bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Environmental Stresses (Heat, Salt, Waterlogging) on Grain Yield and Associated Traits of Wheat under Application of Sulfur-Coated Urea
Authors: Altaf Adil , Zhu Xinkai , Zhu Min , Quan Ma , Irshad Sana , Xu Dongyi , Aleem Muhammad , Zhang Xinbo , Gull Sadia , Li Fujian , Shah Amir Zaman , Zada Ahmad
Published: November 2021

Abiotic stresses, such as heat, salt, waterlogging, and multiple-stress environments have significantly reduced wheat production in recent decades. There is a need to use effective strategies for overcoming crop losses due to these abiotic stresses. Fertilizer-based approaches are readily available and can be managed in all farming communities. This research revealed the effects of sulfur-coated urea (SCU, 130 kg ha−1, release time of 120 days) on wheat crops under heat, salt, waterlogging, and combined-stress climatic conditions. The research was done using a completely randomized design with three replicates. The results revealed that SCU at a rate of 130 kg of N ha−1 showed a significantly (p ≤ 0.05) high SPAD value (55) in the case of waterlogging stress, while it was the lowest (31) in the case of heat stress; the control had a SPAD value of 58. Stress application significantly (p ≤ 0.05) reduced the leaf area and was the highest in control (1898 cm2), followed by salt stress (1509 cm2), waterlogging (1478 cm2), and heat stress (1298 cm2). A significantly (p ≤ 0.05) lowest crop yield was observed in the case of heat stress (3623.47 kg ha−1) among all stresses, while it was 10,270 kg ha−1 in control and was reduced up to 35% after the application of heat stress. Among all stresses, the salt stress showed the highest crop yield of 5473.16 kg ha−1. A significant correlation was observed among growth rate, spike length, yield, and physiological constraints with N content in the soil. The SCU fertilizer was the least effective against heat stress but could tolerate salt stress in wheat plants. The findings suggested the feasibility of adding SCU as an alternative to normal urea to alleviate salt stresses and improve wheat crop growth and yield traits. For heat stress tolerance, the applicability of SCU with a longer release period of ~180 days is recommended as a future prospect for study.
Interactive Impact of Biochar and Arbuscular Mycorrhizal on Root Morphology, Physiological Properties of Fenugreek (Trigonella foenum-graecum L.) and Soil Enzymatic Activities
Authors: Jabborova Dilfuza , Annapurna Kannepalli , Choudhary Ravish , Bhowmik Subrata Nath , Desouky Said E. , Selim Samy , Azab Islam H. El , Hamada Maha M. A. , Nahhas Nihal El , Elkelish Amr
Published: November 2021

Arbuscular mycorrhizal fungi (AMF) inoculation and biochar amendment has been reported to improve the growth of several crop plant; however, their role in stress amelioration individually as well as in combination has not been worked out. Limited information is available about the synergistic use of biochar and Arbuscular Mycorrhizal Fungi (AMF). Here, we investigated the synergistic effect of biochar and AMF on plant development, root architecture, the physiological performance of fenugreek (Trigonella foenum-graecum), and soil enzymatic activities. Biochar and AMF were shown to have a considerable effect on plant height, according to the data (53.3 and 66.6%, respectively), leaf number (22.5 and 45.1%), total root length (19.8 and 40.1%), root volume (32.1 and 71.4%), chlorophyll a content (26.0 and 17.8%), chlorophyll b content (50.0 and 28.9%), total chlorophyll content (30.0 and 18.1%), and carotenoid content (60.0 and 48.0%) over the control treatment. There was a considerable increase in plant height when biochar and AMF were combined together by 80.9%, total root length by 68.9%, projected area by 48.7%, root surface area by 34.4%, root volume by 78.5%, chlorophyll a content by 34.2%, chlorophyll b content by 68.4%, total chlorophyll content by 44.5%, and carotenoid content by 84.0% compared to the control. Our results recommend that the combination of biochar and AMF is advantageous in fenugreek growth, microbial biomass, and soil enzyme activities.
Larvicidal Activity of Geranylacetone Derivatives against Culex quinquefasciatus Larvae and Investigation of Environmental Toxicity and Non-Target Aquatic Species
Authors: Al-Zharani Mohammed , Al-Eissa Mohammed S. , Rudayni Hassan A. , Ali Daoud , Alarifi Saud , Surendrakumar Radhakrishnan , Idhayadhulla Akbar
Published: November 2021

A grindstone method based on Mannich condensation was used to synthesize geranylacetone derivatives (1a–1f). The method showed a high yield under milder reaction conditions. Analyses of the synthesized compounds were carried out by FTIR, 1H, 13C NMR, mass spectrometry, and elemental analysis. We synthesized and evaluated the larvicidal and ichthyotoxic activities of six compounds (1a–1f) in this study. Compound 1f (5,9-dimethyl-1-phenyl-3-(2-(3-phenylallylidene)hydrazinyl)deca-4,8-dien-1-one) was more active (LD50: 14.1 µg/mL) against the second instar larvae of Culex quinquefasciatus than geranylacetone (67.2 µg/mL), whereas the former caused 13.9% mortality at 100 µg/mL. Geranylacetone, in an antifeedant screening test, showed 53.1% against Oreochromis mossambicus within 24 h. The compound 1f showed high larvicidal activity against C. quinquefasciatus and was non-toxic to non-target aquatic species.
The Multiple Activities and the Plant Beneficial Potential of Bacillus spp. Derived from the Permafrost of Western Siberia
Authors: Domanskaya Olga V. , Bome Nina A. , Iashnikov Aleksandr V. , Vasilchenko Anastasia V. , Vasilchenko Alexey S.
Published: November 2021

