bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of an Injection Molding Tool With Exchangable Inserts
Authors: Keresztes Kristóf , Gergely Attila Levente
Published: February 2024

The aim of this work was to design an injection molding tool with replaceable inserts. The tool design is made for a BOY 15S injection molding machine. Based on the interpretation and comparison of the simulation results of the filling process, we optimized the plastic part design, the runner system and the location of the gates and cavities in order to maximize productivity and efficiency while minimizing cost. In the process of the tool design, we also considered the potential problems regarding the manufacturing process of the tool.
Understanding Gen Z and Gen X Responses to Influencer Communications
Authors: Bratina Danijel , Faganel Armand
Published: February 2024

The increased popularity of social media has greatly affected the marketing-communications activities of companies. This study seeks to understand how influencers promoting products affect their followers’ purchasing intentions and attitudes towards endorsed products. Our main interest is to get an insight on differences between two generations (X and Z). We construct a structural model, based on the theory of credibility. Findings suggest that influencer endorsements have an impact on both age groups, with a more noticeable effect observed in the younger generation. The loyalty towards influencers emerges as a constructive intermediary factor, amplifying the influence of credibility on purchasing intentions across both generations. When considering attitudes towards the brands endorsed by the influencers, loyalty’s impact is comparatively modest. The results provide a building block in understanding the influencers’ activities in marketing-communications, and how they can be used for communication with different generations.
Community-Based Tourism and Best Practices with the Sustainable Development Goals
Authors: Abreu Leonilo Alves de , Walkowski Marinês da Conceição , Perinotto André Riani Costa , Fonseca Júlia Fragoso da
Published: February 2024

Community-based tourism (CBT) operates on a paradigm of community self-governance wherein traditional communities assume the role of instigators and protagonists in the realm of tourism within their territories. Within this framework, CBT emerges as a means of realizing the sustainable development goals (SDGs) articulated in the United Nations’ Agenda 2030, outlined in 2015. The present study aims to compare three TBC communities with the SDG criteria and their contribution to the 2023 Agenda. To achieve this aim, we employed a methodological approach rooted in case study, leveraging secondary sources and adopting a qualitative methodology. The principal findings underscore that the three scrutinized CBT communities—Tekoá-Pirá, Chã de Jardim, and Amucafé, located in Brazil—directly contribute to the attainment of seven SDGs and indirectly influence two others. As prospective research avenues, we advocate exploring additional initiatives and implementing empirical studies to delve more profoundly into the realities of these communities.
Configuration Optimization of Temperature–Humidity Sensors Based on Weighted Hilbert–Schmidt Independence Criterion in Chinese Solar Greenhouses
Authors: Song Chengbao , Liu Pingzeng , Liu Xinghua , Liu Lining , Yu Yuting
Published: February 2024

For cost-sensitive Chinese solar greenhouses (CSGs) with an uneven spatial distribution in temperature and humidity, there is a lack of effective strategies for sensor configuration that can reduce sensor usage while monitoring the microclimate precisely. A configuration strategy for integrated temperature–humidity sensors (THSs) based on the improved weighted Hilbert–Schmidt independence criterion (HSIC) is proposed in this paper. The data independence of the THSs in different sites was analyzed based on the improved HSIC, and the selection priority of the THSs was ranked based on the weighted independence of temperature and humidity. Then, according to different cost constraints and monitoring requirements, suitable THSs could be selected sequentially and constitute the monitoring solution. Compared with the original monitoring solution containing twenty-two THSs, the optimized solution used only four THSs (S6, S9 and H6, H5) under strict cost constraints, with a maximum RMSE of the temperature and relative humidity of 0.6 °C and 2.30%, as well as a maximum information gain rate (IGR) of 9.47% and 10.0%. If higher monitoring precision is required, we can increase the THS usage with a greater budget. The optimized solution with six THSs (S6, S9, S8 and H6, H5, H2) could further reduce the maximum RMSE of the temperature and relative humidity to 0.33 °C and 1.10% and the IGR to 6.9% and 8.7%. This indicated that the proposed strategy could use much fewer THSs to achieve accurate and comprehensive monitoring, which would provide efficient and low-cost solutions for CSG microclimate monitoring.
Enhancing the Performance of Sunflower Threshing Machines through Innovative Enhancements
Authors: Ali Khaled Abdeen Mousa , Li Changyou , Wang Han , Mousa Ahmad Mostafa , Mohammed Marwa Abd-Elnaby
Published: February 2024

