bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of an Improved GWO Algorithm for Solving Optimal Paths in Complex Vertical Farms with Multi-Robot Multi-Tasking
Authors: Shen Jiazheng , Hong Tang Sai , Fan Luxin , Zhao Ruixin , Mohd Ariffin Mohd Khairol Anuar b. , As’arry Azizan bin
Published: August 2024

As the global population grows, achieving Zero Hunger by 2030 presents a significant challenge. Vertical farming technology offers a potential solution, making the path planning of agricultural robots in vertical farms a research priority. This study introduces the Vertical Farming System Multi-Robot Trajectory Planning (VFSMRTP) model. To optimize this model, we propose the Elitist Preservation Differential Evolution Grey Wolf Optimizer (EPDE-GWO), an enhanced version of the Grey Wolf Optimizer (GWO) incorporating elite preservation and differential evolution. The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). The experimental results demonstrate that EPDE-GWO reduces path length by 24.6%, prevents premature convergence, and exhibits strong global search capabilities. Thanks to the DE and EP strategies, the EPDE-GWO requires fewer iterations to reach the optimal solution, offers strong stability and robustness, and consistently finds the optimal solution at a high frequency. These attributes are particularly significant in the context of vertical farming, where optimizing robotic path planning is essential for maximizing operational efficiency, reducing energy consumption, and improving the scalability of farming operations.
Key Technologies of Intelligent Weeding for Vegetables: A Review
Authors: Jiao Jinkang , Zang Ying , Chen Chaowen
Published: August 2024

Vegetables are an essential part of people’s daily diet, and weeds can cause serious losses in vegetable yield and quality. Intelligent weeding technology for vegetables will be one of the mainstream technologies in modern agricultural development. This article reviews the current research status of intelligent weeding technology for vegetables, including vegetable and weed detection technology, weeding actuators, and weeding robots. Firstly, the vegetable and weed detection technology was introduced in detail from three aspects: global weed detection, crop-rows detection, and vegetable/weed precise recognition technology. The research results of some researchers were summarised, and the vegetable/weed precise recognition technology, including machine learning and proximal sensor technology, was introduced. Secondly, the weeding actuators and robots were introduced, including intelligent chemical weeding, mechanical weeding, physical weeding, and integrated weed management methods. Some weeding actuators and robots developed by researchers and agricultural companies were showcased. Finally, the challenges and future development directions of intelligent weeding technology were discussed and analysed. Intelligent weeding technology for vegetables is still mainly limited by natural conditions and a lack of technology. In the future, it will be possible to develop in the direction of multi-algorithm and multi-sensor fusion technologies. It is necessary to improve the applicability of intelligent weeding equipment for various environments, crops, and weeds. This article can provide a reference for future research in the field of intelligent weeding for vegetables.
Research on Agricultural Machinery Services for the Purpose of Promoting Conservation Agriculture: An Evolutionary Game Analysis Involving Farmers, Agricultural Machinery Service Organizations and Governments
Authors: Zhang Fan , Bei Jindi , Shi Qingzhe , Wang Ying , Wu Ling
Published: August 2024

Agricultural machinery services are an important guaranteed way to promote Conservation Agriculture. It is of great significance to study how to encourage farmers to choose agricultural machinery services to promote the standard implementation of Conservation Agriculture technology. In order to promote the implementation of Conservation Agriculture and improve the supply of agricultural machinery services, this paper identifies the stakeholders of normative Conservation Agriculture technology adoption behavior and the relationship between agricultural machinery service organizations, farmers and agriculture-related governments. An evolutionary game model was established to evaluate the decision-making characteristics of tripartite behavior and simulate the evolution trend of stakeholder behavior. The results show that agriculture-related governments, agricultural machinery service organizations and farmers can achieve evolutionarily stable strategies. The punishments and subsidies of agriculture-related governments and the supervision cost of all links of agricultural machinery social service organizations can significantly affect the behavior strategies of the three parties. The government set up reasonable subsidy and punishment mechanisms, and the agricultural machinery service organization controls the supervision cost of all links to ensure the stability of the three-party behavior strategy. This study provides theoretical guidance for scientific decision making and active cooperative development of the government, farmers and agricultural machinery service organizations and lays a foundation for countermeasures and suggestions to further promote farmers’ implementation of Conservation Agriculture technology.
Systematic Analysis and Expression Profiling of the Ginger FWL Gene Family Reveal Its Potential Functions in Rhizome Development and Response to Abiotic Stress
Authors: Jiang Yajun , Tang Shihao , Xia Maoqin , Li Hui , Xiao Daoyan , Li Xingyue , Xing Haitao , Wang Biao , Huang Hao , Zhou Shengmao , Li Hong-Lei
Published: August 2024