Agents of biological control are an important part of traditional agriculture, as well as organic farming. However, in the climatic conditions of countries that are located in cold and temperate regions, plant protection requires particular biocontrol agents that have adapted to environments with low and unstable temperatures. This work presents the biocontrol potential and plant-promoting activity of Bacillus spp. that was isolated from permafrost sediments in Western Siberia. It was found that all of the studied strains (n = 10) were able to produce indole-3-acetic acid (IAA) and chitinolytic enzymes at low positive temperatures (5 °C). The antifungal activity of cold-tolerant bacilli against Microdochium sp., Fusarium spp., and Alternaria sp was recorded. In greenhouse and field conditions, the selected strains (B. simplex 948P-1 (IAA-producing) and B. megaterium 312 (with antifungal activity)) were assessed in comparison to a commercially available fungicide (tebuconazole) and biofungicide (B.subtilis 26D). It was found that the bacilli in the seed germination assay exhibited low phytotoxicity and there was no significant advantage over the conventional fungicides in the yield stimulation assay. However, the twin consortia of B. megaterium 312 and B. simplex 948P-1 was able to increase winter wheat yields by 50% (compared to the untreated group), and by 70% (compared to the commercial biofungicide-treated group). Moreover, applying the twin consortia of Bacillus spp. significantly reduced the infection rate of Fusarium spp. in first-generation wheat grain.
It Keeps the Good Boy Healthy from Nose to Tail: Understanding Pet Food Attribute Preferences of US Consumers
Authors: Rombach Meike , Dean David L.
Published: November 2021

The study provides insights for marketing managers in specialized pet supplies retailers, as well as for vets and animal welfare organizations. This study proposes a model that investigates the importance pet owners place on convenience, natural ingredients, and value and health claims as product attributes. For this purpose, an online survey with a sample size of 206 pet-owning US residents was conducted. Partial least squares structural equation modelling shows that pet food purchase involvement positively impacts subjective and objective knowledge about pet food. Subjective knowledge appears to be the strongest factor impacting the importance consumers place on all three attributes. This is followed by objective knowledge. Socio-demographic factors such as gender, age, income, and education appear to have a limited impact as predictors for the importance consumers place on the product attributes.
A Case Series Analysis of Dental Extractions’ Outcome in Cats with Chronic Gingivostomatitis Carrying Retroviral Disease
Authors: Silva Marta , Fernandes Marta , Fialho Mónica , Mestrinho Lisa
Published: November 2021

This study aims to evaluate and compare the clinical outcome after dental extractions of cats with FCGS infected with feline immunodeficiency virus (FIV) and feline leukaemia virus (FeLV). A retrospective case series included cats with diagnosis of FCGS, availability of detailed clinical records, full-mouth dental radiographs, and retroviral disease test results. Effectiveness of surgical treatment (EOT) was registered. Three groups were defined: control, FIV and FeLV. In this study, 111 cats were included: 60 controls, 29 FIV- and 22 FeLV-positive cats. When compared with control cases, FeLV-positive cats had significantly less proliferative stomatitis lesions, and they tended to have more lingual ulcers. Concurrently, FeLV-positive cats had significantly less tooth resorptive lesions. No other significant differences in FCGS clinical signs were found between groups. FeLV-positive cats had a significantly worse outcome after dental extractions compared to the other groups. In fact, FeLV-positive cats had 7.5 times more chances of having no improvement after dental extractions. This study concludes that the response to dental extractions in FeLV-positive cats is significantly worse, when comparing to cats that do not carry retroviral disease. Therefore, it is important to acknowledge the effect of FeLV status on the prognosis of these cats.
Causes of Death in Stray Cat Colonies of Milan: A Five-Year Report
Authors: Grieco Valeria , Crepaldi Paola , Giudice Chiara , Roccabianca Paola , Sironi Giuseppe , Brambilla Eleonora , Magistrelli Sonia , Ravasio Giuliano , Granatiero Federico , Invernizzi Anna , Caniatti Mario
Published: November 2021

The presence of cats in urban environments has a long history. In Italy, stray cats are protected by national and regional laws, and programs of neutering and reintroduction to colonies are ongoing. Colony cats have been widely studied from a behavioral perspective, while surveys regarding their causes of death are limited, although they may provide relevant information related to public health and cat welfare. This retrospective study provides pathological descriptions and statistical analyses of the causes of death of 186 cats from 100 colonies in the city of Milan. Inflammatory processes represent the primary cause of death (37.7%) and include common feline infectious diseases such as feline panleukopenia (67.5%), particularly in kittens, and feline infectious peritonitis (32.5%), most common in adult cats. Trauma was found to be a common cause of death of young/adult cats (14%) with a generally good body condition, while severe parasitosis was less represented (2.6%). The death of old cats was statistically associated with organ failure (24.7%), particularly renal failure, and tumors (11.8%). Knowledge of the most common causes of death of colony cats could make an important contribution to the health monitoring of these cats and sanitary control of their habitats and provide information on possible related emerging animal welfare concerns.
Enhancement of Bioreactor Performance Using Acclimatised Seed Sludge in Anaerobic Treatment of Chicken Slaughterhouse Wastewater: Laboratory Achievement, Energy Recovery, and Its Commercial-Scale Potential
Authors: Marzuki Tuan Nurfarhana Tuan Mohd , Idrus Syazwani , Musa Mohammed Ali , Wahab Abdul Malek Abdul , Jamali Nur Syakina , Man Hasfalina Che , Ng Sabrina Ng Muhamad
Published: November 2021

