bluuebunny/crossref_metadata_2025 huggingface dataset:
The Strong Ekeland Variational Principle in Quasi-Pseudometric Spaces
Authors: Cobzaş Ştefan
Published: February 2024

Roughly speaking, Ekeland’s Variational Principle (EkVP) (J. Math. Anal. Appl. 47 (1974), 324–353) asserts the existence of strict minima of some perturbed versions of lower semicontinuous functions defined on a complete metric space. Later, Pando Georgiev (J. Math. Anal. Appl. 131 (1988), no. 1, 1–21) and Tomonari Suzuki (J. Math. Anal. Appl. 320 (2006), no. 2, 787–794 and Nonlinear Anal. 72 (2010), no. 5, 2204–2209)) proved a Strong Ekeland Variational Principle, meaning the existence of strong minima for such perturbations. Please note that Suzuki also considered the case of functions defined on Banach spaces, emphasizing the key role played by reflexivity. In recent years, an increasing interest was manifested by many researchers to extend EkVP to the asymmetric case, i.e., to quasi-metric spaces (see references). Applications to optimization, behavioral sciences, and others were obtained. The aim of the present paper is to extend the strong Ekeland principle, both Georgiev’s and Suzuki’s versions, to the quasi-pseudometric case. At the end, we ask for the possibility of extending it to asymmetric normed spaces (i.e., the extension of Suzuki’s results).
Inverse pH Gradient-Assay for Facile Characterization of Proton-Antiporters in Xenopus Oocytes
Authors: Belew Zeinu Mussa , Kanstrup Christa , Hua Chengyao , Crocoll Christoph , Nour-Eldin Hussam Hassan
Published: February 2024

Xenopus oocytes represent one of the most versatile model systems for characterizing the properties of membrane transporters. However, for studying proton-coupled antiporters, the use of Xenopus oocytes has so far been limited to so-called injection-based transport assays. In such assays, where the compound is injected directly into the oocytes’ cytosol and transport is detected by monitoring substrate efflux, poor control over internal diffusion and concentration are incompatible with mechanistic characterizations. In this study, we present an inverse pH-gradient transport assay. Herein, an outward-facing proton gradient enables the characterization of proton antiporters via facile import-based transport assays. We describe two approaches for establishing sustained outward-facing proton gradients across the oocyte membrane, namely by applying alkaline external conditions or through surprisingly stable carbonyl cyanide m-chlorophenyl-hydrazone (CCCP)-mediated acidification of the cytosol. Previously, genetic evidence has shown that DTX18 from Arabidopsis thaliana is essential for the deposition of the hydroxycinnamic acid amide p-coumaroylagmatine (coumaroylagmatine) defence compound on the leaf surface. However, direct evidence for its ability to transport coumarol-agmatine has not been provided. Here, using Xenopus oocytes as expression hosts, we demonstrate DTX18’s ability to transport coumaroyl-agmatine via both injection-based and inverse pH-gradient transport assays. Notably, by showing that DTX18 is capable of accumulating its substrate against its concentration gradient, we showcase the compatibility of the latter with mechanistic investigations.
Membrane-Associated Ubiquitin Ligase RING Finger Protein 152 Orchestrates Melanogenesis via Tyrosinase Ubiquitination
Authors: Ueda Ryota , Hashimoto Rina , Fujii Yuki , Menezes José C. J. M. D. S. , Takahashi Hirotaka , Takeda Hiroyuki , Sawasaki Tatsuya , Motokawa Tomonori , Tokunaga Kenzo , Fujita Hideaki
Published: February 2024

Lysosomal degradation of tyrosinase, a pivotal enzyme in melanin synthesis, negatively impacts melanogenesis in melanocytes. Nevertheless, the precise molecular mechanisms by which lysosomes target tyrosinase have remained elusive. Here, we identify RING (Really Interesting New Gene) finger protein 152 (RNF152) as a membrane-associated ubiquitin ligase specifically targeting tyrosinase for the first time, utilizing AlphaScreen technology. We observed that modulating RNF152 levels in B16 cells, either via overexpression or siRNA knockdown, resulted in decreased or increased levels of both tyrosinase and melanin, respectively. Notably, RNF152 and tyrosinase co-localized at the trans-Golgi network (TGN). However, upon treatment with lysosomal inhibitors, both proteins appeared in the lysosomes, indicating that tyrosinase undergoes RNF152-mediated lysosomal degradation. Through ubiquitination assays, we found the indispensable roles of both the RING and transmembrane (TM) domains of RNF152 in facilitating tyrosinase ubiquitination. In summary, our findings underscore RNF152 as a tyrosinase-specific ubiquitin ligase essential for regulating melanogenesis in melanocytes.
Hot Deformation Behavior and Microstructure Evolution of Al-7.92 Zn-1.64 Mg-2.00 Cu Alloy
Authors: Li Chen , Chen Canyang , Huang Ke , Huang Shiquan , Yi Youping
Published: February 2024

