bluuebunny/crossref_metadata_2025 huggingface dataset:
The creation of autotetraploid provides insights into critical features of DNA methylome changes after genome doubling in water spinach (Ipomoea aquatica Forsk)
Authors: Hao Yuanyuan , Su Xiao , Li Wen , Li Lin , Zhang Yu , Mumtaz Muhammad Ali , Shu Huangying , Cheng Shanhan , Zhu Guopeng , Wang Zhiwei
Published: April 2023

Water spinach (Ipomoea aquatica Forsk) is an essential green leafy vegetable in Asia. In this study, we induced autotetraploid water spinach by colchicine. Furthermore, DNA methylation and transcriptome of tetraploid and diploid were compared using Whole Genome Bisulfite Sequencing (WGBS) and RNA-sequencing techniques. Autotetraploid water spinach was created for the first time. Compared with the diploid parent, autotetraploid water spinach had wider leaves, thicker petioles and stems, thicker and shorter adventitious roots, longer stomas, and larger parenchyma cells. The whole genome methylation level of the autotetraploid was slightly higher than that of the diploid. Compared with the diploid, 12281 Differentially Methylated Regions (DMRs)were found in the autotetraploid, including 2356 hypermethylated and 1310 hypomethylated genes, mainly enriched in ‘Arginine and Proline metabolism’, ‘beta − Alanine metabolism’, ‘Plant homone signal translation’, ‘Ribome’, and ‘Plant − pathgen interaction’ pathways. Correlation analysis of transcriptome and DNA methylation data showed that 121 differentially expressed genes undergone differential methylation, related to four pathways ‘Other types of O-glycan biosynthesis’, ‘Terpenoid backbone biosynthesis’, ‘Biosynthesis of secondary metabolites’, and ‘Metabolic paths’. This work obtained important autotetraploid resources of water spinach and revealed the genomic DNA methylation changes after genome doubling, being helpful for further studying the molecular mechanism of variations caused by polyploids of the Ipomoea genus.
Detection and distribution of two dominant alleles associated with the sweet kernel phenotype in almond cultivated germplasm
Authors: Lotti Concetta , Minervini Anna Paola , Delvento Chiara , Losciale Pasquale , Gaeta Liliana , Sánchez-Pérez Raquel , Ricciardi Luigi , Pavan Stefano
Published: April 2023

Almond [Prunus dulcis Miller (D. A. Webb), syn. Prunus amygdalus L.)] is the major tree nut crop worldwide in terms of production and cultivated area. Almond domestication was enabled by the selection of individuals bearing sweet kernels, which do not accumulate high levels of the toxic cyanogenic glucoside amygdalin. Previously, we showed that the Sweet kernel (Sk) gene, controlling the kernel taste in almond, encodes a basic helix loop helix (bHLH) transcription factor regulating the amygdalin biosynthetic pathway. In addition, we characterized a dominant allele of this gene, further referred to as Sk-1, which originates from a C1036→T missense mutation and confers the sweet kernel phenotype. Here we provide evidence indicating that the allele further referred to as Sk-2, originally detected in the cultivar “Atocha” and arising from a T989→G missense mutation, is also dominantly inherited and confers the sweet kernel phenotype in almond cultivated germplasm. The use of single nucleotide polymorphism (SNP) data from genotyping by sequencing (GBS) for population structure and hierarchical clustering analyses indicated that Sk-2 occurs in a group of related genotypes, including the widespread cultivar “Texas”, descending from the same ancestral population. KASP and dual label functional markers were developed for the accurate and high-throughput selection of the Sk-1 and Sk-2 alleles, and the genotyping of a panel of 134 almond cultivars. Overall, our results provide further insights on the understanding of the almond cultivation history. In addition, molecular marker assays and genotypic data presented in this study are expected to be of major interest for the conduction of almond breeding programs, which often need to select sweet kernel individuals in segregant populations.
A critical perspective on updating drug memories through the integration of memory editing and brain stimulation
Authors: Noël Xavier
Published: April 2023

Addiction is a persistent, recurring condition characterized by repeated relapses despite the desire to control drug use or maintain sobriety. The attainment of abstinence is hindered by persistent maladaptive drug-associated memories, which drive drug-seeking and use behavior. This article examines the preliminary evidence supporting the combination of non-invasive brain stimulation (NIBS) techniques and memory editing (or reconsolidation) interventions as add-on forms of treatment for individuals with substance-related disorders (SUD). Studies have shown that NIBS can modestly reduce drug use and craving through improved cognitive control or other undetermined reasons. Memory reconsolidation, a process by which a previously consolidated memory trace can be made labile again, can potentially erase or significantly weaken SUD memories underpinning craving and the propensity for relapse. This approach conveys enthusiasm while also emphasizing the importance of managing boundary conditions and null results for interventions found on fear memory reconsolidation. Recent studies, which align with the state-dependency and activity-selectivity hypotheses, have shown that the combination of NIBS and behavioral interventions holds promise for treating SUD by reducing self-reported and physiological aspects of craving. Effective long-term outcomes for this procedure require better identification of critical memories, a deeper understanding of the brain mechanisms underlying SUD and memory reconsolidation and overcoming any boundary conditions of destabilized memories. This will enable the procedure to be personalized to the unique needs of individual patients.
Does ethnicity influence dementia, stroke and mortality risk? Evidence from the UK Biobank
Authors: Bonnechère Bruno , Liu Jun , Thompson Alexander , Amin Najaf , van Duijn Cornelia
Published: April 2023

Introduction

The number of people with dementia and stroke is increasing worldwide. There is increasing evidence that there are clinically relevant genetic differences across ethnicities. This study aims to quantify risk factors of dementia, stroke, and mortality in Asian and black participants compared to whites.

