bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-Scene Hyperspectral Image Classification Based on Graph Alignment and Distribution Alignment
Authors: Chen Haisong , Ding Shanshan , Wang Aili
Published: May 2024

A domain alignment-based hyperspectral image (HSI) classification method was designed to address the heterogeneity in resolution and band between the source domain and target domain datasets of cross-scene hyperspectral images, as well as the resulting reduction in common features. Firstly, after preliminary feature extraction, perform two domain alignment operations: image alignment and distribution alignment. Image alignment aims to align hyperspectral images of different bands or time points, ensuring that they are within the same spatial reference framework. Distribution alignment adjusts the distribution of features of samples of different categories in the feature space to reduce the distribution differences of the same type of features between two domains. Secondly, adjust the consistency of the two alignment methods to ensure that the features obtained through different alignment methods exhibit consistency in the feature space, thereby improving the comparability and reliability of the features. In addition, this method considers multiple losses in the model from different perspectives and makes comprehensive adjustments through a unified optimization process to more comprehensively capture and utilize the correlation information between data. Experimental results on Houston 2013 and Houston 2018 datasets can improve the hyperspectral prediction performance between datasets with different resolutions and bands, effectively solving the problems of high cost and limited training samples in HSI labeling and significantly improving cross-scene HSI classification performance.
Modeling a Solenoid Driver with Nonlinear Inductive Load Using Circuit Simulation and Magnetic Flux Measurement
Authors: Hofbauer Tobias , Denk Frank
Published: May 2024

This paper describes the procedure for creating a electronic simulation model of a solenoid power electronic driver with a nonlinear inductive load. Furthermore, it discusses the electromagnetic interaction between the driver and the load example electromagnetic valve. The consideration of nonlinear effects in the power electronic components MOSFET and diode is particularly important to distinguish their effects from the nonlinear behaviour of the inductive load.
Enhancing Human Activity Recognition with Siamese Networks: A Comparative Study of Contrastive and Triplet Learning Approaches
Authors: Cha Byung-Rae , Vaidya Binod
Published: May 2024

This paper delves into the realm of human activity recognition (HAR) by leveraging the capabilities of Siamese neural networks (SNNs), focusing on the comparative effectiveness of contrastive and triplet learning approaches. Against the backdrop of HAR’s growing importance in healthcare, sports, and smart environments, the need for advanced models capable of accurately recognizing and classifying complex human activities has become paramount. Addressing this, we have introduced a Siamese network architecture integrated with convolutional neural networks (CNNs) for spatial feature extraction, bidirectional LSTM (Bi-LSTM) for temporal dependency capture, and attention mechanisms to prioritize salient features. Employing both contrastive and triplet loss functions, we meticulously analyze the impact of these learning approaches on the network’s ability to generate discriminative embeddings for HAR tasks. Through extensive experimentation, the study reveals that Siamese networks, particularly those utilizing triplet loss functions, demonstrate superior performance in activity recognition accuracy and F1 scores compared with baseline deep learning models. The inclusion of a stacking meta-classifier further amplifies classification efficacy, showcasing the robustness and adaptability of our proposed model. Conclusively, our findings underscore the potential of Siamese networks with advanced learning paradigms in enhancing HAR systems, paving the way for future research in model optimization and application expansion.
Digitally Controlled Hybrid Switching Step-Up Converter
Authors: Lovasz Evelyn-Astrid , Lascu Dan , Lica Septimiu
Published: May 2024

This paper focuses on the digital closed-loop design for a step-up converter with hybrid switching. For this purpose, for the first time, the control-to-output small-signal transfer function of a hybrid switching converter is determined in the rational form. Based on it, a type 3 analog controller is designed, and then, its digitized counterpart is found, and the digital controller is designed using a digital signal processor. The closed-loop operation is then validated both through simulation and practical implementation.
Fingerprint-Based Localization Enabled by Low-Rank Matrix Reconstruction in Intelligent Reflective Surface-Assisted Networks
Authors: Duan Shiru , Zhang Yuexia , Liu Ruiqi
Published: May 2024

The intelligent reflective surface (IRS) is a novel network node that consists of a large-scale passive reflective array to obtain a customized reflected wave direction by modulating the amplitude phase, which can be easily deployed to change the wireless signal propagation environment and enhance the communication performance under a non-line-of-sight (NLOS) environment, where location services cannot perform accurately. In this study, a low-rank matrix reconstruction-enabled fingerprint-based localization algorithm for IRS-assisted networks is proposed. Firstly, a 5G positioning system based on IRSs is constructed using multiple IRSs deployed to reflect signals. This enables the base station to overcome the influence of NLOS and receive the positioning signal of the point to be positioned. Then, the angular domain power expectation matrix of the received signal is extracted as a fingerprint to form a partial fingerprint database. Next, the complete fingerprint database is reconstructed using the low-rank matrix fitting algorithm, thereby considerably reducing the workload of building the fingerprint database. Finally, maximal ratio combining is used to increase the gap between the fingerprint data, and the Weighted K-Nearest Neighbor (WKNN) algorithm is used to match the fingerprint data and estimate the location of the points to be located. The simulation results demonstrate the feasibility of the proposed method to achieve sub-meter accuracy in an NLOS environment.
AliasClassifier: A High-Performance Router Alias Classifier
Authors: Xie Yuancheng , Zhang Zhaoxin , Chen Enhao , Li Ning
Published: May 2024

