bluuebunny/crossref_metadata_2025 huggingface dataset:
Rider Variables Affecting the Stirrup Directional Force Asymmetry during Simulated Riding Trot
Authors: Baragli Paolo , Alessi Alberto , Pagliai Marco , Felici Martina , Ogi Asahi , Hawson Lesley , Gazzano Angelo , Padalino Barbara
Published: November 2022

Riders’ asymmetry may cause back pain in both human and equine athletes. This pilot study aimed at documenting in a simple and quick way asymmetry in riders during a simulation of three different riding positions on wooden horseback using load cells applied on the stirrup leathers and identifying possible associations between riders’ asymmetry and their gender, age, level of riding ability, years of riding experience, riding style, motivation of riding, primary discipline and handedness. After completing an interview to obtain the previously mentioned information, 147 riders performed a standardized test on a saddle fixed on a wooden horseback-shaped model. The riding simulation was split into three phases of 1 min each: (1) sit in the saddle, (2) standing in the stirrups and (3) rising trot. The directional force on the left and the right stirrup leathers was recorded every 0.2 s. A paired t-test was performed on the recorded data to test the difference (i.e., asymmetry) in each phase. In phases 1, 2 and 3, 99.3% (53.4% heavier on the right (R)), 98% (52.8% heavier on the left (L)) and 46.3% (51.5% heavier on the left (L)) of the riders were asymmetrical, respectively. Chi-square tests showed a significant association between riding ability and riding experience, but no significant association between reported handedness and calculated leg-sidedness (p > 0.05). Univariate logistic (1: asymmetry, 0: symmetry) regression analysis was performed only on the phase 3 data. One-hand riders were found twice more likely to be asymmetrical than two-hand riders (Odds Ratio (OR): 2.18, Confidence Interval (CI): 1.1–4.29; p = 0.024). This preliminary study confirmed that the majority of the riders are asymmetrical in load distribution on stirrups and suggested the riding style as a possible risk factor for asymmetry.
Lysolecithin Improves Broiler Growth Performance through Upregulating Growth-Related Genes and Nutrient Transporter Genes Expression Independent of Experimental Diet Nutrition Level
Authors: Zhang Zhiming , Zhang Song , Nie Kangkang , Zheng He , Luo Zheng , Kim In-Ho
Published: November 2022

We investigated the effect and interaction of lysolecithin (LPL) and nutrition level on growth performance, nutrient ileal digestibility, expression of growth-related genes and nutrient transporter genes in broilers. A total of 1280 one day old Ross 308 mixed sex chicks with an average body weight 42.23 ± 2.4 g were randomly allotted into 2 × 2 factorial arrangement (20 replicates per treatment and 16 chickens per replicate) with two types of diet (Normal nutrition treatments starter, grower and finisher diets with ME of 3000 kcal/kg, 3100 kcal/kg and 3200 kcal/kg, respectively, and CP level of 22%, 21%, and 20%, respectively; high nutrition treatments diets with 50 kcal/kg ME and 0.5% CP higher than normal nutrition treatment at each stage). Two levels of LPL supplementation (0 and 500 mg/kg) were also employed. From day 21 to day 35 and full stage of the experiment, the birds fed a high nutrition (HN) diet had a greater body weight gain (BWG) and lower feed conversion ratio (FCR) than those fed a normal nutrition (NN) diet (p < 0.05). Besides, lysolecithin increased BWG significantly (p < 0.05). The birds fed a diet with LPL revealed increasing fat digestibility compared to birds fed the basal diet (p < 0.05). LPL significantly increased the ileal digestibility of amino acids, including Ile, Thr, Phe, His, Arg, Tyr, Glu, Pro, Gly, Ala (p < 0.05). No interaction was found between LPL and nutrition level in BWG, FCR and nutrient digestibility. In HN diet, the genes expression of myogenic differentiation 1 (MYOD1), myogenin (MYOG), cluster of differentiation 36 (CD36), fatty acid-binding protein (FABP1), cationic amino acid transporter 1 (CAT1) and Y + L amino acid transporter 1 (y+, LAT1) were significantly elevated via LPL supplementation (p < 0.05). In NN diet, LPL significantly increased the genes expression of growth hormone (GH), insulin-like growth factor 1 (IGF1), MYOD1 and y+, LAT1 (p < 0.05). In conclusion, upregulating the nutrients transporter gene and growth-related gene expression of the host, independent of nutrition level changes, may be the action mechanism of lysolecithin on growth promotion in animals.
Intestinal Ecology Changes in Diarrheic Père David’s Deer Revealed by Gut Microbiota and Fecal Metabolites Analysis
Authors: Zhen Junai , Yuan Xueli , Tao Liping , Zhang Huidan , Ren Yijun , Xie Shengbin , Wang Libo , Shen Hua , Chen Yuqing
Published: November 2022

