple with acetyltransferases to trigger the elongation of RNA polymerase II (pol II)
Authors: Zhang Gongyi
Published: August 2024

Transcription is one of the central dogmas of life. Most genes in eukaryotes are transcribed by RNA polymerase II (Pol II). For Pol II to transcribe along the gene body, it must overcome nucleosomes, which are barriers for Pol II. It is still a mystery how Pol II ejects nucleosomes during transcription elongation. I hypothesize that a group of chromatin remodelers (SWI/SNF, RSC, SWR1, INO80) carry a group of histone acetyltransferases (NuA4, Spt-Ada-Gcn-acetyltransferase, NuA3) to deposit acetyl-groups on histone tails to generate pan-acetylated nucleosomes or fragile nucleosomes along gene bodies for Pol II to transcribe. Specifically, for the first round of transcription, the RSC complex works with NuA4 to acetylate histone tails of H2A and H4; the SWI/SNF complex carries SAGA to add acetyl-groups to histone tails of H2B and H3. For the second and subsequent rounds, SWR1 pairs with a piccolo NuA4 to acetylate the histone tails of H2A and H4 of newly inserted nucleosomes, while INO80 pairs with NuA3 to acetylate the histone tails of H2B and H3 within newly inserted nucleosomes along the gene body. After the mission is accomplished, ISW1b couples with Rpd3s to remove acetyl groups on H2A and H4, while CHD1 carries HDA1 along the gene body to remove acetyl groups on H2B and H3.
An exploratory qualitative interview study on grassroots esports in sports clubs
Authors: Baumann André C. K. , Pallesen Ståle , Mentzoni Rune A. , Kolberg Eirin , Waagbø Vegard , Sørensen Anders , Kristensen Joakim H.
Published: August 2024

Aim

The current study aimed to explore grassroots esports in sports clubs in Norway from the perspective of volunteer esports leaders.

Method and results

Fifteen volunteers were recruited from grassroots esports initiatives in various sports clubs and were interviewed via online video conferencing using a pre-developed semi-structured interview guide. Data was analyzed using inductive thematic analysis with a realist approach, which generated the following themes: (1) Local community impact at the center of motivation, (2) lack of support threatens the operations of the initiatives, and (3) competency development to overcome barriers. The participants perceived the grassroots esports initiatives as essential for children in the local community and as the core of their motivation as volunteers. Several challenges were mentioned for sustaining the initiatives, such as maintaining motivation, resource management, and recruiting new volunteers. Finally, competency and qualified esports trainers were mentioned as necessary for a high-quality offer.

Conclusion

The grassroots esports initiatives in sports clubs are viewed by volunteer esports leaders to affect the local community positively. However, there are challenges tied to the operation of such initiatives, such as engaging volunteers and raising competence. Future research should investigate barriers to help develop strategies to support grassroots esports initiatives.
Exploring the potential of human urine derivatives in circular agriculture: a case study on lettuce
Authors: Nicastro Rosalinda , El-Nakhel Christophe , Geelen Danny , Fusco Giovanna Marta , De Pascale Stefania , Rouphael Youssef , Carillo Petronia
Published: August 2024

Unlocking the potential of sustainable agriculture relies on innovative approaches such as recycling crop waste and exploiting wastewater. Herewith, human urine derivatives were integrated into the fertigation of soilless-grown lettuce. The effects were remarkable: not only did they impact primary metabolites such as amino acids, proteins, and sugars, but they also influenced secondary metabolites such as polyphenols and anthocyanins, along with antioxidant enzyme activity. K-struvite, a urine precipitate with CaO and NaOH, elicited responses comparable to those of the control NPK and correlated with high biometric values. Interestingly, urine precipitate–CaO and electrodialysis (ED) concentrate stimulated accumulation of leaf polyphenols and anthocyanins, while urine precipitate–CaO induced high ABTS antioxidant capacity, highlighting their potential to enhance antioxidant activity and nutritive quality. Moreover, hydrolyzed urine and aurin induced a significant boost of essential amino acid content, underlining their role in increasing the nutritive value of lettuce. However, they also correlated with higher levels of MDA, a marker of lipid peroxidation, and reduced APX activity, indicating the need for further optimization. These findings underscore the promising role of human urine as an organic component in soilless lettuce fertilization, paving the way for more sustainable and resource-efficient agricultural practices.
An Efficient Optimization of the Monte Carlo Tree Search Algorithm for Amazons
Authors: Zhang Lijun , Zou Han , Zhu Yungang
Published: August 2024

Amazons is a computerized board game with complex positions that are highly challenging for humans. In this paper, we propose an efficient optimization of the Monte Carlo tree search (MCTS) algorithm for Amazons, fusing the ‘Move Groups’ strategy and the ‘Parallel Evaluation’ optimization strategy (MG-PEO). Specifically, we explain the high efficiency of the Move Groups strategy by defining a new criterion: the winning convergence distance. We also highlight the strategy’s potential issue of falling into a local optimum and propose that the Parallel Evaluation mechanism can compensate for this shortcoming. Moreover, We conducted rigorous performance analysis and experiments. Performance analysis results indicate that the MCTS algorithm with the Move Groups strategy can improve the playing ability of the Amazons game by 20–30 times compared to the traditional MCTS algorithm. The Parallel Evaluation optimization further enhances the playing ability of the Amazons game by 2–3 times. Experimental results show that the MCTS algorithm with the MG-PEO strategy achieves a 23% higher game-winning rate on average compared to the traditional MCTS algorithm. Additionally, the MG-PEO Amazons program proposed in this paper won first prize in the Amazons Competition at the 2023 China Collegiate Computer Games Championship & National Computer Games Tournament.
Simulation and Experimental Study of Gas Turbine Blade Tenon-Root Detachment on Spin Test
Authors: Yu Maoyu , Wang Jianfang , Xuan Haijun , Xiong Wangjiao , He Zekan , Qu Mingmin
Published: August 2024

