bluuebunny/crossref_metadata_2025 huggingface dataset:
A Methodological Approach to Assessing the Tribological Properties of Lubricants Using a Four-Ball Tribometer
Authors: Al-Quraan Tareq M. A. , Alfaqs Fadi , Haddad Jamil , Vojtov Viktor , Voitov Anton , Kravtsov Andrey , Miroshnyk Oleksandr , Kondratiev Andrii
Published: October 2023

Based on the analysis of standards for the testing of lubricants, both liquid and plastic, on a four-ball tribometer, and the analysis of the parameters by which lubricants are evaluated, this paper proposes a methodology and an integral parameter for the estimation of tribological properties. The methodological approach proposed in this paper allows for the integration of a variety of parameters provided in the standards for the testing of lubricants into one indicator. Herein, we show that the developed technique is based on the energy approach and takes into account the specific wear work of the test material (steel balls) in the lubricating medium to be investigated. The results of laboratory tests of a wide range of lubricants are presented: hydraulic fluids, motor and transmission oils of various purposes and classifications. It is shown that the magnitude of the integral parameter can be used to assess the effectiveness of anti-wear and anti-scuff additives in base lubricants, as well as the ranges of their applications. This allows for differentiation and quantitative evaluation of the effectiveness of such additives. The obtained results allow us to state that all tests according to the developed method are reproducible and homogeneous, which is confirmed using the Cochran criterion. The coefficient of variation during testing does not exceed 18%. We show that the presented methodology and the integral parameter can be used in the first stage of the laboratory selection tests of new lubricants and additives of various origins, reducing the costs of their development and implementation.
Progress and Challenges of Integrated Machine Learning and Traditional Numerical Algorithms: Taking Reservoir Numerical Simulation as an Example
Authors: Chen Xu , Zhang Kai , Ji Zhenning , Shen Xiaoli , Liu Piyang , Zhang Liming , Wang Jian , Yao Jun
Published: October 2023

Machine learning techniques have garnered significant attention in various engineering disciplines due to their potential and benefits. Specifically, in reservoir numerical simulations, the core process revolves around solving the partial differential equations delineating oil, gas, and water flow dynamics in porous media. Discretizing these partial differential equations via numerical methods is one cornerstone of this simulation process. The synergy between traditional numerical methods and machine learning can enhance the precision of partial differential equation discretization. Moreover, machine learning algorithms can be employed to solve partial differential equations directly, yielding rapid convergence, heightened computational efficiency, and accuracies surpassing 95%. This manuscript offers an overview of the predominant numerical methods in reservoir simulations, focusing on integrating machine learning methodologies. The innovations in fusing deep learning techniques to solve reservoir partial differential equations are illuminated, coupled with a concise discussion of their inherent advantages and constraints. As machine learning continues to evolve, its conjunction with numerical methods is poised to be pivotal in addressing complex reservoir engineering challenges.
An Inventory Model for Growing Items When the Demand Is Price Sensitive with Imperfect Quality, Inspection Errors, Carbon Emissions, and Planned Backorders
Authors: De-la-Cruz-Márquez Cynthia Griselle , Cárdenas-Barrón Leopoldo Eduardo , Porter J. David , Loera-Hernández Imelda de Jesús , Smith Neale R. , Céspedes-Mota Armando , Treviño-Garza Gerardo , Bourguet-Díaz Rafael Ernesto
Published: October 2023

Inventory models that consider environmental and quality concerns have received some attention in the literature, yet no model developed to date has investigated these features in combination with growing items. Therefore, there is a need to incorporate these three relevant aspects together in a single inventory model to support decisions, compare results, and obtain new knowledge for the complexities of the real world. Moreover, current sustainable inventory management practices aim at mitigating the ecological consequences of an industry while preserving its profitability. The present study aligns with this perspective and introduces an economic order quantity (EOQ) model that considers imperfect quality while also accounting for sustainability principles. More specifically, the model addresses growing items, which have a demand dependent on selling price and the unique ability to grow while being stored in inventory. Additionally, the analysis acknowledges the possibility of classification errors during the inspection process, encompassing both Type-I and Type-II inspection errors. Furthermore, the model permits shortages and ensures that any shortage is completely fulfilled through backorders. The optimization model produces an optimal solution for the proposed model that is derived by optimizing three decision variables: order quantity of newborn items, backordering quantity, and the selling price of perfect items. A numerical example is presented, and the results are discussed. Finally, a sensitivity analysis on variations of parameters such as Type-I and Type-II errors shows that it is advantageous to reduce the percentage of good items that are misclassified as defective (i.e., Type-I error). As there is a direct impact of such errors on sales, it is imperative to address and mitigate this issue. When defective items are mistakenly classified as good Type-II errors, adverse consequences ensue, including a heightened rate of product returns. This, in turn, results in additional costs for the company, such as penalties and diminished customer confidence. Hence, the findings clearly suggest that the presence of Type-I and Type-II errors has a negative effect on the ordering policy and on the total expected profit. Moreover, this work provides a model that can be used with any growing item (including plants), so the decision-maker has the opportunity to analyze a wide variety of scenarios.
Emission Reduction and Channel Decisions in a Two-Echelon Supply Chain Considering Service Spillovers
Authors: Chen Xiaoxu , Wang Jingwei , Xu Peng , Walker Thomas , Yang Guoqiang
Published: October 2023

