bluuebunny/crossref_metadata_2025 huggingface dataset:
Ionomic Approaches for Discovery of Novel Stress-Resilient Genes in Plants
Authors: Ali Sajad , Tyagi Anshika , Bae Hanhong
Published: July 2021

Plants, being sessile, face an array of biotic and abiotic stresses in their lifespan that endanger their survival. Hence, optimized uptake of mineral nutrients creates potential new routes for enhancing plant health and stress resilience. Recently, minerals (both essential and non-essential) have been identified as key players in plant stress biology, owing to their multifaceted functions. However, a realistic understanding of the relationship between different ions and stresses is lacking. In this context, ionomics will provide new platforms for not only understanding the function of the plant ionome during stresses but also identifying the genes and regulatory pathways related to mineral accumulation, transportation, and involvement in different molecular mechanisms under normal or stress conditions. This article provides a general overview of ionomics and the integration of high-throughput ionomic approaches with other “omics” tools. Integrated omics analysis is highly suitable for identification of the genes for various traits that confer biotic and abiotic stress tolerance. Moreover, ionomics advances being used to identify loci using qualitative trait loci and genome-wide association analysis of element uptake and transport within plant tissues, as well as genetic variation within species, are discussed. Furthermore, recent developments in ionomics for the discovery of stress-tolerant genes in plants have also been addressed; these can be used to produce more robust crops with a high nutritional value for sustainable agriculture.
Hydrogen-Assisted Brittle Fracture Behavior of Low Alloy 30CrMo Steel Based on the Combination of Experimental and Numerical Analyses
Authors: Li Yunlong , Zhang Keshi , Lu Damin , Zeng Bin
Published: July 2021

Compact-tension (CT) specimens made of low alloy 30CrMo steels were hydrogen-charged, and then subjected to the fracture toughness test. The experimental results revealed that the higher crack propagation and the lower crack growth resistance (CTOD-R curve) are significantly noticeable with increasing hydrogen embrittlement (HE) indexes. Moreover, the transition in the microstructural fracture mechanism from ductile (microvoid coalescence (MVC)) without hydrogen to a mixed quasi-cleavage (QC) fracture and QC + intergranular (IG) fracture with hydrogen was observed. The hydrogen-enhanced decohesion (HEDE) mechanism was characterized as the dominant HE mechanism. According to the experimental testing, the coupled problem of stress field and hydrogen diffusion field with cohesive zone stress analysis was employed to simulate hydrogen-assisted brittle fracture behavior by using ABAQUS software. The trapezoidal traction-separation law (TSL) was adopted, and the initial TSL parameters from the best fit to the load-displacement and J-integral experimental curves without hydrogen were calibrated for the critical separation of 0.0393 mm and the cohesive strength of 2100 MPa. The HEDE was implemented through hydrogen influence in the TSL, and to estimate the initial hydrogen concentration based on matching numerical and experimental load-line displacement curves with hydrogen. The simulation results show that the general trend of the computational CTOD-R curves corresponding to initial hydrogen concentration is almost the same as that obtained from the experimental data but in full agreement, the computational CTOD values being slightly higher. Comparative analysis of numerical and experimental results shows that the coupled model can provide design and prediction to calculate hydrogen-assisted fracture behavior prior to extensive laboratory testing, provided that the material properties and properly calibrated TSL parameters are known.
Combining Structural Optimization and Process Assurance in Implicit Modelling for Casting Parts
Authors: Rosnitschek Tobias , Erber Maximilian , Hartmann Christoph , Volk Wolfram , Rieg Frank , Tremmel Stephan
Published: July 2021

The structural optimization of manufacturable casting parts is still a challenging and time-consuming task. Today, topology optimization is followed by a manual reconstruction of the design proposal and a process assurance simulation to endorse the design proposal. Consequently, this process is iteratively repeated until it reaches a satisfying compromise. This article shows a method to combine structural optimization and process assurance results to generate automatically structure- and process-optimized die casting parts using implicit geometry modeling. Therefore, evaluation criteria are developed to evaluate the current design proposal and qualitatively measure the improvement of manufacturability between two iterations. For testing the proposed method, we use a cantilever beam as an example of proof. The combined iterative method is compared to manual designed parts and a direct optimization approach and evaluated for mechanical performance and manufacturability. The combination of topology optimization (TO) and process assurance (PA) results is automated and shows a significant enhancement to the manual reconstruction of the design proposals. Further, the improvement of manufacturability is better or equivalent to previous work in the field while using less computational effort, which emphasizes the need for suitable metamodels to significantly reduce the effort for process assurance and enable much shorter iteration times.
Development and Optimization of Cinnamon Oil Nanoemulgel for Enhancement of Solubility and Evaluation of Antibacterial, Antifungal and Analgesic Effects against Oral Microbiota
Authors: Hosny Khaled M. , Khallaf Rasha A. , Asfour Hani Z. , Rizg Waleed Y. , Alhakamy Nabil A. , Sindi Amal M. , Alkhalidi Hala M. , Abualsunun Walaa A. , Bakhaidar Rana B. , Almehmady Alshaimaa M. , Abdulaal Wesam H. , Bakhrebah Muhammed A. , Alsuabeyl Mohammed S. , K. Kammoun Ahmed , Alghaith Adel F. , Alshehri Sultan
Published: July 2021