This paper addresses the critical issue of turbine blade containment in aircraft engines, crucial for ensuring flight safety. Through a comprehensive approach integrating numerical simulations and experimental validations, the containment capabilities of gas turbine engine casings are thoroughly analyzed. The study investigates the impact dynamics, deformation characteristics, and energy absorption mechanisms during blade detachment events, shedding light on the containment process. Based on the multi-stage nature of gas turbines, two different blade structures were designed for turbine blades. Utilizing finite element simulation and the Johnson–Cook constitutive equation, this study accurately simulated single-blade and dual-blade containment scenarios. The simulation results of the single blade indicate that the process of a gas turbine blade impacting the casing primarily consists of three stages. The second stage, where the tenon root strikes the casing, is identified as the main cause of casing damage. Meanwhile, in the dual-blade simulation, the second blade, influenced by the first blade, directly impacts the casing after fracturing, resulting in greater damage. Then, eight corresponding containment tests were conducted based on the simulation results, validating the accuracy of the simulation parameters. Experimental verification of simulation results further confirms the validity of the proposed containment curves, providing essential insights for optimizing casing design and enhancing the safety and reliability of aircraft engines.
Monitoring Maize Canopy Chlorophyll Content throughout the Growth Stages Based on UAV MS and RGB Feature Fusion
Authors: Li Wenfeng , Pan Kun , Liu Wenrong , Xiao Weihua , Ni Shijian , Shi Peng , Chen Xiuyue , Li Tong
Published: August 2024

Chlorophyll content is an important physiological indicator reflecting the growth status of crops. Traditional methods for obtaining crop chlorophyll content are time-consuming and labor-intensive. The rapid development of UAV remote sensing platforms offers new possibilities for monitoring chlorophyll content in field crops. To improve the efficiency and accuracy of monitoring chlorophyll content in maize canopies, this study collected RGB, multispectral (MS), and SPAD data from maize canopies at the jointing, tasseling, and grouting stages, constructing a dataset with fused features. We developed maize canopy chlorophyll content monitoring models based on four machine learning algorithms: BP neural network (BP), multilayer perceptron (MLP), support vector regression (SVR), and gradient boosting decision tree (GBDT). The results showed that, compared to single-feature methods, the MS and RGB fused feature method achieved higher monitoring accuracy, with R² values ranging from 0.808 to 0.896, RMSE values between 2.699 and 3.092, and NRMSE values between 10.36% and 12.26%. The SVR model combined with MS–RGB fused feature data outperformed the BP, MLP, and GBDT models in monitoring maize canopy chlorophyll content, achieving an R² of 0.896, an RMSE of 2.746, and an NRMSE of 10.36%. In summary, this study demonstrates that by using the MS–RGB fused feature method and the SVR model, the accuracy of chlorophyll content monitoring can be effectively improved. This approach reduces the need for traditional methods of measuring chlorophyll content in maize canopies and facilitates real-time management of maize crop nutrition.
Can the Carbon Dioxide Fixation of Processing Tomato Plants Compensate for the Emissions of the Tomato Industry?
Authors: Gutiérrez-Cabanillas Juan Ignacio , Ordiales Rey Elena , Carvajal Micaela , Espinosa Borreguero Francisco
Published: August 2024

Processing tomato is one of the most important crops in Extremadura region, Spain, since the largest national agricultural production and first industrial processing of this sector is concentrated in this area. In these two production stages, greenhouse gases (GHGs) are emitted, but there is also a capture of atmospheric carbon dioxide (CO2) by the plants and therefore, this study focuses on assessing the carbon balance of this activity in this specific crop area. In this work, the amount of CO2 fixed by tomato plants is evaluated, bearing in mind the production area and tomato cultivars. Subsequently, the carbon footprint is calculated, and finally, the carbon balance is established for each location. Under the conditions of this study, each processing tomato plant annually fixes 0.6090 kg of CO2, and each kilogram of tomato produced allows 0.1905 kg of CO2 to be captured. In contrast, GHG emissions average 0.0338 kg CO2 equivalent; therefore, the carbon balance is clearly positive. Even adding the emissions from the industry to those from farming, the carbon balance of this activity is clearly positive (0.0900 kg CO2 captured for each kg of tomato processed), indicating that processing tomato crops in this area of Spain could more than compensate for the emissions produced.
Evaluation of the Long-Term Water Balance in Selected Crop Rotations with Alfalfa in a Soil-Heterogeneous Lowland Region of the Czech Republic
Authors: Placatová Renata , Papaj Vladimír , Fučík Petr , Brázda Jiří , Pacek Lukáš , Tlustoš Pavel
Published: August 2024