The task of router alias resolution for IPv4 networks presents a formidable challenge in the realm of router-level topology inference. Despite the considerable potential exhibited by machine-learning-based alias-resolution methods for IPv4 networks, several constraints impede their effectiveness. These constraints include a low discovery rate of aliased IPs, a failure to account for router aggregation, and a dearth of valid features in current schemes. In this study, we introduce a novel alias resolver, AliasClassifier, which is based on the Random Forest model and the alias triangulation algorithm. This innovative model identifies the key six features from a set of four prevalent routing behaviors that are typically employed to distinguish aliased IPs from non-alienated IPs. Subsequently, the AliasClassifier aggregates aliased IP pairs into routers using an alias triangulation algorithm. Experimental results demonstrate that AliasClassifier excels in discovering aliased IPs in IPv4 networks, boasting a resolution accuracy as high as 94.8% and a recall rate of 40.4%. Its comprehensive performance significantly surpasses that of state-of-the-art alias resolvers such as TreeNET, MLAR, and APPLE. Furthermore, as a typical centralized alias parser, AliasClassifier’s deployment cost is remarkably low. Consequently, AliasClassifier emerges as an ideal tool for router alias resolution in large-scale IPv4 networks.
Enhancing Moisture-Induced Defect Detection in Insulated Steel Pipes through Infrared Thermography and Hybrid Dataset
Authors: Rezayiye Reza Khoshkbary , Ibarra-Castanedo Clemente , Maldague Xavier
Published: May 2024

It is crucial to accurately detect moisture-induced defects in steel pipe insulation in order to combat corrosion under insulation (CUI). This study enhances the capabilities of infrared thermography (IRT) by integrating it with top-performing machine learning models renowned for their effectiveness in image segmentation tasks. A novel methodology was developed to enrich machine learning training, incorporating synthetic datasets generated via finite element method (FEM) simulations with experimental data. The performance of four advanced models—UNet, UNet++, DeepLabV3+, and FPN—was evaluated. These models demonstrated significant enhancements in defect detection capabilities, with notable improvements observed in FPN, which exhibited a mean intersection over union (IoU) increase from 0.78 to 0.94, a reduction in loss from 0.19 to 0.06, and an F1 score increase from 0.92 to 0.96 when trained on hybrid datasets compared to those trained solely on real data. The results highlight the benefits of integrating synthetic and experimental data, effectively overcoming the challenges of limited dataset sizes, and significantly improving the models’ accuracy and generalization capabilities in identifying defects. This approach marks a significant advancement in industrial maintenance and inspection, offering a precise, reliable, and scalable solution to managing the risks associated with CUI.
Zero-FVeinNet: Optimizing Finger Vein Recognition with Shallow CNNs and Zero-Shuffle Attention for Low-Computational Devices
Authors: Tran Nghi C. , Pham Bach-Tung , Chu Vivian Ching-Mei , Li Kuo-Chen , Le Phuong Thi , Chen Shih-Lun , Frisky Aufaclav Zatu Kusuma , Li Yung-Hui , Wang Jia-Ching
Published: May 2024

In the context of increasing reliance on mobile devices, robust personal security solutions are critical. This paper presents Zero-FVeinNet, an innovative, lightweight convolutional neural network (CNN) tailored for finger vein recognition on mobile and embedded devices, which are typically resource-constrained. The model integrates cutting-edge features such as Zero-Shuffle Coordinate Attention and a blur pool layer, enhancing architectural efficiency and recognition accuracy under various imaging conditions. A notable reduction in computational demands is achieved through an optimized design involving only 0.3 M parameters, thereby enabling faster processing and reduced energy consumption, which is essential for mobile applications. An empirical evaluation on several leading public finger vein datasets demonstrates that Zero-FVeinNet not only outperforms traditional biometric systems in speed and efficiency but also establishes new standards in biometric identity verification. The Zero-FVeinNet achieves a Correct Identification Rate (CIR) of 99.9% on the FV-USM dataset, with a similarly high accuracy on other datasets. This paper underscores the potential of Zero-FVeinNet to significantly enhance security features on mobile devices by merging high accuracy with operational efficiency, paving the way for advanced biometric verification technologies.
Analyzing Geospatial Cost Variability of Hybrid Solar–Gravity Storage System in High-Curtailment Suburban Areas
Authors: Basu Soumya , Hoshino Tetsuhito , Okumura Hideyuki
Published: May 2024

The increased decentralization of renewable energy has increased curtailment rates in stagnating demand zones, increasing the levelized cost of energy (LCOE). The geographically dynamic nature of gravity energy storage (GES) is emerging in the field of mechanical energy storage, over pumped hydro. However, GES costs vary geospatially, specifically in decentralized suburban areas, due to the impact of urban socioeconomics. This study aims to find a mathematical approximation of a cost-optimized location for suburban Solar–GES hybrid systems in curtailment-prone areas. A multi-parameterization model mathematically programmed land, transmission, supply chain and excavation costs into geospatial matrix approximations for suburban areas of 2500 km2 in Fukuoka and Ibaraki in Japan. It was found that SPV-GES location-dependent costs were mainly affected by distance from the city’s economic center and flat plains in suburbs, and supply chain and transmission costs optimized the location-dependent cost for GES at a specific point. It was also found that flat terrains were more economical than mountainous terrains due to high GES supply chain costs. With GES found to be cost-competitive compared to other storage technologies in Japan, this study reveals that GES introduction benefits the LCOE of suburban, decentralized SPV when curtailment is >50% irrespective of terrain.
Sulfur Encapsulation into Carbon Nanospheres as an Effective Technique to Limit Sulfide Dissolution and Extend the Cycle Life of Lithium–Sulfur Batteries
Authors: Fawaz Wissam , Wang Zhao , Ng Ka Yuen Simon
Published: May 2024