Lack of good management practice of chicken slaughterhouse wastewater (CSWW) has caused pollution into water bodies. In this study, the potential of seed sludge acclimatised modified synthetic wastewater (MSWW) on bioreactor performance and energy recovery of CSWW treatment was investigated. Two sets of upflow anaerobic sludge blanket (UASB) reactors were employed. The seed sludge in UASB 2 was acclimatised with MSWW for 30 days. In UASB 1, no acclimatisation process was undertaken on seed sludge for control purposes. After the acclimatisation process of UASB 2, both reactors were supplied with CSWW under the same condition of organic loading rate (OLR = 0.5 to 6 gCOD/L/d) and mesophilic condition (37 °C). COD removal efficiencies of UASB 2 were >80% all through the steady-state of the OLR applied. Meanwhile, a drastic decrease in overall performance was observed in UASB 1 when the OLR was increased to 3, 4, 5, and 6 gCOD/L/d. Energy recovery from laboratory scale and projected value from commercial-scale bioreactor were 0.056 kWh and 790.49 kWh per day, respectively. Preliminary design of an on-site commercial-scale anaerobic reactor was proposed at a capacity of 60 m3.
Emodin Improves Intestinal Health and Immunity through Modulation of Gut Microbiota in Mice Infected by Pathogenic Escherichia coli O1
Authors: Gao Ruijuan , Wang Chunjie , Han Aricha , Tian Yanping , Ren Shunan , Lv Wenting , Chen Aorigele , Zhang Jian
Published: November 2021

The effect of emodin on the intestinal mucosal barrier of a mouse E. coli O1-induced diarrhea model was observed. Following successful establishment of a diarrhea model, the mice were treated with drugs for seven days. Intestinal lesions and the shape and the number of goblet cells were assessed via hematoxylin-eosin and periodic-acid-Schiff staining, while changes in inflammatory factors, ultrastructure of the small intestine, expression of MUC-2, and changes in the intestinal microbiota were analyzed via RT-PCR, electron microscopy, immunofluorescence, and 16S rRNA sequencing. Examination showed that emodin ameliorated pathological damage to the intestines of diarrheic mice. RT-PCR indicated that emodin reduced TNF-α, IL-β, IL-6, MPO, and COX-2 mRNA levels in duodenal tissues and increased the levels of sIgA and MUC-2 and the number of goblet cells. Microbiome analysis revealed that Escherichia coli O1 reduced bacterial richness and altered the distribution pattern of bacterial communities at the phylum and order levels in cecum contents. Notably, pathogenic Clostridiales and Enterobacteriales were significantly increased in diarrheic mice. However, emodin reversed the trend. Thus, emodin protected against intestinal damage induced by E. coli O1 and improved intestinal mucosal barrier function in mice by increasing the abundance of beneficial intestinal microbiota and inhibiting the abundance of harmful bacteria, thereby alleviating diarrhea.
Distribution and Clonal Diversity of Staphylococcus aureus and Other Staphylococci in Surface Waters: Detection of ST425-t742 and ST130-t843 mecC-Positive MRSA Strains
Authors: Silva Vanessa , Ferreira Eugénia , Manageiro Vera , Reis Lígia , Tejedor-Junco María Teresa , Sampaio Ana , Capelo José Luis , Caniça Manuela , Igrejas Gilberto , Poeta Patrícia
Published: November 2021

Natural aquatic environments represent one of the most important vehicles of bacterial dissemination. Therefore, we aimed to isolate staphylococci from surface waters and to investigate the presence of antimicrobial resistance genes and virulence factors as well as the genetic lineages of all Staphylococcus aureus isolates. Staphylococci were recovered from water samples collected from 78 surface waters, including rivers, streams, irrigation ditches, dams, lakes, and fountains. The presence of antimicrobial resistance genes and virulence factors was investigated by PCR. Multilocus sequence typing and spa-typing were performed in all S. aureus isolates. From the 78 water samples, 33 S. aureus, one S. pseudintermedius, and 51 coagulase-negative staphylococci (CoNS) were identified. Among the S. aureus isolates, four MRSA were identified, and all harbored the mecC gene. Fourteen S. aureus were susceptible to all antimicrobials tested and the remaining showed resistance to penicillin, erythromycin and/or tetracycline encoded by the blaZ, ermT, msr(A/B), tetL, and vgaA genes. Regarding the clonal lineages, one mecC-MRSA isolate belonged to spa-type t843 and sequence type (ST) 130 and the other three to t742 and ST425. The remaining S. aureus were ascribed 14 spa-types and 17 sequence types. Eleven species of CoNS were isolated: S. sciuri, S. lentus, S. xylosus, S. epidermidis, S. cohnii spp. urealyticus, S. vitulinus, S. caprae, S. carnosus spp. Carnosus, S. equorum, S. simulans, and S. succinus. Thirteen CoNS isolates had a multidrug resistance profile and carried the following genes: mecA, msr(A/B), mph(C), aph(3′)-IIIa, aac(6′)-Ie–aph(2′’)-Ia, dfrA, fusB, catpC221, and tetK. A high diversity of staphylococci was isolated from surface waters including mecCMRSA strains and isolates presenting multidrug-resistance profiles. Studies on the prevalence of antibiotic-resistant staphylococci in surface waters are still very scarce but extremely important to estimate the contribution of the aquatic environment in the spread of these bacteria.
Efficient Node Deployment of Large-Scale Heterogeneous Wireless Sensor Networks
Authors: Elfouly Fatma H. , Ramadan Rabie A. , Khedr Ahmed Y. , Yadav Kusum , Azar Ahmad Taher , Abdelhamed Mohamed A.
Published: November 2021

