bluuebunny/crossref_metadata_2025 huggingface dataset:
QTL Mapping for Seed Tocopherol Content in Soybean
Authors: Zhang Shibi , Agyenim-Boateng Kwadwo Gyapong , Zhang Shengrui , Gu Yongzhe , Qi Jie , Azam Muhammad , Ma Caiyou , Li Yecheng , Feng Yue , Liu Yitian , Li Jing , Li Bin , Qiu Lijuan , Sun Junming
Published: April 2023

Tocopherol plays an important role as a powerful antioxidant in human beings and in plants. This study investigated the genetic basis of tocopherol content in soybean. A RIL population of 192 lines derived from 2 cultivars, ZH13 and ZH35, was evaluated for tocopherol content across 3 environments. QTL mapping identified 38 QTL for tocopherol, with stable QTL identified on Chromosomes 5 and 12. Ninety polymorphic genes were identified from these regions. Further SNP variation of a natural population identified 47 SNPs, with missense variants in 19 genes, including the heat shock transcription factor gene (GmHSFA8) and gamma-tocopherol methyltransferase (GmVTE4), potentially related to tocopherol accumulation in soybean. Haplotype analysis revealed significant variations in these missense variants in the natural population. This study provides insights into the genetic mechanisms underlying tocopherol content in soybean, which is important for breeding high tocopherol soybean cultivars.
Impacts of Irrigation Technology, Irrigation Rate, and Drought-Tolerant Genetics on Silage Corn Production
Authors: Sullivan Tina , Yost Matt A. , Boren Dakota , Creech Earl , Kitchen Boyd , Violett Randall , Barker Burdette
Published: April 2023

Many studies have examined individual water-saving management practices for corn (Zea mays L.), but few studies have looked at how combinations of practices might further enhance water optimization. The research objectives of this paper were to evaluate the impact of irrigation technology, irrigation rate, and crop genetics, as well as their interactions, on silage corn yield and forage quality. Trials were conducted in three Utah locations from 2019 through 2021. The results from five site-years indicated that the best water optimization practices varied by site-year. Low-elevation sprinklers commonly applied water more efficiently, with four of the five site-years having improved or equivalent yield compared to mid-elevation sprinklers. Irrigation rate reductions and yield losses were not proportional, as a 25% irrigation reduction resulted in better silage quality and a 7% average yield loss across site-years. Further, targeted deficit irrigation (less water during vegetation and more during maturation) was inferior to a uniform deficit during all growth stages. Drought-tolerant genetics often maintained but did not improve yield in extreme water stress environments compared to non-DT genetics. No cumulative benefits were observed when combining irrigation technology, rate, and DT genetics. Irrigation technology had the greatest potential of the three factors to optimize water use in silage corn production in the Western U.S. region.
Effect of Seawater Irrigation on Arthrocnemum macrostachyum Growing in Extensive Green Roof Systems under Semi-Arid Mediterranean Climatic Conditions
Authors: Paraskevopoulou Angeliki T. , Ntoulas Nikolaos , Bourtsoukli Dionysia , Bertsouklis Konstantinos
Published: April 2023

The effects of climate change in coastal semi-arid and arid Mediterranean areas are intense. Green roofs planted with native plant species that are able to withstand saline conditions can contribute to supporting climate-change adaptation and species preservation in wetlands, enhancing the character of local landscapes and reducing disaster risk. Considering the limited availability of water resources, there is increasing interest in the use of seawater for irrigation, particularly near coastal areas. The growth of a native Mediterranean halophyte, Arthrocnemum macrostachyum, on a simulated extensive green roof system with six different irrigation treatments with or without seawater for 97 days is presented. The irrigation treatments included tap water every 4 or 8 days, seawater every 4 or 8 days, and seawater alternated with tap water every 4 or 8 days. The plants’ growth indices, heights, ground-cover surface areas, and relative shoot water content, as well as the electrical conductivity of the green roof’s substrate leachates (ECL), were measured at regular intervals. Overall, the plants irrigated with tap water every 4 days and the plants irrigated with seawater alternated with tap water every 4 days showed the greatest growth amongst the different irrigation treatments, while the plants irrigated with seawater or seawater alternated with tap water every 8 days showed the least growth. Furthermore, the plants irrigated with tap water every 8 days or seawater every 4 days showed intermediate growth. To conserve water, irrigation with seawater alternated with tap water every 4 days is proposed. To further conserve water, irrigation every 4 days with seawater only is also proposed.
Reindeer Husbandry in Switzerland—Management, Feeding, and Endoparasite Infections
Authors: Luginbühl Carmen , Gross Josef , Wenker Christian , Hoby Stefan , Basso Walter , Zanolari Patrik
Published: April 2023

