bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Electrical Resistivity Tomography Scheme of Borehole-to-Surface-to-Cliff Detection and Imaging for Grotto Rock Structure
Authors: Yan Jiahe , Zeng Zhaofa , Zhao Xueyu , An Baizhou , Bai Lige , Zhao Jianwei , Li Jing
Published: January 2023

Grotto rock structure detection is precondition of the grotto protection and restoration. As a stable and non-destructive geophysical method, electrical resistivity tomography (ERT) is extensively used to detect the geological structure of the grottoes. However, the traditional ERT measurement scheme is challenging to satisfy the requirements of high accuracy and high resolution in the cliff region. Therefore, we propose a new borehole-to-surface-to-cliff ERT (BSC-ERT) scheme for grotto detection. The sensitivity patterns of five ERT schemes using three configurations (A-MN array, AB-MN array, and AM-BN array) are tested to show the detection capability of different configurations. Two numerical experiments show that the combination of borehole-to-surface ERT (BS-ERT) and surface-to-cliff ERT (SC-ERT) schemes using AM-BN array have better imaging effects and a more reasonable detection range, which is recommended to be implemented for future work. In addition, the numerical experiment also proves that the symmetric effect generated in the AM-BN array in BS-ERT scheme can be suppressed with the combination of the SC-ERT scheme.
Sparse Inversion for the Iterative Marchenko Scheme of Irregularly Sampled Data
Authors: Zeng Jingwen , Han Liguo
Published: January 2023

The Marchenko method is a data-driven way that makes it possible to calculate Green’s functions from virtual points in the subsurface using the reflection data at the surface and requiring only a macro velocity model. This method requires collocated sources and receivers. However, in practice, irregular sampling of sources or receivers will cause gaps and distortions in the obtained focusing functions and Green’s functions. To solve this problem, this paper proposes to integrate a sparse inversion into the iterative Marchenko scheme. Specifically, we add sparsity constraints to the Marchenko equations and apply the sparse inversion during the iterative process. To reduce the strict requirements on acquisition geometries, our work deals with the situation in which the sources are subsampled where the integrations are carried out over the receivers, while the existing point spread function method solves the situation where the receivers are subsampled. We make a step to handle both situations at the same time by integrating this method with our work because of the same iterative framework. Our new method is applied to a two-dimensional numerical example with irregularly sampled data. The result shows that it can effectively fill gaps in the obtained focusing functions and Green’s functions in the Marchenko method.
Automatic Inspection of Bridge Bolts Using Unmanned Aerial Vision and Adaptive Scale Unification-Based Deep Learning
Authors: Jiang Shang , Zhang Jian , Wang Weiguo , Wang Yingjun
Published: January 2023

Bolted connections are essential components that require regular inspection to ensure bridge safety. Existing methods mainly rely on traditional artificial vision-based inspection, which is inefficient due to the many bolts of bridges. A vision-based method using deep learning and unmanned aerial vision is proposed to automatically analyze the bridge bolts’ condition. The contributions are as follows: (1) Addressing the problems that motion blur often exists in videos captured by unmanned ariel systems (UASs) with high moving speed, and that bolt damage is hard to accurately detect due to the few pixels a single bolt occupies, a bolt image preprocessing method, including image deblurring based on inverse filtering with camera motion model and adaptive scaling based on super-resolution, is proposed to eliminate the motion blur of bolt images and segment them into subimages with uniform bolt size. (2) Addressing the problem that directly applying an object detection network for both bolt detection and classification may lead to the wrong identification of bolt damage, a two-stage detection method is proposed to divide bolt inspection into bolt object segmentation and damage classification. The proposed method was verified on an in-service bridge to detect bolts and classify them into normal bolts, corrosion bolts, and loose bolts. The results show that the proposed method can effectively eliminate the inherent defects of data acquired by UAS and accurately classify the bolt defects, verifying the practicability and high precision of the proposed method.
Automated Recognition of Tree Species Composition of Forest Communities Using Sentinel-2 Satellite Data
Authors: Polyakova Alika , Mukharamova Svetlana , Yermolaev Oleg , Shaykhutdinova Galiya
Published: January 2023

Information about the species composition of a forest is necessary for assessing biodiversity in a particular region and making economic decisions on the management of forest resources. Recognition of the species composition, according to the Earth’s remote sensing data, greatly simplifies the work and reduces time and labor costs in comparison with a traditional inventory of the forest, conducted through ground-based observations. This study analyzes the possibilities of tree species discrimination in coniferous–deciduous forests according to Sentinel-2 data using two automated recognition methods: random forest (RF) and generative topographic mapping (GTM). As remote sensing data, Sentinel-2 images of the Raifa section of Volga-Kama State Reserve in the Tatarstan Republic, Russia used: six images for the vegetation period of 2020. The analysis was carried out for the main forest-forming species. The training sample was created based on the cadastral data of the forest fund. The recognition quality was assessed using the F1-score, precision, recall, and accuracy metrics. The RF method showed a higher recognition accuracy. The accuracy of correct recognition by the RF method on the training sample reaches 0.987, F1-score = 0.976, on the control sample, accuracy = 0.764, F1-score = 0.709.
Euro VI-d Compliant Diesel Engine’s Sub-23 nm Particle Emission
Authors: Biró Norbert , Kiss Péter
Published: January 2023

