bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptive SPP–CNN–LSTM–ATT wind farm cluster short-term power prediction model based on transitional weather classification
Authors: Ding Guili , Yan Gaoyang , Wang Zongyao , Kang Bing , Xu Zhihao , Zhang Xingwang , Xiao Hui , He Wenhua
Published: December 2023

With the expansion of the scale of wind power integration, the safe operation of the grid is challenged. At present, the research mainly focuses on the prediction of a single wind farm, lacking coordinated control of the cluster, and there is a large prediction error in transitional weather. In view of the above problems, this study proposes an adaptive wind farm cluster prediction model based on transitional weather classification, aiming to improve the prediction accuracy of the cluster under transitional weather conditions. First, the reference wind farm is selected, and then the improved snake algorithm is used to optimize the extreme gradient boosting tree (CBAMSO-XGB) to divide the transitional weather, and the sensitive meteorological factors under typical transitional weather conditions are optimized. A convolutional neural network (CNN) with a multi-layer spatial pyramid pooling (SPP) structure is utilized to extract variable dimensional features. Finally, the attention (ATT) mechanism is used to redistribute the weight of the long and short term memory (LSTM) network output to obtain the predicted value, and the cluster wind power prediction value is obtained by upscaling it. The results show that the classification accuracy of the CBAMSO-XGB algorithm in the transitional weather of the two test periods is 99.5833% and 95.4167%, respectively, which is higher than the snake optimization (SO) before the improvement and the other two algorithms; compared to the CNN–LSTM model, the mean absolute error (MAE) of the adaptive prediction model is decreased by approximately 42.49%–72.91% under various transitional weather conditions. The relative root mean square error (RMSE) of the cluster is lower than that of each reference wind farm and the prediction method without upscaling. The results show that the method proposed in this paper effectively improves the prediction accuracy of wind farm clusters during transitional weather.
Experimental research on the effect of graphite on heat transfer performance of a latent heat storage system
Authors: Zhao Yuanyuan , Li Guang , Zhang Xinzhi , Wu Hongqiang
Published: December 2023

Phase change materials (PCMs) provide a good resolution for the latent heat storage system which can be used in many application fields such as solar energy utilization and waste heat recovery. This study aims to experimentally investigate the impact of graphite powder on the thermal characteristics and heat transfer performance of paraffin with ceresin (PC) as a PCM, using water as the heat transfer fluid. Experimental tests were conducted to analyze the heat transfer performance of PC and the influence of graphite powder on its thermal characteristics. Different masses of graphite powder were employed to assess their effects on the heating rate and the time required for PC to reach its melting temperature. The experimental results revealed that the addition of graphite powder improved the heating rate of both PC and water, attributed to its high thermal conductivity. Furthermore, the time for PC to reach the melting temperature was decreased with varying amounts of graphite powder, achieving a maximum reduction of 17.2% with the addition of 40 g of graphite powder. However, the effectiveness of graphite powder in enhancing heat transfer efficiency was found to be limited, with the optimal promotion effect observed at around 40 g of graphite powder for 500 g of PC. The findings of this investigation provide valuable insights for the design of phase change energy storage systems, with potential applications including heat pump drying units, greenhouse energy storage in modern agriculture, and solar energy storage utilization technology. The theoretical basis established can contribute to the development and optimization of PCM-based systems in diverse practical scenarios.
Operation and evaluation of digitalized retail electricity markets under low-carbon transition: recent advances and challenges
Authors: Hu Xiuzhen , Tan Weicong , Xie Yuting , Yang Wei , Zeng Zhijian , Huang Yuanming , Xiao Dongliang , Chi Yuquan , Cheng Runting
Published: December 2023

With the growth of electricity consumers purchasing green energy and the development of digital energy trading platforms, the role of digitalized retail electricity markets in the low-carbon transition of electric energy systems is becoming increasingly crucial. In this circumstance, the research work on retail electricity markets needs to be further analyzed and expanded, which would facilitate the efficient decision-making of both market players and policymakers. First, this paper introduces the latest developments in the retail electricity market under low-carbon energy transition and analyzes the limitations of the existing research works. Second, from three aspects of power trading strategy, retail pricing methodology, and market risk management, it provides an overview of the existing operation and mechanism design strategies of the retail electricity market; then, it provides a systematic introduction to the evaluation system and monitoring methodology of electricity markets, which is not sufficient for the current digitalized retail electricity markets. Finally, the issues regarding operation evaluation and platform optimization of the current digitalized retail electricity market are summarized, and the research topics worth further investigations are recommended.
The optimization analysis of multi-type demand-side flexibility resources for renewable energy accommodation in electrical power systems
Authors: Ding Kun , Zhang Lei , Yang Changhai , Wang Zhuxiu
Published: December 2023