Diarrhea is one of the most common diseases affecting the health of Père David’s deer (Elaphurus davidianus). It is believed that an imbalanced intestinal ecology contributes to the etiology of the condition. However, little is known about how the intestinal ecology changes in these diarrheic animals. In this study, 16S rRNA gene sequencing and ultra-high performance liquid chromatography combined with tandem mass spectrometry (UPLC-MS/MS) were used to investigate the gut microbiota and fecal metabolites in five Père David’s deer with diarrhea. The results showed that when compared with healthy individuals, considerable changes in the gut microbiome were observed in diarrheic animals, including a significant reduction in microbial diversity and gut microbiota composition alterations. Furthermore, the profiles of numerous fecal metabolites were altered in diarrheic individuals, showing large-scale metabolite dysregulation. Among metabolites, acylcarnitines, lysophosphatidylcholine, bile acids, and oxidized lipids were elevated significantly. Constantly, several metabolic pathways were significantly altered. Interestingly, predicted metabolic pathways based on 16S rRNA gene sequence and differential metabolite analysis showed that lipid metabolism, cofactor, and vitamin metabolism were altered in sick animals, indicating microbiota-host crosstalk in these deer. When combined, the results provide the first comprehensive description of an intestinal microbiome and metabolic imbalance in diarrheic Père David’s deer, which advances our understanding and potential future treatment of diarrheic animals.
Daily Rhythms in the IGF-1 System in the Liver of Goldfish and Their Synchronization to Light/Dark Cycle and Feeding Time
Authors: Alonso-Gómez Aitana , Madera Diego , Alonso-Gómez Ángel Luis , Valenciano Ana Isabel , Delgado María Jesús
Published: November 2022

The relevance of the insulin-like growth factor-1 (IGF-1) system in several physiological processes is well-known in vertebrates, although little information about their temporal organization is available. This work aims to investigate the possible rhythmicity of the different components of the IGF-1 system (igf-1, the igf1ra and igf1rb receptors and the paralogs of its binding proteins IGFBP1 and IGFBP2) in the liver of goldfish. In addition, we also study the influence of two environmental cues, the light/dark cycle and feeding time, as zeitgebers. The hepatic igf-1 expression showed a significant daily rhythm with the acrophase prior to feeding time, which seems to be strongly dependent on both zeitgebers. Only igfbp1a-b and igfbp1b-b paralogs exhibited a robust daily rhythm of expression in the liver that persists in fish held under constant darkness or randomly fed. The hepatic expression of the two receptor subtypes did not show daily rhythms in any of the experimental conditions. Altogether these results point to the igf-1, igfbp1a-b, and igfbp1b-b as clock-controlled genes, supporting their role as putative rhythmic outputs of the hepatic oscillator, and highlight the relevance of mealtime as an external cue for the 24-h rhythmic expression of the IGF-1 system in fish.
A Methodology for Embedding Building Information Modelling (BIM) in an Undergraduate Civil Engineering Program
Authors: Del Savio Alexandre Almeida , Galantini Velarde Katerina , Díaz-Garay Bertha , Valcárcel Pollard Edgar
Published: November 2022

Undergraduate programs face the permanent challenge of constantly transforming to keep an up-to-date curriculum according to globalization and internationalization processes. In the case of civil engineers, professional training should respond to the needs of the Architecture, Engineering, Construction, and Operation (AECO) industry. In this context, Building Information Modelling (BIM) constitutes a process involving shared digital representations of built assets to facilitate design, construction, and operations processes within the industry to form a reliable base for decision-making. The present research develops a methodology and a proposal to embed BIM in an undergraduate civil engineering competency-based curriculum. Mixed method research was applied with a descriptive approach and a concurrent design. The results show that it is possible to implement a curricular design to embed BIM transversally. The study concludes that this design was embraced by the AECO industry, as the number of students, the number of employed graduates, and institutional national and international agreements have positively increased from 2017, at the launch of the program, to 2022.
Research on Horizontal Directional Drilling (HDD) Trajectory Design and Optimization Using Improved Radial Movement Optimization
Authors: Jin Liangxing , Wei Junjie
Published: November 2022

In practice, the drilling path of horizontal directional drilling (HDD) projects is usually constructed by trial and error based on a preliminary designing trajectory. This study aimed to propose and test a method to predesign and optimize the drilling paths automatically, with the view of improving the efficiency of HDD design preparations. Alternating straight and curvilinear segments is a commonly used method for designing drilling paths, especially the “straight—curvilinear—horizontal straight—curvilinear—straight” five-segment arrangement. The catenary method was proposed to design the drilling path with the advantage of lower friction for the mechanical constraints. However, it is difficult to be implemented with technology limitations due to its continuously changing curvature. In this study, five-segment trajectories were combined with the catenary trajectory to utilize their advantages using the improved radial movement optimization (IRMO) algorithm. Drilling mud pressure was considered in the processes of the mechanical design to avoid collapse or possible instability. Two different examples were tested in different scenarios, theoretical and practical. The results show that the IRMO algorithm has a great potential for automatically designing and optimizing preliminary drilling paths with low time-consumption and high feasibility.
Experimental Study of the Vibration of the Spot Welding Gun at a Robotic Station
Authors: Borys Szymon , Kaczmarek Wojciech , Laskowski Dariusz , Polak Rafał
Published: November 2022

