bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of Utilizing Remote Sensing and GIS Techniques to Estimate the Exposure to Organophosphate Pesticides Drift over Macon, Alabama
Authors: El Afandi Gamal , Ismael Hossam , Fall Souleymane , Ankumah Ramble
Published: June 2023

Farmers utilize pesticides extensively on their farms to control weeds and insects, as well as increase crop productivity. Despite these advantages, their excessive use poses a serious threat, particularly to the population living at the nexus of urban and rural areas. Exposure to pesticide drift can be investigated using geospatial tools. Remote sensing technology and Geographic Information Systems (GIS) techniques have been used intensively and constitute trusted tools in different sectors, especially in agriculture. Remote sensing depends on processing the electromagnetic radiation reflected and emitted from the ground target and can be used to identify the main units of Land Use Land Cover (LULC), in addition to measuring crop areas exposed to pesticides. GIS has powerful tools for building a spatial geo-database of pesticide exposure drift. Therefore, the major objective of the research was to explore the effectiveness of using remote sensing and GIS techniques to estimate the exposure organophosphate pesticides drift over Macon County, Alabama. To achieve this objective, the Cropland Data Layer (CDL) dataset, the available pesticide usage data, and gridded population data were used to estimate the potential pesticide drift on the Macon County level. In addition, the AgDRIFT model was used to estimate the potential drift of pesticides from their intended targets at the field level. The results indicated that 6.6% of Macon County’s residents are considered potentially severely exposed, and the potentially affected population resides primarily in rural areas. In comparison, 23% of residents of the urban-rural interface are considered to have potentially medium to high exposure. In addition, 38% of residents living in suburban areas are considered to have potentially low-to-medium exposure. The results indicated that both GIS and remote sensing could play an effective role in estimating pesticide exposure drift at the State or County level. In addition, the AgDRIFT model was more appropriate for estimating pesticide drift at the field level.
Marked Genotype Diversity among Reoviruses Isolated from Chicken in Selected East-Central European Countries
Authors: Gál Bence , Varga-Kugler Renáta , Ihász Katalin , Kaszab Eszter , Domán Marianna , Farkas Szilvia , Bányai Krisztián
Published: June 2023

The concern that the vaccines currently used against Avian orthoreovirus (ARV) infections are less efficient in the field justifies the need for the close monitoring of circulating ARV strains. In this study, we collected necropsy samples from various chicken breeds and tested for ARV by virus isolation, RT-PCR assay and sequence analysis. ARVs were isolated from birds showing runting-stunting syndrome, uneven growth, lameness or increased mortality, with relative detection rates of 38%, 35%, 6% and 25%, respectively. Partial σC gene sequences were determined for nearly 90% of ARV isolates. The isolates could be classified into one of the major genetic clusters. Interestingly, cluster 2 and cluster 5 were isolated from vaccinated broiler breeders, while clusters 1 to 4 were isolated from unvaccinated broilers. The isolates shared less than 75% amino acid identities with the vaccine strains (range, 44.3–74.6%). This study reaffirms the global distribution of the major genetic clusters of ARVs in chicken. The diversity of ARV strains isolated from unvaccinated broilers was greater than those detected from vaccinated animals, however, the relative importance of passive and active immunity on the selection of novel strains in different chicken breeds needs to be better understood.
Intermittent and Mild Cold Stimulation Maintains Immune Function Stability through Increasing the Levels of Intestinal Barrier Genes of Broilers
Authors: Xing Lu , Li Tingting , Zhang Yong , Bao Jun , Wei Haidong , Li Jianhong
Published: June 2023

In order to improve the adaptability of broilers to low-temperature environments and their ability to resist acute cold stress (ACS), 240 one-day-old broilers were selected and randomly divided into three groups. The control treatment (CC) group was raised at the conventional feeding temperature from 1–43 days (d), the cold stimulation treatment (CS) group was kept at 3 °C below the temperature of CC at 1 d intervals for 3 and 6 h from 15 to 35 d, namely, CS3 and CS6, respectively. Then, all broilers were kept at 20 °C from 36 to 43 d. ACS was then carried out at 44 d, and the ambient temperature was dropped to 10 °C for 6 h. The study investigated the production performance, as well as levels of intestinal barrier genes (including Claudin-1, E-cadherin, Occludin, ZO-1, ZO-2 and Mucin2), secretory IgA in duodenum and jejunum, and immunoglobulins (IgA and IgG) in serum. The results showed that IMCS could increase the daily weight gain and decrease the feed conversion ratio. During IMCS, the expression levels of intestinal barrier genes were up-regulated and the content of secretory IgA was increased. When IMCS ceased for one week, the level of immunoglobulins in serum stabilized, and the expression levels of Occludin, ZO-2 and Mucin2 still maintained high levels. After ACS, broilers that received IMCS training maintained high levels of intestinal barrier genes and secretory IgA.
Effects of Individual and Pair Housing of Calves on Short-Term Health and Behaviour on a UK Commercial Dairy Farm
Authors: Mahendran Sophie A. , Wathes D. Claire , Booth Richard E. , Baker Neil , Blackie Nicola
Published: June 2023