Passenger and commercial transportation significantly contribute to hazardous air pollution. Exhaust gas after-treatment technology advances closely to the emission regulations throughout the world. The upcoming legislation will be EURO VII in European Union, which requirements are not set yet, but the Solid Particle Number (SPN) diameter range is expected to be more severe compared to EURO VI. This paper will revisit the measurement principle differences between over 10 nm and over 23 nm diameter particles in theory and practical engine bench measurement. Two different types of particle counters have performed the soot particle counting measurement; therefore, the applied sensors are different in terms of applied counting principles. The measurement principles of both devices will be introduced, and the experiment’s result will reflect on the sensor differences. From this, a conclusion can be derived in order to determine the severity of the upcoming EURO VII legislation in terms of SPN, and the experiment will also reflect on the measurement sensor differences. The overall results suggested that extending the lower range of the measurement increases the tailpipe particle emission by 20%, although the DPF filtration efficiency is still over 99%.
RSS Model Improvement Considering Road Conditions for the Application of a Variable Focus Function Camera
Authors: Kim Min Joong , Kim Young Min
Published: January 2023

The automobile industry has developed dramatically in recent years, the supply of vehicles has also increased, and thus it has become deeply established in everyday life. Recently, as the supply of vehicles with autonomous driving functions increases, the safety of vehicles is also an emerging issue. Various car-following models for the safe driving of vehicles have long been studied by various people, and recently, a Responsibility-Sensitive Safety (RSS) model has been proposed by Mobileye. However, in existing car-following models or the RSS model, the safe distance between vehicles is presented using only vehicle speed and acceleration information, so there is a limitation in that it cannot respond to changes in road conditions due to the weather. In this paper, in order to ensure safety when the RSS model is applied to a variable focus function camera, an improved RSS model is presented in consideration of the changes in road conditions due to changes in weather, and a safety distance is derived based on the proposed model.
High-Speed Fully Differential Two-Step ADC Design Method for CMOS Image Sensor
Authors: Guo Zhongjie , Wang Yangle , Xu Ruiming , Yu Ningmei
Published: January 2023

The application requirements of high frame rate CMOS image sensors (CIS) in the industry have not been satisfied due to the speed limitations in traditional single-slope and serial two-step analog-to-digital converters (ADCs). In this paper, a high-speed fully differential two-step ADC design method for CIS was proposed. The proposed method was based on differential ramp and time-to-digital conversion (TDC) technology. A parallel conversion mode was formed that is different from serial conversion, and the robustness of the system was ensured due to the existence of differential ramps. Aiming at the inconsistency between traditional TDC technology and single-slope ADC, a TDC technology based on level coding was proposed. The proposed technology achieves the TDC in the last clock cycle of analog-to-digital conversion, and realized a two-step conversion process at another level. This paper presents a complete circuit design, layout design, and test verification of the proposed design method based on the 55 nm 1P4M CMOS experimental platform. Under the design environment of the analog voltage of 3.3 V, the digital voltage of 1.2 V, the clock frequency of 100 MHz, and a dynamic input range of 1.6 V, this design was a 12-bit ADC with a conversion time of 480 ns, column-level power consumption of 62 μW, differential nonlinearity (DNL) of +0.6/−0.6 LSB, and integral nonlinearity (INL) of +1.2/−1.4 LSB. Furthermore, it achieved a signal-to-noise distortion ratio (SNDR) of 70.08 dB. The proposed design provided a large area array with a high frame rate, and compared with the existing advanced single-slope ADC, its conversion speed increased by more than 52%. It provides an effective solution for the implementation of high frame frequency CIS
An Overview on Image-Based and Scanner-Based 3D Modeling Technologies
Authors: Verykokou Styliani , Ioannidis Charalabos
Published: January 2023

Advances in the scientific fields of photogrammetry and computer vision have led to the development of automated multi-image methods that solve the problem of 3D reconstruction. Simultaneously, 3D scanners have become a common source of data acquisition for 3D modeling of real objects/scenes/human bodies. This article presents a comprehensive overview of different 3D modeling technologies that may be used to generate 3D reconstructions of outer or inner surfaces of different kinds of targets. In this context, it covers the topics of 3D modeling using images via different methods, it provides a detailed classification of 3D scanners by additionally presenting the basic operating principles of each type of scanner, and it discusses the problem of generating 3D models from scans. Finally, it outlines some applications of 3D modeling, beyond well-established topographic ones.
Modeling the Design Characteristics of Woven Textile Electrodes for long−Term ECG Monitoring
Authors: Brehm Peter J. , Anderson Allison P.
Published: January 2023