During the thermal deformation of aluminum alloy materials, the deformation conditions such as deformation volume, temperature and strain rate are important factors that influence the deformation mechanisms such as work hardening, dynamic recovery and dynamic recrystallization. Under the interaction of different deformation mechanisms, the properties of aluminum alloy materials will change significantly. In this study, isothermal hot compression experiments were conducted on the Al-7.92 Zn-1.64 Mg-2.00 Cu alloy to analyze its hot flow behavior (T = 250~450 °C, ɛ̇ = 0.001~1 s−1). The obtained flow behavior data were used to construct an Arrhenius-type constitutive equation and processing maps, investigating organizational evolution under diverse hot deformation conditions. The results show that the energy dissipation rate can reach 0.37 when the deformation temperature T = 380~450 °C and the strain rate ɛ̇ < 0.1 s−1, suggesting that the material is most suitable for thermal deformation processing at high temperatures and low strain rates. At a strain rate of 0.1 s−1 and a temperature of 450 °C, the percentage of recrystallized grains and substructures increased by 7.20% and 3.14%, respectively, compared to 300 °C, which is due to the severe dynamic recovery and dynamic recrystallization. At 350 °C and 0.1 s−1, there was a higher percentage of recrystallized grains and substructures, 5.44% and 5.87% higher, respectively, than at a strain rate of 1 s−1, indicating that the release of dislocation accumulation due to deformation storage energy will be more favored at low strain rates, which promotes the enhancement of the dynamic recrystallization mechanism.
Correlation between Surface Integrity and Low Cycle Fatigue Life of Machined Inconel 718
Authors: Cui Pengcheng , Liu Zhanqiang , Zhao Jinfu , Ren Xiaoping
Published: February 2024

This work aims to improve the surface integrity and LCF life of machined Inconel 718. The correlation between the LCF life of Inconel 718 and various states of machined surface integrity is explored. In this paper, the surface integrity of Inconel 718 specimens is enhanced by low-plasticity burnishing (LPB). The LCF life of specimens with different surface integrity is predicted using a micro–macro finite element method (FEM). Firstly, the LCF specimens with different surface integrity are machined by turning (turned specimen), polishing (matrix specimen), and LPB process (LPBed specimen). Secondly, the LCF experiment is carried out to reveal the effect of surface integrity on LCF life. Finally, the LCF micro–macro FEM model is proposed to predict the LCF of machined Inconel 718 specimens. The representative volume element (RVE) model is established based on the measured surface integrity and microstructure of Inconel 718 specimens. The effect of surface integrity on LCF life is transformed to equivalent load. The micro–macro FEM model combined with Tanaka–Mura dislocation crack initiation theory and extended finite element method (XFEM) is applied to predict the LCF life of the machined specimens. The study results show that the LCF life of LPBed specimens can be improved by 90.5% and 36.1% compared with that of turned specimens and polished matrix specimens, respectively. The errors between FEM prediction results and experimental results are 13.1%, 9.2%, and 12.2%, respectively. The proposed micro–macro FEM model could be utilized to predict the LCF life of Inconel 718 with different surface integrities, and to apply the LCF life prediction further in industry.
Fatigue Life Estimation Model of Repaired Components with the Expanded Stop-Hole Technique
Authors: Velilla-Díaz Wilmer , Pinzón Roger , Guillén-Rujano Renny , Pérez-Ruiz José David , de Lacalle Luis Norberto López , Palencia Argemiro , Maury Heriberto , Zambrano Habib R.
Published: February 2024

Fatigue crack growth tests are conducted to assess the efficacy of the stop-hole crack repair method. This straightforward and widely adopted technique involves drilling a hole at the crack tip and subsequently enlarging it using a pin inserted into the hole. A fracture mechanics-based model is proposed to estimate the extension of fatigue life achieved through the implementation of the stop-hole technique. The model’s predictions are validated using data obtained from fatigue crack growth tests conducted on both unrepaired and repaired M(T) specimens, following the guidelines outlined in the ASTM E647 standard. The error of the fracture mechanics-based model was 1.4% in comparison with the fatigue tests.
Genomic Features and Phylogenetic Analysis of Antimicrobial-Resistant Salmonella Mbandaka ST413 Strains
Authors: Benevides Valdinete P. , Saraiva Mauro M. S. , Nascimento Camila F. , Delgado-Suárez Enrique J. , Oliveira Celso J. B. , Silva Saura R. , Miranda Vitor F. O. , Christensen Henrik , Olsen John E. , Berchieri Junior Angelo
Published: February 2024

