bluuebunny/crossref_metadata_2025 huggingface dataset:
The Promotive Effect of Putrescine on Growth, Biochemical Constituents, and Yield of Wheat (Triticum aestivum L.) Plants under Water Stress
Authors: Hussein Hebat-Allah A. , Alshammari Shifaa O. , Abd El-Sadek Marwa E. , Kenawy Sahar K. M. , Badawy Ali A.
Published: February 2023

Drought stress is a significant environmental variable affecting wheat growth and development. Plant stress tolerance is intimately related to growth regulators of plants as polyamines. The study assessed the impact of drought (50% water irrigation and 100% water irrigation), priming of grains in putrescine (0.25, 0.5, and 1 mM), and their interactions on the growth, yield, and physiological attributes of wheat plants. Drought conditions declined plant height, fresh and dry weights, leaves and tillers numbers, and flag leaf area. However, applying putrescine, especially at (1 mM), enhanced wheat growth performance in normal or water-deficit conditions. Drought stress decreased spike length (28.6%), number of spikelets (15.6%), number of grains (30.3%), the weight of the spike (23.5%), and the weight of the grains/spike (37.5%). In addition, drought decreased the contents of chlorophyll a, chlorophyll b, free amino acids, and total phenols, while applying putrescine enhanced wheat plant growth performance in normal or drought conditions. Putrescine at (1 mM) achieved the highest increase in plant height (38.8%), root length (50%), leaves number (166%), tillers number (80%), flag leaf area (70.3%), shoot fresh weight (99.4%), shoot dry weight (98.4%), root fresh weight (97.8%), root dry weight (210%) compared to the untreated plants. Moreover, pretreatment with putrescine improved chlorophyll a (13.3%), chlorophyll b (70.3%), carotenoids (61.8%), soluble sugars (49.1%), amino acids (42.7%), phenols (52.4%), number of spikelets (59.3%), number of grains (81.1%), and weight of spike (45.4%). Moreover, variations in the protein profile of wheat plants were due to drought conditions and putrescine application. In conclusion, priming wheat grains with putrescine effectively induces protective mechanisms against water stress and improves wheat plants’ physiological attributes and yield components.
Non-Target Site Resistance in Summer-Emerging Lolium rigidum and the Effect of Alternative Herbicides
Authors: Thompson Michael , Chauhan Bhagirath S.
Published: February 2023

Herbicide resistance is an important weed management issue. Glyphosate is the most dominant herbicide, which controls a broad spectrum of weeds, including grasses such as Lolium rigidum. Lolium rigidum is a major weed of winter crops in Australia that is developing glyphosate resistance in increasing numbers of populations and has been observed growing throughout summer in recent years. Three L. rigidum populations, one summer-emerging glyphosate-resistant (GR), one winter-emerging glyphosate-susceptible (GS), and one winter-emerging population with unknown resistance status (CC04), were analyzed for target-site resistance to glyphosate after confirming their resistance or susceptibility to glyphosate in a dose–response experiment. Population GR was obtained from plants that emerged in summer and contained plants that survived all rates of glyphosate applied (0 to 4560 g a.e. ha−1). It was found to be 6.1 and 4.4 times more resistant than population GS across two experiments. Population CC04 was identified as susceptible. Plants from each population were analyzed for the presence of target-site mutations in the conserved region of the EPSPS gene; however, no mutations were identified that could cause resistance, suggesting non-target-site resistance in population GR. The effectiveness of alternative herbicides was also analyzed for each population. Paraquat was the most effective herbicide, with 0% survival across all populations. The ACCase-inhibiting herbicide clethodim was also highly effective (0 to 8% survival across populations). Other ACCase-inhibiting herbicides, propaquizafop, haloxyfop, and pinoxaden, were effective at controlling the two susceptible populations, CC04 and GS (0 to 36% and 0 to 20% survival, respectively), but were only moderately effective for controlling GR (28 to 51% survival). Paraquat and clethodim may be alternative options for controlling GR populations of L. rigidum and could be effective for use in management programs to slow the development of GR populations.
Interactions of Microplastics with Pesticides in Soils and Their Ecotoxicological Implications
Authors: Peña Aránzazu , Rodríguez-Liébana José Antonio , Delgado-Moreno Laura
Published: February 2023

In the middle of the 20th century, the production of plastics exploded worldwide because of their low cost and the versatility of their applications. However, since plastic debris is highly resistant to environmental degradation, a growing presence of plastics in all the ecosystems has been confirmed. Among them, plastic particles < 5 mm, also known as microplastics (MPs), are of special concern because they are dispersed in aerial, terrestrial and aquatic environments, being the soil the main environmental sink of these contaminants. Due to their large specific surface area and hydrophobicity, MPs are considered good adsorbents for other environmental organic pollutants also present in terrestrial ecosystems, such as pharmaceuticals, personal-care products or pesticides with which they can interact and thus modify their environmental fate. In this review article, we examine the recent literature (from 2017 to 2022) to get a better understanding of the environmental fate of pesticides in soil (adsorption, mobility and/or degradation) when they are simultaneously present with MPs and the ecological risks on living organisms of the interactions between MPs and pesticides in soil. More studies are needed to fully understand the toxicological impact of the copresence in soil of pesticides and MPs.
Genome-Wide Identification and Expression Analysis of RCC1 Gene Family under Abiotic Stresses in Rice (Oryza sativa L.)
Authors: Cen Qiwen , Kang Lihua , Zhou Danni , Zhang Xian , Tian Quanxiang , Zhang Xiaoqin , Mou Wangshu , Dang Cong , Fang Yunxia , Xue Dawei
Published: February 2023