The aim of the present work was to provide an overview of management and feeding practices, and the prevalence of endoparasite infections in captive Swiss reindeer. On two visits to eight farms or zoos, a standardized questionnaire was completed. A total of 67 reindeer were weighed, and fecal samples were collected. The primary management concerns voiced by owners/managers were feeding and successful breeding. All reindeer were fed roughage ad libitum and supplementary feed for reindeer or other browsers, with different compositions in each herd. Males over two years of age weighed from 60 kg up to 127.5 kg, whereas females had a body weight from 53.5 kg to 86.5 kg. The prevalence of gastrointestinal strongyles was 68.6% (46/67), with reindeer in zoos having a lower prevalence (36%; 9/25) than reindeer from private farms (88%; 37/42). Capillaria sp., Strongyloides sp., and Trichuris sp. were detected in lower prevalences (<24%) and were also more frequent in private farms. Intestinal protozoa, as well as fluke and tapeworms, were not detected in any herd. This study provides an overview on husbandry, feeding, and endoparasite prevalence in reindeer in Switzerland and should be of help for breeders and veterinarians dealing with this animal species.
Evaluation of Increasing Concentrations of Supplemental Choline Chloride on Modern Broiler Chicken Growth Performance and Carcass Characteristics
Authors: Gregg Caroline R. , Hutson Brittany L. , Flees Joshua J. , Lowman Zachary S. , Estes Kari A. , Starkey Jessica D. , Starkey Charles W.
Published: April 2023

Choline has been demonstrated to partially substitute methionine in broiler chicken diets due to their interconnected biosynthesis pathways. Yet, research on the impacts of dietary choline supplementation on modern strains of high-yielding broilers is limited. The objective was to evaluate the effect of increasing additions of choline chloride on the performance and carcass characteristics of broilers fed reduced methionine diets and reared under summer environmental conditions. Ross 708 x Yield Plus male broilers were reared for 41 days on used litter in floor pens (n = 2232; 31 birds per pen). Birds were fed one of six corn and soybean meal-based, reduced methionine diets containing 0, 400, 800, 1200, 1600, or 2000 mg of added choline chloride per kg of feed. Diets were provided in three phases. On day 43, 10 birds per pen were processed. Increasing dietary choline resulted in similar body weight gain, reduced feed intake, and improved feed efficiency. Choline chloride supplementation linearly increased both breast and carcass yields while concomitantly increasing the incidence and severity of wooden-breast-affected fillets. These results indicate that supplementing reduced-methionine broiler diets with choline chloride during high environmental temperatures may improve feed efficiency and increase carcass and breast yields but may also increase wooden breast.
Infrared All-Dielectric Metasurface Beam Splitter Based on Transflective Structures
Authors: Ren Yingzheng , Liang Zhongzhu , Shi Xiaoyan , Yang Fuming , Zhang Xiqing , Dai Rui , Zhang Shoutao , Liu Weizhen
Published: April 2023

Beam splitters are widely applied in various optical systems as a common beam-splitting device. The conventional stereoscopic and flat-type beam splitters greatly limit the packaging and integration of optical systems due to their large size and restricted emitting direction. Recently, beam-splitting devices made of various transmissive or reflective metasurfaces have shown the potential to overcome these challenges. However, in optical systems such as machine vision, these single-ended beam splitters increase the design complexity of the signal feedback link due to the limitation of the beam-splitting path direction. Here, we proposed and numerically simulated a transflective all-dielectric metasurface beam splitter by applying incompletely transmissive structural designs to the metasurface and using the transmission phase modulation mechanism. It can realize the beam separation for arbitrarily polarized incident light on the same side of the normal at both transmissive and reflective ends with a single-layer unit cell arrangement structure and has a similar emergence angle. The results reveal that at 1550 nm, the angular tolerance bandwidth is about 32°, the total splitting efficiency is over 90%, and the splitting ratio is approximately 1:1. After comparison and verification of simulation results, this transflective metasurface beam splitter is hopeful to be applied in new compact optical systems that require real-time signal feedback, such as coaxial light sources and photoelectric sensing.
A Two-Phase Iterative Mathematical Programming-Based Heuristic for a Flexible Job Shop Scheduling Problem with Transportation
Authors: Lim Che Han , Moon Seung Ki
Published: April 2023

In a flexible job shop problem with transportation (FJSPT), a typical flexible manufacturing system comprises transporters that pick up and deliver jobs for processing at flexible job shops. This problem has grown in importance through the wide use of automated transporters in Industry 4.0. In this article, a two-phase iterative mathematical programming-based heuristic is proposed to minimize makespan using a machine-operation assignment centric decomposition scheme. The first phase approximates the FJSPT through an augmented flexible job shop scheduling problem (FJSP + T) that reduces the solution space while serving as a heuristic in locating good machine-operation assignments. In the second phase, a job shop scheduling problem with transportation (JSPT) network is constructed from these assignments and solved for the makespan. Compared to prior JSPT implementations, the proposed JSPT model considers job pre-emption, which is instrumental in enabling this FJSPT implementation to outperform certain established benchmarks, confirming the importance of considering job pre-emption. Results indicate that the proposed approach is effective, robust, and competitive.
Human Factors Analysis of the Improved FRAM Method for Take-Off Quality Lateral Shift
Authors: Ouyang Wenjian , Gan Xusheng , Wu Yarong , Qu Kai , Wang Jiabo
Published: April 2023

