bluuebunny/crossref_metadata_2025 huggingface dataset:
The influence of sex-division, experience, and pacing strategy on performance in the 2020 CrossFit® Open
Authors: Mangine Gerald T. , Zeitz Elisabeth K. , Dexheimer Joshua D. , Hines Ashley , Lively Brandon , Kliszczewicz Brian M.
Published: January 2024

To observe workout pacing strategies and determine which best predicted performance, this retrospective study analyzed recorded efforts from a random selection of 160 high-ranking (top 10,000) men and women (n = 80 each) in the 2020 CrossFit® Open (CFO). Video recordings submitted to the official competition leaderboard for all five tests were analyzed to quantify overall test completion rates (and tie-break time for test 5 only) and within-test repetition completion rate (repetitions × sec−1) for each exercise, as well as the quantity of failed repetitions, break strategy (count and duration), and transition times. Each variable was aggregated into first-half, last-half, and total-test averages, slopes, and coefficient of variation; except on test 5 (total-test only). Spearman's rank correlation coefficients were calculated between test completion rates, each test's respective pacing variables, competitor demographics (height and body mass) and CFO experience (i.e., past participation, consecutive competitions, and ranks). Stepwise regression using significantly (p < 0.05) correlated variables produced two prediction models for test performance (best predictor only and best overall model within 8 variables) in a validation group (50% of valid efforts) and then cross-validated against remaining athletes. When no between-group differences were seen, data were combined and used to create the final prediction models for test 1 (r2adj = 0.64–0.96, SEE = 0.4–1.2 repetitions × sec−1), test 2 (r2adj = 0.28–0.85, SEE = 2.0–4.5 repetitions × sec−1), test 3 (r2adj = 0.49–0.81, SEE = 1.1–1.7 repetitions × sec−1), test 4 (r2adj = 0.63–0.78, SEE = 0.6–0.9 repetitions × sec−1), and test 5 (rate: r2adj = 0.71–0.84, SEE = 1.2–1.6 repetitions × sec−1; tie-break time: r2adj = 0.06–0.62, SEE = 1.4–2.3 min). Across the five 2020 CFO tests, the data suggested that repetition pace, breaking strategy, and/or consistency in completing calisthenic-gymnastics components (when prescribed) was most predictive of performance. However, their influence was affected by the complexity of prescribed resistance training exercises and their relative loads. Athletes should prioritize calisthenic-gymnastics components but divert attention to more complex resistance training exercises when prescribed at higher relative intensity loads. Neither previous competition experience nor sex-division altered the hierarchal importance of these considerations.
Effect of sub-optimal moisture levels on the quality of groundnut (Arachis hypogaea L.) during storage in triple-layer hermetic storage bags
Authors: Swathi Y. , Rajanikanth P. , Jella Satya Narayana , Mangala Uppala N. , Adithya Guntha , Anilkumar Vemula , Sudini Hari Kishan
Published: January 2024

Storage is an important aspect of groundnut, as the in-shell and shelled kernels are prone to infestation by insects, pests, and fungi. Among several storage pests, the groundnut bruchid, Caryedon serratus, causes serious losses. Farmers often resort to different management practices, including hermetic storage, to control it. The moisture content of the commodity plays an important role in insect infestation during storage. Drying to safe moisture levels before storage is known to prevent the activity of various living organisms, such as storage pests. However, drying to low levels of moisture may not be economical for farmers, as they may not have access to devices to accurately check product moisture. In this regard, we wanted to demonstrate the efficacy of triple-layer hermetic storage bags in preventing the damage caused by C. serratus when the groundnuts are stored at intermediate (10%) and high (14%) levels of moisture compared to traditionally used bags such as polypropylene bags and jute bags. Groundnut pods at 10% moisture content and 14% moisture content were separately inoculated with adult bruchids and a toxigenic strain of Aspergillus flavus fungal inoculum before storing them for 6 months. Results from groundnut samples taken at two-month intervals indicated that groundnut pods stored in triple-layer hermetic bags were completely free from infestation by C. serratus by recording a zero number of eggs laid, number of pupae, adult emergence, percentage of loss, and percentage of damage up to 6 months of storage, by creating low oxygen (hypoxia) and high carbon dioxide (hypercarbia) conditions. Results also indicate no loss of pod weight stored in triple-layer bags, but a slight reduction in germination percentage was recorded due to a slight increase in fungal activity, but the reduction was significantly less in triple-layer plastic bags compared to other bag types. Similarly, biochemical constituents such as oil and protein content were slightly reduced in triple-layer plastic bags when pods were stored at a 10% moisture level, but a higher reduction was observed at a 14% moisture level. However, the reduction was very high and significant in other bag types at both 10 and 14% moisture levels.
Off-pump minimally invasive coronary artery bypass grafting in patients with left ventricular dysfunction: the lampang experience
Authors: Ushioda Ryohei , Hirofuji Aina , Yoongtong Dit , Sakboon Boonsap , Cheewinmethasiri Jaroen , Kamiya Hiroyuki , Arayawudhikul Nuttapon
Published: January 2024

Introduction

The minimally invasive cardiac surgery off-pump coronary artery bypass (MICSOPCAB) is technically difficult; therefore, previous studies have indicated that MICSOPCAB should be contraindicated in patients with impaired left ventricular (LV) function. In this study, we investigated the feasibility of MICSOPCAB in patients with impaired LV function.