The Czech Republic has diverse soil conditions, which cause notable differences in crop water balance (WB). To assess the long-term crop WB and crop water stress (CWS) intensity in rainfed conditions, four conventional eight- and ten-year crop rotations (CRs) with perennial forage (alfalfa), cereals, oilseeds, root crops and legumes were proposed for a heterogeneous lowland soil region (six texture classes) in eastern Bohemia. Two of the CRs were selected irrespective of the WB (eight-year, C-8; ten-year, C-10), and the other two were designated according to soil water resources and crop water requirements (CWRs) as water-saving (W-S) and water-demanding (W-D) for this region. All CRs had a negative WB on average (i.e., CWRs exceeded the available water resources), with varying degrees of CWS (categories 1 (low) to 4 (high)). The W-S CR reduced the WB deficit relative to the other CRs by omitting maize, sunflower and sugar beet and including sorghum, and expanded the proportion of the area not affected by CWS (categories 1–2) to 33% for predominantly loamy soils. In contrast, categories 1–2 in the C-8, C-10 and W-D CRs represented only 15%, 14% and 7% of the area, respectively. Other areas were significantly affected by CWS (categories 3–4) and showed a high risk of yield reduction. These results may help in implementing sustainable farming systems that consider environmental perspectives related to agricultural water use in Central Europe.
Comprehensive Dissection of Metabolites in Response to Low Phosphorus Stress in Different Root-Type Alfalfa at Seedling Stage
Authors: Xia Jing , Nan Lili , Wang Kun , Yao Yuheng
Published: August 2024

Medicago sativa is a high-quality legume forage that is widely cultivated around the world. However, low phosphorus (LP) stress is one of the main limiting factors for its yield and quality. Currently, it is unclear how various alfalfa root types respond to LP stress. Thus, the creeping-rooted M. varia ‘Gannong No. 4’ (or GN), tap-rooted M. sativa ‘Longdong’ (or LD), and rhizomatous-rooted M. sativa ‘Qingshui’ (or QS) were selected to detect changes in growth, metabolites, phytohormones, and organic acids after 34 days of LP stress treatment (0.01 mmol·L−1 KH2PO4). We observed LP stress significantly inhibited plant growth, and 123, 73, and 42 considerably upregulated differential metabolites were categorized into 33, 26, and 20 metabolic pathways in GN, LD, and QS under LP stress, respectively. Amino acids, plant growth regulators, and organic acids are the main metabolites. After 34 d of LP treatment, the plant height, total surface area, leaf length, ground biomass, leaf width, total volume, leaf area, and ZT content of different root types of alfalfa significantly decreased, while the contents of malic acid, citric acid, oxalic acid, IAA, ABA, and GA3 significantly increased. The plant height, leaf length, leaf width, leaf area, total surface area, total volume, ground biomass, root biomass, the number of different metabolites, and the contents of malic, citric, and oxalic acid, and IAA of GN were significantly higher than those of QS and LD under LP stress. From this point of view, GN was more tolerant than LD and QS under the LP condition.
Vision Transformers in Optimization of AI-Based Early Detection of Botrytis cinerea
Authors: Christakakis Panagiotis , Giakoumoglou Nikolaos , Kapetas Dimitrios , Tzovaras Dimitrios , Pechlivani Eleftheria-Maria
Published: August 2024

Detecting early plant diseases autonomously poses a significant challenge for self-navigating robots and automated systems utilizing Artificial Intelligence (AI) imaging. For instance, Botrytis cinerea, also known as gray mold disease, is a major threat to agriculture, particularly impacting significant crops in the Cucurbitaceae and Solanaceae families, making early and accurate detection essential for effective disease management. This study focuses on the improvement of deep learning (DL) segmentation models capable of early detecting B. cinerea on Cucurbitaceae crops utilizing Vision Transformer (ViT) encoders, which have shown promising segmentation performance, in systemic use with the Cut-and-Paste method that further improves accuracy and efficiency addressing dataset imbalance. Furthermore, to enhance the robustness of AI models for early detection in real-world settings, an advanced imagery dataset was employed. The dataset consists of healthy and artificially inoculated cucumber plants with B. cinerea and captures the disease progression through multi-spectral imaging over the course of days, depicting the full spectrum of symptoms of the infection, ranging from early, non-visible stages to advanced disease manifestations. Research findings, based on a three-class system, identify the combination of U-Net++ with MobileViTV2-125 as the best-performing model. This model achieved a mean Dice Similarity Coefficient (mDSC) of 0.792, a mean Intersection over Union (mIoU) of 0.816, and a recall rate of 0.885, with a high accuracy of 92%. Analyzing the detection capabilities during the initial days post-inoculation demonstrates the ability to identify invisible B. cinerea infections as early as day 2 and increasing up to day 6, reaching an IoU of 67.1%. This study assesses various infection stages, distinguishing them from abiotic stress responses or physiological deterioration, which is crucial for accurate disease management as it separates pathogenic from non-pathogenic stress factors. The findings of this study indicate a significant advancement in agricultural disease monitoring and control, with the potential for adoption in on-site digital systems (robots, mobile apps, etc.) operating in real settings, showcasing the effectiveness of ViT-based DL segmentation models for prompt and precise botrytis detection.
Use of Bedinvetmab (Librela®) for Canine Osteoarthritis in France, Germany, Italy, Spain, and the UK: Quantitative Analysis of Veterinarian Satisfaction and Real-World Treatment Patterns
Authors: Gildea Edwina , North Cyndy , Walker Kate , Adriaens Francis , Lascelles Benedict Duncan X.
Published: August 2024