Methods

272,660 participants from the UK Biobank were included in the final analysis, among whom the vast majority are white (n = 266,671, 97.80%), followed by Asian (n = 3,790, 1.35%), and black (n = 2,358, 0.84%) participants. Cumulative incidence risk was calculated based on all incident cases occurring during the follow-up of the individuals without dementia and stroke at baseline. We compared the allele frequency of variants in Asian and black participants with the referent ethnicity, whites, by chi-square test. Hierarchical cluster analysis was used in the clustering analysis. Significance level corrected for the false discovery rate was considered.

Results

After adjusting for risk factors, black participants have an increased risk of dementia and stroke compared to white participants, while Asians has similar odds to the white. The risk of mortality is not different in blacks and white participants but Asians have a decreased risk.

Discussion

The study provides important insights into the potential differences in the risk of dementia and stroke among different ethnic groups. Specifically, the study found that black individuals had a higher incidence of dementia and stroke compared to white individuals living in the UK. These findings are particularly significant as they suggest that there may be underlying factors that contribute to these differences, including genetic, environmental, and social factors. By identifying these differences, the study helps to inform interventions and policies aimed at reducing the risk of dementia and stroke, particularly among high-risk populations.
Two cases reports: Severe liver injury caused by 1,2,3-trichloropropane poisoning
Authors: Li Chen , Hu Jinhua , Su Haibin
Published: April 2023

Background

1,2,3-trichloropropane (TCP) poisoning can induce liver damage in humans and animals, but reports of severe liver injury and its histology are rare. We presented two cases of 1,2,3-TCP inhalation poisoning resulting in severe liver injury confirmed by exposure history, toxicology, biochemical index and pathology.

Case description

Two young male presented acute poisoning process with mild to moderate early symptoms, and developed severe jaundice and coagulation dysfunction after exposure to 1,2,3-TCP. The total bilirubin (TBIL) in case 1 and case 2 reached the peak value of 635.8 μmol/L and 437.1 μmol/L on the 25th and 22nd days, respectively. Their liver enzymes and international normalized ratio increased rapidly to peak and fell back, and TBIL remained at a high level. 1,2,3-TCP was detected in their blood, and their liver histology indicated severe necrosis of hepatocytes, infiltration of massive inflammatory cells, and cholestasis. They all finally recovered after a long time of treatment.

Conclusion

The two cases in this study demonstrate that 1,2,3-TCP inhalation poisoning without any protective measures can induce severe liver injury in humans.
Abrupt peaks in perceived risk of occasional drug use after changing the question order in a repeated self-administered survey
Authors: Pérez-Romero César , Barrio Gregorio , Hoyos Juan , Belza María J. , Regidor Enrique , Donat Marta , Politi Julieta , Guerras Juan Miguel , Pulido José
Published: April 2023

Background

Question-order changes in repeated surveys can distort comparisons. We want to describe the evolution of drug risk perceptions among Spanish adolescents and assessing whether the 2006 peaks in perceived risk of occasional drug use can be explained by question-order changes.

Methods

The subjects were secondary students from a biennial national survey during 2000–2012. A one-off intervention was applied in 2006, replacing the two-adjacent items on perceived risk of occasional and regular use of each drug by non-adjacent items. Annual prevalence of high-risk perception were obtained for occasional and regular use of cannabis, heroin, cocaine and ecstasy. Subsequently, the 2006 percent level change (PC) in such were estimated prevalence using segmented Poisson regression, adjusting for various student and parent covariates.

Results

The 2006 PC in prevalence of high-risk perception of occasional drug use ranged from +63% (heroin) to +83% (ecstasy). These PCs were very high in all considered subgroups. However, the 2006 PC in prevalence of high-risk perception of regular drug use ranged from 1% (heroin) to 12% (cannabis). The evolution of preventive interventions does not suggest alternative causal hypotheses for 2006 peaks other than question-order changes.

Conclusion

Within the cognitive heuristics framework, the 2006 spikes in perceived risk of occasional drug use were most likely due to a release of the anchor exerted by perceived risk of regular drug use over that of occasional use triggered by 2006 question-order changes. In repeated surveys it is inexcusable to pre-test the effect of any change in questionnaire format.
Daphnia as a model organism to probe biological responses to nanomaterials—from individual to population effects via adverse outcome pathways
Authors: Reilly Katie , Ellis Laura-Jayne A. , Davoudi Hossein Hayat , Supian Suffeiya , Maia Marcella T. , Silva Gabriela H. , Guo Zhiling , Martinez Diego Stéfani T. , Lynch Iseult
Published: April 2023