In recent years, Salmonella enterica subsp. enterica serovar Mbandaka (S. Mbandaka) has been increasingly isolated from laying hens and shell eggs around the world. Moreover, this serovar has been identified as the causative agent of several salmonellosis outbreaks in humans. Surprisingly, little is known about the characteristics of this emerging serovar, and therefore, we investigated antimicrobial resistance, virulence, and prophage genes of six selected Brazilian strains of Salmonella Mbandaka using Whole Genome Sequencing (WGS). Multi-locus sequence typing revealed that the tested strains belong to Sequence Type 413 (ST413), which has been linked to recent multi-country salmonellosis outbreaks in Europe. A total of nine resistance genes were detected, and the most frequent ones were aac(6′)-Iaa, sul1, qacE, blaOXA-129, tet(B), and aadA1. A point mutation in ParC at the 57th position (threonine → serine) associated with quinolone resistance was present in all investigated genomes. A 112,960 bp IncHI2A plasmid was mapped in 4/6 strains. This plasmid harboured tetracycline (tetACDR) and mercury (mer) resistance genes, genes contributing to conjugative transfer, and genes involved in plasmid maintenance. Most strains (four/six) carried Salmonella genomic island 1 (SGI1). All S. Mbandaka genomes carried seven pathogenicity islands (SPIs) involved in intracellular survival and virulence: SPIs 1-5, 9, and C63PI. The virulence genes csgC, fimY, tcfA, sscA, (two/six), and ssaS (one/six) were absent in some of the genomes; conversely, fimA, prgH, and mgtC were present in all of them. Five Salmonella bacteriophage sequences (with homology to Escherichia phage phiV10, Enterobacteria phage Fels-2, Enterobacteria phage HK542, Enterobacteria phage ST64T, Salmonella phage SW9) were identified, with protein counts between 31 and 54, genome lengths of 24.7 bp and 47.7 bp, and average GC content of 51.25%. In the phylogenetic analysis, the genomes of strains isolated from poultry in Brazil clustered into well-supported clades with a heterogeneous distribution, primarily associated with strains isolated from humans and food. The phylogenetic relationship of Brazilian S. Mbandaka suggests the presence of strains with high epidemiological significance and the potential to be linked to foodborne outbreaks. Overall, our results show that isolated strains of S. Mbandaka are multidrug-resistant and encode a rather conserved virulence machinery, which is an epidemiological hallmark of Salmonella strains that have successfully disseminated both regionally and globally.
Fish DNA Sensors for Authenticity Assessment—Application to Sardine Species Identification
Authors: Kakarelidou Myrto , Christopoulos Panagiotis , Conides Alexis , Kalogianni Despina P. , Christopoulos Theodore K.
Published: February 2024

Food and fish adulteration is a major public concern worldwide. Apart from economic fraud, health issues are in the forefront mainly due to severe allergies. Sardines are one of the most vulnerable-to-adulteration fish species due to their high nutritional value. Adulteration comprises the substitution of one fish species with similar species of lower nutritional value and lower cost. The detection of adulteration, especially in processed fish products, is very challenging because the morphological characteristics of the tissues change, making identification by the naked eye very difficult. Therefore, new analytical methods and (bio)sensors that provide fast analysis with high specificity, especially between closely related fish species, are in high demand. DNA-based methods are considered as important analytical tools for food adulteration detection. In this context, we report the first DNA sensors for sardine species identification. The sensing principle involves species recognition, via short hybridization of PCR-amplified sequences with specific probes, capture in the test zone of the sensor, and detection by the naked eye using gold nanoparticles as reporters; thus, avoiding the need for expensive instruments. As low as 5% adulteration of Sardina pilchardus with Sardinella aurita was detected with high reproducibility in the processed mixtures simulating canned fish products.
The Rapid Non-Destructive Differentiation of Different Varieties of Rice by Fluorescence Hyperspectral Technology Combined with Machine Learning
Authors: Kang Zhiliang , Fan Rongsheng , Zhan Chunyi , Wu Youli , Lin Yi , Li Kunyu , Qing Rui , Xu Lijia
Published: February 2024

A rice classification method for the fast and non-destructive differentiation of different varieties is significant in research at present. In this study, fluorescence hyperspectral technology combined with machine learning techniques was used to distinguish five rice varieties by analyzing the fluorescence hyperspectral features of Thai jasmine rice and four rice varieties with a similar appearance to Thai jasmine rice in the wavelength range of 475–1000 nm. The fluorescence hyperspectral data were preprocessed by a first-order derivative (FD) to reduce the background and baseline drift effects of the rice samples. Then, a principal component analysis (PCA) and t-distributed stochastic neighborhood embedding (t-SNE) were used for feature reduction and 3D visualization display. A partial least squares discriminant analysis (PLS-DA), BP neural network (BP), and random forest (RF) were used to build the rice classification models. The RF classification model parameters were optimized using the gray wolf algorithm (GWO). The results show that FD-t-SNE-GWO-RF is the best model for rice classification, with accuracy values of 99.8% and 95.3% for the training and test sets, respectively. The fluorescence hyperspectral technique combined with machine learning is feasible for classifying rice varieties.
Enhancing Bone Cement Efficacy with Hydrogel Beads Synthesized by Droplet Microfluidics
Authors: Wang Zeyu , Yang Sherwin , He Chunjie , Li Chaoqiang , Louh Rong-Fuh
Published: February 2024