This article proposes an improved FRAM method based on the traditional FRAM method, using the study of aircraft take-off quality as an example to illustrate the operation method of the improved FRAM. To address the impact of pilot operations on take-off instructions during aircraft take-off, a functional network model was constructed based on the improved FRAM (functional resonance analysis method) method for the take-off and roll stages of the aircraft. On the basis of the aircraft take-off taxiing model, a simulation was used to sample the take-off data from the pilot many times under different conditions, and the data were put into the safety envelope for comparative analysis to find functional modules with abnormal changes. Using the functional network model, the resonance relationship between the abnormal module and other related functional modules was determined. According to the resonance relationship, setting up a safety barrier can reduce the risk of accidents. Finally, the safety barrier was substituted back into the improved FRAM method to verify the effectiveness of the safety barrier. Compared with the traditional FRAM method, the improved FRAM method can make full use of historical data, loop iteration, repeated verification, and continuous improvement until the final result reaches the user’s expected goal. The improved FRAM method reduces the dependence on expert evaluation and experience, so its conclusions have higher objectivity and reference value.
RRT*-Fuzzy Dynamic Window Approach (RRT*-FDWA) for Collision-Free Path Planning
Authors: Zhou Lintao , Wu Nanpeng , Chen Hu , Wu Qinge , Lu Yingbo
Published: April 2023

Path planning is an important aspect and component in the research of mobile-robot-related technologies. Many path planning algorithms are only applicable to static environments, while in practical tasks, the uncertainty in dynamic environments increases the difficulty of path planning and obstacle avoidance compared with static environments. To address this problem, this paper proposes an RRT*-FDWA algorithm. RRT* first generates a global optimal path, and then, when obstacles exist nearby, an FDWA algorithm fixes the local path in real time. Compared with other path planning algorithms, RRT*-FDWA can avoid local minima, rapidly perform path replanning, generate a smooth optimal route, and improve the robot’s maneuvering amplitude. In this paper, the effectiveness of the algorithm is verified through experiments in dynamic environments.
JSUM: A Multitask Learning Speech Recognition Model for Jointly Supervised and Unsupervised Learning
Authors: Yolwas Nurmemet , Meng Weijing
Published: April 2023

In recent years, the end-to-end speech recognition model has emerged as a popular alternative to the traditional Deep Neural Network—Hidden Markov Model (DNN-HMM). This approach maps acoustic features directly onto text sequences via a single network architecture, significantly streamlining the model construction process. However, the training of end-to-end speech recognition models typically necessitates a significant quantity of supervised data to achieve good performance, which poses a challenge in low-resource conditions. The use of unsupervised representation significantly reduces this necessity. Recent research has focused on end-to-end techniques employing joint Connectionist Temporal Classification (CTC) and attention mechanisms, with some also concentrating on unsupervised presentation learning. This paper proposes a joint supervised and unsupervised multi-task learning model (JSUM). Our approach leverages the unsupervised pre-trained wav2vec 2.0 model as a shared encoder that integrates the joint CTC-Attention network and the generative adversarial network into a unified end-to-end architecture. Our method provides a new low-resource language speech recognition solution that optimally utilizes supervised and unsupervised datasets by combining CTC, attention, and generative adversarial losses. Furthermore, our proposed approach is suitable for both monolingual and cross-lingual scenarios.
Hepatoprotective Effect of Alpinetin on Thioacetamide-Induced Liver Fibrosis in Sprague Dawley Rat
Authors: Shareef Suhayla Hamad , Juma Ameena S. M. , Agha Derin N. F. , Alzahrani Abdullah R. , Ibrahim Ibrahim Abdel Aziz , Abdulla Mahmood Ameen
Published: April 2023

Alpinetin is an original medicinal plant flavonoid derived from Alpinia katsumadai and has several biological activities. The current research aimed to evaluate the hepatoprotective effects of Alpinetin against thioacetamide (TAA)-induced liver cirrhosis in rats. Five groups of rats were utilized in this study. Hepatic injury was measured macroscopically and microscopically for entire groups. The rats’ body weight was significantly lower in the TAA control group, likened to rats fed with Silymarin or Alpinetin groups, while liver weight was significantly greater in the TAA control group when equated to rats nourished with Alpinetin groups. A histopathological investigation of hepatic tissues displayed that TAA remarkably induced hepatocyte necrosis and gristly connective tissue propagation in the TAA control group. Alpinetin implicitly decreased the influence of TAA toxicity and diminished fibrosis of liver tissues. The TAA control group presented an increase in liver enzymes (ALP, ALT, and AST) and a decrease in total protein and albumin. Rats who were fed Alpinetin had significantly lower hepatic enzyme activity as well as augmented total protein and albumin, yet they were close to the normal range. Superoxide dismutase (SOD) and Catalase (CAT) enzymes in hepatic homogenate were significantly reduced, and malondialdehyde (MDA) was meaningfully elevated in the TAA control group, while rats fed with Alpinetin had significantly increased SOD and CAT achievement and depressed MDA level. Alpinetin-gavaged groups had reduced levels of Tumor necrosis factor-alpha (TNF-α) and Interleukin-6 (IL-6), significantly down-regulated Proliferating cell nuclear antigen (PCNA), Alpha-smooth muscle (α-SMA), and reduced hepatic stellate cell activity. However, the TAA control group significantly up-regulated PCNA and α-SMA and increased the activity of hepatic stellate cells. Alpinetin was nontoxic and could improve defensive mechanisms against hepatic tissue injury. Acute toxicity tests discovered no evidence of any toxic signs or dead rats, which highlights the safety of Alpinetin. Consequently, the investigation´s outcomes revealed that the hepatoprotective effects of Alpinetin in TAA-induced hepatic impairment might be due to reduced TAA toxicity, increased protein and albumin, increased SOD and CAT levels, reduced MDA levels, and modulation of inflammatory cytokines and their anti-oxidant activities, and suppressed PCNA and α-SMA.
Special Issue on Human and Artificial Intelligence
Authors: Sansonetti Giuseppe , D’Aniello Giuseppe , Micarelli Alessandro
Published: April 2023