The development of e-commerce and the green economy has prompted suppliers of green products to introduce internet channels by which products are directly sold to consumers. However, the emergence of “price wars” and “free riding” between the two channels after the introduction of online channels may affect the stability of the green supply chain. This paper uses optimization theory to investigate the impact of service spillover effects and different channel structures on the optimal decision of supply chain members in a Stackelberg game. By comparing the equilibrium outcomes of the single-channel and dual-channel supply chain in a setting with and without retail services, we observe that the supplier prefers to encroach on the market when services that retail locations provide largely spillover to and benefit the direct sales channel. Contrary to popular belief, a higher degree of service spillovers is beneficial for the retailer to achieve more returns under the dual-channel structure, whereas supplier encroachment will lead to a decline in the service level if the spillover degree is relatively low. In addition, the emission reduction level of products under supplier encroachment is always higher than that employed in the single-channel structure if consumers have both low-carbon preference and a high degree of service sensitivity. Finally, we expand our discussion by introducing the carbon cap-and-trade (CCT) mechanism to compare the conditions for achieving Pareto improvement under supplier encroachment. These results can provide helpful insights for decision-makers in supply chain management to implement effective channel selection and achieve sustainable development.
The Relationship between Acid Production and the Microbial Community of Newly Produced Coal Gangue in the Early Oxidation Stage
Authors: Zhu Qi , Ruan Mengying , Hu Zhenqi , Miao Kexin , Ye Chun
Published: October 2023

Coal gangue is a solid waste formed during coal production, and the acid mine drainage it generates during open-pit storage severely pollutes the ecological environment of mining areas. Microorganisms play a crucial catalytic role in acidification, and their species and gene functions change during the oxidation process of coal gangue. In this study, the changes in microbial community structure were investigated during the initial acidification process for newly produced gangue exposed to moisture by monitoring the changes in pH, EC, sulfate ion concentration, and the iron oxidation rate of gangue leaching solutions. Moreover, the composition and functional abundance of microbial communities on the surface of the gangue were analyzed with rainfall simulation experiments and 16S rRNA sequencing. The study yielded the following findings: (1) The critical period for newly produced gangue oxidation spanned from 0~15 d after its exposure to water; the pH of leaching solutions decreased from 4.65 to 4.09 during this time, and the concentration and oxidation rate of iron in the leaching solutions remained at low levels, indicating that iron oxidation was not the main driver for acidification during this stage. (2) When the gangue was kept dry, Burkholderia spp. dominated the gangue microbial community. When the gangue was exposed to moisture, the rate of acidification accelerated, and Pseudomonas replaced Burkholderia as the dominant genus in the community. (3) In terms of gene function, the microbial community of the acidified gangue had stronger nitrogen cycling functions, and an increase in the abundance of microorganisms related to the sulfur cycle occurred after day 15 of the experiment. The microbial community in the acidified gangue had more stress resistance than the community of the newly formed gangue, but its potential to decompose environmental pollutants decreased.
Optimization of Alkali Treatment for Production of Fermentable Sugars and Phenolic Compounds from Potato Peel Waste Using Topographical Characterization and FTIR Spectroscopy
Authors: Mushtaq Qudsia , Joly Nicolas , Martin Patrick , Qazi Javed Iqbal
Published: October 2023

Potato peel waste (PPW) was utilized as a bio-template for the production of valuable compounds such as reducing sugars (RS), total sugar (TS) and total phenolic compounds (TPC). Two methods of alkali treatments, i.e., chemical (NaOH) and thermochemical (NaOH assisted with autoclaving) processes, were employed for the deconstruction of PPW. Response surface methodology (RSM) was used to study the effects of alkali concentration (0.6–1.0 w/v), substrate concentration (5–15 g) and time (4–8 h) on the extraction of RS, TS and TP from PPW. The application of alkali plus steam treatment in Box-Behnken design (BBD) with three levels yielded the optimum releases of RS, TS and TP as 7.163, 28.971 and 4.064 mg/mL, respectively, corresponding to 10% substrate loading, in 0.6% NaOH for 8 h. However, the alkali treatment reported optimum extractions of RS, TS and TP as 4.061, 17.432 and 2.993 mg/mL, respectively. The thermochemical pretreatment was proven a beneficial process as it led to higher productions of TP. FTIR and SEM were used to analyze the deterioration levels of the substrate. The present work was used to explore the sustainable management of PPW, which is a highly neglected substrate bioresource but is excessively dumped in open environment, raising environmental concerns. The cost-effective methods for the breakdown of PPW starch into fermentable sugars might be utilized to extract valuable compounds.
Biological Activities of Citrus aurantium Leaf Extract by Optimized Ultrasound-Assisted Extraction
Authors: Wang Guey-Horng , Huang Chun-Ta , Huang Hsiu-Ju , Tang Chi-Hsiang , Chung Ying-Chien
Published: October 2023