The significant increase in the proportion of renewable energy access has led to a burgeoning and urgent demand for flexible resources within the power system, and the prominence of flexible resources on the demand side has been underscored. The existing research on demand-side response primarily focuses on addressing peak load challenges, while the optimization of demand response for accommodating renewable energy remains inadequate. Considering this issue, the present study initially examines the flexibility mechanism offered by demand-side resources and proposes a calculation approach for determining the adjustable capacity of demand-side flexible resources. Furthermore, considering the limitations of the load that can be shifted, transferred, and curtailed, we develop a collaborative optimization operational model for accommodating renewable energy with multiple types of demand response. Finally, based on the provincial power grid example, the simulation study verifies the efficacy of a multi-type demand response. The results demonstrate that shiftable and transferable loads can effectively facilitate the accommodation of new energy, and their optimal allocation capacity ratios are 5.8% and 2.3%, respectively.
Grouting solidification technology for fractured soft coal seams and its application in coalbed methane (coal mine gas) extraction
Authors: Guangbo Zhang , Suian Zhang , Wei Jia , Xiao Zhang , Yang Zhang , Haoyu Lian , Xiaohua Lian , Huili Fang
Published: December 2023

This article presents an effective method for improving the structure and performance of coal rock masses, thereby facilitating coalbed methane extraction—the grouting solidification technique. A systematic review is conducted on grouting solidification materials, process methods, evaluation techniques, and other related aspects. In conclusion, it is emphasized that the grouting solidification technique requires further refinement in its system, and its continued significance in the dynamically evolving energy and coal industry is underscored. This is crucial for ensuring the efficient development and sustainable utilization of coal and coalbed methane resources.
Population pharmacokinetics and individualized dosing of vancomycin for critically ill patients receiving continuous renal replacement therapy: the role of residual diuresis
Authors: Yu Zhenwei , Liu Jieqiong , Yu Haitao , Zhou Ling , Zhu Jianping , Liang Gang , Yang Yi , Zheng Ying , Han Yun , Xu Junjun , Han Gang , Yu Lingyan , Zhao Yuhua
Published: December 2023

Background: Vancomycin dosing is difficult in critically ill patients receiving continuous renal replacement therapy (CRRT). Previous population pharmacokinetic (PopPK) models seldom consider the effect of residual diuresis, a significant factor of elimination, and thus have poor external utility. This study aimed to build a PopPK model of vancomycin that incorporates daily urine volume to better describe the elimination of vancomycin in these patients.

Methods: We performed a multicenter retrospective study that included critically ill patients who received intermittent intravenous vancomycin and CRRT. The PopPK model was developed using the NONMEM program. Goodness-of-fit plots and bootstrap analysis were employed to evaluate the final model. Monte Carlo simulation was performed to explore the optimal dosage regimen with a target area under the curve of ≥400 mg/L h and 400–600 mg/L h.

Results: Overall, 113 observations available from 71 patients were included in the PopPK model. The pharmacokinetics could be well illustrated by a one-compartment model with first-order elimination, with the 24-h urine volume as a significant covariate of clearance. The final typical clearance was 1.05 L/h, and the mean volume of distribution was 69.0 L. For patients with anuria or oliguria, a maintenance dosage regimen of 750 mg q12h is recommended.

Conclusion: Vancomycin pharmacokinetics in critically ill patients receiving CRRT were well described by the developed PopPK model, which incorporates 24-h urine volume as a covariate. This study will help to better understand vancomycin elimination and benefit precision dosing in these patients.
A case study of College English teachers' emotional experiences in the blended teaching context
Authors: Shi Yu , Gu Haibo , Wang Qian
Published: December 2023

The current research on language teacher education has witnessed a surge in studies focusing on teacher emotions due to their recognized importance in teaching. However, limited efforts have been found to investigate the emotions of Chinese College English teachers in the blended teaching context. This qualitative case study aims to uncover the emotional experiences of four Chinese College English teachers and explore the causes of their emotions in the blended teaching context. Data for the study was primarily gathered through interviews and case documents. The findings indicate that teachers in Eastern China experienced more positive emotions than negative emotions in the blended teaching context, while teachers in Western China exhibited the reverse pattern. These emotions were caused by their continuous appraisal of the interaction between their personal goals and various ecological systems. The research findings underscore the crucial role of teacher emotion in blended teaching and provide implications for enhancing blended teaching practices.
Effect of the Light Environment on Image-Based SPAD Value Prediction of Radish Leaves
Authors: Kamiwaki Yuto , Fukuda Shinji
Published: December 2023

This study aims to clarify the influence of photographic environments under different light sources on image-based SPAD value prediction. The input variables for the SPAD value prediction using Random Forests, XGBoost, and LightGBM were RGB values, HSL values, HSV values, light color temperature (LCT), and illuminance (ILL). Model performance was assessed using Pearson’s correlation coefficient (COR), Nash–Sutcliffe efficiency (NSE), and root mean squared error (RMSE). Especially, SPAD value prediction with Random Forests resulted in high accuracy in a stable light environment; CORRGB+ILL+LCT and CORHSL+ILL+LCT were 0.929 and 0.922, respectively. Image-based SPAD value prediction was effective under halogen light with a similar color temperature at dusk; CORRGB+ILL and CORHSL+ILL were 0.895 and 0.876, respectively. The HSL value under LED could be used to predict the SPAD value with high accuracy in all performance measures. The results supported the applicability of SPAD value prediction using Random Forests under a wide range of lighting conditions, such as dusk, by training a model based on data collected under different illuminance conditions in various light sources. Further studies are required to examine this method under outdoor conditions in spatiotemporally dynamic light environments.
Study of Error Flow for Hydraulic System Simulation Models for Construction Machinery Based on the State-Space Approach
Authors: Su Deying , Rao Hongyan , Wang Shaojie , Pan Yongjun , Xu Yubing , Hou Liang
Published: December 2023

