bluuebunny/crossref_metadata_2025 huggingface dataset:
Coupled Force–Position Control for Dynamic Contact Force Tracking in Uncertain Environment
Authors: Song Xiaogang , Li Bing , Xu Wenfu , Li Zhisen
Published: June 2022

Both the position and force control of robots are needed in industrial manufacturing, such as in assembly and grinding, etc. In this paper, we concentrate on two issues. One is the system oscillation in traditional hybrid force–position control (HFPC) during switching between force and position control because the diagonal elements in the selection matrix are either 0 or 1. Another issue is the poor force-tracking performance of conventional impedance control, which depends on accurate environmental models. To address these issues, a coupled force–position control (CFPC) method is presented in this paper by combining the proposed adaptive impedance control method with a modified HFPC method. The selection matrix S of HFPC is replaced with a weighted matrix Sw. A weighted matrix regulator is designed to realize smooth switching between position and force control by adjusting the matrix weights in real time, and an adaptive impedance control algorithm is proposed to improve the force-tracking performance in complex environments. To verify the feasibility of the CFPC method proposed in this paper, simulations and physical experiments were conducted. The results show that the CFPC method has the advantages of a better force-tracking performance and a smoother switching between position and force control compared to the traditional HFPC method. A grinding experiment was conducted to further compare the performances of the HFPC and CFPC methods. The roughness values of the ground plates were 0.059 μm for the HFPC method and 0.031 μm for the proposed CFPC method, which demonstrates that the proposed CFPC method has a better performance.
Evaluation of Artificial Neural Network to Model Performance Attributes of a Mechanization Unit (Tractor-Chisel Plow) under Different Working Variables
Authors: Al-Dosary Naji Mordi Naji , Aboukarima Abdulwahed Mohamed , Al-Hamed Saad Abdulrahman
Published: June 2022

The focal objective of the current research is to apply artificial neural network (ANN) and multiple linear regression (MLR) methods for modeling the performance attributes of a mechanization unit (tractor-chisel plow) during the plowing process under both different soil types and working variables. Two different parameters to represent working conditions and soil type were considered as potential input parameters. The first parameter represented soil type by calculating soil texture index as a combination of clay, silt, and sand. The second one was constructed into one dimensionless parameter, namely the field working index. This index linked most working variables such as plowing speed, plow width, soil moisture content, soil bulk density, tractor power, and plowing depth. The performance of the created ANN and MLR models was appraised by computing mean-absolute-error criterion for the testing dataset. The mean absolute error values for draft force, effective field capacity, fuel consumption, drawbar power, overall energy efficiency, rate of plowed soil volume, and loading factor, were 1.44 kN, 0.03 ha/h, 1.17 L/h, 2.28 kW, 0.68%, 73.97 m3/h, and 0.08 (decimal), respectively, when the ANN model was applied. In addition, coefficient of determination (R2) acted as a criterion for judging the performance of the developed models, and their values when ANN was applied were 0.569, 0.384, 0.516, 0.454, 0.486, 0.777, and 0.730 for the same performance attributes, respectively. When the MLR model was applied, the corresponding values of R2 were 0.239, 0.358, 0.352, 0.429, 0.511, 0.482, and 0.422, respectively, for the same attributes. The current study adds to the standing literature by contributing data and information regarding the performance attributes of a tractor-chisel plow unit under specific working variables and soil types. In addition, the models developed for plowing operations in different soil texture and under the field working index are recommended for use in budgeting for diesel consumption, in calculating operation cost, in matching mechanization units of tractor-chisel plows, in estimating energy requirements of tractor-chisel plow combinations, etc.
Foliar Brassinolide Sprays Ameliorate Post-Silking Heat Stress on the Accumulation and Remobilization of Biomass and Nitrogen in Fresh Waxy Maize
Authors: Zhang Xiaoyu , Li Guanghao , Yang Huan , Lu Dalei
Published: June 2022

Heat stress (HS) during grain filling is an extreme environmental factor and affects plant growth and development. Foliar application of exogenous brassinolide (BR) is an effective practice to relieve HS injuries, but the influence on the accumulation and remobilization of biomass and nitrogen is still unclear. In the present study, the effect of foliar BR application at the silking stage on the accumulation and remobilization of biomass and nitrogen in fresh waxy maize under ambient (28/20 °C) and high (35/27 °C) temperatures during grain filling were studied in a phytotron using heat-sensitive Yunuo7 (YN7) and heat-tolerant Jingkenuo2000 (JKN2000) as materials. HS reduced the fresh ear yield by 21.8% and 19.8% in YN7 and JKN2000, respectively, but fresh grain yield was only reduced in the heat-sensitive hybrid (6.9%) and unaffected in the heat-tolerant hybrid. BR application improved the yields of fresh ears (11.3% and 10.9% in YN7 and JKN2000, respectively) and grains (19.9% and 13.2% in YN7 and JKN2000, respectively) under HS, and the increases were higher in YN7. HS decreased the post-silking biomass accumulation by 67.3% and 51.8%, and nitrogen deposition by 61.9% and 50.5%, in YN7 and JKN2000, respectively. The remobilization of pre- and post-silking biomass and nitrogen were increased and decreased by HS in YN7, respectively, but both were unaffected in JKN2000. Under HS, BR application increased the remobilization of post-silking biomass and nitrogen in both hybrids. The grain nitrogen concentration was increased by HS but decreased by BR application in both hybrids. The harvest index of biomass and nitrogen was increased by HS, and it was improved in YN7 and unaffected in JKN2000 by BR application under HS. In conclusion, BR application at the silking stage can relieve HS injuries on fresh waxy maize yields by improving the remobilization of biomass and nitrogen to grain and increasing the harvest index, especially in the heat-sensitive hybrid. Therefore, foliar BR application is a simple, feasible, efficient practice in fresh waxy maize production and is worth popularizing, especially under warmer climates.
Using the Kaplan–Meier Estimator to Assess the Reliability of Agricultural Machinery
Authors: Durczak Karol , Selech Jarosław , Ekielski Adam , Żelaziński Tomasz , Waleński Marcin , Witaszek Kamil
Published: June 2022