Ginger (Zingiber officinale Roscoe) is a significant medicinal and culinary plant, with its growth influenced by various biotic and abiotic factors. The FWL gene, containing the PLAC8 motif, is prevalent in fungi, algae, higher plants, and animals. In plants, FWL primarily regulates fruit weight, cell division, and participates in heavy metal transport. However, the FWL family members in ginger have not been previously identified. This study identified 21 FWL members within the ginger genome, distributed across nine chromosomes. These 21 FWL genes were categorized into five subfamilies based on the phylogenetic analysis. Gene-structure and motif analyses revealed that ZoFWL has been conserved throughout evolution. Concurrently, the ZoFWL gene exhibits a homologous evolutionary relationship only with Musa acuminata. We identified three pairs of fragment-repeat events encompassing five genes, which likely represent the primary mechanism for amplification within the ZoFWL gene family. The promoter regions of the ZoFWL genes are enriched with numerous cis-acting elements implicated in plant growth, development, and responses to abiotic stress. These include elements responsive to low temperatures, anaerobic induction, MYB binding sites integral to defense and stress responses, and drought inducibility. Expression profiling revealed that the ZoFWL genes are responsive to a quartet of abiotic stressors, with ZoFWL18, in particular, demonstrating a pronounced response to osmotic, low-temperature, heat, and salinity stresses. This underscores the pivotal role of ZoFWLs in abiotic-stress responses. Our findings offer valuable insights into the potential of the ZoFWL gene family in modulating ginger rhizome development and the genes’ response to abiotic stressors, laying a foundational framework for future research into ginger’s resistance breeding.
Phenotypic and Genetic Analyses of Mastitis, Endometritis, and Ketosis on Milk Production and Reproduction Traits in Chinese Holstein Cattle
Authors: Ren Xiaoli , Lu Haibo , Wang Yachun , Yan Lei , Liu Changlei , Chu Chu , Yang Zhuo , Bao Xiangnan , Yu Mei , Zhang Zhen , Zhang Shujun
Published: August 2024

Mastitis (MAS), endometritis (MET), and ketosis (KET) are prevalent diseases in dairy cows that result in substantial economic losses for the dairy farming industry. This study gathered 26,014 records of the health and sickness of dairy cows and 99,102 data of reproduction from 13 Holstein dairy farms in Central China; the milk protein and milk fat content from 56,640 milk samples, as well as the pedigree data of 37,836 dairy cows were obtained. The logistic regression method was used to analyze the variations in the prevalence rates of MAS, MET, and KET among various parities; the mixed linear model was used to examine the effects of the three diseases on milk production, milk quality, and reproductive traits. DMU software (version 5.2) utilized the DMUAI module in conjunction with the single-trait and two-trait animal model, as well as best linear unbiased prediction (BLUP), to estimate the genetic parameters for the three diseases, milk production, milk quality, and reproductive traits in dairy cows. The primary findings of the investigation comprised the following: (1) The prevalence rates of MAS, MET, and KET in dairy farms were 20.04%, 10.68%, and 7.33%, respectively. (2) MAS and MET had a substantial impact (p < 0.01) on milk production, resulting in significant decreases of 112 kg and 372 kg in 305-d Milk Yield (305-d MY), 4 kg and 12 kg in 305-d Protein Yield (305-d PY), and 6 kg and 16 kg in 305-d Fat Yield (305-d FY). As a result of their excessive 305-d MY, some cows were diagnosed with KET due to glucose metabolism disorder. The 305-d MY of cows with KET was significantly higher than that of healthy cows (205 kg, p < 0.01). (3) All three diseases resulted in an increase in the Interval from Calving to First Service (CTFS, 0.60–1.50 d), Interval from First Service to Conception (FSTC, 0.20–16.20 d), Calving Interval (CI, 4.00–7.00 d), and Number of Services (NUMS, 0.07–0.35). (4) The heritabilities of cows with MAS, MET, and KET were found to be low, with values of 0.09, 0.01, and 0.02, respectively. The genetic correlation between these traits ranged from 0.14 to 0.44. This study offers valuable insights on the prevention and control of the three diseases, as well as feeding management and genetic breeding.
Characterization of Phenolic Profile and Biological Properties of Astragalus membranaceus Fisch. ex Bunge Commercial Samples
Authors: Shahrivari-Baviloliaei Saba , Erdogan Orhan Ilkay , Abaci Kaplan Nurten , Konopacka Agnieszka , Waleron Krzysztof , Plenis Alina , Viapiana Agnieszka
Published: August 2024

Astragalus membranaceus Fisch. ex Bunge (syn. Astragalus mongholicus Bunge) is one of the notable medicinal and food plants. Therefore, the aim of this study was to calculate the phenolic composition and antioxidant, antimicrobial, as well as enzyme inhibitory [acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and tyrosinase (TYR)] activities with chemometric approaches of the hydromethanolic and water extracts of commercial A. membranaceus samples. Ten individual phenolic compounds were determined using high-performance liquid chromatography (HPLC), and only quercetin was found at a level of above 80 µg/g DW in both extracts. Moreover, the highest antioxidant activity in DPPH, FRAP, ABTS, and CUPRAC assays was found in the sample containing the roots in loose form from USA. A. membranaceus extracts displayed the inhibition zone diameters within the range from 10 to 22 mm antimicrobial activity against S. aureus, while there were no inhibition zones in any extracts in case of E. coli. The extracts of A. membranaceous showed an inhibition rate below 40% against TYR, and among tested extracts, only two samples were able to inhibit BChE with IC50 values of above 30 µg/mL. Correlation analysis showed a highly positive relationship between their phenolic composition and antioxidant activity. Concluding, the obtained results confirmed that A. membranaceus commercial samples could be an important dietary source of natural antioxidants.
Concept of Early Prediction and Identification of Truck Vehicle Failures Supported by In-Vehicle Telematics Platform Based on Abnormality Detection Algorithm
Authors: Semenov Iouri , Świderski Andrzej , Borucka Anna , Guzanek Patrycja
Published: August 2024

