bluuebunny/crossref_metadata_2025 huggingface dataset:
Roles of Phytochemicals in Cancer Prevention and Therapeutics
Authors: Pons Daniel Gabriel
Published: May 2024

This Special Issue focused on the importance of phytochemicals for their use in the prevention and treatment of cancer [...]
Liver Diseases: From Bench to Bedside
Authors: Kanda Tatsuo , Sasaki-Tanaka Reina , Terai Shuji
Published: May 2024

The human genome encodes at least 500 protein kinases, and among them, there are at least 90 tyrosine kinases [...]
A Brain Anti-Senescence Transcriptional Program Triggered by Hypothalamic-Derived Exosomal microRNAs
Authors: Krarup Josefa , Araya Lucas , Álvarez Felipe , Bórquez Daniel A. , Urrutia Pamela J.
Published: May 2024

In contrast to the hypothesis that aging results from cell-autonomous deterioration processes, the programmed longevity theory proposes that aging arises from a partial inactivation of a “longevity program” aimed at maintaining youthfulness in organisms. Supporting this hypothesis, age-related changes in organisms can be reversed by factors circulating in young blood. Concordantly, the endocrine secretion of exosomal microRNAs (miRNAs) by hypothalamic neural stem cells (htNSCs) regulates the aging rate by enhancing physiological fitness in young animals. However, the specific molecular mechanisms through which hypothalamic-derived miRNAs exert their anti-aging effects remain unexplored. Using experimentally validated miRNA–target gene interactions and single-cell transcriptomic data of brain cells during aging and heterochronic parabiosis, we identify the main pathways controlled by these miRNAs and the cell-type-specific gene networks that are altered due to age-related loss of htNSCs and the subsequent decline in specific miRNA levels in the cerebrospinal fluid (CSF). Our bioinformatics analysis suggests that these miRNAs modulate pathways associated with senescence and cellular stress response, targeting crucial genes such as Cdkn2a, Rps27, and Txnip. The oligodendrocyte lineage appears to be the most responsive to age-dependent loss of exosomal miRNA, leading to significant derepression of several miRNA target genes. Furthermore, heterochronic parabiosis can reverse age-related upregulation of specific miRNA-targeted genes, predominantly in brain endothelial cells, including senescence promoting genes such as Cdkn1a and Btg2. Our findings support the presence of an anti-senescence mechanism triggered by the endocrine secretion of htNSC-derived exosomal miRNAs, which is associated with a youthful transcriptional signature.
Plant-Based HSP90 Inhibitors in Breast Cancer Models: A Systematic Review
Authors: Zarguan Ilham , Ghoul Sonia , Belayachi Lamiae , Benjouad Abdelaziz
Published: May 2024

Breast cancer, the most invasive cancer in women globally, necessitates novel treatments due to prevailing limitations of therapeutics. Search of news anticancer targets is more necessary than ever to tackle this pathology. Heat-Shock Protein 90 (HSP90), a chaperone protein, is implicated in breast cancer pathogenesis, rendering it an appealing target. Looking for alternative approach such as Plant-based compounds and natural HSP90 inhibitors offer promising prospects for innovative therapeutic strategies. This study aims to identify plant-based compounds with anticancer effects on breast cancer models and elucidate their mechanism of action in inhibiting the HSP90 protein. A systematic review was conducted and completed in January 2024 and included in vitro, in vivo, and in silico studies that investigated the effectiveness of plant-based HSP90 inhibitors tested on breast cancer models. Eleven studies were included in the review. Six plants and 24 compounds from six different classes were identified and proved to be effective against HSP90 in breast cancer models. The studied plant extracts showed a dose- and time-dependent decrease in cell viability. Variable IC50 values showed antiproliferative effects, with the plant Tubocapsicum anomalum demonstrating the lowest value. Withanolides was the most studied class. Fennel, Trianthema portulacastrum, and Spatholobus suberectus extracts were shown to inhibit tumor growth and angiogenesis and modulate HSP90 expression as well as its cochaperone interactions in breast cancer mouse models. The identified plant extracts and compounds were proven effective against HSP90 in breast cancer models, and this inhibition showed promising effects on breast cancer biology. Collectively, these results urge the need of further studies to better understand the mechanism of action of HSP90 inhibitors using comparable methods for preclinical observations.
Missing Wedge Completion via Unsupervised Learning with Coordinate Networks
Authors: Van Veen Dave , Galaz-Montoya Jesús G. , Shen Liyue , Baldwin Philip , Chaudhari Akshay S. , Lyumkis Dmitry , Schmid Michael F. , Chiu Wah , Pauly John
Published: May 2024