In plants, the essential roles played by the regulator of chromosome condensation 1 (RCC1) in diverse biological processes, including UV-B (ultraviolet-B radiation) response, hormonal signal transduction, cold tolerance and phenotypic plasticity, have been identified. No comprehensive study on the evolution and function of RCC1 gene family in rice has been carried out. A genome-wide analysis of this gene family is thus required. In this study, a total of 26 OsRCC1s unevenly distributed across 10 chromosomes were identified in rice. Based on their phylogenetic relationship and sequence composition, the OsRCC1 family could be classified into six groups. Members within the same group share a similar gene structure and protein motif/domain composition. Gene duplication analysis revealed that segmental duplication might be the main contributor to the expansion of the RCC1 gene family in rice. Several cis-regulatory elements (CREs) relevant to light, abscisic acid (ABA) and methyl jasmonate (MeJA) are abundant in the promoters of OsRCC1s. A large number of microRNA (miRNA) target sites were present in OsRCC1 mRNAs. Additionally, we used data from gene microarray and qRT-PCR to analyze the expression of OsRCC1 genes during various developmental stages and under abiotic stress conditions. OsRCC1s were found to be highly expressed in panicles and seeds, and most OsRCC1s were differentially expressed under abiotic stresses. Taken together, our study provides a systematic characterization of OsRCC1s and preliminarily explores their diversity as well as their biological functions. Evidence demonstrates that OsRCC1s may play vital roles in both development and abiotic stress response. The results presented here lay a foundation for further investigating the functions of OsRCC1s.
Weather-Based Statistical and Neural Network Tools for Forecasting Rice Yields in Major Growing Districts of Karnataka
Authors: Thimmegowda Mathadadoddi Nanjundegowda , Manjunatha Melekote Hanumanthaiah , Huggi Lingaraj , Shivaramu Huchahanumegowdanapalya Sanjeevaiah , Soumya Dadireddihalli Venkatappa , Nagesha Lingegowda , Padmashri Hejjaji Sreekanthamurthy
Published: February 2023

Two multivariate models were compared to assess their yield predictability based on long-term (1980–2021) rice yield and weather datasets over eleven districts of Karnataka. Simple multiple linear regression (SMLR) and artificial neural network models (ANN) were calibrated (1980–2019 data) and validated (2019–2020 data), and yields were forecasted (2021). An intercomparison of the models revealed better yield predictability with ANN, as the observed deviations were smaller (−37.1 to 21.3%, 4% mean deviation) compared to SMLR (−2.5 to 35.0%, 16% mean deviation). Further, district-wise yield forecasting using ANN indicated an underestimation of yield, with higher errors in Mysuru (−0.2%), Uttara Kannada (−1.5%), Hassan (−0.1%), Ballari (−1.5%), and Belagavi (−15.3%) and overestimations in the remaining districts (0.0 to 4.2%) in 2018. Likewise, in 2019 the yields were underestimated in Kodagu (−0.6%), Shivamogga (−0.1%), Davanagere (−0.7%), Hassan (−0.2%), Ballari (−5.1%), and Belagavi (−10.8%) and overestimated for the other five districts (0.0 to 4.8%). Such model yield underestimations are related to the farmers’ yield improvement practices carried out under adverse weather conditions, which were not considered by the model while forecasting. As the deviations are in an acceptable range, they prove the better applicability of ANN for yield forecasting and crop management planning in addition to its use for regional agricultural policy making.
Optimizing Management Practices under Straw Regimes for Global Sustainable Agricultural Production
Authors: Li Pengfei , Zhang Afeng , Huang Shiwei , Han Jiale , Jin Xiangle , Shen Xiaogang , Hussain Qaiser , Wang Xudong , Zhou Jianbin , Chen Zhujun
Published: February 2023

Straw input is a helpful approach that potentially improves soil fertility and crop yield to ensure food security and protect the ecological environment. Nevertheless, unreasonable straw input results in massive greenhouse gas (GHG) emissions, leading to climate change and global warming. To explore the optimum combination of straw input and management practices for achieving green agricultural production, a worldwide data set was created using 3452 comparisons from 323 publications using the meta-analysis method. Overall, straw input increased soil carbon and nitrogen components as compared with no straw input. Additionally, straw input significantly boosted crop yield and nitrogen use efficiency (NUE) by 8.86% and 22.72%, respectively, with low nitrogen fertilizer rate benefiting the most. The cumulative of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions increased by 24.81%, 79.30%, and 28.31%, respectively, when straw was added. Global warming potential (GWP) and greenhouse emission intensity (GHGI) increased with the application of straw, whereas net global warming potential (NGWP) decreased owing to soil carbon sequestration. Low straw input rate, straw mulching, application of straw with C/N ratio > 30, long-term straw input, and no-tillage combined with straw input all result in lower GHG emissions. The GWP and GHGI were strongly related to area-scaled CH4 emissions, but the relationship with N2O emissions was weak. Straw application during the non-rice season is the most important measure for reducing CH4 emissions in paddy–upland fields. An optimum straw management strategy coupled with local conditions can help in climate change mitigation while also promoting sustainable agricultural production.
Rice Plants’ Resistance to Sheath Blight Infection Is Increased by the Synergistic Effects of Trichoderma Inoculation with SRI Management
Authors: Doni Febri , Isahak Anizan , Fathurrahman F. , Yusoff Wan Mohtar Wan
Published: February 2023