The importance of the cladoceran Daphnia as a model organism for ecotoxicity testing has been well-established since the 1980s. Daphnia have been increasingly used in standardised testing of chemicals as they are well characterised and show sensitivity to pollutants, making them an essential indicator species for environmental stress. The mapping of the genomes of D. pulex in 2012 and D. magna in 2017 further consolidated their utility for ecotoxicity testing, including demonstrating the responsiveness of the Daphnia genome to environmental stressors. The short lifecycle and parthenogenetic reproduction make Daphnia useful for assessment of developmental toxicity and adaption to stress. The emergence of nanomaterials (NMs) and their safety assessment has introduced some challenges to the use of standard toxicity tests which were developed for soluble chemicals. NMs have enormous reactive surface areas resulting in dynamic interactions with dissolved organic carbon, proteins and other biomolecules in their surroundings leading to a myriad of physical, chemical, biological, and macromolecular transformations of the NMs and thus changes in their bioavailability to, and impacts on, daphnids. However, NM safety assessments are also driving innovations in our approaches to toxicity testing, for both chemicals and other emerging contaminants such as microplastics (MPs). These advances include establishing more realistic environmental exposures via medium composition tuning including pre-conditioning by the organisms to provide relevant biomolecules as background, development of microfluidics approaches to mimic environmental flow conditions typical in streams, utilisation of field daphnids cultured in the lab to assess adaption and impacts of pre-exposure to pollution gradients, and of course development of mechanistic insights to connect the first encounter with NMs or MPs to an adverse outcome, via the key events in an adverse outcome pathway. Insights into these developments are presented below to inspire further advances and utilisation of these important organisms as part of an overall environmental risk assessment of NMs and MPs impacts, including in mixture exposure scenarios.
Enhancement of Agricultural Materials Separation Efficiency Using a Multi-Purpose Screw Conveyor-Separator
Authors: Hud Victor , Lyashuk Oleg , Hevko Ivan , Ungureanu Nicoleta , Vlăduț Nicolae-Valentin , Stashkiv Mykola , Hevko Olena , Pik Andriy
Published: April 2023

The technological process of agricultural production is inextricably linked to the movement of a large number of goods, ranging from the supply of raw materials to their conversion and delivery of finished products. In the implementation of freight flows at the enterprises of agro-industrial complexes and the complex mechanization of raw material conversion processes, the main role is played by systems of transport and technological machines, which include screw conveyors with the ability to convert materials. For this purpose, the simultaneous performance of transportation and separation processes has been studied. The results of the investigation include the construction and study of the mathematical model of the system «a screw of the screw conveyor—grain mixture and separation process» involving further experimental research. The study of the effectiveness of separating agricultural materials with a multifunctional screw conveyor-separator showed that for effective sifting, the selected rational values of the parameters lie within the following limits: angle of inclination of the sieve was 0–14°, and frequency of rotation of the working body was 300–700 rpm. Some rational parameters were obtained during the grain mixture separation process on the basis of an experimental study, namely: n = 380 rpm; q = 0.9–4.7 kg/h·cm2, γ = 0–14°; P = 0.22–0.7 kW, depending on the size of the working sieve (100 × 200 mm). These rational parameters will make it possible to increase the efficiency of agricultural materials separation by a screw conveyor separator, to achieve maximum productivity, and to reduce energy consumption compared to other sorting devices.
Effect of Row Spacing and Plant Density on Silage Maize Growth, Dry Matter Distribution and Yield
Authors: Fuksa Pavel , Hrevušová Zuzana , Szabó Ondřej , Hakl Josef
Published: April 2023

Maize growth in narrow rows provides a more uniform spatial arrangement, but it does not always lead to increasing yield. A four-year study was conducted to investigate the effect of row spacing on silage maize growth and yield during the growing season and at harvest time. A field experiment with conventional (0.70 m) and narrow rows (0.35 m) at a plant density of 92,000 plants ha−1 was evaluated in the years 2011–2014, and the interaction of row spacing × plant density (92,000 and 110,000 plants ha−1) was tested in 2013–2014. The narrow rows clearly demonstrated potential to support plant height and weight development, together with a higher stalk proportion, at around two months after seeding. However, these contrasts were lost in the later stages and at harvest time. Some potential for non-significantly higher dry matter yield (4.6–10.8%) was shown in the narrow rows in three years of the experiment, in association with lower losses in plant numbers, when compared to conventional row spacing. The potential of yield improvement in the narrow rows showed relationships with weather conditions during the second half of the growing season. In summary, under the growing conditions of the study region, narrow row spacing significantly promoted early plant development, but these effects did not persist until harvest, thus resulting in only limited success in yield improvement.
Study on the Regulation Mechanism of 1-MCP Combined with SO2 Treatment on Postharvest Senescence of Bamboo Shoots (Chimonobambusa quadrangularis) in Karst Mountain Area
Authors: Xu Jinyang , Ji Ning , Wang Rui , Ma Chao , Lei Jiqing , Zhang Ni , Liu Renchan , Deng Yunbing
Published: April 2023