Social pair housing of calves has previously demonstrated positive impacts for calves, so this study aimed to compare the health and behaviour of calves kept in individual compared to pair housing on a single commercial UK dairy farm. A total of 457 Holstein and Jersey heifer calves were recruited and systematically allocated to individual and pair housing. Weekly visits were conducted up to 8 weeks of age, with weight and presence of clinical disease measured using both a standardized scoring system and thoracic ultrasonography. A subset of calves (n = 90) had accelerometers attached to monitor activity, with CCTV placed above a further 16 pens to allow behavioural assessments to be made via continuous focal sampling at 1 and 5 weeks of age. During the study, there was a mortality rate of 2.8%, and an average daily liveweight gain (ADLG) of 0.72 kg/day, with no significant effect of housing group (p = 0.76). However, individually housed calves had increased odds of developing disease (OR = 1.88, p = 0.014). Accelerometer data showed that housing group had no effect on lying times, with a mean of 18 h 11 min per day (SD 39 min) spent lying down. The motion index was significantly higher in pair-housed calves (F1,83 = 440.3, p < 0.01), potentially due to more social play behaviour. The total time engaged in non-nutritive oral behaviours (NNOBs) was not impacted by housing group (p = 0.72). Pair-housed calves split their time conducting NNOBs equally between inanimate objects and on their pen mates’ body. Individually housed calves spent significantly more time with their head out of the front of the pen (p = 0.006), and also engaged in more self-grooming than pair-housed calves (p = 0.017), possibly due to a lack of socialization. The overall findings of this study indicate that within a UK commercial dairy management system, pair-housed calves were healthier and more active than individually housed calves, while housing group did not influence ADLG or the occurrence of NNOBs.
Assessment of Cold Atmospheric Pressure Plasma (CAPP) Treatment for Degradation of Antibiotic Residues in Water
Authors: Wielogorska Ewa , Flynn Padrig B. , Meneely Julie , Thompson Thomas P. , Graham William G. , Gilmore Brendan F. , Elliott Christopher T.
Published: June 2023

The presence of antibiotic residues in water is linked to the emergence of antibiotic resistance globally and necessitates novel decontamination strategies to minimize antibiotic residue exposure in both the environment and food. A holistic assessment of cold atmospheric pressure plasma technology (CAPP) for β-lactam antibiotic residue removal is described in this study. CAPP operating parameters including plasma jet voltage, gas composition and treatment time were optimized, with highest β-lactam degradation efficiencies obtained for a helium jet operated at 6 kV. Main by-products detected indicate pH-driven peroxidation as a main mechanism of CAPP-induced decomposition of β-lactams. No in vitro hepatocytotoxicity was observed in HepG2 cells following exposure to treated samples, and E. coli exposed to CAPP-degraded β-lactams did not exhibit resistance development. In surface water, over 50% decrease in antibiotic levels was achieved after only 5 min of treatment. However, high dependence of treatment efficiency on residue concentration, pH and presence of polar macromolecules was observed.
QUIRMIA—A Phenotype-Based Algorithm for the Inference of Quinolone Resistance Mechanisms in Escherichia coli
Authors: Imkamp Frank , Bodendoerfer Elias , Mancini Stefano
Published: June 2023

Objectives: Quinolone resistance in Escherichia coli occurs mainly as a result of mutations in the quinolone-resistance-determining regions of gyrA and parC, which encode the drugs’ primary targets. Mutational alterations affecting drug permeability or efflux as well as plasmid-based resistance mechanisms can also contribute to resistance, albeit to a lesser extent. Simplifying and generalizing complex evolutionary trajectories, low-level resistance towards fluoroquinolones arises from a single mutation in gyrA, while clinical high-level resistance is associated with two mutations in gyrA plus one mutation in parC. Both low- and high-level resistance can be detected phenotypically using nalidixic acid and fluoroquinolones such as ciprofloxacin, respectively. The aim of this study was to develop a decision tree based on disc diffusion data and to define epidemiological cut-offs to infer resistance mechanisms and to predict clinical resistance in E. coli. This diagnostic algorithm should provide a coherent genotype/phenotype classification, which separates the wildtype from any non-wildtype and further differentiates within the non-wildtype. Methods: Phenotypic susceptibility of 553 clinical E. coli isolates towards nalidixic acid, ciprofloxacin, norfloxacin and levofloxacin was determined by disc diffusion, and the genomes were sequenced. Based on epidemiological cut-offs, we developed a QUInolone Resistance Mechanisms Inference Algorithm (QUIRMIA) to infer the underlying resistance mechanisms responsible for the corresponding phenotypes, resulting in the categorization as “susceptible” (wildtype), “low-level resistance” (non-wildtype) and “high-level resistance” (non-wildtype). The congruence of phenotypes and whole genome sequencing (WGS)-derived genotypes was then assigned using QUIRMIA- and EUCAST-based AST interpretation. Results: QUIRMIA-based inference of resistance mechanisms and sequencing data were highly congruent (542/553, 98%). In contrast, EUCAST-based classification with its binary classification into “susceptible” and “resistant” isolates failed to recognize and properly categorize low-level resistant isolates. Conclusions: QUIRMIA provides a coherent genotype/phenotype categorization and may be integrated in the EUCAST expert rule set, thereby enabling reliable detection of low-level resistant isolates, which may help to better predict outcome and to prevent the emergence of clinical resistance.
Plant Food Dyes with Antioxidant Properties and Allergies—Friend or Enemy?
Authors: Lis Kinga , Bartuzi Zbigniew
Published: June 2023

