bluuebunny/crossref_metadata_2025 huggingface dataset:
Serum Protein Concentration and Serum Protein Fractions in Bottlenose Dolphins (Tursiops truncatus) under Human Care Using Agarose Gel Electrophoresis
Authors: Bonsembiante Federico , Giordano Alessia , Gili Claudia , Mazzariol Sandro , Berlanda Michele , Guglielmini Carlo , Bedin Silvia , Gelain Maria Elena
Published: May 2023

Serum protein electrophoresis (SPE) is the most used and reliable method to determine the percentage of serum protein subfractions. The interpretation of the kinetics of total proteins and albumin and globulin fractions is receiving increased attention in wild animals, as well as in domestic animals, due to the possibility of identifying typical pathologic patterns. However, the interpretation of these data had to be performed in light of an appropriate method—and species- specific reference intervals (RIs). In marine mammals, as well as other non-domestic species, specific attention should also be given to the different environment (free ranging vs. human managed) and the associated different exposure to environmental stimuli. The aim of this report was to establish RIs for the serum protein fractions evaluated using agarose gel electrophoresis (AGE) in bottlenose dolphins under human care. Peripheral blood samples were collected from 40 bottlenose dolphins during standard veterinary procedures to evaluate their health status. Total protein concentration was determined using the biuret method while AGE was performed using an automated system. A pooled dolphin’s serum sample was used to determine the intra-assay and inter-assay imprecision of AGE. The RIs were calculated using an Excel spreadsheet with the Reference Value Advisor set of macroinstructions. The intra and inter-assay imprecisions were 1.2% and 2.5%, respectively, for albumin; 2.9% and 5.7%, respectively, for α-globulins; 3.8% and 4.0%, respectively, for β-globulins; and 3.4% and 4.8%, respectively, for γ-globulins. The total protein, albumin, α-globulin, β-globulin, and γ-globulin concentrations were 65.5 ± 5.4 g/L, 45.5 ± 4.9 g/L, 8.0 ± 1.0 g/L, 5.0 ± 2.0 g/L, and 7.0 ± 2.0 g/L, respectively. We established the RIs for the total protein and serum protein fractions using AGE in bottlenose dolphins under human care.
Chronic Heat Stress Part 2: Increased Stress and Fear Responses in F1 Pekin Ducks Raised from Parents That Experienced Heat Stress
Authors: Oluwagbenga Esther Mary , Tetel Victoria , Schober Jenna , Fraley Gregory S.
Published: May 2023

The effects of HS on the welfare of poultry have been reported to have a transgenerational effect on phenotype plasticity. The goal of our experiment was to determine whether parental exposure to HS would impair the performance, HPA axis response, or behavior of their offspring. We treated adult drakes and hens (n = 80 ducks/treatment) at peak lay with HS or the control temperature for 3 weeks and incubated eggs collected from the last 3 days of the experiment. We utilized 76 ducklings/parental treatment group: control (CON-F1) and HS (HS-F1). Weekly data for body weights, body condition scores (BCSs), and novel object test (NOT) were collected. At 3 weeks of age, the ducks (n = 6/treatment) were subjected to adrenocorticotropic hormone (ACTH/cosyntropin, 0.0625 mg/kg) challenge or vehicle as the control. Blood samples were collected at 0, 1, 2, 3, and 4 h relative to treatment for serum glucocorticoid and heterophil-to-lymphocyte ratio (HLR) analyses. All injected birds were euthanized with pentobarbital on the second day relative to ACTH administration, and the spleen and bursa were removed and weighed immediately. Duck level analyses were completed using one- or two-way ANOVA as appropriate. BCSs were analyzed using a chi-squared test. The HS-F1 ducks had a lower hatch weight (p < 0.05) compared with the CON-F1 ducks but no significant difference in growth rates during the 5-week period. NOT (n = 4) analyses showed that the HS-F1 ducks had a greater fear response (p < 0.001) compared with the CON-F1 ducks. Similarly, an ACTH stimulation test showed that the HS-F1 ducks had significantly (p < 0.05) heightened corticosterone and HLR responses compared with the CON-F1 ducks. The HS-F1 ducks showed altered baseline and ACTH-stimulated levels of cortisol compared with the controls. Our data suggest that parental exposure to HS impacts the HPA response and fearfulness of the F1 generation in Pekin ducks.
Development and Recovery of Liver Injury in Piglets by Incremental Injection of LPS
Authors: Duan Geyan , Huang Pan , Zheng Changbing , Zheng Jie , Yu Jiayi , Zhang Peiwen , Wan Mengliao , Li Fengna , Guo Qiuping , Yin Yulong , Duan Yehui
Published: May 2023