Bedinvetmab (Librela®) represents a new class of canine osteoarthritis pain therapy. The aim of this study was to understand patient selection, usage behaviours, and satisfaction amongst veterinarians using bedinvetmab. Overall, 1932 patient record forms (PRF) were collected from 375 veterinarians across five countries in Europe. Veterinarians were asked to provide 5–7 PRF representing an average patient prescribed bedinvetmab. Veterinarian satisfaction with bedinvetmab usage averaged 8.0 out of 10.0 across all countries. Dissatisfaction as a reason for discontinuation was less than 1% for veterinarians. Veterinarians prescribed bedinvetmab broadly, across patient severity stages, weights, and ages. Adherence to monthly dosing per the product label was over 99%, and compliance with bedinvetmab treatment regimens was 85%. Following initiation of bedinvetmab, the proportion of patients requiring multiple pharmacological therapies for osteoarthritis pain fell from 47% to 31% (p < 0.05). After initiation of bedinvetmab, the mean total number of pharmacological therapies per patient across the population was 1.3, a reduction from 1.9 pre-treatment (p < 0.05). This investigation provides evidence on the benefit of bedinvetmab use post-launch in a broad population of dogs across the five most populous countries in western Europe. Compliance and satisfaction appear high and the use of other analgesic therapies to treat osteoarthritis pain is reduced in most cases following administration of bedinvetmab.
Breeding Value Estimation Based on Morphological Evaluation of the Maremmano Horse Population through Factor Analysis
Authors: Giontella Andrea , Silvestrelli Maurizio , Cocciolone Alessandro , Pieramati Camillo , Sarti Francesca Maria
Published: August 2024

Morphological scoring is a common evaluation method for domestic animals. The National Association of Maremmano Breeders (ANAM) has provided a dataset containing the records of 600 horses, four metric measurements (cm) and 24 traits with a continuous evaluation scale, each one with 15 classes. Moreover, a body condition score (BCS) with five classes is included. In this study, factor analysis was conducted to create a small number of informative factors (3) obtained from these traits, and a new BLUP-AM-MT index was established. The New Estimated Breeding Value (NEBV1) of each horse was computed by adding the genetic indexes of the three factors, with each one multiplied using a coefficient indicated by ANAM. The practical feasibility of the NEBV1 was evaluated through Spearman correlations between the rankings of the NEBV1 and the rankings of the BLUP-AM-MT, estimated through the four biometric measures and the morphological score (MS) assigned to each horse by the ANAM judges. The factorial analysis was used to estimate three factors: the “Trunk Dimension”, “Legs” and “Length”. As the explained variance was only 32%, the model was rotated, and the heritability of the three factors were 0.51, 0.05 and 0.41, respectively. After rotation, the estimated correlations between the new NEBV1 and the biometric measures were improved. These results should encourage breeders to adopt a breeding value index that takes into consideration the factors derived from all the variables observed in the morphological evaluation of the Maremmano. In this way, breeders can use it to select the best animals for breeding.
Comparative Study on the Sperm Proteomes of Horses and Donkeys
Authors: Ren Hong , Wen Xin , He Qianqian , Yi Minna , Dugarjaviin Manglai , Bou Gerelchimeg
Published: August 2024

The reproductive performance of horse sperm and donkey sperm has been reported to differ. Sperm proteins play a crucial role in sperm viability and fertility. Although differences between species are known, no prior study has investigated disparities in the sperm proteome between horses and donkeys. Therefore, this study characterized and compared the sperm proteomes of horses and donkeys using 4D-DIA mass spectrometry technology. We identified 3436 proteins in horse sperm and 3404 proteins in donkey sperm. Of these, 3363 proteins were expressed in both horse and donkey sperm, with 73 proteins being specifically expressed in horse sperm, and 41 in donkey sperm. According to data analysis, donkeys exhibited a greater percentage of motility and progressive movement in straight-line sperm than horses, as well as lower percentages of static and slow sperm than horses. Joint analysis of the results from the horse and donkey sperm proteomes and their CEROS II-read parameters demonstrated a possible association between sperm proteins and their sperm viability patterns. These findings suggest that there are discrepancies in the expression levels and protein compositions of horse and donkey sperm and that certain specific proteins may be responsible for the differences in performance between these two species.
Advances in Donkey and Mule Research
Authors: Martins-Bessa Ana , McLean Amy K.
Published: August 2024

Donkeys (Equus asinus) and mules represent approximately 50% of the entire domestic equine population in the world and play an essential role in the lives of thousands of people, primarily in developing countries [...]
Knowledge of the Serological Response to the Third BNT162b2 Vaccination May Influence Compliance of Healthcare Workers to Booster Dose
Authors: Magid Avi , Hussein Khetam , Dabaja-Younis Halima , Szwarcwort-Cohen Moran , Almog Ronit , Mekel Michal , Weissman Avi , Hyams Gila , Gepstein Vardit , Horowitz Netanel A. , Cohen Saban Hagar , Tarabeia Jalal , Halberthal Michael , Shachor-Meyouhas Yael
Published: August 2024