Lithium–sulfur batteries suffer from a reduced cycle life and diminished coulombic efficiency, which is attributed to the polysulfide shuttle effect. We herein present a process for the fabrication of lithium–sulfur battery cathode material via the recrystallization of dissolved sulfur inside self-assembled carbon nanospheres synthesized through the carbonization of d-glucose. Trapping sulfur in the carbonaceous matrix lessens the rapid dissolution of polysulfides and minimizes the loss of active sulfur, thus extending the cycling stability of these batteries. The carbon–sulfur composite material was characterized via X-ray diffraction (XRD), field emission scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). Electrochemical analysis of the material and its functionality as an electrode for lithium–sulfur battery systems was evaluated in a coin cell format using impedance spectroscopy and a life cycle study. The as-prepared cathode has shown remarkable electrochemical performance with a specific capacity of 781 mA/g at 0.1 C after 500 charge/discharge cycles and 83.4% capacity retention.
A New Feed-Forward Control for Dynamics Improvement in a Dual-Input DC–DC Converter for Hybrid Vehicle Applications
Authors: Benevieri Alessandro , Carbone Lorenzo , Cosso Simone , Marchesoni Mario , Passalacqua Massimiliano , Savio Stefano , Vaccaro Luis
Published: May 2024

In this study, a double-input single-output bidirectional DC–DC converter is considered. This particular architecture allows less switches to be used than a conventional solution. A new feed-forward current control for this DC–DC converter with three switches is presented in this paper. The modulation technique proposed in the literature for the aforementioned converter leads to a consistent loss reduction at low load, exploiting the DCM. As a drawback, when using this control strategy, the dynamic response worsens significantly. To speed up the control, a feed-forward approach is designed and implemented using a simplified converter electrical model. The proposed strategy is compared with the conventional PI controller, and it is validated and verified through simulation results in the MATLAB/Simulink/PLECS environment and through experimental tests using a converter prototype.
Acid Resistance of Metakaolin-Based Geopolymers and Geopolymeric Mortars Reinforced with Coconut Fibers
Authors: Lezzerini Marco , Aquino Andrea , Pagnotta Stefano
Published: May 2024

This paper investigates the durability of geopolymers and geopolymeric mortars made with metakaolin and alkaline activators, with and without a coconut fiber addition, after immersion for seven days into solutions of citric acid (1%, 2.5%, 5%, and 10%); hydrochloric acid (1%, 2.5%, 5%, and 10%); and sulfuric acid (1%, 2.5%, 5%, and 10%). The study focuses on mass changes, uniaxial compressive strength, flexural strength, and ultrasound pulse velocity measurements. X-ray diffraction and scanning electron microscopy are used to analyze the degradation products and microstructural changes. The aim is to assess the effect of acid exposure on the strength and stability of geopolymer materials and identify any protective effects of coconut fiber reinforcement. The samples are immersed in acid solutions of varying concentrations, and their mechanical properties are measured. The presence of coconut fibers slightly modifies the physical properties and the compressive strength, improving the mechanical flexural strength. Geopolymer and geopolymeric mortar materials experienced a weak decrease in strength when exposed to solutions of citric acid and a significant one when exposed to solutions of hydrochloric and sulfuric acids, attributed to depolymerization of the aluminosilicate binders. Brick waste geopolymeric mortars reinforced with coconut fibers showed the best performance in acid solutions with respect to geopolymers and quartz-rich sand geopolymeric mortars, suggesting a more stable cross-linked aluminosilicate geopolymer structure in this material.
Advances in Food Waste Biomass Transformation into High-Value Products
Authors: Spizzirri Umile Gianfranco , Restuccia Donatella
Published: May 2024

In recent years, there has been a concerning surge in waste generation, with agri-food waste emerging as a significant issue across various stages of the food supply chain [...]
A Special Issue on “Food Perception and Preferences in the Context of Health and Sustainability”
Authors: Wallner Marlies , Laureati Monica
Published: May 2024

In a rapidly changing world with increasing environmental and health issues, it is necessary to steer research in an appropriate direction while keeping our health in mind [...]
Size Control of Carbon Xerogel Spheres as Key Factor Governing the H2O2 Selectivity in Metal-Free Bifunctional Electro-Fenton Catalysts for Tetracycline Degradation
Authors: Fajardo-Puerto Edgar , López-García Nerea , Elmouwahidi Abdelhakim , Bailón-García Esther , Carrasco-Marín Francisco , Ramírez-Valencia Lilian D. , Pérez-Cadenas Agustín F.
Published: May 2024