This study aimed to explore the effects of the incremental injection of lipopolysaccharide (LPS) on liver histopathology, inflammation, oxidative status, and mitochondrial function in piglets. Forty healthy Duroc × Landrace × Yorkshire castrated boars (21 ± 2 days old, weight 6.84 ± 0.11 kg) were randomly assigned to five groups (n = 8) and then slaughtered on days 0 (group 0, without LPS injection), 1 (group 1), 5 (group 5), 9 (group 9), and 15 (group 15) of LPS injection, respectively. The results showed that, compared to the piglets without LPS injection, LPS injection caused liver injury in the early phase, as manifested by the increased activities of serum liver injury-related parameters (aspartate amino transferase, alanine aminotransferase, alkaline phosphatase, cholinesterase, and total bile acid) on day 1, and impaired liver morphology (disordered hepatic cell cord arrangement, dissolved and vacuolized hepatocytes, karyopycnosis, and inflammatory cell infiltration and congestion) on days 1 and 5. Meanwhile, LPS injection caused liver inflammation, oxidative stress, and mitochondrial dysfunction on days 1 and 5, as reflected by the upregulated mRNA expression of TNF-α, IL-6, IL-1β, TLR4, MyD88, and NF-κB; increased MPO and MDA content; and impaired mitochondrial morphology. However, these parameters were ameliorated in the later phase (days 9~15). Taken together, our data indicate that the incremental injection of the LPS-induced liver injury of piglets could be self-repaired.
Potential of Dry-Cured Ham Bones as a Sustainable Source to Obtain Antioxidant and DPP-IV Inhibitory Extracts
Authors: Carrera-Alvarado Gisela , Toldrá Fidel , Mora Leticia
Published: May 2023

The utilization of animal bones as a protein source could be used as a sustainable pathway for the production of bioactive compounds. In this study, bones were pretreated with pepsin enzyme (PEP) and then sequentially hydrolyzed with Alcalase (PA) and Alcalase, as well as Protana prime (PAPP). The degree of hydrolysis, antioxidant activity, and DPP-IV inhibitory activity were measured. All three hydrolysates showed antioxidant and DPP-IV inhibitory activity; however, the highest result in both bioactivities was obtained with the PAPP hydrolysate. The obtained free amino acid content was 54.62, 88.12, and 668.46 mg/100 mL of hydrolyzed in PEP, PA, and PAPP, respectively. Pepsin pretreatment did not significantly affect the degree of hydrolysis; however, it is suggested that it promoted the cleavage of certain bonds for subsequent protease action. Accordingly, a total of 550 peptides were identified in PEP hydrolysate, 1087 in PA hydrolysate, and 1124 in PAPP hydrolysate using an LC-MS/MS approach. Pepsin pretreatment could be an effective method in the utilization of bone sources for the production of antioxidant and hypoglycemic peptides.
Extended Fuzzy-Based Models of Production Data Analysis within AI-Based Industry 4.0 Paradigm
Authors: Rojek Izabela , Prokopowicz Piotr , Kotlarz Piotr , Mikołajewski Dariusz
Published: May 2023

Fast, accurate, and efficient analysis of production data is a key element of the Industry 4.0 paradigm. This applies not only to newly built solutions but also to the digitalization, automation, and robotization of existing factories and production or repair lines. In particular, technologists’ extensive experience and know-how are necessary to design correct technological processes to minimize losses during production and product costs. That is why the proper selection of tools, machine tools, and production parameters during the manufacturing process is so important. Properly developed technology affects the entire production process. This paper presents an attempt to develop a post-hoc model of already existing manufacturing processes with the increased requirements and expectations resulting from the introduction of the Industry 4.0 paradigm. In particular, we relied on fuzzy logic to support the description of uncertainties, incomplete data, and discontinuities in the manufacturing process. This translates into better controls compared to conventional systems. An analysis of the proposed solution’s limitations and proposals for further development constitute the novelty and contribution of the article.
Scene Reconstruction Algorithm for Unstructured Weak-Texture Regions Based on Stereo Vision
Authors: Chen Mingju , Duan Zhengxu , Lan Zhongxiao , Yi Sihang
Published: May 2023

At present, Chinese 3D reconstruction solutions using stereo cameras mainly face known, indoor, structured scenes; for the reconstruction of unstructured, larger-scale scenes with a large variety of texture information of different intensities, there are certain difficulties in ensuring accuracy and real-time processing. For the above problems, we propose a scene reconstruction method using stereo vision. Firstly, considering the influence of outdoor lighting and weather on the captured 2D images, the optimized SAD-FAST feature detection algorithm and stereo-matching strategy were employed in the stereo-matching stage to improve the overall efficiency and matching quality at this stage. Then, a homogenized feature extraction algorithm with gradient value decreasing step by step (GVDS) was used in the depth value calculation to ensure a sufficient number of feature points for strong texture information while extracting features from weak-texture areas, which greatly improved the quality and speed of unstructured scene reconstruction. We conducted experiments to validate the proposed method, and the results showed the feasibility of the proposed method and its high practical value.
On the Cycle Stability and Macroscopic Structure of Iron Oxide Pellets for Thermochemical Hydrogen Storage: Influence of Water Content during the Pelletizing Process
Authors: Huber Lea , Heindl Melanie , Schlosser Marc , Pfitzner Arno , Dawoud Belal
Published: May 2023