Background: Previous studies showed that the fourth SARS-CoV-2 vaccine dose has a protective effect against infection, as well as against severe disease and death. This study aimed to examine whether knowledge of a high-level antibody after the third dose may reduce compliance to the fourth booster dose among healthcare workers (HCWs). Methods: We conducted a prospective cohort study among HCWs vaccinated with the first three doses at Rambam Healthcare Campus, a tertiary hospital in northern Israel. Participants underwent a serological test before the fourth booster vaccine was offered to all of them, with results provided to participants. The population was divided into two groups, namely those with antibodies below 955 AU/mL and those with 955 AU/mL and higher, a cutoff found protective in a previous study. Multiple logistic regression was carried out to compare the compliance to the fourth booster between the two groups, adjusted for demographic and clinical variables. Results: After adjusting for the confounding variables, the compliance was higher in those with antibody levels below 955 AU/mL (OR = 1.41, p = 0.05, 95% CI 1.10–1.96). In addition, male sex and age of 60 years and above were also associated with higher vaccination rates (OR = 2.28, p < 0.001, 95% CI 1.64–3.17), (OR = 1.14, p = 0.043, 95% CI 1.06–1.75), respectively. Conclusions: Knowledge of the antibody status may affect compliance with the booster dose. Considering waning immunity over time, reduced compliance may affect the protection of HCWs who declined the fourth dose.
Bioaffinity Ultrafiltration Combined with HPLC-ESI-qTOF-MS/MS for Screening Potential Bioactive Components from the Stems of Dendrobium fimbriatum and In Silico Analysis
Authors: Hsieh Yu-Hui , Chuang Wu-Chang , Lee Ming-Chung , Fan Yu-Hsin , Huang Nai-Kuei , Chen Jih-Jung
Published: August 2024

Dendrobium fimbriatum is a perennial herb, and its stems are high-grade tea and nourishing medicinal materials. Various solvent extracts of D. fimbriatum were evaluated for their anti-inflammatory, anti-acetylcholinesterase (AChE), antioxidant, and anti-α-glucosidase properties. Acetone and EtOAc extracts showed significant antioxidant effects. Acetone, n-hexane, and EtOAc extracts revealed potent inhibition against α-glucosidase. EtOAc, n-hexane, and dichloromethane extracts displayed significant anti-AChE activity. Among the isolated constituents, gigantol, moscatin, and dendrophenol showed potent antioxidant activities in FRAP, DPPH, and ABTS radical scavenging tests. Moscatin (IC50 = 161.86 ± 16.45 μM) and dendrophenol (IC50 = 165.19 ± 13.25 μM) displayed more potent anti-AChE activity than chlorogenic acid (IC50 = 236.24 ± 15.85 μM, positive control). Dendrophenol (IC50 = 14.31 ± 3.17 μM) revealed more efficient anti-NO activity than quercetin (positive control, IC50 = 23.09 ± 1.43 μM). Analysis of AChE and iNOS inhibitory components was performed using molecular docking and/or the bioaffinity ultrafiltration method. In bioaffinity ultrafiltration, the binding affinity of compounds to the enzyme (acetylcholinesterase and inducible nitric oxide synthase) was determined using the enrichment factor (EF). Among the main components of the EtOAc extract from D. fimbriatum stem, moscatin, dendrophenol, gigantol, and batatasin III with acetylcholinesterase exhibited the highest binding affinities, with affinity values of 66.31%, 59.48%, 54.60%, and 31.87%, respectively. Moreover, the affinity capacity of the identified compounds with inducible nitric oxide synthase can be ranked as moscatin (88.99%) > dendrophenol (65.11%) > gigantol (44.84%) > batatasin III (27.18%). This research suggests that the bioactive extracts and components of D. fimbriatum stem could be studied further as hopeful candidates for the prevention or treatment of hyperglycemia, oxidative stress-related diseases, and nervous disorders.
Unveiling the Therapeutic Potential of Kelulut (Stingless Bee) Honey in Alzheimer’s Disease: Findings from a Rat Model Study
Authors: Shaikh Ammara , Ahmad Fairus , Teoh Seong Lin , Kumar Jaya , Yahaya Mohamad Fairuz
Published: August 2024

Alzheimer’s disease (AD) poses a major worldwide health challenge because of its profound impact on cognitive abilities and overall well-being. Despite extensive research and numerous clinical trials, therapeutic options remain limited. Our study aimed to investigate the potential of Kelulut honey (KH) as a novel therapeutic agent for addressing the multifactorial pathology of AD. We tried to evaluate the disease-attenuating and neuroprotective potential of KH in the intrahippocampally induced AD rat model by utilizing histochemistry and enzyme-linked immunosorbent assay (ELISA) studies. A total of 26 male Sprague Dawley rats weighing ~280–380 g were randomly divided into three groups: Control, AD-induced (Aβ), and AD-induced and treated with KH (Aβ+KH). The latter two groups underwent stereotaxic surgery, where 6.25 µg of amyloid β1–42 peptides were injected intrahippocampally. One-week post-surgery, KH was administered to the treatment group at a dose of 1 g/kg body weight for a period of four weeks, after which the rats went through behavior tests. After completion of behavior analysis, the rats were sacrificed, and the brains were processed for histochemistry and ELISA studies. The open field test analysis demonstrated that KH improved the locomotion of Aβ+KH compared to Aβ (p = 0.0013). In comparison, the Morris water maze did not show any nootropic effects on cognition with a paradoxical increase in time spent in the target quadrant by the Aβ group (p = 0.029). Histochemical staining showed markedly increased Congo-red-stained amyloid plaques, which were significantly reduced in dentate gyrus of Aβ+KH compared to Aβ (p < 0.05). Moreover, significantly higher apoptosis was seen in the Aβ group compared to Aβ+KH (p < 0.01) and control groups (p < 0.001). Furthermore, the ELISA studies deduced more phosphorylated tau in the diseased group compared to Aβ+KH (p = 0.038) and controls (p = 0.016). These findings suggest that KH consumption for twenty-eight days has the potential to attenuate the pathological burden of disease while exerting neuroprotective effects in rodent models of AD.
Phytoene and Phytoene-Rich Microalgae Extracts Extend Lifespan in C. elegans and Protect against Amyloid-β Toxicity in an Alzheimer’s Disease Model
Authors: Morón-Ortiz Ángeles , Karamalegkos Antonis A. , Mapelli-Brahm Paula , Ezcurra Marina , Meléndez-Martínez Antonio J.
Published: August 2024