This study presents an error flow research method for simulation models of hydraulic systems in construction machinery based on the state-space approach, aiming to ensure the reliable application of digital twin models. Initially, a comprehensive analysis of errors in the simulation modeling of hydraulic systems in construction machinery was conducted, highlighting simulation model parameters as the primary error sources. Subsequently, a set of metrics for assessing the accuracy of simulation models was developed. Following this, an error flow analysis method for simulation models of hydraulic systems in construction machinery was explored based on the state space approach, delving into the sources, transmission, and accumulation of errors in the simulation modeling of valve-controlled cylinder systems. The research results unequivocally indicate that the spring stiffness, viscous damping coefficient, and hydraulic cylinder external leakage coefficient are critical parameters affecting the accuracy of valve-controlled cylinder system simulation models. Furthermore, it was observed that the simulation model of the control valve has a significantly greater impact on the errors in the valve-controlled cylinder system simulation model than the hydraulic cylinder model. In conclusion, the reliability of the error flow model was confirmed through simulation experiments, revealing a maximum relative error of only 3.73% between the error flow model and the results of the simulation experiments.
Antifungal Activity of Essential Oils on Helminthosporium solani Causing Potato Silver Scurf under In Vitro and In Vivo Conditions
Authors: Kmoch Martin , Loubová Věra , Veselská Marie , Jílková Barbora , Víchová Jana
Published: December 2023

Potato silver scurf, caused by the fungus Helminthosporium solani, is an important storage disease of potato (Solanum tuberosum L.), reducing the market value of tubers. Using in vitro and in vivo assays, the presented experiments aimed to determine the effect of selected essential oils (EOs: α-pinene, carvacrol, cinnamaldehyde, D-carvone, eucalyptol, L-linalool, L-menthol, L-menthone, (R)-(+)-limonene, and thymol) on H. solani growth. All EOs inhibited pathogen growth, but their antifungal activities differed significantly. Thymol, carvacrol, and cinnamaldehyde had the strongest inhibitory effects on mycelial growth under in vitro conditions. (R)-(+)-limonene displayed the weakest inhibition. The effectiveness of those EOs with the greatest antifungal activity was confirmed by in vivo experiments. EOs were applied through dressing and fumigation, with EOs bound to a biopolymer for dressing. Dressing and fumigation brought a highly statistically significant reduction in H. solani infection intensity and sporulation intensity on tubers. Although EOs had an insignificant effect on potato cooking quality, the taste of EO-dressed tubers was degraded by an off-odor and off-taste. EOs could provide an ecological alternative for reducing H. solani tuber infection during storage.
Study on the Relationship between Crack Initiation and Crack Bifurcation in Walnut Shells Based on Energy
Authors: Man Xiaolan , Li Long , Zhang Hong , Lan Haipeng , Fan Xiuwen , Tang Yurong , Zhang Yongcheng
Published: December 2023

Clarifying the dissipated energy required for crack expansion is an effective way to control material crushing. Therefore, based on the material fracture probability model and fractal theory, the energy range required for crack extension was determined, and the morphology of the cracks was quantified. This study investigates the influence of walnut size on crack propagation characteristics; this includes its effects on the crack initiation threshold energy, representing resistance to crack initiation, and the crack bifurcation threshold energy, representing resistance to crack bifurcation. The results show that crack extension has a well-defined threshold energy below which cracks do not initiate or bifurcate. The size of walnuts significantly impacts crack propagation characteristics, showing that both crack initiation threshold energy and crack bifurcation threshold energy decrease with increasing walnut sizes. In addition, there is a positive correlation function between the crack initiation threshold energy and the crack bifurcation threshold energy. The experimental results can offer fresh insights into material fracture prediction and serve as a reference for numerical simulations.
Long-Term Simulated Direct N2O Emissions from German Oilseed Rape Cultivation below the IPCC Emission Factor
Authors: Räbiger Thomas , Neukam Dorothee , Knieß Astrid , Böttcher Ulf , Kage Henning , Kühling Insa
Published: December 2023