Improving the performance of the threshing process is of utmost importance in enhancing the quality of sunflower seeds and minimizing power consumption in sunflower production. In this study, we developed a modified sunflower threshing machine by incorporating two types of threshing rotors, namely the angled rasp bar rotor and the tine bar rotor, as compared to the round bar rotor. The performance of these rotors was evaluated under various rotational speeds (150, 200, 250, and 300 rpm) and concave clearances (10, 15, and 20 mm). The evaluation parameters included machine throughput, the specific energy of threshing, the percentage of damaged seeds, the percentage of unthreshed seeds, and threshing efficiency. The results indicate that the specific energy decreased with an increase in rotor speed and a decrease in concave clearance, with the tine bar rotor exhibiting the lowest values. Threshing efficiency showed an increasing trend with higher rotor speeds and reduced concave clearance. The modifications made to the rotor design resulted in an enhanced threshing efficiency, with an improvement from 96.30% to 97.93% achieved at a rotor revolving speed of 300 rpm and a concave clearance of 10 mm. Moreover, the specific energy consumption reduced from 9.65 kW·h/ton to 5.09 kW·h/ton under the same operational conditions. These findings highlight the efficacy of the novel rotor design modifications in optimizing the performance of the stationary sunflower threshing machine, leading to improved efficiency and reduced energy consumption in sunflower seed threshing operations. Given its performance characteristics, this machine exhibits potential suitability for sunflower farms of small to medium scale.
Indoor Temperature Forecasting in Livestock Buildings: A Data-Driven Approach
Authors: Perez Garcia Carlos Alejandro , Bovo Marco , Torreggiani Daniele , Tassinari Patrizia , Benni Stefano
Published: February 2024

The escalating global population and climate change necessitate sustainable livestock production methods to meet rising food demand. Precision Livestock Farming (PLF) integrates information and communication technologies (ICT) to improve farming efficiency and animal health. Unlike traditional methods, PLF uses machine learning (ML) algorithms to analyze data in real time, providing valuable insights to decision makers. Dairy farming in diverse climates is challenging and requires well-designed structures to regulate internal environmental parameters. This study explores the application of the Facebook-developed Prophet algorithm to predict indoor temperatures in a dairy farm over a 72 h horizon. Exogenous variables sourced from the Open-Meteo platform improve the accuracy of the model. The paper details case study construction, data acquisition, preprocessing, and model training, highlighting the importance of seasonality in environmental variables. Model validation using key metrics shows consistent accuracy across different dates, as the mean absolute percentage error on daily base ranges from 1.71% to 2.62%. The results indicate excellent model performance, especially considering the operational context. The study concludes that black box models, such as the Prophet algorithm, are effective for predicting indoor temperatures in livestock buildings and provide valuable insights for environmental control and optimization in livestock production. Future research should explore gray box models that integrate physical building characteristics to improve predictive performance and HVAC system control.
Cherry Tree Crown Extraction Using Machine Learning Based on Images from UAVs
Authors: Moysiadis Vasileios , Siniosoglou Ilias , Kokkonis Georgios , Argyriou Vasileios , Lagkas Thomas , Goudos Sotirios K. , Sarigiannidis Panagiotis
Published: February 2024

Remote sensing stands out as one of the most widely used operations in the field. In this research area, UAVs offer full coverage of large cultivation areas in a few minutes and provide orthomosaic images with valuable information based on multispectral cameras. Especially for orchards, it is helpful to isolate each tree and then calculate the preferred vegetation indices separately. Thus, tree detection and crown extraction is another important research area in the domain of Smart Farming. In this paper, we propose an innovative tree detection method based on machine learning, designed to isolate each individual tree in an orchard. First, we evaluate the effectiveness of Detectron2 and YOLOv8 object detection algorithms in identifying individual trees and generating corresponding masks. Both algorithms yield satisfactory results in cherry tree detection, with the best F1-Score up to 94.85%. In the second stage, we apply a method based on OTSU thresholding to improve the provided masks and precisely cover the crowns of the detected trees. The proposed method achieves 85.30% on IoU while Detectron2 gives 79.83% and YOLOv8 has 75.36%. Our work uses cherry trees, but it is easy to apply to any other tree species. We believe that our approach will be a key factor in enabling health monitoring for each individual tree.
Toxicity of Ethyl Formate to Tribolium castaneum (Herbst) Exhibiting Different Levels of Phosphine Resistance and Its Influence on Metabolite Profiles
Authors: Shan Changyao , You Xinyue , Li Li , Du Xin , Ren Yonglin , Liu Tao
Published: February 2024

Ethyl formate (EF), a naturally occurring fumigant, has attracted widespread attention owing to its low toxicity in mammals. Here, Direct Immersion Solid-Phase Microextraction (DI-SPME) was employed for sample preparation in mass spectrometry-based untargeted metabolomics to evaluate the effects on Tribolium castaneum (Herbst) strains with different levels of PH3 resistance (sensitive, TC-S; moderately resistant, TC-M; strongly resistant, TC-SR) when exposed to a sub-lethal concentration (LC30) of EF. The bioassay indicated that T. castaneum strains with varying PH3 resistance levels did not confer cross-resistance to EF. A metabolomic analysis revealed that exposure to sublethal doses of EF significantly altered 23 metabolites in T. castaneum, including 2 that are unique to the species which remained unaffected by external conditions, while 11 compounds showed a strong response. A pathway topology analysis indicated that EF caused changes to several metabolic pathways, mainly involving fatty acids and their related metabolic pathways. This study showed that EF can induce highly similar metabolic responses in insects across varying levels of PH3 resistance, suggesting that the mechanisms driving the toxicity of EF and PH3 are distinct. These insights significantly extend our knowledge of the toxic mechanisms of EF and provide direct evidence for the efficacy of EF treatment for managing PH3 resistance in insects.
Dicamba and 2,4-D in the Urine of Pregnant Women in the Midwest: Comparison of Two Cohorts (2010–2012 vs. 2020–2022)
Authors: Daggy Joanne K. , Haas David M. , Yu Yunpeng , Monahan Patrick O. , Guise David , Gaudreau Éric , Larose Jessica , Benbrook Charles M.
Published: February 2024