Wireless Sensor Networks (WSNs) became essential in developing many applications, including smart cities and Internet of Things (IoT) applications. WSN has been used in many critical applications such as healthcare, military, and transportation. Such applications depend mainly on the performance of the deployed sensor nodes. Therefore, the deployment process has to be perfectly arranged. However, the deployment process for a WSN is challenging due to many of the constraints to be taken into consideration. For instance, mobile nodes are already utilized in many applications, and their localization needs to be considered during the deployment process. Besides, heterogeneous nodes are employed in many recent applications due to their efficiency and cost-effectiveness. Moreover, the development areas might have different properties due to their importance. Those parameters increase the deployment complexity and make it hard to reach the best deployment scheme. This work, therefore, seeks to discover the best deployment plan for a WSN, considering these limitations throughout the deployment process. First, the deployment problem is defined as an optimization problem and mathematically formulated using Integer Linear Programming (ILP) to understand the problem better. The main objective function is to maximize the coverage of a given field with a network lifetime constraint. Nodes’ mobility and heterogeneity are added to the deployment constraints. The importance of the monitored field subareas is also introduced in this paper, where some subareas could have more importance than others. The paper utilizes Swarm Intelligence as a heuristic algorithm for the large-scale deployment problem. Simulation experiments show that the proposed algorithm produces efficient deployment schemes with a high coverage rate and minimum energy consumption compared to some recent algorithms. The proposed algorithm shows more than a 30% improvement in coverage and network lifetime.
Fuzzy Sliding Mode Control of Vehicle Magnetorheological Semi-Active Air Suspension
Authors: Li Gang , Ruan Zhiyong , Gu Ruiheng , Hu Guoliang
Published: November 2021

In order to reduce vehicle vibration during driving conditions, a fuzzy sliding mode control strategy (FSMC) for semi-active air suspension based on the magnetorheological (MR) damper is proposed. The MR damper used in the semi-active air suspension system was tested and analyzed. Based on the experimental data, the genetic algorithm was used to identify the parameters of the improved hyperbolic tangent model, which was derived for the MR damper. At the same time, an adaptive neuro fuzzy inference system (ANFIS) was used to build the reverse model of the MR damper. The model of a quarter vehicle semi-active air suspension system equipped with a MR damper was established. Aiming at the uncertainty of the air suspension system, fuzzy control was used to adjust the boundary layer of the sliding mode control, which can effectively suppress the influence of chattering on the control accuracy and ensure system stability. Taking random road excitation and impact road excitation as the input signal, the simulation analysis of passive air suspension, semi-active air suspension based on SMC and FSMC was carried out, respectively. The results show that the semi-active air suspension based on FSMC has better vibration attenuating performance and ride comfort.
3-Hydroxy-5,6-epoxy-β-ionone Isolated from Invasive Harmful Brown Seaweed Sargassum Horneri Protects MH-S Mouse Lung Cells from Urban Particulate Matter-Induced Inflammation
Authors: Sanjeewa K. K. Asanka , Kim Hyun-Soo , Lee Hyo-Geun , Jayawardena Thilina U. , Nagahawatta D. P. , Yang Hye-Won , Udayanga Dhanushka , Kim Jae-Il , Jeon You-Jin
Published: November 2021

Air pollution is a process that mixes pollutants into the atmosphere, which is potentially harmful to humans and causes negative impacts on the surrounding environment (biotic and abiotic). The negative health effects associated with air pollution have been reported from both indoor and outdoor environments. Specifically, dust storms originating in Chinese and Mongolian desert areas introduce significant amounts of particulate matter (PM) to the Korean atmosphere. Previously, several studies reported that urban PM (UPM) is a potential agent that causes inflammation in the lungs by altering multiple signal transduction pathways; therefore, screening and identification of anti-inflammatory compounds against UPM-induced inflammation is an urgent requirement. In the present study, we attempted to study the anti-inflammatory properties of 3-Hydroxy-5,6-epoxy-β-ionone (HEBI), a pure compound isolated from invasive brown seaweed, Sargassum horneri (brown edible seaweed), against UPM-stimulated lung macrophages (MH-S). Anti-inflammatory parameters of HEBI were evaluated using Western blots, ELISA, RT-qPCR, and MTT assays. According to the results, HEBI at concentrations between 31.3 and 125 µg/mL reduced UPM-induced NO, PGE2, and pro-inflammatory cytokine production via blocking the downstream signal transduction of NF-κB and MAPKs. Specifically, HEBI down-regulated the mRNA expression levels of Toll-like receptors 2 and 4, which are well-known NF-κB and MAPKs stimulators. Taken together, HEBI is a potential candidate to develop functional foods and active ingredients in cosmeceuticals because of its profound effects against UPM-induced inflammation in MH-S macrophages.
Development of a Microwave-Assisted Extraction Protocol for the Simultaneous Determination of Mycotoxins and Pesticide Residues in Apples by LC-MS/MS
Authors: Kalogiouri Natasa P. , Papadakis Emmanouil-Nikolaos , Maggalou Maria G. , Karaoglanidis George S. , Samanidou Victoria F. , Menkissoglu-Spiroudi Urania
Published: November 2021