Methods

The 226 patients underwent MICSOPCAB between August 2017 and September 2022. Our study defined impaired LV function as ejection fraction (EF) in echocardiography 40% or less. The patients were divided into Low EF group (n = 39) and Normal EF group (n = 187).

Results

The Low EF group was in a more critical preoperative condition than Normal EF group (41.0% in the Low EF group vs. 14.4% in the Normal EF group; p < 0.001). For preoperative transthoracic echocardiography, LV end-diastolic diameter (5.5 ± 0.9 cm in the Low EF group vs. 5.0 ± 0.8 cm in the Normal EF group; p < 0.001) and LV end-systolic diameter (4.4 ± 1.0 cm in the Low EF group vs. 3.4 ± 1.0 cm in the Normal EF group; p < 0.001) were significantly larger in the Low EF group. No differences were found in the operative time (180 [160–240] min in the Low EF group vs. 205 [165–253] min in the Normal EF group; p = 0.231) and the median number of distal anastomoses (2 [1–2] in the Low EF group vs. 2 [1–3] in the Normal EF group; p = 0.073). Intensive care unit stay was longer in the Low EF group than in the Normal EF group (2 [1–2] in the Low EF group vs. 1 [1–2] in the Normal EF group; p = 0.010). Perioperative transfusion was more common in the Low EF group than in the Normal EF group (69.7% vs. 49.2%; p = 0.023). There were no differences in major complications, hospital stay, and 30-day mortality. The Kaplan–Meier curve showed no significant difference in postoperative major adverse cardiac or cerebrovascular events rates between the two groups (p = 0.185)

Conclusion

In this study, MICSOPCAB can be performed in patients with low EF having short- and mid-term outcomes similar to patients with normal EF. Therefore, low EF should not be contraindicated in MICSOPCAB.
Comparative pathogenicity of infectious bronchitis virus Massachusetts and Delmarva (DMV/1639) genotypes in laying hens
Authors: Farooq Muhammad , Abd-Elsalam Reham M. , Ratcliff Natalya , Hassan Mohamed S. H. , Najimudeen Shahnas M. , Cork Susan C. , Checkley Sylvia , Niu Yan Dong , Abdul-Careem Mohamed Faizal
Published: January 2024

Infectious bronchitis (IB) is a highly contagious and acute viral disease of chicken caused by the infectious bronchitis virus (IBV) of the family Coronaviridae. Even with extensive vaccination against IB by the poultry industry, the occurrence of new IBV genotypes is a continuous challenge encountered by the global poultry industry. This experiment was designed to compare the pathogenicity of two IBV strains belonging to Massachusetts (Mass) and Delmarva DMV/1639 genotypes. Specific pathogen-free laying hens were challenged during the peak of production (30 weeks), keeping a mock-infected control group. During 21 days of observation following infection, a significant drop in egg production with miss-shaped and soft shells was observed in the DMV/1639 IBV-infected hens only. The DMV/1639 IBV infected group showed prolonged and higher cloacal viral shedding compared with the Mass IBV-infected group. At the end of the study (21 days post-infection), the viral genome loads in the respiratory, urogenital, and immune tissues were significantly higher in the DMV/1639 IBV-infected group compared with the Mass IBV-infected group. Macroscopic lesions such as distorted ova leading to egg peritonitis were observed only in the DMV/1639 IBV-infected group. Moreover, microscopic lesion scores were significantly higher in the lung, kidney, cecal tonsils, and oviduct of the DMV/1639 IBV-infected group compared with the Mass IBV-infected group. Finally, the apoptosis index in the kidney, ovary, magnum, isthmus, and shell gland was significantly higher in the DMV/1639 IBV-infected group compared with the control and Mass-infected groups. This study examined the pathogenicity of two IBV genotypes that are impacting the layer industry in North America.
Treatment of clinically severe bovine mastitis – a scoping review
Authors: Wilm Jensine , Svennesen Line , Kirkeby Carsten , Krömker Volker
Published: January 2024

Mastitis is a major health problem for bovines and can be categorized as non-severe or severe, based on clinical symptoms. A severe case of clinical mastitis is usually defined by the cow being affected systemically. It is important to consider how to handle severe cases because these cases can be fatal and cause high production losses. However, there are generally few detailed treatment guidelines. By conducting a scoping review on the topic, we aimed to synthesize the information that is available on treatment and outcomes, as reported from clinical trials and observational studies. This was facilitated by following the PRISMA-guidelines with a stepwise systematic screening of scientific literature on the subject, retrieved via Pubmed and Web of Science, using pre-defined selection criteria. The results yielded a total of 14 reports of treatment and outcomes in cases of naturally occurring severe clinical mastitis. Cross-trial comparison was difficult due to the different exclusion criteria and outcome definitions. Many studies focused on cases caused by gram-negative bacteria treated with intensive antibiotic protocols, often containing antibiotics that are categorized as critical for human health. Few focused on severe cases caused by gram-positive bacteria or on the relative use of non-antibiotic treatment. In general, only a small number of statistically significant differences were found in trials comparing different treatment protocols, with no obvious trends across trials. Our findings emphasize the need for more research into the treatment efficacy of antibiotic and non-antibiotic options for clinically severe mastitis. Furthermore, consideration of how trial conditions relate to the practical circumstances in a field setting could improve the applicability of reported results. This could help to provide practitioners with the information needed to make evidence-based treatment decisions in cases of clinically severe mastitis.
A Biased-Randomized Discrete Event Algorithm to Improve the Productivity of Automated Storage and Retrieval Systems in the Steel Industry
Authors: Neroni Mattia , Bertolini Massimo , Juan Angel A.
Published: January 2024