Phytoene is a colourless carotenoid widely available from dietary sources and a precursor for the synthesis of other carotenoids. Although present at high concentrations across different tissues, phytoene is largely viewed as not having physiological activity. Here, we utilize the model organism C. elegans to show that phytoene is bioactive and has anti-ageing properties. Supplementation with phytoene protects against oxidative damage and amyloid-β42 proteotoxicity (a major pathology of Alzheimer’s disease), and extends lifespan. We also examine extracts from two microalgae, Chlorella sorokiniana and Dunaliella bardawil. We show that the extracts contain high levels of phytoene, and find that these phytoene-rich extracts have protective effects similar to pure phytoene. Our findings show that phytoene is a bioactive molecule with positive effects on ageing and longevity. Our work also suggests that phytoene-rich microalgae extracts can utilized to produce foods or supplements that promote healthy ageing and prevent the development of chronic age-related diseases.
Oxidative Stress in Alcohol Abuse: An Unfortunately Still Open Question
Authors: Fiore Marco
Published: August 2024

As the guest editor of this Special Issue “Alcohol-Induced Oxidative Stress in Health and Disease” of Antioxidants (https://www [...]
Multi-Objective Optimization of Pick-Up and Delivery Operations in Bike-Sharing Systems Using a Hybrid Genetic Algorithm
Authors: Lim Heejong , Chung Kwanghun , Lee Sangbok
Published: August 2024

In this study, we present a framework for optimizing pick-up and delivery operations in bike-sharing systems (BSSs), with particular emphasis on inventory rebalancing and vehicle routing to enhance operational efficiency. By employing a hybrid genetic algorithm (HGA), this study integrates sophisticated predictive models with multi-objective optimization techniques to strike a balance between operational efficiency and demand fulfillment in urban bike-share networks. For probabilistic demand forecasting, the DeepAR model is applied to a large number of bike stations clustered by geological proximity to enable stochastic inventory management. Our proposed HGA approach leverages both the genetic algorithm for generating feasible vehicle routes and mixed-integer programming for bike rebalancing to minimize travel distances while maintaining balanced inventory levels across all clustered stations. Through rigorous empirical evaluations, we demonstrate the effectiveness of our proposed methodology in improving service quality, thus making significant contributions to sustainable urban mobility. This study not only pushes the boundaries of theoretical knowledge in BSS logistics optimization but also offers managerial insights for practical implementation, particularly in densely populated urban settings.
Stratification of Older Adults According to Frailty Status and Falls Using Gait Parameters Explored Using an Inertial System
Authors: Neira Álvarez Marta , Huertas-Hoyas Elisabet , Novak Robert , Sipols Ana Elizabeth , García-Villamil-Neira Guillermo , Rodríguez-Sánchez M. Cristina , Del-Ama Antonio J. , Ruiz-Ruiz Luisa , De Villa Sara García , Jiménez-Ruiz Antonio R.
Published: August 2024

Background: The World Health Organization recommends health initiatives focused on the early detection of frailty and falls. Objectives: 1—To compare clinical characteristics, functional performance and gait parameters (estimated with the G-STRIDE inertial sensor) between different frailty groups in older adults with and without falls. 2—To identify variables that stratify participants according to frailty status and falls. 3—To verify the sensitivity, specificity and accuracy of the model that stratifies participants according to frailty status and falls. Methods: Observational, multicenter case-control study. Participants, adults over 70 years with and without falls were recruited from two outpatient clinics and three nursing homes from September 2021 to March 2022. Clinical variables and gait parameters were gathered using the G-STRIDE inertial sensor. Random Forest regression was applied to stratify participants. Results: 163 participants with a mean age of 82.6 ± 6.2 years, of which 118 (72%) were women, were included. Significant differences were found in all gait parameters (both conventional assessment and G-STRIDE evaluation). A hierarchy of factors contributed to the risk of frailty and falls. The confusion matrix and the performance metrics demonstrated high accuracy in classifying participants. Conclusions: Gait parameters, particularly those assessed by G-STRIDE, are effective in stratifying individuals by frailty status and falls. These findings underscore the importance of gait analysis in early intervention strategies.
A Machine Learning Model for Predicting Critical Minimum Foot Clearance (MFC) Heights
Authors: Nagano Hanatsu , Prokofieva Maria , Asogwa Clement Ogugua , Sarashina Eri , Begg Rezaul
Published: August 2024