An electrocardiograph records the periodic voltage generated by the heart over time. There is growing demand to continuously monitor the ECG for proactive health care and human performance optimization. To meet this demand, new conductive textile electrodes are being developed which offer an attractive alternative to adhesive gel electrodes but they come with their own challenges. The key challenge with textile electrodes is that the relationship between the manufacturing parameters and the ECG measurement is not well understood, making design an iterative process without the ability to prospectively develop woven electrodes with optimized performance. Here we address this challenge by applying the traditional skin−electrode interface circuit model to woven electrodes by constructing a parameterized model of the ECG system. Then the unknown parameters of the system are solved for with an iterative MATLAB optimizer using measured data captured with the woven electrodes. The results of this novel analysis confirm that yarn conductivity and total conductive area reduce skin electrode impedance. The results also indicate that electrode skin pressure and moisture require further investigation. By closing this gap in development, textile electrodes can be better designed and manufactured to meet the demands of long−term ECG capture.
Infrared and Visible Image Fusion Technology and Application: A Review
Authors: Ma Weihong , Wang Kun , Li Jiawei , Yang Simon X. , Li Junfei , Song Lepeng , Li Qifeng
Published: January 2023

The images acquired by a single visible light sensor are very susceptible to light conditions, weather changes, and other factors, while the images acquired by a single infrared light sensor generally have poor resolution, low contrast, low signal-to-noise ratio, and blurred visual effects. The fusion of visible and infrared light can avoid the disadvantages of two single sensors and, in fusing the advantages of both sensors, significantly improve the quality of the images. The fusion of infrared and visible images is widely used in agriculture, industry, medicine, and other fields. In this study, firstly, the architecture of mainstream infrared and visible image fusion technology and application was reviewed; secondly, the application status in robot vision, medical imaging, agricultural remote sensing, and industrial defect detection fields was discussed; thirdly, the evaluation indicators of the main image fusion methods were combined into the subjective evaluation and the objective evaluation, the properties of current mainstream technologies were then specifically analyzed and compared, and the outlook for image fusion was assessed; finally, infrared and visible image fusion was summarized. The results show that the definition and efficiency of the fused infrared and visible image had been improved significantly. However, there were still some problems, such as the poor accuracy of the fused image, and irretrievably lost pixels. There is a need to improve the adaptive design of the traditional algorithm parameters, to combine the innovation of the fusion algorithm and the optimization of the neural network, so as to further improve the image fusion accuracy, reduce noise interference, and improve the real-time performance of the algorithm.
A Sequential Color Correction Approach for Texture Mapping of 3D Meshes
Authors: Dal’Col Lucas , Coelho Daniel , Madeira Tiago , Dias Paulo , Oliveira Miguel
Published: January 2023

Texture mapping can be defined as the colorization of a 3D mesh using one or multiple images. In the case of multiple images, this process often results in textured meshes with unappealing visual artifacts, known as texture seams, caused by the lack of color similarity between the images. The main goal of this work is to create textured meshes free of texture seams by color correcting all the images used. We propose a novel color-correction approach, called sequential pairwise color correction, capable of color correcting multiple images from the same scene, using a pairwise-based method. This approach consists of sequentially color correcting each image of the set with respect to a reference image, following color-correction paths computed from a weighted graph. The color-correction algorithm is integrated with a texture-mapping pipeline that receives uncorrected images, a 3D mesh, and point clouds as inputs, producing color-corrected images and a textured mesh as outputs. Results show that the proposed approach outperforms several state-of-the-art color-correction algorithms, both in qualitative and quantitative evaluations. The approach eliminates most texture seams, significantly increasing the visual quality of the textured meshes.
A Cyber-Physical Framework for Optimal Coordination of Connected and Automated Vehicles on Multi-Lane Freeways
Authors: Sakaguchi Yuta , Bakibillah A. S. M. , Kamal Md Abdus Samad , Yamada Kou
Published: January 2023

Uncoordinated driving behavior is one of the main reasons for bottlenecks on freeways. This paper presents a novel cyber-physical framework for optimal coordination of connected and automated vehicles (CAVs) on multi-lane freeways. We consider that all vehicles are connected to a cloud-based computing framework, where a traffic coordination system optimizes the target trajectories of individual vehicles for smooth and safe lane changing or merging. In the proposed framework, the vehicles are coordinated into groups or platoons, and their trajectories are successively optimized in a receding horizon control (RHC) approach. Optimization of the traffic coordination system aims to provide sufficient gaps when a lane change is necessary while minimizing the speed deviation and acceleration of all vehicles. The coordination information is then provided to individual vehicles equipped with local controllers, and each vehicle decides its control acceleration to follow the target trajectories while ensuring a safe distance. Our proposed method guarantees fast optimization and can be used in real-time. The proposed coordination system was evaluated using microscopic traffic simulations and benchmarked with the traditional driving (human-based) system. The results show significant improvement in fuel economy, average velocity, and travel time for various traffic volumes.
A Review on Bio- and Chemosensors for the Detection of Biogenic Amines in Food Safety Applications: The Status in 2022
Authors: Givanoudi Stella , Heyndrickx Marc , Depuydt Tom , Khorshid Mehran , Robbens Johan , Wagner Patrick
Published: January 2023