Color is an important food attribute which increases its attractiveness, thus influencing consumer preferences and acceptance of food products. The characteristic color of fresh, raw food is due to natural dyes present in natural food sources. Food loses its natural color during processing or storage. Loss of natural color (e.g., graying) often reduces the appeal of a product to consumers. To increase the aesthetic value of food, natural or synthetic dyes are added to it. Interestingly, the use of food coloring to enhance food attractiveness and appetizing appearance has been practiced since antiquity. Food coloring can also cause certain health effects, both negative and positive. Dyes added to food, both natural and synthetic, are primarily chemical substances that may not be neutral to the body. Some of these substances have strong antioxidant properties. Thanks to this activity, they can also perform important pro-health functions, including antiallergic ones. On the other hand, as foreign substances, they can also cause various adverse food reactions, including allergic reactions of varying severity and anaphylactic shock. This article discusses food dyes of plant origins with antioxidant properties (anthocyanins, betanins, chlorophylls, carotenoids, and curcumin) and their relationship with allergy, both as sensitizing agents and immunomodulatory agents with potential antiallergic properties.
Novel Strategies in the Early Detection and Treatment of Endothelial Cell-Specific Mitochondrial Dysfunction in Coronary Artery Disease
Authors: Lee Weiqian E. , Genetzakis Elijah , Figtree Gemma A.
Published: June 2023

Although elevated cholesterol and other recognised cardiovascular risk factors are important in the development of coronary artery disease (CAD) and heart attack, the susceptibility of humans to this fatal process is distinct from other animals. Mitochondrial dysfunction of cells in the arterial wall, particularly the endothelium, has been strongly implicated in the pathogenesis of CAD. In this manuscript, we review the established evidence and mechanisms in detail and explore the potential opportunities arising from analysing mitochondrial function in patient-derived cells such as endothelial colony-forming cells easily cultured from venous blood. We discuss how emerging technology and knowledge may allow us to measure mitochondrial dysfunction as a potential biomarker for diagnosis and risk management. We also discuss the “pros and cons” of animal models of atherosclerosis, and how patient-derived cell models may provide opportunities to develop novel therapies relevant for humans. Finally, we review several targets that potentially alleviate mitochondrial dysfunction working both via direct and indirect mechanisms and evaluate the effect of several classes of compounds in the cardiovascular context.
Disturbances of the Lung Glutathione System in Adult Guinea Pigs Following Neonatal Vitamin C or Cysteine Deficiency
Authors: Teixeira Vitor , Mohamed Ibrahim , Lavoie Jean-Claude
Published: June 2023

In premature infants receiving parenteral nutrition, oxidative stress is a trigger for the development of bronchopulmonary dysplasia, which is an important factor in the development of adult lung diseases. Neonatal vitamin C and glutathione deficiency is suspected to induce permanent modification of redox metabolism favoring the development of neonatal and adult lung diseases. A total of 64 3-day-old guinea pigs were fed an oral diet that was either complete or deficient in vitamin C (VCD), cysteine (CD) (glutathione-limiting substrate) or both (DD) for 4 days. At 1 week of age, half of the animals were sacrificed while the other started a complete diet until 12 weeks of age. At 1 week, the decrease in lung GSH in all deficient groups was partially explained by the oxidation of liver methionine-adenosyltransferase. mRNA levels of kelch-like ECH-associated protein 1 (Keap1), glutathione-reductase (Gsr) and glutaredoxin-1 (Glrx) were significantly lower only in CD but not in DD. At 12 weeks, glutathione levels were increased in VCD and CD. Keap1, Gsr and Glrx mRNA were increased, while glutathione-reductase and glutaredoxin proteins were lower in CD, favoring a higher glutathionylation status. Both neonatal deficiencies result in a long-term change in glutathione metabolism that could contribute to lung diseases’ development.
Optimized Weighted Ensemble Approach for Enhancing Gold Mineralization Prediction
Authors: Zaki M. M. , Chen Shaojie , Zhang Jicheng , Feng Fan , Qi Liu , Mahdy Mohamed A. , Jin Linlin
Published: June 2023