Hydrogen storage based on the repeated reduction and oxidation (redox) reactions of iron oxide/iron composites represents a promising technology. This work is dedicated to studying the influence of the amount of water added during the pelletizing process on the cycle stability and structure of iron oxide pellets. The storage composites were prepared from iron oxide (Fe2O3) and 10 wt.-% support material (cement) with different amounts of water (18 and 33 wt.-%) in a laboratory-scale pelletizing disk. To evaluate the cycle stability of the composites, the kinetics of the redox reactions were experimentally measured at 800 °C in an atmosphere of 50% N2 and 50% H2 (reduction) or 50% steam (oxidation), respectively. Moreover, the structure of the pellets was analyzed by micro-computed tomography scans. It turned out that pellets with higher water contents attained faster kinetics and a higher cycle stability. The sample with the least water content (18 wt.-%) needed about 26 min and 19 min to reach a conversion rate of 80% during the reduction and oxidation reactions of the sixth redox cycle, respectively. In contrast, the sample with the highest water content (33 wt.-%) could achieve the same conversion rate after 18 min (reduction) and 13 min (oxidation) during the ninth redox cycle.
Fast and Accurate Facial Expression Image Classification and Regression Method Based on Knowledge Distillation
Authors: Lee Kunyoung , Kim Seunghyun , Lee Eui Chul
Published: May 2023

As emotional states are diverse, simply classifying them through discrete facial expressions has its limitations. Therefore, to create a facial expression recognition system for practical applications, not only must facial expressions be classified, emotional changes must be measured as continuous values. Based on the knowledge distillation structure and the teacher-bounded loss function, we propose a method to maximize the synergistic effect of jointly learning discrete and continuous emotional states of eight expression classes, valences, and arousal levels. The proposed knowledge distillation model uses Emonet, a state-of-the-art continuous estimation method, as the teacher model, and uses a lightweight network as the student model. It was confirmed that performance degradation can be minimized even though student models have multiply-accumulate operations of approximately 3.9 G and 0.3 G when using EfficientFormer and MobileNetV2, respectively, which is much less than the amount of computation required by the teacher model (16.99 G). Together with the significant improvements in computational efficiency (by 4.35 and 56.63 times using EfficientFormer and MobileNetV2, respectively), the decreases in facial expression classification accuracy were approximately 1.35% and 1.64%, respectively. Therefore, the proposed method is optimized for application-level interaction systems in terms of both the amount of computation required and the accuracy.
Magnetic Properties of Gd-Doped Fe3O4 Nanoparticles
Authors: Apostolova Iliana , Apostolov Angel , Wesselinowa Julia
Published: May 2023

The magnetic properties of pure and rare earth ion-doped Fe3O4 nanoparticles are investigated using a microscopic model and the Green’s function theory. The magnetization Ms and Curie temperature TC are calculated depending on size, temperature and Gd doping concentration. Ms and TC decrease with decreasing nanoparticle size and with increasing the doping concentration. The band gap energy increases with decreasing size and Gd dopants. The obtained results are in good agreement with the experimental data.
Time-Series InSAR Deformation Monitoring of High Fill Characteristic Canal of South–North Water Diversion Project in China
Authors: Liu Hui , Zhao Wenfei , Qin Zhen , Wang Tiesheng , Li Geshuang , Zhu Mengyuan
Published: May 2023

The Middle Route of the South–North Water Diversion Project has changed the water resources pattern in China. As advanced equipment for the country, it is responsible for the water supply “lifeline” of Beijing, Tianjin, Hebei, Henan, etc. Ensuring its safe operation is a top priority to promote social stability and coordinated economic development between the North and the South. Used persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technology to monitor the deformation of the high fill characteristic canal in Wenzhuang Village, Ye County, during the period from October 2016 to June 2017 for the South–North Water Diversion Project showed that there was significant deformation on the 1 km-long slope of the east bank of the canal, with the maximum deformation volume reaching 36 mm. Through the comparison and verification with the second order leveling data, there are more than 87% of the root mean square error of both less than ±2 mm. The correlation coefficient is 0.96, and the two were highly consistent in deformation trends and values. Through the vertical and cross-sectional analysis of the canal’s east bank and four key monitoring sections, it was found that the east bank of the canal presents overall uneven subsidence, and the closer the canal is to the water, the greater the canal deformation, and vice versa. Further comparison of the PS-InSAR deformation results of the canal from October 2016 to February 2018 proves that this technology cannot only monitor the subsidence range and rate of the South–North Water Diversion canal but also accurately identify the subsidence sequence of the east and west banks. It can provide reliable technical support for the safety monitoring and disaster prevention of the South–North Water Diversion canal characterized by high fill and deep excavation.
Mutual-Inductance Computation between Coaxial Thin Conical Sheet Inductor and the Circular Loop in Air
Authors: Babic Slobodan
Published: May 2023

The paper describes a new formula for calculating the mutual inductance between a thin conical sheet inductor and a filamentary circular loop, which are coaxial in air. The presented formula is derived semi-analytically using the complete elliptic integrals of the first, second, and third kind, along with the integral term which will be solved numerically. The results are validated using double and single integration methods, as well as the semi-analytical formula. The mutual inductance between a thin cylindrical solenoid and a filamentary circular loop can be obtained using the new formula for the conical coil and circular loop. Presented formulas can be useful in various applications, such as the excitation coil used in electromagnetic-levitation melting, the production of magnetic field homogeneity and broadband RF and wireless power transfer systems that utilize conical inductors. Overall, the paper presents a valuable contribution to the field of inductor design and can be useful in various applications involving conical inductors.
Forest Plantations in Manabí (Ecuador): Assessment of Fragmentation and Connectivity to Support Dry Tropical Forests Conservation
Authors: Quimis Gómez Alex J. , Rivas Carlos A. , González-Moreno Pablo , Navarro-Cerrillo Rafael M.
Published: May 2023