In automated storage and retrieval systems (AS/RSs), the utilization of intelligent algorithms can reduce the makespan required to complete a series of input/output operations. This paper introduces a simulation optimization algorithm designed to minimize the makespan in a realistic AS/RS commonly found in the steel sector. This system includes weight and quality constraints for the selected items. Our hybrid approach combines discrete event simulation with biased-randomized heuristics. This combination enables us to efficiently address the complex time dependencies inherent in such dynamic scenarios. Simultaneously, it allows for intelligent decision making, resulting in feasible and high-quality solutions within seconds. A series of computational experiments illustrates the potential of our approach, which surpasses an alternative method based on traditional simulated annealing.
Temperature Prediction of Mushrooms Based on a Data—Physics Hybrid Approach
Authors: Wang Mingfei , Kong Xiangshu , Shan Feifei , Zheng Wengang , Ren Pengfei , Wang Jiaoling , Chen Chunling , Zhang Xin , Zhao Chunjiang
Published: January 2024

Temperature has a significant impact on the production of edible mushrooms. The industrial production of edible mushrooms is committed to accurately maintaining the temperature inside the mushroom room within a certain range to achieve quality and efficiency improvement. However, current environmental regulation methods have problems such as lagging regulation and a large range of temperature fluctuations. There is an urgent need to accurately predict the temperature of mushroom houses in the future period to take measures in advance. Therefore, this article proposes a temperature prediction model for mushroom houses using a data–physical hybrid method. Firstly, the Boruta-SHAP algorithm was used to screen out the key influencing factors on the temperature of the mushroom room. Subsequently, the indoor temperature was decomposed using the optimized variational modal decomposition. Then, the gated recurrent unit neural network and attention mechanism were used to predict each modal component, and the mushroom house heat balance equation was incorporated into the model’s loss function. Finally, the predicted values of each component were accumulated to obtain the final result. The results demonstrated that integrating a simplified physical model into the predictive model based on data decomposition led to a 12.50% reduction in the RMSE of the model’s predictions compared to a purely data-driven model. The model proposed in this article exhibited good predictive performance in small datasets, reducing the time required for data collection in modeling.
Influence of Different Agro-Food Waste on Ammonia and Greenhouse Gas Emissions during Composting
Authors: Pereira José L. S. , Costa Telma , Figueiredo Vitor , Marques Francisco , Perdigão Adelaide , Brás Isabel , Silva Maria E. F. , Wessel Dulcineia F.
Published: January 2024

Composting is one of the best organic waste management techniques, with zero waste; however, it generates environmental impacts. The objective of this study was to evaluate the emission of NH3, N2O, CO2, and CH4 from the composting of olive, elderberry, and grape agro-food waste. The experiment was carried out using reactors receiving straw as control and three treatments receiving mixtures of straw and olive, elderberry, or grape wastes. The gas emissions were measured for 150 days, and the composition of the mixtures and composts was determined. The results showed NH3 and CH4 emissions were reduced by 48% and 29% by the Olive and Elderberry treatments, while only NH3 loss was reduced by 24% by the Grape treatment. Nitrous oxide, CO2, and GWP emissions were reduced by 46%, 32%, and 34% by the Olive treatment, while these losses were not reduced by the Elderberry or Grape treatments. It can be concluded olive waste can effectively reduce NH3 and GWP, while elderberry and grape wastes are also effective in reducing NH3, but not GWP. Thus, the addition of agro-food waste appears to be a promising mitigation strategy to reduce gaseous losses from the composting process.
Bibliometric Mining of Research Trends in Machine Learning
Authors: Lundberg Lars , Boldt Martin , Borg Anton , Grahn Håkan
Published: January 2024