The economic value of a mineral resource is highly dependent on the accuracy of grade estimations. Accurate predictions of mineral grades can help businesses decide whether to invest in a mining project and optimize mining operations to maximize the resource. Conventional methods of predicting gold resources are both costly and time-consuming. However, advances in machine learning and processing power are making it possible for mineral estimation to become more efficient and effective. This work introduces a novel approach for predicting the distribution of mineral grades within a deposit. The approach integrates machine learning and optimization techniques. Specifically, the authors propose an approach that integrates the random forest (RF) and k-nearest neighbor (kNN) algorithms with the marine predators optimization algorithm (MPA). The RFKNN_MPA approach uses log normalization to reduce the impact of extreme values and improve the accuracy of the machine learning models. Data segmentation and the MPA algorithm are used to create statistically equivalent subsets of the dataset for use in training and testing. Drill hole locations and rock types are used to create each model. The suggested technique’s performance indices are superior to the others, with a higher R-squared coefficient of 59.7%, a higher R-value of 77%, and lower MSE and RMSE values of 0.17 and 0.44, respectively. The RFKNN_MPA algorithm outperforms geostatistical and conventional machine-learning techniques for estimating mineral orebody grades. The introduced approach offers a novel solution to a problem with practical applications in the mining sector.
Detection of Elbow OCD in the Ultrasound Image by Artificial Intelligence Using YOLOv8
Authors: Inui Atsuyuki , Mifune Yutaka , Nishimoto Hanako , Mukohara Shintaro , Fukuda Sumire , Kato Tatsuo , Furukawa Takahiro , Tanaka Shuya , Kusunose Masaya , Takigami Shunsaku , Ehara Yutaka , Kuroda Ryosuke
Published: June 2023

Background: Screening for elbow osteochondritis dissecans (OCD) using ultrasound (US) is essential for early detection and successful conservative treatment. The aim of the study is to determine the diagnostic accuracy of YOLOv8, a deep-learning-based artificial intelligence model, for US images of OCD or normal elbow-joint images. Methods: A total of 2430 images were used. Using the YOLOv8 model, image classification and object detection were performed to recognize OCD lesions or standard views of normal elbow joints. Results: In the binary classification of normal and OCD lesions, the values from the confusion matrix were the following: Accuracy = 0.998, Recall = 0.9975, Precision = 1.000, and F-measure = 0.9987. The mean average precision (mAP) comparing the bounding box detected by the trained model with the true-label bounding box was 0.994 in the YOLOv8n model and 0.995 in the YOLOv8m model. Conclusions: The YOLOv8 model was trained for image classification and object detection of standard views of elbow joints and OCD lesions. Both tasks were able to be achieved with high accuracy and may be useful for mass screening at medical check-ups for baseball elbow.
CDF-LS: Contrastive Network for Emphasizing Feature Differences with Fusing Long- and Short-Term Interest Features
Authors: Liu Kejian , Wang Wei , Wang Rongju , Cui Xuran , Zhang Liying , Yuan Xianzhi , Li Xianyong
Published: June 2023

Modelling both long- and short-term user interests from historical data is crucial for generating accurate recommendations. However, unifying these metrics across multiple application domains can be challenging, and existing approaches often rely on complex, intertwined models which can be difficult to interpret. To address this issue, we propose a lightweight, plug-and-play interest enhancement module that fuses interest vectors from two independent models. After analyzing the dataset, we identify deviations in the recommendation performance of long- and short-term interest models. To compensate for these differences, we use feature enhancement and loss correction during training. In the fusion process, we explicitly split long-term interest features with longer duration into multiple local features. We then use a shared attention mechanism to fuse multiple local features with short-term interest features to obtain interaction features. To correct for bias between models, we introduce a comparison learning task that monitors the similarity between local features, short-term features, and interaction features. This adaptively reduces the distance between similar features. Our proposed module combines and compares multiple independent long-term and short-term interest models on multiple domain datasets. As a result, it not only accelerates the convergence of the models but also achieves outstanding performance in challenging recommendation scenarios.
Energy Optimization for Agriculture and Agroengineering Systems
Authors: Nozhevnikova Alla , Kharchenko Valeriy , Panchenko Vladimir
Published: June 2023

The use of energy (and renewable energy, in particular) plays an important role in agriculture, where technologies are also being improved from year to year—agricultural production is growing, and machinery and systems are becoming more autonomous and robotic, where it is no longer possible to do without complex computing, optimization, planning, and working with large amounts of data [...]
Multiclass Anomaly Detection of Bridge Monitoring Data with Data Migration between Different Bridges for Balancing Data
Authors: Qu Chunxu , Zhang Hongming , Zhang Rui , Zou Shuang , Huang Lihua , Li Hongnan
Published: June 2023