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3–20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.
Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment
Authors: Qiu Junyu , Cheng Zilin , Jiang Zheng , Gan Luhan , Zhang Zixuan , Xie Zhenzhen
Published: May 2024

An immune checkpoint is a signaling pathway that regulates the recognition of antigens by T-cell receptors (TCRs) during an immune response. These checkpoints play a pivotal role in suppressing excessive immune responses and maintaining immune homeostasis against viral or microbial infections. There are several FDA-approved immune checkpoint inhibitors (ICIs), including ipilimumab, pembrolizumab, and avelumab. These ICIs target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed death ligand 1 (PD-L1). Furthermore, ongoing efforts are focused on developing new ICIs with emerging potential. In comparison to conventional treatments, ICIs offer the advantages of reduced side effects and durable responses. There is growing interest in the potential of combining different ICIs with chemotherapy, radiation therapy, or targeted therapies. This article comprehensively reviews the classification, mechanism of action, application, and combination strategies of ICIs in various cancers and discusses their current limitations. Our objective is to contribute to the future development of more effective anticancer drugs targeting immune checkpoints.
Relationship between the Number of Repeats in the Neck Regions of L-SIGN and Augmented Virus Replication and Immune Responses in Dengue Hemorrhagic Fever
Authors: Liu Keh-Sen , Chen Po-Ming , Wang Lin , Lee Ing-Kit , Yang Kuender D. , Chen Rong-Fu
Published: May 2024

C-type lectins play a crucial role as pathogen-recognition receptors for the dengue virus, which is responsible for causing both dengue fever (DF) and dengue hemorrhagic fever (DHF). DHF is a serious illness caused by the dengue virus, which exists in four different serotypes: DEN-1, DEN-2, DEN-3, and DEN-4. We conducted a genetic association study, during a significant DEN-2 outbreak in southern Taiwan, to explore how variations in the neck-region length of L-SIGN (also known as CD209L, CD299, or CLEC4M) impact the severity of dengue infection. PCR genotyping was utilized to identify polymorphisms in variable-number tandem repeats. We constructed L-SIGN variants containing either 7- or 9-tandem repeats and transfected these constructs into K562 and U937 cells, and cytokine and chemokine levels were evaluated using enzyme-linked immunosorbent assays (ELISAs) following DEN-2 virus infection. The L-SIGN allele 9 was observed to correlate with a heightened risk of developing DHF. Subsequent results revealed that the 9-tandem repeat was linked to elevated viral load alongside predominant T-helper 2 (Th2) cell responses (IL-4 and IL-10) in K562 and U937 cells. Transfecting K562 cells in vitro with L-SIGN variants containing 7- and 9-tandem repeats confirmed that the 9-tandem repeat transfectants facilitated a higher dengue viral load accompanied by increased cytokine production (MCP-1, IL-6, and IL-8). Considering the higher prevalence of DHF and an increased frequency of the L-SIGN neck’s 9-tandem repeat in the Taiwanese population, individuals with the 9-tandem repeat may necessitate more stringent protection against mosquito bites during dengue outbreaks in Taiwan.
Performance Evaluation of Deep Learning Models for Classifying Cybersecurity Attacks in IoT Networks
Authors: Becerra-Suarez Fray L. , Tuesta-Monteza Victor A. , Mejia-Cabrera Heber I. , Arcila-Diaz Juan
Published: May 2024

The Internet of Things (IoT) presents great potential in various fields such as home automation, healthcare, and industry, among others, but its infrastructure, the use of open source code, and lack of software updates make it vulnerable to cyberattacks that can compromise access to data and services, thus making it an attractive target for hackers. The complexity of cyberattacks has increased, posing a greater threat to public and private organizations. This study evaluated the performance of deep learning models for classifying cybersecurity attacks in IoT networks, using the CICIoT2023 dataset. Three architectures based on DNN, LSTM, and CNN were compared, highlighting their differences in layers and activation functions. The results show that the CNN architecture outperformed the others in accuracy and computational efficiency, with an accuracy rate of 99.10% for multiclass classification and 99.40% for binary classification. The importance of data standardization and proper hyperparameter selection is emphasized. These results demonstrate that the CNN-based model emerges as a promising option for detecting cyber threats in IoT environments, supporting the relevance of deep learning in IoT network security.
Evaluation of Pigment-Modified Clear Binders and Asphalts: An Approach towards Sustainable, Heat Harvesting, and Non-Black Pavements
Authors: Badin Gul , Ahmad Naveed , Huang Ying , Mahmood Yasir
Published: May 2024