The possible presence of contaminants, pesticide residues and mycotoxins, in agricultural commodities is a critical issue for food safety, causing great concern. In this work, a simple and rapid analytical method employing liquid chromatography–tandem mass spectrometry (LC-MS/MS) was developed for the simultaneous determination of pesticide residues and mycotoxins in apples. Microwave-assisted extraction (MAE) was used for sample preparation. The MAE protocol was optimized after evaluating the effects of the following extraction parameters: (a) extraction solvent, (b) acidic environment, (c) temperature, and (d) extraction time. The multiresidue MAE-LC-MS/MS method was validated for linearity, accuracy (bias and precision), limits of detection (LODs), limits of quantification (LOQs), and matrix effect. The validation of the method was carried out according to the SANTE/12682/2019 document. The method demonstrated good linearity with R2 ≥ 0.99, acceptable accuracy in the recovery rate range 70–116%, acceptable interassay precision with RSD% ≤ 20, and low LODs and LOQs in the ranges 0.005–0.015 μg/g and 0.01–0.03 μg/g, respectively. Matrix effects were observed only for the 25% of the analytes. The performance of the MAE-LC-MS/MS method was compared to that of the QuEChERS sample preparation method, and the MAE-LC-MS/MS method proved to be rapid and effective.
Tree Internal Defected Imaging Using Model-Driven Deep Learning Network
Authors: Zhou Hongju , Sun Liping , Zhou Hongwei , Zhao Man , Yuan Xinpei , Li Jicheng
Published: November 2021

The health of trees has become an important issue in forestry. How to detect the health of trees quickly and accurately has become a key area of research for scholars in the world. In this paper, a living tree internal defect detection model is established and analyzed using model-driven theory, where the theoretical fundamentals and implementations of the algorithm are clarified. The location information of the defects inside the trees is obtained by setting a relative permittivity matrix. The data-driven inversion algorithm is realized using a model-driven algorithm that is used to optimize the deep convolutional neural network, which combines the advantages of model-driven algorithms and data-driven algorithms. The results of the comparison inversion algorithms, the BP neural network inversion algorithm, and the model-driven deep learning network inversion algorithm, are analyzed through simulations. The results shown that the model-driven deep learning network inversion algorithm maintains a detection accuracy of more than 90% for single defects or homogeneous double defects, while it can still have a detection accuracy of 78.3% for heterogeneous multiple defects. In the simulations, the single defect detection time of the model-driven deep learning network inversion algorithm is kept within 0.1 s. Additionally, the proposed method overcomes the high nonlinearity and ill-posedness electromagnetic inverse scattering and reduces the time cost and computational complexity of detecting internal defects in trees. The results show that resolution and accuracy are improved in the inversion image for detecting the internal defects of trees.
Characterization of Underlying Twin Shield Tunnels Due to Foundation-Excavation Unloading in Soft Soils: An Experimental and Numerical Study
Authors: Cheng Xiaodong , Hong Tianqiu , Lu Zhitang , Cheng Xiaochun
Published: November 2021

Excavation near or above existing shield tunnels often results in adverse impacts on tunnel stability. To ensure the serviceability of existing tunnels, this paper presents experimental and numerical studies with reference to a foundation pit case history excavated above twin-tube shield tunnels in soft soils. The experimental tests were firstly applied to study the deformation characteristics and structural response of the shield tunnels. Thereafter, an extensive numerical investigation was performed to determine the influence of some factors such as cover-to-excavation depth ratio, length-to-depth ratio, and unloading ratio on tunnel displacement behaviors. It was demonstrated that the tunnel heaves as the excavation proceeds, and heaves and horizontal displacements reach their maximum values when the excavation is finished. The earth pressure around the tunnels is symmetrically distributed in a gourd shape, with a larger reduction at the tunnel crown and invert and a smaller reduction at tunnel side walls. Additionally, the earth pressure at the tunnel crown and invert changes more significantly than that at other parts. The tunnel moment increment is significantly affected by the tunnel excavation depth. The axial force at or near the side walls of the tunnel is the most sensitive to the unloading effect induced by the excavation activity.
Organization of Students and Total Task Time: External and Internal Load Recorded during Motor Activity
Authors: García-Ceberino Juan M. , Feu Sebastián , Antúnez Antonio , Ibáñez Sergio J.
Published: November 2021