This article provides an overview on the broad topic of biogenic amines (BAs) that are a persistent concern in the context of food quality and safety. They emerge mainly from the decomposition of amino acids in protein-rich food due to enzymes excreted by pathogenic bacteria that infect food under inappropriate storage conditions. While there are food authority regulations on the maximum allowed amounts of, e.g., histamine in fish, sensitive individuals can still suffer from medical conditions triggered by biogenic amines, and mass outbreaks of scombroid poisoning are reported regularly. We review first the classical techniques used for selective BA detection and quantification in analytical laboratories and focus then on sensor-based solutions aiming at on-site BA detection throughout the food chain. There are receptor-free chemosensors for BA detection and a vastly growing range of bio- and biomimetic sensors that employ receptors to enable selective molecular recognition. Regarding the receptors, we address enzymes, antibodies, molecularly imprinted polymers (MIPs), and aptamers as the most recent class of BA receptors. Furthermore, we address the underlying transducer technologies, including optical, electrochemical, mass-sensitive, and thermal-based sensing principles. The review concludes with an assessment on the persistent limitations of BA sensors, a technological forecast, and thoughts on short-term solutions.
Fiber Loop Mirror Based on Optical Fiber Circulator for Sensing Applications
Authors: Robalinho Paulo , Soares Beatriz , Lobo Ribeiro António , Silva Susana , Frazão Orlando
Published: January 2023

In this paper, a different Fiber Loop Mirror (FLM) configuration with two circulators is presented. This configuration is demonstrated and characterized for sensing applications. This new design concept was used for strain and torsion discrimination. For strain measurement, the interference fringe displacement has a sensitivity of (0.576 ± 0.009) pm‧με−1. When the FFT (Fast Fourier Transformer) is calculated and the frequency shift and signal amplitude are monitored, the sensitivities are (−2.1 ± 0.3) × 10−4 nm−1 με−1 and (4.9 ± 0.3) × 10−7 με−1, respectively. For the characterization in torsion, an FFT peaks variation of (−2.177 ± 0.002) × 10−12 nm−1/° and an amplitude variation of (1.02 ± 0.06) × 10−3/° are achieved. This configuration allows the use of a wide range of fiber lengths and with different refractive indices for controlling the free spectral range (FSR) and achieving refractive index differences, i.e., birefringence, higher than 10−2, which is essential for the development of high sensitivity physical parameter sensors, such as operating on the Vernier effect. Furthermore, this FLM configuration allows the system to be balanced, which is not possible with traditional FLMs.
All-Solid-State Interdigitated Micro-Supercapacitors Based on Porous Gold Electrodes
Authors: Pastre Aymeric , Boé Alexandre , Rolland Nathalie , Bernard Rémy
Published: January 2023

Recent developments in embedded electronics require the development of micro sources of energy. In this paper, the fabrication of an on-chip interdigitated all-solid-state supercapacitor, using porous gold electrodes and a PVA/KOH quasisolid electrolyte, is demonstrated. The fabrication of the interdigitated porous gold electrode is performed using an original bottom-up approach. A templating method is used for porosity, using a wet chemistry process followed by microfabrication techniques. This paper reports the first example of an all-gold electrode micro-supercapacitor. The supercapacitor exhibits a specific capacitance equal to 0.28 mF·cm−2 and a specific energy of 0.14 mJ·cm−2. The capacitance value remains stable up to more than 8000 cycles.
Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Models
Authors: Gómez Jose L. , Villalonga Gabriel , López Antonio M.
Published: January 2023

Semantic image segmentation is a core task for autonomous driving, which is performed by deep models. Since training these models draws to a curse of human-based image labeling, the use of synthetic images with automatically generated labels together with unlabeled real-world images is a promising alternative. This implies addressing an unsupervised domain adaptation (UDA) problem. In this paper, we propose a new co-training procedure for synth-to-real UDA of semantic segmentation models. It performs iterations where the (unlabeled) real-world training images are labeled by intermediate deep models trained with both the (labeled) synthetic images and the real-world ones labeled in previous iterations. More specifically, a self-training stage provides two domain-adapted models and a model collaboration loop allows the mutual improvement of these two models. The final semantic segmentation labels (pseudo-labels) for the real-world images are provided by these two models. The overall procedure treats the deep models as black boxes and drives their collaboration at the level of pseudo-labeled target images, i.e., neither modifying loss functions is required, nor explicit feature alignment. We test our proposal on standard synthetic and real-world datasets for onboard semantic segmentation. Our procedure shows improvements ranging from approximately 13 to 31 mIoU points over baselines.
Simulation Analysis of a Wavefront Reconstruction of a Large Aperture Laser Beam
Authors: Wang Gangyu , Hou Zaihong , Qin Laian , Jing Xu , Wu Yi
Published: January 2023