Oral health is a key contributor to a person’s overall health and well-being. Oral microbiota can pose a serious threat to oral health. Thus, the present study aimed to develop a cinnamon oil (CO)-loaded nanoemulsion gel (NEG1) to enhance the solubilization of oil within the oral cavity, which will enhance its antibacterial, antifungal, and analgesic actions against oral microbiota. For this purpose, the CO-loaded nanoemulsion (CO-NE) was optimized using I-optimal response surface design. A mixture of Pluracare L44 and PlurolOleique CC 497 was used as the surfactant and Capryol was used as the co-surfactant. The optimized CO-NE had a globule size of 92 ± 3 nm, stability index of 95% ± 2%, and a zone of inhibition of 23 ± 1.5 mm. This optimized CO-NE formulation was converted into NEG1 using 2.5% hydroxypropyl cellulose as the gelling agent. The rheological characterizations revealed that the NEG1 formulation exhibited pseudoplastic behavior. The in vitro release of eugenol (the marker molecule for CO) from NEG1 showed an enhanced release compared with that of pure CO. The ex vivo mucosal permeation was found to be highest for NEG1 compared to the aqueous dispersion of CO-NE and pure cinnamon oil. The latency reaction time during the hot-plate test in rats was highest (45 min) for the NEG1 sample at all-time points compared with those of the other tested formulations. The results showed that the CO-NEG formulation could be beneficial in enhancing the actions of CO against oral microbiota, as well as relieving pain and improving overall oral health.
An Insight into Biomolecules for the Treatment of Skin Infectious Diseases
Authors: Felgueiras Helena P.
Published: July 2021

In assigning priorities, skin infectious diseases are frequently classified as minor when compared to infectious diseases of high mortality rates, such as tuberculosis or HIV. However, skin infections are amongst the most common and prevalent diseases worldwide. Elderly individuals present an increased susceptibility to skin infections, which may develop atypical signs and symptoms or even complicate pre-existing chronic disorders. When the skin fails to correct or inhibit the action of certain pathogenic microorganisms, biomolecules endowed with antimicrobial features are frequently administered topically or systemically to assist or treat such conditions. (1) Antibiotics, (2) antimicrobial peptides, or (3) natural extracts display important features that can actively inhibit the propagation of these pathogens and prevent the evolution of infectious diseases. This review highlights the properties and mechanisms of action of these biomolecules, emphasizing their effects on the most prevalent and difficult to treat skin infections caused by pathogenic bacteria, fungi, and viruses. The versatility of biomolecules’ actions, their symbiotic effects with skin cells and other inherent antimicrobial components, and their target-directed signatures are also explored here.
The Role of Mathematical Models in Immuno-Oncology: Challenges and Future Perspectives
Authors: Sancho-Araiz Aymara , Mangas-Sanjuan Victor , Trocóniz Iñaki F.
Published: July 2021

Immuno-oncology (IO) focuses on the ability of the immune system to detect and eliminate cancer cells. Since the approval of the first immune checkpoint inhibitor, immunotherapies have become a major player in oncology treatment and, in 2021, represented the highest number of approved drugs in the field. In spite of this, there is still a fraction of patients that do not respond to these therapies and develop resistance mechanisms. In this sense, mathematical models offer an opportunity to identify predictive biomarkers, optimal dosing schedules and rational combinations to maximize clinical response. This work aims to outline the main therapeutic targets in IO and to provide a description of the different mathematical approaches (top-down, middle-out, and bottom-up) integrating the cancer immunity cycle with immunotherapeutic agents in clinical scenarios. Among the different strategies, middle-out models, which combine both theoretical and evidence-based description of tumor growth and immunological cell-type dynamics, represent an optimal framework to evaluate new IO strategies.
Accuracy Assessment in Convolutional Neural Network-Based Deep Learning Remote Sensing Studies—Part 2: Recommendations and Best Practices
Authors: Maxwell Aaron E. , Warner Timothy A. , Guillén Luis Andrés
Published: July 2021

Convolutional neural network (CNN)-based deep learning (DL) has a wide variety of applications in the geospatial and remote sensing (RS) sciences, and consequently has been a focus of many recent studies. However, a review of accuracy assessment methods used in recently published RS DL studies, focusing on scene classification, object detection, semantic segmentation, and instance segmentation, indicates that RS DL papers appear to follow an accuracy assessment approach that diverges from that of traditional RS studies. Papers reporting on RS DL studies have largely abandoned traditional RS accuracy assessment terminology; they rarely reported a complete confusion matrix; and sampling designs and analysis protocols generally did not provide a population-based confusion matrix, in which the table entries are estimates of the probabilities of occurrence of the mapped landscape. These issues indicate the need for the RS community to develop guidance on best practices for accuracy assessment for CNN-based DL thematic mapping and object detection. As a first step in that process, we explore key issues, including the observation that accuracy assessments should not be biased by the CNN-based training and inference processes that rely on image chips. Furthermore, accuracy assessments should be consistent with prior recommendations and standards in the field, should support the estimation of a population confusion matrix, and should allow for assessment of model generalization. This paper draws from our review of the RS DL literature and the rich record of traditional remote sensing accuracy assessment research while considering the unique nature of CNN-based deep learning to propose accuracy assessment best practices that use appropriate sampling methods, training and validation data partitioning, assessment metrics, and reporting standards.
Mapping 30 m Fractional Forest Cover over China’s Three-North Region from Landsat-8 Data Using Ensemble Machine Learning Methods
Authors: Liu Xiaobang , Liang Shunlin , Li Bing , Ma Han , He Tao
Published: July 2021