In many tropical regions, national forests plantation programs have been promoted. Those plantations frequently contribute to habitat changes. However, the associated effects of forest plantations on habitat fragmentation and landscape connectivity are unclear. From 2008 to 2018, we examined land use changes, plantations, and deforestation of the Manabí province (Ecuador) provided by the Ecuadorian Ministry of the Environment. Four scenarios were created: (i) land uses in 2008, (ii) land uses in 2018, (iii) land uses in 2018 without deforestation, and iv) land uses in 2018 including reforestation. Fragmentation and connectivity metrics were analyzed using ArcGisPro and Graphad 2.6 software, respectively. Puma yagouaroundi was selected as the reference species. At regional scale, forest plantations had a significant effect on land uses changes and fragmentation during the study period. Forests decreased from 33.7% to 32.4% between 2008 and 2018, although other natural land uses, mostly those involving shrubs, increased by almost double (from 2.4% to 4.6%). Most of the deforestation affected native forests during this period, and most reforested areas in 2018 covered former agricultural land. Fragmentation decreased in the number of patches and increased in the average patch size. When considering reforestation, deforestation was higher than the reforested area (58 km2 of difference), increasing the number of patches but with smaller size. Reforestation increased connectivity with a higher number of links and distance, particularly in central and extreme northeast areas of Manabí province. The scenario without deforestation also increased connectivity for Puma yagouaroundi in the west part of the Manabí province. Our findings suggest that forest plantations contribute to forest conservation by increasing the connectivity between fragmented patches.
Soil Trail as a Tool to Promote Cultural and Geoheritage: The Case Study of Mount Cusna Geosite (Northern Italian Apennines)
Authors: Masseroli Anna , Bollati Irene M. , Fracasetti Laura , Trombino Luca
Published: May 2023

The soil is a component of geodiversity, a geoheritage element providing knowledge of how the geosphere works and interacts with other Earth subsystems. To promote soil as a geoheritage element, we aim to create a geotouristic trail focused on soil, geomorphology, and geoarcheology in the area of Mt. Cusna (Tuscan-Emilian Apennine National Park, Northern Italy), where there is a 20-years long-lasting history of research on geopedology, geoarcheology, and geomorphology. Along existing hiking paths, five soil profiles are identified as sites of potential pedological interest, whereas three more sites are selected to show the geomorphological context of the area and one the geoarcheological evidence. The soil evidence allows for the reconstruction of paleoenvironmental and paleoclimatic conditions, and/or retraction of the human impact that has affected the area over time. In order to communicate the information about the geotouristic trail, illustrative panels were prepared for each trail site and underwent a formative evaluation by students attending academic courses in Natural Sciences to improve the offer. Through the trail, it will be possible to enable the visitor to discover the soil concept, which is often poorly known or even underestimated in its scientific and cultural value. Moreover, the cultural opportunities of the Mt. Cusna geosite will be enhanced.
Small Earthquakes Can Help Predict Large Earthquakes: A Machine Learning Perspective
Authors: Wang Xi , Zhong Zeyuan , Yao Yuechen , Li Zexu , Zhou Shiyong , Jiang Changsheng , Jia Ke
Published: May 2023

Earthquake prediction is a long-standing problem in seismology that has garnered attention from the scientific community and the public. Despite ongoing efforts to understand the physical mechanisms of earthquake occurrence, there is no convincing physical or statistical model for predicting large earthquakes. Machine learning methods, such as random forest and long short-term memory (LSTM) neural networks, excel at identifying patterns in large-scale databases and offer a potential means to improve earthquake prediction performance. Differing from physical and statistical approaches to earthquake prediction, we explore whether small earthquakes can be used to predict large earthquakes within the framework of machine learning. Specifically, we attempt to answer two questions for a given region: (1) Is there a likelihood of a large earthquake (e.g., M ≥ 6.0) occurring within the next year? (2) What is the maximum magnitude of an earthquake expected to occur within the next year? Our results show that the random forest method performs best in classifying large earthquake occurrences, while the LSTM method provides a rough estimation of earthquake magnitude. We conclude that small earthquakes contain information relevant to predicting future large earthquakes and that machine learning provides a promising avenue for improving the prediction of earthquake occurrences.
AFFNet: An Attention-Based Feature-Fused Network for Surface Defect Segmentation
Authors: Chen Xiaodong , Fu Chong , Tie Ming , Sham Chiu-Wing , Ma Hongfeng
Published: May 2023

Recently, deep learning methods have widely been employed for surface defect segmentation in industrial production with remarkable success. Nevertheless, accurate segmentation of various types of defects is still challenging due to their irregular appearance and low contrast with the background. In light of this challenge, we propose an attention-based network with a U-shaped structure, referred to as AFFNet. In the encoder part, we present a newly designed module, Residual-RepGhost-Dblock (RRD), which focuses on the extraction of more representative features using CA attention and dilated convolution with varying expansion rates without a concomitant increase in the parameters. In the decoder part, we introduce a novel global feature attention (GFA) module to selectively fuse low-level and high-level features, suppressing distracting information such as background. Moreover, considering the imbalance of the dataset sampled from actual industrial production and the difficulty of training samples with small defects, we use the online hard sample mining (OHEM) cross-entropy loss function to improve the learning ability of hard samples. Experimental results on the NEU-seg dataset demonstrate the superiority of our method over other state-of-the-art methods.
Air Quality Improvement in Urban Street Canyons: An Assessment of the Effects of Selected Traffic Management Strategies Using OSPM Model
Authors: Oleniacz Robert , Bogacki Marek , Rzeszutek Mateusz , Bździuch Paulina
Published: May 2023