In order to solve the problem of atmospheric influence on the far-field measurement of the quality of a laser beam, we proposed a direct wavefront measurement system based on the Hartmann detection principle, which can measure large apertures and high-power laser beams. The measuring system was composed of a lens array and a detector. The wavefront detection of a large aperture laser beam could be realized by controlling the distance between the lenses and the size of the lens. The influence of different duty cycle factors on the accuracy of the wavefront reconstruction under the same arrangement and different arrangement conditions was simulated and analyzed. The simulation results showed that when the sub-lenses of the system were not in close contact, the reconstruction accuracy of the duty factor of 0.8 was close to that of the case of the duty factor of 1. Within a certain detection range, the hexagonal arrangement of 19 lenses and the arrangement of 8 × 8 lens arrays had a high wavefront restoration accuracy; both were lower than 0.10 λ. The system proposed in this paper was suitable for measuring a large aperture laser beam, providing a new idea for measuring and analyzing the quality of large aperture laser beams. It also has an important significance for improving the measurement accuracy of the beam quality.
Reliability and Validity of a Wearable Sensing System and Online Gait Analysis Report in Persons after Stroke
Authors: Schwarz Anne , Al-Haj Husain Adib , Einaudi Lorenzo , Thürlimann Eva , Läderach Julia , Awai Easthope Chris , Held Jeremia P. O. , Luft Andreas R.
Published: January 2023

The restoration of gait and mobility after stroke is an important and challenging therapy goal due to the complexity of the potentially impaired functions. As a result, precise and clinically feasible assessment methods are required for personalized gait rehabilitation after stroke. The aim of this study is to investigate the reliability and validity of a sensor-based gait analysis system in stroke survivors with different severities of gait deficits. For this purpose, 28 chronic stroke survivors (9 women, ages: 62.04 ± 11.68 years) with mild to moderate walking impairments performed a set of ambulatory assessments (3× 10MWT, 1× 6MWT per session) twice while being equipped with a sensor suit. The derived gait reports provided information about speed, step length, step width, swing and stance phases, as well as joint angles of the hip, knee, and ankle, which we analyzed for test-retest reliability and hypothesis testing. Further, test-retest reliability resulted in a mean ICC of 0.78 (range: 0.46–0.88) for walking 10 m and a mean ICC of 0.90 (range: 0.63–0.99) for walking 6 min. Additionally, all gait parameters showed moderate-to-strong correlations with clinical scales reflecting lower limb function. These results support the applicability of this sensor-based gait analysis system for individuals with stroke-related walking impairments.
Semantic Reasoning for Geolocalized Assessment of Crime Risk in Smart Cities
Authors: Minardi Rosario , Villani Maria Luisa , De Nicola Antonio
Published: January 2023

The increasing number of crimes affecting urban areas requires the adoption of countermeasures to tackle this problem from different perspectives, including the technological one. Currently, there are many research initiatives with the goal of applying machine or deep learning techniques leveraging historical data to predict the occurrence of crime incidents. Conversely, there is a lack of tools aiming at crime risk assessment, in particular, by supporting the police in conceiving what could be the crime incidents affecting a given city area. To this purpose, we propose the Crime Prevention System, a modular software application for qualitative crime risk assessment. This consists of an ontology of crime risk, a module to retrieve contextual data from OpenStreetMap, semantics reasoning functionalities, and a GIS interface. We discuss how this system can be used through a case study related to the Italian city of Syracuse.
Combined Static Stretching and Electrical Muscle Stimulation Induce Greater Changes in Range of Motion, Passive Torque, and Tendon Displacement Compared with Static Stretching
Authors: Mizuno Takamasa
Published: January 2023

The purpose of this study was to determine the combined effects of static stretching and electrical muscle stimulation on maximal dorsiflexion angle and passive properties. Sixteen healthy subjects participated in three randomly ordered experimental trials: combined static stretching and electrical muscle stimulation, static stretching alone, and control. In combined trial, subjects performed 5 min of calf stretching while receiving electrical muscle stimulation of the gastrocnemius medialis. In static stretching trial, subjects performed calf stretching only. Maximal dorsiflexion angle, passive torque, and muscle displacement were measured before and after intervention. Tendon displacement was also calculated. The difference from pre- to post-intervention in maximal dorsiflexion angle in combined trial was greater compared with that in the control (p = 0.026), but the static stretching trial exhibited no significant difference (both p > 0.05). Passive torque at submaximal dorsiflexion angles was significantly decreased only after combined trial (all p < 0.05). Muscle displacement at maximal dorsiflexion angle was significantly increased in all conditions (all p < 0.05). Tendon displacement at maximal dorsiflexion angle was higher after combined trial compared with static stretching trial (p = 0.030). These results revealed additional effects of adding electrical muscle stimulation to static stretching on maximal dorsiflexion angle, passive torque, and tendon displacement.
Effects of Exercise Frequency with Complex Contrast Training on Measures of Physical Fitness in Active Adult Males
Authors: Kumar Gopal , Pandey Vivek , Thapa Rohit K. , Weldon Anthony , Granacher Urs , Ramirez-Campillo Rodrigo
Published: January 2023