Although tremendous advances have been made in recent years, many real-world problems still cannot be solved by machines alone [...]
Analysis and Application of a New S-Type Bistable Generator Beam in Energy Harvester Featured in Reducing Stress Concentration
Authors: Wu Nan , Fu Jiyang , Xiong Chao
Published: April 2023

This paper presents a newly designed bistable S-type generator beam. For two typical energy harvesting scenarios in a low-frequency excitation environment (up-and-down vibration excitation and wind-induced vibration excitation), two kinds of energy harvesting devices are designed using this S-type generator beam and tested and analyzed, respectively. The results indicate that the S-type generator beam can make full use of materials to avoid premature fatigue failure caused by stress concentration. The peak stress of the S-type generator beam is 34.3% lower than that of the cantilever beam under the same excitation conditions. Furthermore, when the environmental excitation frequency is equal to the third natural frequency (3rd mode, 7.45 Hz) of the generator beam, the motion process of the beam surpasses the potential energy barrier and generates inter-well movement (snap-through). The peak output voltage in the two different environments is 14,350 mV and 17,630 mV, respectively. Additionally, the optimal external resistance of the circuit was determined to be 22 kΩ, with a power output of the energy collector of 0.534 mW and 0.545 mW, respectively.
Predictive Assessment of Mycological State of Bulk-Stored Barley Using B-Splines in Conjunction with Genetic Algorithms
Authors: Wawrzyniak Jolanta
Published: April 2023

Postharvest grain preservation and storage can significantly affect the safety and nutritional value of cereal-based products. Negligence at this stage of the food processing chain can lead to mold development and mycotoxin accumulation, which pose considerable threats to the quality of harvested grain and, thus, to consumer health. Predictive models evaluating the risk associated with fungal activity constitute a promising solution for decision-making modules in advanced preservation management systems. In this study, an attempt was made to combine genetic algorithms and B-spline curves in order to develop a predictive model to assess the mycological state of malting barley grain stored at various temperatures (T = 12–30 °C) and water activity in grain (aw = 0.78–0.96). It was found that the B-spline curves consisting of four second-order polynomials were sufficient to approximate the datasets describing fungal growth in barley ecosystems stored under steady temperature and humidity conditions. Based on the designated structures of B-spline curves, a universal parameterized model covering the entire range of tested conditions was developed. In the model, the coordinates of the control points of B-spline curves were modulated by genetic algorithms using values of storage parameters (aw and T). A statistical assessment of model performance showed its high efficiency (R2 = 0.94, MAE = 0.21, RMSE = 0.28). As the proposed model is based on easily measurable on-line storage parameters, it could be used as an effective tool supporting modern systems of postharvest grain treatment.
Statistical Model of Ship Delays on the Fairway in Terms of Restrictions Resulting from the Port Regulations: Case Study of Świnoujście-Szczecin Fairway
Authors: Durlik Irmina , Gucma Lucjan , Miller Tymoteusz
Published: April 2023

The article describes a study of ship delays on the Świnoujście-Szczecin waterway observed by the VTS operator. The research has led to an understanding of the factors that affect delays of ships calling at the ports of Szczecin and Police, as well as the possibilities of predicting and preventing these delays. This article presents the results of the study on the traffic intensity on the investigated waterway and the process of identifying the port regulation that causes the most frequent delays. Based on the obtained results from the statistical analysis and from using multiple regression, a statistical model has been developed that has the ability to estimate expected delays. Additionally, the model has been expanded to calculate financial losses resulting from delays, taking into account the daily cost of maintaining the studied ships. The study took place during ongoing project “Modernization of the Świnoujście-Szczecin waterway to a depth of 12.5 m” but does not include delays resulting from this project.
Multi-View Joint Learning and BEV Feature-Fusion Network for 3D Object Detection
Authors: Liu Qunming , Li Xiaodong , Zhang Xiaofei , Tan Xiaojun , Shi Bodong
Published: April 2023