Effective filling materials, typically bone cements, are essential for providing mechanical support during bone fracture treatment. A current challenge with bone cement lies in achieving continuous drug release and forming porous structures that facilitate cell migration and enhance osteoconductivity. We report a droplet microfluidics-based method for synthesizing uniform-sized gelatin hydrogel beads. A high hydrogel concentration and increased crosslinking levels were found to enhance drug loading as well as release performance. Consequently, the droplet microfluidic device was optimized in its design and fabrication to enable the stable generation of uniform-sized droplets from high-viscosity gelatin solutions. The size of the generated beads can be selectively controlled from 50 to 300 μm, featuring a high antibiotic loading capacity of up to 43% dry weight. They achieve continuous drug release lasting more than 300 h, ensuring sustained microbial inhibition with minimal cytotoxicity. Furthermore, the hydrogel beads are well suited for integration with calcium phosphate cement, maintaining structural integrity to form porous matrices and improve continuous drug release performance. The uniform size distribution of the beads, achieved through droplet microfluidic synthesis, ensures predictable drug release dynamics and a measurable impact on the mechanical properties of bone cements, positioning this technology as a promising enhancement to bone cement materials.
Polydopamine Nanosystems in Drug Delivery: Effect of Size, Morphology, and Surface Charge
Authors: Menichetti Arianna , Mordini Dario , Montalti Marco
Published: February 2024

Recently, drug delivery strategies based on nanomaterials have attracted a lot of interest in different kinds of therapies because of their superior properties. Polydopamine (PDA), one of the most interesting materials in nanomedicine because of its versatility and biocompatibility, has been widely investigated in the drug delivery field. It can be easily functionalized to favor processes like cellular uptake and blood circulation, and it can also induce drug release through two kinds of stimuli: NIR light irradiation and pH. In this review, we describe PDA nanomaterials’ performance on drug delivery, based on their size, morphology, and surface charge. Indeed, these characteristics strongly influence the main mechanisms involved in a drug delivery system: blood circulation, cellular uptake, drug loading, and drug release. The understanding of the connections between PDA nanosystems’ properties and these phenomena is pivotal to obtain a controlled design of new nanocarriers based on the specific drug delivery applications.
HIV-Infected Hepatic Stellate Cells or HCV-Infected Hepatocytes Are Unable to Promote Latency Reversal among HIV-Infected Mononuclear Cells
Authors: López Cinthya Alicia Marcela , Freiberger Rosa Nicole , Sviercz Franco Agustín , Quarleri Jorge , Delpino María Victoria
Published: February 2024

Due to a common mode of transmission through infected human blood, hepatitis C virus (HCV) and human immunodeficiency virus (HIV) co-infection is relatively prevalent. In alignment with this, HCV co-infection is associated with an increased size of the HIV reservoir in highly active antiretroviral therapy (HAART)-treated individuals. Hence, it is crucial to comprehend the physiological mechanisms governing the latency and reactivation of HIV in reservoirs. Consequently, our study delves into the interplay between HCV/HIV co-infection in liver cells and its impact on the modulation of HIV latency. We utilized the latently infected monocytic cell line (U1) and the latently infected T-cell line (J-Lat) and found that mediators produced by the infection of hepatic stellate cells and hepatocytes with HIV and HCV, respectively, were incapable of inducing latency reversal under the studied conditions. This may favor the maintenance of the HIV reservoir size among latently infected mononuclear cells in the liver. Further investigations are essential to elucidate the role of the interaction between liver cells in regulating HIV latency and/or reactivation, providing a physiologically relevant model for comprehending reservoir microenvironments in vivo.
Leading beyond the Script: A Cross-Sectional Study Exploring Preparedness of Pharmacy Academic Administrators
Authors: Hall Elizabeth A. , Finch Christopher K. , March Katherine L.
Published: February 2024

Limited research exists on the preparedness of pharmacy academic administrators for their roles. This cross-sectional survey aimed to explore the self-perceptions of pharmacy academic administrators, including deans, associate deans, assistant deans, department chairs, and directors, within United States-based Colleges or Schools of Pharmacy. Participants answered questions regarding their demographics, self-perceived readiness for administrative roles, self-perceived leadership skills, and strategies used to develop these skills. Data were analyzed using descriptive statistics, and subgroup comparisons were made using Student’s t-test for normally distributed continuous variables, Mann–Whitney tests for ordinal variables or non-normally distributed continuous variables, and Chi-squared tests for nominal variables. A total of 193 responses were analyzed. Respondents reported feeling least prepared in two areas: entrepreneurial revenue and handling grievances and appeals. There were gender differences noted in preparedness to conduct performance reviews, manage unit finances, and develop entrepreneurial revenue, with men rating themselves significantly higher than women in all three areas. Despite high self-ratings of leadership skills in the overall cohort, significant gender differences were noted in micromanagement with men rating themselves lower than women. Seeking advice from senior colleagues was the most used development strategy, and women showed a significantly higher preference for programs facilitated by professional organizations. This study contributes valuable insights into the preparedness of pharmacy academic administrators to inform future strategies that better support individuals to be successful in their roles.
Bioreactor Systems for Plant Cell Cultivation at the Institute of Plant Physiology of the Russian Academy of Sciences: 50 Years of Technology Evolution from Laboratory to Industrial Implications
Authors: Titova Maria , Popova Elena , Nosov Alexander
Published: February 2024