The capability of endophytic Trichoderma spp. to reduce sheath blight disease in rice caused by Rhizoctonia solani was assessed under the growth conditions established by practices of the System of Rice Intensification (SRI), compared to those of standard irrigated rice cultivation. Rice seeds inoculated with a local isolate of the fungus Trichoderma asperellum SL2 were grown under respective SRI and conventional conditions with the inoculated or uninoculated plants and then infected with the pathogen R. solani. It was seen that inoculation with this strain of Trichoderma protected rice plants against R. solani infection while enhancing plant growth, photosynthetic rate, and stomatal conductance. The biocontrol effectiveness of inoculation with a particular strain of Trichoderma was significantly greater under SRI management compared to conventional cultivation. This is the first report on how a crop management system, in this case, SRI, can influence the biocontrol effectiveness of Trichoderma spp.
Responses of Eight Differentially Heat Sensitive Tomato Cultivars against Chronic Ozone Exposure in the Indo-Gangetic Plain: Growth, Physiology, and Yield
Authors: Gupta Akanksha , Agrawal Shashi Bhushan , Agrawal Madhoolika
Published: February 2023

Tropospheric ozone (O3) is an important abiotic stress to plants and its rising concentration adversely affects crop yield. The studies associated with differential responses of tomato (Solanum lycopersicum L.) cultivars to chronic elevated O3 are lacking and need to be further explored for the recognition of O3 resistant cultivars as an adaptive strategy. In the present research, differentially heat sensitive tomato cultivars were treated with elevated O3 (ambient + 20 ppb) to determine their responses by estimating the foliar injury symptoms, variations in growth, physiology, reproductive and yield related attributes. All the tomato cultivars exhibited foliar injury symptoms under elevated O3 treatment, and the intensity of injury corroborated with yield loss. Elevated O3 treatment negatively impacted biomass, growth, physiological and reproductive characteristics of all cultivars. The hierarchal cluster analysis, cumulative stress response index and yield indices differentiated cultivars into sensitive, moderately sensitive and O3 tolerant categories. The thermotolerant, VRT02 and Kashi chayan cultivars (O3 resistant) demonstrated lower yield losses, whereas the thermotolerant (O3 sensitive) Superbug exhibited higher foliar injury, greater alterations in physiology, growth and reproductive traits resulting in greater yield losses than other cultivars. The cultivars with different heat sensitivity did not respond similarly towards O3 stress. Cultivars VRT 02 and Kashi chayan can be recommended for cultivation in areas experiencing high O3 vis-à-vis high temperature conditions.
Use of Olive Industry By-Products for Value-Added Food Development
Authors: García-Pastor María E. , Ródenas-Soriano Marina , Dobón-Suárez Alicia , Zapata Pedro J. , Giménez María J.
Published: February 2023

The olive industry involves environmental problems of special relevance, such as the generation of residual brines after the pickling process. Moreover, in the pitting and filling operations of the olives, fatty residues are generated that end up being washed away in the wastewater of these industries. The novelty of this work is based on the extraction of high value-added compounds from residues resulting from the industrialization process of olives, whose content in fatty acids, phenolic compounds and other substances could make them susceptible to being considered as a raw material of interest for the development or enrichment of other foods. The results obtained determined that the physico-chemical and functional characteristics of the oil and the brine, generated as by-products in the olive industry, indicated their potential as raw materials. For this reason, new formulations of the filling of olives (anchovy, red pepper, and lemon flavour) were developed, using the residual oil as a by-product, which showed greater global acceptability by consumers compared to a commercial stuffing made with sodium alginate. In addition, wastewater was used as a brine by-product to pickle three types of vegetables: carrot, cauliflower, and onion. All pickled vegetables showed the highest phenolic content and a higher overall liking, the differences being significant with respect to commercial reference. In conclusion, the results obtained could allow for the conversion of a by-product into a co-product, partially solving an environmental problem, and providing added value to the final product.
Precision Phenotyping of Agro-Physiological Responses and Water Use of Sorghum under Different Drought Scenarios
Authors: Tovignan Thierry Klanvi , Basha Yasmeen , Windpassinger Steffen , Augustine Sruthy Maria , Snowdon Rod , Vukasovic Stjepan
Published: February 2023

