bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of the oxidative balance score with obesity and body composition among young and middle-aged adults
Authors: Zhu Zhiyong , Bai Hao , Li Zhaoping , Fan Miaomiao , Li Gang , Chen Liyong
Published: April 2024

Objective

The oxidative balance score (OBS) is important for determining the cause of obesity and its complications. We aimed to evaluate the association between OBS and obesity and other segmental body composition parameters among young and middle-aged U.S. adults.

Methods

9,998 participants from the National Health and Nutrition Examination Survey 2011–2018 were included. Lean mass percentage (LM%) and FM% were evaluated by dual-energy x-ray absorptiometry. Obesity was defined as body FM% ≥25% in men and ≥ 35% in women. The OBS was scored by 5 pro-oxidant and 21 antioxidant factors. Associations of quartiles of OBS with obesity risk were estimated using multivariable logistic regression models. Multivariable linear regression was conducted to estimate the association between OBS and segmental body composition measures including the arm LM%, leg LM%, torso LM%, whole LM%, arm FM%, leg FM%, torso FM% and total FM%.

Results

Compared to participants in the lowest quartile of OBS, those in the highest quartile of OBS were associated with a lower risk of BMI-defined obesity BMI-defined obesity [0.43 (0.36, 0.50)] and FM%-related obesity [0.43 (0.35, 0.52)]. Additionally, OBS was negatively associated with FM% of the limb and torso but positively associated with the percentage of lean mass (LM%) of the limb and trunk.

Conclusion

OBS was negatively associated with the risk of obesity and segmental FM%, but was positively associated with segmental LM% among US adults, indicating that adhering to an anti-oxidative diet and lifestyle management may be beneficial for preventing segmental obesity.
Qualitative and quantitative analysis methods for quality control of rhubarb in Taiwan’s markets
Authors: Au Thanh-Thuy-Dung , Ho Yu-Ling , Chang Yuan-Shiun
Published: April 2024

Introduction: Rhubarb is a traditional Chinese medicine (TCM) used to release heat and has cathartic effects. Official rhubarb in Taiwan Herbal Pharmacopeias 4th edition (THP 4th) and China Pharmacopeia 2020 (CP 2020) are the roots and rhizomes of Rheum palmatum L., Rheum tanguticum Maxim. ex Balf., and Rheum officinale Baill. However, the Rheum genus is a large genus with many different species, and owing to the similarity in appearance and taste with official rhubarb, there needs to be more clarity in the distinction between the species of rhubarb and their applications. Given the time-consuming and complicated extraction and chromatography methods outlined in pharmacopeias, we improved the qualitative analysis and quantitative analysis methods for rhubarb in the market. Hence, we applied our method to identify the species and quality of official and unofficial rhubarb.

Method: We analyzed 21 rhubarb samples from the Taiwanese market using a proposed HPLC-based extraction and qualitative analysis employing eight markers: aloe-emodin, rhein, emodin, chrysophanol, physcion, rhapontigenin, rhaponticin, and resveratrol. Additionally, we developed a TLC method for the analysis of rhubarb. KEGG pathway analysis was used to clarify the phytochemical and pharmacological knowledge of official and unofficial rhubarb.

Results: Rhein and rhapontigenin emerged as key markers to differentiate official and unofficial rhubarb. Rhapontigenin is abundant in unofficial rhubarb; however, rhein content was low. In contrast, their contents in official rhubarb were opposite to their contents in unofficial rhubarb. The TLC analysis used rhein and rhapontigenin to identify rhubarb in Taiwan’s markets, whereas the KEGG pathway analysis revealed that anthraquinones and stilbenes affected different pathways.

Discussion: Eight reference standards were used in this study to propose a quality control method for rhubarb in Taiwanese markets. We propose a rapid extraction method and quantitative analysis of rhubarb to differentiate between official and unofficial rhubarb.
Where in the brain is creativity? The fallacy of a creativity faculty in the brain
Authors: Dietrich Arne
Published: April 2024

The neuroscience of creativity is built on a tacit and near universal assumption that is false. Paradoxically, this is not contentious; once made explicit, the assumption is readily conceded as false. Psychology regards creativity as made up of many complex, multifaceted, and varied cognitive and emotional processes deployed across many different domains. But we instead think of, and treat, creativity as if it were a single, separate, cohesive, and discrete thing—as in, Einstein hadit. In a straightforward extension of this fallacy, cognitive neuroscientists have looked for uniquely creative cognition that (1) is distinct from all other kinds of cognition and (2) has a proprietary neural substrate. In other words, a standalone and monolithic creativity faculty in the brain that managesonlycreativity andallcreativity. First, this paper brings into sharp focus the nature and ubiquity of this fallacy. It then outlines the alternative theoretical position that is (1) based on fundamental neural principles and (2) predicated on taking seriously the concept of creativity as complex and diverse. Like morality or secretiveness, it holds that creativity does not exist as its own, specialized entity in the brain. Instead, its neurocognitive mechanisms are distributed, embedded, and varied; that is, creativity is everywhere and multiply realizable.
Bipolar disorders and schizophrenia: discrete disorders?
Authors: Dines Micaela , Kes Mariana , Ailán Delfina , Cetkovich-Bakmas Marcelo , Born Christoph , Grunze Heinz
Published: April 2024

Background

With similarities in heritability, neurobiology and symptomatology, the question has been raised whether schizophrenia and bipolar disorder are truly distinctive disorders or belong to a continuum. This narrative review summarizes common and distinctive findings from genetics, neuroimaging, cognition and clinical course that may help to solve this ethiopathogenetic puzzle.