The paper presents issues associated with the experimental study of the vibration of a spot welding gun mounted on a robotic arm. The main aim of the study was to assess the vibration of the robot flange and the vibration of the mounted tool. Because of the tools’ large size and weight (up to 150 kg), manipulating it in a limited space is a challenge for programmers when defining trajectories. The article presents the results of inertial measurements of the KUKA KR120 R2500 industrial robot equipped with a pneumatic welding tool, paying particular attention to the vibrations occurring at the process points. Inertial tests on the robotic station were made using triaxial accelerometers and a high-speed camera. The methodology developed by the authors confirmed the existence of structural vibrations and allowed for defining the relationship between the robot’s motion parameters (notably velocity and acceleration) and the size of the vibrations present. The paper presents selected test results for various parameters of robot motion (speeds from 2000 mm/s to 500 mm/s and acceleration ramps ranging from 100% to 25%). In the course of the study, a disturbance was noticed in the form of a reduction in the value of maximum acceleration. This could be attributed to the appearance of the structure’s natural vibrations. Their character is not constant, and they are damped.
Microbial Bioremediation and Biodegradation of Petroleum Products—A Mini Review
Authors: Adedeji Jeremiah A. , Tetteh Emmanuel Kweinor , Opoku Amankwa Mark , Asante-Sackey Dennis , Ofori-Frimpong Samuel , Armah Edward Kwaku , Rathilal Sudesh , Mohammadi Amir H. , Chetty Maggie
Published: November 2022

The demand for technological and industrial change has become heavily dependent on the availability and use of petroleum products as a source of energy for socio-economic development. Notwithstanding, petroleum and petrochemical products are strongly related to global economic activities, and their extensive distribution, refining processes, and final routes into the environment pose a threat to human health and the ecosystem. Additional global environmental challenges related to the toxicological impact of air, soil, and water pollutants from hydrocarbons are carcinogenic to animals and humans. Therefore, it is practical to introduce biodegradation as a biological catalyst to address the remediation of petroleum-contaminated ecosystems, adverse impacts, the complexity of hydrocarbons, and resistance to biodegradation. This review presents the bioremediation of petroleum hydrocarbon contaminants in water and soil, focusing on petroleum biodegradable microorganisms essential for the biodegradation of petroleum contaminants. Moreover, explore the mineralization and transformation of complex organic and inorganic contaminants into other simpler compounds by biological agents. In addition, physicochemical and biological factors affecting biodegradation mechanisms and enzymatic systems are expanded. Finally, recent studies on bioremediation techniques with economic prospects for petroleum spill remediation are highlighted.
Experimental Evaluation of Display Field Communication Based on Machine Learning and Modem Design
Authors: Kim Yu-Jeong , Singh Pankaj , Jung Sung-Yoon
Published: November 2022

Display field communication (DFC) is a frequency-domain unobtrusive display-to-camera (D2C) communication, in which an electronic display serves as a transmitter and a camera serves as a receiver. In this paper, we propose a machine learning-based DFC scheme and evaluate its performance in a lab test scenario. First of all, we adopt the Discrete Cosine Transform (DCT) to transform a spatial-domain image into its spectral-domain equivalent. To reduce the computational complexity during the data-embedding process, addition allocation and subtraction data retrieval techniques are used. Moreover, channel coding is applied to overcome the data error caused by the optical wireless channel. In particular, robust turbo coding is used for error detection and correction. Afterward, we perform the experiments to validate the performance of the proposed system. After capturing the displayed image with a camera, data restoration is done using a deep learning technique. Extensive real-world experiments were performed considering various geometric distortions, noise, and different standard input images. As a result, we found that by increasing the transmit display image size (upsampling), the overall error rate can be reduced. In addition, real-world noise analysis is performed and it is notified that the actual noise is dominant in the low-frequency region of an image. The experimental results confirm the robust performance of the proposed DFC scheme and show that an error-free performance can be achieved up to a distance of 1 m in the given lab test environment setting.
Study on the Effect of Insulation Materials on the Temperature Field of Piles in Ice-Rich Areas
Authors: Sheng Yingjie , Yu Tianlai , Wu Yuxuan , Wang Xingyu
Published: November 2022

Concrete piles in ice-rich areas exist in negative-temperature environments, which seriously affect the concrete’s strength. In order to maintain the quality of concrete piles in these areas, the temperature during the concrete strength formation period needs to be controlled. In this paper, the temperature field of the pile body of a test pile with double sheaths filled with polyurethane insulation and one without polyurethane insulation were measured. The temperature disturbance law of the pile base with/without insulation was obtained and comprehensively analyzed. The temperature of the pile body was shown to increase with the thickness of the insulation layer. Analysis of the thermal and physical properties of the insulation materials showed a linear relationship between pile temperature and thermal conductivity, in which a lower thermal conductivity resulted in a higher pile temperature. The effect of applying insulation around the pile perimeter in the ice-rich permafrost region on the concrete strength of the pile foundation was verified. The test pile with insulated double sheaths showed better strength at all ages than the test pile without insulation. The use of insulation maintained the temperature of pile foundations in ice-rich areas and ensured that the pile foundations were in better condition, thus improving the concrete strength at all ages. Adopting a double-sheathing configuration with polyurethane as an insulating layer can improve the concrete strength of the pile. This method is applicable to the ice-rich permafrost area in the Daxinganling Mountains and also has reference value for middle and low-latitude wetland permafrost areas.
A Fast Calculation of Partially Corroded, Grounding-Resistive Electrode Electrical Parameters
Authors: Denche Gregorio , Faleiro Eduardo , Asensio Gabriel , Moreno Jorge
Published: November 2022