The organization of the students and the time taken to execute the learning tasks determine the physical (external load) and physiological (internal load) demands the students support during physical education classes. The aim of this study was to determine which organizational and pedagogical elements used to design different learning tasks for soccer provoke greater external (Player Load (PL)) and internal (Heart Rate (HR)) load and thus help the students to fulfil the adequate physical activity recommendations (moderate to vigorous physical activity for ≥50% of class time). The organizational elements studied were (1) the participation type and (2) total task time, and the pedagogical element of (3) the game situation. A total of 40 students from the fifth year of primary education participated in the study distributed into two class groups. The basic analysis units were the data on physical activity recorded in each of the tasks carried out by the students during the practical sessions (1500 records), and they were recorded using WIMU ProTM inertial movement devices. A descriptive and inferential analysis was performed with the Mann–Whitney U and Kruskal–Wallis H statistical tests. The results recommend the following types of tasks with simultaneous participation: individual games, numerical inequality SSG, numerical equality SSG lasting less than 6 min, numerical equality SSG, and full games lasting between 6 and 10 min. This type of learning task makes the students move more (medium Player Load between 0.80 and 1.20) and at greater intensities (Heart Rate zone 4, between 161 and 181 bpm). Therefore, physical education teachers must take into account the pedagogical and organizational elements studied to make the sessions more intense and associated with health benefits.
Sparse-View Neutron CT Reconstruction Using a Modified Weighted Total Difference Minimization Method
Authors: Wu Yapeng , Yang Min , He Linfeng , Lin Qiang , Wu Meimei , Li Zhengyao , Li Yuqing , Liu Xiaoguang
Published: November 2021

Indirect neutron imaging is an effective method for nondestructive testing of spent nuclear fuel elements. Considering the difficulty of obtaining experimental data in a high-radiation environment and the characteristic of high noise of neutron images, it is difficult to use the traditional FBP algorithm to recover the complete information of the sample based on the limited projection data. Therefore, it is necessary to develop the sparse-view CT reconstruction algorithm for indirect neutron imaging. In order to improve the quality of the reconstruction image, an iterative reconstruction method combining SIRT, MRP, and WTDM regularization is proposed. The reconstruction results obtained by using the proposed method on simulated data and actual neutron projection data are compared with the results of four other algorithms (FBP, SIRT, SIRT-TV, and SIRT-WTDM). The experimental results show that the SIRT-MWTDM algorithm has great advantages in both objective evaluation index and subjective observation in the reconstruction image of simulated data and neutron projection data.
Three-Component Microseismic Data Denoising Based on Re-Constrain Variational Mode Decomposition
Authors: Chen Zhili , Wang Peng , Gui Zhixian , Mao Qinghui
Published: November 2021

Microseismic monitoring is an important technology used to evaluate hydraulic fracturing, and denoising is a crucial processing step. Analyses of the characteristics of acquired three-component microseismic data have indicated that the vertical component has a higher signal-to-noise ratio (SNR) than the two horizontal components. Therefore, we propose a new denoising method for three-component microseismic data using re-constrain variational mode decomposition (VMD). In this method, it is assumed that there is a linear relationship between the modes with the same center frequency among the VMD results of the three-component data. Then, the decomposition result of the vertical component is used as a constraint to the whole denoising effect of the three-component data. On the basis of VMD, we add a constraint condition to form the re-constrain VMD, and deduce the corresponding solution process. According to the synthesis data analysis, the proposed method can not only improve the SNR level of three-component records, it also improves the accuracy of polarization analysis. The proposed method also achieved a satisfactory effect for field data.
Synthesis and Characterization of Biochar-Based Geopolymer Materials
Authors: Piccolo Federica , Andreola Fernanda , Barbieri Luisa , Lancellotti Isabella
Published: November 2021

The aim of this research is to evaluate the possibility to realize alkali-activated materials exploiting biochar, a secondary raw material coming from pyrolysis/gasification processes, for environmental benefits, such as improvement of soil fertility and reduction of CO2 emissions into the atmosphere thanks to the carbon sink process where carbon dioxide is subtracted from the cycle of carbon. For the matrix of the geopolymers, a waste material derived from incinerator bottom ash was used and compared to pure metakaolin matrix. The materials obtained are lightweight and porous, with high water absorption capacity and moisture adsorption/desorption. BET analysis shows an increase in specific surface by increasing the biochar content and the biochar acts as a filler in the pores. From porosimetry analysis it is possible to follow the evolution of the curing process of the geopolymer prepared: specimens containing 70 wt% biochar after 28 and 90 days showed an increase in total Hg intrusion volume, pore area and total porosity but a decrease in the dimensions of pores. Due to the technical properties of materials containing biochar, they can be used in the future for a cleaner design of products in the field of sustainable construction for insulating panels or lightweight materials for houses and gardens in terraces and balconies.
Developments in Smart Multi-Function Gait Assistive Devices for the Prevention and Treatment of Knee Osteoarthritis—A Literature Review
Authors: Nagano Hanatsu , Sparrow William , Begg Rezaul
Published: November 2021