Traditional 3D object detectors use BEV (bird’s eye view) feature maps to generate 3D object proposals, but in a single BEV feature map, there are inevitably the problems of high compression and information loss. To solve this problem, we propose a multi-view joint learning and BEV feature-fusion network. In this network, we mainly propose two fusion modules: the multi-view feature-fusion module and the multi-BEV feature-fusion module. The multi-view feature fusion module performs joint learning from multiple views, fusing features learned from multiple views, and supplementing missing information in the BEV feature map. The multi-BEV feature-fusion module fuses BEV feature map outputs from different feature extractors to further enrich the feature information in the BEV feature map, in order to generate better quality 3D object proposals. We conducted experiments on a widely used KITTI dataset. The results show that our method has significantly improved the detection accuracy of the cyclist category.For cyclist detection tasks at the easy, moderate, and hard levels of the KITTI test dataset, our method improves by 1.57%, 2.03%, and 0.67%, respectively, compared to PV-RCNN.
Electronic Atlas of Climatic Changes in the Western Russian Arctic in 1950–2021 as Geoinformatic Support of Railway Development
Authors: Gvishiani Alexei D. , Rozenberg Igor N. , Soloviev Anatoly A. , Kostianoy Andrey G. , Gvozdik Sofia A. , Serykh Ilya V. , Krasnoperov Roman I. , Sazonov Nikolay V. , Dubchak Irina A. , Popov Anton B. , Kostianaia Evgenia A. , Gvozdik Georgy A.
Published: April 2023

The Arctic zone of the Russian Federation is one of the most intensively developing regions of the country. Amongst the major domains of economic and industrial growth and improvement is transport infrastructure and particularly the railway network. This area is being exposed to negative factors of rapid climate change that can significantly affect and compromise this activity. Thus, it is vital to take them into account during design, construction, and operation of the railway infrastructure facilities. This work details the production of a digital atlas comprising the 1950–2021 dynamics of the main hydrometeorological parameters: air and soil temperature, precipitation, wind speed, air and soil humidity, and snow cover thickness. The maps are based on climatic data derived from the MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) reanalysis. In total there are 459, which are arranged into 7 chapters. The atlas geographically covers the western part of the Russian Arctic encompassing the regions of quite intensive transport development, which includes the construction of the Northern Latitudinal Railway. Original algorithms of geospatial data processing and their further representation as well as the maps compiled in GIS environment are discussed. Comprehensive analysis of climatic changes in the region of the Russian Arctic including detailed quantitative evaluation over 40 years is given. In the Discussion, we focus on those changes of the regional climate which, from our point of view, are the most significant for consideration by railway operators. The obtained results contribute to framing the theoretical basis of design, development, and sustainable operation of the railway infrastructure in the Arctic and facilitate the decision-making process. This is the first experience of building a specialized climatic cartographic product for the needs of the Russian railways, and to our knowledge the first atlas such as that in the world. In the future, the amassed experience may be transferred to other regions of the Russian Federation as well as similar regions in Canada, Sweden and Highland China that are also subject to significant climate change.
The Design and Implementation of a Secure Datastore Based on Ethereum Smart Contract
Authors: Aldyaflah Izdehar M. , Zhao Wenbing , Upadhyay Himanshu , Lagos Leonel
Published: April 2023

In this paper, we present a secure datastore based on an Ethereum smart contract. Our research is guided by three research questions. First, we will explore to what extend a smart-contract-based datastore should resemble a traditional database system. Second, we will investigate how to store the data in a smart-contract-based datastore for maximum flexibility while minimizing the gas consumption. Third, we seek answers regarding whether or not a smart-contract-based datastore should incorporate complex processing such as data encryption and data analytic algorithms. The proposed smart-contract-based datastore aims to strike a good balance between several constraints: (1) smart contracts are publicly visible, which may create a confidentiality concern for the data stored in the datastore; (2) unlike traditional database systems, the Ethereum smart contract programming language (i.e., Solidity) offers very limited data structures for data management; (3) all operations that mutate the blockchain state would incur financial costs and the developers for smart contracts must make sure sufficient gas is provisioned for every smart contract call, and ideally, the gas consumption should be minimized. Our investigation shows that although it is essential for a smart-contract-based datastore to offer some basic data query functionality, it is impractical to offer query flexibility that resembles that of a traditional database system. Furthermore, we propose that data should be structured as tag-value pairs, where the tag serves as a non-unique key that describes the nature of the value. We also conclude that complex processing should not be allowed in the smart contract due to the financial burden and security concerns. The tag-based secure datastore designed this way also defines its applicative perimeter, i.e., only applications that align with our strategy would find the proposed datastore a good fit. Those that would rather incur higher financial cost for more data query flexibility and/or less user burden on data pre- and post-processing would find the proposed database too restrictive.
Estimation of Relative Acoustic Impedance Perturbation from Reverse Time Migration Using a Modified Inverse Scattering Imaging Condition
Authors: Liang Hong , Zhang Houzhu , Liu Hongwei
Published: April 2023