The cultivation of plant cells in large-scale bioreactor systems has long been considered a promising alternative for the overexploitation of wild plants as a source of bioactive phytochemicals. This idea, however, faced multiple constraints upon realization, resulting in very few examples of technologically feasible and economically effective biotechnological companies. The bioreactor cultivation of plant cells is challenging. Even well-growing and highly biosynthetically potent cell lines require a thorough optimization of cultivation parameters when upscaling the cultivation process from laboratory to industrial volumes. The optimization includes, but is not limited to, the bioreactor’s shape and design, cultivation regime (batch, fed-batch, continuous, semi-continuous), aeration, homogenization, anti-foaming measures, etc., while maintaining a high biomass and metabolite production. Based on the literature data and our experience, the cell cultures often demonstrate cell line- or species-specific responses to parameter changes, with the dissolved oxygen concentration (pO2) and shear stress caused by stirring being frequent growth-limiting factors. The mass transfer coefficient also plays a vital role in upscaling the cultivation process from smaller to larger volumes. The Experimental Biotechnological Facility at the K.A. Timiryazev Institute of Plant Physiology has operated since the 1970s and currently hosts a cascade of bioreactors from the laboratory (20 L) to the pilot (75 L) and a semi-industrial volume (630 L) adapted for the cultivation of plant cells. In this review, we discuss the most appealing cases of the cell cultivation process’s adaptation to bioreactor conditions featuring the cell cultures of medicinal plants Dioscorea deltoidea Wall. ex Griseb., Taxus wallichiana Zucc., Stephania glabra (Roxb.) Miers, Panax japonicus (T. Nees) C.A.Mey., Polyscias filicifolia (C. Moore ex E. Fourn.) L.H. Bailey, and P. fruticosa L. Harms. The results of cell cultivation in bioreactors of different types and designs using various cultivation regimes are covered and compared with the literature data. We also discuss the role of the critical factors affecting cell behavior in bioreactors with large volumes.
Longer Photoperiod Substantially Increases Indoor-Grown Cannabis’ Yield and Quality: A Study of Two High-THC Cultivars Grown under 12 h vs. 13 h Days
Authors: Ahrens Ashleigh , Llewellyn David , Zheng Youbin
Published: February 2024

Indoor-grown Cannabis sativa is commonly transitioned to a 12 h daily photoperiod to promote flowering. However, our previous research has shown that some indoor-grown cannabis cultivars can initiate strong flowering responses under daily photoperiods longer than 12 h. Since longer photoperiods inherently provide higher daily light integrals (DLIs), they may also increase growth and yield. To test this hypothesis, two THC-dominant cannabis cultivars, ‘Incredible Milk’ (IM) and ‘Gorilla Glue’ (GG), were grown to commercial maturity at a canopy level PPFD of 540 µmol·m−2·s−1 from white LEDS under 12 h or 13 h daily photoperiods, resulting in DLIs of 23.8 and 25.7 mol·m−2·d−1, respectively. Both treatments were harvested when the plants in the 12 h treatment reached maturity according to established commercial protocols. There was no delay in flowering initiation time in GG, but flowering initiation in IM was delayed by about 1.5 d under 13 h. Stigma browning and trichome ambering also occurred earlier and progressed faster in the 12 h treatment in both cultivars. The vegetative growth of IM plants in the 13 h treatment was greater and more robust. The inflorescence yields were strikingly higher in the 13 h vs. 12 h treatment, i.e., 1.35 times and 1.50 times higher in IM and GG, respectively, which is 4 to 6 times higher than the relative increase in DLIs. The inflorescence concentrations of major cannabinoids in the 13 h treatment were either higher or not different from the 12 h treatment in both cultivars. These results suggest that there may be substantial commercial benefits for using photoperiods longer than 12 h for increasing inflorescence yields without decreasing cannabinoid concentrations in some cannabis cultivars grown in indoor environments.
A Community-Based Framework Integrates Interspecific Interactions into Forest Genetic Conservation
Authors: Wang Xi , Xiao Yu , Lv Yan-Wen , He Zi-Han , Yeh Francis C. , Hu Xin-Sheng
Published: February 2024

Forest genetic conservation is typically species-specific and does not integrate interspecific interaction and community structure. It mainly focuses on the theories of population and quantitative genetics. This approach depicts the intraspecific patterns of population genetic structure derived from genetic markers and the genetic differentiation of adaptive quantitative traits in provenance trials. However, it neglects possible interspecific interaction in natural forests and overlooks natural hybridization or subspeciation. We propose that the genetic diversity of a given species in a forest community is shaped by both intraspecific population and interspecific community evolutionary processes, and expand the traditional forest genetic conservation concept under the community ecology framework. We show that a community-specific phylogeny derived from molecular markers would allow us to explore the genetic mechanisms of a tree species interacting with other resident species. It would also facilitate the exploration of a species’ ecological role in forest community assembly and the taxonomic relationship of the species with other species specific to its resident forest community. Phylogenetic β-diversity would assess the similarities and differences of a tree species across communities regarding ecological function, the strength of selection pressure, and the nature and extent of its interaction with other species. Our forest genetic conservation proposal that integrates intraspecific population and interspecific community genetic variations is suitable for conserving a taxonomic species complex and maintaining its evolutionary potential in natural forests. This provides complementary information to conventional population and quantitative genetics-based conservation strategies.
Efficient Single Nucleotide Polymorphism Marker-Assisted Selection to Fusarium Wilt in Chickpea
Authors: Castro Patricia , Caballo Cristina , Carmona Alejandro , Millan Teresa , Gil Juan , Die José V. , Izquierdo Inmaculada , Rubio Josefa
Published: February 2024