Kaplan–Meier analyses can be used in many disciplines, e.g., agricultural engineering. Agricultural machinery and vehicles can be regarded as objects that ‘die’ because, like living creatures, they failed, although after repair they can be used until scrapped. This article presents an example of using the Kaplan–Meier estimator to plot the reliability function curves of five different models of Zetor farm tractors. The research shows that the median operating time for one of the tested models, which is about 200 engine-operating hours, is 20% lower than for the entire population of analyzed Zetor tractors. This means that the quality of the model, which is very popular in Poland, differs significantly from the other models of this manufacturer. The method cannot be validated, due to a lack of similar functions for other brands of tractors. Progressive automation and digitization of agriculture can contribute to improving the reliability of agriculture work. The user can focus on the correct performance of agrotechnical treatments, and modern control systems will signal in real time, about identified or approaching costly failures.
Evaluation of Citriculture Mechanisation Level in Valencia Region (Spain): Poll Results
Authors: Ortiz Coral , Torregrosa Antonio , Martínez Jose Miguel
Published: June 2022

The increase of the technology level of citrus production operations is required to improve production profitability and reduce production costs. In the framework of the project CITRUSTECH (“Technological advances for modernisation and sustainability in citrus production”), three different poll questionnaires were developed and conducted in the Valencia region to assess the citriculture mechanisation level. In total, 142 questionaries for small and medium-size plantations, 32 for cooperative technicians and 16 for large-size plantations were conducted. From a socioeconomic point of view, clear age and sex inequalities were found. From the technological point of view, relevant differences were found between plantation sizes. The role of the cooperative mechanisation services (custom cost) and other customer services was revealed, with a higher percentage of the area under cultivation at the expense of the small-size plantations. The use of some manual tools was confirmed in pruning, even in large-size orchards. In small-size orchards, the use of backpack sprayers was verified. Regarding farm machinery, besides tractors, hydro-pneumatic sprayers and agricultural shredders were employed. No farm machinery was used during harvesting operations, apart from transport equipment, due to the reduced plantation frames.
A Time to Sow, a Time to Reap: Modifications to Biological and Economic Rhythms in Southwest Asian Plant and Animal Domestication
Authors: Fuks Daniel , Lister Diane L. , Distelfeld Assaf , Marom Nimrod
Published: June 2022

This paper reviews changes to lifecycle temporality in Southwest Asian plant and animal domestication, exploring their relationship to long-term processes associated with ancient and contemporary globalization. We survey changes under domestication to the timing of seed dispersal, germination, vegetative growth, flowering and maturation in wheat and barley and to birth, reproduction, lactation, wool production and death in sheep, goats and cattle. Changes in biological temporality among domesticates are ultimately related to globally increasing production intensity, geographic diffusion, and agricultural diversity associated with cultivar/breed evolution. Recently, however, increasing crop production intensity and geographic diffusion are accompanied by declining agricultural diversity worldwide. Similar processes are apparent in contemporary economic and cultural globalization, suggesting that long-term agricultural developments might be viewed as a subset of globalization. Moreover, the origin of certain features of contemporary globalization may be traced back to the beginnings of plant and animal domestication. Thus, while biologists since Darwin considered domestication as a model for the study of evolution, we suggest that domestication may also offer a model for the study of globalization.
Evaluation of Single-Cropping under Reduced Water Supply in Strawberry Cultivation
Authors: Marcellini Micol , Mazzoni Luca , Raffaelli Davide , Pergolotti Valeria , Balducci Francesca , Capocasa Franco , Mezzetti Bruno
Published: June 2022

Genotype, environment, and cultivation system strongly influence strawberry yield and quality. Specifically, the growth of strawberry plants is dependent on the water supply. Nevertheless, the abuse of water in agriculture is necessitating the choice of the lowest water-consumptive plants. The following study showed the performance of ‘Romina’, ‘Sibilla’, and ‘Cristina’ cultivars, grown in open-field conditions, and treated with three doses of water (W): 100% local standard regime, and 20% (W80) and 40% (W60) reductions. The average amount of water administered for W100, W80, and W60 was 1120 m3 ha−1, 891 m3 ha−1, and 666 m3 ha−1, respectively. The water treatment at W60 negatively affected the plant growth and yield, resulting in reduced plant height, leaf number, leaf length and width, and a minor yield. Instead, fruit quality showed higher values of total soluble solids and titratable acidity. Conversely, plants watered with W80 showed results similar to the control (W100) in terms of development and yield. In conclusion, it is possible to assume that a reduction of water is desirable, guaranteeing economic and environmental gains for farmers.
First Unmanned Aerial Vehicle Observation of Epimeletic Behavior in Indo-Pacific Humpback Dolphins
Authors: Chung Tabris Yik-To , Ho Heysen Hei-Nam , Tsui Henry Chun-Lok , Kot Brian Chin-Wing
Published: June 2022

