bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Temperature on the Functionalization Process of Structural Self-Healing Epoxy Resin
Authors: Vertuccio Luigi , Calabrese Elisa , Raimondo Marialuigia , Catauro Michelina , Sorrentino Andrea , Naddeo Carlo , Longo Raffaele , Guadagno Liberata
Published: May 2023

This work deals with developing a self-healing resin designed for aeronautical and aerospace applications. The bifunctional epoxy precursor was suitably functionalized to enhance its toughness to realize good compatibilization with a rubber phase dispersed in the hosting epoxy resin. Subsequently, the resulting mixture was loaded with healing molecules. The effect of the temperature on the epoxy precursor’s functionalization process was deeply studied. Fourier trans-former infrared (FT-IR) spectroscopy and dynamic mechanical analyses (DMA) evidenced that the highest temperature (160 °C) allows for obtaining a bigger amount of rubber phase bonded to the matrix. Elastomeric domains of dimensions lower than 500–600 nanometers were found well distributed in the matrix. Self-healing efficiency evaluated with the tapered double cantilever beam (TDCB) method evidenced a healing efficiency for the system functionalized at 160 °C higher than 69% for all the explored fillers. The highest value was detected for the sample with DBA, for which 88% was found. The healing efficiency of the same sample functionalized at 120 °C was found to decrease to the value of 52%. These results evidence the relevant role of the amount and distribution of rubber domains into the resin for improving the resin’s dynamic properties. The adopted strategy allows for optimizing the self-healing performance.
Numerical Study on Asteroid Deflection by Penetrating Explosion Based on Single-Material ALE Method and FE-SPH Adaptive Method
Authors: Han Pengfei , He Qiguang , Chen Xiaowei , Lv He
Published: May 2023

An asteroid impact can potentially destroy life on this planet. Therefore, asteroids should be prevented from impacting the Earth to impede severe disasters. Nuclear explosions are currently the only option to prevent an incoming asteroid impact when the asteroid is large or the warning time is short. However, asteroids exist in an absolute vacuum, where the explosion energy propagation mechanism differs from that in an air environment. It is difficult to describe this process using standard numerical simulation methods. In this study, we used the single-material arbitrary Lagrangian–Eulerian (ALE) method and the finite element-smoothed particle hydrodynamics (FE-SPH) adaptive method to simulate the process of deflecting hazardous asteroids using penetrating explosions. The single-material ALE method can demonstrate the expansion process of explosion products and energy coupling in absolute vacuum. The FE-SPH adaptive method can transform failed elements into SPH particles during the simulation, avoiding system mass loss, energy loss, and element distortion. We analyzed the shock initiation and explosion damage process and obtained an effective simulation of the damage evolution, stress propagation, and fragment distribution of the asteroid. In addition, we decoupled the penetrating explosion into two processes: kinetic impact and static explosion at the impact crater. The corresponding asteroid damage modes, velocity changes, and fragmentation degrees were simulated and compared. Finally, the high efficiency of the nuclear explosion was confirmed by comparing the contribution rates of the kinetic impact and nuclear explosion in the penetrating explosion scheme.
Calibration of Ramie Stalk Contact Parameters Based on the Discrete Element Method
Authors: Hu Yao , Xiang Wei , Duan Yiping , Yan Bo , Ma Lan , Liu Jiajie , Lyu Jiangnan
Published: May 2023

To obtain the physical parameters and contact parameters of ramie stalk decorticating simulation, the structural dimensions, density, moisture content, elastic modulus, and contact parameters of the ramie stalk were measured in this study based on the phloem and xylem of the ramie stalk. The physical stacking angles of the phloem and xylem were measured by the cylinder lift method and the extraction of the partition method, respectively. The contact parameters between the xylem and phloem of the ramie stalk were directly calibrated. Additionally, the contact parameters of the phloem–phloem, phloem–Q235A steel, xylem–xylem, and xylem–Q235A steel were used as calibration objects, and the simulated stacking angle was used as the evaluation index. Then, the Plackett–Burman test was designed to screen for the parameters which were significantly affecting the simulated stacking angle. Furthermore, the steepest ascent test determined the optimal range of values for two significant parameters of the phloem and three significant parameters of the xylem. Based on the central composite design, the second-order regression equations between the significant parameters of the phloem and xylem and the stacking angle were established, respectively. The physical stacking angles of 37.93° for phloem and 27.17° for xylem were the target values to obtain the optimal parameter group. The results showed that the restitution, static, and rolling friction coefficients between the xylem and phloem were 0.60, 0.53, and 0.021, respectively. The static and rolling friction coefficients between the phloem and phloem were 0.41 and 0.056, respectively. The rolling friction coefficient between the xylem and Q235A steel was 0.033, and the static and rolling friction coefficients between the xylem and xylem were 0.44 and 0.016, respectively. The verification test showed that the relative error values were less than 2.11%, which further indicated that the modeling method and parameter calibration of the ramie stalk phloem and xylem models were accurate and reliable. They can be used for the subsequent calibration simulation tests of ramie stalk bonding parameters and ramie stalk decorticating simulations.
Innovative Design Method of Hydro-Pneumatic Suspension for Large High-Clearance Sprayer Based on Improved NSGA-II Algorithm
Authors: Yang Fan , Du Yuefeng , Li Wei , Li Zhen , Mao Enrong , Zhu Zhongxiang
Published: May 2023