Pavement construction practices have evolved due to increasing environmental impact and urban heat island (UHI) effects, as pavements, covering over 30% of urban areas, contribute to elevated air temperatures. This study introduces heat-reflective pavements, by replacing conventional black bitumen with a clear binder and pigment-modified clear binders. Titanium dioxide white, zinc ferrite yellow, and iron oxide red pigments are used to give asphalt corresponding shades. The asphalt and bitumen specimens were subjected to thermal analysis in heat sinks, under varying solar fluxes. The pigment dosage was maintained at 4%, according to the weight of the total mix, for all pigment types. The samples were heated and cooled for 3 h and 2 h, respectively. Mechanical testing was conducted to ascertain the impact of temperature variations on both the neat clear binder (C.B) and pigmented C.B and asphalt mixture samples. Wheel tracking and dynamic modulus tests were conducted to evaluate their performance under high temperatures. The results indicate that non-black asphalt mixtures exhibit significant temperature reductions, up to 9 °C, which are further enhanced by pigmented binders, up to 11 °C. It was found that asphalt with a clear or transparent binder demonstrated lower temperatures and faster heat dissipation in extreme conditions. Moreover, C.B asphalt mixtures displayed a rut resistance of 15%, with the pigmented C.B asphalt mixture showing a remarkable rut resistance of 73%, outperforming conventional asphalt. Non-black mixtures, especially C.B + zinc ferrite, showed improved resistance to permanent deformation in dynamic modulus tests.
Rheumatic and Degenerative Mitral Stenosis: From an Iconic Clinical Case to the Literature Review
Authors: Napoli Francesca , Vella Ciro , Ferri Luca , Ancona Marco , Bellini Barbara , Russo Filippo , Agricola Eustachio , Esposito Antonio , Montorfano Matteo
Published: May 2024

Mitral stenosis (MS) poses significant challenges in diagnosis and management due to its varied etiologies, such as rheumatic mitral stenosis (RMS) and degenerative mitral stenosis (DMS). While rheumatic fever-induced RMS has declined in prevalence, DMS is rising with aging populations and comorbidities. Starting from a complex clinical case of DMS, the aim of this paper is to review the literature on mitral stenosis by analyzing the available tools and the differences in terms of diagnosis and treatment for rheumatic and degenerative stenosis. Emerging transcatheter techniques, such as transcatheter mitral valve replacement (TMVR) and lithotripsy-facilitated percutaneous mitral commissurotomy (PMC), represent promising alternatives for DMS patients deemed unfit for surgery. In particular, intravascular lithotripsy (IVL) has shown potential in facilitating percutaneous interventions by fracturing calcific deposits and enabling subsequent interventions. However, larger prospective studies are warranted to validate these findings and establish IVL’s role in DMS management. To further enhance this technique, research could focus on investigating the long-term outcomes and durability of mitral lithotripsy, as well as exploring its potential in combination with PMC or TMVR.
Effect of the Incorporation of Olive Tree Pruning Sawdust in the Production of Lightweight Mortars
Authors: Oya-Monzón Marina , Eliche-Quesada Dolores , La Rubia M. Dolores
Published: May 2024