The accurate monitoring of forest cover and its changes are essential for environmental change research, but current satellite products for forest coverage carry many uncertainties. This study used 30-m Landsat-8 data, and aggregated 1-m GaoFen-2 (GF-2) satellite images to construct the training samples and used multiple machine learning algorithms (MLAs) to estimate the fractional forest cover (FFC) in China’s Three North Region (TNR). In this study, multiple MLAs were merged to construct stacked generalization (SG) models based on the idea of SG, and the performances of the MLAs in the FFC estimation were evaluated. The results of the 10-fold cross-validation showed that all non-linear algorithms had a good performance, with an R2 value of greater than 0.8 and a root-mean square error (RMSE) of less than 0.05. In the bagging ensemble, the random forest (RF) (R2 = 0.993, RMSE = 0.020) model performed the best and in the boosting ensemble, the light gradient boosted machine (LGBM) (R2 = 0.992, RMSE = 0.022) performed the best. Although the evaluation index of the RF is slightly better than that of the LGBM, the independent validation results show that the two models have similar performances. The model evaluation results of the independent datasets showed that, in the SG model, the performance of the SG(LGBM) (R2 = 0.991, RMSE = 0.034) was better than that of the single or non-ensemble model. Comparing the FFC estimates of our model with those of existing datasets showed that our model exhibited more forest spatial distribution details and higher accuracy in complex landscapes. Overall, in this study, the method of using high-resolution remote sensing (RS) images to extract samples for FFC estimation is feasible. Our results demonstrate the potential of the ensemble MLAs to map the FFC. The research results also show that among many MALs, the RF algorithm is the most suitable algorithm for estimating FFC, which provides a reference for future research.
Action Generative Networks Planning for Deformable Object with Raw Observations
Authors: Sheng Ziqi , Jin Kebing , Ma Zhihao , Zhuo Hankz-Hankui
Published: July 2021

Synthesizing plans for a deformable object to transit from initial observations to goal observations, both of which are represented by high-dimensional data (namely “raw” data), is challenging due to the difficulty of learning abstract state representations of raw data and transition models of continuous states and continuous actions. Even though there have been some approaches making remarkable progress regarding the planning problem, they often neglect actions between observations and are unable to generate action sequences from initial observations to goal observations. In this paper, we propose a novel algorithm framework, namely AGN. We first learn a state-abstractor model to abstract states from raw observations, a state-generator model to generate raw observations from states, a heuristic model to predict actions to be executed in current states, and a transition model to transform current states to next states after executing specific actions. After that, we directly generate plans for a deformable object by performing the four models. We evaluate our approach in continuous domains and show that our approach is effective with comparison to state-of-the-art algorithms.
Esophagus Segmentation in CT Images via Spatial Attention Network and STAPLE Algorithm
Authors: Tran Minh-Trieu , Kim Soo-Hyung , Yang Hyung-Jeong , Lee Guee-Sang , Oh In-Jae , Kang Sae-Ryung
Published: July 2021

One essential step in radiotherapy treatment planning is the organ at risk of segmentation in Computed Tomography (CT). Many recent studies have focused on several organs such as the lung, heart, esophagus, trachea, liver, aorta, kidney, and prostate. However, among the above organs, the esophagus is one of the most difficult organs to segment because of its small size, ambiguous boundary, and very low contrast in CT images. To address these challenges, we propose a fully automated framework for the esophagus segmentation from CT images. The proposed method is based on the processing of slice images from the original three-dimensional (3D) image so that our method does not require large computational resources. We employ the spatial attention mechanism with the atrous spatial pyramid pooling module to locate the esophagus effectively, which enhances the segmentation performance. To optimize our model, we use group normalization because the computation is independent of batch sizes, and its performance is stable. We also used the simultaneous truth and performance level estimation (STAPLE) algorithm to reach robust results for segmentation. Firstly, our model was trained by k-fold cross-validation. And then, the candidate labels generated by each fold were combined by using the STAPLE algorithm. And as a result, Dice and Hausdorff Distance scores have an improvement when applying this algorithm to our segmentation results. Our method was evaluated on SegTHOR and StructSeg 2019 datasets, and the experiment shows that our method outperforms the state-of-the-art methods in esophagus segmentation. Our approach shows a promising result in esophagus segmentation, which is still challenging in medical analyses.
Study on the Value Model of Urban Green Infrastructure Development—A Case Study of the Central District of Taichung City
Authors: Hsu Kuo-Wei , Chao Jen-Chih
Published: July 2021