Epimeletic behavior has been reported in various species of cetaceans and sometimes in wild populations during vessel-based surveys. Epimeletic behavior in cetaceans involves complex social interactions which have been described using observational and acoustic studies. The recent advances in unmanned aerial vehicle (UAV) technology allowed its application in wildlife research and frequently in cetaceans in conjunction with vessel-based surveys. This article is the first report of intraspecific epimeletic behavior of Indo-Pacific humpback dolphins (Sousa chinensis) in Hong Kong waters using a combination of UAV- and vessel-based photography. Using both techniques, we were able to observe and qualitative analyze the individual body condition, group behavior, and swimming pattern during the epimeletic event. This study highlighted that UAVs can be used to observe the complex social behaviors and interactions of cetaceans from the aerial angle while keeping a minimal level of disturbance to the animals. Aerial footage can also be quantitatively analyzed to provide further insights on the group behaviors of cetaceans. The application allows efficient assessment of health, behavior, and ecology of wild animals, offering valuable opportunities for researchers working on free-ranging populations.
Using Pruning-Based YOLOv3 Deep Learning Algorithm for Accurate Detection of Sheep Face
Authors: Song Shuang , Liu Tonghai , Wang Hai , Hasi Bagen , Yuan Chuangchuang , Gao Fangyu , Shi Hongxiao
Published: June 2022

Accurate identification of sheep is important for achieving precise animal management and welfare farming in large farms. In this study, a sheep face detection method based on YOLOv3 model pruning is proposed, abbreviated as YOLOv3-P in the text. The method is used to identify sheep in pastures, reduce stress and achieve welfare farming. Specifically, in this study, we chose to collect Sunit sheep face images from a certain pasture in Xilin Gol League Sunit Right Banner, Inner Mongolia, and used YOLOv3, YOLOv4, Faster R-CNN, SSD and other classical target recognition algorithms to train and compare the recognition results, respectively. Ultimately, the choice was made to optimize YOLOv3. The mAP was increased from 95.3% to 96.4% by clustering the anchor frames in YOLOv3 using the sheep face dataset. The mAP of the compressed model was also increased from 96.4% to 97.2%. The model size was also reduced to 1/4 times the size of the original model. In addition, we restructured the original dataset and performed a 10-fold cross-validation experiment with a value of 96.84% for mAP. The results show that clustering the anchor boxes and compressing the model using this dataset is an effective method for identifying sheep. The method is characterized by low memory requirement, high-recognition accuracy and fast recognition speed, which can accurately identify sheep and has important applications in precision animal management and welfare farming.
Anti-Inflammatory and Anti-Acne Effects of Hamamelis virginiana Bark in Human Keratinocytes
Authors: Piazza Stefano , Martinelli Giulia , Vrhovsek Urska , Masuero Domenico , Fumagalli Marco , Magnavacca Andrea , Pozzoli Carola , Canilli Luisa , Terno Massimo , Angarano Marco , Dell’Agli Mario , Sangiovanni Enrico
Published: June 2022

Cutibacterium acnes (C. acnes) is recognized as one of the main triggers of the cutaneous inflammatory response in acne vulgaris, a chronic skin disorder with a multifactorial origin. Witch hazel (Hamamelis virginiana L.) is a plant widely used for skin inflammatory conditions, with some preliminary anti-inflammatory evidence on the skin, but lacking data on acne conditions. This study aimed to evaluate the effect of a glycolic extract from Hamamelis virginiana bark (HVE) versus C. acnes-induced inflammation in human keratinocytes (HaCaT). Phytochemical investigations of HVE identified hamamelitannin (HT) and proanthocyanidins as the most abundant compounds (respectively, 0.29% and 0.30% w/wextract). HVE inhibited C. acnes-induced IL-6 release (IC50: 136.90 μg/mL), by partially impairing NF-κB activation; however, no antibacterial or antibiofilm activities were found. In addition, HVE showed greater anti-inflammatory activity when TNF-α was used as a proinflammatory stimulus (IC50 of 38.93 μg/mL for IL-8 release), partially acting by antioxidant mechanisms, as shown for VEGF inhibition. The effects of HVE are primarily based on the proanthocyanidin content, as HT was found inactive on all the parameters tested. These results suggest further investigations of HVE in other inflammatory-based skin diseases.
Diabetes Aggravates Photoreceptor Pathologies in a Mouse Model for Ocular Vitamin A Deficiency
Authors: Ramkumar Srinivasagan , Parmar Vipul M. , Moon Jean , Lee Chieh , Taylor Patricia R. , von Lintig Johannes
Published: June 2022