Reverse Time Migration (RTM) is a preferred depth migration method for imaging complex structures. It solves the complete wave equation and can model all types of complex wave propagation with no dip limitation. Reverse time migration using the inverse scattering imaging condition produces structural images with an amplitude approximate to the reflectivity, which is a composite effect of the impedance and velocity changes in the acoustic media with variable velocity and density. In this study, we present a modified inverse scattering imaging condition to separate the effect of the impedance and velocity perturbations from the reflectivity. The proposed imaging condition is designed to predict the relative impedance perturbation by selecting near-angle reflections during common-shot RTM. We validate our approach on synthetic models and show that the proposed method can estimate reliable impedance perturbation.
A Study of Ammonium Bifluoride as an Agent for Cleaning Silicon Contamination in the Wafer Dicing Process
Authors: Tsai Teh-Hua , Wang Chen-Yu
Published: April 2023

A new cleaning agent for silicon contamination in the wafer dicing process was formulated in this research. Ammonium bifluoride was introduced as the main ingredient in the formula, and MSA and sulfuric acid were added as the solvent and buffer solution against metal corrosion. It was confirmed that the new formula cleaning agent could be used in the cleaning of silicon contamination from dicing. Silicon contamination is common in the wafer dicing process and consists of silicon powder and relevant metal particles during cutting, all of which are mixed with some adhesive residues. These contaminating particles on the IC surface are exposed to cleaning agents. However, while it is imperative to clean the wafer, the exposed surface is also vulnerable to damage from the solution. This further complicates the procedure because there is currently no ideal cleaning agent for the process. Our proposed formula hopefully provides an ideal chemical for use in wafer cleaning (SC-1, SC-2, BOE), since it uses a less toxic compound, ammonium bifluoride, which yielded good results during our experiments.
Industrial Roll-to-Roll Printing Register Control Using a Pulse-Width Subdivision Detection Algorithm
Authors: Liu Bangchao , Chen Youping , Xie Jingming , Chen Bing
Published: April 2023

Register control systems are a necessary technical measure and an important means of large-scale roll-to-roll industrial printing production. They are effective in reducing the generation of unqualified printing products and improving the accuracy and stability of industrial printing production lines. In this paper, we propose a new register control algorithm that effectively improves the detection accuracy and compensation speed of printing register control systems. Firstly, according to the principle of register color mark detection, a new pulse-width subdivision detection algorithm is proposed, which can greatly improve the accuracy of register error detection without increasing the resolution of external encoder pulse signals. Then, the optimized error compensation method can adaptively adjust the corresponding system parameters, such as the output intensity, error filtering period and output period, according to the current register error size. The new output method greatly improves the error compensation speed without increasing error oscillation. Lastly, the experimental results of 0.01 mm show that the proposed control approach significantly improves the detection accuracy of register errors. Furthermore, the new control algorithm can be applied in the industrial field.
Experimental Study of Ultrasound-Assisted Reaming of Carbon Fiber-Reinforced Plastics/Titanium Alloy Stacks
Authors: Liu Shengtong , Kang Renke , Qin Yan , Dong Zhigang , Guo Xiaoguang , Wang Yidan
Published: April 2023

Carbon fiber-reinforced plastic/titanium alloy (CFRP/Ti) stacks are widely used in the aerospace field based on their high strength to weight ratio and heat resistance. High-quality bolt hole assembly is critical for the safety of the aerospace industry. Reaming is a crucial process in precision machining and is extensively used to improve the quality of bolt holes. Due to the different properties of the material, machining with conventional reaming (CR) presents some challenges, such as tolerance variations across the hole group and difficulty in controlling thrust. In this paper, ultrasonic vibration is applied to the reaming process. A geometrical model of ultrasonic vibration reaming (UVR) was established to analyze its kinematic law. UVR experiments on CFRP/Ti stacks were carried out to study the influence of different ultrasonic amplitudes on reaming thrust and the influence of tool speed on thrust, dimensional accuracy, and surface roughness under optimal ultrasonic amplitude. The average thrust forces in UVR decreased by over 57% (Ti) and 40% (CFRP), respectively, compared to CR. The roughness of CFRP is reduced by 20% with UVR and 28% for titanium alloys. The surface topography of the holes is significantly improved by UVR. This work guides the manufacture of high-quality bolt holes for CFRP/Ti stacks.
An Improved Direct Predictive Torque Control for Torque Ripple and Copper Loss Reduction in SRM Drive
Authors: Sheng Linhao , Wang Guofeng , Fan Yunsheng , Liu Jian , Liu Di , Mu Dongdong
Published: April 2023

This paper introduces a direct predictive torque control (DPTC) method to minimize the torque ripple and copper loss of the switched reluctance motor (SRM). Generally, there is a problem with torque ripple during the SRM’s commutation. In this method, the commutation optimization is provided by a direct predictive torque control algorithm. Firstly, the reachable range of phase torques is predicted and the boundary of two continuous phases is modified. By dividing the torque range directly to determine the torque allocation set, the suppression of torque ripple becomes simple. Secondly, considering the optimization problem of copper loss during commutation, a cost function only related to the phase current is constructed. Further, the minimization of copper loss can be achieved by solving the cost function, and the work of setting weight parameters is not required. Finally, the proposed DPTC method is tested by simulation and experiment in a three-phase 12/8-pole SRM drive system and the results are compared with the existing predictive torque control methods. The results show that the proposed method has less torque ripple and copper loss, which effectively improves the torque control performance.
Physics-Informed Neural Network for Flow Prediction Based on Flow Visualization in Bridge Engineering
Authors: Yan Hui , Wang Yaning , Yan Yan , Cui Jiahuan
Published: April 2023