Large high-clearance sprayers are widely used in the field of plant protection due to their high work efficiency. Influenced by the characteristics of a large ground clearance, fast driving speed and constantly changing sprung mass, how to solve the contradiction between the vibration reduction performance of a large sprayer and the friendliness of farmland roads has become a current research hotspot. In order to improve the driving performance of the sprayers, the design, optimization and verification scheme of the hydro-pneumatic suspension of a large sprayer based on the improved NSGA-II algorithm was completely constructed in this study. The hydro-pneumatic suspension system of a sprayer was mainly designed and a real-time time-varying model under field road excitation was established. The NSGA-II algorithm was improved by introducing the adaptive crossover operator and DE mutation operator, and a real-time interactive interface between the time-varying model was established for multi-objective optimization. Finally, system simulation analysis was conducted and a vibration test bench was built for experimental verification. The results show that vibration reduction indicators improved by 19.4%, 10.7% and 4.0%, respectively, compared with those before optimization. The performance of the designed hydro-pneumatic suspension was better than that of the ordinary suspension.
A Step toward Water Use Sustainability: Implementing a Business Model Canvas for Irrigation Advisory Services
Authors: Santini Alessandra , Di Fonzo Antonella , Giampietri Elisa , Martelli Andrea , Cimino Orlando , Dalla Marta Anna , Annosi Maria Carmela , Blanco-Velázquez Francisco José , Del Giudice Teresa , Altobelli Filiberto
Published: May 2023

Some major future global challenges are linked to more efficient use of water for irrigation to respond to the growing water scarcity coupled with the increasing food demand. Although irrigation advisory services (IASs) are considered effective instruments to increase water use efficiency in agriculture, their diffusion remains limited. This is due to several constraints mainly linked to their low accessibility and high costs. To overcome the bottlenecks associated with IASs’ adoption, this paper proposes a business model (BM) as a tool for scaling up IASs within a business perspective, with the aim of encouraging the diffusion of this technology while enhancing the associated environmental and social benefits. Drawn from the experience of the OPERA project, we structured the business model taking advantage of the opinion of relevant stakeholders and IASs’ potential users to identify specific limitations and understand their needs. It turned out that farmers are willing to adopt IASs but require that the service is easily accessible, with high-quality information that are delivered at an affordable cost. Indeed, here a BM with an innovative way to produce and deliver value is proposed. The value proposition is built upon key features namely, integration, customization, accessibility, and sustainability that reflect users’ needs and preferences. Our BM also provides a detailed revenues strategy that guarantees the financial sustainability of IASs. To design and represent our BM, the “Business Model Canvas ©” has been adopted. We concluded that an innovative and well-structured BM has the potential to leave the IASs profitable and capable to ensure environmental and social sustainability.
Non-Invasive Single-Grain Screening of Proteins and Other Features by Combination of Near-Infrared Spectroscopy and Nuclear Magnetic Resonance
Authors: Keil Peter , Gündel Beate , Gündel André , Rolletschek Hardy , Borisjuk Ljudmilla
Published: May 2023

The non-invasive analysis of seeds is of great interest to experimental biologists and breeders. To reach a high varietal identity and purity of seed material, it is often necessary to access features of individual seeds via the screening of mutant populations. While near-infrared spectroscopy (NIRS) and time-domain nuclear-magnetic-resonance spectroscopy (TD-NMR) are well-known in seed research and industry for bulk seed measurements, their application for individual seeds is challenging. Here we demonstrate how to overcome this limitation using a practical approach to cereal grains using oat (Avena sp.) as a model. For this, we generated a representative collection of oat seeds from the ex situ German federal gene bank, which includes wide variation in grain size, shape, and coloration. Next, we established a short experimental pipeline to exemplify how to improve the procedure for individual seed measurements. In its current state, the method is ready to use for the high-accuracy estimation of nitrogen (protein) content (R2 = 0.877), water content (R2 = 0.715), and seed weight (R2 = 0.897) of individual oat grains. This work introduces the combination of NIRS and TD-NMR as an efficient, precise, and, most importantly, non-destructive analytic platform for a high throughput analysis of individual intact seeds.
Artificial Intelligence: Implications for the Agri-Food Sector
Authors: Taneja Akriti , Nair Gayathri , Joshi Manisha , Sharma Somesh , Sharma Surabhi , Jambrak Anet Rezek , Roselló-Soto Elena , Barba Francisco J. , Castagnini Juan M. , Leksawasdi Noppol , Phimolsiripol Yuthana
Published: May 2023

Artificial intelligence (AI) involves the development of algorithms and computational models that enable machines to process and analyze large amounts of data, identify patterns and relationships, and make predictions or decisions based on that analysis. AI has become increasingly pervasive across a wide range of industries and sectors, with healthcare, finance, transportation, manufacturing, retail, education, and agriculture are a few examples to mention. As AI technology continues to advance, it is expected to have an even greater impact on industries in the future. For instance, AI is being increasingly used in the agri-food sector to improve productivity, efficiency, and sustainability. It has the potential to revolutionize the agri-food sector in several ways, including but not limited to precision agriculture, crop monitoring, predictive analytics, supply chain optimization, food processing, quality control, personalized nutrition, and food safety. This review emphasizes how recent developments in AI technology have transformed the agri-food sector by improving efficiency, reducing waste, and enhancing food safety and quality, providing particular examples. Furthermore, the challenges, limitations, and future prospects of AI in the field of food and agriculture are summarized.
Use of Biometric Images to Predict Body Weight and Hot Carcass Weight of Nellore Cattle
Authors: Cominotte Alexandre , Fernandes Arthur , Dórea João , Rosa Guilherme , Torres Rodrigo , Pereira Guilherme , Baldassini Welder , Machado Neto Otávio
Published: May 2023