We present a method, including tool support, for bibliometric mining of trends in large and dynamic research areas. The method is applied to the machine learning research area for the years 2013 to 2022. A total number of 398,782 documents from Scopus were analyzed. A taxonomy containing 26 research directions within machine learning was defined by four experts with the help of a Python program and existing taxonomies. The trends in terms of productivity, growth rate, and citations were analyzed for the research directions in the taxonomy. Our results show that the two directions, Applications and Algorithms, are the largest, and that the direction Convolutional Neural Networks is the one that grows the fastest and has the highest average number of citations per document. It also turns out that there is a clear correlation between the growth rate and the average number of citations per document, i.e., documents in fast-growing research directions have more citations. The trends for machine learning research in four geographic regions (North America, Europe, the BRICS countries, and The Rest of the World) were also analyzed. The number of documents during the time period considered is approximately the same for all regions. BRICS has the highest growth rate, and, on average, North America has the highest number of citations per document. Using our tool and method, we expect that one could perform a similar study in some other large and dynamic research area in a relatively short time.
Enhancing Thermo-Acoustic Waste Heat Recovery through Machine Learning: A Comparative Analysis of Artificial Neural Network–Particle Swarm Optimization, Adaptive Neuro Fuzzy Inference System, and Artificial Neural Network Models
Authors: Ngcukayitobi Miniyenkosi , Tartibu Lagouge Kwanda , Bannwart Flávio
Published: January 2024

Waste heat recovery stands out as a promising technique for tackling both energy shortages and environmental pollution. Currently, this valuable resource, generated through processes like fuel combustion or chemical reactions, is often dissipated into the environment, despite its potential to significantly contribute to the economy. To harness this untapped potential, a traveling-wave thermo-acoustic generator has been designed and subjected to comprehensive experimental analysis. Fifty-two data corresponding to different working conditions of the system were extracted to build ANN, ANFIS, and ANN-PSO models. Evaluation of performance metrics reveals that the ANN-PSO model demonstrates the highest predictive accuracy (R2=0.9959), particularly in relation to output voltage. This research demonstrates the potential of machine learning techniques for the analysis of thermo-acoustic systems. In doing so, it is possible to obtain an insight into nonlinearities inherent to thermo-acoustic systems. This advancement empowers researchers to forecast the performance characteristics of alternative configurations with a heightened level of precision.
Skepticism in the Early Stage of the Introduction of Environmental Enrichment in Japanese Zoos
Authors: Ota Kazuhiko , Yamazaki Saika
Published: January 2024

This study examines the Japanese zoo staff’s initial skepticism and bewilderment regarding animal welfare and environmental enrichment in the mid-1990s. Utilizing a 2001 questionnaire conducted by the Japanese Association of Zoos and Aquariums and existing literature reveals that this resistance stemmed from inadequate information, cultural history, and legal perspectives on animal care. Specifically, environmental enrichment was initially misunderstood as an exhibition strategy, partly due to post-WWII trends in mobile zoos and legal views of animals as non-sentient under Japan’s Animal Protection Law. The research highlights the early hurdles in adopting animal welfare and environmental enrichment in non-Western settings, aiming to provide insights for other regions dealing with similar transitional challenges. It also addresses misperceptions about environmental enrichment in the context of empathetic relationships and professional ethics in Japanese zoology, offering insights into regions facing similar issues. Additionally, the paper discusses the progression of animal welfare practices in Japanese zoos and related managerial challenges, acknowledging cultural and institutional factors. Despite regional differences, this study aims to contribute to understanding and improving the universal acceptance and application of animal welfare.
Anatomical and Functional Study of the Ostrich (Struthio camelus) Lung through Macroscopic Analysis in Combination with Optical and Electron Microscopy Techniques
Authors: Makanya Andrew , Djonov Valentin
Published: January 2024

The Ostrich occupies a unique position as the largest bird on the planet. Like other ratites, it has been reputed to have a phylogenetically primitive lung. We used macroscopy, light microscopy, transmission and scanning electron microscopy as well as silicon rubber casting to elucidate the functional design of its lung and compare it with what is already documented for the avian species. The neopulmonic region was very small and poorly developed. The categories of the secondary bronchi (SB) present and their respective numbers included laterodorsal (8–10), lateroventral (4–5), medioventral (4–6) and posterior (16–24). The lateral aspects of the laterodorsals were covered with a transparent collapsible membrane internally lined with a squamous to cuboidal epithelium. The bulk of these SB were in close proximity to intercostal spaces and the intercostal muscles and were thought to be important in the propulsion of gases. The lung parenchyma was rigid, with the atria well supported by septa containing smooth muscles, connective tissue interparabronchial septa were absent, and blood capillaries were supported by epithelial bridges. There were two categories of epithelia bridges: the homogenous squamous type comprising two leaflets of type I cells and the heterogeneous type consisting of a type I pneumocyte and type II cell. Additional type two cells were found at the atrial openings as well as the walls of the infundibulae and the air capillaries. The atria were shallow and opened either directly into several air capillaries or into a few infundibulae. The presence of numerous type II cells and the absence of interparabronchial connective tissue septa may imply that the ostrich lung could be capable of some degree of compliance.
Immune Cells in the Spleen of Mice Mediate the Inflammatory Response Induced by Mannheimia haemolytica A2 Serotype
Authors: Jiao Zizhuo , Jiang Junming , Meng Yong , Wu Guansheng , Tang Jiayang , Chen Taoyu , Fu Yujing , Chen Yuanyuan , Zhang Zhenxing , Gao Hongyan , Man Churiga , Chen Qiaoling , Du Li , Wang Fengyang , Chen Si
Published: January 2024