Carbon xerogel spheres co-doped with nitrogen and eco-graphene were synthesized using a typical solvothermal method. The results indicate that the incorporation of eco-graphene enhances the electrochemical properties, such as the current density (JK) and the selectivity for the four transferred electrons (n). Additionally, nitrogen doping has a significant effect on the degradation efficiency, varying with the size of the carbon xerogel spheres, which could be attributed to the type of nitrogenous group doped in the carbon material. The degradation efficiency improved in the nanometric spheres (48.3% to 61.6%) but decreased in the micrometric-scale spheres (58.6% to 53.4%). This effect was attributed to the N-functional groups present in each sample, with N-CNS-5 exhibiting a higher percentage of graphitic nitrogen (35.7%) compared to N-CMS-5 (15.3%). These findings highlight the critical role of sphere size in determining the type of N-functional groups present in the sample. leading to enhanced degradation of pollutants as a result of the electro-Fenton process.
Hidden from Family History: The Ethics of Remembering
Authors: Robb Martin
Published: May 2024

This article draws on case studies or ‘microhistories’ from the author’s own research to explore the ethical responsibility of family historians to represent the experiences of those whose lives have been ‘hidden from history’, and in particular the lives of one’s female ancestors, as a way of correcting the omissions and erasures of official histories. It also discusses the ethical dilemmas posed by the discovery that one’s ancestors were involved in activities that are now regarded as morally suspect, such as profiting from the ownership of slaves. Finally, the article debates ethical arguments about respecting the rights of the dead to privacy.
Distribution of BCR::ABL1 Transcripts in the Different Clinical Phases of Chronic Myeloid Leukemia: Effect on Hematological Parameters and Patient Survival
Authors: Romero-Morelos Pablo , González-Yebra Ana , Herrerías-García Anaid , Ruíz-Velázquez Francisco , Bueno-Rosario Luis , González-Yebra Beatríz
Published: May 2024

Chronic myeloid leukemia (CML) is a hematopoietic stem cell disorder characterized by the presence of the Philadelphia chromosome, a product of the reciprocal translocation t(9;22)(q34;q11), in the BCR and ABL genes. These rearrangements in both genes lead to the formation of various fusion mRNA products, with preferential expression of b2a2, b3a2, and other BCR::ABL1 mRNA variants, combined with additional chromosomal abnormalities. Notably, the distribution and frequency of different mRNA variants vary in different populations. However, studies concerning this in Mexico are limited, and the results have been inconclusive. This study therefore aimed to determine the distribution of BCR::ABL1 mRNA variants in different clinical phases of CML and their effect on hematological parameters and patient survival. This study included 33 patients, whose demographic, clinical, and molecular data on BCR::ABL1 mRNA variants and hematological parameters were collected to identify potential associations. A total of 84.8% (n = 28) of patients had BCR::ABL1 translocation and increased platelet and basophil counts. The most frequent mRNA variant was b3a2 (64.3%), followed by b2a2 (28.6%) and e1a2 (3.6%). Concerning the clinical phases of CML, 75.8% (n = 25), 21.2% (n = 7), and 3% (n = 1) of patients were in the chronic, blast, and accelerated phases, respectively. Moreover, the b3a2 mRNA variant was more commonly identified in patients in the chronic phase. No correlation was observed between mRNA variant expression and patient survival. However, b2a2 was indicative of patients with longer survival as well as those treated with imatinib or nilotinib. Additionally, platelet count could be a marker of BCR::ABL1 translocation.
Prenatal Genome-Wide Cell-Free DNA Screening: Three Years of Clinical Experience in a Hospital Prenatal Diagnostic Unit in Spain
Authors: Pedrola Vidal Laia , Roselló Piera Mónica , Martín-Grau Carla , Rubio Moll Juan S. , Gómez Portero Rosa , Marcos Puig Beatriz , Cervera Zamora Jose V. , Quiroga Ramiro , Orellana Alonso Carmen
Published: May 2024

Genome-wide prenatal cell-free DNA (cfDNA) screening can be used to screen for a wide range of fetal chromosomal anomalies in pregnant patients. In this study, we describe our clinical experience with a genome-wide cfDNA assay in screening for common trisomies, sex chromosomal aneuploidies (SCAs), rare autosomal aneuploidies (RAAs), and copy-number variations (CNVs) in about 6000 patients over a three-year period at our hospital’s Prenatal Diagnostic Unit in Spain. Overall, 204 (3.3%) patients had a high-risk call, which included 76 trisomy 21, 21 trisomy 18, 7 trisomy 13, 29 SCAs, 31 RAAs, 31 CNVs, and 9 cases with multiple anomalies. The diagnostic outcomes were obtained for the high-risk cases when available, allowing for the calculation of positive predictive values (PPVs). Calculated PPVs were 95.9% for trisomy 21, 77.8% for trisomy 18, 66.7% for trisomy 13, 10.7% for RAAs, and 10.7% for CNVs. Pregnancy and birth outcomes were also collected for the majority of RAA and CNV cases. Adverse perinatal outcomes for some of these cases included preeclampsia, fetal growth restriction, preterm birth, reduced birth weight, and major congenital structural abnormalities. In conclusion, our study showed strong performance for genome-wide cfDNA screening in a large cohort of pregnancy patients in Spain.
Insights into Salinity Tolerance in Wheat
Authors: Zhang Zechao , Xia Zelin , Zhou Chunjiang , Wang Geng , Meng Xiao , Yin Pengcheng
Published: May 2024