The objective of this study was to evaluate different methods of predicting body weight (BW) and hot carcass weight (HCW) from biometric measurements obtained through three-dimensional images of Nellore cattle. We collected BW and HCW of 1350 male Nellore cattle (bulls and steers) from four different experiments. Three-dimensional images of each animal were obtained using the Kinect® model 1473 sensor (Microsoft Corporation, Redmond, WA, USA). Models were compared based on root mean square error estimation and concordance correlation coefficient. The predictive quality of the approaches used multiple linear regression (MLR); least absolute shrinkage and selection operator (LASSO); partial least square (PLS), and artificial neutral network (ANN) and was affected not only by the conditions (set) but also by the objective (BW vs. HCW). The most stable for BW was the ANN (Set 1: RMSEP = 19.68; CCC = 0.73; Set 2: RMSEP = 27.22; CCC = 0.66; Set 3: RMSEP = 27.23; CCC = 0.70; Set 4: RMSEP = 33.74; CCC = 0.74), which showed predictive quality regardless of the set analyzed. However, when evaluating predictive quality for HCW, the models obtained by LASSO and PLS showed greater quality over the different sets. Overall, the use of three-dimensional images was able to predict BW and HCW in Nellore cattle.
Characterization of blaKPC-2 and blaNDM-1 Plasmids of a K. pneumoniae ST11 Outbreak Clone
Authors: Boralli Camila Maria dos Santos , Paganini Julian Andres , Meneses Rodrigo Silva , Mata Camila Pacheco Silveira Martins da , Leite Edna Marilea Meireles , Schürch Anita C. , Paganelli Fernanda L. , Willems Rob J. L. , Camargo Ilana Lopes Baratella Cunha
Published: May 2023

The most common resistance mechanism to carbapenems is the production of carbapenemases. In 2021, the Pan American Health Organization warned of the emergence and increase in new carbapenemase combinations in Enterobacterales in Latin America. In this study, we characterized four Klebsiella pneumoniae isolates harboring blaKPC and blaNDM from an outbreak during the COVID-19 pandemic in a Brazilian hospital. We assessed their plasmids’ transference ability, fitness effects, and relative copy number in different hosts. The K. pneumoniae BHKPC93 and BHKPC104 strains were selected for whole genome sequencing (WGS) based on their pulsed-field gel electrophoresis profile. The WGS revealed that both isolates belong to ST11, and 20 resistance genes were identified in each isolate, including blaKPC-2 and blaNDM-1. The blaKPC gene was present on a ~56 Kbp IncN plasmid and the blaNDM-1 gene on a ~102 Kbp IncC plasmid, along with five other resistance genes. Although the blaNDM plasmid contained genes for conjugational transfer, only the blaKPC plasmid conjugated to E. coli J53, without apparent fitness effects. The minimum inhibitory concentrations (MICs) of meropenem/imipenem against BHKPC93 and BHKPC104 were 128/64 and 256/128 mg/L, respectively. Although the meropenem and imipenem MICs against E. coli J53 transconjugants carrying the blaKPC gene were 2 mg/L, this was a substantial increment in the MIC relative to the original J53 strain. The blaKPC plasmid copy number was higher in K. pneumoniae BHKPC93 and BHKPC104 than in E. coli and higher than that of the blaNDM plasmids. In conclusion, two ST11 K. pneumoniae isolates that were part of a hospital outbreak co-harbored blaKPC-2 and blaNDM-1. The blaKPC-harboring IncN plasmid has been circulating in this hospital since at least 2015, and its high copy number might have contributed to the conjugative transfer of this particular plasmid to an E. coli host. The observation that the blaKPC-containing plasmid had a lower copy number in this E. coli strain may explain why this plasmid did not confer phenotypic resistance against meropenem and imipenem.
The COVID-19 Pandemic Enhanced the Decade-Long Trend of the Decreasing Utilization of Antibiotics
Authors: Tanislav Christian , Rosenbauer Josef , Kostev Karel
Published: May 2023

Purpose/Introduction: A decline in antibiotic (AB) prescriptions was reported during the coronavirus 2019 (COVID-19) pandemic. Therefore, we investigated AB utilization during the COVID-19 pandemic using data from a large database in Germany. Methods: AB prescriptions in the Disease Analyzer database (IQVIA) were analyzed for each year between 2011 and 2021. Descriptive statistics were used to assess developments in relation to age group, sex, and antibacterial substances. Infection incidence rates were also investigated. Results: In total, 1,165,642 patients received antibiotic prescriptions during the entire study period (mean age: 51.8; SD: 18.4 years; 55.3% females). AB prescriptions started to decline in 2015 (505 patients per practice), and this development persisted until 2021 (2020: 300 patients per practice and 2021: 266 patients per practice). The sharpest drop was observed in 2020 and occurred in both women and men (27.4% and 30.1%). In the youngest age group (≤30), the decrease was −56%, while in the age group >70, it was −38%. The number of patients with prescriptions for fluoroquinolones dropped the most, falling from 117 in 2015 to 35 in 2021 (−70%), followed by macrolides (−56%) and tetracyclines (−56%). In 2021, 46% fewer patients were diagnosed with acute lower respiratory infections, 19% fewer with chronic lower respiratory diseases, and just 10% fewer with diseases of the urinary system. Conclusion: AB prescriptions decreased more in the first year (2020) of the COVID-19 pandemic than infectious diseases did. While the factor of older age influenced this trend negatively, it remained unaffected by the factor of sex and the selected antibacterial substance.
Evaluation of the Effects of Chia (Salvia hispanica L.) Leaves Ethanolic Extracts Supplementation on Biochemical and Hepatic Markers on Diet-Induced Obese Mice
Authors: Maturana Gabriela , Segovia Javiera , Olea-Azar Claudio , Uribe-Oporto Ernesto , Espinosa Alejandra , Zúñiga-López María Carolina
Published: May 2023