(1) Background: Mannheimia haemolytica (M. haemolytica) is an opportunistic pathogen and is mainly associated with respiratory diseases in cattle, sheep, and goats. (2) Methods: In this study, a mouse infection model was established using a M. haemolytica strain isolated from goats. Histopathological observations were conducted on various organs of the mice, and bacterial load determination and RNA-seq analysis were specifically performed on the spleens of the mice. (3) Results: The findings of this study suggest that chemokines, potentially present in the spleen of mice following a M. haemolytica challenge, may induce the migration of leukocytes to the spleen and suppress the release of pro-inflammatory factors through a negative feedback regulation mechanism. Additionally, an interesting observation was made regarding the potential of hematopoietic stem/progenitor cells congregating in the spleen to differentiate into immune cells, which could potentially collaborate with leukocytes in their efforts to counteract M. haemolytica invasion. (4) Conclusions: This study revealed the immune regulation mechanism induced by M. haemolytica in the mouse spleen, providing valuable insights into host–pathogen interactions and offering a theoretical basis for the prevention, control, and treatment of mannheimiosis.
Astaxanthin Improved the Quality of Hu Ram Semen by Increasing the Antioxidant Capacity and Mitochondrial Potential and Mitigating Free Radicals-Induced Oxidative Damage
Authors: Sohail Tariq , Zhang Liuming , Wang Xuyang , Jiang Caiyu , Wang Jian , Sun Xiaomei , Li Yongjun
Published: January 2024

The objective of this research was to investigate the effect of astaxanthin supplementations of semen extender on the quality of Hu ram semen after up to five days of preservation at 4 °C. Semen samples were collected from five healthy Hu rams using an artificial vagina during breeding season (April to August 2023) and diluted with a basic extender supplemented with control (0), 1 µM, 2 µM, 3.5 µM, or 4.5 µM of AXT. Overall, 170 semen ejaculate samples (34 repetitions) from five healthy Hu rams were used in our research study. The results revealed that the addition of AXT (3.5 µM) significantly (p ≤ 0.05) increased the sperm kinematic indexes (T.M%, P.M%, MAD%, STR%, and LIN %), sperm viability, plasma membrane integrity, acrosome integrity, total antioxidant content (T-AOC), and mitochondrial membrane potential (MMP) of the Hu rams spermatozoa after up to five days of preservation at 4 °C. Contrary to that, the addition of the best concentration of AXT (3.5 µM) to the semen extender significantly (p ≤ 0.05) reduced the reactive oxygen species (ROS) and malondialdehyde (MDA) concentration of Hu ram semen. In conclusion, the results of the current study indicate that the addition of a semen extender with AXT improves the quality of Hu ram spermatozoa by increasing the total antioxidant capacity (T-AOC) and mitochondrial membrane potential (MMP). On the other hand, reducing free radicals induced oxidative (ROS) and per oxidative (MDA) damage to Hu ram semen.
Linezolid Resistance Genes and Mutations among Linezolid-Susceptible Enterococcus spp.—A Loose Cannon?
Authors: Bender Jennifer K. , Fleige Carola , Funk Finn , Moretó-Castellsagué Clara , Fischer Martin A. , Werner Guido
Published: January 2024

The National Reference Centre for Enterococci receives an increasing number of linezolid-resistant Enterococcus isolates. Linezolid (LIN) resistance is mediated by G2576T 23S rDNA gene mutations and/or acquisition of resistance genes (cfr, optrA, poxtA). There are anecdotal reports that those resistance traits may be present in phenotypically linezolid-susceptible isolates. We aimed to determine the prevalence of LIN resistance genes and mutations in enterococci with a LIN MIC of 4 mg/L in broth microdilution (EUCAST = susceptible) isolated from German hospital patients 2019–2021. LIN MICs were additionally determined by ETEST® and VITEK2. Selected strains were subjected to LIN selective pressure and growth was monitored with increasing antibiotic concentrations. We received 195 isolates (LIN MIC = 4 mg/L). In total, 78/195 (40%) isolates contained either a putative resistance gene, the G2576T mutation, or a combination thereof. Very major error was high for broth microdilution. The ability to predict phenotypic resistance from genotypic profile was highest for G2576T-mediated resistance. Selection experiments revealed that, in particular, E. faecium isolates with resistance gene mutations or poxtA rapidly adapt to MICs above the clinical breakpoint. In conclusion, LIN resistance genes and mutations can be observed in phenotypically linezolid-susceptible enterococci. Those isolates may rapidly develop resistance under LIN selective pressure potentially leading to treatment failure.
Continuous Adsorption of Acid Wood Dyes onto an Activated Carbon Prepared from Pine Sawdust
Authors: Pimentel Catarina Helena , Freire María Sonia , Gómez-Díaz Diego , González-Álvarez Julia
Published: January 2024