Emerging evidence indicates that diabetes disturbs photoreceptor function and vitamin A homeostasis. However, the biochemical basis of this phenotype is not well established. Here, we compared the effects of streptozotocin-induced diabetes in wild-type (WT) mice and Stra6-/- mice, a mouse model for ocular vitamin A deficiency. After 8 weeks, diabetes increased serum retinyl esters in mice of both genotypes. The eyes of diabetic WT mice displayed increased superoxide levels but no changes in retinoid concentrations. Diabetic Stra6-/- mice showed increased ocular retinoid concentrations, but superoxide levels remained unchanged. After 30 weeks, significant alterations in liver and fat retinoid concentrations were observed in diabetic mice. Diabetic WT mice exhibited a decreased expression of visual cycle proteins and a thinning of the photoreceptor layer. Stra6-/- mice displayed significantly lower ocular retinoid concentration than WT mice. An altered retinal morphology and a reduced expression of photoreceptor marker genes paralleled these biochemical changes and were more pronounced in the diabetic animals. Taken together, we observed that diabetes altered vitamin A homeostasis in several organ systems and aggravated photoreceptor pathologies in the vitamin-deficient mouse eyes.
The Current Status, Bioactivity, Food, and Pharmaceutical Approaches of Calocybe indica: A Review
Authors: Shashikant Meghna , Bains Aarti , Chawla Prince , Fogarasi Melinda , Fogarasi Szabolcs
Published: June 2022

Over the past few years, mushrooms have been extensively explored in the field of pharmaceutical and food science, and researchers are heading toward the search for vital components with a higher safety margin and multitarget applications. Moreover, among all age group populations, mushroom consumption has increased immensely owing to their great nutritional aspects, desirable organoleptic properties, and aroma. In addition, mushrooms continue to generate much attention chiefly in their consumption as food, as a cure for different ailments, as well as a vital commodity globally, owing to their dietary, antioxidant, and therapeutic values. Mushrooms are considered one of the important and suitable diets for patients having multiple types of diseases. Additionally, due to potential immunomodulatory effects, quality protein, and low fat, and cholesterol content, mushrooms are used as an important ingredient for food formulation. Therefore, this review article provides detailed information on Calocybe indica as they are the third most important commercially grown mushroom following button and oyster mushrooms. This review brings tangible evidence that milky white mushrooms are a great source of natural components and antioxidants with potential application in pharmaceuticals and in treating and managing different diseases. Several food applications of milky white mushrooms have also been discussed and reviewed.
Development of the Dynamic Stiffness Method for the Out-of-Plane Natural Vibration of an Orthotropic Plate
Authors: Chauhan Manish , Mishra Pawan , Dwivedi Sarvagya , Ragulskis Minvydas , Burdzik Rafał , Ranjan Vinayak
Published: June 2022

In this present paper, the dynamic stiffness method (DSM) was formulated to investigate the out-of-plane natural vibration of a thin orthotropic plate using the classical plate theory (CPT). Hamilton’s principle was implemented to derive the governing differential equation of motion for free vibration of the orthotropic plate for Levy-type boundary conditions. The Wittrick–Williams (W–W) algorithm was used as a solution technique to compute the natural frequencies of a thin orthotropic plate for different boundary conditions, aspect ratios, thickness ratios, and modulus ratios. The obtained results are compared with the results by the finite element method using commercial software (ANSYS and those available) in the published literature. The presented results by the dynamic stiffness method can be used as a benchmark solution to compare the natural frequencies of orthotropic plates.
Investigation of the Heat Transfer and Pressure Drop in Tubes with Transverse Ribs of Zigzag Configurations
Authors: Ahmed Mohamed H.
Published: June 2022

Heat transfer through tube walls can be promoted using a ribbed tube configuration. Most of the ribs used in previous reports have equal height along the tube length. In this numerical study, we investigate the heat transfer and pressure drop in a transverse ribbed tube where ribs of unequal heights are mounted such that the tops of the ribs form a zigzag shape. Four configurations were studied. Each configuration had a set of two neighboring ribs of different heights. The set was repeated along the tube length to form a zigzag shape. The rib height ratios, e2/e1, of the four sets were 0.25, 0.5, 0.75, and 1.0. The ratios of the height of the taller rib, pitch, and width to the tube diameter were kept constant at values of e1/d = 0.1, p/d = 1.0, and w/d = 0.05, respectively. The Reynolds number ranged from 10,000 to 60,000, while the Prandtl number ranged from 0.71 to 7.0. The results from the k-ε and k-ω models were first validated and compared with the experimental results of smooth and ribbed tubes. The two models showed comparable results, with the k-ε showing slightly better performance and was thus selected to perform the current study. It was found that the average Nusselt number increases along with increases in the rib height ratio, Prandtl number, and Reynolds number. The friction factor changed exponentially with the rib height ratio, while the Reynolds number showed a minor effect. At the same pumping power, a maximum thermal performance enhancement of approximately 8% was achieved at rib height ratios of 0.25 and 0.5. The rib height ratio of 0.5 has an advantage over that of 0.25 as it has a higher average Nusselt number. Two correlations were introduced to estimate the Nusselt number and friction factor for the current ribbed tube of zigzag configurations.
Pavement Distress Detection Using Three-Dimension Ground Penetrating Radar and Deep Learning
Authors: Yang Jiangang , Ruan Kaiguo , Gao Jie , Yang Shenggang , Zhang Lichao
Published: June 2022