Obesity is a significant health concern affecting 13% of the world’s population. It is often associated with insulin resistance and metabolic-associated fatty liver disease (MAFLD), which can cause chronic inflammation in the liver and adipose tissue. Obese hepatocytes show increased lipid droplets and lipid peroxidation, which can lead to the progression of liver damage. Polyphenols have been shown to have the ability to reduce lipid peroxidation, thereby promoting hepatocyte health. Chia leaves, a by-product of chia seed production, are a natural source of bioactive antioxidant compounds, such as cinnamic acids and flavonoids, which have antioxidant and anti-inflammatory properties. In this study, chia leaves’ ethanolic extracts of two seed phenotypes were tested on diet-induced obese mice to evaluate their therapeutic potential. Results show that the chia leaf extract positively affected insulin resistance and lipid peroxidation in the liver. In addition, the extract improved the HOMA-IR index compared to the obese control group, reducing the number and size of lipid droplets and lipid peroxidation. These results suggest that chia leaf extract may help treat insulin resistance and liver damage associated with MAFLD.
Hemodialysis Serum Stimulates the TXNIP-eNOS-STAT3 Inflammatory Pathway In Vitro
Authors: Cohen-Hagai Keren , Kashua Hadil , Benchetrit Sydney , Zitman-Gal Tali
Published: May 2023

Background: Endothelial dysfunction, vascular inflammation and accelerated atherosclerosis have been investigated extensively in patients with chronic kidney disease (CKD). These conditions, as well as protein–energy malnutrition and oxidative stress, impair kidney function and contribute to increased morbidity and mortality among patients with end-stage kidney disease undergoing hemodialysis (HD). TXNIP, a key regulator of oxidative stress, has been linked to inflammation and suppresses eNOS activity. STAT3 activation adds to endothelial cell dysfunction, macrophage polarization, immunity and inflammation. Therefore, it is critically involved in atherosclerosis. This study evaluated the effect of sera from HD patients on the TXNIP-eNOS-STAT3 pathway using an in vitro model of human umbilical vein endothelial cells (HUVECs). Methods: Thirty HD patients with end-stage kidney disease and ten healthy volunteers were recruited. Serum samples were taken at dialysis initiation. HUVECs were treated with HD or healthy serum (10% v/v) for 24 h. Then, cells were collected for mRNA and protein analysis. Results: TXNIP mRNA and protein expression were significantly increased in HUVECs treated with HD serum compared to healthy controls (fold changes: 2.41 ± 1.84 vs. 1.41 ± 0.5 and 2.04 ± 1.16 vs. 0.92 ± 0.29, respectively), as were IL-8 mRNA (fold changes: 2.22 ± 1.09 vs. 0.98 ± 0.64) and STAT3 protein expression (fold changes: 1.31 ± 0.75 vs. 0.57 ± 0.43). The expression of eNOS mRNA and protein (fold changes: 0.64 ± 0.11 vs. 0.95 ± 0.24; 0.56 ± 0.28 vs. 4.35 ± 1.77, respectively) and that of SOCS3 and SIRT1 proteins were decreased. Patients’ nutritional status, reflected by their malnutrition–inflammation scores, did not affect these inflammatory markers. Conclusions: This study showed that sera from HD patients stimulated a novel inflammatory pathway, regardless of their nutritional status.
Extracts of Eryngium foetidum Leaves from the Amazonia Were Efficient Scavengers of ROS and RNS
Authors: Leitão Deusa do Socorro Teixeira Costa , Barbosa-Carvalho Anna Paula Pereira , de Siqueira Francilia Campos , Sousa Railson Pontes e , Lopes Alessandra Santos , Chisté Renan Campos
Published: May 2023