Knee osteoarthritis (OA) is a degenerative condition that critically affects locomotor ability and quality of life and, the condition is particularly prevalent in the senior population. The current review presents a gait biomechanics conceptual framework for designing active knee orthoses to prevent and remediate knee OA. Constant excessive loading diminishes knee joint articular cartilage and, therefore, measures to reduce kinetic stresses due to the fact of adduction moments and joint compression are an essential target for OA prevention. A powered orthosis enables torque generation to support knee joint motions and machine-learning-driven “smart systems” can optimise the magnitude and timing of joint actuator forces. Although further research is required, recent findings raise the possibility of exoskeleton-supported, non-surgical OA interventions, increasing the treatment options for this prevalent, painful and seriously debilitating disease. Combined with advances in regenerative medicine, such as stem cell implantation and manipulation of messenger ribonucleic acid (m-RNA) transcription, active knee orthoses can be designed to incorporate electro-magnetic stimulators to promote articular cartilage resynthesis.
Valorization of Carrot Pomace: UVC Induced Accumulation of Antioxidant Phenolic Compounds
Authors: Sánchez-Rangel Juan Carlos , Benavides Jorge , Jacobo-Velázquez Daniel A.
Published: November 2021

Carrot pomace is the main waste residue obtained during carrot juice extraction. Plant tissues respond to abiotic stresses (i.e., wounding stress and ultraviolet C (UVC) radiation) by accumulating bioactive compounds. Due to the mechanical damage occurring during juice extraction, carrot pomace undergoes extreme wounding stress. In this study, the effects of UVC light (11.8 W m−2, 0–120 min) and storage time (48 h, 25 °C) on the accumulation of phenolics compounds and the antioxidant activity (AOX) of carrot pomace were evaluated. Carrot pomace that was non-treated with UVC (control) showed a 709.5% increase in total phenolics at 48 h. A high correlation of AOX values against total phenolics (R2 = 0.87) was observed, indicating that phenolics were the main contributors to the AOX of the tissue. After UVC treatment, the pomace that was radiated for 120 min with UVC showed an increase (40.4%) in chlorogenic acid (CHA) content. At 24 h, protocatechuic acid and 3,5-dicaffeoylquinic acid, which were not detected before storage, showed accumulation by 166.5 mg/kg and 169.4 mg/kg, respectively, in UVC treated pomace. Chlorogenic acid showed the highest increase (143.6%) at 48 h in the control. Valorization of carrot pomace was achieved by increasing its concentration of antioxidant phenolics through UVC radiation.
Weakly Supervised Learning for Object Localization Based on an Attention Mechanism
Authors: Park Nojin , Ko Hanseok
Published: November 2021

Recently, deep learning has been successfully applied to object detection and localization tasks in images. When setting up deep learning frameworks for supervised training with large datasets, strongly labeling the objects facilitates good performance; however, the complexity of the image scene and large size of the dataset make this a laborious task. Hence, it is of paramount importance that the expensive work associated with the tasks involving strong labeling, such as bounding box annotation, is reduced. In this paper, we propose a method to perform object localization tasks without bounding box annotation in the training process by means of employing a two-path activation-map-based classifier framework. In particular, we develop an activation-map-based framework to judicially control the attention map in the perception branch by adding a two-feature extractor so that better attention weights can be distributed to induce improved performance. The experimental results indicate that our method surpasses the performance of the existing deep learning models based on weakly supervised object localization. The experimental results show that the proposed method achieves the best performance, with 75.21% Top-1 classification accuracy and 55.15% Top-1 localization accuracy on the CUB-200-2011 dataset.
Design and Experimental Study of Potato-Soil Separation Device for Sticky Soils Condition
Authors: Wu Bei , Huang Tianci , Qiu Xuanxuan , Zuo Tianlin , Wang Xiushan , Xie Fangping
Published: November 2021

The potato-soil separation device comprising five function areas (i.e., shearing, bending, throwing, cleaning, and conveying) was developed to address the mentioned problems (e.g., soil with high moisture content, large viscosity, and poor separation efficacy) in the harvesting process for winter idle paddy fields of Southern China. Given the kinetic analyses for the potato-soil mixture of five function areas, the crucial factors of the effect of potato-soil separation were determined. Subsequently, the orthogonal test of 4 factors and 3 levels was performed, and the percentage of small soil λ, the percentage of soil adhering to potato tuber γ, and damage rate of potato tuber K were adopted as assessment indexes. Regression analyses and programming for the orthogonal test result were conducted to optimize the device run parameters, and the optimal run parameters included the rotational speed of the soil-crushing mechanism of 84.18 r/min, linear velocity of second-stage lifting chain of 0.75 m/s, and inclination angle of lifting chain of 15.87°. The field experiments were performed with the modified potato harvester. As indicated from the result, the visible potato rate was 94.31% and damage rate of potato was 0.89%, and the requirement of the national standard was satisfied. This study presented technical feasibility data and equipment for potato-soil separation under sticky soils condition.
An Improved Similarity Trajectory Method Based on Monitoring Data under Multiple Operating Conditions
Authors: Yin Jiancheng , Li Yuqing , Wang Rixin , Xu Minqiang
Published: November 2021