Constantly changing vehicle stock, modification of road infrastructure, and other conditions result in a need to update the knowledge on the effectiveness of individual traffic management strategies, which could form the basis for actions taken by local authorities to improve air quality in crowded city centers, especially in street canyons. The article presents research results that evaluate the theoretical effects of introducing select traffic reorganization scenarios in the example of four street canyons located in Krakow (Poland) that are different in terms of vehicle traffic volume and canyon geometry. These scenarios were based on a reduction in the average traffic speed, road capacity or the admission of cars meeting certain exhaust emission standards. The authors estimated changes in emissions of nitrogen oxides (NO, NO2 and total NOx) and particulate matter (PM10 and PM2.5) as well as investigated the effect of these changes on air quality in the canyons using the Operational Street Pollution Model (OSPM). Significant effects in terms of improving air quality were identified only in scenarios based on a significant reduction in traffic volume and the elimination of passenger cars and light commercial vehicles with internal combustion engines that did not meet the requirements of the Euro 4, Euro 5 or Euro 6 emission standards. For these scenarios, depending on the variant and canyon analyzed, the emission reduction was achieved at a level of approximately 36–66% for NO, 28–77% for NO2, 35–67% for NOx and 44–78% for both PM10 and PM2.5. The expected effect of improving air quality in individual street canyons for these substances was 15–44%, 5–14%, 11–36% and 3–14%, respectively. The differences obtained in the percentage reduction of emissions and pollutant concentrations in the air were the result of a relatively high background of pollutants that suppress the achieved effect of improving air quality to a large extent.
Numerical Simulation and Analysis of the Causes and Distribution of Secondary Lining Cracks in Overlapping Railway Tunnels
Authors: Xu Qianwei , Xie Jinli , Zhou Feng , Tang Zhuohua
Published: May 2023

The construction of new tunnels above existing tunnels has become increasingly common to optimize underground space utilization. However, such construction may pose potential engineering hazards due to cracking in the secondary lining of the lower tunnel. This study investigates the occurrence and evolutionary characteristics of longitudinal cracks in the secondary lining of the lower tunnel during the construction of the upper tunnel adjacent to the pre-existing lower tunnel. Our findings demonstrate that the construction of the upper tunnel has a significant impact on the lower tunnel, as confirmed by on-site monitoring and numerical simulation results. The redistribution of surrounding rock pressure alters the stress distribution of the secondary lining of the lower tunnel, which is the primary reason for the observed cracking. To mitigate the risk of cracks, two different methods are recommended based on the density of the cracks. In areas with less dense cracks, the method of chiseling and grouting is adopted to improve the strength of the secondary lining, while in relatively dense areas, resin anchor rods with saddle joints are used to enhance the stability of the surrounding rock. Long-term monitoring, classification, and early warning of cracks are also recommended.
Fuzzy Decision Algorithm for Health Impact Assessment in a 5G Environment
Authors: Pantelić Slađana , Vulević Branislav , Milić Saša
Published: May 2023

The widespread use of mobile phones and other wireless communication devices raises concerns about radiation’s impact on humans. A new algorithm for making decisions for the assessment of the biological impact of non-ionizing radiation is presented in this paper. The algorithm was developed according to ICNIRP (the International Commission on Non-Ionizing Radiation Protection) guidelines using fuzzy logic. Appropriate membership function choices and optimized fuzzy rule selections are crucial for fuzzy modeling. Fuzzy logic is widely applied for multiparameter process modeling using linguistic forms and mathematical expressions. A comprehensive analysis of 4G and 5G network parameters was carried out including electrical and magnetic field strengths, frequency ranges, power densities, and exposure times. The proposed hands-on fuzzy decision-making algorithm can be used for fast, easy, and reliable non-ionizing radiation risk assessment for the following social groups: residents, on-site workers, and professional users.
Experimental Verification of the CFD Model of the Squeeze Film Lifting Effect
Authors: Bastian Bartosz , Gawarkiewicz Rafał , Wasilczuk Michał , Wodtke Michał
Published: May 2023

The presented study shows the results of the research into the squeeze film levitation phenomena. The system introduced in the investigation is composed of a vibrating surface, air squeeze film, and the surface of the body freely suspended over the film. The use of the CFD (Computational Fluid Dynamics) model used in the system allows us to determine the steady state, periodic behavior of the air film (described by Navier–Stokes, continuity equations, and ideal gas law), and the lifted object dynamics. The model allows us to determine multiple factors, among others, mean film thickness and pressure distribution inside the fluid film. The influence of factors, such as vibration amplitude, frequency, and load on the lifting conditions, was presented. A series of calculations show the levitations height in the range of 5.61 up to 58.12 microns, obtained for masses of samples between 5–20 g, vibration frequency of 5–25 kHz, and the motions amplitude of 0.5–1.5 µm. A series of CFD multivariable calculations for a standing wave inducer were not previously published. The CFD model was validated with the use of experiments on a specially developed test rig. The authors experimentally obtained the height of levitation up to 200 microns.
Musculoskeletal Asymmetries in Young Soccer Players: 8 Weeks of an Applied Individual Corrective Exercise Intervention Program
Authors: Theodorou Eleni , Tryfonidis Marios , Zaras Nikolaos , Hadjicharalambous Marios
Published: May 2023