As automotive technology advances in the realm of digitization, vehicles are becoming smarter and, at the same time, more vulnerable to various threats. This paper focuses on techniques for detecting faults to mitigate the risk of freight transportation. Our observations show that vehicle uptime varies significantly even under similar operating conditions. This variation stems from differences in the wear and tear of moving and stationary parts, the characteristics of transported loads, driving styles, the quality of maintenance, etc. These factors are particularly crucial for abnormal vehicles designed to carry AILs (Abnormal Indivisible Loads). Such vehicles are especially prone to surprising threats, requiring efficient techniques for monitoring separate vehicle components and providing drivers with vital information about their operational status. The presented article proposes an original concept of an integrated three-level monitoring system based on the AOP (All-in-One Platform) principle, using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, which is a tool oriented to distinguish points from three categories: basic, boundary, and external. This is a solution not yet found in the literature. It is based on assessments of LOFs (Local Outlier Factors) and to detect anomalies in the measured values of operational parameters. The purpose of our study was to determine whether providing truck drivers with current information from an active threat warning system could help reduce unplanned downtimes.
The Effect of Communicating AI Confidence on Human Decision Making When Performing a Binary Decision Task
Authors: Ishizu Nanami , Yeoh Wen Liang , Okumura Hiroshi , Fukuda Osamu
Published: August 2024

In this study, we experimentally analyzed whether people can perceive the accuracy or smartness of AI judgments, and whether the judgment accuracy of AI and the level of confidence in those judgments affect people’s decision-making. The results showed that people may perceive an AI’s smartness even when it only presents information on the results of its judgments. The results also suggest that AI accuracy and confidence affect human decision-making, and that the magnitude of the effect of AI confidence varies with AI accuracy. We also found that when a person’s ability to make a decision is less than or equal to the AI’s ability to make a decision, the human performance in a binary decision task improves regardless of AI accuracy. The results obtained in this study are similar in some respects to relationships in which people make decisions while interacting, and the findings from research on human interactions may apply to the research and development of human–AI interactions.
The Characteristics of the Spatial and Temporal Distribution of the Initial Compression Wave Induced by a 400 km/h High-Speed Train Entering a Tunnel
Authors: Mei Yuangui , Wang Zixian , Sun Qi , Hu Xiao
Published: August 2024

The initial compression wave induced by a 400 km/h high-speed train entering a tunnel in two cases (offset running and center running) is investigated by overset mesh technology. The governing equations of the IDDES model for three-dimensional, unsteady, compressible flow are employed. The meshing strategy and numerical algorithm are validated by moving model test data. The spatial and temporal distribution characteristics of the initial compression wave and the one-dimensional planar wave characteristics are analyzed. The results show that the compression waves undergo three stages: from an irregular spherical shape near the train to an oblique shape, and finally to a one-dimensional planar wave. The initial compression wave captured at the measurement points at a distance of 5Di (Di represents the equivalent diameter of the tunnel) from the tunnel portal has been fully characterized by one-dimensional features, which can provide a boundary input for the propagation of the initial compression wave towards the tunnel exit. Compared to the offset running case, the initial compression wave amplitude and pressure gradient amplitude induced by central running are reduced by 3.66% and 6.87%, respectively.
Age-Associated Changes in Carotid Intima–Media Thickness in Relation to Redox Balance Indices in Metabolic Syndrome
Authors: Bekyarova Ganka Y. , Bekyarov Nicolai A. , Madjova Valentina H. , Madjova Christiana R. , Kalevska Evgenia D. , Salim Ayshe S. , Vankova Deyana G. , Ivanova Diana G. , Kiselova-Kaneva Yoana D.
Published: August 2024