With the complexity of the task requirement, multiple operating conditions have gradually become the common scenario for equipment. However, the degradation trend of monitoring data cannot be accurately extracted in life prediction under multiple operating conditions, which is because some monitoring data is affected by the operating conditions. Aiming at this problem, this paper proposes an improved similarity trajectory method that can directly use the monitoring data under multiple operating conditions for life prediction. The morphological pattern and symbolic aggregate approximation-based similarity measurement method (MP-SAX) is first used to measure the similarity between the monitoring data under multiple operating conditions. Then, the similar life candidate set, and corresponding weight are obtained according to the MP-SAX. Finally, the life prediction results of equipment under multiple operating conditions can be calculated by aggregating the similar life candidate set. The proposed method is validated by the public datasets from NASA Ames Prognostics Data Repository. The results show that the proposed method can directly and effectively use the original monitoring data for life prediction without extracting the degradation trend of the monitoring data.
Methods for Mid-Term Forecasting of Crop Export and Production
Authors: Devyatkin Dmitry , Otmakhova Yulia
Published: November 2021

A vast number of studies are devoted to the short-term forecasting of agricultural production and market. However, those results are more helpful for market traders than producers and agricultural policy regulators because any structural change in that field requires a while to be implemented. The mid and long-term predictions (from one year and more) of production and market demand seem more helpful. However, this problem requires considering long-term dependencies between various features. The most natural way of analyzing all those features together is with deep neural networks. The paper presents neural network models for mid-term forecasting of crop production and export, which considers heterogeneous features such as trade flows, production levels, macroeconomic indicators, fuel pricing, and vegetation indexes. They also utilize text-mining to assess changes in the news flow related to the state agricultural policy, sanctions, and the context in the local and international food markets. We collected and combined data from various local and international providers such as UN FAOSTAT, UN Comtrade, social media, the International Monetary Fund for 15 of the world’s top wheat exporters. The experiments show that the proposed models with additive regularization can accurately predict grain export and production levels. We also confirmed that vegetation indexes and fuel prices are crucial for export prediction. Still, the fuel prices seem to be more important for predicting production than the NDVI indexes from past observations.
Effect of Probabilistic Similarity Measure on Metric-Based Few-Shot Classification
Authors: Lee Youngjae , Park Hyeyoung
Published: November 2021

In developing a few-shot classification model using deep networks, the limited number of samples in each class causes difficulty in utilizing statistical characteristics of the class distributions. In this paper, we propose a method to treat this difficulty by combining a probabilistic similarity based on intra-class statistics with a metric-based few-shot classification model. Noting that the probabilistic similarity estimated from intra-class statistics and the classifier of conventional few-shot classification models have a common assumption on the class distributions, we propose to apply the probabilistic similarity to obtain loss value for episodic learning of embedding network as well as to classify unseen test data. By defining the probabilistic similarity as the probability density of difference vectors between two samples with the same class label, it is possible to obtain a more reliable estimate of the similarity especially for the case of large number of classes. Through experiments on various benchmark data, we confirm that the probabilistic similarity can improve the classification performance, especially when the number of classes is large.
Assessment of Computer-Aided Design Tools for Topology Optimization of Additively Manufactured Automotive Components
Authors: Dalpadulo Enrico , Pini Fabio , Leali Francesco
Published: November 2021

The use of Topology Optimization techniques has seen a great development since the last decade. The principal contributor to this trend is the widespread use of Additive Manufacturing technologies to effectively build complex and performant structures over different settings. Nevertheless, the use of Topology Optimization in Design for Additive Manufacturing processes is not simple and research aims to fill the gap between theory and practice by evolving at the same time both approaches, workflows, and design software that allow their implementation. Since a strong connection between methodologies and tools exists, this work proposes a method to assess computer-aided design tools or platforms. This can be applied to sustain the key phase for selection and adoption of the computer-aided tools in industrial settings embracing Additive Manufacturing. The workflow for Topology Optimization implementation, the structure of the proposed evaluation approach, and its application, are presented to demonstrate effective usability. The automotive case study is the redesign of internal combustion engine piston to benefit of metal Additive Manufacturing based enhanced product performance. A preliminary finite element model is defined and a Topology Optimization based redesign is concurrently set up through four different commercial computer-based platforms. The method accounting for the assessment of required operations for the design optimization is applied to perform the tools selection phase.
Changes of Extreme Precipitation and Possible Influence of ENSO Events in a Humid Basin in China
Authors: Yang Xiaoxia , Wu Juan , Liu Jia , Ye Xuchun
Published: November 2021

In this study, 11 extreme precipitation indices were selected to examine the spatiotemporal variation of extreme precipitation in the Poyang Lake Basin during 1960–2017. The responses of extreme precipitation indices to El Nino/Southern Oscillation (ENSO) events of different Pacific Ocean areas were further investigated. The results show that the temperature in the Poyang Lake Basin has increased significantly since the 1990s, and the inter-decadal precipitation fluctuated. Most extreme precipitation indices showed an increasing trend with abrupt changes occurring around 1991. Spatially, most of the extreme precipitation indices decreased from northeast to southwest. The increasing trend of most indices in the center and south of the basin was relatively prominent. The linear correlations between the extreme precipitation indices and Nino 1 + 2 were the most significant. On the timescale of 2–6 years, a common oscillation period between the extreme precipitation of the basin and the four ENSO indices can be observed. After 2010, the positive correlation between the precipitation of the Poyang Lake Basin and the SST (sea surface temperature) anomalies in the equatorial Pacific increased significantly. Additionally, annual total wet–day precipitation in most areas of the Poyang Lake Basin increased with varying degrees in warm ENSO years. The results of this study will improve the understanding of the complex background and driving mechanism of flood disasters in the Poyang Lake Basin.