Fusarium wilt is one of the most destructive chickpea diseases worldwide. Race 5 (Foc5) is the most harmful in the Mediterranean basin. The primary objective of this study is to validate a block of six SNP markers previously mapped in Ca2 in a diverse panel of cultivars, advanced and inbred lines phenotyped for resistance to fusarium wilt. Additionally, we aim to assess the effectiveness of using these markers in the selection of resistant Foc5 lines in an ongoing breeding program. The results showed a 100% coincidence between phenotype and expected haplotype in plant material evaluated for Foc5. We also analyzed 67 inbred lines previously phenotyped by different authors for fusarium wilt reaction, though the specific race was not specified. In these accessions, 65.8% of the analyzed lines exhibited complete correspondence between the phenotype and haplotype. Our results suggest that in early generations it is possible to select resistant materials with reliability, leading to the removal of a significant number of lines, thereby reducing costs and facilitating the handling of materials for additional trait evaluations. Functional annotation of genes delimited by the SNP block revealed several genes in the “response to stimulus” category with potential roles in the resistance reaction.
Migration and Transformation of Heavy Metal and Its Fate in Intertidal Sediments: A Review
Authors: Geng Nan , Xia Yinfeng , Li Dongfeng , Bai Fuqing , Xu Cundong
Published: February 2024

Intertidal sediments are rich in biological resources, which are important for material circulation and energy exchange. Meanwhile, these areas can be treated as sinks as well as sources of coastal heavy metal pollutants. Due to the influence of the tide, the intertidal sediments are in a state of periodic flooding and exposure, and environmental factors such as dissolved oxygen, salinity and overlying water pressure are changeable. Heavy metals in sediments are prone to migration and transformation with the dynamic effects of tidal water and the changes in the environment factors, which increase the bioavailability of heavy metals. In this review, the characteristics of distribution and the bioavailability of heavy metals in intertidal sediments are described; the migration and transformation behavior of heavy metals and its influencing factors under tidal conditions are analyzed; and the mechanisms of heavy metal’s migration and transformation in the intertidal zone are summarized. Moreover, the bioaccumulation of heavy metal by organisms and the remediation techniques are discussed. Therefore, this review systematically summarizes the states of existence, the transport mechanisms, and the fate of heavy metals in the intertidal sediment, fills in the research gap of the cycling of heavy metal in the intertidal zone, and provides a theoretical basis for the control of heavy metal pollution.
Exergy and Environmental Analysis for Optimal Condition Finding of a New Combined Cycle
Authors: Mansir Ibrahim B.
Published: February 2024

In this paper, various thermal energy systems are studied to recover waste heat from gas turbines with different configurations. The exergy analysis and environmental examination are applied to achieve better insight into the suggested systems. Also, multi-objective optimization is employed to find the optimal condition of the introduced plants. In this work, various systems such as gas turbine (GT), organic Rankine cycle (ORC), and Kalina cycle (KC) with Proton Exchange Membrane (PEM) electrolyzer are combined to achieve a new system design. In this study, Engineering Equation Solver (V11.755) and Matlab (R2023a) software are used to simulate and optimize the proposed system. The comparison of systems shows that the combustion chamber with 3622 kW has the most considerable exergy destruction in the IGT/ORC-KC plant. The comparative investigation shows that IGT/ORC-KC has the highest output at 5659 kW, while the smallest exergy destruction is associated with the IGT system with 1779 kW. The multi-objective optimization considering three objective functions, namely, exergy efficiency, product cost, and environmental effects of exergy destruction, is conducted. Three-objective optimization on the IGT/ORC-KC unit shows that in the optimum point selected by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, the exergy efficiency, cost of product, and environmental effect of exergy destruction rate are 29.5%, 0.31 USD/kWh, and 13.22 mPt/s.
A Hybrid Feature-Selection Method Based on mRMR and Binary Differential Evolution for Gene Selection
Authors: Yu Kun , Li Wei , Xie Weidong , Wang Linjie
Published: February 2024

The selection of critical features from microarray data as biomarkers holds significant importance in disease diagnosis and drug development. It is essential to reduce the number of biomarkers while maintaining their performance to effectively minimize subsequent validation costs. However, the processing of microarray data often encounters the challenge of the “curse of dimensionality”. Existing feature-selection methods face difficulties in effectively reducing feature dimensionality while ensuring classification accuracy, algorithm efficiency, and optimal search space exploration. This paper proposes a hybrid feature-selection algorithm based on an enhanced version of the Max Relevance and Min Redundancy (mRMR) method, coupled with differential evolution. The proposed method improves the quantization functions of mRMR to accommodate the continuous nature of microarray data attributes, utilizing them as the initial step in feature selection. Subsequently, an enhanced differential evolution algorithm is employed to further filter the features. Two adaptive mechanisms are introduced to enhance early search efficiency and late population diversity, thus reducing the number of features and balancing the algorithm’s exploration and exploitation. The results highlight the improved performance and efficiency of the hybrid algorithm in feature selection for microarray data analysis.
Locality-Based Action-Poisoning Attack against the Continuous Control of an Autonomous Driving Model
Authors: An Yoonsoo , Yang Wonseok , Choi Daeseon
Published: February 2024