Three-dimensional ground penetrating radar (3D GPR) is a non-destructive examination technology for pavement distress detection, for which its horizontal plane images provide a unique perspective for the task. However, a 3D GPR collects thousands of horizontal plane images per kilometer of the investigated pavement. The existing detection methods using GPR images are time-consuming and risky for subjective judgment. To solve the problem, this study used deep learning methods and 3D GPR horizontal plane images to detect pavement structural distress, including cracks, repairs, voids, poor interlayer bonding, and mixture segregation. In this study, two deep learning methods, called CP-YOLOX and SViT, were used to achieve the aim. A dataset for anomalous waveform localization (3688 images) was first created by pre-processing 3D-GPR horizontal plane images. A CP-YOLOX model was then trained to localize anomalous waveforms. Five SViT models with different numbers of encoders were adopted to perform the classification of anomalous waveforms using the localization results from the CP-YOLOX model. The numerical experiment results showed that 3D GPR horizontal plane images have the potential to be an assistant for pavement structural distress detection. The CP-YOLOX model achieved 87.71% precision, 80.64% mAP, and 33.57 sheets/s detection speed in locating anomalous waveforms. The optimal SViT achieved 63.63%, 68.12%, and 75.57% classification accuracies for the 5-category, 4-category, and 3-category datasets, respectively. The proposed models outperformed other deep learning methods on distress detection using 3D GPR horizontal plane images. In the future, more radar images should be collected to improve the accuracy of SViT.
3D Tiled Code Generation for Nussinov’s Algorithm
Authors: Bielecki Włodzimierz , Błaszyński Piotr , Pałkowski Marek
Published: June 2022

Current state-of-the-art parallel codes used to calculate the maximum number of pairs for a given RNA sequence by means of Nussinov’s algorithm do not allow for achieving speedup close up to the number of the processors used for execution of those codes on multi-core computers. This is due to the fact that known codes do not make full use of and derive benefit from cache memory of such computers. There is a need to develop new approaches allowing for increasing cache exploitation in multi-core computers. One of such possibilities is increasing the dimension of tiles in generated target tiled code and assuring a similar size of generated tiles. The article presents an approach allowing us to produce 3D parallel code with tiling calculating Nussinov’s RNA folding, i.e., code with the maximal tile dimension possible for the loop nest, executing Nussinov’s algorithm. The approach guarantees that generated tiles are of a similar size. The code generated with the presented approach is characterized by increased code locality and outperforms all closely related ones examined by us. This allows us to considerably reduce execution time required for computing the maximum number of pairs of any nested structure for larger RNA sequences by means of Nussinov’s algorithm.
A Simulation Method of Two-Dimensional Sea-Surface Current Field for Trajectory Crossing Spaceborne SAR
Authors: Li Yan , Chong Jinsong , Li Zongze
Published: June 2022

The trajectory-crossing method is an important and effective method for spaceborne SAR (synthetic aperture radar) to detect a two-dimensional current field. However, in practical applications, there are few spaceborne SAR data that meet the requirements of close acquisition time and overlapping trajectories, which makes it difficult to comprehensively analyze the impact of different systems and environmental parameters on current measurement results from real data processing. With the proposal of a SAR constellation plan in the future, the data resources will be constantly enriched, and the trajectory-crossing method will be widely used. It is, thus, necessary to lay some theoretical foundation at present. A two-dimensional sea-surface-current-field simulation method for trajectory crossing spaceborne SAR is proposed in this paper. Based on the principles of the trajectory-crossing method, the proposed method can realize the simulation of two-dimensional sea-surface-current field under given spaceborne SAR system and environmental parameters. In this paper, the simulation process of this method is given, and the simulation experiment is performed. Compared with the current measurement results of SAR data, the simulation experiment shows that the current velocity error is less than 0.03 m/s and the direction error is less than 10 degrees, which proves the reliability of the proposed simulation method. The proposed method lays a foundation for analyzing the influence of various parameters in the application of the trajectory-crossing method.
The Chloroform Extracts of Vietnamese Sophora flavescens Ait. Inhibit the Proliferation of HepG2 Cells through Apoptosis Induction
Authors: Trang Cao Ngoc Minh , Chi Ho Nguyen Quynh , Manh Nguyen Khac , Son Hoang Nghia , Ngo Dai-Nghiep , Long Le Thanh
Published: June 2022