Wind loads can endanger the safety and stability of bridges, especially long-span cable-supported bridges. Therefore, it is important to evaluate the potential wind loads during the bridge design stage. Traditionally, wind load evaluation is performed by wind tunnel testing, which is relatively expensive. With the development of computational fluid dynamics and high-performance computing, numerical simulations are becoming more accessible for designers. However, the costs required for accurate numerical results are still high, especially for high-fidelity simulations. Under this condition, searching for a more efficient method to evaluate the wind loads in bridge wind engineering has become a new goal. It seems that flow visualization is a good entry point. Although flow visualization techniques have been developed in recent years, it remains difficult to extract velocity and pressure fields from images. To address this problem, physics-informed neural networks (PINNs) have been developed and validated. This study establishes a PINN to investigate the two-dimensional viscous incompressible fluid flow passing a generic bridge deck section. Two cases with different Reynolds numbers are tested. After careful training, it is found that the PINN can accurately extract the velocity and pressure fields from the concentration field and predict the drag and lift coefficients. The results demonstrate that PINNs are a promising method for extracting useful flow information from flow visualization data in engineering applications.
Impact of NOx and NH3 Emission Reduction on Particulate Matter across Po Valley: A LIFE-IP-PREPAIR Study
Authors: Veratti Giorgio , Stortini Michele , Amorati Roberta , Bressan Lidia , Giovannini Giulia , Bande Stefano , Bissardella Francesca , Ghigo Stefania , Angelino Elisabetta , Colombo Loris , Fossati Giuseppe , Malvestiti Giulia , Marongiu Alessandro , Dalla Fontana Alberto , Intini Barbara , Pillon Silvia
Published: April 2023

Air quality in Europe continues to remain poor in many areas, with regulation limits often exceeded by many countries. The EU Life-IP PREPAIR Project, involving administrations and environmental protection agencies of eight regions and three municipalities in Northern Italy and Slovenia, was designed to support the implementation of the regional air quality plans in the Po Valley, one of the most critical areas in Europe in terms of pollution levels. In this study, four air quality modelling systems, based on three chemical transport models (CHIMERE, FARM and CAMx) were applied over the Po Valley to assess the sensitivity of PM2.5 concentrations to NOx and NH3 emission reductions. These two precursors were reduced (individually and simultaneously) from 25% up to 75% for a total of 10 scenarios, aimed at identifying the most efficient emission reduction strategies and to assess the non-linear response of PM2.5 concentrations to precursor changes. The multi-model analysis shows that reductions across multiple emission sectors are necessary to achieve optimal results. In addition, the analysis of non-linearities revealed that during the cold season, the efficiency of PM2.5 abatement tends to increase by increasing the emission reductions, while during summertime, the same efficiency remains almost constant, or slightly decreases towards higher reduction strengths. Since the concentrations of PM2.5 are greater in winter than in summer, it is reasonable to infer that significant emission reductions should be planned to maximise reduction effectiveness.
Heatwaves and Mortality in Spain and Greece: A Comparative Analysis
Authors: Dimitriadou Lida , Zerefos Christos
Published: April 2023

Background: Heatwaves have become a public health emergency raising great public health concerns. Correspondingly, due to climate change, the increase in extreme weather events, such as heatwaves, floods and hurricanes, is predicted through state-of-the-art models and robust statistical analyses. Since the Mediterranean basin is recognized as the most prominent global climate change hot spot, further scientific research on the future impacts of heatwaves on human mortality, as well as human health and well-being, in the Mediterranean region is critical. Methods: The aim of the present study is to compare the relationship between three different causes of mortality (i.e., cardiological, respiratory and cardiorespiratory) and temperature between two countries (Spain and Greece) and five cities (i.e., Madrid, Barcelona, Valencia, Attica and Thessaloniki). To compare the five cities under examination, a robust statistical methodological framework (i.e., Threshold Regression Analysis (TRA)) was applied so as to examine the critical value above which the mean temperature affects cardiological, respiratory and cardiorespiratory mortality. Results: Our results prove that the relationship between mortality and temperature is a nonlinear relationship shaping a U- or J-shaped curve, meaning that mortality is affected by temperature in a non-constant way, indicating that mortality increases during both low and high temperatures. Conclusions: By calculating different temperature thresholds for the five cities under examination, we show that different temperature thresholds are more accurate for different climatic conditions. Hence, climatic conditions should be taken into account when examining the impacts of temperature on human health.
A Framework to Predict Community Risk from Severe Weather Threats Using Probabilistic Hazard Information (PHI)
Authors: Kim Jooho , Campbell Patrick A. , Calhoun Kristin
Published: April 2023