Urban green infrastructure has become an important concept for sustainable urban development. Regarding the joining up of green spaces into green networks, it can have major positive impacts on the environment, societies and economies, and ecology. This study proposes a value model for investing in urban green infrastructure, with impact factors including land use value, energy conservation value, carbon reduction, and disaster prevention value. It establishes that through the interaction between all four of these factors, urban green infrastructure investment increases net operating income. Additionally, as disaster prevention value increases, urban disaster risk declines, and this has an important positive effect on overall value. Our modeling also indicates that in the face of climatic extremes, the construction of urban green infrastructure is increasingly important, particularly in terms of energy value and disaster prevention value. Specific incentives and catalysts for promoting investment in urban green infrastructure are proposed.
Experimental Study of Thermal Response of Vertically Loaded Energy Pipe Pile
Authors: Wang Junlin , Li Zhao
Published: July 2021

Energy piles are a relatively new technology that have dual function as heat transferring and load bearing. Due to the influence of temperature cycles, additional thermal stress and relative displacement of the pile will be generated; this is different from the load transferring mechanism of the conventional pile. In order to study the thermodynamic characteristics of the energy pipe pile under dual working conditions and temperature cycles, field tests were carried out on the PHC (prestressed high-strength concrete) energy pipe pile without constraining on the top of the piles. Displacement gauges were arranged on the top of the pile, and concrete strain gauges (temperature, strain) were embedded in the pile. The variation laws of temperature, thermal strain, thermal stress, side friction resistance, and displacement of the pile top during the temperature cycling were analyzed. The test results show that the heat exchange system reached a stable state after being heated for 5 days in summer. The average temperature of the pile increased by 15.17 °C, to 34.68 °C; it was low at both ends and high in the middle part. After 5 days in the winter environment, the average temperature of the pile decreased by 10.09 °C, to 9.54 °C, which was high at both ends and low in the middle. The thermal stress was generated inside the pile, and the maximum compressive stress was 3.446 MPa and the maximum tensile stress was 2.69 MPa. The neutral point of the side friction resistance appeared 8 m below the pile top, about 2/3 of the pile length. The maximum negative side friction resistance under the summer condition was 42.06 KPa, the maximum positive side friction resistance under the winter condition was 29.93 KPa, and the lateral resistance of the pile degraded in winter. Under the influence of thermal load, the final pile top displacements in the summer and winter were −0.7 mm (0.175%D) and 0.77 mm (0.193%D), respectively.
Ferric Oxide-Containing Waterworks Sludge Reduces Emissions of Hydrogen Sulfide in Biogas Plants and the Needs for Virgin Chemicals
Authors: Persson Tobias , Persson Kenneth M. , Åström Jenny
Published: July 2021

Ferric oxide-containing waterworks sludge can be used to reduce the formation of hydrogen sulfide during anaerobic digestion. The ferric compound is reduced biochemically in the digester and forms insoluble pyrite in digester sludge. Virgin ferric chloride is often used to solve the hydrogen sulfide problem. Since 2013, Sydvatten AB has supplied a growing number of digestion plants in Sweden with ferric-containing dewatered waterworks sludge derived from the drinking water treatment plant Ringsjöverket to limit the formation of hydrogen sulfide. At the waterworks, ferric chloride is added to enhance the coagulation of organic matter from the source water. The sludge formed in this process is dewatered and landfilled, but also recycled in biogas production in order to decrease the hydrogen sulfide concentration. In this study, the use of sludge for hydrogen sulfide removal in digesters was technically and economically evaluated via case studies from 13 full-scale digesters in Sweden. Compared with the use of fresh ferric chloride, the operational costs are reduced by up to 50% by using sludge. The quality of the sludge is high and its content in metals is low or very low, especially when compared with the requirements of different certification standards for biosolid reuse applied in Sweden. The addition of waterworks sludge containing iron to a digester for the removal of dissolved hydrogen sulfide is a technically and economically good alternative when producing biogas. It is also one step closer to a circular economy, as replacing the use of virgin chemicals with the by-product waterworks sludge saves energy and materials and reduces the carbon footprint of the waterworks.
Effect of Newly Synthesized Salts and Three Common Micropollutants on the Biochemical Activity of Nitrifiers
Authors: Olejnik Dorota , Galamon Malgorzata , Liwarska-Bizukojc Ewa , Delbeke Elisabeth , Van Geem Kevin M. , Stevens Christian V.
Published: July 2021

Often, different types of contaminants in wastewater are suspected of adversely affecting the treatment efficiency of a wastewater treatment plant (WWTP). Therefore, it is essential to study the effects of newly synthesized substances on the activity of activated sludge microorganisms. The aim of this study was to determine the effect of innovative biosurfactants, i.e., sophorolipids quaternary ammonium salts (SQAS), and three common micropollutants (MPs), i.e., diclofenac (DCP), 17α-ethynylestradiol (EE2), and 4-nonylenol (4-NP), on the biochemical activity of activated sludge microorganisms. The effect of all tested substances was more significant on nitrite-oxidizing bacteria (NOB) than on ammonia-oxidizing bacteria (AOB), and least on the respiratory activity of heterotrophic organisms (HET). SQAS inhibited nitrification even at the lowest concentration tested (5 mg L−1) and the inhibition degree was in the range of 37% to 78%; at the highest concentration of SQAS studied (160 mg L−1), it was about 45–96%. In most cases, the degree of inhibition increased when the SQAS concentration approached 80–160 mg L−1. MPs influenced the activity of nitrifiers to a lower extent than SQAS. The inhibition degree varied from 25% to 75%, depending on the micropollutant tested and its concentration.
Sustainable Construction Investment, Real Estate Development, and COVID-19: A Review of Literature in the Field
Authors: Kaklauskas Arturas , Zavadskas Edmundas Kazimieras , Lepkova Natalija , Raslanas Saulius , Dauksys Kestutis , Vetloviene Ingrida , Ubarte Ieva
Published: July 2021