The low nitrogen (N)-use efficiency of intensive winter oilseed rape (WOSR) cropping systems may cause negative environmental impacts, especially due to N leaching and gaseous losses. The aim of this study was to use data from field experiments (five sites across Germany representing typical WOSR regions) for parametrization of a nitrous oxide (N2O) emission component for implementation into a process-based dynamic plant-soil-atmosphere model (PSAM). After calibration and evaluation with three years of field data from five different N fertilizer treatments, a long-term simulation with 25-year historical weather data was conducted to derive functional relations and emission factors (EFs). The model performed best at higher aggregation levels (cumulative emissions over the entire cropping period, R2 of 0.48/0.77 for calibration/evaluation), but also reasonably simulated short-term dynamics (e.g., fertilizer applications, extreme weather events). Site-specific and year-specific N2O emissions varied within the range of medians from 0.56–4.93 kg N2O-N ha−1. Mineral fertilizer-induced EFs at economic optimal N inputs ranged from 0.16–0.65%, which was markedly below the aggregated IPCC standard value of 1% for direct N2O emissions. Generally, the simulated emissions were consistently higher with finer soil textures and increasing N inputs. The process-based approach, moreover, allowed the identification of the major source of N2O, which mainly originated from nitrification processes.
Influence of Application Timings, Rates, and Adjuvants on Tiencarbazone-Methyl Plus Isoxaflutole and Mesotrione with Nicosulfuron and Rimsulfuron on Weed Control and Yield of Maize
Authors: Idziak Robert , Sakowicz Tomasz , Waligóra Hubert , Szulc Piotr , Majchrzak Leszek , Stachowiak Barbara , Neumann Małgorzata
Published: December 2023

Weed control in maize is usually limited to a single herbicide treatment, but the application of two or more herbicides is associated with many benefits, e.g., increasing the spectrum of control weeds, reducing the risk of damage to crops by using reduced rates of herbicides, limiting their residues in the soil or crop, etc. This field experiment was conducted in the years 2016–2018 to determine whether the split application of soil-applied thiencarbazone-methyl + isoxaflutole and foliar-applied mesotrione + nicosulfuron + rimsulfuron, in reduced rates with adjuvants, can contribute to enhancing herbicide effectiveness and increasing maize yield. Weed control in maize in a split-dose system with a mixture of thiencarbazone-methyl + isoxaflutole at strongly reduced rates with the addition of UAN and the adjuvant Atpolan SoilMaxx or Grounded, and then mesotrione + nicosulfuron + rimsulfuron at strongly reduced rates with UAN and Atpolan SoilMaxx or Actirob 842 EC allowed for great control of weeds. The total amount of substances was slightly higher than in single treatments with adjuvants, but lower than for individual active substances, leading to a reduction in the amount of active substances reaching the environment, while maintaining very high herbicide efficacy.
Nitric Oxide Promoted the Seed Germination of Cynanchum auriculatum under Cadmium Stress
Authors: Liu Fang-Fang , Qiao Xuan-Huan , Yang Tao , Zhao Peng , Zhu Zhi-Peng , Zhao Jun-Hao , Luo Jia-Ming , Xiong Ai-Sheng , Sun Miao
Published: December 2023

Cynanchum auriculatum, an early food-medicine homologous plant native to Asia, possesses significant nutritional and health benefits. However, the presence of cadmium (Cd) in the soil poses a hazard to the germination and growth of C. auriculatum. As nitric oxide (NO) plays a vital role in plant resistance to heavy metal stress, we used three different concentrations of SNP treatment during the germination phase, aiming to alleviate the inhibitory effects of Cd stress on the seed germination of C. auriculatum. The results indicated that when compared to seeds treated with SNP concentrations of 0.2 mM and 0.8 mM, C. auriculatum seeds treated with 0.4 mM SNP exhibited an improved germination rate and germination index, as well as longer hypocotyl. Furthermore, in comparison to NOS-like, the SNP application stimulated the production of endogenous NO through NR catalysis. Additional investigations showed that the ABA level decreased while the GA level increased under normal conditions, while the SNP application enhanced the accumulation of both ABA and GA in C. auriculatum seeds under Cd stress. Histochemical staining and biochemical indicators demonstrated that SNP treatment enhanced the enzymatic activity of SOD, POD, and CAT, while inhibiting the production of hydrogen peroxide and superoxide anion. Moreover, SNP treatment resulted in increased α-amylase activity, which facilitated starch hydrolysis and the generation of soluble sugar. Ultimately, the seed vitality of C. auriculatum under Cd stress was promoted. Our findings present a theoretical framework for the application of SNP in the seed germination mechanism of C. auriculatum and establish the groundwork for comprehending the physiological role of NO under Cd stress.
Lessons from the Varietal Evolution of Durum Wheat in Italy
Authors: Careddu Martina Ludovica , Giunta Francesco , Motzo Rosella
Published: December 2023