Community assets, including physical structures and critical infrastructure, provide the essential services that underpin our communities. Their destruction or incapacitation from severe weather threats such as hail and tornadoes can have a debilitating impact on a community’s quality of life, economy, and public health. Recently, prototype Probabilistic Hazard Information (PHI) from the NOAA Forecasting a Continuum of Environmental Threats (FACETs) program has been developed to reflect the rapidly changing nature of severe weather threats to support forecasters, emergency management agencies, and the public. This study develops a holistic framework to merge PHI with a geodatabase of local infrastructure and community assets to predict possible impacts during events and to assist with post-event recovery. To measure the degree of damage of each building, this study uses the predicted intensity from forecasters along with damage indicators from the Enhanced Fujita scale for a range of wind speeds associated with the predicted intensity. The proposed framework provides the possibility of (1) live prediction of risks to community assets due to local vulnerability, and (2) provision of detailed damage assessments, such as degree of damage of systems or assets, and affected areas, to emergency agencies, infrastructure managers, and the public immediately following an event. With further refinement and verification, this community risk assessment prediction may be able to better communicate possible impacts and improve community resiliency from severe weather threats by supporting multiple phases of emergency management, including preparedness, response, and recovery.
Deactivation Mechanism and Anti-Deactivation Measures of Metal Catalyst in the Dry Reforming of Methane: A Review
Authors: Yuan Bo , Zhu Tao , Han Yiwei , Zhang Xueli , Wang Meidan , Li Chen
Published: April 2023

In recent decades, the massive emission of greenhouse gases, such as carbon dioxide and methane, into the atmosphere has had a serious impact on the ecological environment. The dry reforming of carbon dioxide and methane to syngas cannot only realize the resource utilization of methane and carbon dioxide but also reduce global climate change. It is of great significance in carbon emission reduction. Owing to the dry reforming of methane (DRM) being a strongly endothermic reaction, it needs to be carried out under high-temperature conditions. It makes the catalyst have problems of the sintering of metal, carbon deposition, and poisoning. This article revolves around the problem of catalyst deactivation during the DRM reaction. It expands upon the thermodynamics and mechanisms of the DRM reaction, analyzes the causes of metal catalyst deactivation due to carbon deposition, sintering, and poisoning, and summarizes how the active components, supports, and additives of metal catalysts restrain the DRM catalyst deactivation during the reaction. The analysis revealed that changing the type and size of the active metal, adjusting the properties of the support, and adding additives can further regulate the dispersion of the active component, the interaction between the active component and the support, the oxygen vacancies of the support, and the acidity and basicity of the catalyst surface, ultimately achieving control over the metal catalyst’s resistance to sintering, carbon deposition, and sulfur poisoning. In addition, it discusses the application of metal catalysts in photothermal and plasma-catalyzed DRM. Finally, it outlines the prospects for research on metal catalysts for the DRM.
Microbial Diversity and Authigenic Mineral Formation of Modern Bottom Sediments in the Littoral Zone of Lake Issyk-Kul, Kyrgyz Republic (Central Asia)
Authors: Krivonogov Sergei , Maltsev Anton , Zelenina Darya , Safonov Alexey
Published: April 2023

This article presents geochemical, mineralogical and microbiological characteristics of five samples of modern bottom sediments in the littoral zone of the high-mountain salty lake Issyk-Kul. The 16S rRNA gene sequencing method shows that the microbial community consists of organic carbon degraders (representatives of phyla: Proteobacteria, Chloroflexi, Bacteroidota and Verrucomicrobiota and families Anaerolineaceae and Hungateiclostridiaceae), photosynthetic microorganisms (representatives of Chloroflexi, phototrophic Acidobacteria, purple sulphur bacteria Chromatiaceae and cyanobacteria) and bacteria of the reducing branches of the sulphur biogeochemical cycle (representatives of Desulfobacterota, Desulfosarcinaceae and Desulfocapsaceae). The participation of microorganisms in processes in the formation of a number of authigenic minerals (calcite, framboidal pyrite, barite and amorphous Si) is established. The high diversity of microbial communities indicates the presence of labile organic components involved in modern biogeochemical processes in sediments. The active destruction of organic matter begins at the water-sediment interface.
Progressive Learning Hill Climbing Algorithm with Energy-Map-Based Initialization for Image Reconstruction
Authors: Zhang Yuhui , Wei Wenhong , Wang Zijia
Published: April 2023

Image reconstruction is an interesting yet challenging optimization problem that has several potential applications. The task is to reconstruct an image using a fixed number of transparent polygons. Traditional gradient-based algorithms cannot be applied to the problem since the optimization objective has no explicit expression and cannot be represented by computational graphs. Metaheuristic search algorithms are powerful optimization techniques for solving complex optimization problems, especially in the context of incomplete information or limited computational capability. In this paper, we developed a novel metaheuristic search algorithm named progressive learning hill climbing (ProHC) for image reconstruction. Instead of placing all the polygons on a blank canvas at once, ProHC starts from one polygon and gradually adds new polygons to the canvas until reaching the number limit. Furthermore, an energy-map-based initialization operator was designed to facilitate the generation of new solutions. To assess the performance of the proposed algorithm, we constructed a benchmark problem set containing four different types of images. The experimental results demonstrated that ProHC was able to produce visually pleasing reconstructions of the benchmark images. Moreover, the time consumed by ProHC was much shorter than that of the existing approach.