Methods

The authors conducted a literature search for papers listed in PubMed and Google Scholar, using the search terms “schizophrenia” and “bipolar disorder” combined with different terms such as “genes”, “neuroimaging studies”, “phenomenology differences”, “cognition”, “epidemiology”. Articles were considered for inclusion if they were written in English or Spanish, published as full articles, if they compared subjects with schizophrenia and bipolar disorder, or subjects with either disorder with healthy controls, addressing differences between groups.

Results

Several findings support the hypothesis that schizophrenia and bipolar disorder are discrete disorders, yet some overlapping of findings exists. The evidence for heritability of both SZ and BD is obvious, as well as the environmental impact on individual manifestations of both disorders. Neuroimaging studies support subtle differences between disorders, it appears to be rather a pattern of irregularities than an unequivocally unique finding distinguishing schizophrenia from bipolar disorder. The cognitive profile displays differences between disorders in certain domains, such as premorbid intellectual functioning and executive functions. Finally, the timing and trajectory of cognitive impairment in both disorders also differs.

Conclusion

The question whether SZ and BD belong to a continuum or are separate disorders remains a challenge for further research. Currently, our research tools may be not precise enough to carve out distinctive, unique and undisputable differences between SZ and BD, but current evidence favors separate disorders. Given that differences are subtle, a way to overcome diagnostic uncertainties in the future could be the application of artificial intelligence based on BigData.

Limitations

Despite the detailed search, this article is not a full and complete review of all available studies on the topic. The search and selection of papers was also limited to articles in English and Spanish. Selection of papers and conclusions may be biased by the personal view and clinical experience of the authors.
Gender mainstreaming in sweetpotato breeding and dissemination in Ghana and Malawi
Authors: Utoblo Obaiya G. , Abidin Putri Ernawati , Dery Eric Kuuna , Bidzakin John K. , Mudege Netsayi N. , Dorgbetor Isaac Korku , Ebregt Marjolein , Carey Edward E.
Published: April 2024

Gender responsiveness in breeding programs to meet client and end user preferences for crops is essential. This case study analyzes the implementation experience of gender-responsive breeding and variety dissemination in Malawi and Ghana, focusing on good practices and challenges encountered. In Malawi, a training-of-trainers approach was employed to share knowledge among trained farmers. In Ghana, a research study was conducted to identify gender-based preferences for sweetpotato to define breeding objectives. The participation of social scientists, food scientists, and sweetpotato breeders in the GREAT (Gender Researchers Equipped for Agricultural Transformation) team provided a multidisciplinary perspective, addressing questions and responses in the field. Research efforts were strengthened by focusing on food quality through the establishment of an analytical laboratory for rapid evaluation of nutrition and food quality, including sugars. This helped develop sensory analytical capacity to better understand quality attributes and market segments, guiding breeding and improving market opportunities for women. Breeding outcomes resulting from gender inclusion led to the release of some sweetpotato varieties meeting end user and consumer preferences, as well as adoption of OFSP varieties by men and women. Other good practices for gender inclusion and responsiveness include providing funds for gender-based research and activities, engaging gender specialists and social scientists in trans-disciplinary teams, designing program activities with gender considerations, and incorporating traits in seed multiplication and dissemination decisions. Application of these gender inclusion practices resulted in adoption and development of acceptable sweetpotato varieties.
Sequence-based epitope mapping of high pathogenicity avian influenza H5 clade 2.3.4.4b in Latin America
Authors: Ospina-Jimenez Andres F. , Gomez Arlen P. , Osorio-Zambrano William F. , Alvarez-Munoz Santiago , Ramirez-Nieto Gloria C.
Published: April 2024

High Pathogenicity Avian Influenza (HPAI) poses a significant threat to public and animal health. Clade 2.3.4.4b recently emerged from the Eastern hemisphere and disseminated globally, reaching the Latin American (LATAM) region in late 2022 for the first time. HPAI in LATAM has resulted in massive mortalities and culling of poultry and wild birds, causing infection in mammals and humans. Despite its meaningful impact in the region, only occasional evidence about the genetic and epitope characteristics of the introduced HPAI is reported. Hence, this study seeks to phylogenetically characterize the molecular features and the source of HPAI in LATAM by evaluating potential antigenic variations. For such a purpose, we analyzed 302 whole genome sequences. All Latin American viruses are descendants of the 2.3.4.4b clade of the European H5N1 subtype. According to genomic constellations deriving from European and American reassortments, the identification of three major subtypes and eight sub-genotypes was achievable. Based on the variation of antigenic motifs at the HA protein in LATAM, we detected three potential antigenic variants, indicating the HA-C group as the dominant variant. This study decidedly contributes to unraveling the origin of the 2.3.4.4b clade in LATAM, its geographic dissemination, and evolutionary dynamics within Latin American countries. These findings offer useful information for public health interventions and surveillance initiatives planned to prevent and manage the transmission of avian influenza viruses.
A New Species of Diploderma (Squamata, Agamidae) from the Valley of Dadu River in Sichuan Province, with a Redescription of Topotypes of D. splendidum from Hubei Province, China
Authors: Cai Bo , Liu Fengjing , Liang Dong , Hou Mian , Zhou Huaming , Zhong Jiayun , Li Jing , Chang Jiang
Published: April 2024