Salt stress has a detrimental impact on food crop production, with its severity escalating due to both natural and man-made factors. As one of the most important food crops, wheat is susceptible to salt stress, resulting in abnormal plant growth and reduced yields; therefore, damage from salt stress should be of great concern. Additionally, the utilization of land in coastal areas warrants increased attention, given diminishing supplies of fresh water and arable land, and the escalating demand for wheat. A comprehensive understanding of the physiological and molecular changes in wheat under salt stress can offer insights into mitigating the adverse effects of salt stress on wheat. In this review, we summarized the genes and molecular mechanisms involved in ion transport, signal transduction, and enzyme and hormone regulation, in response to salt stress based on the physiological processes in wheat. Then, we surveyed the latest progress in improving the salt tolerance of wheat through breeding, exogenous applications, and microbial pathways. Breeding efficiency can be improved through a combination of gene editing and multiple omics techniques, which is the fundamental strategy for dealing with salt stress. Possible challenges and prospects in this process were also discussed.
Acute Effects of Combining Weight and Elastic Resistance Exercise on Vascular Function in Older Adults
Authors: Paditsaeree Kampanart , Mitranun Witid
Published: May 2024

Prior research has suggested that resistance exercise may result in a temporary decrease in vascular function, as measured by flow-mediated dilation (FMD), among untrained young individuals. However, the immediate impact of combined elastic and weight resistance training on older adults remains insufficiently explored. We assessed vascular function before, after, and 30 min after acute exercise under three resistance conditions to evaluate whether a combination of weight and elastic resistance exercises has an acute effect on vascular function in older adults. Fourteen older adults (65.6 ± 2.9 years) executed three sets of 12 repetitions at 65% of one repetition maximum (1 RM) of the bench press (BP) exercise. Testing was performed on three separate days as follows: (1) barbell alone (BA); (2) barbell plus elastic bands (10% of 65% 1 RM) (BE10); and (3) barbell plus elastic bands (20% of 65% 1 RM) (BE20). A two-way (time × condition) repeated measures analysis of variance was employed to assess the time and condition effects on flow-mediated dilation (FMD) and pulse wave velocity (PWV). At 0 min post-exercise, FMD was significantly higher during BE10 than during BA (p < 0.05); however, at 30 min post-exercise, no significant difference (p ≥ 0.05) was observed between the three conditions. In each condition, FMD results did not differ significantly at different times (p ≥ 0.05). For FMD, the main effect of the condition (F[2,26] = 3.86, p = 0.034) and that of the time and condition (F[4,52] = 3.66, p = 0.011) were significant. For PWV, only the difference between the BA and BE10 conditions was significant at 0 min (p < 0.05). PWV increased from baseline in the BA condition (p < 0.05) but not significantly in the BE10 and BE20 conditions (p ≥ 0.05). Therefore, BA, BE10, and BE20 demonstrated various changes in vascular function. Long-term training intervention studies are needed to validate these findings.
Water Deficit Severity during the Preceding Year Determines Plant Tolerance to Subsequent Year Drought Stress Challenges: A Case Study in Damask Rose
Authors: Aalam Fatemeh , Rezaei Nejad Abdolhossein , Mousavi-Fard Sadegh , Raji Mohammadreza , Nikoloudakis Nikolaos , Goumenaki Eleni , Fanourakis Dimitrios
Published: May 2024

Damask rose is an important essential oil crop. In the present study, plants were subjected to three different water deficit levels (70, 40, and 10% available water content) for two periods (June–October). Plant phenology, growth, essential oil yield, gas exchange features, membrane stability and major antioxidant defense elements were monitored across two years. Soil water deficit was related to quicker completion of the growth cycle (up to 7.4 d), and smaller plants (up to 49.7%). Under these conditions, biomass accumulation was jointly constrained by decreased leaf area, chlorophyll content, CO2 intake, and photosynthetic efficiency (up to 82.8, 56.9, 27.3 and 68.2%, respectively). The decrease in CO2 intake was driven by a reduction in stomatal conductance (up to 41.2%), while the decrease in leaf area was mediated by reductions in both number of leaves, and individual leaf area (up to 54.3, and 64.0%, respectively). Although the reactive oxygen species scavenging system was activated (i.e., proline accumulation, and enhanced activity of three antioxidant enzymes) by water deficit, oxidative stress symptoms were still apparent. These effects were amplified, as soil water deficit became more intense. Notably, the adverse effects of water deficit were generally less pronounced when plants had been exposed to water severity during the preceding year. Therefore, exposure to water deficit elicited plant tolerance to future exposure. This phenotypic response was further dependent on the water deficit level. At more intense soil water deficit across the preceding year, plants were less vulnerable to water deficit during the subsequent one. Therefore, our results reveal a direct link between water deficit severity and plant tolerance to future water stress challenges, providing for the first time evidence for stress memory in damask rose.
Characterization and Phylogenetic Analyses of the Complete Chloroplast Genome Sequence in Arachis Species
Authors: Yu Xiaona , Liang Tianzhu , Guo Yi , Liang Yan , Zou Xiaoxia , Si Tong , Ni Yu , Zhang Xiaojun
Published: May 2024