The leading role of Italy in the cultivation of durum wheat stimulated intense breeding activities in the country from the beginning of the 20th century, much earlier than in any other country involved in durum wheat production. Older, genetically more heterogeneous landraces were replaced with new, highly productive, superior quality varieties, and this led to an inevitable reduction in the overall genetic diversity among new cultivars, which makes the genetic variability preserved in old cultivars particularly valuable and important. The aim of this paper was to assist future breeding programs by providing a detailed description of the history of durum wheat breeding in Italy and of the changes in yield, quality, and related traits that subsequently occurred, starting from the most diffuse landraces present between 1900 and 1920 up until the present day. The parallel evolution of breeding techniques, breeding goals, and agricultural systems in this period is also described, and some future breeding goals suggested. In the current context of climate change and of rapidly mutating pathogen populations, preserving the yield level through the continuous introduction of new cultivars by exploiting the reservoir of largely unused genetic variation stored in old cultivars and landraces could be as important as increasing grain yield and quality.
A Sensor-Based Decision Model for Precision Weed Harrowing
Authors: Berge Therese W. , Urdal Frode , Torp Torfinn , Andreasen Christian
Published: December 2023

Weed harrowing is commonly used to manage weeds in organic farming but is also applied in conventional farming to replace herbicides. Due to its whole-field application, weed harrowing after crop emergence has relatively poor selectivity and may cause crop damage. Weediness generally varies within a field. Therefore, there is a potential to improve the selectivity and consider the within-field variation in weediness. This paper describes a decision model for precision post-emergence weed harrowing in cereals based on experimental data in spring barley and nonlinear regression analysis. The model predicts the optimal weed harrowing intensity in terms of the tine angle of the harrow for a given weediness (in terms of percentage weed cover), a given draft force of tines, and the biological weed damage threshold (in terms of percentage weed cover). Weed cover was measured with near-ground RGB images analyzed with a machine vision algorithm based on deep learning techniques. The draft force of tines was estimated with an electronic load cell. The proposed model is the first that uses a weed damage threshold in addition to site-specific values of weed cover and soil hardness to predict the site-specific optimal weed harrow tine angle. Future field trials should validate the suggested model.
The Potential Role of Zinc and Silicon in Improving Grain Yield and Lodging Resistance of Rice (Oryza sativa L.)
Authors: Fu Weiqing , Zhao Yanjie , Zha Xinrui , Ullah Jawad , Ye Mao , Shah Farooq , Yuan Qianhua , Wang Peng , Tao Yang , Wu Wei
Published: December 2023

Understanding the agronomic interventions that ensure higher crop yields and minimize their chances of failure is critical for meeting global nutritional demands. Rice is a staple food crop that is prone to lodging risk, particularly when higher yields are desired. The potential role of a combined application of Zinc (Zn) and Silicon (Si) in determining the grain yield and lodging resistance has been rarely investigated under field conditions. Thus, field trials were carried out to evaluate the grain yield and lodging resistance of rice at two different locations i.e., Qionghai and Wuzhishan, under three levels of Zn (0, 40, and 80 kg ha−1) and Si (0, 120, and 240 kg ha−1). The results showed that Zn application at the rates of 40 and 80 kg ha−1 increased rice yield by 9% and 5% at Qionghai, and by 5% and 6% at Wuzhishan, respectively. The improved grain yield due to Zn application could be attributed to the increased panicles m−2, splikelets m−2, and aboveground biomass. Meanwhile, Zn failed to show any remarkable impact on stem and root lodging susceptibility. Conversely, no significant influence of applying Si on grain yield was observed, while its application at the rates of 120 and 240 kg Si ha−1 enhanced the stem and root lodging resistance (denoted by their respective safety factors, for stem (SFs) and for root (SFr) by 32% and 22% at Qionghai, and by 11% and 34% at Wuzhishan, respectively, compared to zero Si application. The improved lodging resistance in terms of SFs and SFr could be ascribed to the increased stem bending strength and anchorage strength, while self-weight moment of whole plant decreased. In summary, a beneficial role of Si in lodging resistance and Zn in yield enhancement were evidenced in the present study across the two sites. It can be concluded that by combining 40 kg Zn ha−1 with 120 kg Si ha−1, both grain yield and lodging resistance could be simultaneously improved in rice crops.
Characteristics and Influence Factors of Soil Water and Salt Movement in the Yellow River Irrigation District
Authors: He Kangkang , Zhang Qiuying , Ai Zhipin , Xu Ning , Qiao Yunfeng , Tian Chao , Leng Peifang , Cheng Hefa , Chen Gang , Li Fadong
Published: December 2023