Tripping is the largest cause of falls, and low swing foot ground clearance during the mid-swing phase, particularly at the critical gait event known as Minimum Foot Clearance (MFC), is the major risk factor for tripping-related falls. Intervention strategies to increase MFC height can be effective if applied in real-time based on feed-forward prediction. The current study investigated the capability of machine learning models to classify the MFC into various categories using toe-off kinematics data. Specifically, three MFC sub-categories (less than 1.5 cm, between 1.5 and 2.0 cm, and higher than 2.0 cm) were predicted to apply machine learning approaches. A total of 18,490 swing phase gait cycles’ data were extracted from six healthy young adults, each walking for 5 min at a constant speed of 4 km/h on a motorized treadmill. K-Nearest Neighbor (KNN), Random Forest, and XGBoost were utilized for prediction based on the data from toe-off for five consecutive frames (0.025 s duration). Foot kinematics data were obtained from an inertial measurement unit attached to the mid-foot, recording tri-axial linear accelerations and angular velocities of the local coordinate. KNN, Random Forest, and XGBoost achieved 84%, 86%, and 75% accuracy, respectively, in classifying MFC into the three sub-categories with run times of 0.39 s, 13.98 s, and 170.98 s, respectively. The KNN-based model was found to be more effective if incorporated into an active exoskeleton as the intelligent system to control MFC based on the preceding gait event, i.e., toe-off, due to its quicker computation time. The machine learning-based prediction model shows promise for the prediction of critical MFC data, indicating higher tripping risk.
A Lightweight YOLOv8 Model for Apple Leaf Disease Detection
Authors: Gao Lijun , Zhao Xing , Yue Xishen , Yue Yawei , Wang Xiaoqiang , Wu Huanhuan , Zhang Xuedong
Published: August 2024

China holds the top position globally in apple production and consumption. Detecting diseases during the planting process is crucial for increasing yields and promoting the rapid development of the apple industry. This study proposes a lightweight algorithm for apple leaf disease detection in natural environments, which is conducive to application on mobile and embedded devices. Our approach modifies the YOLOv8n framework to improve accuracy and efficiency. Key improvements include replacing conventional Conv layers with GhostConv and parts of the C2f structure with C3Ghost, reducing the model’s parameter count, and enhancing performance. Additionally, we integrate a Global attention mechanism (GAM) to improve lesion detection by more accurately identifying affected areas. An improved Bi-Directional Feature Pyramid Network (BiFPN) is also incorporated for better feature fusion, enabling more effective detection of small lesions in complex environments. Experimental results show a 32.9% reduction in computational complexity and a 39.7% reduction in model size to 3.8 M, with performance metrics improving by 3.4% to a mAP@0.5 of 86.9%. Comparisons with popular models like YOLOv7-Tiny, YOLOv6, YOLOv5s, and YOLOv3-Tiny demonstrate that our YOLOv8n–GGi model offers superior detection accuracy, the smallest size, and the best overall performance for identifying critical apple diseases. It can serve as a guide for implementing real-time crop disease detection on mobile and embedded devices.
Synergistic Effects of Fuel Components on Aromatics Formation in Combustion: A Review
Authors: Hussain Bilal , Li Wei , Fang Qilong , Li Yuyang
Published: August 2024

Aromatics, especially polycyclic aromatic hydrocarbons (PAHs), are important combustion pollutants known to be carcinogenic and mutagenic and are also precursors of soot and, consequently, combustion-generated particulate matters that can significantly threaten environmental security and human health. In engine combustion, the multi-component and broad-source feature of transportation fuels makes synergistic effects commonly exist and greatly enhances the formation of aromatics and soot. Understanding the synergistic effects of different fuel components on aromatic formation facilitates concrete guidance for controlling soot emissions. This review focuses specifically on the synergistic effects of aromatics formation, including benzene, indene, naphthalene, and larger PAHs, in combustion among hydrocarbon blends and hydrocarbons blended with oxygenated fuels. Progresses in experimental measurements, theoretical calculations of critical reactions, and kinetic modeling are reviewed in detail. Special attention is paid to blends of aromatics and linear fuels, which show pronounced synergistic effects in PAH formation. Furthermore, some prospects for future research on synergistic effects in aromatic formation are provided.
A Model of Information Visualization Interpretation
Authors: Hilgers Michael G.
Published: August 2024

Since the groundbreaking work by Cleveland and McGill in 1984, studies have revealed the difficulties humans have extracting quantitative data from visualizations as simple as bar graphs. As a first step toward understanding this situation, this paper proposes a mathematical model of the interpretation effort of a bar graph using concepts drawn from eye tracking. First, three key areas of interest (AOIs) are identified, and fixations are modeled as random point clouds within the AOIs. Stochastic geometry is introduced via random triangles connecting fixations within the adjacent key visual regions. The so-called landmark methodology provides the basis for the probabilistic analysis of the constructed system. It is found that the random length of interest in a stochastic triangle has a noncentral chi distribution with a known mean. Unique to this model, in terms of previous landmark applications, is the inclusion of a correlation between fixations, which is justified by physiological studies of the eyes. This approach introduces several model parameters, such as the noncentrality parameter, variance of the fixation cloud, correlation between fixations, and a visualization scale. A detailed parametric analysis examining the dependence of the mean on these parameters is conducted. The paper ties this work to the visualization via a definition of the expected visual measurement error. An asymptotic analysis of the visual error is performed, and a simple expression is found to relate the expected visual measurement error to the key model parameters. From this expression, the influence these parameters have on a visualization’s interpretation is considered.
Performance of Strengthened Accelerated Oscillator Damper for Vibration Control of Bridges
Authors: Zhao Qiuming , Tan Yonggang , Sun Minggang , Jiang Yunlong , Wang Pinqing , Meng Fanxu , Li Zhijun
Published: August 2024