The present study evaluated the effects of Sophora flavescens Ait. root extract on the proliferation of human hepatoma cell line HepG2. HPLC-UV analysis showed that the highest matrine and oxymatrine contents were obtained in the chloroform extract, compared to ethanol extract and ethyl acetate extract. The morphological analysis revealed that the chloroform extract of Sophora flavescens Ait. (SFA-CHCl3 extract) induced alterations of HepG2 cell morphology, resulting in the shrinkage of cells, the formation of debris, and cell detachment. The proliferation of HepG2 cells was inhibited by SFA-CHCl3 extract treatment. Cell cycle analysis exhibited that the cell proportion of the G0/G1 phase of HepG2 cells with SFA-CHCl3 extract treatment was decreased, while the cell proportion of the G2/M phase was increased. Flow cytometry analysis indicated a dramatic increase in the apoptotic percentage of HepG2 cells over the time of SFA-CHCl3 extract treatment. The SFA-CHCl3 extract also caused morphological changes in HepG2 nuclear, including chromatin condensation and DNA fragmentation. SFA-CHCl3 extract treatment induced the bax up-regulation and the bcl-2 down-regulation in HepG2 cells. These results revealed that SFA-CHCl3 extract could be a potential apoptosis inducer in HepG2 cells.
Analysis and Ranking of IT Risk Factors Using Fuzzy TOPSIS-Based Approach
Authors: Alshahrani Haya Mesfer , Alotaibi Saud S. , Ansari Md Tarique Jamal , Asiri Mashael M. , Agrawal Alka , Khan Raees Ahmad , Mohsen Heba , Hilal Anwer Mustafa
Published: June 2022

In today’s age of information and communication technology (ICT), many companies are using advanced digital technologies as well as the application of information technology to grow the company and effectively manage their processes. The risk management of information technology plays a crucial role in protecting the important information and data assets of an enterprise. The key objective of risk management in information technology is to safeguard the digital infrastructure from ICT-related harm. An efficient as well as cost effective risk managing mechanism is an integral aspect of an extensive safety system for information technology. A successful approach to IT risk management would strive to protect the company and its infrastructure, not just its digital assets, to conduct their process. Subsequently, the risk managing mechanism must not be viewed solely for instance as a procedural task performed by the IT specialists who run and administer the IT program but as the organization’s critical management task. The risks of information technology assets are of a dynamic nature; different strategies tackle the management of information security risk. This research paper is intended to review and discuss information technology risk managing procedures. We also carried out a multi-criteria decision-making (MCDM)-based empirical investigation to analyses and prioritized different IT risk factors. This has recognized that there are many reports on the techniques, and that various approaches to risk management exist.
Thermoelastic Analysis in Poro-Elastic Materials Using a TPL Model
Authors: Hobiny Aatef , Abbas Ibrahim , Alshehri Hashim , Vlase Sorin , Marin Marin
Published: June 2022

The main aim of the paper is to study the impact of delay times in a poro-elastic medium using the finite element approach and the three-phase lag thermo-elastic theory. The governing equations were obtained for a three-phase lag model with six delay times. Consideration was given to a one-dimensional application of a poro-elastic half-space. Because of the complex form of the basic equations, the finite element approach was used to solve this problem. Asymmetric and symmetric tensors were used to represent all of the physical quantities. The numerical results were presented in graphical form. The effects of porosity and delays were introduced. Finally, the results were plotted to show the difference between the three-phase delay (TPL) and the Green−Naghdi with and without energy dissipation (GNIII) models.
The Role of Verbal Feedback in the Motor Learning of Gymnastic Skills: A Systematic Review
Authors: Starzak Marcin , Biegajło Michał , Nogal Marta , Niźnikowski Tomasz , Ambroży Tadeusz , Rydzik Łukasz , Jaszczur-Nowicki Jarosław
Published: June 2022

The main purpose of this study was to systematically review the effects of feedback on motor skill acquisition in gymnastic skills. A systematic literature search was conducted in the electronic databases MEDLINE (EBSCO), Scopus, SPORTDiscus (EBSCO), and Web of Science. Of the initial 743 search articles, 13 studies were included in the quantitative analysis. Studies were included if they met the following criteria: (a) healthy subjects, (b) studies with gymnastic, artistic gymnastic, or trampoline elements in the study protocol, (c) verbal feedback intervention, (d) the study compared verbal feedback intervention with other forms of feedback, instructional intervention, or with a control intervention, and (e) task performance evaluation. Methodological quality was identified using the PEDro scale. Combining verbal instructions with different forms of feedback is beneficial when learning complex gymnastic skills. Verbal feedback may be useful to improve the technical performance of a gymnastic element; in particular, information regarding the errors committed in a key element of the performance seems to be effective in the motor learning process.
Combining Sun-Photometer, PM Monitor and SMPS to Inverse the Missing Columnar AVSD and Analyze Its Characteristics in Central China
Authors: Miao Ao , Jin Shikuan , Ma Yingying , Liu Boming , Jiang Nan , He Wenzhuo , Qian Xiaokun , Zheng Yifan
Published: June 2022