This study describes a novel species of Diploderma (Squamata, Agamidae) from the lower valley of the Dadu River of the Sichuan Province of Western China based on its distinct morphological features and molecular evidence. D. daduense sp. nov. can be distinguished from its congeners by its tympanum concealed; head mainly green-yellow, supplemented by black; skin folds under the nuchal and dorsal crest obviously present in adult males only, its vertebral crest discontinuous between nuchal and dorsal sections with a distinct gap; transverse gular fold present but not obvious in some individuals; gular spot absent in both sexes; dorsolateral stripes green-yellow anteriorly, cyan in the center and blurry off-white posteriorly in adult males, the upper edge of dorsolateral stripes strongly jagged in adult males; no radial stripes around the eyes; inner-lip coloration smoky-white, and the coloration of the tongue and oral cavity as a light-flesh color in life; bright green-yellow transverse stripes on dorsal body in males; black patches are evenly distributed along the vertebral line between the dorsolateral stripes from the neck to the base of the tail in males; beech-brown or gray-brown line along the vertebral line with heart-shaped or diamond-shaped black patches on the dorsal body in females; and supratemporals fewer than four on at least one side. The phylogenetic tree based on mitochondrial ND2 sequences indicates that D. daduense sp. nov. forms an independent clade with strong support 1/100 in ML bootstrap/Bayesian posterior probability and is the sister group to D. splendidum. At the inter-species level, the p-distance is at least 6.95%, further confirming that an independent species had been identified. Our work raises the number of species within the genus Diploderma to 47.
Exploration of Fragmentation Mechanisms of Yellow Split Peas during Grinding Using a Multimodal Approach
Authors: Koëgel Laurène , Barbar Reine , Réau Adrien , Cuq Bernard
Published: April 2024

In the context of food and agro-ecological transitions, the development of food applications based on legume flours and plant proteins requires a mastery of grain milling. While wheat grain milling has been extensively studied and is well-mastered, legume grinding and its underlying mechanisms are still poorly understood. The aim of this work is to contribute to the study of the fragmentation mechanisms of pea grains during grinding. Experiments were carried out on hulled yellow pea grains (Kameleon variety) ground under different conditions using a ball mill (MM400, Retsch®, Haan, Germany) or a micro-cylinder mill. The results showed that the grinding of pea grains, regardless of the type of mill, produced powders characterized by particle size distribution curves with a multimodal shape. The curve analysis was performed according to a simplified deconvolution approach, taking into account different particle populations without diameter overlap. Four particle populations of different sizes were identified and correlated with specific mechanisms governing the grinding of yellow split peas. The physical and biochemical properties of the resulting powders were determined. Taking into account the proportions of the four populations within the powders, the results showed a positive correlation between the volume proportions of very fine (0–10 µm) and fine (10–55 µm) particles within the powders and the starch damage rate and the specific surface area developed, irrespective of the type of mill.
A Method for Measuring Spatial Information of Area Maps Considering the Diversity of Node–Edge and Gestalt Principles
Authors: Kang Qiankun , Zhou Xiaoguang , Hou Dongyang
Published: April 2024

Existing methods for measuring the spatial information of area maps fail to take into account the diversity of adjacency relations and the heterogeneity of adjacency distances among area objects, resulting in insufficient measurement information. This article proposes a method for measuring area map information that considers the diversity of the node–edge and Gestalt principles. Firstly, this method utilizes the adjacency relations between the Voronoi diagram of area objects to construct an adjacency graph that characterizes the spatial distribution of area objects in area maps. This adjacency graph serves as the information representation of area maps. Secondly, the method selects four characteristic indicators, namely geometric information, node degree, adjacency distance, and adjacency strength, to represent the diversity of nodes and edges in the graph that affect spatial information. Finally, nodes in the adjacency graph are taken as the basic units, and the spatial information of area maps is comprehensively calculated by integrating the four characteristics that represent spatial information. To verify the validity and rationality of the proposed method, a dataset of continuously simplified area maps and a dataset of artificially simulated degrees of randomness were designed to evaluate the performance of the existing method and the method proposed in this paper. The results indicate that the correlation between the measurement results obtained by the method proposed in this paper and the degree of disorder is as high as 0.94, outperforming the existing representative methods. Additionally, the correlation between the measurement results of this method and the degree of simplification reaches 1, indicating that the variation range of the measured values is more consistent with the cognitive assumptions based on artificial simulations compared to the existing methods. The experimental results show that the method proposed in this paper is an effective metric approach for representing spatial information in area maps.
Natural Ventilation to Manage Ammonia Concentration and Temperature in a Rabbit Barn in Central Mexico
Authors: Cano David Vargas , Flores-Velazquez Jorge , Garcia Agustín Ruiz
Published: April 2024