Understanding sorghum response to water stress at different developmental stages is important for developing sorghum varieties with improved tolerance to drought. This study set out to finely characterize key agro-physiological responses and water use of sorghum subjected to different drought scenarios. A greenhouse experiment was conducted using a DroughtSpotter facility that enables real-time quantification of water use by gravimetric tracking. Four different water treatments were assessed: (i) early vegetative drought stress (DS1), (ii) DS1 plus recovery (DS1R), (iii) late vegetative drought stress (DS2), and (iv) well-watered (WW). Plant pheno-morphology and yield data were recorded. Leaf fluorescence and photosynthesis were continuously recorded throughout the experiment. Our results showed that green leaf number and plant leaf area were more affected by DS2 than DS1 and delayed plant flowering. Nevertheless, plants in DS2 were taller and produced higher stem and leaf biomass compared to DS1. No significant difference was recorded in grain yield between DS1 and DS2 but were outperformed by DS1R and WW. The transpiration and photosynthetic rates were shown to decrease at the same time as the stomatal conductance. This can therefore be assimilated to a stomatal down-regulation limiting CO2 uptake. However, the increase in intercellular CO2 concentration is likely to indicate the presence of CO2 in the substomatal cavity that was not conveyed to the carboxylation sites. This suggests a non-stomatal limitation of the photosynthesis. Moreover, the plants recovered quite well from DS1, and this was more prominent for physiological parameters than morphological ones. Globally, water use efficiency (WUE) for DS2 was higher compared to WW and DS1 treatments, confirming the growing point differentiation as a critical stage where drought stress should be avoided to ensure yield and better WUE. Adaptation responses were related to the reduction of transpiration through plant leaf area reduction, the reduction of stomatal conductance, and the increase of intercellular CO2 limiting photosynthesis. Further studies focusing on the biomarkers of stress and transcriptomic analyses are needed to provide further insight into the drought adaptation mechanisms of this line.
Synergistic Antimicrobial Activity of Ceftriaxone and Polyalthia longifolia Methanol (MEPL) Leaf Extract against Methicillin-Resistant Staphylococcus aureus and Modulation of mecA Gene Presence
Authors: Ranjutha Valiappan , Chen Yeng , Al-Keridis Lamya Ahmed , Patel Mitesh , Alshammari Nawaf , Adnan Mohd , Sahreen Sumaira , Gopinath Subash C. B. , Sasidharan Sreenivasan
Published: February 2023

Medicinal plants are an essential source of traditional curatives for numerous skin diseases. Polyalthia longifolia (Sonn.) Thwaites (Annonaceae family) is a medicinal plant used to cure skin illnesses. P. longifolia is usually applied in folkloric therapeutical systems to treat skin diseases. The methicillin-resistant Staphylococcus aureus (MRSA) bacteria is among the essential bacteria contributing to skin diseases. Hence, to verify the traditional medicinal claim of P. longifolia usage in skin disease treatment, the current research was performed to study the synergistic antibacterial activity of standardized Polyalthia longifolia methanol leaf extract (MEPL) against MRSA bacteria. The synergistic antimicrobial activity result of ceftriaxone, when mixed with MEPL, against MRSA was investigated by the disc diffusion method, broth microdilution method, checkerboard dilution test, and modulation of mecA gene expression by multiplex polymerase chain reaction (multiplex PCR). The MEPL extract exhibited good synergistic antimicrobial activity against MRSA. Using the checkerboard method, we confirmed the synergistic effect of MEPL from P. longifolia and ceftriaxone (2:1) for MRSA with a marked reduction of the MIC value of the ceftriaxone from 8000 µg/mL to 1000 µg/mL. Moreover, the combination of MEPL with ceftriaxone significantly (p < 0.05) inhibited the presence of the resistant mecA gene in the tested strain. The LC–ESI–MS/MS analysis identified compounds that were reported to exhibit antimicrobial activity. Conclusively, the MEPL extract, an important etiological agent for skin diseases, showed worthy synergistic antimicrobial action against MRSA bacteria, thus supporting the traditional use of P. longifolia.
α-Pinene: Docking Study, Cytotoxicity, Mechanism of Action, and Anti-Biofilm Effect against Candida albicans
Authors: Bomfim de Barros Daniela , de Oliveira e Lima Luanna , Alves da Silva Larissa , Cavalcante Fonseca Mariana , Ferreira Rafael Carlos , Diniz Neto Hermes , da Nóbrega Alves Danielle , da Silva Rocha Walicyranison Plinio , Scotti Luciana , de Oliveira Lima Edeltrudes , Vieira Sobral Marianna , Cançado Castellano Lúcio Roberto , Moura-Mendes Juliana , Queiroga Sarmento Guerra Felipe , da Silva Márcia Vanusa
Published: February 2023