Currently, there are no known human biomonitoring studies that concurrently examine biomarkers of dicamba and 2,4-D. We sought to compare biomarkers of exposure to herbicides in pregnant women residing in the US Midwest before and after the adoption of dicamba-tolerant soybean technology using urine specimens obtained in 2010–2012 from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (N = 61) and in 2020–2022 from the Heartland Study (N = 91). Specific gravity-standardized concentration levels for each analyte were compared between the cohorts, assuming data are lognormal and specifying values below the LOD as left-censored. The proportion of pregnant individuals with dicamba detected above the LOD significantly increased from 28% (95% CI: 16%, 40%) in 2010–2012 to 70% (95% CI: 60%, 79%) in 2020–2022, and dicamba concentrations also significantly increased from 0.066 μg/L (95% CI: 0.042, 0.104) to 0.271 μg/L (95% CI: 0.205, 0.358). All pregnant individuals from both cohorts had 2,4-D detected. Though 2,4-D concentration levels increased, the difference was not significant (p-value = 0.226). Reliance on herbicides has drastically increased in the last ten years in the United States, and the results obtained in this study highlight the need to track exposure and impacts on adverse maternal and neonatal outcomes.
Exploring the Impact of Alternate Wetting and Drying and the System of Rice Intensification on Greenhouse Gas Emissions: A Review of Rice Cultivation Practices
Authors: Dahlgreen James , Parr Adam
Published: February 2024

Rice provides ~20% of human dietary energy and, for many people, a similar share of their protein. Rice cultivation, however, produces significant greenhouse gas (GHG) emissions, comparable to those from the aviation sector. The main GHG from rice production is methane, mostly a result of conventional rice cultivation (CRC) keeping rice fields continuously flooded during the crop cycle. There is extensive evidence that alternate wetting and drying (AWD) of rice fields substantially reduces methane emissions. AWD is one component of the System of Rice Intensification (SRI), an agroecological approach to the management of plants, water, soil, and nutrients. This article reviews field studies measuring GHG emissions associated with the adoption of AWD and SRI. The review confirms that both AWD and SRI offer substantial reductions in methane emissions per hectare compared with CRC. These benefits are, however, partly offset by increases in emissions of nitrous oxide and carbon dioxide. The studies also show that SRI (but not AWD) improves yield and therefore further reduces GHG emissions per kg of rice. The review concludes that while both AWD and SRI substantially reduce emissions per hectare and per kilogram of rice, SRI can simultaneously contribute to food security while addressing the drivers of climate change. Further investigation of carbon emissions and sequestration under different rice cultivation methods is needed to strengthen the evidence base.
Effects of Cd Stress on Morphological and Physiological Characteristics of Maize Seedlings
Authors: Deng Siqing , Wu Yueying , Zeng Qingping , Zhang Aoni , Duan Meijuan , Deng Min
Published: February 2024

Heavy metal (HM) contamination poses a serious threat to safe crop production and human health, and different maize inbred lines respond differently to cadmium (Cd) stress. However, the morphological and physiological characteristics of maize inbred lines seedlings are not clear under Cd stress. In this study, we analyzed the agronomic traits and physiological and biochemical indices of inbred maize seedlings under Cd stress in the seedling stage using the inbred lines Kui3, CML118, Mo17, B73, and B77 as the materials. These five inbred maizes were treated with five different concentrations of Cd (0, 1, 3, 5, and 7 mg L−1, respectively) were applied and the indices of the maize seedlings determined on day 15. The aboveground and belowground biomass of five maize inbred lines seedlings showed a decreasing trend under Cd stress. Leaf relative water content and SPAD values also decreased, but the overall decrease in relative water content was small, and the differences were not significant. Surprisingly, Cd stress affected the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), leading to enhanced mem-brane lipid peroxidation. The cadmium content varied greatly between varieties under Cd stress, but all of them had lower Cd content above ground than below ground, and the varieties with the highest and lowest transfer coefficients were Mo17 (0.33–0.83) and B73 (0.06–0.44), respectively. Kui3 had the greatest difference in soluble protein content under Cd stress, which showed a de-creasing trend, and the soluble sugar content was significantly decreased in general compared to that of CK. The soluble sugar content was higher than CK under Cd treatment, and the proline content of the maize seedlings of all of the inbred lines showed an increasing trend compared to CK. Overall, there were significant genotypic differences in the Cd stress response to Cd toxicity in the maize inbred lines seedlings, and, in general, this study helps us to understand the mechanism of maize inbred lines seedlings response to Cd stress. It provides a theoretical basis for the se-lection and breeding of varieties, and food safety.
Effect of Different Sowing Seasons, Growth Stages, Leaf Positions, and Soybean Varieties on the Growth of Clanis bilineata tsingtauica Mell Larvae
Authors: Liu Nan , Yan Yulu , Yang Longwei , Xu Yufei , Jiang Huiyan , Ye Zhihao , Wang Hao , Gai Junyi , Xing Guangnan
Published: February 2024