Fresh bamboo shoots (Chimonobambusa quadrangularis) are subjected to senescence (e.g., lignification and browning) during postharvest storage. This study investigated the effects of 1-MCP and SO2 treatment on bamboo shoot senescence and its regulation mechanism in order to extend bamboo shoot storage time. 1-MCP and SO2 treatments significantly inhibited the browning and lignification of fresh bamboo shoots during storage, according to the results. Its lower browning index and lignin content are directly related to its lower lignin content compared to the CK control group. The browning index and lignin content of the 1-MCP + SO2 treatment during the late storage period were 90.55% and 81.50% of the CK treatment, respectively. The result of the in-depth analysis suggested that 1-MCP and SO2 treatments reduced nutrient loss and maintained the nutritional value of bamboo shoots by inhibiting respiration and physiological metabolism. The PPO activity was inhibited to inhibit the browning process. Moreover, the scavenging ability of ROS was enhanced, the accumulation of MDA was inhibited, and the senescence of bamboo shoots was delayed after higher contents of total flavonoids and ascorbic acid were maintained and the activities of ascorbic acid peroxidase and superoxide dismutase were stimulated. Furthermore, lignin biosynthesis was hindered, and the lignification of bamboo shoots was delayed after the activities of POD and PAL were inhibited. In brief, 1-MCP + SO2 treatment is capable of inhibiting the physiological metabolism, browning, and lignification of bamboo shoots, maintaining good quality during storage, and delaying the senescence of bamboo shoots. Clarifying the senescence mechanism of bamboo shoots is of great significance for expanding the bamboo shoot industry and slowing down rocky desertification in karst mountainous areas.
Insight into the Mechanisms of Carbapenem Resistance in Klebsiella pneumoniae: A Study on IS26 Integrons, Beta-Lactamases, Porin Modifications, and Plasmidome Analysis
Authors: Tseng Chien-Hao , Huang Yao-Ting , Mao Yan-Chiao , Lai Chung-Hsu , Yeh Ting-Kuang , Ho Chung-Mei , Liu Po-Yu
Published: April 2023

The emergence of carbapenem-resistant Klebsiella pneumoniae poses a significant threat to public health. In this study, we aimed to investigate the distribution and genetic diversity of plasmids carrying beta-lactamase resistance determinants in a collection of carbapenem-resistant K. pneumoniae blood isolates. Blood isolates of carbapenem-resistant K. pneumoniae bacteremia were collected and identified. Whole-genome sequencing, assembly and analysis were performed for the prediction of antimicrobial resistance determinants. Plasmidome analysis was also performed. Our plasmidome analysis revealed two major plasmid groups, IncFII/IncR and IncC, as key players in the dissemination of carbapenem resistance among carbapenem-resistant K. pneumoniae. Notably, plasmids within the same group exhibited conservation of encapsulated genes, suggesting that these plasmid groups may serve as conservative carriers of carbapenem-resistant determinants. Additionally, we investigated the evolution and expansion of IS26 integrons in carbapenem-resistant K. pneumoniae isolates using long-read sequencing. Our findings revealed the evolution and expansion of IS26 structure, which may have contributed to the development of carbapenem resistance in these strains. Our findings indicate that IncC group plasmids are associated with the endemic occurrence of carbapenem-resistant K. pneumoniae, highlighting the need for targeted interventions to control its spread. Although our study focuses on the endemic presence of carbapenem-resistant K. pneumoniae, it is important to note that carbapenem-resistant K. pneumoniae is indeed a global problem, with cases reported in multiple regions worldwide. Further research is necessary to better understand the factors driving the worldwide dissemination of carbapenem-resistant K. pneumoniae and to develop effective strategies for its prevention and control.
Use of Probiotics to Control Biofilm Formation in Food Industries
Authors: Tomé Andreia R. , Carvalho Fábio M. , Teixeira-Santos Rita , Burmølle Mette , Mergulhão Filipe J. M. , Gomes Luciana C.
Published: April 2023

Microorganisms tend to adhere to food contact surfaces and form biofilms, which serve as reservoirs for bacteria that can contaminate food. As part of a biofilm, bacteria are protected from the stressful conditions found during food processing and become tolerant to antimicrobials, including traditional chemical sanitisers and disinfectants. Several studies in the food industry have shown that probiotics can prevent attachment and the consequent biofilm formation by spoilage and pathogenic microorganisms. This review discusses the most recent and relevant studies on the effects of probiotics and their metabolites on pre-established biofilms in the food industry. It shows that the use of probiotics is a promising approach to disrupt biofilms formed by a large spectrum of foodborne microorganisms, with Lactiplantibacillus and Lacticaseibacillus being the most tested genera, both in the form of probiotic cells and as sources of cell-free supernatant. The standardisation of anti-biofilm assays for evaluating the potential of probiotics in biofilm control is of extreme importance, enabling more reliable, comparable, and predictable results, thus promoting significant advances in this field.
Influence of Redox and Dopamine Regulation in Cocaine-Induced Phenotypes Using Drosophila
Authors: Filošević Vujnović Ana , Rubinić Marko , Starčević Ivona , Andretić Waldowski Rozi
Published: April 2023