Various studies have been conducted on Multi-Agent Reinforcement Learning (MARL) to control multiple agents to drive effectively and safely in a simulation, demonstrating the applicability of MARL in autonomous driving. However, several studies have indicated that MARL is vulnerable to poisoning attacks. This study proposes a ’locality-based action-poisoning attack’ against MARL-based continuous control systems. Each bird in a flock interacts with its neighbors to generate the collective behavior, which is implemented through rules in the Reynolds’ flocking algorithm, where each individual maintains an appropriate distance from its neighbors and moves in a similar direction. We use this concept to propose an action-poisoning attack, based on the hypothesis that if an agent is performing significantly different behaviors from neighboring agents, it can disturb the driving stability of the entirety of the agents. We demonstrate that when a MARL-based continuous control system is trained in an environment where a single target agent performs an action that violates Reynolds’ rules, the driving performance of all victim agents decreases, and the model can converge to a suboptimal policy. The proposed attack method can disrupt the training performance of the victim model by up to 97% compared to the original model in certain setting, when the attacker is allowed black-box access.
Model for Technology Risk Assessment in Commercial Banks
Authors: Kang Wenhao , Cheung Chi Fai
Published: February 2024

As the complexity of banking technology systems increases, the prevention of technological risk becomes an endless battle. Currently, most banks rely on the experience and subjective judgement of experts and employees to allocate resources for technological risk management, which does not effectively reduce the frequency of technology-related incidents. Through an analysis of mainstream risk management models, this study proposes a technology-based risk assessment system based on machine learning. It first identifies risk factors in bank IT, preprocesses the sample data, and uses different regression prediction models to train the processed data to build an intelligent assessment model. The experimental results indicated that the Genetic Algorithm–Backpropagation Neural Network model achieved the best performance. Based on assessment indicators, indicator weight values, and risk levels, commercial banks can develop targeted prevention and control measures by applying limited resources to the most critical corrective actions, thereby effectively reducing the frequency of technology-related incidents.
A Novel Approach to Simulating Realistic Exoskeleton Behavior in Response to Human Motion
Authors: Yao Zhejun , Mir Latifi Seyed Milad , Molz Carla , Scherb David , Löffelmann Christopher , Sänger Johannes , Miehling Jörg , Wartzack Sandro , Lindenmann Andreas , Matthiesen Sven , Weidner Robert
Published: February 2024

Simulation models are a valuable tool for exoskeleton development, especially for system optimization and evaluation. It allows an assessment of the performance and effectiveness of exoskeletons even at an early stage of their development without physical realization. Due to the closed physical interaction between the exoskeleton and the user, accurate modeling of the human–exoskeleton interaction in defined scenarios is essential for exoskeleton simulations. This paper presents a novel approach to simulate exoskeleton motion in response to human motion and the interaction forces at the physical interfaces between the human and the exoskeleton. Our approach uses a multibody model of a shoulder exoskeleton in MATLAB R2021b and imports human motion via virtual markers from a digital human model to simulate human–exoskeleton interaction. To validate the human-motion-based approach, simulated exoskeleton motion and interaction forces are compared with experimental data from a previous lab study. The results demonstrate the feasibility of our approach to simulate human–exoskeleton interaction based on human motion. In addition, the approach is used to optimize the support profile of an exoskeleton, indicating its potential to assist exoskeleton development prior to physical prototyping.
Occupational Gender Segregation and Mental Health among Professionals: Women’s Risk Exposure in Five Micro Classes
Authors: Cattani Lorenzo , Rizza Roberto
Published: February 2024

This study explores the intricate interplay between gender, occupation, and mental health using data from the 2020 EU-LFS ad hoc module on 38,066 female professionals in Western Europe. We examine their exposure to work-related risks impacting mental health, focusing on variables such as work overload, violence, and challenging client interactions. Our primary objective is to discern how various occupations contribute to distinct experiences of work-induced strains. Key findings challenge the compensating differential theory, according to which the lower wages in female-dominated occupations are compensated by more friendly working conditions, revealing that interactive service-sector jobs pose higher risks to mental well-being. Health professionals, legal-cultural professionals, and teachers are particularly susceptible, with shift and weekend work exacerbating risk exposure to violence and violent behaviors. This study underscores the significance of a “within-gender” perspective, uncovering nuanced occupation-based inequalities for women. It introduces a novel approach to occupational segregation, highlighting the uneven distribution of work-induced strains among different occupations. It also urges to reassess customer-worker relationships and proposes gender-specific measures to alleviate heightened risks to mental well-being for interactive service occupations. In conclusion, this study analyzes the intersection of gender, occupation, and work-induced strains, emphasizing the role of micro-classes in shaping women’s mental health.
Semantic Networks of Election Fraud: Comparing the Twitter Discourses of the U.S. and Korean Presidential Elections
Authors: Lee Jongmyung , Chung Chung Joo , Kim Daesik
Published: February 2024