Clanis bilineata tsingtauica Mell (Lepidoptera: Sphingidae, CBT), as a traditional edible insect, is becoming popular in China due to its high nutritional value, but production needs to be improved to meet the expanding market. In the present study, CBT eggs were artificially inoculated on soybean leaves to evaluate the effects of leaf position, growth stage, sowing season, and soybean variety on CBT larval growth, respectively. The results showed that (1) the larval weight and survival rate were poorly correlated, so they could represent two different larval growth and development indicators for CBT. The 21-day-old larval weight was significantly different between the sowing seasons and between soybean growth stages, which was suitable as a key indicator for evaluating CBT larval rearing factors. (2) Compared with autumn-sown soybeans, the weight of 21-day-old larvae feeding on V6 stage (sixth trifoliolate) leaves of summer-sown soybeans was significantly higher, with an average increase of 44.7%. (3) Under autumn sowing conditions, the weight of 21-day-old larvae feeding on soybeans in the V6 stage was significantly higher than those fed on soybeans in the R3 stage (beginning pod), increasing by 33.9%. (4) Under summer sowing conditions, the weight of 21-day-old larvae feeding on the third-top leaf (the third leaf from the top of the soybeans’ main stem) was significantly higher than those feeding on the third-bottom leaf (the third leaf from the bottom of the soybeans’ main stem) at V6 stage by 35.7%. Similar results also appeared in autumn sowing; the average weights of 21-day-old larvae feeding on the third-top leaf increased significantly by 29.9% compared to those feeding on the third-bottom leaf. Moreover, the survival rate of larvae fed with the third-top leaf was significantly higher than that of those fed with the third-bottom leaf at the V6 stage in autumn sowing. Leaf position is the main factor affecting the survival rate of larvae. (5) Under summer sowing conditions, the weights of larvae fed with the third-top leaf of the susceptible-soybean varieties NN89-29 and NN1138-2 were significantly higher than that of those fed with the third-bottom leaf of these varieties. This difference was significantly reduced with autumn sowing. In conclusion, the CBT eggs inoculated on the third-top leaf of NN89-29 and NN1138-2 at the V6 stage in summer sowing could achieve maximum larval yield.
Use of Cactus Pear Meal in the Feeding of Laying Hens in Semi-Intensive System
Authors: Sousa Iara S. , Bezerra Roseane M. , Silva Filho Edson C. , Bezerra Leilson R. , Edvan Ricardo L. , Lima Stelio B. P. , Lopes Elainy Cristina , Carvalho Francisca Luana A. , Moura Francinete A. S. , Souza Gabriela I. , Dourado Leilane R. B.
Published: February 2024

Little information is available in the literature on the use of cactus pear meal (CPM) in poultry diets; therefore, it is important to evaluate diets that provide excellent performance and lower production costs. Our objective was to study the use of Miúda CPM in the diets of laying hens. In the first study, two diets for male and female chicks were used—1: 80% reference diet + 20% Miúda cactus pear meal (CPM) and 2: 80% reference diet + 20% Gigante cactus pear meal (CPM). The variety Miúda provided a better use of metabolizable energy, as well as a greater digestibility coefficient of dry matter, protein, and mineral matter. In the second study, a control diet was compared to three diets with different levels of Miúda CPM for laying hens in the proportions of 3%, 6%, and 9%. No significant differences were found in productive performance. However, there were significant differences in the some parameters egg quality, texture and color profile of the cooked yolk, egg composition, fatty acids and cholesterol in the yolk. It is possible to use 9% Miúda CPM in the diet of laying hens in a semi-intensive system that does not compromise performance and egg quality, and using 3% Miúda CPM provides a higher economic return.
Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview
Authors: Kamel Mohamed S. , Davidson Josiah Levi , Verma Mohit S.
Published: February 2024