In order to reduce energy consumption in buildings, this study used olive pruning sawdust (OTPS) instead of natural sand in the production of lightweight mortars. Different percentages of natural sand substitution were tested: 0, 10, 25, and 50% by volume of sand over 7 and 28 days of curing time. Additionally, the influence of a chemical pretreatment in an aqueous solution of calcium hydroxide on the OTPS was also evaluated to mineralize the wood before its addition to the mortar mixture. Mortars with OTPS incorporations were characterized by volumetric shrinkage, bulk density, and capillary water absorption. Mechanical behavior was tested through compression and flexural tests. The addition of this byproduct decreased bulk density and increased mortar porosity. Pretreating olive pruning sawdust with an aqueous solution of calcium hydroxide was effective for wood mineralization, resulting in physical and mechanical properties superior to mortars without pretreatment. The results showed that a maximum addition of 10% by volume of OTPS treated with calcium hydroxide solution produced lighter mortars with similar mechanical properties to the control mortar. Adding higher amounts of pretreated olive pruning (25–50% by volume) led to a more pronounced deterioration of mechanical properties.
Resorption Rates of Bone Graft Materials after Crestal Maxillary Sinus Floor Elevation and Its Influencing Factors
Authors: Jing Ling , Su Baohui
Published: May 2024

The aim of this study is to analyze the resorption rate of bone graft materials after crestal sinus floor elevation, study its influencing factors, and improve the long-term success rate of implants after crestal maxillary sinus floor elevation. Measurement and analysis were conducted at six postoperative timepoints (0 months, 6 months, 12 months, 18 months, 24 months, and 30 months) using cone beam computed tomography (CBCT) data on 31 patients from the Chenghuaxinguanghua Dental Clinic who underwent crestal maxillary sinus floor elevation, involving 38 graft sites. The materials resorption rates of the bone graft height (BH) and bone graft width (BW) were assessed. BH and BW resorption rates followed the same trend (p = 0.07), with BH and BW resorption rates decreasing with time (rBH = −0.32, p < 0.01; rBW = −0.18, p < 0.01), and were maximal in the 0–6 month interval, with BH and BW resorption rates of 3.42%/mth and 3.03%/mth, respectively. The average monthly BH and BW resorption rates in the 6–12 month interval rapidly decreased to 1.75%/mth and 1.29%/mth, respectively. The monthly BH and BW resorption rates in the 12–30 month intervals stabilized at 1.45%/mth (p > 0.05) and 1.22%/mth (p > 0.05), respectively. The higher the initial bone graft height (BH0), the lower the BH resorption rates (rBH = −0.98, p < 0.05), and the BW resorption rate was different for different graft sites (p = 0.01). The resorption rates of bone graft materials implanted through crestal maxillary sinus floor elevation decreased rapidly within the first 12 months post operation and remained stable after 12 months. BH0 was identified as a significant factor influencing the resorption rates of bone graft materials. These results could suggest dentists should pay attention to the trend of resorption rates over time and carefully manage the initial height of bone grafts and inspire the research of new bone grafting materials for crestal maxillary sinus floor elevation.
Sleep Quality in Greek Adolescent Swimmers
Authors: Stavrou Vasileios T. , Vavougios George D. , Tsirimona Glykeria , Daniil Zoe , Gourgoulianis Konstantinos I.
Published: May 2024

The aim of our study was to investigate the relationship between sleep quality and functional indices, swimming distance and gender in adolescent competitive swimmers. Forty-eight adolescent swimmers (boys, n = 22, 15.7 ± 1.0 years and girls, n = 26, 15.1 ± 0.8 years) were included in our study. They were assessed for handgrip strength, respiratory muscle strength and pulmonary function, answered a Pittsburg Sleep Quality Index questionnaire (PSQI), and recorded their anthropometric and morphological characteristics and training load for the last four weeks. The results showed differences between swimming distance and chest circumference difference, between maximal inhalation and exhalation (Δchest) (p = 0.033), PSQI score (p < 0.001), and sleep quality domains for “cannot breathe comfortably” (p = 0.037) and “have pain” (p = 0.003). Binary logistic regression (chi-square = 37.457, p = 0.001) showed that the variables Δchest (p = 0.038, 95% CI: 1.05–6.07) and PSQI score (p = 0.048, 95% CI: 0.1–1.07) remained independent predictors of the swim distance groups. Girls had a lower percentage of predicted values for the maximal inspiratory pressure (p < 0.001), maximal expiratory pressure (p = 0.027), forced expiratory volume within the first second (p = 0.026), forced vital capacity (p = 0.008) and sleep quality domains for “cough or snore loudly” (p = 0.032) compared to boys. A regression analysis showed that the sleep quality score was explained by the six independent variables: respiratory muscle strength (t = 2.177, β = 0.164, p = 0.035), Δchest (t = −2.353, β = −0.17, p = 0.023), distance (t = −5.962, β = −0.475, p < 0.001), total body water (t = −7.466, β = −0.687, p < 0.001), lean body mass (t = −3.120, β = −0.434, p = 0.003), and handgrip (t = 7.752, β = 1.136, p < 0.001). Our findings demonstrate that sleep quality in adolescent swimmers is a multifactorial result of morphometric characteristics, strength and respiratory function.
Large-Eddy Simulation of Low-Frequency Flow Oscillations for NACA0012 and Dynarig Sail at Large Attack Angles
Authors: Zeng Qingsong , Cai Wei , Xu Junhui
Published: May 2024