Columnar aerosol volume size distribution (AVSD) is an important atmospheric parameter that shows aerosol microphysical properties and can be used to analyze the impact of aerosols on the radiation budget balance, as well as regional climate effects. Usually, columnar AVSD can be obtained by using a sun photometer, but its observation conditions are relatively strict, and the columnar AVSD will be missing in cloudy or hazy weather due to cloud cover and other factors. This study introduces a novel algorithm for inversion of missing columnar AVSD under haze periods by using a machine learning approach and other ground-based observations. The principle is as follows. We are based on joint observational experiments. Since the scanning mobility particle sizer (SMPS) and particulate matter (PM) monitor sample the surface data, they can be stitched together to obtain the surface AVSD according to their observation range. Additionally, the sun-photometer scans the whole sky, so it can obtain columnar AVSD and aerosol optical depth (AOD). Then we use the back propagation neural network (BPNN) model to establish the relationship between the surface AVSD and the columnar AVSD and add AOD as a constraint. Next, the model is trained with the observation data of the same period. After the model training is completed, the surface AVSD and AOD can be used to invert the missing columnar AVSD during the haze period. In experiments on the 2015 dataset, the results show that the correlation coefficient and root mean square error between our model inversion results and the original sun photometer observations were 0.967 and 0.008 in winter, 0.968 and 0.010 in spring, 0.969 and 0.013 in summer, 0.972 and 0.007 in autumn, respectively. It shows a generally good performance that can be applied to the four seasons. Furthermore, the method was applied to fill the missing columnar AVSD of Wuhan, a city in central China, under adverse weather conditions. The final results were shown to be consistent with the climatic characteristics of Wuhan. Therefore, it can indeed solve the problem that sun photometer observations are heavily dependent on weather conditions, contributing to a more comprehensive study of the effects of aerosols on climate and radiation balance.
Inclusion of Electron Interactions by Rate Equations in Chemical Models
Authors: Campbell Laurence , Muccignat Dale L. , Brunger Michael J.
Published: June 2022

The concept of treating subranges of the electron energy spectrum as species in chemical models is investigated. This is intended to facilitate simple modification of chemical models by incorporating the electron interactions as additional rate equations. It is anticipated that this embedding of fine details of the energy dependence of the electron interactions into rate equations will yield an improvement in computational efficiency compared to other methods. It will be applicable in situations where the electron density is low enough that the electron interactions with chemical species are significant compared to electron–electron interactions. A target application is the simulation of electron processes in the D-region of the Earth’s atmosphere, but it is anticipated that the method would be useful in other areas, including enhancement of Monte Carlo simulation of electron–liquid interactions and simulations of chemical reactions and radical generation induced by electrons and positrons in biomolecular systems. The aim here is to investigate the accuracy and practicality of the method. In particular, energy must be conserved, while the number of subranges should be small to reduce computation time and their distribution should be logarithmic in order to represent processes over a wide range of electron energies. The method is applied here to the interaction by inelastic and superelastic collisions of electrons with a gas of molecules with only one excited vibrational level. While this is unphysical, it allows the method to be validated by checking for accuracy, energy conservation, maintenance of equilibrium and evolution of a Maxwellian electron spectrum.
Robust Spectral Clustering Incorporating Statistical Sub-Graph Affinity Model
Authors: Lin Zhenxian , Wang Jiagang , Wu Chengmao
Published: June 2022

Hyperspectral image (HSI) clustering is a challenging work due to its high complexity. Subspace clustering has been proven to successfully excavate the intrinsic relationships between data points, while traditional subspace clustering methods ignore the inherent structural information between data points. This study uses graph convolutional subspace clustering (GCSC) for robust HSI clustering. The model remaps the self-expression of the data to non-Euclidean domains, which can generate a robust graph embedding dictionary. The EKGCSC model can achieve a globally optimal closed-form solution by using a subspace clustering model with the Frobenius norm and a Gaussian kernel function, making it easier to implement, train, and apply. However, the presence of noise can have a noteworthy negative impact on the segmentation performance. To diminish the impact of image noise, the concept of sub-graph affinity is introduced, where each node in the primary graph is modeled as a sub-graph describing the neighborhood around the node. A statistical sub-graph affinity matrix is then constructed based on the statistical relationships between sub-graphs of connected nodes in the primary graph, thus counteracting the uncertainty image noise by using more information. The model used in this work was named statistical sub-graph affinity kernel graph convolutional subspace clustering (SSAKGCSC). Experiment results on Salinas, Indian Pines, Pavia Center, and Pavia University data sets showed that the SSAKGCSC model can achieve improved segmentation performance and better noise resistance ability.
Nonoscillation and Oscillation Criteria for a Class of Second-Order Nonlinear Neutral Delay Differential Equations with Positive and Negative Coefficients
Authors: Guo Rongrong , Huang Qingdao , Tian Haifeng
Published: June 2022

In this paper, we investigate some nonoscillatory and oscillatory solutions for a class of second-order nonlinear neutral delay differential equations with positive and negative coefficients. By means of the method of contraction mapping principle and some integral inequality techniques, we extend the recent results provided in the literature.
Decision-Making Using Big Data Relevant to Sustainable Development Goals (SDGs)
Authors: Fattahi Saman , Ura Sharifu , Noor-E-Alam Md.
Published: June 2022