In this paper, an activated carbon obtained from Pinus radiata sawdust is applied to remove blue, red, and black wood dyes from aqueous solutions in a fixed-bed column. The flow rate (7.7–30.8 mL min−1), initial dye concentration (25–500 mg L−1), and bed height (2–4 cm) highly influence the breakthrough-curves’ features. The results indicate that the adsorption capacity increased by decreasing the flow rate and increasing the initial dye concentration, except for the black dye, and increasing bed height, except for the red dye. In addition, the breakthrough time changed by modifying the studied variables. The curves became steeper as the flow rate increased and as the bed height decreased. Also, by increasing the inlet dye concentration, the breakthrough time decreased significantly, and sharper breakthrough curves were obtained. The activated carbon with a surface area of 2826 m2 g−1 led to high values of the adsorption capacity between 150 and 1300 mg g−1. The Yoon–Nelson and Thomas models were the ones that best described the adsorption data. The activated carbon saturated with black dye could be used in three successive cycles after regeneration with H2O2.
Photobiomodulation Effect of Different Diode Wavelengths on the Proliferation of Human Buccal Fat Pad Mesenchymal Cells
Authors: Etemadi Ardavan , Khajehmougahi Koosha , Solimei Luca , Benedicenti Stefano , Chiniforush Nasim
Published: January 2024

This study aimed to determine the most effective wavelength for the proliferation of Human Buccal Fat Pad Mesenchymal Stem Cells (BFPMSCs) in cell culture. These cells can be used for different purposes such as regenerative periodontal procedures. Materials and Methods: The wells containing BFPMSCs were subjected to laser irradiation at 635, 660, 808, and 980 nm wavelengths with 1, 1.5, 2.5, and 4 J/cm2 energy densities. Cell proliferation and viability were evaluated after 1, 3, and 5 days with the methyl thiazolyl tetrazolium (MTT) assay. Result: The proliferation rate of human Buccal Fat Pad Mesenchymal Cells (BFPMSCs) was increased on the first and third days at a wavelength of 808 nm and day five at a wavelength of 980 nm in comparison to the control group. Our findings distinguished that PBMT with 635, 660, 808, and 980 nm wavelengths increased the proliferation of BFPMSCs. Conclusion: The best laser radiation setting, which led to the highest proliferation rate of the cells, included a wavelength of 808 nm with 2.5 J/cm2 energy density.
Analysis of Bridge Tests on Sandy Overburden Site with Fault Dislocating
Authors: Ma Jianke , Zhang Jianyi , Zhang Haonan , Tian Jing
Published: January 2024

Performance-based seismic design methods for bridges are advancing, yet limited research has explored the damage mechanisms of bridges subjected to extreme seismic effects, such as those near or across faults. To investigate the damage mechanisms under bedrock dislocation and bridge rupture resistance, providing essential insights for the standardized design and construction of bridges in close proximity to seismic rupture sites, we developed a large-scale device to model bridges in the immediate vicinity of tilted-slip strong seismic rupture sites. This included a synchronous bedrock dislocation loading system. Four sets of typical sandy soil modeling tests were concurrently conducted. The results indicate: (1) The overall shear deformation zone of the foundation and surface uneven deformation primarily concentrate the overburdened soil body along the fault dip. The damaged area under the low-dip reverse fault is lighter on the surface and inside the soil body compared to the high-dip-positive fault. (2) The presence of bridges reduces the width of the main rupture zone and avoidance distance to some extent. However, this reduction is not as significant as anticipated. The damage to the bridge pile foundation along the fault dislocation tendency notably leads to the bending damage of the bridge deck. (3) Input parameters for fracture-resistant bridge design (surface rupture zone location, extent, maximum deformation, etc.) can be deduced from the free site. Within the rupture zone, a “fuse” design can be implemented using simply supported girders. Additionally, combining the “fuse” design with simple supported girders on both sides and utilizing simple support beams for “fuse” design within the rupture zone, along with structural “disconnection”, allows for reinforcing measures on the bridge structure’s foundation platform and pile in the soil body.
Attributes Relevance in Content-Based Music Recommendation System
Authors: Kostrzewa Daniel , Chrobak Jonatan , Brzeski Robert
Published: January 2024

The possibility of recommendations of musical songs is becoming increasingly required because of the millions of users and songs included in online databases. Therefore, effective methods that automatically solve this issue need to be created. In this paper, the mentioned task is solved using three basic factors based on genre classification made by neural network, Mel-frequency cepstral coefficients (MFCCs), and the tempo of the song. The recommendation system is built using a probability function based on these three factors. The authors’ contribution to the development of an automatic content-based recommendation system are methods built with the use of the mentioned three factors. Using different combinations of them, four strategies were created. All four strategies were evaluated based on the feedback score of 37 users, who created a total of 300 surveys. The proposed recommendation methods show a definite improvement in comparison with a random method. The obtained results indicate that the MFCC parameters have the greatest impact on the quality of recommendations.
Automated Think-Aloud Protocol for Identifying Students with Reading Comprehension Impairment Using Sentence Embedding
Authors: Yoo Yongseok
Published: January 2024