Unmanned sailboats, harnessing wind for propulsion, offer great potential for extended marine research due to their virtually unlimited endurance. The sails typically operate at high attack angles, which contrasts with aircraft that maintain small angles to prevent stalling. Despite the reduction in lift during stalling, the resultant increase in drag contributes significantly to the sail’s thrust. However, the sail often experiences vortex shedding due to high attack angles, leading to low-frequency oscillations and erratic navigation. This study employs large-eddy simulations (LESs) on a 3D NACA0012 sail at a Reynolds number of 3.6 × 105, which is validated by experimental data. It observes the lift and drag coefficients across attack angles from 5 to 90 degrees and compares these with a Dynarig sail. The findings reveal that higher attack angles amplify fluctuations in lift and drag coefficients. Vortex shedding, resulting from flow separation, creates pressure changes and oscillations in aerodynamic forces. Fast Fourier transformation (FFT) analysis identifies dominant frequencies between 0.5 and 10 Hz, indicating low-frequency oscillations. The study’s insights into the impact of attack angle and sail type on the oscillation frequency are favorable for the design of unmanned sailboats, aiding in the prediction of wind-induced frequencies and optimal attack angle determination.
The Analysis of Intelligent Functions Required for Inland Ships
Authors: Hao Guozhu , Xiao Wenhui , Huang Liwen , Chen Jiahao , Zhang Ke , Chen Yaojie
Published: May 2024

Sorting out the requirements for intelligent functions is the prerequisite and foundation of the top-level design for the development of intelligent ships. In light of the development of inland intelligent ships for 2030, 2035, and 2050, based on the analysis of the division of intelligent ship functional modules by international representative classification societies and relevant research institutions, eight necessary functional modules have been proposed: intelligent navigation, intelligent hull, intelligent engine room, intelligent energy efficiency management, intelligent cargo management, intelligent integration platform, remote control, and autonomous operation. Taking the technical realization of each functional module as the goal, this paper analyzes the status quo and development trend of related intelligent technologies and their feasibility and applicability when applied to each functional module. At the same time, it clarifies the composition of specific functional elements of each functional module, puts forward the stage goals of China’s inland intelligent ship development and the specific functional requirements of different modules under each stage, and provides reference for the Chinese government to subsequently formulate the top-level design development planning and implementation path of inland waterway intelligent ships.
The Impact of Offshore Photovoltaic Utilization on Resources and Environment Using Spatial Information Technology
Authors: Wang Peng , Zhou Jingru , Jin Xinfei , Shi Jingchao , Chan Ngai Weng , Tan Mou Leong , Lin Xingwen , Ma Xu , Lin Xia , Zheng Kaixuan , Wu Jiexuan , Zhang Fei
Published: May 2024

In recent years, the rapid development of the photovoltaic (PV) industry has resulted in a saturation of research on onshore PV power plant construction. However, current studies on the impact of marine PVs on the marine environment remain limited and scarce. In order to facilitate the implementation of carbon reduction goals and promote the sustainable development of the offshore PV industry, this study analyzes the environmental impact of PV sea-use resources based on spatial information technology in the western part of Gaotang Island. The findings show that the MIKE21FM model provides relatively accurate simulations of tidal flow and tide level in the marine PV area. Flow velocity in the marine PV area exhibits a decreasing trend, with an average decrease ranging from 0.03 to 0.07 m/s. This decrease minimally affects surrounding navigational channels and large-scale flow fields. The resulting siltation is also deemed less significant, with an annual deposition from 0.03 to 0.06 m/a. Moreover, offshore PV construction resulted in a total intertidal biological loss of 123.45 t. The suspension of sediment during cofferdam construction and removal has a potential effect on zooplankton and fishery resources. Overall, it is proposed that careful planning, prudent site selection, and the execution of countermeasures during marine PV construction will combine to minimize the impact on the marine environment.
Dynamic Stability Analysis of Subsea Tunnel Crossing Active Fault Zone: A Case Study
Authors: Li Zhiqiang , Liu Qiushi , Liu Shian , Liu Xueying , Zhang Yongqiang , Jia Shixiang , Song Guoliang , Zhao Yuting
Published: May 2024