The calculation of the grounding resistance of electrodes built with partially oxidized non-perfect conductors is addressed in this paper. A model based on circuit analysis to account for internal resistance is used, while the oxidation or partial coating of the conductor surface is modeled using the concept of the equivalent radius of the coated electrode. From the proposed model, the values of the electrical parameters of the grounding electrodes, such as the grounding resistance and the step and touch potentials, are calculated for real electrodes affected by coating or corrosion and compared with those values under ideal conditions. The results show significant differences in certain configurations that may compromise the safety margins established by current regulations.
Mechanical Performance of Polymer Materials for Low-Temperature Applications
Authors: Kim Yongjin , Kim Myung-Sung , Jeon Hyeon-Jong , Kim Jeong-Hyeon , Chun Kang Woo
Published: November 2022

The present study investigates the strain-rate-dependent mechanical performances of three different kinds of polymers in low-temperature applications, including plastic piping systems. Recently, lightweight constructions have been increasingly used in ship and offshore structures because using low-density materials reduces the structural weight of products. However, most of the existing research outcomes have not focused on low-temperature applications. In the present study, the mechanical and failure characteristics of acrylonitrile butadiene styrene (ABS), polyethylene (PE), and polyvinylidene fluoride (PVDF), which are the most widely used in ship and offshore industries, were tested under low-temperature conditions. The quasistatic tensile stress–strain responses of the polymers were observed at rates of 10−2, 10−3, and 10−4 s−1. As the temperature decreased, the tensile strength and Young’s modulus of tested polymers increased. The fracture strain and modulus of toughness of ABS were considerably lower than those of PE and PVDF at room and low temperatures. When compared with mechanical properties, PVDF displayed superior capability, and each polymer showed different fracture surface characteristics, such as ductility and brittleness. The quantitative material properties tested at various temperatures and strain-rates can be used as material information for the finite element (FE) analysis and material parameters for the development of advanced constitutive models.
Gamification of Upper Limb Rehabilitation in Mixed-Reality Environment
Authors: Pillai Aditya , Sunny Md Samiul Haque , Shahria Md Tanzil , Banik Nayan , Rahman Mohammad Habibur
Published: November 2022

The advancements in mixed reality (MR) technology in recent years have provided us with excellent prospects for creating novel approaches to supplement conventional physiotherapy to maintain a sufficient quantity and quality of rehabilitation. The use of MR systems to facilitate patients’ participation in intensive, repetitive, and task-oriented practice using cutting-edge technologies to enhance functionality and facilitate recovery is very encouraging. Multiple studies have found that patients who undergo therapy using MR experience significant improvements in upper limb function; however, assessing the efficacy of MR is challenging due to the wide variety of methods and tools used. Because of these challenges, a novel approach, gamified MR-based solution for upper extremity rehabilitation, is proposed, which is an MR application for the Microsoft HoloLens 2, complete with game levels, and can measure the ranges of motion of the arm joints. The proposed rehabilitative system’s functionality and usability were evaluated with ten healthy adult participants with no prior arm-related injuries and two occupational therapists (OTs). The system successfully provided rehab exercises for upper limb injuries through interactive mixed-reality games. The system can mimic upper limb behavior without additional sensors during rehab sessions. Unlike previously researched technologically-based rehabilitation methods, this method can integrate arm–joint data within the application and are independent of one another. The results and comparisons show that this system is relevant, accurate, and superior to previous VR-based rehabilitation methods because the VR-based system is blind to the surroundings, whereas the proposed approach has spatial awareness of the environment.
Investigation of the Behaviors of Methanol Spray Impingement and Wall Wetting
Authors: Zhang Ya-Jie , Wei Yan-Ju , Jamil Huzaifa , Liu Sheng-Hua
Published: November 2022

Port fuel injection is an important technical route in methanol engines. To obtain a theoretical basis for injector arrangement and injection strategy development in methanol engines, an optimal experimental platform based on diffuse back-illumination and the refractive index matching method (RIM) was designed and built in this study. The experiments on the behavior of low-pressure methanol spray-wall impingement and wall film were carried out and the influence of the three boundary conditions of spray distance (Dimp), wall temperature (Twall), and injection pressure (Pinj) were analyzed comprehensively. Results showed that with the increase of Dimp, the overall shape of spray before impinging the wall changed from conical to cylindrical. The impinging spray height Hi and impinging spray width Wi increased with the decrease of Dimp and the increase of Pinj. Adhesive fuel film mass Mf increased with the increase of Dimp due to the decrease of kinetic energy during wall impact. In addition, the increase of the wall temperature Twall reduced Mf due to evaporation, but when Twall reached 423 K, Mf rebounded due to the Leidenfrost effect. The results of this study are helpful to improve the accuracy of the numerical methanol engine model.
Estimation of Postal Service Delivery Time and Energy Cost with E-Scooter by Machine Learning Algorithms
Authors: İnaç Hakan , Ayözen Yunus Emre , Atalan Abdulkadir , Dönmez Cem Çağrı
Published: November 2022