The concentration of ammonia (NH3) and the temperature of the air surrounding the rabbit habitat in the farm condition basic health processes such as breathing and feeding. The indoor climate in a rabbit farm is largely conditioned by the ventilation system (air conditioning). The objective of this study was to build a numerical model based on computational fluid dynamics (CFD) in order to evaluate, by numerical simulations, the air dynamics of a rustic farm. After the validation of the computational model, the thermal gradient and ammonia concentration were analyzed under three wind incidence angles (0°, 45°, and 90° with respect to the horizontal Z axis of the facility). The results of the simulations showed that, in the area occupied by the rabbits (AOR), the concentration of ammonia with respect to the source was reduced by 37.3% in the most favorable case (wind direction at 45°), and 21.2% in the least favorable case (wind direction at 0°), and the indoor temperature presented a maximum difference of 2 °C with respect to the outside temperature. Climate control is a more expensive cost in rabbit farm exploitation; dynamics modulation can serve as an auxiliary tool for reducing health risks in rabbits. The use of models based on fluid dynamics allowed us to understand the efficiency of the ventilation system, which must be increased to reduce the found temperature gradient. Through numerical simulation it will be possible to find alternatives to increase the ventilation rate.
Enriching User-Visitor Experiences in Digital Museology: Combining Social and Virtual Interaction within a Metaverse Environment
Authors: Alabau Alba , Fabra Lidia , Martí-Testón Ana , Muñoz Adolfo , Solanes J. Ernesto , Gracia Luis
Published: April 2024

This study investigates the potential of integrating multilayer animations and sophisticated shader technologies to enhance visitor social interactions within metaverse exhibition spaces. It is part of a broader initiative aimed at developing innovative digital museology strategies that foster social engagement through virtual reality (VR) experiences. The methodology adopted seeks to provide a more immersive and human-centric exploration of 3D digital environments by blending elements of physical spaces with the interactive dynamics common in video games. A virtual exhibition space themed around Mars was created as a testbed to facilitate social interactions among users, who navigate the environment via avatars. This digital space was developed using a specialized Unity template designed by the metaverse platform Spatial.io. Overcoming the programming constraints imposed by Spatial.io, which limits the use of external scripts for security and stability, posed a significant challenge. Nonetheless, by leveraging the ability to modify shader codes used for material creation and employing advanced animation techniques with layered effects, the authors of this work achieved dynamic material responses to lighting changes and initiated complex asset interactions beyond simple linear animations.
Exploring the Efficacy of Learning Techniques in Model Extraction Attacks on Image Classifiers: A Comparative Study
Authors: Han Dong , Babaei Reza , Zhao Shangqing , Cheng Samuel
Published: April 2024

In the rapidly evolving landscape of cybersecurity, model extraction attacks pose a significant challenge, undermining the integrity of machine learning models by enabling adversaries to replicate proprietary algorithms without direct access. This paper presents a comprehensive study on model extraction attacks towards image classification models, focusing on the efficacy of various Deep Q-network (DQN) extensions for enhancing the performance of surrogate models. The goal is to identify the most efficient approaches for choosing images that optimize adversarial benefits. Additionally, we explore synthetic data generation techniques, including the Jacobian-based method, Linf-projected Gradient Descent (LinfPGD), and Fast Gradient Sign Method (FGSM) aiming to facilitate the training of adversary models with enhanced performance. Our investigation also extends to the realm of data-free model extraction attacks, examining their feasibility and performance under constrained query budgets. Our investigation extends to the comparison of these methods under constrained query budgets, where the Prioritized Experience Replay (PER) technique emerges as the most effective, outperforming other DQN extensions and synthetic data generation methods. Through rigorous experimentation, including multiple trials to ensure statistical significance, this work provides valuable insights into optimizing model extraction attacks.
Optimal Planning of Battery Swapping Stations Incorporating Dynamic Network Reconfiguration Considering Technical Aspects of the Power Grid
Authors: Al-Zaidi Waleed Khalid Mahmood , Inan Aslan
Published: April 2024

In order to drive electric vehicle adoption and bolster grid stability, the incorporation of battery swapping stations (BSSs) into the power grid is imperative. Conversely, network reconfiguration plays a crucial role in optimizing energy exchange within the power network, ensuring its economical and safe operation. Therefore, this study proposes an optimal planning method for battery swapping stations that integrates dynamic power distribution network reconfiguration while addressing technical aspects of the grid. The proposed method aims to concurrently optimize the placement and capacity of battery swapping stations, along with power distribution network reconfiguration, to enhance grid reliability and efficiency. The optimization model accounts for various factors including power quality, technical considerations, grid limitations, and operational expenses. A multi-objective optimization framework is devised to simultaneously reduce system losses, improve voltage stability, and mitigate environmental impacts of the power distribution network incorporating DG units. Case studies are conducted to illustrate the efficacy of the proposed approach in enhancing overall grid performance while accommodating the integration of battery swapping stations. The findings underscore the significance of considering technical factors and grid reconfiguration in battery swapping station planning to achieve optimal system operation and maximize benefits for electric vehicle users and grid operators alike.
Numerical Simulation on the Leakage-Induced Collapse of Segmental Tunnels
Authors: Sun Qihao , Liu Xian , De Corte Wouter , Taerwe Luc
Published: April 2024