Structural health inspection systems are widely used to manage and maintain infrastructure that involves massive sensor devices. However, these sensors receive the natural environment or external factors in the long-term exposure to the outdoor environment, resulting in the failure of the sensors, which causes multiple categories of abnormal data in the collected data. The data often is unbalanced due to the random nature of failures. This unbalanced anomaly data poses a major challenge to existing anomaly detection methods and will affect the effectiveness of the information provided by the structural health monitoring system. In the paper, a data migration method is proposed to migrate bridge data to the target bridge dataset for expansion so that the number of images of different categories in the target bridge dataset increases. This method can be divided into three steps: firstly, to classify the data; secondly, to determine the suitability of the data and to construct the dataset; and finally, to train the data. The comparative validation is used to compare the training performance of the dataset using data migration with the dataset only using the target bridge to analyze the abnormal data identification in each category. In the experiment, the recall of some categories of data reached a significant increase of more than 30%, achieving better identification of various categories of abnormal data. Adopting the method of data migration between different bridges can solve the impact of imbalanced data and improve the recognition performance of categories with fewer images.
Correction: Alencar et al. Bearing Capacity of Footings on Rock Masses Using Flow Laws. Appl. Sci. 2021, 11, 11829
Authors: Alencar Ana , Galindo Ruben , Marañón Claudio Olalla , Melentijevic Svetlana
Published: June 2023

Svetlana Melentijevic was not included as an author in the original publication [...]
Robotic System for Post Office Package Handling
Authors: Vismanis Oskars , Arents Janis , Freivalds Karlis , Ahluwalia Vaibhav , Ozols Kaspars
Published: June 2023

Parcel sorting is becoming a significant challenge for delivery distribution centers and is mostly automated by using high-throughput sorting machinery, but manual work is still used to feed these machines by placing the parcels on the conveyor belt. In this paper, an AI-based robotic solution that automates the parcel placement task was developed. The architecture of the proposed system along with methods on how to implement it are described by using the currently available hardware and software components. The described choices lead to a well-functioning system and the gained insights will facilitate building similar systems for parcel delivery automation.
Influence of Mining Parameters on the Distribution Law of Separation Layer and Water-Flowing Fracture in Mining Overburden
Authors: Xie Jianlin , Zhang Jiakui , Wang Xiaozhen
Published: June 2023

The internal overburden movement after coal mining may cause many disasters to the on-site production. It is of great guiding significance for the engineering treatment such as separation layer grouting and gas extraction to master the evolution law of separation layer and fracture in the overburden. Combined with the full-columnar overburden of a certain working face, this study established a number of models using 3DEC simulation software and analyzed the influence of different mining heights and widths on the distribution law of separation layer and fracture after strata movement. The simulation results show that the evolution of separation layer in the overburden after mining roughly consists of three stages, namely, initial generation, reaching peak, and tending to close (stable). The development of the separation layer is positively correlated with the mining height and negatively correlated with the mining width. When the mining height increases from 3 m to 5 m, the peak value of cumulative separation increases from 0.7 m to 2.1 m. On the contrary, when the mining width increases from 250 m to 350 m, the peak value of cumulative separation decreases from 2.8 m to 1.1 m. The pre-bearing stress concentration will be formed in the mining process of the working face. The influence of mining width change on the peak of stress concentration is greater than that of mining height change, and the subsidence is mainly affected by mining height. A quantitative analysis method of water-flowing fracture development height was developed by using the penetration height of joint shear displacement. The calculated fracture zone height 117.33 m was in good agreement with the actual measured results 120 m, verifying the validity of this method. These findings are of great reference for mastering the distribution law of separation layer and fracture in the mining overburden.
Experimental Wear Characterization and Durability Enhancement of an Aeronautic Braking System
Authors: Logozzo Silvia , Valigi Maria Cristina
Published: June 2023

This paper is focused on the experimental wear characterization of an electromagnetic braking system used for helicopters. The characterization was performed through the evaluation of some monitoring parameters during endurance tests on a test bench and through the visual analysis of the worn surfaces after the tests. The monitoring parameters were the engagement threshold voltage, the release threshold voltage, the inductance, and the braking torque, which are directly correlated with the wear progress. The visual analysis allowed the assessment of the wear extent and the distribution of wear particles at the interfaces. The test performed on the initial base configuration, having ten springs and carbon fibers as friction materials, demonstrated that the braking system had insufficient durability in terms of actuation cycles. The results allowed the design of two new configurations based on different brake architectures and on different friction pairs. One of the new configurations was based on a reduction in the number of springs (eight-spring configuration), and the second one was based on the employment of a different friction material (NAO configuration). Both of these optimized configurations showed enhanced durability and wear resistance, but only the second one showed sufficient durability with respect to the requirements and was defined as acceptable. The final results showed a durability of 3000 actuation cycles for the base configuration, 4385 for the eight-spring configuration, and 35,223 for the NAO configuration. Nevertheless, the analysis of results allowed the cause of the wear phenomena to be studied and eventual further improvements in the system to be suggested.
Implementation of Soil and Water Conservation in Indonesia and Its Impacts on Biodiversity, Hydrology, Soil Erosion and Microclimate
Authors: Dharmawan I Wayan Susi , Pratiwi  , Siregar Chairil Anwar , Narendra Budi Hadi , Undaharta Ni Kadek Erosi , Sitepu Bina Swasta , Sukmana Asep , Wiratmoko Michael Daru Enggar , Abywijaya Ilham Kurnia , Sari Nilam
Published: June 2023