Aspects of sustainable construction investment and real estate development (CIRED) and their interrelations during the period pre-, intra-, and post-COVID-19, are presented in the research. Applications of the topic model, environmental psychology theory, building life cycle method, and certain elements of bibliometrics, webometrics, article level metrics, altmetrics, and scientometrics make it possible to perform a quantitative analysis on CIRED. The CIRED topic model was developed in seven steps. This paper aims to present a literature review on CIRED throughout the pandemic and to look at the responses from the real estate and construction sector. This sector is a field that appears to be rapidly expanding, judging from the volume of current research papers. This review focuses on last year’s leading peer-reviewed journals. A combination of various keywords was applied for the review and the criteria for paper selections included construction investment, real estate development, civil engineering, COVID-19, and sustainability, as well as residential, industrial, commercial, land, and special purpose real estate, along with their risks, strategies, and trends. The articles reviewed for this paper, which analyzes three hypotheses, look at pre-, intra-, and post-pandemic CIRED. The three hypotheses were validated by analyzing scientific publications from around the world. Two innovative elements make this study stand out among the most advanced research on pre-, intra-, and post-pandemic CIRED. The first of the two innovations is the integrated analysis of the COVID-19 pandemic, COVID-19-related national policies, and business investment strategies relevant to CIRED and the interests of investors as well as on the impact a CIRED policy and investors make on the spread of COVID-19. In addition, this research demonstrates a marked increase in the effectiveness of a CIRED analysis, when the life cycle of a CIRED, the involved stakeholders with their own individual interests, the COVID-19 situation, and the external micro-, meso-, and macro-environments are covered comprehensively as a single entity.
A Sustainable and Global Health Perspective of the Dietary Pattern of French Population during the 1998–2015 Period from INCA Surveys
Authors: Fardet Anthony , Thivel David , Gerbaud Laurent , Rock Edmond
Published: July 2021

In France, the evolution of dietary pattern relative to sustainability and global health remains insufficiently studied. The objective of this study was to assess dietary changes during 1998–2015 through three generic metrics potentially related to sustainability. Food consumption data were collected from three French National Individual Study of Food Consumption surveys (INCA) for children (0–17 years) and adults (18–79 years) representative of the French population. The consumed foods were converted into plant (metric 1) and non-ultra-processed (UPF, metric 2) calories, and analyzed in meeting dietary recommended intakes (metric 3). French children and adults consumed high levels of animal and UPF calories, and nutrient deficiencies were observed in adults from the 2015 survey, e.g., fiber, EPA, DHA, magnesium, retinol, and vitamin C. In children, UPF daily calories increased from 42.8 to 45.5% and decreased in adults from 39.2 to 35.0%. In children and adults, diet revegetation was observed. While the level of physical activity decreased, overweight, obesity and type 2 diabetes prevalence increased in French adults. The French dietary pattern is not sustainable for global health unless public health policy is reinforced, with at least a twofold decrease in animal and UPF calories and improved food diversity.
Modeling of Low Visibility-Related Rural Single-Vehicle Crashes Considering Unobserved Heterogeneity and Spatial Correlation
Authors: Cai Zhenggan , Wei Fulu , Wang Zhenyu , Guo Yongqing , Chen Long , Li Xin
Published: July 2021

Accident analysis and prevention are helpful to ensure the sustainable development of transportation. The aim of this research was to investigate the factors associated with the severity of low-visibility-related rural single-vehicle crashes. Firstly, a latent class clustering model was implemented to partition the whole-dataset into a relatively homogeneous sub-dataset. Then, a spatial random parameters logit model was established for each dataset to capture unobserved heterogeneity and spatial correlation. Analysis was conducted based on the crash data (2014–2019) from 110 two-lane road segments. The results show that the proposed method is a superior crash severity modeling approach to accommodate the unobserved heterogeneity and spatial correlation. Three variables—seatbelt not used, motorcycle, and collision with fixed object—have a stable positive correlation with crash severity. Motorcycle leads to a 12.8%, 23.8%, and 12.6% increase in the risk of serious crashes in the whole-dataset, cluster 3, and cluster 4, respectively. In the whole-dataset, cluster 2, and cluster 3, the risk of serious crashes caused by seatbelt not used increased by 5.5%, 0.1%, and 30.6%, respectively, and caused by collision with fixed object increased by 33.2%, 1.2%, and 13.2%, respectively. The results can provide valuable information for engineers and policy makers to develop targeted measures.
Integrated Application of Composted Agricultural Wastes, Chemical Fertilizers and Biofertilizers as an Avenue to Promote Growth, Yield and Quality of Maize in an Arid Agro-Ecosystem
Authors: Al-Suhaibani Nasser , Selim Mostafa , Alderfasi Ali , El-Hendawy Salah
Published: July 2021