Despite significant advances in vaccination strategies and antibiotic therapy, bovine respiratory disease (BRD) continues to be the leading disease affecting the global cattle industry. The etiology of BRD is complex, often involving multiple microbial agents, which lead to intricate interactions between the host immune system and pathogens during various beef production stages. These interactions present environmental, social, and geographical challenges. Accurate diagnosis is essential for effective disease management. Nevertheless, correct identification of BRD cases remains a daunting challenge for animal health technicians in feedlots. In response to current regulations, there is a growing interest in refining clinical diagnoses of BRD to curb the overuse of antimicrobials. This shift marks a pivotal first step toward establishing a structured diagnostic framework for this disease. This review article provides an update on recent developments and future perspectives in clinical diagnostics and prognostic techniques for BRD, assessing their benefits and limitations. The methods discussed include the evaluation of clinical signs and animal behavior, biomarker analysis, molecular diagnostics, ultrasound imaging, and prognostic modeling. While some techniques show promise as standalone diagnostics, it is likely that a multifaceted approach—leveraging a combination of these methods—will yield the most accurate diagnosis of BRD.
Enhancing Weaned Piglet Health and Performance: The Role of Autolyzed Yeast (Saccharomyces cerevisiae) and β-Glucans as a Blood Plasma Alternative in Diets
Authors: Barducci Robson Sfaciotti , Santos Anderson Aparecido Dias , Pacheco Leticia Graziele , Putarov Thaila Cristina , Koch João Fernando Albers , Callegari Marco Aurélio , Dias Cleandro Pazinato , de Carvalho Rafael Humberto , da Silva Caio Abércio
Published: February 2024

The objective of this study was to evaluate the inclusion of the autolyzed yeast (AY) Saccharomyces cerevisiae with or without an immunomodulator (1,3/1,6 β-glucans) as a total/partial substitute for blood plasma (BP) in the diet of post-weaning piglets; zootechnical performance, intestinal health and microbiota, immune responses and energy metabolism were assessed. A total of 240 castrated male and female piglets, with a mean age of 22 days and mean initial weight of 5.24 ± 0.82 kg, were randomly divided into blocks of four treatments with 12 replicates. The dietary inclusions were blood plasma (BP), autolyzed yeast (AY), autolyzed yeast + immunomodulator (AYI) and 50% BP and 50% AY (BPAY). In pre-initial phase II (29–35 days), piglets fed AY showed better feed conversion (FCR = 1.358) than the piglets in the BP (1.484), AYI (1.379) and BPAY (1.442) groups, i.e., 8.49% (0.126), 1.52% (0.021) and 4.50% (0.084), respectively (p = 0.0293). In the total period (21–42 days), better FCR was observed in the AYI (1.458) group, i.e., 4.64% (0.071), 1.15% (0.017) and 4.58% (0.070), than in the BP (1.529), AY (1.475) and BPAY (1.528) groups, respectively (p = 0.0150). In piglets fed AY (n = 3) and BPAY (n = 2), there was a reduction in the number of medications, i.e., 82.35% (−14n) and 88.23% (−15n), respectively (p = 0.0001), compared with that in the BP group (n = 17). In the AY group (73.83 mg/dL), AYI group (69.92 mg/dL), and BPAY group (69.58 mg/dL), piglets exhibited increases in triglyceride levels of 79.32%, 69.83%, and 69.00%, respectively, in comparison to those in the BP group, which had triglyceride levels of 41.17 mg/dL (p = 0.0400). The beta-hydroxybutyrate concentration in the AY group (79.96 ng/μL) was lower by 31.95%, 22.64%, and 5.89% compared to the BP group (117.50 ng/μL), AYI group (103.36 ng/μL), and BPAY group (84.67 ng/μL), respectively (p = 0.0072). In the AYI group, there was modulation of the microbiota, with an increase in the relative abundance of bacteria of the genera Lactobacillus, Collinsella and Bulleidia. AY, associated or not associated with an immunomodulator, is a potential substitute for BP in diets for piglets in the nursery phase, with positive effects on immune, metabolic, and intestinal microbial performance.
Blackleg: A Review of the Agent and Management of the Disease in Brazil
Authors: Sousa Ananda Iara de Jesus , Galvão Cleideanny Cancela , Pires Prhiscylla Sadanã , Salvarani Felipe Masiero
Published: February 2024

The genus Clostridium is an important group of pathogenic and nonpathogenic Gram-positive anaerobic bacteria with a sporulation capacity and wide distribution in different environments, including the gastrointestinal tracts of healthy and diseased animals and humans. Among the pathogenic species of the genus, Clostridium chauvoei stands out as a histotoxic agent. It causes significant myonecrosis such as blackleg, a disease with high lethality, especially in young cattle, and is responsible for significant livestock losses worldwide. The pathogenicity of the disease is complex and has not yet been fully elucidated. Current hypotheses cover processes from the initial absorption to the transport and deposition of the agent in the affected tissues. The virulence factors of C. chauvoei have been divided into somatic and flagellar antigens and soluble antigens/toxins, which are the main antigens used in vaccines against blackleg in Brazil and worldwide. This review provides important information on the first and current approaches to the agent C. chauvoei and its virulence factors as well as a compilation of data on Brazilian studies related to blackleg.
Optimization of Deposition Parameters of SnO2 Particles on Tubular Alumina Substrate for H2 Gas Sensing
Authors: Lee Myoung Hoon , Mirzaei Ali , Kim Hyoun Woo , Kim Sang Sub
Published: February 2024