Soil and water are natural resources that support the life of various creatures on Earth, including humans. The main problem, so far, is that both resources can be easily damaged or degraded by human-induced drivers. The threat of damage or degradation is increasing due to rapid human population growth and humans’ insatiable daily necessities. Indonesia has had various experiences in soil and water conservation (SWC) programmes for a long time, which can be a good lesson learned for future strategy development. This article aims to provide an overview of the benefits of implementing SWC in Indonesia for biodiversity, hydrology, soil erosion, and microclimate to support sustainable ecological landscape management. Various vegetative and mechanical techniques that have been known and implemented can be utilized to improve future SWC strategies. It is expected that proper strategy development in the future for SWC in Indonesia will support the sustainability of ecological landscape management. Forthcoming SWC programmes are also expected to incorporate local knowledge into their implementation. The programmes also require coordination between stakeholders, i.e., local communities, management authorities, policymakers, and scientists, and seamless integration between varying fields and levels of governance. The main findings of this study are that SWC increased the adaptation of native plants to local rainfall and soil conditions; SWC increased infiltration and improved soil hydrological characteristics; and SWC, through vegetation techniques, played a role in lowering temperatures, increasing humidity, and reducing intensity levels.
Quartz Powder Valorisation in White Self-Compacting Concrete: Mortar Level Study
Authors: Matos Ana Mafalda , Maia Lino , Coutinho Joana Sousa
Published: June 2023

Quartz powder (QP) from mining exploration has increased, and valorisation solutions are sought. QP incorporation in structural concrete is an exciting strategy for the growth and sustainable development of the concrete industry, waste management and environmental protection. This work addresses the valorisation of QP from a Portuguese company on powder-type self-compacting concrete for architectural and structural purposes, combining the light colour of quartz with white cement. As such, QP was used as a partial cement replacement, acting as a filler on self-compacting white mortars (SCWM) and pastes (SCWP). Firstly, the QP was characterised by chemical, physical and morphological properties. Afterwards, SCWM with 10% of the white Portland cement with QP were produced and, with 10% cement replacement by limestone fillers, commercially available, for comparison purposes. The following engineering properties were evaluated, flowability and viscosity, electrical resistivity, porosity and mechanical strength. In equivalent pastes samples, the heat of hydration was accessed. Finally, an architectonic element prototype was produced using SCWM-QP, and colour and aesthetics were evaluated. All SCWM reached adequate deformability and viscosity for self-compaction. In the hardened state, compressive strength, electrical resistivity and water-permeable porosity presented similar results for mortars incorporating quartz powder and limestone fillers. The isothermal calorimetry in equivalent pastes revealed a slight desacceleration of hydration for SCWP incorporating QP. The major findings of this study confirm the feasibility of SCWM with QP, meeting the required performance while reducing resource depletion in the concrete industry and adding value to a by-product.
Method for Simulation Modeling of Integrated Multi-Energy Systems Based on the Concept of an Energy Hub
Authors: Ilyushin Pavel , Gerasimov Dmitry , Suslov Konstantin
Published: June 2023

The concept of multi-energy systems (MES) is widely applied in various areas of energy supply. This approach makes it possible to analyze the distribution of energy flows and their mutual influence both for local facilities and for power supply systems. At the same time, currently, promising systems for analysis, forecast, and control of the behavior of energy facilities are those that employ innovative methods, for example, different technologies of mathematical modeling. Their successful application requires a methodological approach to build mathematical models of integrated energy systems relying on simulation modeling. The approach proposed in this paper is based on the concept of an energy hub. It has been tested on a simulation model for two energy supply channels for a fragment of a real-world energy facility. The presented methodological approach to create mathematical models of integrated energy systems is based on simulation. This approach offers broad prospects for expanding the capabilities in the design and operation of integrated multi-energy systems.
Advancements and Environmental Implications in Oil Shale Exploration and Processing
Authors: Jia Bao , Su Jianzheng
Published: June 2023

This comprehensive review presents a holistic examination of oil shale as a significant energy resource, focusing on its global reserves, extraction technologies, chemical characteristics, economic considerations, and environmental implications. Oil shale, boasting reserves equivalent to approximately 6 trillion barrels of shale oil worldwide, holds substantial potential to augment the global energy supply. Key extraction methods analyzed include surface mining, modified in situ, and true in situ conversion processes, each exhibiting distinct operational parameters and efficiencies. The review further delves into the chemical aspects of oil shale retorting and pyrolysis, highlighting the critical role of variables such as retorting temperature, residence time, particle size, and heating rate in determining the yield and composition of shale oil and byproducts. Economic analyses reveal that capital and operating costs, which vary according to the specific extraction and processing technologies implemented, are crucial in appraising the economic feasibility of oil shale projects. Lastly, the review acknowledges the potential environmental hazards linked with oil shale development, such as groundwater contamination and harmful emissions. It emphasizes the importance of rigorous monitoring programs, environmental impact assessments, sustainable technologies, and innovative strategies like co-combustion and comprehensive utilization systems in mitigating such impacts. The review underlines the need for a balanced approach that harmonizes technological advancement, economic viability, and environmental sustainability in oil shale exploitation.
Machine Learning-Based Shoveling Trajectory Optimization of Wheel Loader for Fuel Consumption Reduction
Authors: Chen Yanhui , Shi Gang , Tan Cheng , Wang Zhiwen
Published: June 2023