Eryngium foetidum L. is an edible plant widespread in Amazonian cuisine and its leaves have high levels of promising phenolic compounds for the production of extracts to be used as natural antioxidant additives. In this study, the in vitro scavenging capacity of three freeze-dried extracts of E. foetidum leaves, obtained by ultrasound-assisted extraction using green solvents [water (H2O), ethanol (EtOH), and ethanol/water (EtOH/H2O)], was investigated against the most common reactive oxygen species (ROS) and reactive nitrogen species (RNS) generated in both physiological and food systems. Six phenolic compounds were identified, chlorogenic acid (2198, 1816 and 506 μg/g) being the major compound for EtOH/H2O, H2O, and EtOH extracts, respectively. All E. foetidum extracts were efficient in scavenging all the ROS and RNS (IC50 = 45–1000 µg/mL), especially ROS. The EtOH/H2O extract showed the highest contents of phenolic compounds (5781 μg/g) and showed the highest efficiency in scavenging all the reactive species, with high efficiency for O2•− (IC50 = 45 μg/mL), except for ROO•, for which EtOH extract was the most efficient. Therefore, E. foetidum leaf extracts, especially EtOH/H2O, showed high antioxidant potential to be used as natural antioxidants in food formulations and are promising for nutraceuticals products.
Changes of Gait Patterns after Correction of Refractive Error in the Elderly with Cataracts
Authors: Noh Jae-Hyeon , Cho Hyun-Gug , Moon Byeong-Yeon , Yu Dong-Sik , Kim Sang-Yeob
Published: May 2023

The aim of this study was to verify whether providing older adults with actual corrected glasses for refractive errors would have a positive impact on their gait patterns. This study included 30 subjects with an average age of 78.77 ± 7.27 years. The measurement of gait patterns was performed using the Optogait analysis system, and a comparative analysis was performed to compare the patients before and after they wore correction glasses. Step length, stride length, and width showed significant increases after the patients wore correction glasses, and cadence showed a decrease compared to before they wore correction glasses (p < 0.05). A strong positive correlation was observed between step length and stride length (r = 0.779, p < 0.001), and a decrease in cadence (r = −0.686, p < 0.001) was observed with increasing step length. In addition, a proportional increase in speed with increasing step length was observed after the patients wore correction glasses (r = 0.416, p < 0.05). The correction of residual refractive errors in order to provide optimal visual information can have a positive effect on gait patterns. Therefore, efforts by optometry professionals to provide the accurate correction of refractive errors in elderly patients can contribute to the prevention of falls, and collaboration with other experts is needed.
High-Efficiency Navigation of Nonholonomic Mobile Robots Based on Improved Hybrid A* Algorithm
Authors: Chi Zhaozhan , Yu Zhenhan , Wei Qianyu , He Qiancheng , Li Guangxian , Ding Songlin
Published: May 2023

With the development of automation technologies, autonomous robots are increasingly used in many important applications. However, precise self-navigation and accurate path planning remain a significant challenge, particularly for the robots operating in complex circumstances such as city centers. In this paper, a nonholonomically constrained robot with high-precision navigation and path planning capability was designed based on the Robot Operating System (ROS), and an improved hybrid A* algorithm was developed to increase the processing efficiency and accuracy of the global path planning and navigation of the robot. The performance and effectiveness of the algorithm were evaluated by using randomly constructed maps in MATLAB and validated in a practical circumstance. Local path planning and obstacle avoidance were carried out based on the model predictive control (MPC) theory. Compared with the conventional A* + DWA (dynamic window approach) method, the average searching time was reduced by 12.62~24.5%, and the average search length was reduced by 9.25~9.5%. In practical navigating tests, the average search time was reduced by 18~24%, and the average search length was reduced by 10.3~12%, while the overall path was smoother. The results demonstrate that the improved algorithm can enable precise and efficient navigation and path planning of the robot in complex circumstances.
Predicting Consumer Personalities from What They Say
Authors: Tsao Hsiu-Yuan , Lin Ching-Chang , Lo Hui-Yi , Lu Ruei-Shan
Published: May 2023

This study mapped personality based on the newly proposed extraction method from consumers’ textual data and revealed the relevance (attention) and polarity (affection) of words associated with a specific personality trait. Furthermore, we illustrate how unique words are used to predict a consumer’s behavior associated with certain personality traits. In this study, we employed the scales of the Kaggle MBTI Personality dataset to examine the methodology’s effectiveness, extract the personality traits from the textual data into features, and map them into the traits/dimensions of the existing scale. Based on the results obtained in this study, we assert that using the TF-IDF algorithm is a good way to generate a custom dictionary. Furthermore, sentiment scoring with an AI-empowered machine learning algorithm provides useful data to filter and validate more coherent words to understand and, thus, communicate a particular aspect of personality. Finally, we proposed that four situations involving the interaction between attention (frequency) and affection (sentiment) allow us to better understand the consumer and how to use the feature words in terms of the interaction between attention (TF-IDF score) and affection (sentiment score).
SAR Image Aircraft Target Recognition Based on Improved YOLOv5
Authors: Wang Xing , Hong Wen , Liu Yunqing , Hu Dongmei , Xin Ping
Published: May 2023

Synthetic aperture radar (SAR) is an active ground-surveillance radar system, which can observe targets regardless of time and weather. Passenger aircrafts are important targets for SAR, as it is of great importance for accurately recognizing the type of aircraft. SAR can provide dynamic monitoring of aircraft flights in civil aviation, which is helpful for the efficient management of airports. Due to the unique imaging characteristics of SAR, traditional target-detection algorithms have poor generalization ability, low detection accuracy, and a cumbersome recognition process. Target detection in high-resolution SAR images based on deep-learning methods is currently a major research hotspot. You Only Look Once v5 (YOLOv5) has the problems of missed detection and false alarms. In this study, we propose an improved version of YOLOv5. A multiscale feature adaptive fusion module is proposed to adaptively assign different weights to each scale of the feature layers, which can extract richer semantic and textural information. The SIOU loss function is proposed to replace the original CIOU loss function to speed up the convergence of the algorithm. The improved Ghost structure is proposed to optimize the YOLOv5 network to decrease the parameters of the model and the amount of computation. A coordinate attention (CA) module is incorporated into the backbone section to help extract useful information. The experimental results demonstrate that the improved YOLOv5 performs better in terms of detection without affecting calculation speed. The mean average precision (mAP) value of the improved YOLOv5 increased by 5.8% compared with the original YOLOv5.
Study on Load–Slip Curve of a PBL Shear Key at a Steel–Concrete Composite Joint
Authors: Wang Haibo , Wang Wenxuan , Wu Shasha
Published: May 2023