Reactive Oxidative Species (ROS) are produced during cellular metabolism and their amount is finely regulated because of negative consequences that ROS accumulation has on cellular functioning and survival. However, ROS play an important role in maintaining a healthy brain by participating in cellular signaling and regulating neuronal plasticity, which led to a shift in our understanding of ROS from being solely detrimental to having a more complex role in the brain. Here we use Drosophila melanogaster to investigate the influence of ROS on behavioral phenotypes induced by single or double exposure to volatilized cocaine (vCOC), sensitivity and locomotor sensitization (LS). Sensitivity and LS depend on glutathione antioxidant defense. Catalase activity and hydrogen peroxide (H2O2) accumulation play a minor role, but their presence is necessary in dopaminergic and serotonergic neurons for LS. Feeding flies the antioxidant quercetin completely abolishes LS confirming the permissive role of H2O2 in the development of LS. This can only partially be rescued by co-feeding H2O2 or the dopamine precursor 3,4-dihydroxy-L-phenylalanine (L-DA) showing coordinate and similar contribution of dopamine and H2O2. Genetic versatility of Drosophila can be used as a tool for more precise dissection of temporal, spatial and transcriptional events that regulate behaviors induced by vCOC.
Stray Magnetic Field Measurement Method of Magnetic Hysteresis Curve of Open-Ended Sensor and Actuator Cores
Authors: Kašper Patrik , Šmelko Miroslav , Kessler Jaroslav , Lipovský Pavol , Draganová Katarína
Published: April 2023

In the design and development of measurement systems, such as magnetometric security systems or sophisticated devices such as satellites, it is necessary to consider the magnetic properties of all its parts and components, especially if it contains any magnetometric subsystem. The magnetic parameters of the materials are generally well described by the manufacturers in relation to their unprocessed raw state. However, their magnetic properties change as the subsequent machining or heat treatment is performed. These behavioral reactions of the material may lead to changes in its hysteresis during the magnetization cycles. This effect is necessary to consider, especially in the case of metallic ribbons, the magnetic characteristics of which are usually estimated by measurements performed on toroidal cores. Since the magnetic properties of a toroidal core differ from the magnetic properties of the preferably used open-ended samples, the corresponding measurement method needs to be used to determine its magnetic characteristics. Therefore, in the proposed article, the authors present a stray magnetic field-based method and measuring workstation intended to measure the magnetic hysteresis curves of the ferromagnetic open-ended samples used in the applications concerning the magnetometric systems and stabilization subsystems of small satellites. The physical background of the measurement method is described in detail, as well as the hardware and software used. The magnetic hysteresis curves of a small satellite electromagnetic actuator were measured as an example of an open-ended ferromagnetic component produced from amorphous ribbons, the permeability of which differs in comparison to manufacturer-stated permeability of raw amorphous material. The results are supplemented by measurements of the core characteristics of the used magnetometer probe, as well as by the characteristics of the semi-produced materials used for the production of both investigated cores. The primary advantage of the presented measurement method lies in the ability of design validation prior to the production of the final component and its assembly.
Rare Variants Residing in Novel Cis-Acting Element in Visual System Homeobox 1 and Their Contribution in the Pathogenesis of Keratoconus
Authors: Alswailmi Farhan Khashim , Malik Rida Khursheed , Parrey Mujeeb Ur Rehman , Siddiqi Abdul Rauf , Karimulla Shaik , Alanezi Abdulkareem A. , Qamar Raheel , Azam Maleeha , Ahmad Ashfaq
Published: April 2023

(1) Background: The visual system homeobox 1 (VSX1) may contribute to the incidence of keratoconus (KC) in different populations. The present study investigated the role of VSX1 in autosomal recessive Pakistani families and sporadic KC patients using in silico analysis of the rare variants for the identification of the cis-acting elements in VSX1; (2) Methods: Mutation analysis of VSX1 was undertaken using Sanger sequencing of samples from seven KC families and 100 sporadic patients. In silico analysis of the rare variants and identification of cis-acting elements was determined using Human Splicing Finder (HSF), ESE finder, RESCUE-ESE and through Exon- Identity Element (EIEs) prediction software suits, combined with various algorithms to identify the effect of variations in splicing motifs; (3) Results: Screening of VSX1 did not reveal any novel mutation in the KC panel, but a synonymous polymorphism rs12480307 (c.546A>G; p.Ala182Ala) in exon three and 3′UTR rs76499395 (c.*496A>G) were observed in two separate probands. These polymorphisms were not found in any of the sporadic KC cases or 100 ethnically matched control samples. The analysis of these rare variants revealed a plausible role for these two single nucleotide polymorphisms (SNPs) in KC development through the identification of novel cis-acting elements, an exonic splicing enhancer element (ESE) and binding motifs for two micro RNAs, miRNA-203 binding and hsa-miR-3938, in the VSX1 gene structure; (4) Conclusions: Rare genetic variations in the VSX1 were found to have a potential contribution to KC development.
Recurrent Neural Network-Based Hybrid Modeling Method for Digital Twin of Boiler System in Coal-Fired Power Plant
Authors: Zhao Yanbo , Cai Yuanli , Jiang Haonan
Published: April 2023