This research aims to estimate the delivery time and energy cost of e-scooter vehicles for distributing mail or packages and to show the usage efficiency of e-scooter sharing services in postal service delivery in Turkey. The machine learning (ML) methods used to implement the prediction of delivery time and energy cost as output variables include random forest (RF), gradient boosting (GB), k-nearest neighbour (kNN), and neural network (NN) algorithms. Fifteen input variables under demographic, environmental, geographical, time, and meta-features are utilised in the ML algorithms. The correlation coefficient (R2) values of RF, GB, NN, and kNN algorithms were computed for delivery time as 0.816, 0.845, 0.821, and 0.786, respectively. The GB algorithm, which has a high R2 and the slightest margin of error, exhibited the best prediction performance for delivery time and energy cost. Regarding delivery time, the GB algorithm’s MSE, RMSE, and MAE values were calculated as 149.32, 12.22, and 6.08, respectively. The R2 values of RF, GB, NN, and kNN algorithms were computed for energy cost as 0.917, 0.953, 0.400, and 0.365, respectively. The MSE, RMSE, and MAE values of the GB algorithm were calculated as 0.001, 0.019, and 0.009, respectively. The average energy cost to complete a package or mail delivery process with e-scooter vehicles is calculated as 0.125 TL, and the required time is approximately computed as 11.21 min. The scientific innovation of the study shows that e-scooter delivery vehicles are better for the environment, cost, and energy than traditional delivery vehicles. At the same time, using e-scooters as the preferred way to deliver packages or mail has shown how well the delivery service works. Because of this, the results of this study will help in the development of ways to make the use of e-scooters in delivery service even more efficient.
The Importance of Robust Datasets to Assess Urban Accessibility: A Comparable Study in the Distrito Tec, Monterrey, Mexico, and the Stanford District, San Francisco Bay Area, USA
Authors: Rodríguez-Hernández Karen Lizette , Narezo-Balzaretti Jorge , Gaxiola-Beltrán Ana Luisa , Ramírez-Moreno Mauricio Adolfo , Pérez-Henríquez Blas Luis , Ramírez-Mendoza Ricardo Ambrocio , Krajzewicz Daniel , Lozoya-Santos Jorge de-Jesús
Published: November 2022

Urban planning has a crucial role in helping cities meet the United Nations’ Sustainable Development Goals and robust datasets to assess mobility accessibility are central to smart urban planning. These datasets provide the information necessary to perform detailed analyses that help develop targeted urban interventions that increase accessibility in cities as related to the emerging vision of the 15 Minute City. This study discusses the need for such data by performing a comparative urban accessibility analysis of two university campuses and their surrounding urban areas, here defined as the Stanford District, located in the San Francisco Bay Area in the United States, and Distrito Tec in Monterrey, Mexico. The open-source tool Urban Mobility Accessibility Computer (UrMoAC) is used to assess accessibility measures in each district using available data. UrMoAC calculates distances and average travel times from block groups to major destinations using different transport modes considering the morphology of the city, which makes this study transferable and scalable. The results show that both areas have medium levels of accessibility if cycling is used as the primary mode of transportation. Hence, improving the safety and quality of cycling in both cities emerges as one of the main recommendations from the research. Finally, the results obtained can be used to generate public policies that address the specific needs of each community’s urban region based on their accessibility performance.
Dynamic Modeling and Nonlinear Analysis of a Spur Gear System Considering a Nonuniformly Distributed Meshing Force
Authors: Jin Bohan , Bian Yushu , Liu Xihui , Gao Zhihui
Published: November 2022

In previous studies, the meshing force of a gear system is usually treated as being uniformly distributed for the convenience of analysis. In practical applications, however, it is nonuniformly distributed along the line of action due to machining errors, assembly errors, misalignment errors, etc. When a nonuniformly distributed meshing force is coupled with the shaft deformation, dynamic center distance, and time-varying meshing stiffness, the transmission performance of the gear system will be seriously degraded. Therefore, a nonuniformly distributed meshing force cannot be ignored when considering the gear systems used in complicated working conditions. In this study, the gear’s nonuniformly distributed meshing force is analyzed. Then, an 18 degrees-of-freedom bending-torsion-swing-coupled dynamic model of a pair of involute spur gears is put forward. Through this model, the coupling relationship between the nonuniformly distributed meshing force, shaft bending deformation, and dynamic center distance is accurately described. The influence of meshing frequency, stiffness excitation, damping, and error excitation on the nonlinear dynamic characteristics of the gear system was researched through bifurcation diagrams, phase diagrams, Poincaré maps, and time-domain diagrams. Various complicated nonlinear dynamic behaviors, such as quasiperiodic motion, bifurcation, chaotic motion, and chaotic banding, are revealed. Reasonable parameter ranges that guarantee the gear system is in a stable motion were extracted. By evading complicated nonlinear dynamic behavior, the transmission performance of a gear system was improved. This research will contribute to reducing the vibration and noise of gear systems.
Enhanced Firefly-K-Means Clustering with Adaptive Mutation and Central Limit Theorem for Automatic Clustering of High-Dimensional Datasets
Authors: Ikotun Abiodun M. , Ezugwu Absalom E.
Published: November 2022