Policymakers, practitioners, and researchers around the globe have been acting in a coordinated manner, yet remaining independent, to achieve the seventeen Sustainable Development Goals (SDGs) defined by the United Nations. Remarkably, SDG-centric activities have manifested a huge information silo known as big data. In most cases, a relevant subset of big data is visualized using several two-dimensional plots. These plots are then used to decide a course of action for achieving the relevant SDGs, and the whole process remains rather informal. Consequently, the question of how to make a formal decision using big data-generated two-dimensional plots is a critical one. This article fills this gap by presenting a novel decision-making approach (method and tool). The approach formally makes decisions where the decision-relevant information is two-dimensional plots rather than numerical data. The efficacy of the proposed approach is demonstrated by conducting two case studies relevant to SDG 12 (responsible consumption and production). The first case study confirms whether or not the proposed decision-making approach produces reliable results. In this case study, datasets of wooden and polymeric materials regarding two eco-indicators (CO2 footprint and water usage) are represented using two two-dimensional plots. The plots show that wooden and polymeric materials are indifferent in water usage, whereas wooden materials are better than polymeric materials in terms of CO2 footprint. The proposed decision-making approach correctly captures this fact and correctly ranks the materials. For the other case study, three materials (mild steel, aluminum alloys, and magnesium alloys) are ranked using six criteria (strength, modulus of elasticity, cost, density, CO2 footprint, and water usage) and their relative weights. The datasets relevant to the six criteria are made available using three two-dimensional plots. The plots show the relative positions of mild steel, aluminum alloys, and magnesium alloys. The proposed decision-making approach correctly captures the decision-relevant information of these three plots and correctly ranks the materials. Thus, the outcomes of this article can help those who wish to develop pragmatic decision support systems leveraging the capacity of big data in fulfilling SDGs.
ITRAQ-Based Proteomic Analysis of Wheat (Triticum aestivum) Spikes in Response to Tilletia controversa Kühn and Tilletia foetida Kühn Infection, Causal Organisms of Dwarf Bunt and Common Bunt of Wheat
Authors: He Ting , Xu Tongshuo , Muhae-Ud-Din Ghulam , Guo Qingyun , Liu Taiguo , Chen Wanquan , Gao Li
Published: June 2022

Dwarf bunt and common bunt diseases of wheat are caused by Tilletia controversa Kühn and Tilletia foetida Kühn, respectively, and losses caused by these diseases can reach 70–80% in favourable conditions. T. controversa and T. foetida are fungal pathogens belonging to the Exobasidiomycetes within the basidiomycetous smut fungi (Ustilaginomycotina). In order to illuminate the proteomics differences of wheat spikes after the infection of T. controversa and T. foetida, the isobaric tags for relative and absolute quantification (iTRAQ) technique was used for better clarification. A total of 4553 proteins were differentially detected after T. controversa infection; 4100 were upregulated, and 453 were downregulated. After T. foetida infection, 804 differentially expressed proteins were detected; 447 were upregulated and 357 were downregulated. In-depth data analysis revealed that 44, 50 and 82 proteins after T. controversa and 9, 6 and 16 proteins after T. foetida were differentially expressed, which are antioxidant, plant-pathogen interaction and glutathione proteins, respectively, and 9 proteins showed results consistent with PRM. The top 20 KEGG enrichment pathways were identified after pathogen infection. On the basis of gene ontology, the upregulated proteins were linked with metabolic process, catalytic activity, transferase activity, photosynthetic membrane, extracellular region and oxidoreductase activity. The results expanded our understanding of the proteome in wheat spikes in response to T. controversa and T. foetida infection and provide a basis for further investigation for improving the defense mechanism of the wheat crops.
Isolation, Identification and Hyperparasitism of a Novel Cladosporium cladosporioides Isolate Hyperparasitic to Puccinia striiformis f. sp. tritici, the Wheat Stripe Rust Pathogen
Authors: Zhang Hongjuan , He Mengying , Fan Xin , Dai Lu , Zhang Shan , Hu Zeyu , Wang Ning
Published: June 2022

Wheat rust outbreaks have caused significantly economic losses all over the world. Puccinia striiformis f. sp. tritici (Pst) is an obligate biotrophic fungus causing stripe rust on wheat. Application of fungicides may cause environmental problems. The effects of hyperparasites on plant pathogens are the basis for biological control of plant pathogenic fungi and parasites of Pst have great value in biological agents development. Here, we report the isolation and characterization of isolate of Cladosporium cladosporioides from Pst based on morphological characterization and analysis of molecular markers. The hyperparasitic isolate was isolated from taupe-colored uredinia of Pst. Upon artificial inoculation, the hyperparasitic isolate was able to reduce the production and germination rate of Pst urediospores, and Pst uredinia changed color from yellow to taupe. Scanning electron microscopy demonstrated that the strain could efficiently colonize Pst urediospores. Therefore, the isolate has the potential to be developed into a biological control agent for managing wheat stripe rust.
Recent Insight into Lipid Binding and Lipid Modulation of Pentameric Ligand-Gated Ion Channels
Authors: Ananchenko Anna , Hussein Toka O. K. , Mody Deepansh , Thompson Mackenzie J. , Baenziger John E.
Published: June 2022

Pentameric ligand-gated ion channels (pLGICs) play a leading role in synaptic communication, are implicated in a variety of neurological processes, and are important targets for the treatment of neurological and neuromuscular disorders. Endogenous lipids and lipophilic compounds are potent modulators of pLGIC function and may help shape synaptic communication. Increasing structural and biophysical data reveal sites for lipid binding to pLGICs. Here, we update our evolving understanding of pLGIC–lipid interactions highlighting newly identified modes of lipid binding along with the mechanistic understanding derived from the new structural data.