Formulating new integrated plant nutrient management (IPNM) strategies in order to sustain crop production and protect the environment has become an important issue in the present agricultural system. Therefore, a field study was carried out in the two seasons 2016 and 2017 to formulate the best IPNM strategies for improving the growth, yield, and quality of maize grown in an arid agro-ecosystem. The IPNM comprised full-dose NPK (T1); composted agricultural wastes based on cow manure (T2), poultry manure (T3), and a mixture of sheep and camel manure (T4) as activators at the rate of 5 t ha−1 for each; half-dose NPK was combined with the mixture of the three types of composted agricultural wastes at the rate of 5 t ha−1 (T5) or 10 t ha−1 (T6), and a mixture of the three types of composted agricultural wastes at the rate of 10 t ha−1 (T7), 15 t ha−1 (T8), or 20 t ha−1 (T9), either with or without biofertilizers. The results showed that, as compared to T1, T6 or T9 significantly increased different growth, yield, and quality parameters of maize by 11.4–27.3%, 0.8–31.8%, and 4.6–17.2%, while T2 significantly decreased these parameters by 2.2–17.8%, 3.5–16.7%, and 4.5–9.4%, respectively. Seed inoculation with biofertilizers significantly increased different parameters of maize by 1.8–12.9%, compared to that of the non-inoculation seed treatment. Principal component analysis showed a strong relationship between different parameters of maize and treatments T5, T6, T8, and T9 with seed inoculation. Further, a significant and linear relationship was observed between different parameters of maize and the amount of N (R2 = 0.65–0.77), P (R2 = 0.58–0.71), and K (R2 = 0.63–0.73). These results indicated that any IPNM strategies that manage the NPK status and dynamics in the soil are a promising avenue for improving the growth and productivity of maize grown in the arid agro-ecosystem.
Engaging ICT Engineering Undergraduates in a Management Subject through First Day of Class Activities: An Empirical Study
Authors: Petchamé Josep , Iriondo Ignasi , Canaleta Xavi , Riu David , Necchi Silvia
Published: July 2021

The expectations, attitudes, engagement, and motivation of students are key elements when designing learning activities. Several studies have been implemented and different strategies and activities have been analyzed to improve the aforesaid aspects of learning content. In the context of the New Learning Context (NLC), this paper presents the findings of two first day of class activities aimed at engaging engineering students in a business and management subject from the very first moment: an empirical study conducted by means of a survey answered by engineering students in Information and Communication Technologies (ICT), followed by an interactive activity between students and instructors carried out through a reciprocal interview activity. The survey was performed with the objective of identifying what they ‘liked’ and ‘disliked’ on their first day of class of a business subject. The findings are presented and compared with previous studies and have proven to be mostly consistent with previous academic work. Finally, a reciprocal interview activity was chosen to potentially enhance the students’ engagement and motivation. According to the feedback received, this activity was positively valued by the students.
Experimental and Informational Modeling Study of Sustainable Self-Compacting Geopolymer Concrete
Authors: Faridmehr Iman , Nehdi Moncef L. , Huseien Ghasan Fahim , Baghban Mohammad Hajmohammadian , Sam Abdul Rahman Mohd , Algaifi Hassan Amer
Published: July 2021

Self-compacting concrete (SCC) became a strong candidate for various construction applications owing to its excellent workability, low labor demand, and enhanced finish-ability, and because it provides a solution to the problem of mechanical vibration and related noise pollution in urban settings. However, the production of Portland cement (PC) as a primary constituent of SCC is energy-intensive, contributing to about 7% of global carbon dioxide (CO2) emissions. Conversely, the use of alternative geopolymer binders (GBs) in concrete can significantly reduce the energy consumption and CO2 emissions. In addition, using GBs in SCC can produce unique sustainable concrete with unparallel engineering properties. In this outlook, this work investigated the development of some eco-efficient self-compacting geopolymer concretes (SCGCs) obtained by incorporating different dosages of fly ash (FA) and ground blast furnace slag (GBFS). The structural, morphological, and mechanical traits of these SCGCs were examined via non-destructive tests like X-ray diffraction (XRD) and scanning electron microscopy (SEM). The workability and mechanical properties of six SCGC mixtures were examined using various measurements, and the obtained results were analyzed and discussed. Furthermore, an optimized hybrid artificial neural network (ANN) coupled with a metaheuristic Bat optimization algorithm was developed to estimate the compressive strength (CS) of these SCGCs. The results demonstrated that it is possible to achieve appropriate workability and mechanical strength through 50% partial replacement of GBFS with FA in the SCGC precursor binder. It is established that the proposed Bat-ANN model can offer an effective intelligent method for estimating the mechanical properties of various SCGC mixtures with superior reliability and accuracy via preventing the need for laborious, costly, and time-consuming laboratory trial batches that are responsible for substantial materials wastage.
Changes in Reserve Mobilization Caused by Salinity Could Interfere in the Initial Growth of Jatropha curcas
Authors: Lira Emannuella , Souza Joilma , Galdino Lucas , Macêdo Cristiane , Silva Anselmo , Melo Yuri , Santos Ivanice , Arriel Nair , Meneses Carlos , Maia Josemir
Published: July 2021