The steel–concrete composite truss adopts a new type of steel-concrete composite joint with high rigidity and load-carrying capacity. In order to more conveniently and clearly grasp the working mechanism of Perfobond Leiste (PBL) shear keys in the core area of new composite structures such as steel–concrete composite trusses, the lack of strong theoretical support for the theoretical formula of load–slip relationships in the entire loading process of single PBL shear keys is solved. By proposing a straight–curved–straight three-stage simplified load–slip curve with respect to the PBL shear key, the stress process of the PBL shear key is divided into three stages—the elastic stage, plastic stage, and strengthening stage—based on the compressive yield and failure critical point of tenon concrete in the shear key. With reference to the calculation method of the bearing capacity of the order pile under horizontal loads and by calculating the shear stiffness of the shear key, a theoretical formula suitable for separating the load–slip relationship of a single PBL shear key in the entire loading process of the ear plate composite joint is proposed. The results show that, in the elastic section, the slope of the curve is related to the concrete reaction coefficient and the material parameters of the penetrating steel bar; moreover, in the strengthened section, the coefficient is related to the shear modulus of the penetrating steel bar, and a more uniform length distribution of the penetrating steel bar between the two joint plates will improve the initial stiffness of the PBL shear key to a certain extent. The results of the proposed method are in good agreement with the finite element results and experimental values. This research study’s results can provide a convenient design method for the design of the internal PBL shear keys of new composite structure joints, promoting the promotion and application of new composite structures and advancing the development of the engineering field.
New Fusion Network with Dual-Branch Encoder and Triple-Branch Decoder for Remote Sensing Image Change Detection
Authors: Zhai Cong , Wang Liejun , Yuan Jian
Published: May 2023

Deep learning plays a highly essential role in the domain of remote sensing change detection (CD) due to its high efficiency. From some existing methods, we can observe that the fusion of information at each scale is quite vital for the accuracy of the CD results, especially for the common problems of pseudo-change and the difficult detection of change edges in the CD task. With this in mind, we propose a New Fusion network with Dual-branch Encoder and Triple-branch Decoder (DETDNet) that follows a codec structure as a whole, where the encoder adopts a siamese Res2Net-50 structure to extract the local features of the bitemporal images. As for the decoder in previous works, they usually employed a single branch, and this approach only preserved the fusion features of the encoder’s bitemporal images. Distinguished from these approaches, we adopt the triple-branch architecture in the decoder for the first time. The triple-branch structure preserves not only the dual-branch features from the encoder in the left and right branches, respectively, to learn the effective and powerful individual features of each temporal image but also the fusion features from the encoder in the middle branch. The middle branch utilizes triple-branch aggregation (TA) to realize the feature interaction of the three branches in the decoder, which enhances the integrated features and provides abundant and supplementary bitemporal feature information to improve the CD performance. The triple-branch architecture of the decoder ensures that the respective features of the bitemporal images as well as their fused features are preserved, making the feature extraction more integrated. In addition, the three branches employ a multiscale feature extraction module (MFE) per layer to extract multiscale contextual information and enhance the feature representation capability of the CD. We conducted comparison experiments on the BCDD, LEVIR-CD, and SYSU-CD datasets, which were created in New Zealand, the USA, and Hong Kong, respectively. The data were preprocessed to contain 7434, 10,192, and 20,000 image pairs, respectively. The experimental results show that DETDNet achieves F1 scores of 92.7%, 90.99%, and 81.13%, respectively, which shows better results compared to some recent works, which means that the model is more robust. In addition, the lower FP and FN indicate lower error and misdetection rates. Moreover, from the analysis of the experimental results, compared with some existing methods, the problem of pseudo-changes and the difficulty of detecting small change areas is better solved.
Experimental Evaluation of AGV Dispatching Methods in an Agent-Based Simulation Environment and a Digital Twin
Authors: Maas genannt Bermpohl Fabian , Bresser Andreas , Langosz Malte
Published: May 2023