Several studies have explored the biological activities of Citrus aurantium flowers, fruits, and seeds, but the bioactivity of C. aurantium leaves, which are treated as waste, remains unclear. Thus, this study developed a pilot-scale ultrasonic-assisted extraction process using the Box–Behnken design (BBD) for the optimized extraction of active compounds from C. aurantium leaves, and their antityrosinase, antioxidant, antiaging, and antimicrobial activities were evaluated. Under optimal conditions in a 150× scaleup configuration (a 30 L ultrasonic machine) of a pilot plant, the total phenolic content was 69.09 mg gallic acid equivalent/g dry weight, which was slightly lower (3.17%) than the theoretical value. The half maximal inhibitory concentration of C. aurantium leaf extract (CALE) for 2,2-diphenyl-1-picrylhydrazyl–scavenging, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)–scavenging, antityrosinase, anticollagenase, antielastase and anti-matrix metalloprotein-1 activities were 123.5, 58.5, 181.3, 196.4, 216.3, and 326.4 mg/L, respectively. Moreover, the minimal inhibitory concentrations for bacteria and fungi were 150–350 and 500 mg/L, respectively. In total, 17 active compounds were detected in CALE—with linalool, linalyl acetate, limonene, and α-terpineol having the highest concentrations. Finally, the overall transdermal absorption and permeation efficiency of CALE was 95.9%. In conclusion, our CALE demonstrated potential whitening, antioxidant, antiaging, and antimicrobial activities; it was also nontoxic and easily absorbed into the skin as well as inexpensive to produce. Therefore, it has potential applications in various industries.
Nanoparticles of a Pyrazolo-Pyridazine Derivative as Potential EGFR and CDK-2 Inhibitors: Design, Structure Determination, Anticancer Evaluation and In Silico Studies
Authors: Hashem Heba E. , Amr Abd El-Galil E. , Almehizia Abdulrahman A. , Naglah Ahmed M. , Kariuki Benson M. , Eassa Heba A. , Nossier Eman S.
Published: October 2023

The strategic planning of this study is based upon using the nanoformulation method to prepare nanoparticles 4-SLNs and 4-LPHNPs of the previously prepared 4,5-diphenyl-1H-pyrazolo[3,4-c]pyridazin-3-amine (4) after confirming its structure with single crystal X-ray analysis. These nanoparticles exhibited promising cytotoxic activity against HepG-2, HCT-116 and MCF-7 cancer cell lines in comparison with the reference doxorubicin and the original derivative 4. Moreover, their inhibitory assessment against EGFR and CDK-2/cyclin A2 displayed improved and more favorable impact than the parent 4 and the references. Detection of their influence upon cancer biomarkers revealed upregulation of Bax, p53 and caspase-3 levels and downregulation of Bcl-2 levels. The docking simulation demonstrated that the presence of the pyrazolo[3,4-c]pyridazin-3-amine scaffold is amenable to enclosure and binding well within EGFR and CDK-2 receptors through different hydrophilic interactions. The pharmacokinetic and physicochemical properties of target 4 were also assessed with ADME investigation, and the outcome indicated good drug-like characteristics.
Remote Residual Instability Evaluation of Comb-Based Precise Frequency Transmission for Optical Clock
Authors: Li Zhaolong , Gui Sibo , Wu Haitao , Guo Ziyu , Zhao Jianye
Published: October 2023

Optical clocks can be used as the absolute frequency reference due to their high accuracy and stability. In a precise optical clock transmission system, the instability loss of the link is usually evaluated by beating the remote optical signal with the reference clock, which is not suitable for real frequency distribution applications. Therefore, it is necessary to assess the performance directly at the remote site for the optical frequency transfer, because the two sites of the link are usually not co-located. In this paper, we proposed a comb-based remote residual instability evaluation scheme. Two coherent optical combs with different wavelengths were extracted from a frequency stable comb and transmitted after multiplexing. The residual instability was evaluated directly at the remote site by measuring the phase fluctuation difference between the two combs. We achieved 8.61 × 10−19 at 40,000 s over a 10 km fiber link, reaching the instability of optical clocks. These results revealed that our scheme can evaluate optical clock frequency transmission directly at the remote site, which made the method truly practical.
Historical Ethnobotany: Interpreting the Old Records
Authors: Kalle Raivo , Sõukand Renata
Published: October 2023

For centuries, knowledge about the use of plants has been collected, published, or simply left in archives [...]
Early Detection of Rice Blast Using a Semi-Supervised Contrastive Unpaired Translation Iterative Network Based on UAV Images
Authors: Lin Shaodan , Li Jiayi , Huang Deyao , Cheng Zuxin , Xiang Lirong , Ye Dapeng , Weng Haiyong
Published: October 2023