Due to the simplified assumptions or unascertained equipment parameters, traditional mechanism models of boiler system in coal-fired power plant usually have predictive errors that cannot be ignored. In order to further improve the predictive accuracy of the model, this paper proposes a novel recurrent neural network-based hybrid modeling method for digital twin of boiler system. First, the mechanism model of boiler system is described through recurrent neural network (RNN) to facilitate training and updating parameters, while the interpretability of the model does not degenerate. Second, for the time-varying parameters in the mechanism model, the functional relationship between them and the state variables is constructed by neurons to improve the predictive accuracy. Third, the long short-term memory (LSTM) neural network model is established to describe the unascertained dynamic characteristics to compensate the predictive residual of the mechanism model. Fourth, the update architecture and training algorithm applicable to the hybrid model are established to realize the iterative optimization of model parameters. Finally, experimental results show that the hybrid modeling method proposed in this paper can improve the predictive performance of traditional models effectively.
A Ship Trajectory Prediction Model Based on Attention-BILSTM Optimized by the Whale Optimization Algorithm
Authors: Jia Hongyu , Yang Yaoyu , An Jintang , Fu Rui
Published: April 2023

Nowadays, maritime transportation has become one of the most important ways of international trade. However, with the increase in ship transportation, the complex maritime environment has led to frequent traffic accidents, causing huge economic losses and safety hazards. For ships in maritime transportation, collision avoidance and route planning can be achieved by predicting the ship’s trajectory, which can give crews warning to avoid dangers. How to predict the ship’s trajectory more accurately is of great significance for risk avoidance. However, existing ship trajectory prediction models suffer from problems such as poor prediction accuracy, poor applicability, and difficult hyperparameter design. To address these issues, this paper adopts the Bidirectional Long Short-Term Memory (BILSTM) model as the base model, as it considers contextual information of time-series data more comprehensively. Meanwhile, to improve the accuracy and fitness of complex ship trajectories, this paper adds an attention mechanism to the BILSTM model to improve the weight of key information. In addition, to solve the problem of difficult hyperparameter design, this paper optimizes the hyperparameters of the Attention-BILSTM network by fusing the Whale Optimization Algorithm (WOA). In this paper, the AIS data are filtered, and the trajectory is complemented by the cubic spline interpolation method. Using the pre-processed AIS data, this WOA-Attention-BILSTM model is compared and assessed with traditional models. The results show that compared with other models, the WOA-Attention-BILSTM prediction model has high prediction accuracy, high applicability, and high stability, which provides an effective and feasible method for ship collision avoidance, maritime surveillance, and intelligent shipping.
Variations in Gold Nanoparticle Size on DNA Damage: A Monte Carlo Study Based on a Multiple-Particle Model Using Electron Beams
Authors: Santiago Christine A. , Chow James C. L.
Published: April 2023

Research is currently focused on maximizing cancer cell death while minimizing harm to healthy cells. Gold nanoparticles (GNPs) have been extensively studied as a radiosensitizer to improve cancer cell death while sparing normal tissue. Previous research and simulations have demonstrated that the presence of a single GNP increases DNA damage and dose. In this study, a Monte Carlo simulation using the Geant4-DNA code was used to investigate the effects of multiple GNPs on DNA damage when exposed to electron beams with energies of 50, 100, 150, and 200 keV. The study examined DNA damage caused by 1–4 GNPs of the same total volume by analyzing both single- and double-strand breaks. The results indicate that increasing the number of GNPs and decreasing the electron beam energy increases the total number of strand breaks. Although DNA damage increased, the proportion of double-strand breaks remained unchanged in relation to the total number of strand breaks.
Review of Transition from Mining 4.0 to Mining 5.0 Innovative Technologies
Authors: Zhironkin Sergey , Ezdina Natalya
Published: April 2023

The sustainable provision of mankind with energy and mineral raw materials is associated with an increase not only in industrial but also in the ecological and economic development of the raw material sector. Expanding demand for energy, metals, building and chemical raw materials on the one hand, and the deterioration of the living environment along with a growth of raw materials extraction on the other, put the human-centric development of mining at the forefront. This forms a transition trend from Mining 4.0 technologies such as artificial intelligence, big data, smart sensors and robots, machine vision, etc., to Mining 5.0, presented with collaborative robots and deserted enterprises, bioextraction of useful minerals, postmining, and revitalization of mining areas. This “bridge” is formed by the technological convergence of information, cognitive, and biochemical technologies with traditional geotechnology, which should radically change the role of the resource sector in the economy and society of the 21st century. The transition from Mining 3.0 to 4.0 cannot be considered complete. However, at the same time, the foundation is already being laid for the transition to Mining 5.0, inspired, on the one hand, by an unprecedented gain in productivity, labor safety, and predictability of commodity markets, on the other hand, by the upcoming onset of Industry 5.0. This review provides a multilateral observation of the conditions, processes, and features of the current transition to Mining 4.0 and the upcoming transformation on the Mining 5.0 platform, highlighting its core and prospects for replacing humans with collaborated robots and artificial intelligence. In addition, the main limitations of the transition to Mining 5.0 are discussed, the overcoming of which is associated with the development of green mining and ESG (environment, social, and governance) investment.
HDLNIDS: Hybrid Deep-Learning-Based Network Intrusion Detection System
Authors: Qazi Emad Ul Haq , Faheem Muhammad Hamza , Zia Tanveer
Published: April 2023