Sudden leakage during tunnel construction poses a great threat to the safety of the tunnel. There are relatively few studies on the mechanism of structural collapse induced by tunnel leakage, so it is difficult to propose effective control measures. To solve this problem, a coupled fluid–solid strata analysis model and a nonlinear FEM tunnel model were established based on model test results to analyze the mechanism of tunnel collapse. The following conclusions were drawn: (1) A DEM-based coupled fluid–solid model combined with a nonlinear FEM tunnel model can effectively simulate the physical process of tunnel collapse. (2) The mechanism of tunnel leakage-induced strata response is the continuous destabilization and reappearance of the soil arching effect, which restricts the erosion of the soil and results in macroscopic soil caves, and finally leads to the impact load of the destabilized soil. (3) The process of the tunnel structure collapse is as follows: firstly, a large deformation of the tunnel structure is caused by the redistribution of external loads generated by the earth arching effect; then, due to the multiple impact loads from the destabilization of the soil, plastic hinges are generated at the tunnel joints, and the tunnel collapses.
Research on Online Review Information Classification Based on Multimodal Deep Learning
Authors: Liu Jingnan , Sun Yefang , Zhang Yueyi , Lu Chenyuan
Published: April 2024

The incessant evolution of online platforms has ushered in a multitude of shopping modalities. Within the food industry, however, assessing the delectability of meals can only be tentatively determined based on consumer feedback encompassing aspects such as taste, pricing, packaging, service quality, delivery timeliness, hygiene standards, and environmental considerations. Traditional text data mining techniques primarily focus on consumers’ emotional traits, disregarding pertinent information pertaining to the online products themselves. In light of these aforementioned issues in current research methodologies, this paper introduces the Bert BiGRU Softmax model combined with multimodal features to enhance the efficacy of sentiment classification in data analysis. Comparative experiments conducted using existing data demonstrate that the accuracy rate of the model employed in this study reaches 90.9%. In comparison to single models or combinations of three models with the highest accuracy rate of 7.7%, the proposed model exhibits superior accuracy and proves to be highly applicable to online reviews.
Concrete Structures: Latest Advances and Prospects for a Sustainable Future
Authors: Diaferio Mariella , Varona Francisco B.
Published: April 2024

Along with structural steel, structural concrete is probably one of the most widely used construction materials worldwide for building construction and civil engineering infrastructures [...]
Injury Incidence in Traineras: Analysis of Traditional Rowing by Competitive Level and Gender
Authors: León-Guereño Patxi , Penichet-Tomas Alfonso , Castañeda-Babarro Arkaitz , Jimenez-Olmedo Jose M.
Published: April 2024

The growing interest in “Traineras”, a traditional competitive rowing modality prevalent in Northern Spain, underscores the need for a comprehensive analysis of the injury incidence associated with this sporting practice. Despite rowing’s significance in the international sports arena and its inclusion since the beginnings of the modern Olympic Games, research into injuries in this sport, especially in traditional modalities such as Traineras, has been limited. This study aimed to identify and describe the predominant injuries among Traineras rowers, analyzing their epidemiology, characteristics, affected body regions, and diagnoses, further differentiated by competitive level and gender. A retrospective survey completed by 773 rowers (24% women, 76% men) participating in various leagues (ACT, ARC1, ARC2, LGT1, LGT2, ETE, and LGT-F) during the season revealed that 68.2% suffered from at least one injury, predominantly due to overuse (91.1% in men, 83.1% in women). The most affected regions were the lower back and shoulders, with the main diagnoses being muscle cramps and tendinitis, showing statistically significant differences between sexes. The findings of this study not only provide a deeper understanding of the etiology and origin of injuries in this sport but also lay the groundwork for developing specific injury prevention plans, thereby contributing to the safety and optimal performance of athletes.
A Building Heat Load Prediction Method Driven by a Multi-Component Fusion LSTM Ridge Regression Ensemble Model
Authors: Zhang Yu , Chen Guangshu
Published: April 2024