Metaheuristic algorithms have been hybridized with the standard K-means to address the latter’s challenges in finding a solution to automatic clustering problems. However, the distance calculations required in the standard K-means phase of the hybrid clustering algorithms increase as the number of clusters increases, and the associated computational cost rises in proportion to the dataset dimensionality. The use of the standard K-means algorithm in the metaheuristic-based K-means hybrid algorithm for the automatic clustering of high-dimensional real-world datasets poses a great challenge to the clustering performance of the resultant hybrid algorithms in terms of computational cost. Reducing the computation time required in the K-means phase of the hybrid algorithm for the automatic clustering of high-dimensional datasets will inevitably reduce the algorithm’s complexity. In this paper, a preprocessing phase is introduced into the K-means phase of an improved firefly-based K-means hybrid algorithm using the concept of the central limit theorem to partition the high-dimensional dataset into subgroups of randomly formed subsets on which the K-means algorithm is applied to obtain representative cluster centers for the final clustering procedure. The enhanced firefly algorithm (FA) is hybridized with the CLT-based K-means algorithm to automatically determine the optimum number of cluster centroids and generate corresponding optimum initial cluster centroids for the K-means algorithm to achieve optimal global convergence. Twenty high-dimensional datasets from the UCI machine learning repository are used to investigate the performance of the proposed algorithm. The empirical results indicate that the hybrid FA-K-means clustering method demonstrates statistically significant superiority in the employed performance measures and reducing computation time cost for clustering high-dimensional dataset problems, compared to other advanced hybrid search variants.
Cinema Divina and Autotheory: An Interview with Marilyn Freeman
Authors: Freeman Marilyn , Auburn Cat
Published: November 2022

This is an interview with moving image artist, writer, and contemplative practitioner, Marilyn (M) Freeman by artist, Cat Auburn. They explore Freeman’s contemplative filmmaking practice, ‘Cinema Divina’ and the relationship of Freeman’s life, artistic practice and research interests to autotheory. Autotheory is widely held to be the coalescence of autobiography with theory (or philosophy) within a work of art or literature, often with an aim towards offering social or cultural narration and service. The impulse to collaborate on this interview came from Auburn’s encounter with Cinema Divina during an online group contemplative session facilitated by Freeman in February 2022. This interview covers Freeman’s development of Cinema Divina, such topics as Freeman’s theory of Vertical Dissonance, the risks of working autotheoretically, mysticism, interior life, the hierarchies of knowledge production and the potential for what Freeman calls ‘the illuminated space’ to create radical opportunities for personal transformation. Ultimately, this interview establishes that Cinema Divina can be seen as an autotheoretical practice that uses contemplative practices rooted in lectio divina, a meditative prayer ritual of early Benedictine monastics, to theorize through Freeman’s embodied, lived experiences and artistic outcomes.
Internet Traffic Prediction with Distributed Multi-Agent Learning
Authors: Jiang Weiwei , He Miao , Gu Weixi
Published: November 2022

Internet traffic prediction has been considered a research topic and the basis for intelligent network management and planning, e.g., elastic network service provision and content delivery optimization. Various methods have been proposed in the literature for Internet traffic prediction, including statistical, machine learning and deep learning methods. However, most of the existing approaches are trained and deployed in a centralized approach, without considering the realistic scenario in which multiple parties are concerned about the prediction process and the prediction model can be trained in a distributed approach. In this study, a distributed multi-agent learning framework is proposed to fill the research gap and predict Internet traffic in a distributed approach, in which each agent trains a base prediction model and the individual models are further aggregated with the cooperative interaction process. In the numerical experiments, two sophisticated deep learning models are chosen as the base prediction model, namely, long short-term memory (LSTM) and gated recurrent unit (GRU). The numerical experiments demonstrate that the GRU model trained with five agents achieves state-of-the-art performance on a real-world Internet traffic dataset collected in a campus backbone network in terms of root mean square error (RMSE) and mean absolute error (MAE).
Air Pollution and Tear Lactoferrin among Dry Eye Disease Modifications by Stress and Allergy: A Case–Control Study of Taxi Drivers
Authors: Hao Wei , Kong Fanxue , Song Wei , Zhang Lei , Xu Xueying , Ren Zhongjuan , Li Jing , Yu Fei
Published: November 2022