Peanut is an important oilseed and a widely cultivated crop worldwide. Knowledge of the phylogenetic relationships and information on the chloroplast genomes of wild and cultivated peanuts is crucial for the evolution of peanuts. In this study, we sequenced and assembled 14 complete chloroplast genomes of Arachis. The total lengths varied from 156,287 bp to 156, 402 bp, and the average guanine–cytosine content was 36.4% in 14 Arachis species. A total of 85 simple sequence repeats (SSRs) loci were detected, including 3 dinucleotide and 82 polynucleotide SSRs. Based on 110 complete chloroplast genomes of Arachis, a phylogenetic tree was constructed, which was divided into two groups (I and II). A total of 79 different genes were identified, of which six double-copy genes (ndhB, rpl2, rpl23, rps7, ycf1, and ycf2) and one triple-copy gene (rps12) are present in all 14 Arachis species, implying that these genes may be critical for photosynthesis. The dN/dS ratios for four genes (rps18, accD, clpP, ycf1) were larger than 1, indicating that these genes are subject to positive selection. These results not only provided rich genetic resources for molecular breeding but also candidate genes for further functional gene research.
The Risk Perception of the Chinese Diaspora during the COVID-19 Pandemic: Targeting Cognitive Dissonance through Storytelling
Authors: Leung Doris Yuet Lan , Khan Shoilee , Hwu Hilary , Mamuji Aaida , Rozdilsky Jack , Chu Terri , Lee Charlotte
Published: May 2024

The global COVID-19 pandemic in 2020 required risk communications to mitigate the virus’ spread. However, social media not only conveyed health information to minimize the contagion, but also distracted from the threat by linking it to an externalized ‘other’—primarily those appearing to be of Chinese descent. This disinformation caused the attribution of blame to Chinese people worldwide. In Canada’s Greater Toronto Area, Chinese individuals reported widespread public stigma that compounded their risk of contagion; to the degree that it was driven by cognitive dissonance, it generated experiences of social and cultural vulnerability. In this paper, we draw on the aforementioned study’s findings to explain how the risk perception and threat appraisal of Chinese diaspora individuals were impacted by different cognitive dissonance pathways. These findings explore how storytelling is a viable intervention with which to target and mitigate cognitive dissonance. Indeed, the mechanisms of cognitive dissonance can modify risk perception and mitigate social and cultural vulnerability, thereby averting potential long-term negative consequences for one’s mental health and well-being. We hope our guidance, training educators to target pathways of cognitive dissonance by drawing on storytelling (with humour), can assist them to better convey information in ways that are more inclusive during public health emergencies.
Disclosing Strain: How Psychosocial Risk Factors Influence Work-Related Musculoskeletal Disorders in Healthcare Workers Preceding and during the COVID-19 Pandemic
Authors: Barros Carla , Baylina Pilar
Published: May 2024

Healthcare workers, particularly nurses, engage in a daily work routine that takes a toll on their emotional well-being, rendering them vulnerable to psychosocial risk factors. This research seeks to analyse the influence of psychosocial risk factors on the occurrence of work-related musculoskeletal disorders among nurses. An additional analysis was performed to understand the role of age in work-related musculoskeletal disorders and the perception of psychosocial risk factors. The study was conducted during two separate periods—pre-pandemic and pandemic times—involving a sample of 456 nurses from both public and private hospitals in Portugal. The INSAT—Health and Work Survey—was used as measuring instrument. The primary observations indicated a consistency between psychosocial risk factors and the occurrence of work-related musculoskeletal disorders. The findings revealed a significant exposure to psychosocial risk factors, with work pace, intensity, work relationships, and emotional demands exhibiting higher global average percentages during both periods, pre-pandemic and pandemic. Nonetheless, we find that the psychosocial risk factors change when we analyse the pre-pandemic and pandemic results. During the period before the pandemic, the psychosocial risk factors that were most commonly reported included the demanding pace of work, long working hours, and emotional demands. Through the pandemic, the most pronounced psychosocial risk factors were work relationships, employment relationships, and ethical and values conflicts. Therefore, research in this domain is essential to understanding psychosocial risk factors and assessing the less obvious links between work and health.
Diagnosis in Bytes: Comparing the Diagnostic Accuracy of Google and ChatGPT 3.5 as an Educational Support Tool
Authors: Guimaraes Guilherme R. , Figueiredo Ricardo G. , Silva Caroline Santos , Arata Vanessa , Contreras Jean Carlos Z. , Gomes Cristiano M. , Tiraboschi Ricardo B. , Bessa Junior José
Published: May 2024

Background: Adopting advanced digital technologies as diagnostic support tools in healthcare is an unquestionable trend accelerated by the COVID-19 pandemic. However, their accuracy in suggesting diagnoses remains controversial and needs to be explored. We aimed to evaluate and compare the diagnostic accuracy of two free accessible internet search tools: Google and ChatGPT 3.5. Methods: To assess the effectiveness of both medical platforms, we conducted evaluations using a sample of 60 clinical cases related to urological pathologies. We organized the urological cases into two distinct categories for our analysis: (i) prevalent conditions, which were compiled using the most common symptoms, as outlined by EAU and UpToDate guidelines, and (ii) unusual disorders, identified through case reports published in the ‘Urology Case Reports’ journal from 2022 to 2023. The outcomes were meticulously classified into three categories to determine the accuracy of each platform: “correct diagnosis”, “likely differential diagnosis”, and “incorrect diagnosis”. A group of experts evaluated the responses blindly and randomly. Results: For commonly encountered urological conditions, Google’s accuracy was 53.3%, with an additional 23.3% of its results falling within a plausible range of differential diagnoses, and the remaining outcomes were incorrect. ChatGPT 3.5 outperformed Google with an accuracy of 86.6%, provided a likely differential diagnosis in 13.3% of cases, and made no unsuitable diagnosis. In evaluating unusual disorders, Google failed to deliver any correct diagnoses but proposed a likely differential diagnosis in 20% of cases. ChatGPT 3.5 identified the proper diagnosis in 16.6% of rare cases and offered a reasonable differential diagnosis in half of the cases. Conclusion: ChatGPT 3.5 demonstrated higher diagnostic accuracy than Google in both contexts. The platform showed satisfactory accuracy when diagnosing common cases, yet its performance in identifying rare conditions remains limited.
Histone Lactylation Is Involved in Mouse Oocyte Maturation and Embryo Development
Authors: Yang Diqi , Zheng Haoyi , Lu Wenjie , Tian Xueqi , Sun Yanyu , Peng Hui
Published: May 2024