Under the background of “double carbon”, building carbon emission reduction is urgent, and improving energy efficiency through short-term building heat load forecasting is an efficient means of building carbon emission reduction. Aiming at the characteristics of the decomposed short-term building heat load data, such as complex trend changes, significant seasonal changes, and randomness, a single-step short-term building heat load prediction method driven by the multi-component fusion LSTM Ridge Regression Ensemble Model (ST-LSTM-RR) is designed and implemented. First, the trend and seasonal components of the heat load are decomposed by the STL seasonal decomposition algorithm, which are fused into the original data to construct three diversified datasets; second, three basic models, namely, the trend LSTM, the seasonal LSTM, and the original LSTM, are trained; and then, the ridge regression model is trained to fuse the predicted values of the three basic models to obtain the final predicted values. Finally, the method of this paper is applied to the heat load prediction of eight groups in a large mountain hotel park, and the root mean square error (RMSE) and mean absolute error (MAE) are used as the evaluation indexes. The experimental results show that the average RMSE and average MAE of the prediction results of the proposed method in this paper are minimized on the eight groups.
BIMO: Bootstrap Inter–Intra Modality at Once Unsupervised Learning for Multivariate Time Series
Authors: Heo Seongsil , Kim Sungsik , Lee Jaekoo
Published: April 2024

It is difficult to learn meaningful representations of time-series data since they are sparsely labeled and unpredictable. Hence, we propose bootstrap inter–intra modality at once (BIMO), an unsupervised representation learning method based on time series. Unlike previous works, the proposed BIMO method learns both inter-sample and intra-temporal modality representations simultaneously without negative pairs. BIMO comprises a main network and two auxiliary networks, namely inter-auxiliary and intra-auxiliary networks. The main network is trained to learn inter–intra modality representations sequentially by regulating the use of each auxiliary network dynamically. Thus, BIMO thoroughly learns inter–intra modality representations simultaneously. The experimental results demonstrate that the proposed BIMO method outperforms the state-of-the-art unsupervised methods and achieves comparable performance to existing supervised methods.
Kinetic Comparison between Drop Jumps and Horizontal Drop Jumps in Elite Jumpers and Sprinters
Authors: Montoro-Bombú Raynier , Miranda-Oliveira Paulo , Valamatos Maria João , João Filipa , Buurke Tom J. W. , Cupido Santos Amândio , Rama Luís
Published: April 2024

Previous research addressed the spatiotemporal variables of the drop jump (DJ) versus the horizontal drop jump (HDJ). This study compared the kinetic variables of the DJ versus the HDJ in elite jumpers and sprinters. In a single session, sixteen elite jumpers and sprinters performed two DJ attempts with three different fall heights (0.30 m, 0.40 m, and 0.50 m), and after 2 h, performed two HDJ attempts from the same fall heights (0.30 m, 0.40 m, and 0.50 m). Kinetic variables: eccentric ground reaction forces (GRFE) and concentric ground reaction forces; eccentric impulse (PE) and concentric impulse (PC); peak power in the concentric phase; and rate of force decrease (RFDe) were measured using a research-grade force plate. The Wilcoxon test was used to compare the vertical and anteroposterior axes. GRFE was significantly higher (p ≤ 0.05) in the DJ vs the HDJ with large effect sizes. The PE (p ≤ 0.006) and PC (p = 0.002) were significantly lower in the DJ than in the HDJ. The RFDe was also significantly lower in the DJ at 0.30 m vs. the HDJ at 0.30 m (p = 0.002). In summary, elite jumpers and sprinters may benefit from incorporating both the DJ and the HDJ into their training regimens, with the DJ being particularly advantageous for enhancing power metrics and RFDe.
Area of Interest Tracking Techniques for Driving Scenarios Focusing on Visual Distraction Detection
Authors: Nagy Viktor , Földesi Péter , Istenes György
Published: April 2024

On-road driving studies are essential for comprehending real-world driver behavior. This study investigates the use of eye-tracking (ET) technology in research on driver behavior and attention during Controlled Driving Studies (CDS). One significant challenge in these studies is accurately detecting when drivers divert their attention from crucial driving tasks. To tackle this issue, we present an improved method for analyzing raw gaze data, using a new algorithm for identifying ID tags called Binarized Area of Interest Tracking (BAIT). This technique improves the detection of incidents where the driver’s eyes are off the road through binarizing frames under different conditions and iteratively recognizing markers. It represents a significant improvement over traditional methods. The study shows that BAIT performs better than other software in identifying a driver’s focus on the windscreen and dashboard with higher accuracy. This study highlights the potential of our method to enhance the analysis of driver attention in real-world conditions, paving the way for future developments for application in naturalistic driving studies.
Reproducibility and Data Storage for Active Learning-Aided Systematic Reviews
Authors: Lombaers Peter , de Bruin Jonathan , van de Schoot Rens
Published: April 2024

In the screening phase of a systematic review, screening prioritization via active learning effectively reduces the workload. However, the PRISMA guidelines are not sufficient for reporting the screening phase in a reproducible manner. Text screening with active learning is an iterative process, but the labeling decisions and the training of the active learning model can happen independently of each other in time. Therefore, it is not trivial to store the data from both events so that one can still know which iteration of the model was used for each labeling decision. Moreover, many iterations of the active learning model will be trained throughout the screening process, producing an enormous amount of data (think of many gigabytes or even terabytes of data), and machine learning models are continually becoming larger. This article clarifies the steps in an active learning-aided screening process and what data is produced at every step. We consider what reproducibility means in this context and we show that there is tension between the desire to be reproducible and the amount of data that is stored. Finally, we present the RDAL Checklist (Reproducibility and Data storage for Active Learning-Aided Systematic Reviews Checklist), which helps users and creators of active learning software make their screening process reproducible.
Preventive Maintenance Decision-Making Optimization Method for Airport Runway Composite Pavements
Authors: Ling Jianming , Wang Zengyi , Liu Shifu , Tian Yu
Published: April 2024