Complex contrast training (CCT) is an exercise modality that utilizes both high-load resistance activity and low-load plyometric activity in a set-by-set fashion within a single exercise session. Such a combination of exercises targets multiple aspects of the force–velocity curve and may thus lead to improvement of various components of physical fitness. However, no previous study has attempted to compare the effects of load-equated two vs. three CCT sessions per week on measures of physical fitness. Forty-five male participants aged 21.4 ± 2.0 years were randomly assigned to either two weekly CCT sessions (CCT-2; n = 15), three weekly CCT sessions (CCT-3; n = 15), or an active control group (CG; n = 15). Selected measures of physical fitness were assessed pre- and post-six weeks of training. The tests included the assessment of 15 and 30 m linear sprint speeds, upper (medicine ball throw) and lower limb muscle power (standing long jump and countermovement jump with arm thrust), muscle strength (isokinetic peak knee extensor/flexor torque), and change-of-direction speed (modified agility T-test (MAT)). Significant group–time interactions were observed for all dependent variables (all p < 0.001, ɳp2 = 0.51–0.78) using ANOVA. Post hoc tests indicated significant performance improvements for the CCT-2 and CCT3 groups for all dependent variables (Hedge’s g = 0.28–3.26, %Δ = 2.4–16.7), including the 15 and 30 m linear sprint speeds (p < 0.001), medicine ball throw (p < 0.001), standing long jump (p < 0.001), countermovement jump with arm thrust (p < 0.001), right leg knee extensor (p < 0.001) and flexor peak torque (p < 0.001), left leg knee extensor (p < 0.001) and flexor peak torque (p < 0.001), and change-of-direction speed (p < 0.001). The CCT-3 group showed greater improvements in MAT compared to the CCT-2 group (g = 3.26 vs. 0.70, p < 0.001). In conclusion, compared to active controls, the load-equated CCT-2 and CCT-3 programs provided similar effects on measures of physical fitness in active adult males. However, an athlete’s goal is to improve their MAT score, the CCT-3 program may elicit greater improvements compared with the CCT-2 program.
The Assessment of Ankle Range-of-Motion and Its Relationship with Overall Muscle Strength in a Cross-Section of Soccer Players
Authors: Francia Piergiorgio , Ferri Marini Carlo , Bocchi Leonardo , Piccini Barbara , Seghieri Giuseppe , Federici Ario , Toni Sonia , Lucertini Francesco
Published: January 2023

Soccer (football) practice can induce a limitation of ankle range of motion (ROM) that is a possible risk factor for injury and other negative consequences over time. The main objective of this research was to investigate the effects of soccer practice on ankle ROM throughout the entire period of a sports career of soccer players (SP). Furthermore, the relationship between ankle ROM and muscle strength in SP of different ages was studied. A total of 204 SP (range 6.7–45.1 years) and 87 controls (range: 7.5–45.2 years) matched for age, body mass index (BMI), and gender, were assessed. Ankle ROM in both plantar flexion (APF) and dorsiflexion (ADF) in addition to handgrip strength (HGS) were evaluated using an inclinometer and the Jamar hydraulic hand dynamometer, respectively. The comparison between SP and control groups showed a significant reduction in ankle ROM of both APF (26.3 ± 7.2° vs. 32.6 ± 7.4°; d = −0.90; p < 0.001) and ADF (95.5 ± 15.6° vs. 105.5 ± 15.8°; d = −0.66; p < 0.001). In SP, the results of the ANOVAs test indicate that age had a significant effect on ADF (F = 4.352, p = 0.038, partial eta-squared (ηp2) = 0.015) but not on APF (F = 0.430, p = 0.746, ηp2 = 0.001). Moreover, considering only the SP, a weak inverse correlation between ADF and HGS group ADF was found (rs = −0.27; p < 0.001). Factors such as the non-linear trend of growth in young SP could hinder the definition of the relationship between ankle ROM, age, and muscle strength. However, the appropriate consideration of age and muscle strength could facilitate the management of ankle ROM in PF of different ages.
Experience, Training Preferences, and Fighting Style Are Differentially Related to Measures of Body Composition, Strength, and Power in Male Brazilian Jiu Jitsu Athletes—A Pilot Study
Authors: Almeda Christian G. , Mangine Gerald T. , Green Zackary H. , Feito Yuri , French Duncan N.
Published: January 2023

To examine relationships between Brazilian Jiu Jitsu (BJJ) descriptors (belt rank, experience, gi preference, and fighting style), resistance training (RT) experience, and measures of body composition, strength (maximal handgrip, 3-5-repetition maximum [RM] in barbell glute bridge [GB], prone bench row [PBR], and bench press [BP]), and velocity (GB, PBR, and BP at 7 kg and 30–60% 1-RM), 13 experienced (4.3 ± 3.4 years) BJJ athletes were recruited for this cross-sectional, pilot study. Significant (p < 0.05) Kendall’s tau and Bayesian relationships were seen between belt rank and body fat percentage (τ = −0.53, BF10 = 6.5), BJJ experience and body fat percentage (τ = −0.44 to −0.66, BF10 = 2.6–30.8) and GB velocity (τ = −0.45 to −0.46, BF10 = 2.8–3.1), RT experience and strength (τ = 0.44 to 0.73, BF10 = 2.6–75.1) and velocity (τ = −0.44 to 0.47, BF10 = 2.6–3.3), gi preference-training and relative PBR strength (τ = 0.70, BF10 = 51.9), gi preference-competition and height and lean mass (τ = −0.57 to 0.67, BF10 = 5.3–12.4) and BP velocity (τ = −0.52 to 0.67, BF10 = 3.5–14.0). The relevance of body composition and performance measures to sport-specific training and research interpretation are differentially affected by a BJJ athlete’s experience (BJJ, belt rank, RT), gi preferences, and fighting style.
The Legal Transition towards a More Circular Electrical and Electronic Equipment Chain—A Case Study of The Netherlands
Authors: de Waal Ida Mae
Published: January 2023