The difference in fuel consumption of wheel loaders can be more than 30% according to different shoveling trajectories for shoveling operations, and the optimization of shoveling trajectories is an important way to reduce the fuel consumption of shoveling operations. The existing shoveling trajectory optimization method is mainly through theoretical calculation and simulation analysis, which cannot fully consider the high randomness and complexity of the shoveling process. It is difficult to achieve the desired optimization effect. Therefore, this paper takes the actual shoveling operation data as the basis. The factors that have a high impact on the fuel consumption of shoveling are screened out through Kernel Principal Component Analysis. Moreover, the mathematical model of fuel consumption of shoveling operation is established by Support Vector Machine and combined with the Improved Particle Swarm Optimization algorithm to optimize the shoveling trajectory. To demonstrate the generalization ability of the model, two materials, gravel, and sand, are selected. Meanwhile, the influence of different engine speeds on the shoveling operation is considered. We optimize the shoveling trajectories for three different engine speeds. The optimized trajectories are verified and compared with the sample data and manually controlled shoveling data. The results show that the optimized trajectory can reduce the fuel consumption of shoveling operation by 27.66% and 24.34% compared with the manually controlled shoveling of gravel and sand, respectively. This study provides guidance for the energy-efficient operation of wheel loaders.
Experimental Study on Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Three Regression Models for Electric Vehicle Application
Authors: Ha Vo Thanh , Giang Pham Thi
Published: June 2023

This paper presents three regression models that predict the lithium-ion battery life for electric cars based on a supervised machine learning regression algorithm. The linear regression, bagging regressor, and random forest regressor models will be compared for the capacity prediction of lithium-ion batteries based on voltage-dependent per-cell modeling. When sufficient test data are available, three linear regression learning algorithms will train this model to give a promising battery capacity prediction result. The effectiveness of the three linear regression models will be demonstrated experimentally. The experiment table system is built with an NVIDIA Jetson Nano 4 GB Developer Kit B01, a battery, an Arduino, and a voltage sensor. The random forest regressor model has evaluated the model’s accuracy based on the average of the square of the difference between the initial value and the predicted value in the data set (MSE (mean square error)) and RMSE (root mean squared error), which is smaller than the linear regression model and bagging regressor model (MSE is 516.332762; RMSE is 22.722957). The linear regression model with MSE and RMSE is the biggest (MSE is 22060.500669; RMSE is 148.527777). This result allows the random forest regressor model to remain helpful in predicting the life of lithium-ion batteries. Moreover, this result allows rapid identification of battery manufacturing processes and will enable users to decide to replace defective batteries when deterioration in battery performance and lifespan is identified.
Design of the Sabot-Stopping System for a Single-Stage Light-Gas Gun for High-Velocity Impacts
Authors: Barilaro Leonardo , Wylie Mark , Shafeeg Theeba
Published: June 2023

Collisions of space debris and micrometeorites with spacecraft represent an existential hazard for human activities in near-Earth orbits. Currently, guidelines, policies, and best practices are encouraged to help mitigate further propagation of this space debris field from redundant spacecraft and satellites. However, the existing space debris field is an environment that still poses a great threat and requires the design of contingency and fail-safe systems for new spacecraft. In this context, both the monitoring and tracking of space debris impact paths, along with knowledge of spacecraft design features that can withstand such impacts, are essential. Regarding the latter, terrestrial test facilities allow for replicating of space debris collisions in a safe and controlled laboratory environment. In particular, light-gas guns allow launching impactors at speeds in the high-velocity and hypervelocity ranges. The data acquired from these tests can be employed to validate in-orbit observations and structural simulations and to verify spacecraft components’ survivability. Typically, projectiles are launched and protected using a sabot system. This assembly, known as a launch package, is fired towards a sabot-stopping system. The sabot separates from the rest of the launch package, to avoid target contamination, and allows the projectile to travel towards the target through an opening in the assembly. The response and survivability of the sabot-stopping system, along with the transmission of the forces to the light-gas gun structure and prevention of target contamination, is an important design feature of these test apparatuses. In the framework of the development of Malta’s first high-velocity impact facility, particular attention was dedicated to this topic: in this paper, the description of a novel sabot-stopping system is provided. The system described in this research is mechanically decoupled from the interaction with the impact chamber and the light-gas gun pump tube; this solution avoids damage in case of failures and allows easier operations during the pre- and post-test phases.
Subwavelength-Cavity High-Gain Circularly Polarized Antenna with Planar Metamaterials
Authors: Wang Wei , Lu Guang , Diao Chao , Li Junyang , Liu Fen , Du Guiqiang
Published: June 2023