Vibration control has emerged as a significant concern in civil engineering, aiming to minimize the displacement and stress exerted on structures during seismic events. The accelerated oscillator damper (AOD), which is a damping device that depends on acceleration, has been demonstrated to be highly effective. However, in the case of traditional bridges, it is difficult to accurately place the secondary mass, spring, and damping components at the piers. Additionally, it has been found that as a general single-degree-of-freedom (SDOF) damping device, a significant limitation of the AOD system is its insufficient damping effect in the near-resonance region. This study presents a strengthened AOD with a liner spring (SAOD-LS), in which the secondary spring and damper are linked to the primary structure rather than being attached to the piers. This design not only provides enough space for the secondary system but also has a higher amplification factor of secondary spring and damping components compared with the original layout. In addition, we suggest a nonlinear spring device (NSD) that includes connecting rods and inclined linear springs arranged in a diamond configuration. This innovative design is intended to introduce nonlinear stiffness characteristics into the equivalent stiffness, thereby improving the device’s performance and providing effective anti-resonance features in the near-resonance region. We have confirmed the motion equations for the SAOD-LS and used finite element (FE) analysis to validate the formulation of the equivalent external force and deformation of the NSD. We have thoroughly investigated both the SAOD-LS and the strengthened AOD equipped with NSD as the secondary spring (SAOD-NSD) for their potential implementation in a bridge project. These damping systems demonstrate exceptional performance and robustness, making them highly suitable for enhancing structural resistance to seismic activity.
Electrocatalytic Nanomaterials Improve Microbial Extracellular Electron Transfer: A Review
Authors: Wang Xiaopin , Li Xu , Zhu Qisu
Published: August 2024

Microbial electrochemical systems that integrate the advantages of inorganic electrocatalysis and microbial catalysis are expected to provide sustainable solutions to the increasing energy shortages, resource depletion, and climate degradation. However, sluggish extracellular electron transfer (EET) at the interface between electroactive microorganisms and inorganic electrode materials is a critical bottleneck that limits the performance of systems. Electrocatalytic nanomaterials are highly competitive in overcoming this obstacle due to their effective association with microbial catalysis. Therefore, this review focuses on the cutting-edge applications and enhancement mechanisms of nanomaterials with electrocatalytic activity in promoting microbial EET. First, the EET mechanism of microbial electrocatalysis in both microbial anodes and cathodes is briefly introduced, and then recent applications of various electrocatalytic nanomaterials in diverse microbial electrochemical systems are summarized, including heteroatom-doped carbons and precious metal, as well as transition metal oxides, sulfides, carbides, and nitrides. The synergistic effects of nanomaterial electrocatalysis and microbial catalysis on enhancing interfacial EET are analyzed. Finally, the challenges and perspectives of realizing high-performance microbial electrochemical systems are also discussed in order to offer some reference for further research.
Observations about Propagation, Attenuation, and Radiation of EMI from HVDC Converter Stations
Authors: Schneider John B. , Olsen Robert G.
Published: August 2024

The electromagnetic interference (EMI) generated by switching operations within high-voltage DC (HVDC) converter stations is an issue that has been addressed by CIGRE, and methods to manage EMI should be considered in the design phase using electromagnetic modeling techniques. It is shown that the methods of the moments-based techniques that have been used in many previous studies may not be sufficient. Here, a finite-difference time-domain method is used to study the properties of single switching events using a realistic model of an HVDC converter station with a special emphasis on determining the impact of the valve hall on shielding EMI. It is shown that the valve hall does not confine high-frequency electromagnetic fields to the valve hall; rather, it delays them from exiting through bushings in the wall and spreads them out in time. Further, it is shown that incorporating electromagnetic absorbing material into the valve hall’s design can significantly reduce EMI outside the converter station.
Health Benefits of Kimchi, Sauerkraut, and Other Fermented Foods of the Genus Brassica
Authors: Fijan Sabina , Fijan Polona , Wei Lei , Marco Maria L.
Published: August 2024

Fermented foods made through microbial growth and enzymatic conversions have been integral to human diets for at least 10,000 years. Recent interest in fermented foods has surged due to their functional properties and health benefits. Cruciferous vegetables of the genus Brassica, such as cabbage, broccoli, and cauliflower, are commonly used to produce fermented foods like sauerkraut, kimchi, pao cai, fermented turnips, and others. These foods are rich in lactic acid bacteria (LAB) and bioactive compounds, which contribute to their potential health-promoting properties. We examined 12 clinical trials investigating fermented foods of the genus Brassica. These studies, which mainly assessed the health benefits of kimchi or sauerkraut consumption, found that regular intake can alleviate symptoms of irritable bowel syndrome (IBS), aid weight loss, and enhance metabolic health. Seven observational studies also observed health benefits when consuming fermented foods of the genus Brassica. Six of the seven observational studies on kimchi intake linked kimchi intake to reduced obesity risk and other health benefits. An observational study linked sauerkraut and cabbage consumption to reduced breast cancer risk. Despite these findings, the exact roles of various microorganisms and bioactive compounds within these health effects require further investigation. This review underscores the potential of fermented cruciferous vegetables as functional foods, and advocates for more clinical trials and mechanistic studies to understand and optimize their health benefits.