Metabolic syndrome (MetS) is defined by the World Health Organisation (WHO) as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidaemia. The components of MetS and the associated cardiovascular risks may disrupt the vascular endothelial function and the structure of the vascular wall, increasing the risk of atherosclerosis and vascular diseases. In this study we evaluated the relationship between the carotid intima–media thickness (CIMT), the redox balance parameters of plasma asymmetric dimethylarginine (ADMA), malondialdehyde (MDA), and heme oxygenase 1 (HO-1), and the expression of oxidative stress-related nuclear factor kappa B (NF-kB), nuclear factor erythroid 2-related factor 2 (Nrf2), and HO-1 in peripheral blood mononuclear cells (PBMCs) in MetS. Significantly higher CIMT was established in MetS patients aged ≥ 55 years as compared with the control group (0.96 ± 0.29 vs. 0.74 ± 0.21, p < 0.05). Expression was higher in MetS patients aged < 55 years (83% for NF-kB, p < 0.05; 251% for Nrf2, p < 0.05, and 337% for HO-1, p < 0.05) in comparison to the control group. Similarly, expression was higher in CIMT < 0.90 mm than the control group by 80% for NF-kB, p < 0.01; 260% for Nrf2, p < 0.05, and 303% for HO-1, p < 0.05. In contrast, gene expression was under-regulated in the subgroups of MetS patients aged ≥ 55 years and MetS patients with CIMT ≥ 0.90 mm. Significantly higher plasma levels for MDA, ADMA, and HO-1 were established in the age < 55 and age ≥ 55 MetS subgroups and the CIMT < 0.90 mm and CIMT ≥ 0.90 mm subgroups. In conclusion, MetS individuals aged ≥ 55 are at higher risk of increased CIMT and impaired redox balance.
Research on the Performance, Measurement, and Influencing Factors of the Acoustic Environment in Hospital Buildings
Authors: Lin Xiao , Chen Chiung-Yao
Published: August 2024

In this study, the current noise situation in eight hospitals in central and northern Taiwan was investigated and analyzed. Recording equipment was utilized to measure environmental noise levels at the busiest points in the hospital lobby, specifically the pricing and medicine waiting areas. Furthermore, the acoustic data of the recorded audio samples were analyzed to determine the psychoacoustic parameter, namely, loudness. Subsequently, correlation analysis was performed between the analyzed data spectrum and the subjective psychological noise value. Ultimately, it was found that the mid-frequency band (MF) had a greater impact on the subjects compared to the other two frequency bands. When comparing the correlation coefficient analysis with the prior factor analysis, the primary sources of intrusive noise affecting the subjects were identified. The mid-frequency band is predominantly attributed to footsteps and conversations, and the high-frequency band is predominantly attributed to broadcast sound.
Estimation of Processing Times and Economic Feasibility of Producing Moringa oleifera Lam. Capsules in Mexico
Authors: Delfín-Portela Elizabeth , Meléndez-Armenta Roberto Ángel , Gurruchaga-Rodríguez María Eloísa , Baez-Senties Oscar , Heredia-Roldan Miguel Josué , Carrión-Delgado Juan Manuel , Betanzo-Torres Erick Arturo
Published: August 2024

The production of Moringa oleifera capsules has emerged as a promising agricultural activity in Mexico, driven by the plant’s well-documented health and nutritional benefits. In response, farmers have begun producing Moringa oleifera as a dietary supplement, using artisanal methods with minimal production controls. This study aimed to estimate the processing times of the Moringa oleifera production system using simulation modeling with Arena® software and to evaluate the economic feasibility of capsule production. Methodologically, it was approached as a case study in the state of Veracruz, and processing times were estimated through systematic sampling and modeled with Arena simulation software. Three simulation scenarios were considered to select a technically and economically viable alternative for agricultural producers, as follows: one with a 200-capsule encapsulator (1E200C), another with two 200-capsule encapsulators (2E200C), and a third with an 800-capsule encapsulator (1E800C). For the initial diagnosis, a research stay was conducted for 180 days, and the production capacity was set at 24,000 capsules due to raw material limitations. Results indicated that the 1E800C scenario reduced processing time by 60% compared to the 1E200C scenario and by 35% compared to the 2E200C scenario. Additionally, the 1E800C model required only Arena simulation software version 162 days (16 h) of work, while the 2E200C required 4 days (32 h) and the 1E200C required 7 days (56 h). In terms of production costs per unit of 90 capsules, the 1E200C was USD 3.93, the 2E200C was USD 3.64, and the 1E800C was USD 3.45. This study concluded that due to raw material limitations, the company can produce 12,800 units of 90 capsules per year. It is recommended to adopt the 1E800C encapsulator, which would lower the overall production costs by 12.23%, representing USD 0.48 per unit produced and resulting in an additional profit of USD 6150.50. Over a five-year evaluation period, the benefit–cost ratio was 5.03, the NPV was 922,370.11, and the IRR was 42.09%, indicating that this type of agribusiness in Mexico is both technically and economically feasible.
Camera-Sourced Heart Rate Synchronicity: A Measure of Immersion in Audiovisual Experiences
Authors: Williams Joseph , Francombe Jon , Murphy Damian
Published: August 2024

Audio presentation is often attributed as being capable of influencing a viewer’s feeling of immersion during an audiovisual experience. However, there is limited empirical research supporting this claim. This study aimed to explore this effect by presenting a clip renowned for its immersive soundtrack to two groups of participants with either high-end or basic audio presentation. To measure immersion, a novel method is applied, which utilises a camera instead of an electroencephalogram (ECG) for acquiring a heart rate synchronisation feature. The results of the study showed no difference in the feature, or in the responses to an established immersion questionnaire, between the two groups of participants. However, the camera-sourced HR synchronicity feature correlated with the results of the immersion questionnaire. Moreover, the camera-sourced HR synchronicity feature was found to correlate with an equivalent feature sourced from synchronously recorded ECG data. Hence, this shows the viability of using a camera instead of an ECG sensor to quantify heart rate synchronisation but suggests that audio presentation alone is not capable of eliciting a measurable difference in the feeling of immersion in this context.
Augmented Data-Driven Approach towards 3D Printed Concrete Mix Prediction
Authors: Rehman Saif Ur , Riaz Raja Dilawar , Usman Muhammad , Kim In-Ho
Published: August 2024