Climate change and human activities lead to freshwater shortage, soil salinization, and food security crises in arable land. To explore the natural and irrigation factors on soil water and salt movement, this study quantitatively analyzed the dynamic characteristics of soil water and salt movement under precipitation, groundwater irrigation, and brackish water irrigation conditions for the next 30 years using Hydrus-1D model-based parameters obtained from the winter wheat–summer maize rotation experiments in the Yellow River Irrigation District. The results showed that precipitation was the key factor of climate change affecting soil water and salt migration, especially in the 0–20 cm soil layer. Under both SSP585 and SSP245 climate scenarios, rainfall in normal and wet years promoted salt leaching up to 1 m below the surface soil. But in dry years, salt washing treatment was required for the tillage layer to prevent salt accumulation. The higher the groundwater level was, the higher the soil water and salt content was in the 0–100 cm soil layer. In this soil layer, a 2 m groundwater level contributed 30% to wheat water needs, while a 3 m groundwater level contributed 18%, and no significant contribution was observed for a 4 m groundwater level. The salinity of the soil profile showed an overall increasing trend with irrigation using 1–3 g/L brackish water for 30 years. However, the salinity in the 0–100 cm soil layer was below the salt tolerance threshold of winter wheat and summer maize with salts accumulated in the 1–2 m soil layer. Considering the salinization of the root zone and crop water needs, it is recommended that the safe groundwater level for brackish water irrigation should be 3 m in the study region. This study provides scientific reference for groundwater–farmland ecosystems to utilize brackish water and treat saline–alkali lands.
Assessing the Antioxidant Properties, In Vitro Cytotoxicity and Antitumoral Effects of Polyphenol-Rich Perilla leaves Extracts
Authors: Adam Gigi , Cojocaru Florina Daniela , Verestiuc Liliana , Cioanca Oana , Vasilache Ingrid-Andrada , Adam Ana-Maria , Mircea Cornelia , Nechita Aurel , Harabor Valeriu , Huzum Bogdan , Harabor AnaMaria , Hancianu Monica
Published: December 2023

(1) Background: This study aimed to outline the antioxidant, antitumoral, and cytotoxic proprieties of various types of Perilla frutescens extracts obtained from the leaves of the species. (2) Methods: We determined total polyphenols, flavonoids and anthocyanins contents, as well as the in vitro antioxidant, antitumoral, and cytotoxic actions in three types of ethanolic extracts (E1, E2, E3) and in three types of acetone: ethanol extracts (A1, A2, A3) of Perilla frutescens according to standardized procedures. (3) Results: We found that Perilla frutescens ethanolic extracts had the highest total phenol and anthocyanins concentrations. The flavonoids concentration was not statistically different between the extracts. The iron chelating capacity, hydroxyl radical scavenging capacity, superoxide anion radical scavenging capacity, and lipoxygenase inhibition capacity showed a significant increase with higher concentrations of Perilla frutescens extracts, particularly the ethanolic extracts. Perillyl alcohol had greater cytotoxic capacity in the MG-63 cell line and E1 extract showed similar significant cytotoxic effects in the A431 cell line. (4) Conclusions: Both ethanolic and acetone–ethanol extracts from Perilla frutescens exhibited important antioxidant and antitumoral actions in vitro, which proportionally increased with concentration. The cytotoxic threshold determined in this study for various types of extracts could help determine the best dosage with the maximum antioxidant and antitumoral potential. Our results could serve as a basis for further studies that will investigate the cytotoxic effects of Perilla frutescens variants on various types of cancer cell lines.
Inverse Kinematics Proposal to Automatize the 3D Scanning of Handball Shoes by Using a Robotic Arm with 3 Actuated Joints
Authors: Pancu Rareș , Șuteu Marius Darius , Vesselenyi Tiberiu , Buhas Sorin Dacian , Szabo-Alexi Mariana , Szabo-Alexi Paul , Dragos Paul Florian
Published: December 2023

The purpose of this paper is to present a procedure for automating the scanning process based on a mathematical model for a handheld 3D scanner for shoes used in some indoor sports. The study aims to use inverse kinematics to automate 3d footwear scanning used for indoor sport (handball) using a robotic arm with three joints. A modeling of the robotic arm and final effector was performed, to simulate the minimum and maximum trajectory of the robot arm according to the angles shown based on the mathematical model and inverse kinematics. With an easy-to-use interface and ergonomic design, this 3D scanning solution offers the versatility to scan various objects (such as scanning two shoe models used in indoor sports) and complex surface types. This scanning manner represents the state of the art of 3D scanning solutions as well as a benchmark in the 3D measurement equipment industry. The data obtained as a result of this research provide new directions and solutions for sports shoe scanning for indoor sports based on scanning trajectories preset by inverse kinematics in order to automate the scanning process using a handheld 3D scanner. Based on the mathematical model presented in the paper, automation of the scanning process can be achieved by maintaining the proposed trajectory using an automated arm operating through a control program that can be run on a simple controller.
Motion-Based Control Strategy of Knee Actuated Exoskeletal Gait Orthosis for Hemiplegic Patients: A Feasibility Study
Authors: Heo Yoon , Choi Hyuk-Jae , Lee Jong-Won , Cho Hyeon-Seok , Kim Gyoo-Suk
Published: December 2023

In this study, we developed a unilateral knee actuated exoskeletal gait orthosis (KAEGO) for hemiplegic patients to conduct gait training in real-world environments without spatial limitations. For this purpose, it is crucial that the controller interacts with the patient’s gait intentions. This study newly proposes a simple gait control strategy that detects the gait state and recognizes the patient’s gait intentions using only the motion information of the lower limbs obtained from an embedded inertial measurement units (IMU) sensor and a knee angle sensor without employing ground reaction force (GRF) sensors. In addition, a torque generation method based on negative damping was newly applied as a method to determine the appropriate amount of assistive torque to support flexion or extension movements of the knee joint. To validate the performance of the developed KAEGO and the effectiveness of our proposed gait control strategy, we conducted walking tests with a hemiplegic patient. These tests included verifying the accuracy of gait recognition and comparing the metabolic cost of transport (COT). The experimental results confirmed that our gait control approach effectively recognizes the patient’s gait intentions without GRF sensors and reduces the metabolic cost by approximately 8% compared to not wearing the device.
Dynamic Cloud Resource Allocation: A Broker-Based Multi-Criteria Approach for Optimal Task Assignment
Authors: Aljuhani Abdulmajeed , Alhubaishy Abdulaziz
Published: December 2023