Attacks on networks are currently the most pressing issue confronting modern society. Network risks affect all networks, from small to large. An intrusion detection system must be present for detecting and mitigating hostile attacks inside networks. Machine Learning and Deep Learning are currently used in several sectors, particularly the security of information, to design efficient intrusion detection systems. These systems can quickly and accurately identify threats. However, because malicious threats emerge and evolve regularly, networks need an advanced security solution. Hence, building an intrusion detection system that is both effective and intelligent is one of the most cognizant research issues. There are several public datasets available for research on intrusion detection. Because of the complexity of attacks and the continually evolving detection of an attack method, publicly available intrusion databases must be updated frequently. A convolutional recurrent neural network is employed in this study to construct a deep-learning-based hybrid intrusion detection system that detects attacks over a network. To boost the efficiency of the intrusion detection system and predictability, the convolutional neural network performs the convolution to collect local features, while a deep-layered recurrent neural network extracts the features in the proposed Hybrid Deep-Learning-Based Network Intrusion Detection System (HDLNIDS). Experiments are conducted using publicly accessible benchmark CICIDS-2018 data, to determine the effectiveness of the proposed system. The findings of the research demonstrate that the proposed HDLNIDS outperforms current intrusion detection approaches with an average accuracy of 98.90% in detecting malicious attacks.
Special Issue on Geotechnical Engineering Hazards
Authors: Kalatehjari Roohollah
Published: April 2023

Geotechnical engineering is a complex field that deals with various hazards that can impact soil, rock, and other geologic materials [...]
A Dynamic Grid Index for CkNN Queries on Large-Scale Road Networks with Moving Objects
Authors: Tang Kailei , Dong Zhiyan , Shi Wenxiang , Gan Zhongxue
Published: April 2023

As the Internet of Things devices are deployed on a large scale, location-based services are being increasingly utilized. Among these services, kNN (k-nearest neighbor) queries based on road network constraints have gained importance. This study focuses on the CkNN (continuous k-nearest neighbor) queries for non-uniformly distributed moving objects with large-scale dynamic road network constraints, where CkNN objects are continuously and periodically queried based on their motion evolution. The present CkNN high-concurrency query under the constraints of a super-large road network faces problems, such as high computational cost and low query efficiency. The aim of this study is to ensure high concurrency nearest neighbor query requests while shortening the query response time and reducing global computation costs. To address this issue, we propose the DVTG-Index (Dynamic V-Tree Double-Layer Grid Index), which intelligently adjusts the index granularity by continuously merging and splitting subgraphs as the objects move, thereby filtering unnecessary vertices. Based on DVTG-Index, we further propose the DVTG-CkNN algorithm to calculate the initial kNN query and utilize the existing results to speed up the CkNN query. Finally, extensive experiments on real road networks confirm the superior performance of our proposed method, which has significant practical applications in large-scale dynamic road network constraints with non-uniformly distributed moving objects.
The Time Variation Law of Concrete Compressive Strength: A Review
Authors: Wang Weina , Yue Qingxia
Published: April 2023

Concrete is a building material that is most widely used because of its excellent mechanical performance and durability. Compressive strength is an essential property of concrete, which changes with time under various factors. In this paper, the time variation law of the compressive strength of concrete was reviewed from three aspects: single, multiple and material internal factors. The mathematical models of compressive strength relative to time under single factors such as carbonization, freeze–thaw cycle, temperature effect and sulfate attack were summarized. Based on the statistical analysis of laboratory experimental data and field test data, the time variation laws of concrete under the coupling action of two or more factors were analyzed. The results show that the strength loss of concrete under the coupling effect of multiple factors is more serious than under the effect of a single factor. In addition, the time variation models of compressive strength in existing buildings were discussed, and it was observed that there are obvious differences between these models. After analysis, it is known that the different data sources and normalization methods are the primary causes of differences. Finally, the influences of concrete internal factors on compressive strength were outlined. The main conclusions of the time variation law of compressive strength were summarized, and further research directions were also proposed.
CVMan: A Framework for Clone-Incurred Vulnerability Management
Authors: Shi Jian , Zou Deqing , Xu Shouhuai , Jin Hai
Published: April 2023

Software clones may cause vulnerability proliferation, which highlights the importance of investigating clone-incurred vulnerabilities. In this paper, we propose a framework for automatically managing clone-incurred vulnerabilities. Two innovations of the framework are the notion of the spatial clone-relation graph, which describes clone-based relationships between software programs, and the temporal clone-relation graph, which describes the evolution of clones in software over time. As a case study, we apply the framework to analyze eight versions of Ubuntu while drawing a number of insights, such as: (i) clones are prevalent with about one-sixth of the codebase being clones; (ii) intra-program clones are often attributed to polymorphisms or functional similarities between procedures, while inter-program clones are often attributed to shared code repositories and the reuse of libraries; (iii) the clone surface of Linux remains stable at around 0.6, meaning that spatial and temporal clones in Linux account for about 60% of the codebase, while the lifetime of 53% clones spans eight versions; and (iv) the clone-incurred vulnerability surface in Linux is small, while vulnerable clones and non-vulnerable clones have similar lifetimes.
Reliability Prediction and FMEA of Loading and Unloading Truss Robot for CNC Punch
Authors: Zhang Kaiyue , Jia Zhixin , Bian Renpeng , He Ketai , Jia Zhicheng
Published: April 2023