The think-aloud protocol is a valuable tool for investigating readers’ cognitive processes during reading. However, its reliance on experienced human evaluators poses challenges in terms of efficiency and scalability. To address this limitation, this study proposes a novel application of natural language processing to automate the think-aloud protocol. Specifically, we use a sentence embedding technique to encode the stimulus text and corresponding readers’ responses into high-dimensional vectors, and the similarity between these embeddings serves as a feature. The properties of the feature are investigated for word-frequency-based and contextualized embedding models. Differences in the sentence embedding-based feature between poor comprehenders and normal readers are investigated. Using these features, seven machine learning models were trained to classify readers into normal and abnormal groups. The highest F1 score of 0.74 was achieved with the contextualized embedding and random forest classifier. This highlights the effectiveness of the embedding technique in extracting useful features for automating the think-aloud protocol for assessing reading comprehension abilities. The potential benefits of this automated approach include increased efficiency and scalability, ultimately facilitating the early diagnosis of reading comprehension impairment and individualized interventions.
Transformer Fault Diagnosis Method Based on SCA-VMD and Improved GoogLeNet
Authors: Zhang Kezhan , Sun Wenlei , Ba Yinjun , Liu Zhiyuan
Published: January 2024

Aiming at the influence of the fundamental frequency and its harmonics in transformer vibration signals on fault signals, which cause a low fault identification rate and degradation of classification model performance, a new strategy is proposed for fault diagnosis using periodic map spectrum feature maps as input features. In this study, the optimal decomposition parameters were first found adaptively using the VMD improved by the positive cosine optimisation algorithm; then, the transformer vibration signal was modally decomposed, and the periodic map spectrum features were plotted according to the differences in the energy distribution of the different modal components at different frequencies. Finally, the GoogLeNet classification model with the improved attention mechanism assigned different weights to the feature maps in both spatial and channel dimensions to improve the classification accuracy and achieve transformer fault diagnosis. The experimental results verified the validity of the adopted feature map and the proposed model, and the accuracy was significantly improved to 99.04% compared with the traditional GoogLeNet, which is valuable for engineering applications.
Development of Architectural Object Automatic Classification Technology for Point Cloud-Based Remodeling of Aging Buildings
Authors: Kim Taehoon , Gu Hyeongmo , Hong Soonmin , Choo Seungyeon
Published: January 2024

In this study, we address the challenge of efficiently handling the maintenance and remodeling of buildings constructed post-1960s, lacking architectural drawings. The conventional approach involves manual measurements and data recording, followed by digital drawing creation. However, we leverage Fourth Industrial Revolution technologies to develop a deep learning-based automatic object classification system using point cloud data. We employ the FCAF3D network with multiscale cells, optimizing its configuration for classifying building components such as walls, floors, roofs, and other objects. While classifying walls, floors, and roofs using bounding boxes led to some boundary-related errors, the model performed well for objects with distinct shapes. Our approach emphasizes efficiency in the remodeling process rather than precise numerical calculations, reducing labor and improving architectural planning quality. While our dataset labeling strategy involved bounding boxes with limitations in numerical precision, future research could explore polygon-based labeling, minimizing loss of space and potentially yielding more meaningful results in classification. In summary, our technology aligns with the initial research objectives, and further investigations could enhance the methodology for even more accurate building object classification.
Weighted Matrix Factorization Recommendation Model Incorporating Social Trust
Authors: Sang Shengwei , Ma Mingyang , Pang Huanli
Published: January 2024

Utilizing user social networks can unearth more effective information to improve the performance of traditional recommendation models. However, existing models often solely utilize trust relationships and information, lacking efficient models that integrate with user historical ratings, as well as methods for accurately adjusting weights and filtering interfering data. This leads to the models’ inability to efficiently use social networks to enhance recommendation accuracy. Therefore, this paper proposes a novel trust-based weighted matrix factorization recommendation model, Trust-WMF. Initially, the model preliminarily calculates users’ predicted ratings for items using trust relationships in the social network and user similarity relations in user historical ratings, simultaneously dynamically integrating these two parts of predicted ratings using adaptive weights. Subsequently, the ratings are incorporated into an improved weighted matrix factorization model, allowing them to have different weights in training compared to user historical ratings. This enriches matrix information and reduces the impact of noise data, thus forming an efficient, unified, and trustworthy recommendation model. Finally, the model was compared and validated on the Epinions and Ciao datasets, with results confirming its efficiency.
Exposure Assessment of Young Adults to Pesticides That Have Effects on the Thyroid—A Contribution to “One Health”
Authors: Djekic Ilija , Smigic Nada , Tomic Nikola , Sredojevic Ana , Stevic Milan , Vrbnicanin Sava , Radusin Kristina , Udovicki Bozidar
Published: January 2024

The objective of this research was to evaluate the cumulative exposure of the population aged 10–24 years to pesticides that have a chronic effect on the thyroid. A consumption study covering fresh fruits and vegetables was collected from 377 respondents. In parallel, 2369 fruit and vegetable samples were chemically analyzed for pesticide residues. As a result, cumulative exposure was calculated for four different scenarios (as is, maximum residue level, 70% of MRL and below detection limit) using two recall methods. The results show that, depending on the scenario, cyprodinil from green lettuce and strawberries, fluopyram blueberries and strawberries, and fluxapyroxad, detected in grapes, contribute most to exposure. More stringent scenarios, with limits at 70% of the MRLs (0.7 MRL) and below the detection limit (“zero residue” approach), show that the estimated total margin of exposure increases by up to 50% in the “0.7 MRL” model, while levels almost triple in the “zero residue” model. The optimization of pesticide use has a beneficial effect on human health and the environment, contributing to the “One Health” approach.
Clinical Effectiveness of Ritonavir-Boosted Nirmatrelvir—A Literature Review
Authors: Paltra Sydney , Conrad Tim O. F.
Published: January 2024