Rice blast has caused major production losses in rice, and thus the early detection of rice blast plays a crucial role in global food security. In this study, a semi-supervised contrastive unpaired translation iterative network is specifically designed based on unmanned aerial vehicle (UAV) images for rice blast detection. It incorporates multiple critic contrastive unpaired translation networks to generate fake images with different disease levels through an iterative process of data augmentation. These generated fake images, along with real images, are then used to establish a detection network called RiceBlastYolo. Notably, the RiceBlastYolo model integrates an improved fpn and a general soft labeling approach. The results show that the detection precision of RiceBlastYolo is 99.51% under intersection over union (IOU0.5) conditions and the average precision is 98.75% under IOU0.5–0.9 conditions. The precision and recall rates are respectively 98.23% and 99.99%, which are higher than those of common detection models (YOLO, YOLACT, YOLACT++, Mask R-CNN, and Faster R-CNN). Additionally, external data also verified the ability of the model. The findings demonstrate that our proposed model can accurately identify rice blast under field-scale conditions.
A Review of Interactions between Plants and Whitefly-Transmitted Begomoviruses
Authors: Naveed Hassan , Islam Waqar , Jafir Muhammad , Andoh Vivian , Chen Liang , Chen Keping
Published: October 2023

The transmission of plant viruses from infected to healthy host plants is a process in which insects play a major role, using various transmission strategies. Environmental factors have an impact on the transmission of viruses and the subsequent development of infections or diseases. When viruses are successful, plant virus diseases can reach epidemic proportions. Many plants across different regions are vulnerable to viral infections transmitted by the whitefly vector. Begomoviruses, which are transmitted by whiteflies, represent a significant threat to agriculture worldwide. The review highlights the mechanisms of virus acquisition and transmission by whiteflies and explores the factors influencing these interactions. Understanding the impacts of these changes is crucial for managing the spread of pests and mitigating damage to crops. It underscores the need for continued research to elucidate the mechanisms driving plant–insect–virus interactions and to identify new approaches for sustainable pest management.
ASVmaker: A New Tool to Improve Taxonomic Identifications for Amplicon Sequencing Data
Authors: Plessis Clément , Jeanne Thomas , Dionne Antoine , Vivancos Julien , Droit Arnaud , Hogue Richard
Published: October 2023

The taxonomic assignment of sequences obtained by high throughput amplicon sequencing poses a limitation for various applications in the biomedical, environmental, and agricultural fields. Identifications are constrained by the length of the obtained sequences and the computational processes employed to efficiently assign taxonomy. Arriving at a consensus is often preferable to uncertain identification for ecological purposes. To address this issue, a new tool called “ASVmaker” has been developed to facilitate the creation of custom databases, thereby enhancing the precision of specific identifications. ASVmaker is specifically designed to generate reference databases for allocating amplicon sequencing data. It uses publicly available reference data and generates specific sequences derived from the primers used to create amplicon sequencing libraries. This versatile tool can complete taxonomic assignments performed with pre-trained classifiers from the SILVA and UNITE databases. Moreover, it enables the generation of comprehensive reference databases for specific genes in cases where no directly applicable database exists for taxonomic classification tools.
Modeling the Effects of NO3−, H+ and Potential HNE on Nitro TAP through Response Surface Methodology
Authors: Portillo Carlos , Gallegos Sandra , Salazar Iván , Jamett Ingrid , Castillo Jonathan , Cerecedo-Sáenz Eduardo , Salinas-Rodríguez Eleazar , Saldaña Manuel
Published: October 2023

Nitration is a chemical process that introduces a nitro group into a molecule, which modifies properties of organic compounds, impacting their reactivity and physical attributes. In copper mining, elevated nitrate levels present operational difficulties, impacting recovery percentages and leading to the deterioration of organic extractants. Historically, various elements such as intense electrolyte acidity, sunlight exposure, Mn presence, high temperatures, and microbial activity have been linked to this degradation. Over time, numerous methods, including the introduction of additives and the implementation of recirculation approaches, have been developed to address the nitration issue. Mathematical modeling of nitration (like response surface methodology, RSM) based on explanatory variables, such as NO3−, H+, and Potential HNE, has the potential to obtain a better understanding of nitration processes. This study highlights the effectiveness of the TAP Test in assessing the aggressiveness level of nitrates in aqueous solutions and, given the increase in complexity of the minerals in mining sites, it is plausible to anticipate a rise in usage of these tests within hydrometallurgical plants in near future. Using RSM and design of experiments proved robust in examining the nitration phenomenon. Maximum TAP nitration occurred at elevated levels of NO3−, H+, and Potential HNE, with an experimental peak of 17.9%; this contrasts with the theoretical 16.25% from the fitted model (R2≅90%).
Model Error (or Ambiguity) and Its Estimation, with Particular Application to Loss Reserving
Authors: Taylor Greg , McGuire Gráinne
Published: October 2023