Introduction: In youth soccer, for examining injury prevention and exercise performance, most of the interventional studies concerning corrective postural asymmetries have applied general intervention programs, ignoring the specific individual corrective needs of each youth player separately. The aim, therefore, of the present study was to examine the effect of 8 weeks of an individualized corrective exercise intervention program on musculoskeletal asymmetries in young soccer players. Materials and Methods: Eighty young male soccer players (age: 14.4 ± 1.2 years; body height: 166.3 ± 9.6 cm; body mass: 59.1 ± 11.5 kg) participated in the current laboratory-based study. A battery of postural and musculoskeletal asymmetry evaluations were initially performed. After the completion of the initial assessment, each player was provided with an individual musculoskeletal asymmetry corrective exercise intervention program which lasted for 8-weeks, with the aim of restoring muscular asymmetries. Following the application of the intervention program, a re-evaluation of their musculoskeletal asymmetries was performed. Results: There was a significant improvement in the primary angle of trunk rotation (r = −0.56, p < 0.001), hamstring flexibility (right: r = −0.55, p < 0.001; left: r = −0.48, p < 0.001), hip external rotation (right: r = −0.46, p < 0.001; left: r = −0.26, p = 0.020), hip internal rotation (right: r = −0.26, p = 0.021; left: r = −0.35, p = 0.002), the opened-eyes Stork Test (right: r = −0.33, p = 0.003: left: r = −0.33, p = 0.003), the closed-eyes Stork Test (right: r = −0.39, p < 0.001; left: r = −0.43, p < 0.001), the Thomas test [right: (χ2(3) = 52.281, p = 0.001, γ^ = −0.751; left: (χ2(3) = 45.832, p = 0.001, γ^ = −0.696)] and of ankle prone passive dorsiflexion (flexed knees) (χ2(2) = 13.019, p = 0.005, V = 0.285). Conclusions: An 8-week individual corrective intervention exercise program may improve postural and musculoskeletal asymmetry status in young male soccer players.
Development of Pitch Cycle-Based Iterative Learning Contour Control for Thread Milling Operations in CNC Machine Tools
Authors: Yeh Syh-Shiuh , Jiang Wei-Jia
Published: May 2023

The helical contour motion accuracy of feed drive axes is important for thread milling operations in computer numerical control (CNC) machine tools. However, the motion dynamics and external disturbances significantly affect the contour motion results, while the feed drive axes perform helical motions in thread milling operations. Although existing iterative learning contour control (ILCC) methods can improve contour motion accuracy, the problems of data recording and processing on memory usage and computational burden in control systems, wasted materials, and increased costs in thread manufacturing still limit the practical applications of ILCC. Therefore, considering the similar motion dynamics and external disturbances of the feed drive axes during the pitch cycle motions of a helical path, this study developed a pitch cycle-based iterative learning contour control (PCB-ILCC) method to address the control system and thread manufacturing problems caused by the use of ILCC. For PCB-ILCC, this study adopted contour error vector estimation by referring to the interpolated positions on the pitch cycle of the helical path to simplify the computational complexity and designed the ILCC using the cycle learning method to easily implement the ILCC structure. Thus, this study developed a permanent magnet synchronous motor (PMSM) driving control utilizing the robust control method to mitigate the problems of motion dynamics and external disturbances on the feed drive axes. Thread milling experiments performed on a five-axis CNC machining center demonstrated the feasibility of the PCB-ILCC and validated that it can significantly improve the helical contour motion accuracy of the feed drive axes and achieve an 80% contour error reduction rate in comparison with the proportional–proportional–integral control, which is extensively used in commercialized PMSM drivers and CNC controllers.
An Object Detection Method Based on Feature Uncertainty Domain Adaptation for Autonomous Driving
Authors: Zhu Yuan , Xu Ruidong , Tao Chongben , An Hao , Sun Zhipeng , Lu Ke
Published: May 2023

The environment perception algorithm in autonomous driving is trained in the source domain, leading to domain drift and reduced detection accuracy in the target domain due to shifts in background feature distribution. To address this issue, a domain adaptive object detection algorithm based on feature uncertainty is proposed, which can improve the detection performance of object detection algorithms in unlabeled data. Firstly, a local alignment module based on channel information is proposed, which can obtain the model’s uncertainty about different domain data based on the feature channels obtained through the feature extraction network, achieving adaptive dynamic local alignment. Secondly, an instance-level alignment module guided by local feature uncertainty is proposed, which can obtain the corresponding instance-level uncertainty through ROI mapping. To improve the domain invariance of bounding box regression, a multi-class, multi-regression instance-level uncertainty alignment module is proposed, which can achieve spatial decoupling of classification and regression tasks, further improving the model’s domain adaptive ability. Finally, the effectiveness of the proposed algorithm is validated on Cityscapes, KITTI, and real vehicle data.
Comparison of Different Carbon Sources on Biomethane Production with Clostridium cellulovorans and Methanogens
Authors: Sawada Haruki , Tomita Hisao , Okazaki Fumiyoshi , Tamaru Yutaka
Published: May 2023