Nirmatrelvir/Ritonavir is an oral treatment for mild to moderate COVID-19 cases with a high risk for a severe course of the disease. For this paper, a comprehensive literature review was performed, leading to a summary of currently available data on Nirmatrelvir/Ritonavir’s ability to reduce the risk of progressing to a severe disease state. Herein, the focus lies on publications that include comparisons between patients receiving Nirmatrelvir/Ritonavir and a control group. The findings can be summarized as follows: Data from the time when the Delta-variant was dominant show that Nirmatrelvir/Ritonavir reduced the risk of hospitalization or death by 88.9% for unvaccinated, non-hospitalized high-risk individuals. Data from the time when the Omicron variant was dominant found decreased relative risk reductions for various vaccination statuses: between 26% and 65% for hospitalization. The presented papers that differentiate between unvaccinated and vaccinated individuals agree that unvaccinated patients benefit more from treatment with Nirmatrelvir/Ritonavir. However, when it comes to the dependency of potential on age and comorbidities, further studies are necessary. From the available data, one can conclude that Nirmatrelvir/Ritonavir cannot substitute vaccinations; however, its low manufacturing cost and easy administration make it a valuable tool in fighting COVID-19, especially for countries with low vaccination rates.
Climate Change Facilitates the Potentially Suitable Habitats of the Invasive Crop Insect Ectomyelois ceratoniae (Zeller)
Authors: Liu Changqing , Yang Ming , Li Ming , Jin Zhenan , Yang Nianwan , Yu Hao , Liu Wanxue
Published: January 2024

Invasive alien insects directly or indirectly driven by climate change threaten crop production and increase economic costs worldwide. Ectomyelois ceratoniae (Zeller) is a highly reproductive invasive crop insect that can severely damage fruit commodities and cause significant economic losses globally. Estimating the global potentially suitable habitats (PSH) of E. ceratoniae is an important aspect of its invasive risk assessment and early warning. Here, we constructed an optimized MaxEnt model based on the global distribution records of E. ceratoniae, and nine environmental variables (EVs), to predict its global PSH under current and future climates. Our results showed that the RM value was 2.0 and the mean area under receiver operating characteristic curve (AUC) value was 0.972, indicating the high accuracy of the optimal MaxEnt model. The mean temperature of driest quarter (bio9, 50.2%), mean temperature of wettest quarter (bio8, 16.9%), temperature seasonality (bio4, 9.7%), and precipitation of coldest quarter (bio19, 9.1%) were the significant EVs affecting its distribution patterns. The global PSH of E. ceratoniae are mainly located in western Asia under current climate scenarios (687.57 × 104 km2), which showed an increasing trend under future climate scenarios. The PSH of E. ceratoniae achieved the maximum under the shared socioeconomic pathway (SSP) 1–2.6 in the 2030s and under the SSP2-4.5 in the 2050s. The increased PSH of E. ceratoniae are mainly located in southwestern Asia, northwestern Europe, northwestern South America, northwestern North America, southern Oceania, and northwestern Africa. Our findings suggest that quarantine officials and governmental departments in the above high-risk invasion areas should strengthen monitoring and early warning to control E. ceratoniae; in particular, cultural measures should be taken in areas where its further expansion is expected in the future.
Integrating Ensemble Weather Predictions in a Hydrologic-Hydraulic Modelling System for Fine-Resolution Flood Forecasting: The Case of Skala Bridge at Evrotas River, Greece
Authors: Varlas George , Papadopoulos Anastasios , Papaioannou George , Markogianni Vassiliki , Alamanos Angelos , Dimitriou Elias
Published: January 2024

Ensemble weather forecasting involves the integration of multiple simulations to improve the accuracy of predictions by introducing a probabilistic approach. It is difficult to accurately predict heavy rainfall events that cause flash floods and, thus, ensemble forecasting could be useful to reduce uncertainty in the forecast, thus improving emergency response. In this framework, this study presents the efforts to develop and assess a flash flood forecasting system that combines meteorological, hydrological, and hydraulic modeling, adopting an ensemble approach. The integration of ensemble weather forecasting and, subsequently, ensemble hydrological-hydraulic modeling can improve the accuracy of flash flood predictions, providing useful probabilistic information. The flash flood that occurred on 26 January 2023 in the Evrotas river basin (Greece) is used as a case study. The meteorological model, using 33 different initial and boundary condition datasets, simulated heavy rainfall, the hydrological model, using weather inputs, simulated discharge, and the hydraulic model, using discharge data, estimated water level at a bridge. The results show that the ensemble modeling system results in timely forecasts, while also providing valuable flooding probability information for 1 to 5 days prior, thus facilitating bridge flood warning. The continued refinement of such ensemble multi-model systems will further enhance the effectiveness of flash flood predictions and ultimately save lives and property.