This paper is concerned with the estimation of forecast error, particularly in relation to insurance loss reserving. Forecast error is generally regarded as consisting of three components, namely parameter, process and model errors. The first two of these components, and their estimation, are well understood, but less so model error. Model error itself is considered in two parts: one part that is capable of estimation from past data (internal model error), and another part that is not (external model error). Attention is focused here on internal model error. Estimation of this error component is approached by means of Bayesian model averaging, using the Bayesian interpretation of the LASSO. This is used to generate a set of admissible models, each with its prior probability and likelihood of observed data. A posterior on the model set, conditional on the data, may then be calculated. An estimate of model error (for a loss reserve estimate) is obtained as the variance of the loss reserve according to this posterior. The population of models entering materially into the support of the posterior may turn out to be “thinner” than desired, and bootstrapping of the LASSO is used to increase this population. This also provides the bonus of an estimate of parameter error. It turns out that the estimates of parameter and model errors are entangled, and dissociation of them is at least difficult, and possibly not even meaningful. These matters are discussed. The majority of the discussion applies to forecasting generally, but numerical illustration of the concepts is given in relation to insurance data and the problem of insurance loss reserving.
Adaptation of YOLOv7 and YOLOv7_tiny for Soccer-Ball Multi-Detection with DeepSORT for Tracking by Semi-Supervised System
Authors: Vicente-Martínez Jorge Armando , Márquez-Olivera Moisés , García-Aliaga Abraham , Hernández-Herrera Viridiana
Published: October 2023

Object recognition and tracking have long been a challenge, drawing considerable attention from analysts and researchers, particularly in the realm of sports, where it plays a pivotal role in refining trajectory analysis. This study introduces a different approach, advancing the detection and tracking of soccer balls through the implementation of a semi-supervised network. Leveraging the YOLOv7 convolutional neural network, and incorporating the focal loss function, the proposed framework achieves a remarkable 95% accuracy in ball detection. This strategy outperforms previous methodologies researched in the bibliography. The integration of focal loss brings a distinctive edge to the model, improving the detection challenge for soccer balls on different fields. This pivotal modification, in tandem with the utilization of the YOLOv7 architecture, results in a marked improvement in accuracy. Following the attainment of this result, the implementation of DeepSORT enriches the study by enabling precise trajectory tracking. In the comparative analysis between versions, the efficacy of this approach is underscored, demonstrating its superiority over conventional methods with default loss function. In the Materials and Methods section, a meticulously curated dataset of soccer balls is assembled. Combining images sourced from freely available digital media with additional images from training sessions and amateur matches taken by ourselves, the dataset contains a total of 6331 images. This diverse dataset enables comprehensive testing, providing a solid foundation for evaluating the model’s performance under varying conditions, which is divided by 5731 images for supervised system and the last 600 images for semi-supervised. The results are striking, with an accuracy increase to 95% with the focal loss function. The visual representations of real-world scenarios underscore the model’s proficiency in both detection and classification tasks, further affirming its effectiveness, the impact, and the innovative approach. In the discussion, the hardware specifications employed are also touched on, any encountered errors are highlighted, and promising avenues for future research are outlined.
SGN-YOLO: Detecting Wood Defects with Improved YOLOv5 Based on Semi-Global Network
Authors: Meng Wei , Yuan Yilin
Published: October 2023

Object detection based on wood defects involves using bounding boxes to label defects in the surface image of the wood. This step is crucial before the transformation of wood products. Due to the small size and diverse shape of wood defects, most previous object detection models are unable to filter out critical features effectively. Consequently, they have faced challenges in generating adequate contextual information to detect defects accurately. In this paper, we proposed a YOLOv5 model based on a Semi-Global Network (SGN) to detect wood defects. Unlike previous models, firstly, a lightweight SGN is introduced in the backbone to model the global context, which can improve the accuracy and reduce the complexity of the network at the same time; the backbone is embedded with the Extended Efficient Layer Aggregation Network (E-ELAN), which continuously enhances the learning ability of the network; and finally, the Efficient Intersection and Merger (EIOU) loss is used to solve the problems of slow convergence speed and inaccurate regression results. Experimental results on public wood defect datasets demonstrated that our approach outperformed existing target detection models. The mAP value was 86.4%, a 3.1% improvement over the baseline network model, a 7.1% improvement over SSD, and a 13.6% improvement over Faster R-CNN. These results show the effectiveness of our proposed methodology.
Design and Finite Element Simulation of a Novel 3D-CMUT Device for Simultaneous Sensing of In-Plane and Out-of-Plane Displacements of Ultrasonic Guided Waves
Authors: Zhang Sai , Lu Wei , Wang Ailing , Hao Guodong , Wang Renxing , Yilmaz Mehmet
Published: October 2023

In this study, we introduce a physical model of a three-dimensional (3D) guided wave sensor called 3D-CMUT, which is based on capacitive micro-machined ultrasonic transducers (CMUTs). This 3D-CMUT sensor is designed to effectively and simultaneously obtain 3D vibration information about ultrasonic guided waves in the out-of-plane (z-direction) and in-plane (x and y-directions). The basic unit of the 3D-CMUT is much smaller than the wavelength of the guided waves and consists of two orthogonal comb-like CMUT cells and one piston-type CMUT cell. These cells are used to sense displacement signals in the x, y, and z-directions. To ensure proper functioning of the 3D-CMUT unit, the resonant frequencies of the three composed cells are set to be identical by adjusting the microstructural parameters appropriately. Moreover, the same sensitivity in the x, y, and z-directions is theoretically achieved by tuning the amplification parameters in the external circuit. We establish a transient analysis model of the 3D-CMUT using COMSOL finite element simulation software to confirm its ability to sense multimode ultrasonic guided waves, including A0, S0, and SH0 modes. Additionally, we simulate the ball drop impact acoustic emission signal on a plate to demonstrate that the 3D-CMUT can not only utilize in-plane information for positioning but also out-of-plane information. The proposed 3D-CMUT holds significant potential for applications in the field of structural health monitoring (SHM).
Assessing Vehicle Wandering Effects on the Accuracy of Weigh-in-Motion Measurement Based on In-Pavement Fiber Bragg Sensors through a Hybrid Sensor-Camera System
Authors: Yang Xinyi , Wang Xingyu , Podolsky Joseph , Huang Ying , Lu Pan
Published: October 2023