Candida albicans is associated with serious infections in immunocompromised patients. Terpenes are natural-product derivatives, widely studied as antifungal alternatives. In a previous study reported by our group, the antifungal activity of α-pinene against C. albicans was verified; α-pinene presented an MIC between 128–512 µg/mL. In this study, we evaluate time-kill, a mechanism of action using in silico and in vitro tests, anti-biofilm activity against the Candida albicans, and toxicity against human cells (HaCaT). Results from the molecular-docking simulation demonstrated that thymidylate synthase (−52 kcal mol−1), and δ-14-sterol reductase (−44 kcal mol−1) presented the best interactions. Our in vitro results suggest that α-pinene’s antifungal activity involves binding to ergosterol in the cellular membrane. In the time-kill assay, the antifungal activity was not time-dependent, and also inhibited biofilm formation, while rupturing up to 88% of existing biofilm. It was non-cytotoxic to human keratinocytes. Our study supports α-pinene as a candidate to treat fungal infections caused by C. albicans.
Bacterial Volatiles (mVOC) Emitted by the Phytopathogen Erwinia amylovora Promote Arabidopsis thaliana Growth and Oxidative Stress
Authors: Parmagnani Ambra S. , Kanchiswamy Chidananda Nagamangala , Paponov Ivan A. , Bossi Simone , Malnoy Mickael , Maffei Massimo E.
Published: February 2023

Phytopathogens are well known for their devastating activity that causes worldwide significant crop losses. However, their exploitation for crop welfare is relatively unknown. Here, we show that the microbial volatile organic compound (mVOC) profile of the bacterial phytopathogen, Erwinia amylovora, enhances Arabidopsis thaliana shoot and root growth. GC-MS head-space analyses revealed the presence of typical microbial volatiles, including 1-nonanol and 1-dodecanol. E. amylovora mVOCs triggered early signaling events including plasma transmembrane potential Vm depolarization, cytosolic Ca2+ fluctuation, K+-gated channel activity, and reactive oxygen species (ROS) and nitric oxide (NO) burst from few minutes to 16 h upon exposure. These early events were followed by the modulation of the expression of genes involved in plant growth and defense responses and responsive to phytohormones, including abscisic acid, gibberellin, and auxin (including the efflux carriers PIN1 and PIN3). When tested, synthetic 1-nonanol and 1-dodecanol induced root growth and modulated genes coding for ROS. Our results show that E. amylovora mVOCs affect A. thaliana growth through a cascade of early and late signaling events that involve phytohormones and ROS.
Designing a Large-Scale Immersive Visit in Architecture, Engineering, and Construction
Authors: Belaroussi Rachid , Dai Huiying , González Elena Díaz , Gutiérrez Jorge Martín
Published: February 2023

Throughout history, tools for engineering in the building industry have evolved. Due to the arrival of Industry 4.0, Computer-Aided Design (CAD) and Building Information Modeling (BIM) software have replaced the usage of pens, pencils, and paper in the design process. This paper describes the work required to design a large-scale immersive visit of a district under construction in a suburban area of Greater Paris, France. As part of this real estate project, called LaVallée, we have access to its city information model: all the BIMs of the works to be carried out including roads, terrain, street furniture, fountains, and landscaping. This paper describes all the technical operations necessary for the design of an immersive 3D model with a high level of detail of the neighborhood with its surroundings. The objective of this technical report was to provide practitioners with feedback on such an achievement based on industrial-level data. The development of the city model begins with the registration of all the BIMs from different firms in a common Geographic Information System: this gives the opportunity to confront the operational requirement of a construction phase and the actual current practice of architecture firms. A first prototype was developed using the archviz tool TwinMotion. In order to increase the realism of the model, we describe the creation of a pipeline in Unreal Engine with the automated tasks of material and mesh replacement and the lighting and landscape configuration. The main contribution of this work is to give relevant experience on building such a large-scale model, with the Python script when possible, as well as the necessary manual steps. It is a valuable contribution to the making of large-scale immersive visits with a high level of detail and their requirements.
Numerical Verification of the Drive-By Monitoring Method for Identifying Vehicle and Bridge Mechanical Parameters
Authors: Yamamoto Kyosuke , Shin Ryota , Mudahemuka Eugene
Published: February 2023

The PRE (numerical simulation-based vehicle and bridge parameter and road roughness estimation) method uses vehicle vibration data to identify the vehicle’s and bridge’s mechanical parameters and estimate road unevenness simultaneously. This method randomly assumes the mechanical parameters first. Secondly, it solves the vehicle’s IEP (input estimation problem) and the bridge’s DRS (dynamic response simulation) from the vehicle vibration data to obtain road profiles of the front and rear wheels. Repeat the random assumption of the mechanical parameters to minimize the residual between the obtained road unevenness because the road unevenness of the front and rear wheels are expected to match. To search for a better combination of the mechanical parameters, the MCMC (Monte Carlo Markov chain) algorithm is adopted in this paper. This paper also numerically simulates vehicle vibration data for the cases of the reduced-stiffness bridge model and examines whether this method can identify the position, range, and magnitude of stiffness reduction. The numerical simulation results show that bridge-stiffness reduction can be estimated reasonably.
Novel Design for Rotary Burner for Low-Quality Pellets
Authors: Holubcik Michal , Durcansky Peter , Jandacka Jozef , Najser Jan , Klacko Andrej
Published: February 2023