Salinity in soil can affect Jatropha seedling metabolism, interfering with plant establishment. In this study, the effect of salinity on the mobilization of reserves during the development of Jatropha seedlings was tested. Two genotypes of Jatropha were used and three concentrations of NaCl were applied between the 4th and 8th days after germination. The effects of salinity on seedling growth, in terms of fresh and dry phytomass, ionic partition, and sugar quantification, starch, proteins, amino acids, and lipids were evaluated in cotyledon leaves, hypocotyls, and roots. There was an increase in the content of all classes of macromolecules analyzed in at least one of the organs. It is hypothesized that the hypocotyls acted as an accumulating organ of Na+. The accumulations of amino acids and protein in roots suggest that metabolic responses occurred in response to the ionic and osmotic effects of NaCl, although this accumulation did not appear to prevent biomass losses in seedlings. Furthermore, the findings of this study demonstrate that salinity inhibits the mobilization of lipids and carbon stocks from cotyledon leaves to the rest of the plant, and together with the synthesis of proteins and amino acids that occurred primarily in roots, contributed to response of these plants to salinity.
Application of Gamma Attenuation Technique and Artificial Intelligence to Detect Scale Thickness in Pipelines in Which Two-Phase Flows with Different Flow Regimes and Void Fractions Exist
Authors: Alamoudi Mohammed , Sattari Mohammad Amir , Balubaid Mohammed , Eftekhari-Zadeh Ehsan , Nazemi Ehsan , Taylan Osman , Kalmoun El Mostafa
Published: July 2021

Scale deposits can reduce equipment efficiency in the oil and petrochemical industry. The gamma attenuation technique can be used as a non-invasive effective tool for detecting scale deposits in petroleum pipelines. The goal of this study is to propose a dual-energy gamma attenuation method with radial basis function neural network (RBFNN) to determine scale thickness in petroleum pipelines in which two-phase flows with different symmetrical flow regimes and void fractions exist. The detection system consists of a dual-energy gamma source, with Ba-133 and Cs-137 radioisotopes and two 2.54-cm × 2.54-cm sodium iodide (NaI) detectors to record photons. The first detector related to transmitted photons, and the second one to scattered photons. The transmission detector recorded two signals, which were the counts under photopeak of Ba-133 and Cs-137 with the energy of 356 keV and 662 keV, respectively. The one signal recorded in the scattering detector, total counts, was applied to RBFNN as the inputs, and scale thickness was assigned as the output.
In Vivo Production of HN Protein Increases the Protection Rates of a Minicircle DNA Vaccine against Genotype VII Newcastle Disease Virus
Authors: Wang Zhannan , Zhao Xiaohan , Wang Ying , Sun Chao , Sun Ming , Gao Xingyun , Jia Futing , Shan Chenxin , Yang Guilian , Wang Jianzhong , Huang Haibin , Shi Chunwei , Yang Wentao , Qian Aidong , Wang Chunfeng , Jiang Yanlong
Published: July 2021

The Cre-recombinase mediated in vivo minicircle DNA vaccine platform (CRIM) provided a novel option to replace a traditional DNA vaccine. To further improve the immune response of our CRIM vaccine, we designed a dual promoter expression plasmid named pYL87 which could synthesize short HN protein under a prokaryotic in vivo promoter PpagC and full length HN protein of genotype VII Newcastle disease virus (NDV) under the previous eukaryotic CMV promoter at the same time. Making use of the self-lysed Salmonella strain as a delivery vesicle, chickens immunized with the pYL87 construction showed an increased serum haemagglutination inhibition antibody response, as well as an increased cell proliferation level and cellular IL-4 and IL-18 cytokines, compared with the previous CRIM vector pYL47. After the virus challenge, the pYL87 vector could provide 80% protection compared to 50% protection against genotype VII NDV in pYL47 immunized chickens, indicating a promising dual promoter strategy used in vaccine design.
Foreign Policy of China and the United States' Imposition of a Bipolar Confrontation on China
Authors:   Financial University under the Government of the Russian Federation, Perskaya Victoria V.
Published: July 2021

The article analyzes the US policy in terms of rebuilding bipolarity in the world community, where the Communist Party of China is designated as the main enemy of progressive humanity, an attempt is made to reform alliances of supporters of confrontation with China and countries that are confidently striving to pursue sovereign foreign and domestic policies. For the United States, this positioning corresponds to the tradition of foreign policy activities in the world community. In addition, it is based on the success of the policy of counteracting the camp of socialism and the USSR, and it was proposed to implement the same course in relation to the CPC of the PRC. A study of the main conceptual provisions determining the content of the PRC’s foreign policy strategy was carried out, it was proved that China does not seek to become a hegemon in the world community, but economic leadership and its economic interests will try to promote in all possible ways, excluding military actions. The economic expansion of the PRC can only be counteracted by the countries gaining genuine national economic sovereignty and building up national competitiveness, an interstate foreign policy strategy pursued by countries on the basis of realizing national interests and reaching an agreed consensus in sensitive sectors of economic interaction.
Monuments and Evaluations
Authors:   Institute for Economic Strategies, Ageev Aleksandr
Published: July 2021