Methane (CH4) has attracted attention as not only one of the hydrogen carriers in terms of energy density, but also synthetic natural gas. In nature, the decomposition of organic compounds is performed with bacterial ecosystems that can produce CH4. Clostridium cellulovorans as a decomposer was cultivated with pig manure (PM) as an unused biomass in this study. As a result of high-performance liquid chromatography (HPLC) analysis, while formate and lactate were decreased in the C. cellulovorans medium containing 0.5% PM, acetate and butyrate were increased in it. Accordingly, in order to compare with the effect of carbon sources for methane production, the cocultivation of C. cellulovorans and the methanogenesis of Methanosarcina mazei or microbial flora of methane production (MFMP) was carried out in the C. cellulovorans medium. As a result, only the cocultivation with C. cellulovorans and MFMP showed methane production in 0.5% acetate medium. Moreover, in comparison with a carbon source in either 1% acetate or 1% methanol medium, MFMP was only cultivated after being precultivated with 0.5% glucose medium for 12 h. The results revealed that MFMP with a 1% methanol medium produced methane approximately eight times higher than with 1% acetate medium. After cultivation with 1% acetate or 1% methanol, next-generation sequencing (NGS) analysis of MFMP was carried out. Interestingly, Methanofollis (0.211%), belonging to methanogens through the CO2 reduction pathway, was dominant in the 1% acetate medium for 72 h cultivation, while Methanosarcina siciliae (1.178%), M. barkeri (0.571%), and Methanofollis (0.490%) were major species in 1% methanol medium for 72 h cultivation. Since Methanosarcina spp. belong to acetoclasts (acetoclastic pathway), methanol could promote the growth of Methanosarcina spp., rather than acetate. Therefore, it seems that Methanosarcina spp. may play a key methanogenesis role in MFMP. Thus, these results will provide important information for low-cost biomethane production.
Airborne Air Pollutant Emission Characteristics of Mobile Vehicles in Taiwan
Authors: Tsai Jiun-Horng , Chen Jian-You , Chiang Hung-Lung
Published: May 2023

This study examines the air pollutant emission characteristics, activity intensity, and trends of mobile sources from 2013 to 2021. The target pollutants include criteria pollutants (fine particulate matters, nitrogen oxides, and hydrocarbons) and hazardous air pollutants (benzene, formaldehyde, and BaP). The results indicated that the activity intensity levels of road mobile sources in Taiwan were148 × 109, 156 × 109, 159 × 109, and 155 × 109 km/year in 2013, 2016, 2019, and 2021, respectively, with the largest proportion attributed to gasoline passenger cars (42.6%), followed by four-stroke motorcycles (32.6%). An emission factor of PM2.5 was estimated by EPA’s MOVES (Motor Vehicle Emission Simulator) model, and the results showed that the emission sequence was diesel > gasoline > motorcycle; the NOx emission factor was estimated using the MOBILE6.2 model, and the results showed that the order was diesel > gasoline > motorcycle; the HC emission factor was compiled with the use of gasoline vehicle dynamometer data, and the results showed that motorcycle > gasoline vehicles. Further results showed that the emission sequence for benzene was motorcycle > gasoline ≥ diesel; the formaldehyde emission sequence was diesel > motorcycle ≥ gasoline. The BaP emission factors of different vehicle types were estimated using MOVES, and the emission factors of old heavy-duty diesel vehicles were the highest.
Small-Scale Anisotropy in Stably Stratified Turbulence; Inferences Based on Katabatic Flows
Authors: Kit Eliezer , Fernando Harindra J. S.
Published: May 2023

The focus of the current study is on the anisotropy of stably stratified turbulence that is not only limited to large scales and an inertial subrange but also penetrates to small-scale turbulence in the viscous/dissipation subrange on the order of the Kolmogorov scale. The anisotropy of buoyancy forces is well-known, including ensuing effects such as horizontal layering and pancakes structures. Laboratory experiments in the nineties by Van Atta and his students showed that the anisotropy penetrates to very small scales, but their experiments were performed only at a relatively low Reλ (i.e., at Taylor Reynolds numbers) and, therefore, did not provide convincing evidence of anisotropy penetration into viscous sublayers. Nocturnal katabatic flows having configurations of stratified parallel shear flows and developing on mountain slopes provide high Reynolds number data for testing the notion of anisotropy at viscous scales, but obtaining appropriate time series of the data representing stratified shear flows devoid of unwarranted atmospheric factors is a challenge. This study employed the “in situ” calibration of multiple hot-film-sensors collocated with a sonic anemometer that enabled obtaining a 90 min continuous time series of a “clean” katabatic flow. A detailed analysis of the structure functions was conducted in the inertial and viscous subranges at an Reλ around 1250. The results of DNS simulations by Kimura and Herring were employed for the interpretation of data.
Turbulence along the Runway Glide Path: The Invisible Hazard Assessment Based on a Wind Tunnel Study and Interpretable TPE-Optimized KTBoost Approach
Authors: Khattak Afaq , Zhang Jianping , Chan Pak-Wai , Chen Feng
Published: May 2023