Resistive gas sensors, which are widely used for the detection of various toxic gases and vapors, can be fabricated in planar and tubular configurations by the deposition of a semiconducting sensing layer over an insulating substrate. However, their deposition parameters are not often optimized to obtain the highest sensing results. Here, we have investigated the effect of deposition variables on the H2 gas sensing performance of commercially available SnO2 particles on tubular alumina substrate. Utilizing a tubular alumina substrate equipped with gold electrodes, we varied the number of deposited layers, rotational speed of the substrate, and number of rotations of the substrate on the output of the deposited sensor in terms of response to H2 gas. Additionally, the effect of annealing temperatures (400, 500, 600, and 700 °C for 1 h) was investigated. According to our findings, the optimal conditions for sensor fabrication to achieve the best performance were the application of one layer of the sensing material on the sensor with ten rotations and a rotation speed of 7 rpm. In addition, annealing at a lower temperature (400 °C) resulted in better sensor performance. The optimized sensor displayed a high response of ~12 to 500 ppm at 300 °C. This study demonstrates the importance of optimization of deposition parameters on tubular substrates to achieve the best gas sensing performance, which should be considered when preparing gas sensors.
A Soft Measurement Method for the Tail Diameter in the Growing Process of Czochralski Silicon Single Crystals
Authors: Jiang Lei , Teng Da , Zhao Yue
Published: February 2024

In the Czochralski silicon single crystal growth process, the tail diameter is a key parameter that cannot be directly measured. In this paper, we propose a real-time soft measurement method that combines a deep belief network (DBN) and a support vector regression (SVR) network based on system identification to accurately predict the crystal diameter. The main steps of the proposed method are as follows: First, we address the delay problem of the effects of the temperature and crystal pulling speed on the tail diameter growth by using a back propagation (BP) neural network based on the mean impact value (MIV) method to determine the optimal delay time. Second, we construct a prediction model of the tail diameter by using the DBN network with the temperature and crystal pulling speed as input variables in the crystal growth process. Third, we improve the DBN network by using the SVR network to enhance its linear regression capability. We also employ the ant colony optimization (ACO) algorithm to obtain the optimal parameters of the SVR network. Finally, we compare the performance of the DBN-ACO-SVR network based on system identification with the DBN and SVR networks, and the results show that our method can effectively deal with the delay problem and achieve the accurate prediction of the tail diameter in the Czochralski silicon single crystal growth process.
A Practical Approach to Using Energy Integration in the Simulation of Biomass Thermochemical Processes: Application to Supercritical Water Gasification
Authors: Gutiérrez Ortiz Francisco Javier , López-Guirao F.
Published: February 2024

Solid biomass is usually simulated by decomposing it into a solid phase (carbon, ash, and sulfur) and a gas phase (water and diatomic molecules of H2, N2, O2, and Cl2) from the proximate and ultimate analysis before entering a reactor operating under chemical equilibrium when using Aspen Plus. However, this method prevents the use of energy integration for the feed stream from the system inlet to the reactor. This paper proposes an approach to solving this issue, considering biomass with both known and unknown chemical compositions; the latter involves the decomposition of biomass into complex molecular compounds. Different process arrangements were assessed to achieve a realistic simulation, and a sensitivity analysis was carried out to examine the effect of the concentration and heating upstream of the reactor, focused on supercritical water gasification (SCWG) of orange peel. This process is very energy-intensive, so the approach is useful for a better calculation of the energy requirement and exergy losses in a plant; these are usually and mainly related to the train of heat exchangers. In addition to this application to SCWG, this approach can be used for any other thermochemical process, such as gasification, pyrolysis, or combustion, and for any real biomass. Upon a base case study using a wet biomass of 10,000 kg/h with 90 wt.% water where the SCWG reaction takes place at 240 bar and 800 °C, if the temperature at the SCWG reactor inlet increases from 350 °C to 400 °C, the heat exchange increases by 57% from 4 MW and by 34% if the water content decreases to 70 wt.%, although more heat relative to the solid is saved.
A Survey of Preservatives Used in Cosmetic Products
Authors: Poddębniak Patrycja , Kalinowska-Lis Urszula
Published: February 2024

The aim of this study was to indicate the type of preservatives used in selected categories of cosmetic products sold in Poland (part of the EU market) and determine the frequency of their use. The tested products consisted of 200 leave-on cosmetics, viz. body lotions (n = 100) and face creams (n = 100) and rinse-off cosmetics (n = 100) and mascaras (n = 25). The product labels of 325 adult cosmetic products from international brands were analyzed for the presence of preservatives based on the INCI compositions. The survey focused on preservatives included in Annex V of the Regulation (EC) No. 1223/2009 of the European Parliament and Council of 30 November 2009 on cosmetic products. The tested products contained 29 different preservatives belonging to eight chemical groups. Most preservatives were alcohols or their derivatives, carboxylic acids or their salts, or parabens. The most common types were phenoxyethanol, present in 198/325 (60.9%) formulations, followed by sodium benzoate, in 137 (42.2%), potassium sorbate, in 116 (35.7%), benzyl alcohol, in 76 (23.4%), and methylparaben in 33 (10.2%). Also, 33 of the 60 preservatives included in Annex V of Regulation (EC) No. 1223/2009 were not used in any of the tested preparations. In each category of products, the most common were combinations of two preservatives per single product (34.8% of all products), followed by single-preservative products (25.5%) and three-preservative products (19.4%).
Performance Development of Fluidic Oscillator Nozzle for Cleaning Autonomous-Driving Sensors
Authors: Kim Chan-Hoo , Choi Ji-Hyun , Park Sung-Young
Published: February 2024