Loading and unloading truss robot for computer numerical control (CNC) punch is widely used in the production of sheet metal parts, as its reliability level is directly related to the quality of sheet metal parts. Especially for the automatic sheet metal production line, it is urgent to predict the reliability of the loading and unloading truss robot for CNC punch. In this paper, a new method for the reliability prediction of the loading and unloading truss robot for CNC punch is proposed. The method uses the component counting method to predict the failure rate and mean time between failures (MTBF) of the electrical control system. Then, according to the MTBF value of the electrical control system, the MTBF value and failure rate of the mechanical system and pneumatic system are calculated by expert scoring method based on fuzzy theory. The MTBF value and failure rate of the loading and unloading truss robot for CNC punch are estimated, and the weak link of the loading and unloading truss robot for CNC punch is obtained. Finally, through the collected fault maintenance data records, the failure modes and effects analysis (FMEA) of the loading and unloading truss robot for CNC punch is carried out, and the reliability prediction method proposed in this paper is validated by the fault location analysis results.
Rapid Synthesis of Silver Nanowires in the Polyol Process with Conventional and Microwave Heating
Authors: Dzido Grzegorz , Smolska Aleksandra , Farooq Muhammad Omer
Published: April 2023

Silver nanowires (AgNWs) represent an excellent material for many advanced applications due to their thermal and electrical properties. However, synthesising materials with the desired characteristics requires knowledge of the parameters affecting their size and an appropriate fabrication method. This paper presents a study on the synthesis of silver nanowires using the polyol process by conventional and microwave heating. Various polyols (1,2-ethanediol, 1,3-propanediol, 1,3-butanediol, 1,4-butanediol, 1,5-pentanediol) with different viscosities and dielectric properties were used as reductants. It resulted in nanowires with an average diameter of 119–198 nm. It was found that, in contrast to the viscosity and dielectric constant of the alcohol used, the heating method had a limited effect on the average diameter and length value of the final product. The performed studies indicate an optimal strategy for fabricating one-dimensional silver nanostructures using the polyol method.
Controller for an Asymmetric Underactuated Hovercraft in Terms of Quasi-Velocities
Authors: Herman Przemyslaw
Published: April 2023

In this paper, a nonlinear controller for tracking a desired trajectory for an underactuated hovercraft is considered. It is a modification of a method known from the literature. However, the control algorithm considered here has two important features that differ from the mentioned control strategy. First, it concerns the case when the center of mass does not coincide with the geometric center, which results in additional forces and moments of force. The lack of symmetry causes the original trajectory tracking method not to take this fact into account, while the proposed approach is a generalization of the known concept. Here, a diagonalization of the inertia matrix has been applied, by means of a velocity transformation, which made it possible to reduce the symmetric matrix to a diagonal form. Secondly, the transformed quasi-velocity equations of motion allow some insight into the dynamics of the vehicle as it moves, which was not shown in the source work. The offered approach was verified by numerical tests for a hovercraft model with three DOF and for two desired trajectories. The method can be useful in preliminary simulation studies at the controller selection stage without experimental validation.
Enhanced Herbicide Metabolism and Target-Site Mutations Confer Multiple Resistance to Fomesafen and Nicosulfuron in Amaranthus retroflexus L.
Authors: Yang Cheng , Wang Hao , Duan Yunxia , Bei Feng , Jia Sisi , Wang Jinxin , Wang Hengzhi , Liu Weitang
Published: April 2023

Amaranthus retroflexus L. is a highly competitive broadleaf weed of corn–soybean rotation in northeastern China. In recent years, the herbicide(s) resistance evolution has been threatening its effective management in crop fields. One resistant A. retroflexus (HW-01) population that survived the protoporphyrinogen oxidase (PPO) inhibitor fomesafen and acetolactate synthase (ALS) inhibitor nicosulfuron applied at their field-recommended rate was collected from a soybean field in Wudalianchi City, Heilongjiang Province. This study aimed to investigate the resistance mechanisms of fomesafen and nicosulfuron and determine the resistance profile of HW-01 to other herbicides. Whole plant dose–response bioassays revealed that HW-01 had evolved resistance to fomesafen (50.7-fold) and nicosulfuron (5.2-fold). Gene sequencing showed that the HW-01 population has a mutation in PPX2 (Arg-128-Gly) and a rare mutation in ALS (Ala-205-Val, eight/twenty mutations/total plants). In vitro enzyme activity assays showed that ALS extracted from the HW-01 plants was less sensitive to nicosulfuron (3.2-fold) than ST-1 plants. Pre-treatment with the cytochrome P450 inhibitors malathion, piperonyl butoxide (PBO), 3-amino-1,2,4-triazole (amitrole), and the GSTs inhibitor 4-chloro-7-nitrobenzofurazan (NBD-Cl) significantly increased fomesafen and nicosulfuron sensitivity in the HW-01 population compared with that of the sensitive (S) population ST-1. Moreover, the rapid fomesafen and nicosulfuron metabolism in the HW-01 plants was also confirmed via HPLC-MS/MS analysis. Furthermore, the HW-01 population showed multiple resistance (MR) to PPO, ALS, and PSII inhibitors, with resistance index (RI) values ranging from 3.8 to 9.6. This study confirmed MR to PPO-, ALS-, and PSII-inhibiting herbicides in the A. retroflexus population HW-01, as well as confirming that the cytochrome P450- and GST-based herbicide metabolic along with TSR mechanisms contribute to their multiple resistance to fomesafen and nicosulfuron.