Formulating a mix design for 3D concrete printing (3DCP) is challenging, as it involves an iterative approach, wasting a lot of resources, time, and effort to optimize the mix for strength and printability. A potential solution is mix formulation through artificial intelligence (AI); however, being a new and emerging field, the open-source availability of datasets is limited. Limited datasets significantly restrict the predictive performance of machine learning (ML) models. This research explores data augmentation techniques like deep generative adversarial network (DGAN) and bootstrap resampling (BR) to increase the available data to train three ML models, namely support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting regression (XGBoost). Their performance was evaluated using R2, MSE, RMSE, and MAE metrics. Models trained on BR-augmented data showed higher accuracy than those trained on the DGAN-augmented data. The BR-trained XGBoost exhibited the highest R2 scores of 0.982, 0.970, 0.972, 0.971, and 0.980 for cast compressive strength, printed compressive strength direction 1, 2, 3, and slump flow respectively. The proposed method of predicting the slump flow (mm), cast, and anisotropic compressive strength (MPa) can effectively predict the mix design for printable concrete, unlocking its full potential for application in the construction industry.
Designing Thriving School Ecosystems: The Synergy of Biophilic Design, Wellbeing Science, and Systems Science
Authors: Gray Fiona , Downie Andrea
Published: August 2024

This article presents a novel approach that integrates biophilic design, wellbeing science, and systems science into a holistic strategy designated as the Biophilic Wellbeing Systems Approach (BWSA). This transdisciplinary approach aims to enhance student wellbeing in educational settings by fostering a deep connection with nature, supported by positive psychology and systems thinking. The research explores how these combined disciplines can shape educational environments that improve learning outcomes and promote human thriving. The study advocates for a transformative redesign of school environments, emphasising the interdependence of individual and planetary health, drawing on Indigenous wisdom and contemporary scientific knowledge. This foundational strategy holds significant potential to fundamentally change how schools are designed and operated. By fostering environments that deeply integrate wellbeing principles, this approach not only influences the physical buildings but also extends to the entire school ecosystem. It works synergistically to promote educational excellence and holistic wellbeing, ensuring that all elements of the school environment contribute to the overall development and health of students and staff.
Ascending to Well-Being through Mediated Spaces: An Alternative to Informal Learning and Physical Activity Environments in Vertical Schools
Authors: Ebrahimi Salari Elia , Westbrook Nigel
Published: August 2024

The correlation between health and well-being, outdoor activity, and the natural environment in learning environments has been recognised by pioneers like Samuel Wilderspin and modern theorists like Maria Montessori, who have underscored the importance of integrating nature into school designs to foster connections between students, teachers, and the community, thereby promoting physical, social, and mental well-being. However, for schools in hot–humid climatic regions in densely populated cities of Southeast Asia, reduced time spent in nature due to adverse climatic conditions has led to an increasingly inactive lifestyle, impacting children’s health and well-being. Overpopulation in major cities, such as those in Southeast Asia, further exacerbates this challenge, leading to a scarcity of land and the rise of high-rise buildings, including vertical schools. This article explores the evolving learning environment for children, emphasising the critical correlation between well-being, nature, and school settings. It evaluates case studies of best practices in learning environment design, focusing on how architecture can support pedagogical goals. The analysis identifies spaces that affect well-being, termed mediated spaces, and recommends guidelines for such spaces tailored to vertical schools in hot–humid climates. The methodology includes a literature review of learning theories, the integration of learning environments with nature, and biophilic design. This review forms the basis for developing adaptable design guidelines tailored to hot–humid climates. Additionally, case study analyses of exemplary schools are conducted to identify mediated spaces that enhance well-being and adapt these findings to vertical school designs.
Monthly Precipitation Outlooks for Mexico Using El Niño Southern Oscillation Indices Approach
Authors: González-González Miguel Angel , Corrales-Suastegui Arturo
Published: August 2024