Few studies have explored the possible associations between air pollution and tear lactoferrin (Lf) levels, a non-invasive biological marker of ocular surface diseases, among taxi drivers, while none have explored the modifications by stress and allergic tendencies in the relationship. We recruited 1905 taxi drivers with dry eye disease (DED) and 3803 non-DED controls in Liaoning, China, in 2012–2014. After physical examination and questionnaires were recorded, ocular surface was measured and tear Lf was determined by electrophoresis. Air pollutants and humidity were estimated by measured concentrations from monitoring stations. Conditional logistic regression models were employed to examine the associations of air pollutants and humidity with tear Lf levels. Among taxi drivers with stress or allergic tendencies, an IQR (26 μg/m3, 10 μg/m3) increase in PM10 and NO2 levels elevated the adjusted odds ratio by 1.89 (95% CI, 1.19 to 3.08) or 1.77 (95% CI, 1.06 to 2.90); and 2.87 (95% CI, 1.60 to 3.58) or 2.93 (95% CI, 1.64 to 3.83), respectively. In contrast, humidity was inversely associated for taxi drivers with stress [0.51 (95% CI, 0.38 to 0.64)] or allergic tendencies [0.49 (95% CI, 0.11 to 0.84)]; and for taxi drivers without stress [0.33 (95% CI: 0.17, 0.39)] or without allergic tendencies [0.39 (95% CI, 0.19 to 0.59)]. Tear Lf was negatively associated with each quartile of PM10 or NO2 exposure, and low humidity. PM10, NO2, and low humidity were inversely associated with Lf levels, especially for DED taxi drivers with stress and allergic tendencies.
Overview of Radon Flux Characteristics, Measurements, Models and Its Potential Use for the Estimation of Radon Priority Areas
Authors: Čeliković Igor , Pantelić Gordana , Vukanac Ivana , Nikolić Jelena Krneta , Živanović Miloš , Cinelli Giorgia , Gruber Valeria , Baumann Sebastian , Ciotoli Giancarlo , Poncela Luis Santiago Quindos , Rábago Daniel
Published: November 2022

Radon flux measurements provide information about how much radon rises from the ground toward the atmosphere, thus, they could serve as good predictors of indoor radon concentrations. Although there are many different mapping methods with many different input data, radon flux data are generally missing and are not included for the delineation of radon priority areas (RPA). The aim of this literature review is to investigate to what extent radon flux was used, or could be used, for the delineation of RPAs. Numerous factors influencing radon flux were identified, but quantifying their contribution to radon flux measurement still remains a challenge. Different methods and measuring devices were used for the determination of radon flux, thus it is necessary to identify possible inconsistencies in order to harmonise different radon flux measurements. Due to the complexity of radon flux measurements, only two countries were identified to have performed national surveys on outdoor radon, which were of much smaller scale compared to those on indoor radon. A positive correlation between radon flux and radon quantities, such as radon in soil gas and indoor radon, indicates that radon flux could be used as an input parameter for the estimation of RPA. By reviewing radon flux models, it was concluded that up-to-date modelled radon flux maps have reached excellent spatial resolution and will be further improved, hence, they could serve as an input for the estimation and delineation of RPA.
Establishment of Crop Water Stress Index for Sustainable Wheat Production under Climate Change in a Semi-Arid Region of Pakistan
Authors: Khan Muhammad Imran , Saddique Qaisar , Zhu Xingye , Ali Sikandar , Ajaz Ali , Zaman Muhammad , Saddique Naeem , Buttar Noman Ali , Arshad Rao Husnain , Sarwar Abid
Published: November 2022

The Crop Water Stress Index (CWSI) is a useful tool for evaluating irrigation scheduling and achieving water conservation and crop yield goals. This study examined the CWSI under different water stress conditions for the scheduling of wheat crop irrigation and developed indices using the leaf canopy temperature in Faisalabad, Pakistan. The experiments were conducted using a randomized, complete block design and four irrigation treatments with deficit levels of D0%, D20%, and D40% from the field capacity (FC) and D100% (100% deficit level). The CWSI was determined at pre-heading and post-heading stages through the lower baseline (fully watered crop) and upper limit (maximum stress). These baselines were computed using the air temperature and canopy temperature of plant leaves and the vapor pressure deficit (VPD). The CWSI for each irrigation treatment was calculated and the average seasonal CWSI value for the whole season was used to develop the empirical relationships for scheduling irrigation. The relationships between the air canopy temperatures and the VPD resulted in slope (x) = −0.735 and interception (c) = −0.8731 as well as x = −0.5143 and c = −1.273 at the pre- and post-heading stages, respectively. The values of the CWSI for the treatment at deficit levels of D0%, D20%, D40%, and D100% were found to be 0.08, 0.61, 0.20, and 0.64, respectively. The CWSI values developed in this study can be effectively used to promote better the monitoring of irrigated wheat crops in the region.
Emulation of a Chemical Transport Model to Assess Air Quality under Future Emission Scenarios for the Southwest of Western Australia
Authors: Vander Hoorn Stephen , Johnson Jill S. , Murray Kevin , Smit Robin , Heyworth Jane , Lam Sean , Cope Martin
Published: November 2022