The transition towards a circular economy in the EU requires that the legal framework does not create (legal) barriers, but rather enables or stimulates this transition. At this moment, however, the existing literature argues that the current legal system that governs the life cycle of materials and products—EU chemicals, product and waste legislation—might hamper the transition. This article looks into the legal framework for the transition of the product stream of electrical and electronic equipment (EEE) and more specifically into the general and specific applicable EU chemicals, product and waste legislation, as well as its implementation in the Netherlands. By means of both doctrinal and empirical legal research, this article identifies legal barriers, gaps and incentives in the current legal framework that governs the life cycle of EEE in light of the transition towards a circular economy (CE). To enable or stimulate the CE transition in the EEE chain, it appears that it would be desirable to improve the interaction within this legal system and better align it with the objectives of the CE and life cycle thinking. Moreover, this research shows that a different approach within EU chemicals, product and waste legislation could be beneficial for the CE transition. With regard to EEE, a holistic approach could enable a more circular EEE chain, either within the current sector-approach, or with a more product-specific or material-specific approach within the EU chemicals, product and waste legislation governing EEE.
Students’ Perceptions of Online Learning in the Post-COVID Era: A Focused Case from the Universities of Applied Sciences in China
Authors: Zhang Ye , Chen Xinrong
Published: January 2023

Currently, while most universities around the world have returned to offline teaching, most universities in China are still using online teaching. In the current educational context, Chinese universities switch between online and offline teaching modes at any time depending on the epidemic situation in their city. This paper discusses students’ perceptions of online learning in the post-COVID era in China. Based on the data collected from student questionnaires, the teaching and learning situation in the post-COVID era and student preferences for online learning are discussed. In addition to this, the statistics program JMP was used to perform the data analysis. The correlations among study characteristics, socio-economic factors, organisational and didactic design, and the acceptance and use of online learning are analysed. The results show that students spend more time in university courses in the post-COVID era than in previous academic years. Students prefer to study alone and at individual times that are set by themselves. Study characteristics and the socio-economic situation of the students are not related to the acceptance and usage behaviour of online learning. The organisational and didactic design of online learning is correlated with its acceptance. In the end, the reflection on opportunities for online learning in the post-COVID era is concluded.
An Improved Cellular Automata Traffic Flow Model Considering Driving Styles
Authors: Feng Tianjun , Liu Keyi , Liang Chunyan
Published: January 2023

An improved cellular automata model (CA model) considering driving styles is proposed to analyze traffic flow characteristics and study traffic congestion’s dissipation mechanism. The data were taken from a particular case in the Next Generation Simulation (NGSIM) program, which selected US-101 as the survey location from 7:50 a.m.–8:05 a.m. to investigate vehicle trajectory information. Different driving styles and the differences in vehicle parameters (speed, acceleration, deceleration, etc.) were obtained using principal component analysis and the k-means clustering method. The selected model was proposed for improvement based on analyzing the existing CA models and combining them with the actual road conditions. Considerations of driving styles and two operation mechanisms (over-acceleration and speed adaptation) were introduced in the improved model. The result obtained after the traffic simulation shows that the improved CA model is effective, and the mutual transformation of different traffic flow phases can be simulated. In the improved CA model, dissipating traffic congestion effectively and balancing the overall flow of the road are realized to improve the traffic capacity up to around 115% compared to the NaSch model and meet the demand of all kinds of drivers expecting to drive at the safest distance, which provides a theoretical basis for relieving traffic congestion. The various driving styles in terms of safety, comfort, and effectiveness are performed differently in the improved CA model. An aggressive driving style contributes to increasing traffic capacity up to around 181% compared to a calm driving style, while the calm style contributes to maintaining traffic flow stability.
Particle Swarm-Based Federated Learning Approach for Early Detection of Forest Fires
Authors: Supriya Y. , Gadekallu Thippa Reddy
Published: January 2023