The burning of low-quality fuels causes several problems in the operation of combustion equipment, which can negatively affect the equipment’s efficiency. The possibilities for the burning of pellets made from low-quality raw materials are limited mainly by the fusibility of the ash, which settles and melts on the surfaces of the burner, gradually causing it to clog. Smelted ash also causes a decrease in heat transfer efficiency, which negatively affects the overall efficiency of the heat source. A possible solution is provided by burners with a rotating combustion chamber, where the contact time of the molten ash with the walls of the burner is shortened, and thus there is no significant melting of the ash in the burner. This manuscript is dedicated to summarizing the current state of development of burners with a rotary chamber, presenting a novel design for such a burner, and providing an analysis of that design. To conclude, the results of experimental measurements on a classic burner and a burner with a rotary chamber are presented, including a comparison and evaluation mainly in terms of emissions. The novel-designed rotary burner achieved a higher heat output than the retort burner, but a similar thermal efficiency. The rotary burner produced 32.5% lower CO emissions, 12.5% higher NOx emissions, 23% lower OGC emissions, and 44.7% higher PM emissions in comparison with a retort burner under the same conditions. This novel rotary burner concept could, after optimization, be a suitable option for efficient combustion of alternative biofuels.
Mathematical Modeling of Screw Press Configuration for Processing Safflower Oil
Authors: Mursalykova Maigul , Kakimov Mukhtarbek , Kassenov Amirzhan , Iskakov Bauyrzhan , Sergibayeva Zhadra , Kaspakov Esen , Zhumadilova Gulmira , Shulenova Assem , Kokayeva Gulnara , Suychinov Anuarbek
Published: February 2023

This article is devoted to modeling the pressing process of an experimental screw press for safflower oil production in small enterprises of the grain processing industry. The theoretical analysis for developing the process of oil pressing in a screw press is considered. Using methods of mathematical modeling, the problem of squeezing the liquid phase from dispersed material is described and solved. The basic scheme and characteristics of the press equipment and the principle of its work are presented. The proposed method of the theoretical calculation of the pressing process helps to determine the optimal parameters and to press safflower oil using the proposed design of the screw press. During the process of pressing, the highest value of oil yield is reached at the diaphragm gap of δ = 0.1 mm and screw rotation speed of ω = 6.2 rad/s.
Chidroid: A Mobile Android Application for Log Collection and Security Analysis in Healthcare and IoMT
Authors: Karagiannis Stylianos , Ribeiro Luís Landeiro , Ntantogian Christoforos , Magkos Emmanouil , Campos Luís Miguel
Published: February 2023

The Internet of Medical Things (IoMT) is a growing trend that has led to the use of connected devices, known as the Internet of Health. The healthcare domain has been a target of cyberattacks, especially with a large number of IoMT devices connected to hospital networks. This factor could allow attackers to access patients’ personal health information (PHI). This research paper proposes Chidroid, an innovative mobile Android application that can retrieve, collect, and distribute logs from smart healthcare devices. The proposed approach enables the creation of datasets, allowing non-structured data to be parsed into semi-structured or structured data that can be used for machine learning and deep learning, and the proposed approach can serve as a universal policy-based tool to examine and analyse security issues in most recent Android versions by distributing logs for analysis. The validation tests demonstrated that the application could retrieve logs and system metrics from various assets and devices in an efficient manner. The collected logs can provide visibility into the device’s activities and help to detect and mitigate potential security risks. This research introduces a way to perform a security analysis on Android devices that uses minimal system resources and reduces battery consumption by pushing the analysis stage to the edge.
Polarization Effect on the Performance of On-Chip Wireless Optical Point-to-Point Links
Authors: Calò Giovanna , Bellanca Gaetano , Fuschini Franco , Barbiroli Marina , Tralli Velio , Petruzzelli Vincenzo
Published: February 2023

Optical on-chip wireless interconnection is an emerging technology that aims to overcome the communication bottleneck in computing architectures and in which multiple processing units are exploited for data-intensive applications. In this work, we propose an integrated dielectric Vivaldi antenna, which exhibits the same gain performances for both TE and TM input polarizations. Point-to-point on-chip communication links between two Vivaldi antennas are analyzed. Moreover, the effect of wave polarization on the link performances is numerically studied in on-chip multilayer structures in connection with the multilayer characteristic parameters, i.e., cladding layer thickness and refractive index. The numerical results show that, with the same antenna gain, TM polarization is affected by lower propagation losses when suitable cladding layer thickness and refractive index are considered.
Blockchain-Based Decentralized Architecture for Software Version Control
Authors: Hammad Muhammad , Iqbal Jawaid , Hassan Ch Anwar ul , Hussain Saddam , Ullah Syed Sajid , Uddin Mueen , Malik Urooj Ali , Abdelhaq Maha , Alsaqour Raed
Published: February 2023

Version control is an important component of configuration management, and most enterprise-level software uses different tools and technologies to manage the software version control such as CVS, Subversion, or Perforce. Following the success of bitcoin, the first practical application of blockchain, it is being implemented in other fields such as healthcare, supply chains, financial management, real estate, electoral systems, and so on. Blockchain’s core features include decentralization, immutability, and interminability. Most version control repositories are centralized and can be modified by external sources, implying that they are in danger of being corrupted or controlled. In this study, we present the BDA-SCV architecture for implementing a version control system in blockchain technology. Our proposed approach would replace the necessity for a centralized system, with a decentralized approach implemented in the blockchain using distributed file storage, for which we will use the InterPlanetary File System (IPFS), which is a distributed file system. The proof of authority (PoA) consensus algorithm will be used to approve the developer communicating modifications to the private blockchain network; the authority will only provide permission and will not be able to add, edit, or delete code files. For each change, a ledger block will be created with a reference to the file stored in the distributed repository. A block cannot be manipulated once it has been created. Smart contracts will be used to register developers, create blocks, and manage the repository. The suggested model is implemented using the Hyperledger Fabric network, and the developer and authorizer ends are built into the dotnet web application.
NFT Image Plagiarism Check Using EfficientNet-Based Deep Neural Network with Triplet Semi-Hard Loss
Authors: Prihatno Aji Teguh , Suryanto Naufal , Oh Sangbong , Le Thi-Thu-Huong , Kim Howon
Published: February 2023