Cloud brokers and service providers are concerned with utilizing available resources to maximize their profits. On the other hand, customers seek the best service provider/resource to provide them with maximum satisfaction. One of the main concerns is the variability of available service providers on the cloud, their capabilities, and the availability of their resources. Furthermore, various criteria influence the effective assignment of a task to a virtual machine (VM) before it is, in turn, submitted to the physical machine (PM). To bring cloud service providers (CSPs) and customers together, this study proposes a broker-based mechanism that measures the tendency of each customer’s task. Then, the proposed mechanism assigns all tasks—in prioritized order of importance—to the best available service provider/resource. The model acquires the importance of each task, CSP, or resource by extracting and manipulating the evaluations provided by decision makers and by adopting a multi-criteria decision-making (MCDM) method. Thus, a partial result of the proposed mechanism is a defined and prioritized pool for each of the tasks, CSPs, and resources. Various MCDM methods are examined and compared to validate the proposed model, and experiments show the applicability of the various methods within the model. Furthermore, the results of the experiments verify the suitability and applicability of the proposed model within the cloud environment.
A Novel Zeroing Neural Network Control Scheme for Tracked Mobile Robot Based on an Extended State Observer
Authors: Cao Yuxuan , Pu Jinyun
Published: December 2023

A novel zeroing neural network control scheme based on an extended state observer is proposed for the trajectory tracking of a tracked mobile robot which is subject to unknown external disturbances and uncertainties. To estimate unknown lumped disturbances and unmeasured velocities, a third-order fixed-time extended state observer is proposed, and the observation errors converge to zero in fixed time. Based on the estimated values, the zeroing neural network controller is designed for a tracked mobile robot to track an eight shape. The stability of the system is analyzed based on Lyapunov theory. Simulation results are illustrated to show the effectiveness of the proposed control scheme.
Deep Learning and Machine Learning Applications in Biomedicine
Authors: Yan Peiyi , Liu Yaojia , Jia Yuran , Zhao Tianyi
Published: December 2023

The rise of omics research, spanning genomics, transcriptomics, proteomics, and epigenomics, has revolutionized our understanding of biological systems [...]
An Improved Contact Force Model of Polyhedral Elements for the Discrete Element Method
Authors: Wang Yue , Liu Jun , Zhen Mengyang , Liu Zheng , Zheng Haowen , Zhao Futian , Ou Chen , Liu Pengcheng
Published: December 2023

The discrete element method (DEM) serves as a robust tool for simulating the mechanical behavior of granular materials. The accuracy of the DEM simulation is determined by the calculation of contact forces between elements. Compared to spherical elements, the contact modes of polyhedral elements are more complex. In this work, the contact force between polyhedral elements under different contact modes was investigated by experiment. Based on the experimental results, the normal stiffness coefficient in the Cundall’s contact model was modified. The improved contact force model was then applied in the DEM simulation and validated by means of comparison with the results of packing experiments. The research results demonstrate that the improved contact force model can be effectively applied to the simulation of different contact modes between polyhedral elements. The results of the packing experiment highly coincide with the results of the DEM simulation, which confirms the accuracy and reliability of the improved contact force model.
Doppler Factor in the Omega-k Algorithm for Pulsed and Continuous Wave Synthetic Aperture Radar Raw Data Processing
Authors: Jancco-Chara Jhohan , Palomino-Quispe Facundo , Coaquira-Castillo Roger Jesus , Herrera-Levano Julio Cesar , Florez Ruben
Published: December 2023

Synthetic aperture radar (SAR) raw data do not have a direct application; therefore, SAR raw signal processing algorithms are used to generate images that are used for various required applications. Currently, there are several algorithms focusing SAR raw data such as the range-Doppler algorithm, Chirp Scaling algorithm, and Omega-k algorithm, with these algorithms being the most used and traditional in SAR raw signal processing. The most prominent algorithm that operates in the frequency domain for focusing SAR raw data obtained by a synthetic aperture radar with large synthetic apertures is the Omega-k algorithm, which operates in the two-dimensional frequency domain; therefore, in this paper, we used the Omega-k algorithm to produce SAR images and modify the Omega-k algorithm by adding the Doppler factor to improve the accuracy of SAR raw data processing obtained by the continuous wave and pulsed frequency modulated linear frequency modulated radar system from the surfaces of interest. On the other hand, for the case of unmanned aerial vehicle-borne linear frequency modulated continuous wave (LFM-CW) SAR systems, we added motion compensation to the modified Omega-k algorithm. Finally, the testing and validation of the developed Omega-k algorithm used simulated and real SAR raw data for both pulsed synthetic aperture and continuous wave radars. The real SAR raw data used for the validation of the modified Omega-k algorithm were the raw data obtained by the micro advanced synthetic aperture radar (MicroASAR) system, which is an LFM-CW synthetic aperture radar installed on board an unmanned aerial system and the raw data obtained by European remote sensing (ERS-2) satellite with a synthetic aperture radar installed.
Topological Optimization of Bi-Directional Progressive Structures with Dynamic Stress Constraints under Aperiodic Load
Authors: Li Yongxin , Chang Tao , Kong Weiyu , Wu Fenghe , Kong Xiangdong
Published: December 2023