A critical part of Automated Material Handling Systems (AMHS) is the task allocation and dispatching strategy employed. In order to better understand and investigate this component, we here present an extensive experimental evaluation of three different approaches with randomly generated, as well as custom designed, environment configurations. While previous studies typically focused on use cases based on highly constrained navigation capabilities (e.g., overhead hoist transport systems), our evaluation is built around highly mobile, free-ranging vehicles, i.e., Autonomous Mobile Robots (AMR) that are gaining popularity in a broad range of applications. Consequently, our experiments are conducted using a microscopic agent-based simulation, instead of the more common discrete-event simulation model. Dispatching methods often are built around the assumption of the asynchronous evaluation of an event-based model, i.e., vehicles trigger a cascade of individual dispatching decisions, e.g., when reaching intersections. We find that this does not translate very well to a fleet of highly mobile systems that can change direction at any time. With this in mind, we present formulations of well known dispatching approaches that are better suited for a synchronous evaluation of the dispatching decisions. The formulations are based on the Stable Marriage Problem (SMP) and the Linear Sum Assignment Problem (LSAP). We use matching and assignment algorithms to compute the actual dispatching decisions. The selected algorithms are evaluated in a multi-agent simulation environment. To integrate a centralised fleet management, a digital twin concept is proposed and implemented. By this approach, the fleet management is independent of the implementation of the specific agents, allowing to quickly adapt to other simulation-based or real application scenarios. For the experimental evaluation, two new performance measures related to the efficiency of a material handling system are proposed, Travel Efficiency and Throughput Effort. The experimental evaluation indicates that reassignment mechanisms in the dispatching method can help to increase the overall efficiency of the fleet. We did not find significant differences in absolute performance in terms of throughput rate. Additionally, the difference in performance between SMP- and LSAP-based dispatching with reassignment seems negligible. We conclude with a discussion, where we consider potential confounding factors and relate the findings to previously reported results found in the literature.
Special Issue on Advances in Environmental Applied Physics
Authors: Caridi Francesco
Published: May 2023

This Special Issue, “Advances in Environmental Applied Physics”, is dedicated to collecting original papers from eminent researchers in the field of environmental pollutants, which constitute a health risk to the population, increasing the likelihood of incurring cancer [...]
Pharmacophore-Modeling-Based Optimal Placement and Sizing of Large-Scale Energy Storage Stations in a Power System including Wind Farms
Authors: Fayek Hady H. , Fayek Fady H. , Rusu Eugen
Published: May 2023

The world is targeting fully sustainable electricity by 2050. Energy storage systems have the biggest role to play in the 100% renewable energy scenario. This paper presents an optimal method for energy storage sizing and allocation in a power system including a share of wind farms. The power system, which is used as a test system, is a modified version of the IEEE 39 bus system. The optimization is applied using novel pharmacophore modeling (PM), which is compared to state-of-the-art techniques. The objective of the optimization is to minimize the costs of power losses, peak demand and voltage deviation. The PM optimization is applied using two methods, namely, weighting factor and normalization. The optimization and simulation are applied in the DIgSILENT power factory software application. The results show that normalization of PM optimization drives the power system to less cost in terms of total power losses by up to 29% and voltage deviation by up to 4% and better covers peak demand than state-of-the-art optimization techniques.
Experimental Quantification of Fire Damage Inside Pyrotechnic Stores
Authors: León David , Castells Blanca , Amez Isabel , Casín Juan , García-Torrent Javier
Published: May 2023

A fire inside a pyrotechnic store can lead to simultaneous initiation of the stored articles, regardless of their risk category, producing a shockwave caused by the released gas pressure. In fact, several accidents have occurred throughout history in pyrotechnic stores. This indicates the high risk posed by pyrotechnics due to their flammability. Due to the lack of global or European legislation on guidelines for the design of pyrotechnic stores and associated risk assessment, the present research aims to analyze the consequences of a fire inside pyrotechnic stores and to establish globally possible effective prevention and protection measures in order to reduce explosion risk and avoid future accidents. The observed consequences and the reflected pressure (pressure measured when the wave is incident perpendicularly on the transducer) measured during fire tests inside a pyrotechnic store indicated the need to minimize the potential occurrence of fires. The limitation of the maximum permissible load, considering the volume of the store (kg/m3), reduces consequence severity in the event of an accident. However, the maximum permissible levels should be so low as to make their use for retail sales of pyrotechnic products unviable. The solution is the use of automatic fire detection and extinguishing systems with a high cooling capacity in order to prevent the spread to nearby packaging by rapid detection.
Comprehensive Evaluations of NLOS and Linearization Errors on UWB Positioning
Authors: Li Yan , Gao Zhouzheng , Xu Qiaozhuang , Yang Cheng
Published: May 2023

Currently, ultra-wide band (UWB) is adopted as a useful high-accuracy positioning technique in satellite-blocked areas. However, UWB’s positioning performance would be limited significantly because of non-line of sight (NLOS) errors. Additionally, the truncation errors in these linearization-based adjustments such as least squares (LS) and extended Kalman filter (EKF) would also visibly degrade UWB positioning accuracy. To overcome the impacts of NLOS errors and truncation errors, this paper introduced a robust-theory-based particle filter (RPF) into UWB positioning. In such a method, the IGG-III model and PF were adopted to limit the impacts of NLOS errors and truncation errors, respectively, by introducing a weight inflation factor and particle group. For comparison, the Bancroft, LS, EKF, unscented Kalman filter (UKF), cubature Kalman filter (CKF), PF, and RPF were also presented. Here, the influences of truncation errors were analyzed by comparing the results based on LS and EKF with those calculated by UKF, CKF, and PF. The impacts of NLOS errors were evaluated by making a comparison between the results of PF and RPF. Results based on a set of simulated UWB data and a group of experiment UWB data demonstrated that the RPF can significantly avoid the positioning errors caused by both truncation errors and NLOS errors. In general, position improvements percentages of 57.2%, 52.7%, 39.6%, 38.2%, 26.6%, and 20.4% can be obtained by RPF compared to those calculated by Bancroft, LS, EKF, UKF, CKF, and PF, respectively. As a comparison, the truncation error would lead to about 8.1%, 10.1%, and 33.2% accuracy decrease in the north, east, and vertical directions on average. Such accuracy-decrease rates caused by NLOS were 6.1%, 5.2%, and 25%.
Biogeochemical State of Salinized Irrigated Soils of Central Fergana (Uzbekistan, Central Asia)
Authors: Turdaliev Avazbek , Askarov Kamoliddin , Abakumov Evgeny , Makhkamov Elyorbek , Rahmatullayev Gayratbek , Mamajonov Gaybullo , Akhmadjonov Avazbek , Axunov Akmal
Published: May 2023