Simulation outputs from chemical transport models (CTMs) are essential to plan effective air quality policies. A key strength of these models is their ability to separate out source-specific components which facilitate the simulation of the potential impact of policy on future air quality. However, configuring and running these models is complex and computationally intensive, making the evaluation of multiple scenarios less accessible to many researchers and policy experts. The aim of this work is to present how Gaussian process emulation can provide a top-down approach to interrogating and interpreting the outputs from CTMs at minimal computational cost. A case study is presented (based on fine particle sources in the southwest of Western Australia) to illustrate how an emulator can be constructed to simultaneously evaluate changes in emissions from on-road transport and electricity sectors. This study demonstrates how emulation provides a flexible way of exploring local impacts of electric vehicles and wider regional effects of emissions from electricity generation. The potential for emulators to be applied to other settings involving air quality research is discussed.
Some Properties of Bazilevič Functions Involving Srivastava–Tomovski Operator
Authors: Breaz Daniel , Karthikeyan Kadhavoor R. , Umadevi Elangho , Senguttuvan Alagiriswamy
Published: November 2022

We introduce a new class of Bazilevič functions involving the Srivastava–Tomovski generalization of the Mittag-Leffler function. The family of functions introduced here is superordinated by a conic domain, which is impacted by the Janowski function. We obtain coefficient estimates and subordination conditions for starlikeness and Fekete–Szegö functional for functions belonging to the class.
Surgical Gesture Recognition in Laparoscopic Tasks Based on the Transformer Network and Self-Supervised Learning
Authors: Gazis Athanasios , Karaiskos Pantelis , Loukas Constantinos
Published: November 2022

In this study, we propose a deep learning framework and a self-supervision scheme for video-based surgical gesture recognition. The proposed framework is modular. First, a 3D convolutional network extracts feature vectors from video clips for encoding spatial and short-term temporal features. Second, the feature vectors are fed into a transformer network for capturing long-term temporal dependencies. Two main models are proposed, based on the backbone framework: C3DTrans (supervised) and SSC3DTrans (self-supervised). The dataset consisted of 80 videos from two basic laparoscopic tasks: peg transfer (PT) and knot tying (KT). To examine the potential of self-supervision, the models were trained on 60% and 100% of the annotated dataset. In addition, the best-performing model was evaluated on the JIGSAWS robotic surgery dataset. The best model (C3DTrans) achieves an accuracy of 88.0%, a 95.2% clip level, and 97.5% and 97.9% (gesture level), for PT and KT, respectively. The SSC3DTrans performed similar to C3DTrans when training on 60% of the annotated dataset (about 84% and 93% clip-level accuracies for PT and KT, respectively). The performance of C3DTrans on JIGSAWS was close to 76% accuracy, which was similar to or higher than prior techniques based on a single video stream, no additional video training, and online processing.
Application of Extracellular Vesicles in Gynecologic Cancer Treatment
Authors: Zhang Renwen , Zou Yixing , Luo Jing
Published: November 2022

Ovarian, cervical, and endometrial cancer are the three most common gynecological malignancies that seriously threaten women’s health. With the development of molecular biology technology, immunotherapy and targeted therapy for gynecologic tumors are being carried out in clinical treatment. Extracellular vesicles are nanosized; they exist in various body fluids and play an essential role in intercellular communication and in the regulation of various biological process. Several studies have shown that extracellular vesicles are important targets in gynecologic cancer treatment as they promote tumor growth, progression, angiogenesis, metastasis, chemoresistance, and immune system escape. This article reviews the progress of research into extracellular vesicles in common gynecologic tumors and discusses the role of extracellular vesicles in gynecologic tumor treatment.
Morphological Changes of Glial Lamina Cribrosa of Rats Suffering from Chronic High Intraocular Pressure
Authors: Zhang Jingxi , Liu Yushu , Liu Liu , Li Lin , Qian Xiuqing
Published: November 2022

Deformations or remodeling of the lamina cribrosa (LC) induced by elevated intraocular pressure (IOP) are associated with optic nerve injury. The quantitative analysis of the morphology changes of the LC will provide the basis for the study of the pathogenesis of glaucoma. After the chronic high-IOP rat model was induced by cauterizing episcleral veins with 5-Fluorouracil subconjunctival injection, the optic nerve head (ONH) cross sections were immunohistochemically stained at 2 w, 4 w, 8 w, and 12 w. Then the sections were imaged by a confocal microscope, and six morphological parameters of the ONH were calculated after the images were processed using Matlab. The results showed that the morphology of the ONH changed with the duration of chronic high IOP. The glial LC pore area fraction, the ratio of glial LC pore area to the glial LC tissue area, first decreased at 2 w and 4 w and then increased to the same level as the control group at 8 w and continued to increase until 12 w. The number and density of nuclei increased significantly at 8 w in the glial LC region. The results might mean the fraction of glial LC beam increased and astrocytes proliferated at the early stage of high IOP. Combined with the images of the ONH, the results showed the glial LC was damaged with the duration of chronic elevated IOP.