Forests are a vital part of the ecological system. Forest fires are a serious issue that may cause significant loss of life and infrastructure. Forest fires may occur due to human or man-made climate effects. Numerous artificial intelligence-based strategies such as machine learning (ML) and deep learning (DL) have helped researchers to predict forest fires. However, ML and DL strategies pose some challenges such as large multidimensional data, communication lags, transmission latency, lack of processing power, and privacy concerns. Federated Learning (FL) is a recent development in ML that enables the collection and process of multidimensional, large volumes of data efficiently, which has the potential to solve the aforementioned challenges. FL can also help in identifying the trends based on the geographical locations that can help the authorities to respond faster to forest fires. However, FL algorithms send and receive large amounts of weights of the client-side trained models, and also it induces significant communication overhead. To overcome this issue, in this paper, we propose a unified framework based on FL with a particle swarm-optimization algorithm (PSO) that enables the authorities to respond faster to forest fires. The proposed PSO-enabled FL framework is evaluated by using multidimensional forest fire image data from Kaggle. In comparison to the state-of-the-art federated average model, the proposed model performed better in situations of data imbalance, incurred lower communication costs, and thus proved to be more network efficient. The results of the proposed framework have been validated and 94.47% prediction accuracy has been recorded. These results obtained by the proposed framework can serve as a useful component in the development of early warning systems for forest fires.
Review of Financing Mechanisms to Promote Decarbonization Alternatives in Rail and Inland Waterway Transport
Authors: Camargo-Díaz Clara Paola , Paipa-Sanabria Edwin , Zapata-Cortes Julian Andres , Briceño-Chaves Andres Mauricio , Serna-Castaño Cristian Fernando
Published: January 2023

The financial market has a strong influence on supporting the transition to a zero-emission transport system, as this sector requires large investments to implement low-emission technologies and infrastructure and to promote intermodality. This article presents the results obtained from a literature review on the financing mechanisms that have been used in different countries to finance alternatives to decarbonization in rail and inland waterway modes. For this purpose, databases such as Google Scholar, Scopus, MDPI, websites of governments and other related organizations were reviewed. Over 240 sources of information from articles and documents focusing on green finance in rail and inland waterway modes were reviewed. Our study identified many gaps in the literature on green transport financing. We also identified that in the databases consulted, it was possible to obtain more academic sources related to rail transport than inland waterway transport. Finally, an analysis is made of how implementation projects in the rail and inland waterway modes have been financed in Colombia.
Evolution of Green Finance: A Bibliometric Analysis through Complex Networks and Machine Learning
Authors: Maria Mariana Reis , Ballini Rosangela , Souza Roney Fraga
Published: January 2023

A fundamental structural transformation that must occur to break global temperature rise and advance sustainable development is the green transition to a low-carbon system. However, dismantling the carbon lock-in situation requires substantial investment in green finance. Historically, investments have been concentrated in carbon-intensive technologies. Nonetheless, green finance has blossomed in recent years, and efforts to organise this literature have emerged, but a deeper understanding of this growing field is needed. For this goal, this paper aims to delineate this literature’s existing groups and explore its heterogeneity. From a bibliometric coupling network, we identified the main groups in the literature; then, we described the characteristics of these articles through a novel combination of complex network analysis, topological measures, and a type of unsupervised machine learning technique called structural topic modelling (STM). The use of computational methods to explore literature trends is increasing as it is expected to be compatible with a large amount of information and complement the expert-based knowledge approach. The contribution of this article is twofold: first, identifying the most relevant articles in the network related to each group and, second, the most prestigious topics in the field and their contributions to the literature. A final sample of 3275 articles shows three main groups in the literature. The more mature is mainly related to the distribution of climate finance from the developed to the developing world. In contrast, the most recent ones are related to climate financial risks, green bonds, and the insertion of financial development in energy-emissions-economics models. Researchers and policy-makers can recognise current research challenges and make better decisions with the help of the central research topics and emerging trends identified from STM. The field’s evolution shows a clear movement from an international perspective to a nationally-determined discussion on finance to the green transition.
Urban Parks in Curitiba as Biodiversity Refuges of Montane Mixed Ombrophilous Forests
Authors: da Silva Santos Adriana , de Souza Inti , de Souza Jana Magaly Tesserolli , Schaffrath Valter Roberto , Galvão Franklin , Bohn Reckziegel Rafael
Published: January 2023

The assessment of the conservation status of urban forest remnants is essential for sustaining tree diversity in metropolitan cities. This study evaluated the composition and structure of forest remnants in four urban parks within the natural distribution of Montane Mixed Ombrophilous Forest in Curitiba (PR, Brazil). We allocated 66 plots of 100 m2 and recorded all trees with perimeters at breast height ≥ 15 cm. A total of 1256 individuals from 44 botanical families and 117 tree species were identified, of which three are alien species. Tree density ranged from 1670 to 2095 trees ha−1, while the density of standing dead trees varied between 90 and 188 trees ha−1. We experienced values for the Shannon diversity index between 3.00 and 3.52 nats ind−1, which are comparable to the values for other non-urban forest remnants. Non-pioneer species represented 84.6% of the tree community (99 spp.), and 76% were zoochoric species (89 spp.). The research findings feed the discussion on the need of specific and integrated measures for the management of the urban parks reserved to the conservation of tree diversity in a specific phytoecological formation, while considering aspects of climate change and historical anthropisation.