Blockchain technology is used to support digital assets such as cryptocurrencies and tokens. Commonly, smart contracts are used to generate tokens on top of the blockchain network. There are two fundamental types of tokens: fungible and non-fungible (NFTs). This paper focuses on NFTs and offers a technique to spot plagiarism in NFT images. NFTs are information that is appended to files to produce distinctive signatures. It can be found in image files, real artifacts, literature published online, and various other digital media. Plagiarism and fraudulent NFT images are becoming a big concern for artists and customers. This paper proposes an efficient deep learning-based approach for NFT image plagiarism detection using the EfficientNet-B0 architecture and the Triplet Semi-Hard Loss function. We trained our model using a dataset of NFT images and evaluated its performance using several metrics, including loss and accuracy. The results showed that the EfficientNet-B0-based deep neural network with triplet semi-hard loss outperformed other models such as Resnet50, DenseNet, and MobileNetV2 in detecting plagiarized NFTs. The experimental results demonstrate sufficient to be implemented in various NFT marketplaces.
Experimental and Statistical Studies of the Microstructure Characteristics of Nano-Silica-Modified Silty Clay in the Qinghai–Tibet Plateau
Authors: Li Kunyu , Wang Chong , Li Jianguo , Xie Liang , Wu Yumo , Li Shuangyang
Published: February 2023

Nanomaterials have been widely used for improving the physicochemical properties of geomaterials. However, quantitative interpretation of the microscopic mechanisms is still not well understood. In this study, a statistical principle was applied to study the microscopic characteristics of nano-silica (NS) modified silty clay. We use mercury intrusion porosimetry (MIP) to measure the micro-pore parameters (median pore diameter and cumulative volume of pore diameters smaller than 0.1 µm) based on various NS-modified silty clays (NS mass contents 0, 0.25%, 1%, and 3%). The test results indicate two micro-pore parameters have significant randomness and uncertainty, and soil pores become smaller and more compacted. Furthermore, four potential probability distributions were selected to compare with measured data. All distributions agree excellently with the experimental data, and three distributions satisfy the hypothesis testing, except the Weibull distribution. Finally, according to the information spread estimation method and chi-square test effect evaluation indexes, the normal distribution was proposed because it has the optimal described effect for the statistical characteristics of NS-modified silty clay. These results have important implications for understanding the randomness and evolution of microstructures of NS geomaterials, which are helpful to guide the evaluation of freezing process and water transport in modified soils.
Performance Analysis of the Cylinder Gas Film Seal between Dual-Rotor Reverse Shafts Considering Lubrication and Centrifugal Expansion Effects
Authors: Zhao Shuaike , Su Hua
Published: February 2023

The cylinder gas film seal between dual-rotor reverse shafts is a new method for sealing aircraft engines that has excellent developmental prospects. We propose a novel method for determining if the sealing ring is fully fluid-lubricated using the average Reynolds equation. Considering surface roughness and centrifugal expansion, we calculated the dynamic pressure, gas film force and friction power consumption with and without inlet pressure differences for each of the four rotation modes. The gas film’s dynamic pressure effects were weakest when the dual rotors rotated in a reverse direction (Mode 3), with or without differences in inlet pressure, since solid contact is most likely to occur under counter-rotation. When the dual rotors were in counter-rotation with an inlet differential pressure of 80 kPa and fixed inner and outer rotor speeds (e.g., 3000 rpm), we calculated the minimum sealing ring film thickness, leakage rate, friction power consumption and gas film force. Changes in outer rotor speed greatly influenced the minimum film thickness and the sealing ring’s performance. Meanwhile, changes in the inner rotor speed had little influence on the minimum film thickness and sealing ring’s lubrication performance. When the speed difference was fixed and the sealing ring was fully fluid-lubricated, lubrication performance changes were mainly affected by changes in centrifugal expansion caused by the outer rotor speed. Given a fixed rotor speed and under dual-rotor counter-rotation, we calculated the effects of inlet differential pressure changes on minimum gas film thickness, leakage rate, friction power consumption, gas film force and other sealing performance variables. Leakage rate and the friction power consumption increase as inlet differential pressure increases. Our results provide a theoretical reference for avoiding solid contact of the cylinder seal between dual-rotor reverse shafts.
Comparative Analysis of Primary Photosynthetic Reactions Assessed by OJIP Kinetics in Three Brassica Crops after Drought and Recovery
Authors: Antunović Dunić Jasenka , Mlinarić Selma , Pavlović Iva , Lepeduš Hrvoje , Salopek-Sondi Branka
Published: February 2023