The socioeconomic sector increasingly relies on accessible and cost-effective tools for predicting climatic conditions. This study employs a straightforward decision tree classifier model to identify similar monthly ENSO (El Niño Southern Oscillation) conditions from December 2000 to November 2023, using historically monthly ENSO Indices data from December 1950 to November 2000 as a reference. The latter is to construct monthly precipitation hindcasts for Mexico spanning from December 2000 to November 2023 through historically high-resolution monthly precipitation rasters. The model’s performance is evaluated at a global and local scale across seasonal periods (winter, spring, summer, and fall). Assessment using global Hansen–Kuiper Skill Score and Heidkee Skill Score metrics indicates skillful performance across all seasons (>0.3) nationwide. However, local metrics reveal a higher spatial percent of corrects (>0.40) in winter and spring, corresponding to dry seasons, while a lower percent of corrects (<0.40) are observed in more extensive areas during summer and fall, indicative of rainy seasons, due to increased variability in precipitation. The choice of averaging method influences the degree of underestimations and overestimations, impacting the model’s variability. Spearman correlations highlight regions with significant model performance, revealing potential misinterpretations of high hit rates during winter and spring. Notably, during the fall, the model demonstrates spatial skill across most of Mexico, while in the spring, it performs well in the southern and northeastern regions and, in the summer, in the northwestern areas. Integration of accurate forecasts of ENSO Indices to predict precipitation months ahead is crucial for the operational efficacy of this model, given its heavy reliance on anticipating ENSO behavior. Overall, the empirical method exhibits great promise and potential for application in other developing countries directly impacted by the El Niño phenomenon, owing to its low resource costs.
Causal Relationship between Aging and Anorexia Nervosa: A White-Matter-Microstructure-Mediated Mendelian Randomization Analysis
Authors: Qiu Haoyuan , Shi Miao , Zhong Zicheng , Hu Haoran , Sang Hunini , Zhou Meijuan , Feng Zhijun
Published: August 2024

This study employed a two-step Mendelian randomization analysis to explore the causal relationship between telomere length, as a marker of aging, and anorexia nervosa and to evaluate the mediating role of changes in the white matter microstructure across different brain regions. We selected genetic variants associated with 675 diffusion magnetic resonance imaging phenotypes representing changes in brain white matter. F-statistics confirmed the validity of the instruments, ensuring robust causal inference. Sensitivity analyses, including heterogeneity tests, horizontal pleiotropy tests, and leave-one-out tests, validated the results. The results show that telomere length is significantly negatively correlated with anorexia nervosa in a unidirectional manner (p = 0.017). Additionally, changes in specific white matter structures, such as the internal capsule, corona radiata, posterior thalamic radiation, left cingulate gyrus, left longitudinal fasciculus, and left forceps minor (p < 0.05), were identified as mediators. These findings enhance our understanding of the neural mechanisms, underlying the exacerbation of anorexia nervosa with aging; emphasize the role of brain functional networks in disease progression; and provide potential biological targets for future therapeutic interventions.
A Miniature Modular Fluorescence Flow Cytometry System
Authors: Huang Shaoqi , Li Jiale , Wei Li , Zheng Lulu , Shi Zheng , Guo Shiwei , Dai Bo , Zhang Dawei , Zhuang Songlin
Published: August 2024

Fluorescence flow cytometry is a powerful instrument to distinguish cells or particles labelled with high-specificity fluorophores. However, traditional flow cytometry is complex, bulky, and inconvenient for users to adjust fluorescence channels. In this paper, we present a modular fluorescence flow cytometry (M-FCM) system in which fluorescence channels can be flexibly arranged. Modules for particle focusing and fluorescence detection were developed. After hydrodynamical focusing, the cells were measured in the detection modules, which were integrated with in situ illumination and fluorescence detection. The signal-to-noise ratio of the detection reached to 33.2 dB. The crosstalk among the fluorescence channels was eliminated. The M-FCM system was applied to evaluate cell viability in drug screening, agreeing well with the commercial cytometry. The modular cytometry presents several outstanding features: flexibility in setting fluorescence channels, cost efficiency, compact construction, ease of operation, and the potential to upgrade for multifunctional measurements. The modular cytometry provides a multifunctional platform for various biophysical measurements, e.g., electrical impedance and refractive-index detection. The proposed work paves an innovative avenue for the multivariate analysis of cellular characteristics.
Understanding Quality of Life for People with Motor Neurone Disease Who Use Tracheostomy Ventilation and Family Members: A Scoping Review
Authors: Turner Nicola , Faull Christina , Palmer Jonathan , Armstrong Alison , Bedford Jennifer , Turner Martin R. , Wilson Eleanor
Published: August 2024

Tracheostomy ventilation (TV) can increase survival time for people living with motor neurone disease (MND); however, the use of TV varies between countries. Concerns regarding anticipated quality of life (QoL) are among the reasons given by healthcare professionals for not recommending this intervention, yet little is known about QoL in this context. This scoping review was conducted to examine the evidence on QoL for those with MND who use TV and family members involved in their care. Using the methodological guidance of the Joanna Briggs Institute, 23 papers were identified for inclusion, and findings were inductively analysed to identify key themes. We found that people living with MND tend to rate QoL post TV more positively than anticipated by healthcare professionals or family members. QoL was found to be related to positive relationships and activities the person could maintain. Feeling able to make a choice and an adequate level of financial resources were also important factors. Family members tended to experience lower QoL, associated with the uncertainty surrounding an emergency procedure and the complexity of subsequently required care. More evidence on QoL from the perspectives of people with MND who use TV is needed to support decision making and inform guidance.
Relationship between Problematic Internet Use and Depression in Young Latin American College Students
Authors: Vázquez-Martínez Andrea , Villanueva-Silvestre Verónica , Abad-Villaverde Beatriz , Santos-González Cristina , Rial-Boubeta Antonio , Villanueva-Blasco Víctor José
Published: August 2024