We present a specific subwavelength-cavity high-gain circularly polarized ultra-thin antenna made of planar metamaterials. The antenna is designed to operate at 2.80 GHz with a fixed thickness of approximately 1/6 of the operating wavelength in free space. The asymmetric unit cells of the metamaterial antenna exhibit two characteristics, namely, negative permeability and polarization selection. A linear-polarization micro-strip patch, which can realize circular polarization without a complicated feeding network, is embedded in the cavity as a feed. The circular polarization mode of the antenna can be changed by simply rotating the planar metamaterial horizontally. Simulations and experiments conducted on this antenna yielded results that are in good agreement with each other. This new subwavelength planar antenna can have potentially important applications in communication, early warning systems, and radio observation.
Mechanical Behaviors and Numerical Simulation Analysis of a New Isolation System
Authors: Liu Bo , Pan Danguang , Zhang Wanying , Lu Yankai , Ni Guowei
Published: June 2023

Finite element analysis is one of the key steps in evaluating the effectiveness of an isolation system. The aim of this paper is to research the mechanical properties of sliding and rolling friction systems and their application for isolating frame structures. A hybrid seismic isolation system is proposed, which aims to protect the superstructure by reducing dynamic response. The effect of different parameters on the friction coefficient of the isolation bearing was tested using a compression-shear testing machine, and the results showed that various parameters significantly affected the friction coefficient. In addition, a numerical analysis finite element model was established using SAP2000 software to compare the seismic isolation performance of the hybrid isolation system with that of traditional seismic-resistant structures. The results showed that the composite isolation system not only effectively reduced inter-story shear and acceleration, but also slightly enhanced the seismic isolation effect as the friction coefficient decreased.
LTAnomaly: A Transformer Variant for Syslog Anomaly Detection Based on Multi-Scale Representation and Long Sequence Capture
Authors: Han Delong , Sun Mengjie , Li Min , Chen Qinghui
Published: June 2023

Detailed information on system operation is recorded by system logs, from which fast and accurate detection of anomalies is conducive to service management and system maintenance. Log anomaly detection methods often only handle a single type of anomaly, and the utilization of log messages could be higher, which makes it challenging to improve the performance of log anomaly detection models. This article presents the LTAnomaly model to accomplish log anomaly detection using semantic information, sequence relationships, and component values to make a vector representation of logs, and we add Transformer with long short-term memory (LSTM) as our final classification model. When sequences are processed sequentially, the model is also influenced by the information from the global information, thus increasing the dependence on feature information. This improves the utilization of log messages with a flexible, simple, and robust model. To evaluate the effectiveness of our method, experiments are performed on the HDFS and BGL datasets, with the F1-measures reaching 0.985 and 0.975, respectively, showing that the proposed method enjoys higher accuracy and a more comprehensive application range than existing models.
Assessment of AC Corrosion Probability in Buried Pipelines with a FEM-Assisted Stochastic Approach
Authors: Lucca Giovanni , Sandrolini Leonardo , Popoli Arturo , Simonazzi Mattia , Cristofolini Andrea
Published: June 2023

In this paper, a stochastic approach is combined with field theory and circuit methods to study how the geometrical and electrical properties of holidays (defects or pores in the insulating coating) in a metallic pipeline influence the probability of exceeding the current density limit for corrosion. Three-dimensional FEM simulations are conducted to assess the influence of the shape and electrical resistivity of the pore on the computed spread resistance value. The obtained results are then used to evaluate the probability of exceeding a given current density value for different sizes of pore and soil resistivities. Finally, a case of 50 Hz interference along a pipeline-transmission line routing is examined. The probabilistic approach presented in this paper allows the pipeline sections more subjected to the induced AC corrosion risk to be identified to be used as an auxiliary tool for adopting preventive protection countermeasures. Lastly, unlike most papers devoted to assessing electromagnetic interference on pipelines, the present work uses a probabilistic rather than a deterministic approach, representing its main novelty aspect.
The Effect of Red Potato Pulp Preparation and Stage of Its Incorporation into Sourdough or Dough on the Quality and Health-Promoting Value of Bread
Authors: Litwinek Dorota , Gumul Dorota , Łukasiewicz Marcin , Zięba Tomasz , Kowalski Stanisław
Published: June 2023

The quality and health-promoting properties of enriched bread depend not only on the composition of the additive but also on the baking technology. In this study, the preparation (rice flour, maltodextrin, and red potato pulp) was used in the amount of 5% of the flour in the recipe at various stages of bread production, i.e., during sourdough fermentation or dough kneading. The aim of the study was to analyze the effect of adding the preparation containing red potato pulp on the content of polyphenols and the ability to neutralize free radicals, nutritional composition, physical parameters, and quality of wheat–rye bread using two different baking technologies. The preparations made with red potato pulp are an excellent source of bioactive compounds. The breads with preparations added to the sourdough were characterized by greater volume and lower hardness, and higher levels of minerals and dietary fiber than breads with preparations added to the dough. It was found that the breads with preparations added to the dough were characterized by up to 4.5 times more polyphenols, 3.5 times more flavonoids, and 6 times more phenolic acids and flavonols than breads with preparations added to sourdough, which translated into their greater antioxidant potential.