Weigh-in-motion (WIM) systems are essential for efficient transportation and monitoring parameters such as vehicle number, speed, and weight to ensure regulatory compliance and enhance road safety. Recently, WIM measurements using the Glass Fiber Reinforced Polymer Fiber Bragg Grating (GFRP-FBG) sensors have shown robustness and effectiveness. However, the accuracy of weight evaluation using the WIM systems based on GFRP-FBG sensors can be significantly influenced by the vehicle-wandering effect, which introduces uncertainties in wheel position determination and weight calculations. This paper assessed the impact of vehicle wandering on the accuracy of a WIM measurement system based on GFRP-FBG sensors by utilizing a new hybrid sensor-camera system that integrates roadside cameras and in-pavement GFRP-FBG sensors. The detailed methodology and framework of the developed hybrid system are introduced, followed by field testing on Highway I-94 in the United States. The field testing results indicate that by using the hybrid system, the wheel load detection accuracy of the WIM system based on GFRP-FBG sensors can be controlled to be a Type I or Type III WIM according to the ASTM 1318E-09 standard, with an average accuracy ranging from 87.83% to 94.65%. At the same time, when the wander distance is less than or equal to 9 cm, the developed WIM system proves to be very cost-effective as it only comprises two GFRP-FBG sensors, one temperature FBG sensor, and one camera. These findings indicate the practical potential to enhance the accuracy of WIM systems based on GFRP-FBG sensors designed for highways for low-coast, reliable, and accurate measurements by addressing vehicle wandering effects.
Co-Channel Compatibility Analysis of IMT Networks and Digital Terrestrial Television Broadcasting in the Frequency Range 470–694 MHz Based on Monte Carlo Simulation
Authors: Taha Hussein , Vári Péter , Nagy Szilvia
Published: October 2023

According to Resolution 235 adopted during the World Radiocommunication Conference 2015 (WRC-15) and the preliminary agenda item 1.5 of WRC-2023, the International Telecommunication Union Radiocommunication Sector (ITU-R) has been entrusted to carry out sharing and compatibility studies between broadcasting and mobile services in the frequency range 470–694 MHz in Region 1. This study specifically focuses on evaluating electromagnetic compatibility in potential co-channel sharing scenarios between Digital Terrestrial Television Broadcasting (DTTB) and International Mobile Telecommunications (IMT) systems within the 470–694 MHz frequency band that may arise in the foreseeable future. To assess the conditions for coexistence, a Monte Carlo simulation method implemented through the SEAMCAT software version 5.4.2 is employed, examining six potential interference scenarios. The simulation results yield the minimum coordination distance required between IMT and DTTB services in the 470–694 MHz band based on the protection criteria to ensure harmonious coexistence while maintaining satisfactory performance. Furthermore, the study investigates the impact of various factors such as transmitter power, antenna heights, coverage radius, antenna discrimination, and antenna tilt angle on the separation distances. The focus lies primarily on critical interference scenarios across neighboring countries’ borders. The simulation outcomes confirm that sharing the same frequency band between IMT and DTTB networks would result in significant mutual interference. Nevertheless, carefully analyzing diverse parameters and assumptions helped provide recommendations to reduce the required separation distances. These findings are valuable for broadcasters, mobile operators, and regulators in establishing the technical coexistence conditions for DTTB and IMT in the new band.
Overcoming Periodic Stripe Noise in Infrared Linear Array Images: The Fourier-Assisted Correlative Denoising Method
Authors: Chen Weicong , Li Bohan
Published: October 2023