Traditional news outlets, such as newspapers and television, are no longer major sources of news. These media channels have been replaced by social platforms, which have increased in value as information distributors. This change in communication is an underlying reason for the election fraud controversies that occurred in the United States and South Korea, which hold high standards of democracy, during similar periods. This study investigates a model for sharing political disputes over social networks, especially Twitter, and illustrates the influence of political polarization. This study examines Twitter content around the presidential elections in the United States and South Korea in 2020 and 2022, respectively. It applies semantic network analysis and structural topic modeling to describe and compare the dynamics of online discourse on the issue of election fraud. The results show that online spaces such as Twitter serve as public spheres for discussion among active political participants. Social networks are key settings for forming and spreading election fraud controversies in the United States and South Korea, with differences in content. In addition, the study applies large-volume text data and new analytical methods such as the structural topic model to examine the in-depth relationships among political issues in cyberspace.
The Attitudes of Patients with Cardiovascular Diseases towards Online Exercise with the Mobile Monitoring of Their Health-Related Vital Signs
Authors: Ntovoli Apostolia , Anifanti Maria , Koukouvou Georgia , Mitropoulos Alexandros , Kouidi Evangelia , Alexandris Kostas
Published: February 2024

The health care cost of cardiovascular diseases (CVD) in the EU is estimated to be today over 282 billion euros. It is well documented today that exercise training is one of the main strategies for secondary disease prevention and the follow-up integration of these patients. This study aimed to examine patients’ attitudes towards online exercise with mobile monitoring of their vital signs. More specifically, the research objectives were as follows: (a) to examine patients’ attitudes and expectations of online exercise, (b) cluster patients in high- and low-attitude groups and examine their intention to participate in online exercise, and (c) to examine age and gender differences in terms of their intention to exercise online. The final goal of this project was to develop a real application that could be of use to patients and professionals. Data were collected from fifty patients in the city of Thessaloniki, Greece. The results revealed that most patients were positive about exercising online if the programs were perceived as fun and, especially, safe. The use of an online monitoring application with the distant supervision of health professionals could both motivate them and strengthen their feeling of safety.
Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning
Authors: Sarikaya Ayse Gul , Uzun Almira
Published: February 2024

Species of the Berberis genus, which are widely distributed naturally throughout the world, are cultivated and used for various purposes such as food, medicinal applications, and manufacturing dyes. Model-based machine learning is a language for specifying models, allowing the definition of a model using concise code, and enabling the automatic creation of software that implements the specified model. Maximum entropy (MaxEnt 3.4.1) is an algorithm used to model the appropriate distribution of species across geographical regions and is based on the species distribution model that is frequently also used in modeling the current and future potential distribution areas of plant species. Therefore, this study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in Türkiye for the periods 2041–2060 and 2081–2100, according to the SSP2 4.5 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. For this purpose, the coordinates obtained in the WGS 84 coordinate system were marked using the 5 m high spatial resolution Google Satellite Hybrid base maps, which are readily available in the 3.10.4 QGIS program, the current version of QGIS (Quantum GIS). The CM6A-LR climate model, the latest version of the IPSL climate models, was used to predict the species’ future distribution area. The area showed a high correlation with the points representing B. vulgaris, which is generally distributed in the Mediterranean and the central and eastern Black Sea regions of Türkiye, and the very suitable areas encompassed 45,413.82 km2. However, when the SSP2 4.5 scenario was considered for the period 2041–2060, the areas very suitable for Berberis vulgaris comprised 59,120.05 km2, and in the SSP2 4.5 scenario, very suitable areas were found to encompass 56,730.46 km2 in the 2081–2100 period. Considering the SSP5 8.5 scenario for the period 2041–2060, the area most suitable for the B. vulgaris species is 66,670.39 km2. In the SSP5 8.5 scenario, very suitable areas were found to cover 20,108.29 km2 in the 2081–2100 period. Careful consideration of both the potential positive and negative impacts of climate change is essential, and these should be regarded as opportunities to implement appropriate adaptation strategies. The necessary conditions for the continued existence and sustainability of B. vulgaris—that is, areas with ecological niche potential—have been determined.
Resource Efficiency and Environmental Impact Assessment Method for Small-Scale Producers: A Case Study of Pond and In-Pond Raceway System Production for Growing Nile Tilapia
Authors: Panthai Pimchanok , Kungwalsong Kanokporn
Published: February 2024

The purpose of this study was to employ Resource Value Mapping (REVAM) and carbon footprint assessments to evaluate the resource efficiency and environmental impact of the aquaculture sector in Thailand. Focusing on tilapia production, a case study that compares the innovative In-Pond Raceway System (IPRS) with the traditional pond system was conducted to serve as a guideline for small-scale producers toward achieving the Sustainable Development Goals (SDGs). The assessment applied lean classification to the agriculture context and used both machine and non-machine resources. Moreover, the Muda Index (MI) and the concurrent assessment of greenhouse gas (GHG) emissions through the proposed map were introduced to identify resource efficiencies and environmental impacts across activities, respectively. The analysis highlighted resources with the highest MI values, waste proportions, and emissions requiring improvement. This study shows that addressing specific resources in REVAM can enhance resource management, facilitate control over variable costs, and ensure sustainability in both of these dimensions. Finally, a feasibility analysis was incorporated to weigh investment between in-pond and IPRS systems, in addition to resource use efficiency and environmental impact dimensions, creating an opportunity to meet the increasing demands in the international market.