(1) Problematic Internet use (PIU) in young people is a topic of great interest both in the field of addictions and mental health, but scientific evidence is limited in Latin America. The aim was to analyze the relationship between PIU and depression in Latin American college students. (2) Methods: The sample consisted of 1828 college students (63.7% women), aged between 18–30 years (M = 21.64 years). (3) Results: PIU was detected in 40.2% of cases, and severe or moderately severe depression in 31.7%. Rates of severe depression in students with PIU were 3.02 times higher than in those without PIU (χ2(3) = 168.443; p < 0.000). The presence of PIU was also statistically significantly higher among youth with depressive symptoms. Linear and logistic regression models for predicting PIU, show how the depression level constitutes a risk factor for PIU: seven times higher for severe depression; more than five times higher for moderate depression; and more than two times for mild depression. (4) Conclusions: There is a clear association between depression and PIU, suggesting that a higher level of depression would act as a predictor of PIU. However, this finding is exploratory. Future studies should clarify the directionality of the relationship between both variables.
Asymmetric Adaption in Social Learning: Understanding the Dilemma of Competition and Cooperation
Authors: Li Siying , Huang Yulong , Xu Cheng , Wu Jie , Qu Chen
Published: August 2024

The constant challenge in social interactions involves making informed decisions in the face of competitive and cooperative dilemmas. The decision-making process can be influenced by various factors present in the social context. According to the behavior-pattern-categorization framework of information acquisition, potential biases may develop at all stages of decision-making as information about social context is progressively entered and integrated. In this study, employing the Chicken Game, we investigated the influence of varying information levels within the behavior-pattern-categorization framework (i.e., competitiveness of behavior choice, uncertainty of behavior pattern, and sociality of category) on decision-making in the dilemma of competition and cooperation. Combined with reinforcement learning models, our findings from three experiments showed that participants exhibited basic complementary behavior, becoming less competitive against highly competitive opponents and vice versa. Notably, individuals exhibited varying adaptation rates to different levels of opponent competitiveness and fluctuations. Specifically, participants adapted slower to highly competitive opponents and faster to cooperative opponents. This asymmetric adaptation in social learning is related to the rate at which various levels of information are updated. The current study disentangles the different levels of information acquisition and highlights the asymmetric processing that can occur during the updating of information within each level.
Integrating Multimodal Generative AI and Blockchain for Enhancing Generative Design in the Early Phase of Architectural Design Process
Authors: Fitriawijaya Adam , Jeng Taysheng
Published: August 2024

Multimodal generative AI and generative design empower architects to create better-performing, sustainable, and efficient design solutions and explore diverse design possibilities. Blockchain technology ensures secure data management and traceability. This study aims to design and evaluate a framework that integrates blockchain into generative AI-driven design drawing processes in architectural design to enhance authenticity and traceability. We employed a scenario as an example to integrate generative AI and blockchain into architectural designs by using a generative AI tool and leveraging multimodal generative AI to enhance design creativity by combining textual and visual inputs. These images were stored on blockchain systems, where metadata were attached to each image before being converted into NFT format, which ensured secure data ownership and management. This research exemplifies the pragmatic fusion of generative AI and blockchain technology applied in architectural design for more transparent, secure, and effective results in the early stages of the architectural design process.
Airport Service Providers in Support of SDGs
Authors: Tigu Gabriela , Cioranu Adrian , Miron Alexandra , State Olimpia , Diaconescu Vlad
Published: August 2024

This pilot study investigates the contributions of an airport service provider from Romania specializing in ground handling, operations, and passenger services towards achieving the United Nations Sustainable Development Goals (SDGs). Recognizing the critical role of service providers in the aviation ecosystem, this research focuses on how operational practices can be optimized to support sustainability objectives. It also reveals how businesses can leverage achievements and internal policies that would fit under, and support, SDGs. The study covers the operations of an airport service provider at several airports across the country. Through a series of qualitative questionnaires and interviews with employees, the research identifies best practices and challenges in aligning airport services with the SDGs. The study underscores the importance of collaboration between service providers, airport authorities, and regulatory bodies to achieve sustainable outcomes. By providing practical recommendations and a framework for sustainable operations, this pilot study aims to guide airport service providers in contributing to the global sustainability agenda, demonstrating the potential for meaningful impact in the aviation sector.
Impact of Breast Cancer on Cardiometabolic Health in Spanish Women ≥50 Years with Pre-Existing Type 2 Diabetes Mellitus
Authors: Fernández-Arce Lucía , Robles-Rodríguez Nena , Fernández-Feito Ana , Fernández-Iglesias Rocío , Fernández-Álvarez María del Mar , Lana Alberto
Published: August 2024