The Central Fergana region is one of the overpopulated regions of Central Asia, which includes parts of Uzbekistan, Kyrgyzstan, and Tajikistan. Here, in the dry subtropical climate are the most ancient, irrigated oases used for agriculture. Fergana valley is the key to the food security of the region as a whole. The article provides information on diversity and chemical composition of newly developed, new and old-irrigated Calcisols soils formed on alluvial and alluvial–prolluvial sediments. Soils are poor with organic matter (0.37–0.81% of organic carbon), with high nitrogen content (C/N ratio is 4.92–5.79), and with neutral (7.01–7.30) pH values. Data on the content and the ratio of the key components of soil salinity (Na2CO3, Ca(HCO3)2, CaSO4, MgSO4, Na2SO4, NaCl) and the bulk content of salts in soils under different irrigation regimes are presented. It was shown that Na2CO3 concentration is minimal in all the soils, and this salt presents only in ground waters (0.100–0.135 g L−1). Newly irrigated soils are characterized by higher content of salts than old irrigated soils. All the soils investigated are characterized by increasing salinity rate within the soil depth with the highest content of all salts in ground waters. This chloride–sulfate type of salinization is most pronounced in all the soils studied. Gypsum content in agricultural soils results in limited water and nutrient retention and the potential for dissolution, primarily in response to irrigation. The soils of the Fergana Valley are also subjected to polychemical pollution, so the content of trace elements in them was studied. Irrigated meadow-takyr and meadow-saz soils show low levels of environmental hazard, but irrigation results in accumulation of such trace elements as nickel (30 mg kg−1), arsenic (11.75 mg kg−1), bromine (5.00 mg kg−1), antimony (1.48 mg kg−1), cesium (5.00 mg kg−1), and hafnium (2.97 mg kg−1). Irrigation also affects the soil texture and thus increases fine particle percentages in the superficial soil horizons. Thus, the complex chemical characteristics of salinized soils are presented for numerous irrigated landscapes of the region.
New Inogranic Scintillators’ Application in the Electromagnetic Calorimetry in High-Energy Physics
Authors: Averyanov Dmitry , Blau Dmitry
Published: May 2023

Scintillation crystals Gd3Al2Ga3O12 (GAGG) are an excellent candidate for application in ionizing-radiation detectors because of their high radiation resistance, density and light yield. These crystals can be used in combination with lead tungstate (PbWO4 or PWO) crystals for the development of a new generation of electromagnetic calorimeter with advanced spatial and energy resolutions in a broad energy range. PWO crystals enable the accurate detection of high-energy photons, while GAGG crystals provide the possibility of precisely measuring photon energies, down to a few MeV. Different options for a composite electromagnetic calorimeter based on PWO and GAGG crystals are considered to optimize spatial and energy resolutions in a broad energy range (from 1 MeV to 100 GeV). In particular, different lengths of the GAGG section of the calorimeter are considered, from 0.5 to 10 cm. The separation of signals from photons and hadrons is also taken into consideration through the study of shower shape in the calorimeter. The optimization is based on Geant4 simulations, considering light collection as well as the use of different photodetectors and electronic noise. Simulations are verified with light yield measurements of GAGG samples obtained using radioactive sources and test beam measurements of the prototype of the PWO-based Photon Spectrometer of the ALICE experiment at CERN.
Experimental Study on the Properties of Autoclave Curing High-Strength Concrete According to CaO/SiO2 Ratio
Authors: Ra Jeongmin , Shin Sangchul , Kim Jinman
Published: May 2023

In this experimental study, tests were conducted to obtain the CaO/SiO2 (C/S) molar ratio that minimizes the micropores of hardened concrete. To this end, the compressive strength, thermogravimetric analysis (TGA), and microporous structure of hardened concrete were investigated using concrete specimens made with silica fume and quartz powder under high-temperature/high-pressure conditions. The tests yielded the following results: (1) the highest compressive strength (200 MP) was exhibited in the C/S molar ratio range of 0.7–0.9, and lower compressive strength was exhibited in the C/S molar ratio ranges of ≤ 0.6 and ≥ 0.95; (2) the productivity of calcium silicate hydrate (C-S-H) tended to increase in proportion to the C/S molar ratio in all specimens; (3) the microstructure was measured using mercury intrusion porosimetry (MIP), and the maximum total porosity of specimens was calculated to be 10%. As the C/S molar ratio increased, the total porosity decreased, as did the pore diameter and threshold pore diameter. Thus, C/S molar ratio was found to be a major factor affecting the compressive strength and microporous structure of autoclave-cured cement and the optimal mechanical properties were exhibited in the C/S molar ratio of 0.8–0.9. However, the reactivity varies depending on the material used and curing conditions employed. Therefore, the hydration products obtained using the curing conditions need to be investigated further.