Numerous post-translational modifications are involved in oocyte maturation and embryo development. Recently, lactylation has emerged as a novel epigenetic modification implicated in the regulation of diverse cellular processes. However, it remains unclear whether lactylation occurs during oocyte maturation and embryo development processes. Herein, the lysine lactylation (Kla) modifications were determined during mouse oocyte maturation and early embryo development by immunofluorescence staining. Exogenous lactate was supplemented to explore the consequences of modulating histone lactylation levels on oocyte maturation and embryo development processes by transcriptomics. Results demonstrated that lactylated proteins are widely present in mice with tissue- and cell-specific distribution. During mouse oocyte maturation, immunofluorescence for H3K9la, H3K14la, H4K8la, and H4K12la was most intense at the germinal vesicle (GV) stage and subsequently weakened or disappeared. Further, supplementing the culture medium with 10 mM sodium lactate elevated both the oocyte maturation rate and the histone Kla levels in GV oocytes, and there were substantial increases in Kla levels in metaphase II (MII) oocytes. It altered the transcription of molecules involved in oxidative phosphorylation. Moreover, histone lactylation levels changed dynamically during mouse early embryogenesis. Sodium lactate at 10 mM enhanced early embryo development and significantly increased lactylation, while impacting glycolytic gene transcription. This study reveals the roles of lactylation during oocyte maturation and embryo development, providing new insights to improving oocyte maturation and embryo quality.
Hesperidin as a Species-Specific Modifier of Aphid Behavior
Authors: Stec Katarzyna , Kordan Bożena , Bocianowski Jan , Gabryś Beata
Published: May 2024

Hesperidin is a highly bioactive natural flavonoid whose role in ecological interactions is poorly known. In particular, the effects of hesperidin on herbivores are rarely reported. Flavonoids have been considered as prospective biopesticides; therefore, the aim of the present study was to examine the influence of hesperidin on the host plant selection behavior of three aphid (Hemiptera: Aphididae) species: Acyrthosiphon pisum Harrris, Rhopalosiphum padi (L.), and Myzus persicae (Sulz.). The aphid host plants were treated with 0.1% and 0.5% ethanolic solutions of hesperidin. Aphid probing behavior in the no-choice experiment was monitored using electropenetrography and aphid settling on plants in the choice experiment was recorded. The results demonstrated that hesperidin can be applied as a pre-ingestive, ingestive, and post-ingestive deterrent against A. pisum, as an ingestive deterrent against R. padi, and as a post-ingestive deterrent against M. persicae using the relatively low 0.1% concentration. While in A. pisum the deterrent effects of hesperidin were manifested as early as during aphid probing in peripheral plant tissues, in M. persicae, the avoidance of plants was probably the consequence of consuming the hesperidin-containing phloem sap.
Evaluating the Diagnostic Potential of Combined Salivary and Skin Biomarkers in Parkinson’s Disease
Authors: Costanzo Matteo , Galosi Eleonora , De Bartolo Maria Ilenia , Gallo Gaetano , Leodori Giorgio , Belvisi Daniele , Conte Antonella , Fabbrini Giovanni , Truini Andrea , Berardelli Alfredo , Vivacqua Giorgio
Published: May 2024

Oligomeric alpha-synuclein (α-syn) in saliva and phosphorylated α-syn deposits in the skin have emerged as promising diagnostic biomarkers for Parkinson’s disease (PD). This study aimed to assess and compare the diagnostic value of these biomarkers in discriminating between 38 PD patients and 24 healthy subjects (HSs) using easily accessible biological samples. Additionally, the study sought to determine the diagnostic potential of combining these biomarkers and to explore their correlations with clinical features. Salivary oligomeric α-syn levels were quantified using competitive ELISA, while skin biopsies were analyzed through immunofluorescence to detect phosphorylated α-syn at Ser129 (p-S129). Both biomarkers individually were accurate in discriminating PD patients from HSs, with a modest agreement between them. The combined positivity of salivary α-syn oligomers and skin p-S129 aggregates differentiated PD patients from HSs with an excellent discriminative ability with an AUC of 0.9095. The modest agreement observed between salivary and skin biomarkers individually suggests that they may reflect different aspects of PD pathology, thus providing complementary information when combined. This study’s results highlight the potential of utilizing a multimodal biomarker approach to enhance diagnostic accuracy in PD.
A Two-Faced Gut Microbiome: Butyrogenic and Proinflammatory Bacteria Predominate in the Intestinal Milieu of People Living with HIV from Western Mexico
Authors: Baltazar-Díaz Tonatiuh Abimael , Andrade-Villanueva Jaime F. , Sánchez-Álvarez Paulina , Amador-Lara Fernando , Holguín-Aguirre Tania , Sánchez-Reyes Karina , Álvarez-Zavala Monserrat , López-Roa Rocío Ivette , Bueno-Topete Miriam Ruth , González-Hernández Luz Alicia
Published: May 2024