Plant drought tolerance depends on adaptations of the photosynthetic apparatus to changing environments triggered by water deficit. The seedlings of three Brassica crops differing in drought sensitivity, Brassica oleracea L. var. capitata—white cabbage, Brassica oleracea L. var. acephala—kale, and Brassica rapa L. var. pekinensis—Chinese cabbage, were exposed to drought by withholding water. Detailed insight into the photosynthetic machinery was carried out when the seedling reached a relative water content of about 45% and after re-watering by analyzing the OJIP kinetics. The key objective of this study was to find reliable parameters for distinguishing drought−tolerant and drought-sensitive varieties before permanent structural and functional changes in the photosynthetic apparatus occur. According to our findings, an increase in the total performance index (PItotal) and structure–function index (SFI), positive L and K bands, total driving forces (ΔDF), and drought resistance index (DRI) suggest drought tolerance. At the same time, susceptible varieties can be distinguished based on negative L and K bands, PItotal, SFI, and the density of reaction centers (RC/CS0). Kale proved to be the most tolerant, Chinese cabbage was moderately susceptible, and white cabbage showed high sensitivity to the investigated drought stress. The genetic variation revealed among the selected Brassica crops could be used in breeding programs and high-precision crop management.
Hierarchical LSTM-Based Network Intrusion Detection System Using Hybrid Classification
Authors: Han Jonghoo , Pak Wooguil
Published: February 2023

Most existing network intrusion detection systems (NIDSs) perform intrusion detection using only a partial packet data of fixed size, but they suffer to increase the detection rate. In this study, in order to find the cause of a limited detection rate, accurate intrusion detection performance was analyzed by adjusting the amount of information used as features according to the size of the packet and length of the session. The results indicate that the total packet data and all packets in the session should be used for the maximum detection rate. However, existing NIDS cannot be extended to use all packet data of each session because the model could be too large owing to the excessive number of features, hampering realistic training and classification speeds. Therefore, in this paper, we present a novel approach for the classifier of NIDSs. The proposed NIDS can effectively handle the entire packet information using the hierarchical long short-term memory and achieves higher detection accuracy than existing methods. Performance evaluation confirms that detection performance can be greatly improved compared to existing NIDSs that use only partial packet information. The proposed NIDS achieves a detection rate of 95.16% and 99.70% when the existing NIDS show the highest detection rate of 93.49% and 98.31% based on the F1-score using two datasets. The proposed method can improve the limitations of existing NIDS and safeguard the network from malicious users by utilizing information on the entire packet.
Occlusion Avoidance in a Simulated Environment Using Reinforcement Learning
Authors: Szemenyei Márton , Szántó Mátyás
Published: February 2023

Neural network-based solutions have revolutionized the field of computer vision by achieving outstanding performance in a number of applications. Yet, while these deep learning models outclass previous methods, they still have significant shortcomings relating to generalization and robustness to input disturbances, such as occlusion. Most existing methods that tackle this latter problem use passive neural network architectures that are unable to act on and, thus, influence the observed scene. In this paper, we argue that an active observer agent may be able to achieve superior performance by changing the parameters of the scene, thus, avoiding occlusion by moving to a different position in the scene. To demonstrate this, a reinforcement learning environment is introduced that implements OpenAI Gym’s interface, and allows the creation of synthetic scenes with realistic occlusion. The environment is implemented using differentiable rendering, allowing us to perform direct gradient-based optimization of the camera position. Moreover, two additional methods are also presented, one utilizing self-supervised learning to predict occlusion segments, and optimal camera positions, while the other learns to avoid occlusion using Reinforcement Learning. We present comparative experiments of the proposed methods to demonstrate their efficiency. It was shown, via Bayesian t-tests, that the neural network-based methods credibly outperformed the gradient-based avoidance strategy by avoiding occlusion with an average of 5.0 fewer steps in multi-object scenes.
A Manifold-Level Hybrid Deep Learning Approach for Sentiment Classification Using an Autoregressive Model
Authors: Ranjan Roop , Pandey Dilkeshwar , Rai Ashok Kumar , Singh Pawan , Vidyarthi Ankit , Gupta Deepak , Revanth Kumar Puranam , Mohanty Sachi Nandan
Published: February 2023

With the recent expansion of social media in the form of social networks, online portals, and microblogs, users have generated a vast number of opinions, reviews, ratings, and feedback. Businesses, governments, and individuals benefit greatly from this information. While this information is intended to be informative, a large portion of it necessitates the use of text mining and sentiment analysis models. It is a matter of concern that reviews on social media lack text context semantics. A model for sentiment classification for customer reviews based on manifold dimensions and manifold modeling is presented to fully exploit the sentiment data provided in reviews and handle the issue of the absence of text context semantics. This paper uses a deep learning framework to model review texts using two dimensions of language texts and ideogrammatic icons and three levels of documents, sentences, and words for a text context semantic analysis review that enhances the precision of the sentiment categorization process. Observations from the experiments show that the proposed model outperforms the current sentiment categorization techniques by more than 8.86%, with an average accuracy rate of 97.30%.