Long-term preventive maintenance planning using finite annual budgets is vital for maintaining the service performance of airport runway composite pavements. Using the pavement condition index (PCI) to quantify composite pavement performance, this study investigated the PCI deterioration tendencies of middle runways, terminal runways, and taxiways and developed prediction models related to structural thickness and air traffic. Performance jump (PJ) and deterioration rate reduction (DRR) were used to measure maintenance benefits. Based on 112 composite pavement sections in the Long-term Pavement Performance Program, this study analyzed the influences of five typical preventive maintenance technologies on PJ, DRR, and PCI deterioration rates. The logarithmic regression relationship between PJ and PCI was obtained. For sections treated with crack sealing and crack filling, the DRR was nearly 0. For sections treated with fog seal, thin HMA overlay, and hot-mix recycled AC, the DRR was 0.2, 0.7, and 0.8, respectively. To solve the multi-objective maintenance problem, this study proposed a decision-making optimization method based on dynamic programming, and the solution algorithm was optimized, which was applied in a five-year maintenance plan. Considering different PCI deterioration tendencies of airport regions, as well as PJ, DRR, and costs of maintenance technologies, the preventive maintenance decision-making optimization method meets performance and financial requirements sufficiently.
Vertical Distribution and Mineralization Dynamics of Organic Carbon in Soil and Its Aggregates in the Chinese Loess Plateau Driven by Precipitation
Authors: Gao Chunyang , Zhang Zhidan , Li Meijia , Feng Bohan , Zhou Yipeng , Zhang Jinjing , He Nianpeng
Published: April 2024

The mineralization of soil organic carbon (SOC) is a critical process in the soil carbon cycle. This study aimed to investigate the vertical distribution characteristics and mineralization dynamics of SOC in soils and their aggregates across different steppe types in the Loess Plateau (LP). Soil profiles from three steppe types under varying precipitation gradients were selected: meadow steppe (MS), typical steppe (TS), and desert steppe (DS). A 60-day controlled laboratory incubation study was conducted for carbon mineralization and the influence of climatic and soil properties on SOC mineralization was analyzed. The results showed that the SOC content and cumulative mineralization (CM) in 1–2 mm aggregates were higher than in other particle sizes; SOC content and CM followed the order MS > TS > DS and both decreased significantly with increasing soil depth. Correlation analysis revealed that precipitation significantly affected aggregate mineralization (p < 0.001) and that mineralization in the 1–2 mm aggregates was more closely related to mean annual precipitation (MAP), SOC, and water-soluble organic carbon (SWOC). Precipitation primarily controlled SOC mineralization in the 0–50 cm soil layer, while SOC mineralization in the 50–100 cm layer was influenced by soil-related carbon content. Structural Equation Modeling indicated that precipitation influences the mineralization of organic carbon in topsoil indirectly through its direct impact on SOC. In the context of global warming, the SOC turnover rate in high-precipitation areas (MS) was faster than in low-precipitation areas (TS, DS), necessitating greater attention to soil carbon dynamics in these regions.
Intermonitor Variability of Garmin Vivofit® Jr. Wristband
Authors: Díaz-Quesada Gema , Gimenez-Egido José María , Connor Jonathan , Ortega-Toro Enrique , Torres-Luque Gema
Published: April 2024

The main objective of this study was to evaluate the reliability of Garmin Vivofit® Jr. physical activity (PA) wristbands during daily life physical activities. Six wristbands were randomly selected from a stock of twenty-four. The wristbands were worn by a single four-year-old participant, with three on the right wrist area and three on the left wrist area. To assess device reliability under laboratory conditions on a treadmill (Powerjog, model JM200, Sport Engineering Ltd., Birmingham, UK), the participant wore the six wristbands while performing five work conditions: sitting and standing (30 times per minute, controlled by a metronome), walking at 3 km/h, walking at 4 km/h, running at 5 km/h, and running at 6 km/h. Throughout the six minutes, variables related to physical activity provided by the device, step volume, and minutes of physical activity were recorded using the specific application of the wristband (Garmin International Inc., Olathe, KS, USA). The intraclass correlation coefficients (ICCs) were high for all six wristbands with each other, for both the number of steps taken (ICC = 0.991–0.998) and the number of minutes of PA (ICC = 0.892–0.977). The critical alpha value of the Cusum test was highest at.050 for all wristband associations. In conclusion, good reliability was found among the six wristbands, which could be adopted for field-based research to quantify physical activities.
Simulation and Experimental Study of the Suppression of Low-Frequency Flow Noise Signals by a Placoid-Scale Skin
Authors: Cheng Mingxin , Zhu Zhijuan , Wu Bin , Ye Lingyun , Song Kaichen
Published: April 2024