Infrared linear array detectors frequently experience vertical, low-frequency, and periodic stripe noise during imaging, stemming from electro-mechanical interference. Unlike conventional periodic disturbances, this interference showcases long periodicities and is uniquely columnar in orientation. Its presence, especially within the low-frequency domain, renders conventional filtering techniques ineffective and, at times, detrimental to image quality. Addressing this challenge, we introduce Fourier-Assisted Correlative Denoising (FACD), a correlation-centric denoising approach tailored for such unique interference patterns. This mechanism begins with the capture of a pure background image, inclusive of periodic noise, during the non-uniform correction phase of the infrared detector. Leveraging the noise’s frequency domain attributes, we extract a one-dimensional single-cycle noise signal. The infrared image is subsequently segmented into parts, and using the detected noise periodicity, the one-dimensional signals for each segment are computed. By leveraging the correlation between these signals and the benchmark one-dimensional noise pattern, we ascertain the noise profile within each segment. This profile is then employed for spatial domain denoising across the entire image frame. Empirical assessments confirm that the FACD outperforms contemporary denoising techniques by augmenting the peak signal-to-noise ratio by approximately 2.5 dB, underscoring its superior robustness. Furthermore, in light of its specificity to this noise model, FACD rapidly denoises high-resolution real infrared linear array scans, thus meeting the stringent real-time and resolution imperatives of advanced infrared linear array scanning apparatuses.
Untargeted Screening of Per- and Polyfluoroalkyl Substances (PFASs) in Airborne Particulate of Three Italian E-Waste Recycling Facilities
Authors: Barola Carolina , Bucaletti Elisabetta , Moretti Simone , Buiarelli Francesca , Simonetti Giulia , Lucarelli Franco , Goracci Laura , Lorenzetti Stefano , Di Filippo Patrizia , Pomata Donatella , Riccardi Carmela , Galarini Roberta
Published: October 2023

Poly- and perfluorinated alkyl substances (PFASs) are widely used in the electrical and electronic appliance industry to the point that waste of electrical and electronic equipment (WEEE), also known as e-waste, creates significant potential for PFAS exposure (by inhalation, ingestion, or dermal exposure) for people handling and recycling e-waste. The aim of this work was the development of an untargeted analytical approach in order to detect the presence of possible unknown PFASs in particulate matter collected in three Italian e-waste facilities through liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-HR-MS/MS) in negative ionization mode. By means of three acquisition experiments, nine compounds were detected as candidate PFASs, and three were definitively confirmed by comparison with their authentic standards. Among these, bistriflimide (bis (trifluoromethylsulfonyl) imide), an ionic liquid with several promising technological applications, was the most abundant compound detected in all three recycling plants. This is the first study associating the presence of fluorinated ionic liquids with e-waste, and as these chemicals are not only toxic and persistent but also highly mobile, our results indicate the need to include them in future PFAS research. Only further data on their actual environmental diffusion will determine whether they are emerging pollutants or not.
Breaking the Silence: Perceived Barriers to Safeguarding Child and Young Athletes in Uganda and a Rights-Based Framework for Positive Change
Authors: Kisakye Eva Tumwiine , Chatziefstathiou Dikaia , Tuakli-Wosornu Yetsa A.
Published: October 2023

Over 8 million children in Uganda are considered vulnerable to various forms of maltreatment, of which sexual violence is experienced by 26 girls daily. In the context of Ugandan sport, the types and magnitude of violence against child and young athletes is yet to be determined. The study aims to: (1) examine the barriers associated with prioritizing and implementing policies and programs to safeguard child and young athletes against harassment and abuse in Uganda as perceived by local stakeholders across Ugandan sport, and (2) offer a rights-based framework for implementing positive change in sport safeguarding in Uganda and other countries of similar cultural backgrounds. The study includes eleven (n = 11) purposively selected participants: athletes, coaches, medical practitioners, and policy makers, all born and living in Uganda. This is a qualitative inquiry that involves online in-depth interviews. The Consolidated Framework for Implementation Research (CFIR) guides our exploratory analysis to examine context-specific barriers to better inform key recommendations for interventions. A rights-based, multi-contextual framework (TRAUMA) with multi-stakeholder engagement is proposed as a culturally tailored response for the safeguarding of child and young athletes in Uganda and other similar cultural backgrounds.
Neonatal Hypoxic-Ischemic Encephalopathy Grading from Multi-Channel EEG Time-Series Data Using a Fully Convolutional Neural Network
Authors: Yu Shuwen , Marnane William P. , Boylan Geraldine B. , Lightbody Gordon
Published: October 2023

A deep learning classifier is proposed for grading hypoxic-ischemic encephalopathy (HIE) in neonates. Rather than using handcrafted features, this architecture can be fed with raw EEG. Fully convolutional layers were adopted both in the feature extraction and classification blocks, which makes this architecture simpler, and deeper, but with fewer parameters. Here, two large (335 h and 338 h, respectively) multi-center neonatal continuous EEG datasets were used for training and testing. The model was trained based on weak labels and channel independence. A majority vote method was used for the post-processing of the classifier results (across time and channels) to increase the robustness of the prediction. A dimension reduction tool, UMAP, was used to visualize the model classification effect. The proposed system achieved an accuracy of 86.09% (95% confidence interval: 82.41–89.78%), an MCC of 0.7691, and an AUC of 86.23% on the large unseen test set. Two convolutional neural network architectures which utilized time-frequency distribution features were selected as the baseline as they had been developed or tested on the same datasets. A relative improvement of 23.65% in test accuracy was obtained as compared with the best baseline. In addition, if only one channel was available, the test accuracy was only reduced by 2.63–5.91% compared with making decisions based on the eight channels.
Vaccine Development against Infectious Diseases: State of the Art, New Insights, and Future Directions
Authors: Conceição Silva Fatima , De Luca Paula Mello , Lima-Junior Josué da Costa
Published: October 2023