During breast cancer (BC), cardiometabolic disorders can worsen prognosis, particularly in women with type 2 diabetes mellitus (T2DM). This study aimed to determine the impact of BC diagnosis on cardiometabolic parameters and the incidence of complication in women over 50 years of age (90% aged ≥ 65 years) with pre-existing T2DM. Using primary care registries from Asturias (Spain), a total of 106 women diagnosed with T2DM followed by BC were selected and matched with women with T2DM (n = 212) in a cohort study. Indicators of cardiometabolic health and microvascular complications associated with T2DM were collected. Women were monitored from two years prior to five years after BC diagnosis. Conditional logistic regressions were used to compare the adjusted odds of staying below each indicator’s threshold. During follow-up, women with T2DM+BC had a higher risk of fasting blood glucose ≥126 mg/dL (adjusted odds ratio [aOR] = 1.83; 95% confidence interval [CI95%]: 1.01–3.32) and glycosylated hemoglobin (Hb1Ac) ≥ 48 mmol/mol or 6.5% (aOR: 2.44; IC95%: 1.21–4.91). There was no difference between the groups regarding the incidence of microvascular complications. BC incidence negatively impacted the glycemic control of Spanish women with pre-existing T2DM measured by basal blood glucose and HbA1c, but not cardiometabolic health indicators or T2DM complications.
Resistance to Anti-HER2 Therapies in Gastrointestinal Malignancies
Authors: Mo Christiana , Sterpi Michelle , Jeon Hyein , Bteich Fernand
Published: August 2024

Human epidermal growth factor 2 (HER2) is a tyrosine kinase receptor that interacts with multiple signaling pathways related to cellular growth and proliferation. Overexpression or amplification of HER2 is linked to various malignancies, and there have been decades of research dedicated to targeting HER2. Despite the landmark ToGA trial, progress in HER2-positive gastrointestinal malignancies has been hampered by drug resistance. This review examines current HER2 expression patterns and therapies for gastroesophageal, colorectal, biliary tract, and small bowel cancers, while dissecting potential resistance mechanisms that limit treatment effectiveness.
Predicting Postoperative Length of Stay in Patients Undergoing Laparoscopic Right Hemicolectomy for Colon Cancer: A Machine Learning Approach Using SICE (Società Italiana di Chirurgia Endoscopica) CoDIG Data
Authors: Anania Gabriele , Chiozza Matteo , Pedarzani Emma , Resta Giuseppe , Campagnaro Alberto , Pedon Sabrina , Valpiani Giorgia , Silecchia Gianfranco , Mascagni Pietro , Cuccurullo Diego , Reddavid Rossella , Azzolina Danila ,   On behalf of SICE CoDIG (ColonDx Italian Group)
Published: August 2024

The evolution of laparoscopic right hemicolectomy, particularly with complete mesocolic excision (CME) and central vascular ligation (CVL), represents a significant advancement in colon cancer surgery. The CoDIG 1 and CoDIG 2 studies highlighted Italy’s progressive approach, providing useful findings for optimizing patient outcomes and procedural efficiency. Within this context, accurately predicting postoperative length of stay (LoS) is crucial for improving resource allocation and patient care, yet its determination through machine learning techniques (MLTs) remains underexplored. This study aimed to harness MLTs to forecast the LoS for patients undergoing right hemicolectomy for colon cancer, using data from the CoDIG 1 (1224 patients) and CoDIG 2 (788 patients) studies. Multiple MLT algorithms, including random forest (RF) and support vector machine (SVM), were trained to predict LoS, with CoDIG 1 data used for internal validation and CoDIG 2 data for external validation. The RF algorithm showed a strong internal validation performance, achieving the best performances and a 0.92 ROC in predicting long-term stays (more than 5 days). External validation using the SVM model demonstrated 75% ROC values. Factors such as fast-track protocols, anastomosis, and drainage emerged as key predictors of LoS. Integrating MLTs into predicting postoperative LOS in colon cancer surgery offers a promising avenue for personalized patient care and improved surgical management. Using intraoperative features in the algorithm enables the profiling of a patient’s stay based on the planned intervention. This issue is important for tailoring postoperative care to individual patients and for hospitals to effectively plan and manage long-term stays for more critical procedures.
Strategies for Improving CAR T Cell Persistence in Solid Tumors
Authors: Wittling Megen C. , Cole Anna C. , Brammer Brianna , Diatikar Kailey G. , Schmitt Nicole C. , Paulos Chrystal M.
Published: August 2024

CAR T cells require optimization to be effective in patients with solid tumors. There are many barriers affecting their ability to succeed. One barrier is persistence, as to achieve an optimal antitumor response, infused CAR T cells must engraft and persist. This singular variable is impacted by a multitude of factors—the CAR T cell design, lymphodepletion regimen used, expansion method to generate the T cell product, and more. Additionally, external agents can be utilized to augment CAR T cells, such as the addition of novel cytokines, pharmaceutical drugs that bolster memory formation, or other agents during either the ex vivo expansion process or after CAR T cell infusion to support them in the oppressive tumor microenvironment. This review highlights many strategies being used to optimize T cell persistence as well as future directions for improving the persistence of infused cells.