Contaminated autonomous-driving sensors frequently malfunction, resulting in accidents; these sensors need regular cleaning. The autonomous-driving sensor-cleaning nozzle currently used is the windshield-washer nozzle; few studies have focused on the sensor-cleaning nozzle. We investigated the flow characteristics of the nozzle to improve its performance in cleaning the autonomous-driving sensor. The nozzle concept was based on the fluidic oscillator nozzle. Various performance parameters of the fluidic oscillator nozzle were selected and investigated. Transient fluid flow was simulated to determine the effect of the design parameters to maximize the oscillation flow phenomenon. Additionally, the spray angle and frequency were calculated. Analysis results showed that the change in flow speed affects the frequency, and the change in feedback-channel-inlet flow rate affects the angle change. To verify the simulation result, the three best models (R4+RC10, R6+RC11, R8+RC10) and the base model were manufactured and tested. The test results were consistent with the simulation results within a 6% error.
Enhancing Safety in Automatic Electric Vehicle Charging: A Novel Collision Classification Approach
Authors: Lin Haoyu , Quan Pengkun , Liang Zhuo , Wei Dongbo , Di Shichun
Published: February 2024

With the rise of electric vehicles, autonomous driving, and valet parking technologies, considerable research has been dedicated to automatic charging solutions. While the current focus lies on charging robot design and the visual positioning of charging ports, a notable gap exists in addressing safety aspects during the charging plug-in process. This study aims to bridge this gap by proposing a collision classification scheme for robot manipulators in automatic electric vehicle charging scenarios. In situations with minimal visual positioning deviation, robots employ impedance control for effective insertion. Significant deviations may lead to potential collisions with other vehicle parts, demanding discrimination through a global visual system. For moderate deviations, where a robot’s end-effector encounters difficulty in insertion, existing methods prove inadequate. To address this, we propose a novel data-driven collision classification method, utilizing vibration signals generated during collisions, integrating the robust light gradient boosting machine (LightGBM) algorithm. This approach effectively discerns the acceptability of collision contacts in scenarios involving moderate deviations. Considering the impact of passing vehicles introducing environmental noise, a noise suppression module is introduced into the proposed collision classification method, leveraging empirical mode decomposition (EMD) to enhance its robustness in noisy charging scenarios. This study significantly contributes to the safety of automatic charging processes, offering a practical and applicable collision classification solution tailored to diverse noisy scenarios and potential contact forms encountered by charging robots. The experimental results affirm the effectiveness of the collision classification method, integrating LightGBM and EMD, and highlight its promising prediction accuracy. These findings offer valuable perspectives to steer future research endeavors in the domain of autonomous charging systems.
Automatic Feature Construction-Based Genetic Programming for Degraded Image Classification
Authors: Sun Yu , Zhang Zhiqiang
Published: February 2024

Accurately classifying degraded images is a challenging task that relies on domain expertise to devise effective image processing techniques for various levels of degradation. Genetic Programming (GP) has been proven to be an excellent approach for solving image classification tasks. However, the program structures designed in current GP-based methods are not effective in classifying images with quality degradation. During the iterative process of GP algorithms, the high similarity between individuals often results in convergence to local optima, hindering the discovery of the best solutions. Moreover, the varied degrees of image quality degradation often lead to overfitting in the solutions derived by GP. Therefore, this research introduces an innovative program structure, distinct from the traditional program structure, which automates the creation of new features by transmitting information learned across multiple nodes, thus improving GP individual ability in constructing discriminative features. An accompanying evolution strategy addresses high similarity among GP individuals by retaining promising ones, thereby refining the algorithm’s development of more effective GP solutions. To counter the potential overfitting issue of the best GP individual, a multi-generational individual ensemble strategy is proposed, focusing on constructing an ensemble GP individual with an enhanced generalization capability. The new method evaluates performance in original, blurry, low contrast, noisy, and occlusion scenarios for six different types of datasets. It compares with a multitude of effective methods. The results show that the new method achieves better classification performance on degraded images compared with the comparative methods.
Hydraulic Characterization of Green Roof Substrates by Evaporation Experiments
Authors: Autovino Dario , Alagna Vincenzo , Bondì Cristina , Iovino Massimo
Published: February 2024