Aircraft landings can be dangerous near airport runways due to wind variability. As a result, an aircraft could potentially miss an approach or divert off its flight path. In this study, turbulence intensity along the runway glide path was investigated using a scaled-down model of Hong Kong International Airport (HKIA) and the complex terrain nearby built in a TJ-3 atmospheric boundary layer wind tunnel. Different factors, including the effect of terrain, distance from the runway threshold, assigned approach runway, wind direction, and wind speed, were taken into consideration. Next, based on the experimental results, we trained and tested a novel tree-structured Parzen estimator (TPE)-optimized kernel and tree-boosting (KTBoost) model. The results obtained by the TPE-optimized KTBoost model outperformed other advanced machine learning models in terms of MAE (0.83), MSE (1.44), RMSE (1.20), and R2 (0.89). The permutation-based importance analysis using the TPE-optimized KTBoost model also revealed that the top three factors that contributed to the high turbulence intensity were the effect of terrain, distance from the runway threshold, and wind direction. The presence of terrain, the shorter distance from the runway, and the wind direction from 90 degrees to 165 degrees all contributed to high turbulence intensity.
Landscape as a Palimpsest for Energy Transition: Correlations between the Spatial Development of Energy-Production Infrastructure and Climate-Mitigation Goals
Authors: Lobosco Gianni , Tinti Lorenzo , Magagnoli Beatrice , Mencarini Vittoria , Mannucci Simona , Ferrero Marco
Published: May 2023

The spatial footprint of energy infrastructures requires a re-evaluation of design and planning processes, especially in relation to the sustainable development goals enshrined in the United Nations 2030 Agenda. This study investigates the Ravenna area (Italy)’s transition potential towards renewable energy sources, considering their spatial interaction with the landscape and the environment. The primary objective is to identify the opportunities and limitations associated with each type of renewable energy production and provide indications for the strategic actions needed to achieve total emissions reduction by 2050. The methodology applied involves several steps to compare both the efficiency and the spatial arrangements of alternative mono-energy scenarios over time. In order to manage the uncertainty inherent in technological development and the variability of territorial policies, the study puts forward the hypothesis of a mixed strategy capable of structuring the energy transition on the specificities of the local landscape palimpsest by identifying location criteria and related impacts. The research demonstrates how site-specific assessments are important to inform resilient strategic choices, and provide decision-makers and stakeholders with data and spatialized representations of future scenarios to discuss and share.
Analysis of Precipitation Process and Operational Precipitation Enhancement in Panxi Region Based on Cloud Parameters Retrievals from China’s Next−Generation Geostationary Meteorological Satellite FY−4A
Authors: Guo Xiaomei , Lin Dan , Wu Fan
Published: May 2023

Geostationary meteorological satellite data with high spatial and temporal resolution can be used to retrieve cloud physical parameters, which has significant advantages in tracking cloud evolution and development. Based on satellite multispectral RGB composite image and cloud physical analysis methods, we quantitatively analyze the evolution characteristics of cloud parameters in the pre-, mid- and post-artificially influenced weather process, explore the application potential benefits of satellite data in monitoring the operating conditions of the artificially influenced weather in the Panxi region, and verify the feasibility analysis of the evaluation of their effects. In this study, cloud parameters such as cloud particle effective radius (Re), cloud liquid water path (LWP), cloud ice water path (IWP), and cloud top height and temperature (CTH and CTT) are retrieved using FY−4A satellite data. For the Panxi region, the evolution characteristics of typical cloud parameters in the affected area before and after two aircraft artificial operational precipitation enhancements are analyzed. The results show that the satellite retrieval of cloud characteristic parameters in the Panxi region has good application value, which can be used to guide the artificial Operational Precipitation Enhancement. In this precipitation process, there are solid particles in the upper layer cloud and supercooled water in the lower layer cloud. After the cold cloud catalysis, the cloud top height, liquid water and ice water content, particle effective radius and ground precipitation in the operational area increased, and the cloud top temperature decreased. Thus, it effectively alleviated the drought in the Panxi region. The satellite retrieval of cloud characteristic parameters in the Panxi region has a good application value, which can provide a basis and guidance for future weather modification operations in the Panxi region.
Development and Field Testing of an Online Monitoring System for Atmospheric Particle-Bound Reactive Oxygen Species (ROS)
Authors: Liu Yuan , Tang Xiancheng , Zhang Zhiwei , Li Ling , Chen Jianmin
Published: May 2023

Excessive accumulation of reactive oxygen species (ROS) in the body can lead to a redox imbalance and result in cellular and tissue damage. Since ROS are highly reactive, traditional offline methods may underestimate their true concentration. In this study, we developed an online monitoring system for particle-bound ROS based on the fluorescent probe 2′,7′-dichlorofluorescin (DCFH), which consists of an Aerosol Collector and a Fluorescence Detector. The performance of the system was evaluated in terms of collection efficiency, instrument calibration, and comparison with offline methods. The results demonstrate that the collection efficiency of the system is over 93%, the calibration correlation coefficient (R2) is 99.75%, and the online system reduces ROS loss due to offline methods by more than 60%. The system has a temporal resolution of 20 min and the limit of detection of the system was 1.9 nmol H2O2/m3. Field observations revealed that particle-bound ROS exhibited similar diurnal variations to O3, and photochemical reactions were the main factors affecting its diurnal variation.