In the 18th century, English physician Edward Jenner laid the foundation for modern vaccination by achieving protection against variola [...]
Forestry Insights of Some Asian and European Countries: National Forest Harvesting Strategies and New Approaches
Authors: LOTFALİAN Majid , ERLER Jorn , PENTEK Tibor , AKAY Abdullah Emin , PİCHİO Rodolfo , PORŠİNSKY Tomislav
Published: October 2023

As forestry approaches have been formed according to the demands and aspirations of the society, the forest sector implies different concerns such as social, economic, and environmental. Harvesting and extraction of wood at low cost, protection of stands against degradation and changes in land use, proper implementation of afforestation and forest extension, conservation of endemic species, preservation of soil, providing jobs, and supporting national and domestic development have a different priority for foresters, depending on the time and area conditions. Of course, all of these have always been discussed by the shareholders in the forest sector with the main attention to forest sustainability. However, the question is: Are forestry approaches compatible with the changes in the world today? With increasing environmental concerns, as discussed at the Glasgow 2021 Conference, the importance of forests and their protection has doubled, and it seems that forestry practices in the world need a new approach. In addition to climate change, increasing human population and regional and global economic changes affect the use of forests and the form of forest management and utilization. This paper aims to take an analytical look at this issue and examine the current situation in five countries (Iran, Germany, Croatia, Turkiye and Italy). It was also targeted with the help of the DPSIR Framework to elaborate on the social consequences of the situation, and an analysis was presented about what to do or not. This paper emphasizes that forest managers and policymakers need to modify and adapt the plans and methods in a way that is appropriate to the progress of time and its changes, while protecting forests and ensuring their sustainability, limiting non-professionals from involving directly in the decision-making process.
Development of the methodology for the formation of the Statement of Financial Results in the system of Russian accounting standards
Authors:   Federal State Autonomous Educational Institution of Higher Education “Lobachevsky State University of Nizhni Novgorod”, Nizhny Novgorod, Russia, Druzhilovskaya T.Y.
Published: October 2023

The article examines methodological approaches to the formation of the most important reporting form that characterizes the performance of organizations — the Report on Financial Results. The program for the development of federal accounting standards provides for the adoption of a standard dedicated to financial statements, which, among other things, will contain regulations for the formation of a Report on financial results. Currently, Draft FSBU 4/2023 “Accounting (financial) statements” has been developed and published for discussion. This article examines the methodological approaches presented in this Project to the preparation of the Statement of Financial Performance. Comparison of the regulations for the formation of the Statement of Financial Results proposed in the FSBU Draft 4/2023 with methodological approaches to the formation of this reporting form in the current PBU 4/99 “Accounting statements of the organization” and the Order of the Ministry of Finance of Russia No. 66n dated July 2, 2010 “On Forms of Accounting Statements of Organizations”. Both expedient and debatable aspects of methodological approaches to the formation of the Statement of Financial Results in the Draft FSBU 4/2023 “Accounting (financial) statements” are identified. Recommendations for solving debatable methodological issues are argued.
Processo de execução civil: a atuação do advogado na demanda
Authors: Baldo Arthur Soprani , Menezes Pedro Henrique da Silva
Published: October 2023

O presente artigo se propõe a dissertar acerca das dificuldades que os advogados encontram nas demandas de execução civil, embasando-se na legislação nacional, a saber, o Código de Processo Civil e ainda nas críticas doutrinárias e embates jurídicos sobre a questão, haja vista a repercussão ao tema que tem sido dada, com teóricos renomados procurando alternativas para viabilizar o processo de execução. Ainda, far-se-á um levantamento de sugestões de advogados processualistas da cidade de Linhares sobre como acreditam que o instituto pode melhorar. Em suma, o processo de execução no Brasil é demasiadamente demorado e tem como as principais causas a facilidade do devedor em esconder bens, frustrando a execução e por vezes uma atuação passiva do advogado, que, nesse tipo de situação deve adotar outra postura.
PERSEPSI PENGURUS LINGKUNGAN STASI SANTA MARIA RATU DAMAI SLAHUNG PONOROGO TENTANG HAKEKAT LINGKUNGAN
Authors: Wilhelmus Ola Rongan , Suparlis Yulius
Published: October 2023

Basic Christian Community is a way of life for the Church of Christ's disciples in society. The community is present in the midst of society to live out and proclaim the Gospel of Christ for families and society through fellowship, worship, preaching, witnessing and community service. Many members and administrators of the community do not understand and appreciate well and deeply the nature of the Basic Christian Community. The research was conducted with the aim of analyzing the understanding of Basic Christian Community administrators regarding the nature of the community. The research was carried out using a quantitative approach, and the type of research was a survey. The research respondents consisted of the community administrators at the Santa Maria Ratu Damai Slahung Station, Ponorogo. The main variables of this research are the Basic Christian Community, the purpose and function of the community, community members and administrators, and the relationship between the parish and the community. The results of the research data analysis revealed that majority of respondents perceived that Basic Christian Community is the way of life for Christ's disciples in the Church. The results of the research data analysis also indicated that the community was formed with the aim of experiencing the 5 aspects of Church life (fellowship, worship, preaching, witnessing and community service) both in the family and society.