Green roofs can be a valid solution for stormwater management in urban environments. The objective of this study was to develop a laboratory procedure for the hydraulic characterization of artificial substrates, used in the realization of green roofs, based on transient evaporation and steady-state unit hydraulic gradient (UHG) experiments. The retention, θ(h), and hydraulic conductivity, K(h), curves of two commercial substrates Terra Mediterranea® (TMT) and AgriTERRAM® (ATV) and a specifically developed substrate made by mixing peat, compost and sandy loam soil (MIX) were investigated. The unimodal van Genuchten–Mualem (VGM) hydraulic functions obtained by the direct evaporation method with different choices of the fitting parameters were compared with UHG measurements of K(h) conducted close to saturation. A numerical inversion of the transient evaporation experiments performed by Hydrus-1D software was also conducted, assuming that the hydraulic properties could be expressed either by unimodal or bimodal VGM models. The results indicated that an appropriate a priori choice of the residual water content parameter improved the estimation of the water retention curve. Moreover, the water retention data estimated from the direct evaporation method were not statistically different from those obtained with the inverse Hydrus-1D. The unsaturated hydraulic conductivity estimations obtained by the direct and inverse methods were highly correlated and the use of the bimodal VGM model improved the estimation of K(h) in the wet range. The numerical inversion of laboratory evaporation data with the hydraulic characteristics expressed by the bimodal VGM model proved to be a reliable and effective procedure for hydraulic characterization of artificial substrates, thus improving the reliability of simulated water fluxes in green roofs.
Do Continuous Rotating Endodontic Instruments Extrude Fewer Apical Debris Than Reciprocating Instruments in Non-Surgical Endodontic Retreatments? A Systematic Review
Authors: Puleio Francesco , Giordano Francesco , Bellezza Ugo , Rizzo David , Coppini Valentina , Lo Giudice Roberto
Published: February 2024

Background: All endodontic treatment techniques are associated with the extrusion of debris into periradicular tissues through the apex. The extrusion of apical debris can lead to delayed healing or even therapy failure. It is possible to reduce the extrusion into periapical tissues through various approaches. The objective of this systematic review is to evaluate whether, in cases of non-surgical endodontic retreatment, reciprocating instruments cause greater extrusion of debris compared to instruments with continuous rotation. Methods: A search was conducted on PubMed, Ovid MEDLINE, and the Web of Science. The inclusion criterion was in vitro studies comparing apical extrusion in endodontically treated elements using continuously rotating and reciprocating files. Results: The search on scientific databases yielded 164 results, out of which only 16 were eligible for evaluation after screening. Conclusions: The authors of the research included in this review do not agree on the results obtained. Based on the articles analyzed in this systematic review, it remains unclear whether continuous rotation or reciprocating movement of the endodontic instrument can lead to significant differences in apical debris extrusion; it is not possible to provide a clear clinical recommendation regarding the choice of instrument movement for endodontic procedures.
Motion Planning for Autonomous Vehicles in Unanticipated Obstacle Scenarios at Intersections Based on Artificial Potential Field
Authors: Mu Rui , Yu Wenhao , Li Zhongxing , Wang Changjun , Zhao Guangming , Zhou Wenhui , Ma Mingyue
Published: February 2024

In unanticipated obstacle scenarios at intersections, the safety and mobility of autonomous vehicles (AVs) are negatively impacted due to the conflict between traffic law compliance and obstacle avoidance. To solve this problem, an obstacle avoidance motion planning algorithm based on artificial potential field (APF) is proposed. An APF-switching logic is utilized to design the motion planning framework. Collision risk and travel delay are quantified as the switching triggers. The intersection traffic laws are digitalized and classified to construct compliance-oriented potential fields. A potential violation cost index (PVCI) is designed according to theories of autonomous driving ethics. The compliance-oriented potential fields are reconfigured according to the PVCI, forming violation cost potential fields. A cost function is designed based on compliance-oriented and violation cost potential fields, integrated with model predictive control (MPC) for trajectory optimization and tracking. The effectiveness of the proposed algorithm is verified through simulation experiments comparing diverse traffic law constraint strategies. The results indicate that the algorithm can help AVs avoid obstacles safely in unanticipated obstacle scenarios at intersections.
SCGFormer: Semantic Chebyshev Graph Convolution Transformer for 3D Human Pose Estimation
Authors: Liang Jiayao , Yin Mengxiao
Published: February 2024

With the rapid advancement of deep learning, 3D human pose estimation has largely freed itself from reliance on manually annotated methods. The effective utilization of joint features has become significant. Utilizing 2D human joint information to predict 3D human skeletons is of paramount importance. Effectively leveraging 2D joint data can improve the accuracy of 3D human skeleton prediction. In this paper, we propose the SCGFormer model to reduce the error in predicting human skeletal poses in three-dimensional space. The network architecture of SCGFormer encompasses Transformer and two distinct types of graph convolution, organized into two interconnected modules: SGraAttention and AcChebGconv. SGraAttention extracts global feature information from each 2D human joint, thereby augmenting local feature learning by integrating prior knowledge of human joint relationships. Simultaneously, AcChebGconv broadens the receptive field for graph structure information and constructs implicit joint relationships to aggregate more valuable adjacent features. SCGraFormer is tested on widely recognized benchmark datasets such as Human3.6M and MPI-INF-3DHP and achieves excellent results. In particular, on Human3.6M, our method achieves the best results in 9 actions (out of a total of 15 actions), with an overall average error reduction of about 1.5 points compared to state-of-the-art methods, demonstrating the excellent performance of SCGFormer.