HIV infection results in marked alterations in the gut microbiota (GM), such as the loss of microbial diversity and different taxonomic and metabolic profiles. Despite antiretroviral therapy (ART) partially ablating gastrointestinal alterations, the taxonomic profile after successful new ART has shown wide variations. Our objective was to determine the GM composition and functions in people living with HIV (PLWHIV) under ART in comparison to seronegative controls (SC). Fecal samples from 21 subjects (treated with integrase strand-transfer inhibitors, INSTIs) and 18 SC were included. We employed 16S rRNA amplicon sequencing, coupled with PICRUSt2 and fecal short-chain fatty acid (SCFA) quantification by gas chromatography. The INSTI group showed a decreased α-diversity (p < 0.001) compared to the SC group, at the expense of increased amounts of Pseudomonadota (Proteobacteria), Segatella copri, Lactobacillus, and Gram-negative bacteria. Concurrently, we observed an enrichment in Megasphaera and Butyricicoccus, both SCFA-producing bacteria, and significant elevations in fecal butyrate in this group (p < 0.001). Interestingly, gut dysbiosis in PLWHIV was characterized by a proinflammatory environment orchestrated by Pseudomonadota and elevated levels of butyrate associated with bacterial metabolic pathways, as well as the evident presence of butyrogenic bacteria. The role of this unique GM in PLWHIV should be evaluated, as well as the use of butyrate-based supplements and ART regimens that contain succinate, such as tenofovir disoproxil succinate. This mixed profile is described for the first time in PLWHIV from Mexico.
Unraveling the Significance of Nanog in the Generation of Embryonic Stem-like Cells from Spermatogonia Stem Cells: A Combined In Silico Analysis and In Vitro Experimental Approach
Authors: Ghasemi Nima , Azizi Hossein , Skutella Thomas
Published: May 2024

Embryonic stem-like cells (ES-like cells) are promising for medical research and clinical applications. Traditional methods involve “Yamanaka” transcription (OSKM) to derive these cells from somatic cells in vitro. Recently, a novel approach has emerged, obtaining ES-like cells from spermatogonia stem cells (SSCs) in a time-related process without adding artificial additives to cell cultures, like transcription factors or small molecules such as pten or p53 inhibitors. This study aims to investigate the role of the Nanog in the conversion of SSCs to pluripotent stem cells through both in silico analysis and in vitro experiments. We used bioinformatic methods and microarray data to find significant genes connected to this derivation path, to construct PPI networks, using enrichment analysis, and to construct miRNA-lncRNA networks, as well as in vitro experiments, immunostaining, and Fluidigm qPCR analysis to connect the dots of Nanog significance. We concluded that Nanog is one of the most crucial differentially expressed genes during SSC conversion, collaborating with critical regulators such as Sox2, Dazl, Pou5f1, Dnmt3, and Cdh1. This intricate protein network positions Nanog as a pivotal factor in pathway enrichment for generating ES-like cells, including Wnt signaling, focal adhesion, and PI3K-Akt-mTOR signaling. Nanog expression is presumed to play a vital role in deriving ES-like cells from SSCs in vitro. Finding its pivotal role in this path illuminates future research and clinical applications.
Early Blood–Brain Barrier Impairment as a Pathological Hallmark in a Novel Model of Closed-Head Concussive Brain Injury (CBI) in Mice
Authors: Blaschke Stefan J. , Rautenberg Nora , Endepols Heike , Jendro Aileen , Konrad Jens , Vlachakis Susan , Wiedermann Dirk , Schroeter Michael , Hoffmann Bernd , Merkel Rudolf , Marklund Niklas , Fink Gereon R. , Rueger Maria A.
Published: May 2024

Concussion, caused by a rotational acceleration/deceleration injury mild enough to avoid structural brain damage, is insufficiently captured in recent preclinical models, hampering the relation of pathophysiological findings on the cellular level to functional and behavioral deficits. We here describe a novel model of unrestrained, single vs. repetitive concussive brain injury (CBI) in male C56Bl/6j mice. Longitudinal behavioral assessments were conducted for up to seven days afterward, alongside the evaluation of structural cerebral integrity by in vivo magnetic resonance imaging (MRI, 9.4 T), and validated ex vivo by histology. Blood–brain barrier (BBB) integrity was analyzed by means of fluorescent dextran- as well as immunoglobulin G (IgG) extravasation, and neuroinflammatory processes were characterized both in vivo by positron emission tomography (PET) using [18F]DPA-714 and ex vivo using immunohistochemistry. While a single CBI resulted in a defined, subacute neuropsychiatric phenotype, longitudinal cognitive testing revealed a marked decrease in spatial cognition, most pronounced in mice subjected to CBI at high frequency (every 48 h). Functional deficits were correlated to a parallel disruption of the BBB, (R2 = 0.29, p < 0.01), even detectable by a significant increase in hippocampal uptake of [18F]DPA-714, which was not due to activation of microglia, as confirmed immunohistochemically. Featuring a mild but widespread disruption of the BBB without evidence of macroscopic damage, this model induces a characteristic neuro-psychiatric phenotype that correlates to the degree of BBB disruption. Based on these findings, the BBB may function as both a biomarker of CBI severity and as a potential treatment target to improve recovery from concussion.