The topology optimization of dynamic stress constraints is highly nonlinear and singular and has been little studied. Dynamic stress based on progressive structural optimization is only available by applying the modal iteration method, but due to the nonlinear limitations of the modal superposition method, there is an urgent need to develop a progressive structural optimization method based on dynamic stress sensitivity under direct integration. This method is for the dynamic stresses under non-periodic loading with iterative cycle updating variations. This article proposes a topological optimization method of continuum structures with stress constraints under an aperiodic load based on the Bi-directional Evolutionary Structural Optimization Method (BESO). First, the P-norm condensation function was used to obtain the global stress to approximate maximum stress. By introducing the Lagrange multiplier, the design goal was to increase the P-norm stress on the basis of the smallest volume. After that, based on the dynamic finite element theory, the sensitivity of each cell formula of the objective function and the constraint conditions of the design variables were strictly derived. Then, the performance evaluation index was put forward based on volume and stress, and the convergence criterion based on the performance evaluation index was defined. This method solves the topology optimization problem of stress constraints under a non-periodic load and the topology optimization problem of stress constraints under a periodic load, such as a simple harmonic load.
Stand-Up Time Dependence on Protective Roof–Pillar Bearing Structure of Bauxite
Authors: Jiang Lichun , Liu Wei
Published: December 2023

The immediate roof of Shanxi sedimentary bauxite is hard clay rock, which maintain stable difficultly in goaf. It is necessary to ensure the stability of the goaf during the mine production period. The relevant research objects did not involve soft rock mass such as bauxite and hard clay and did not pay attention to the weakening characteristics of load-bearing structures under the action of weathering and rheology. This paper provides theoretical support for the safety production of bauxite and similar mines. In order to study the relationship between the stability of the protective roof-pillar bearing structure and time, this paper uses elastic thin plates and rheological theory to build the physical model of the bauxite protective roof-pillar bearing structure, and gives the calculation formula of the stand-up time of the bearing structure. The influence of factors such as the thickness of the protective roof, the uniform surface force coefficient of pillar, the span of the goaf and the thickness of the overlying rock layer on the stand-up time of the bearing structure is analyzed. The relationship between the ultimate bearing capacity and stand-up time of the bearing structure is quantified. The results show that the bearing capacity of the bearing structure is affected by the mechanical properties of the rock mass and the structural parameters of the goaf. Under the condition that the influencing factors of the mechanical parameters of the rock mass remain unchanged, the stand-up time T, which represents the bearing capacity of the bearing structure, is positively correlated with the thickness of the protective roof, positively correlated with the uniform surface force coefficient of the pillar, negatively correlated with the span of the goaf and negatively correlated with the thickness of the overlying rock layer. The engineering example verifies the rationality of theoretical calculation and provides a new idea for mining safety.
Investigation of Laser Ablation Quality Based on Data Science and Machine Learning XGBoost Classifier
Authors: Tsai Chien-Chung , Yiu Tung-Hon
Published: December 2023

This work proposes a matching data science approach for the laser ablation quality, reb, the study of Si3N4 film based on supervised machine learning classifiers in the CMOS-MEMS process. The study demonstrates that there exists an energy threshold, Eth, for laser ablation. If the laser energy surpasses this threshold, increasing the interval time will not contribute significantly to the recovery of pulse laser energy. Thus, reb enhancement is limited. When the energy is greater than 0.258 mJ, there exists a critical value of interval time at which the reb value is relatively low for each energy level, respectively. In addition, the variation of reb, Δreb, is independent of the interval time at the invariant point of energy between 0.32 mJ and 0.36 mJ. Energy and interval time exhibit a Pearson correlation of 0.82 and 0.53 with reb, respectively. To maintain Δreb below 0.15, green laser ablation of Si3N4 at operating energies of 0.258–0.378 mJ can adopt a baseline interval time of the initial baseline multiplied by 1/∜2. Additionally, for operating energies of 0.288–0.378 mJ during Si3N4 laser ablation, Δreb can be kept below 0.1. With the forced partition methods, namely, the k-means method and percentile method, the XGBoost (v 2.0.3) classifier maintains a competitive accuracy across test sizes of 0.20–0.40, outperforming the machine learning algorithms Random Forest and Logistic Regression, with the highest accuracy of 0.78 at a test size of 0.20.