Opening address of the Editor-in-chief
Visual research in the subject field of modern cultural studies
Authors: Tsyplyakova D.I.
Published: July 2021

This paper is devoted to the peculiarities of visual research in the subject field of modern culturology, argumentation of the significance of the category of visual experience for cultural studies and the analysis of visual practices that create it.
Digital transformation and resistance in the transition to the online world
Authors: Yarnykh Elvira Arkadievna , Zhukova Ekaterina Evgenievna
Published: July 2021

The article describes the consequences of the pandemic for business and the behavior of some market participants and educational institutions both during the pandemic and after its expected end. Such issues as the changing nature of the movement towards universal digitalization, as well as the reasons that affect the ease of its adoption, are raised, and the situation of market participants who decide to return to the previous format of work after the end of the pandemic is analyzed. The materials of the article can be used in the preparation of students in the field of Economics.
Flaws of the TV journalist's voice and ways to eliminate them
Authors: Savostyanov Aleksandr Ivanovich
Published: July 2021

The article deals with the problem of a TV journalist's voice as one of the main components in his professional activity. The article points out its flaws and provides a number of exercises to eliminate them.
The cultural code of Europe: Antiquity and its "eternal return"
Authors: Kozyakova Mariya Ivanovna
Published: July 2021

The author demonstrates that cultural level raising, socialization, and disclosure of personal qualities are included in the context of the tasks of almost all educational institutions. The humanitarian component, which develops the human capital of any society, its intellectual, spiritual and moral potential, is especially important. Education of a person and a citizen takes place through familiarity with culture and its history, since culture is a sphere that "grows and nourishes the individual" (P.A. Florenskiy). The future specialist needs to develop universal competencies that complement the complex of professional ones. In this regard, we can speak about the presence of non-core disciplines that provide the necessary cultural competence of the individual, as well as about obtaining professional humanitarian training.
Procedural features of the consideration of disputes related to social partnership relations
Authors: Shemyakin R.K.
Published: July 2021

Based on the analysis of labor legislation and the civil procedure legislation of Russia, the article examines disputes related to social partnership relations. By the beginning of the 2020s, trade unions, as key participants in social dialogue, are unable to cope with their main task - to protect the rights and interests of workers. What are the procedural features of disputes over the protection of an indefinite number of persons by trade unions? This and other questions can be answered in the presented study.
Solution of social problems by the organization (private pension funds)
Authors: Shevchenko V.A. , Maksimova E.V.
Published: July 2021

The article discusses position and role of private (non-state) pension funds in solving social problems. Activity of private pension funds related to the investment of pension savings or use of funds from pension reserves is analyzed. Principles and goals of investing these funds, list of investment objects, as well as requirements for the structure of the investment portfolio are disclosed. Private pension funds are looking for opportunities for highly profitable investment options for collected receipts, because this will increase their attractiveness to potential clients (it will correspond to their macroeconomic function within the country’s economy), and will also meet the objective of increasing their own profit (within the framework of microeconomic function of the company as a business entity).
Measurements as part of a special assessment of working conditions on oil platforms
Authors: Volkovinsky Anatoly
Published: July 2021

Anatoly Volkovinsky, Leading Engineer of the Testing Laboratory of LLC "Service for Certification of Workplaces", talks about instrumental measurements of harmful and hazardous production factors as part of a special assessment of working conditions.
LA INTELIGENCIA DE NEGOCIOS: HERRAMIENTA CLAVE PARA EL USO DE LA INFORMACIÓN Y LA TOMA DE DECISIONES EMPRESARIALES
Authors: García-Jiménez Alejandra de-Jesús , Aguilar-Morales Norma , Hernández-Triano Leonardo , Lancaster-Díaz Eduardo
Published: July 2021

El entorno actual donde las empresas pequeñas y medianas se desarrollan, ha cambiado a raíz del efecto de apertura comercial surgido posterior a la segunda guerra mundial. El objetivo de este documento es analizar la aplicación de la Inteligencia de negocios como una herramienta clave para que las pequeñas y medianas empresas utilicen la información como un insumo de apoyo a la toma de decisiones empresariales. La metodología empleada fue la revisión documental como herramienta, con un enfoque cualitativo descriptivo en el que se utilizaron bases de datos científicas como Dialnet, ScienceDirect y Scielo; y palabras clave como Inteligencias de Negocios, Toma de decisiones, Información. Los criterios de inclusión son aquellos documentos que describan los atributos de la Inteligencia de Negocios, Toma de decisiones e Información para realizar un análisis teórico, crítico y comparativo de las aportaciones de los autores. Los resultados indican que la Inteligencia de Negocios tiene los siguientes componentes: proceso interactivo, explorar, analizar, almacenamiento, tecnología y comunicar. Se concluye que la Inteligencia de Negocios es una solución valorable y viable para las organizaciones pues a través de su uso y aplicación proveen un soporte de conocimiento a los tomadores de decisiones.