This paper addresses the challenge of mitigating low-frequency flow noise signals in autonomous underwater vehicles through the optimization of a placoid-scale skin. Drawing inspiration from the bio-inspired surface features of cylindrical shell structures, an enhanced design of placoid-scale skin is developed using 3D printing technology. This improved structure effectively reduced boundary layer vortices and wake intensity, thereby contributing to the suppression of low-frequency flow noise signals. Experimental results demonstrate that the notable reduction in low-frequency flow noise within the frequency range of 0–500 Hz, with average noise reduction of approximately 5 dB observed at 150 Hz. This reduction is validated by a combination of numerical simulations and experimental testing, confirming the efficacy of the optimized placoid-scale skin in attenuating the low-frequency flow noise associated with uniformly advancing turbulent boundary layers underwater.
Speech Puzzles (Spuzzles): Engaging the Reduced, Causal, and Semantic Listening Modes for Puzzle Design in Audio Games
Authors: Rovithis Emmanouel , Papadopoulou Agnes , Komianos Vasileios , Garneli Varvara , Floros Andreas
Published: April 2024

This paper proposes a novel approach to audio game design by introducing the concept of speech puzzles (spuzzles) to describe the utilisation of recorded voice for the creation of audio puzzles in ways that challenge players’ different listening modes. In the fields of audio games and audio-interactive applications, speech serves instructive, descriptive, narrative, and in some cases—in the form of hints or quizzes—gameplay purposes by addressing users through language. The suggested approach of spuzzles extends this potential by including, besides encoded meaning, the acoustic properties of sound, thus engaging the user’s causal and reduced listening modes in parallel with the semantic listening mode. An audio game consisting of four inherently different spuzzles was designed as proof of concept and tested by seven third-year students of Audiovisual Arts, who elaborated on their experience through a focus group semi-structured discussion. Despite their difficulty, the spuzzles were well accepted by most of the participants (5/7), whereas all participants agreed on their acoustic richness, need for concentration, and independence from pre-existing musical knowledge. Therefore, the authors suggest that the proposed design approach could serve as a paradigm for future research in the design of complex audio-based game mechanics.
Quantitative and Qualitative Determination of Polyphenolic Compounds in Castanea sativa Leaves and Evaluation of Their Biological Activities
Authors: Żurek Natalia , Pawłowska Agata Maria , Pycia Karolina , Potocki Leszek , Kapusta Ireneusz Tomasz
Published: April 2024

The aim of the study was to evaluate the polyphenol profile of Castanea sativa leaf methanolic extract and further evaluate its biological activities in vitro. After purification with an RP-18 resin, the extract was assessed for its polyphenol profile by UPLC-PDA-MS/MS, as well as for the antioxidant potential (ABTS, CUPRAC, ChA, ROS scavenging methods), anticancer, antiobesity, antidiabetic and antimicrobial potential. Eighteen polyphenols were identified and the dominant compounds were chestatin followed by quercetin 3-O-glucoside. The total phenolic content of the extract showed a value of 1426.55 mg/100 g d.w. The obtained preparation showed the ability to scavenge O2•− (0.067 mg/mL) and OH• (0.207 mg/mL) radicals and had a stronger anti-obesity than anti-diabetic effect. Additionally, this extract exhibited a strong anticancer activity against the Caco-2 line (153.54 µg/mL), with anti-migratory and anti-proliferative activity. In turn, among the tested strains, the highest activity was demonstrated against Staphylococcus aureus. Moreover, the effects demonstrated were strongly dependent on the content of polyphenols. In conclusion, C. sativa is a promising source of natural antioxidant, antibacterial, antiobesity, antidiabetic and chemopreventive compounds for food-pharma industry; however, further experimental studies are needed to validate its pharmacological properties.
Using Genetic Algorithms and Core Values of Cooperative Games to Solve Fuzzy Multiobjective Optimization Problems
Authors: Wu Hsien-Chung
Published: April 2024

A new methodology for solving the fuzzy multiobjective optimization problems is proposed in this paper by considering the fusion of cooperative game theory and genetic algorithm. The original fuzzy multiobjective optimization problem needs to be transformed into a scalar optimization problem, which is a conventional optimization problem. Usually, the assignments of suitable coefficients to the corresponding scalar optimization problem are subjectively determined by the decision makers. However, these assignments may cause some biases by their subjectivity. Therefore, this paper proposes a mechanical procedure to avoid this subjective biases. We are going to formulate a cooperative game using the α-level functions of the multiple fuzzy objective functions. Under this setting, the suitable coefficients can be determined mechanically by involving the core values of the cooperative game, which is formulated using the multiple fuzzy objective functions. We shall prove that the optimal solutions of the transformed scalar optimization problem are indeed the nondominated solutions of fuzzy multiobjective optimization problem. Since the core-nondominated solutions will depend on the coefficients that are determined by the core values of cooperative game, there will be a lot of core-nondominated solutions that will also depend on the corresponding coefficients. In order to obtain the best core-nondominated solution, we shall invoke the genetic algorithms by evolving the coefficients.