The rock strength in an active fault zone is low and the surrounding rock is fractured and has poor stability, making any subsea tunnel crossing the active fault zone extremely susceptible to disasters such as tunnel collapse, sudden water ingress, and mud inrush. This poses a potential threat to the construction project, making the dynamic stability analysis of a subsea tunnel crossing an active fault zone of great significance. This study takes the second subsea tunnel crossing the Cangkou Fault in Jiaozhou Bay as the engineering background and conducts numerical simulations by employing different lining stiffnesses for tunnel excavation, as well as applying dynamic loads. The dynamic stability of the subsea tunnel crossing the active fault zone is evaluated by comparing and analyzing the lining’s displacement, peak acceleration, and stress characteristics. This study explores the disaster-causing mechanisms of active fractures, determining that the hazard of orthogonal misalignment in an active fault zone is the least severe, while the hazard of opposite misalignment is the most severe. This research provides a basis for disaster prevention and mitigation in active fracture zones.
A Review on Submarine Geological Risks and Secondary Disaster Issues during Natural Gas Hydrate Depressurization Production
Authors: Ma Xianzhuang , Jiang Yujing , Yan Peng , Luan Hengjie , Wang Changsheng , Shan Qinglin , Cheng Xianzhen
Published: May 2024

The safe and efficient production of marine natural gas hydrates faces the challenges of seabed geological risk issues. Geological risk issues can be categorized from weak to strong threats in four aspects: sand production, wellbore instability, seafloor subsidence, and submarine landslides, with the potential risk of natural gas leakage, and the geological risk problems that can cause secondary disasters dominated by gas eruptions and seawater intrusion. If the gas in a reservoir is not discharged in a smooth and timely manner during production, it can build up inside the formation to form super pore pressure leading to a sudden gas eruption when the overburden is damaged. There is a high risk of overburden destabilization around production wells, and reservoirs are prone to forming a connection with the seafloor resulting in seawater intrusion under osmotic pressure. This paper summarizes the application of field observation, experimental research, and numerical simulation methods in evaluating the stability problem of the seafloor surface. The theoretical model of multi-field coupling can be used to describe and evaluate the seafloor geologic risk issues during depressurization production, and the controlling equations accurately describing the characteristics of the reservoir are the key theoretical basis for evaluating the stability of the seafloor geomechanics. It is necessary to seek a balance between submarine formation stability and reservoir production efficiency in order to assess the optimal production and predict the region of plastic damage in the reservoir. Prediction and assessment allow measures to be taken at fixed points to improve reservoir mechanical stability with the numerical simulation method. Hydrate reservoirs need to be filled with gravel to enhance mechanical strength and permeability, and overburden need to be grouted to reinforce stability.
Bio-Priming with Bacillus Isolates Suppresses Seed Infection and Improves the Germination of Garden Peas in the Presence of Fusarium Strains
Authors: Miljaković Dragana , Marinković Jelena , Tamindžić Gordana , Milošević Dragana , Ignjatov Maja , Karačić Vasiljka , Jakšić Snežana
Published: May 2024

Seed infection caused by Fusarium spp. is one of the major threats to the seed quality and yield of agricultural crops, including garden peas. The use of Bacillus spp. with multiple antagonistic and plant growth-promoting (PGP) abilities represents a potential disease control strategy. This study was performed to evaluate the biocontrol potential of new Bacillus spp. rhizosphere isolates against two Fusarium strains affecting garden peas. Six Bacillus isolates identified by 16S rDNA sequencing as B. velezensis (B42), B. subtilis (B43), B. mojavensis (B44, B46), B. amyloliquefaciens (B50), and B. halotolerans (B66) showed the highest in vitro inhibition of F. proliferatum PS1 and F. equiseti PS18 growth (over 40%). The selected Bacillus isolates possessed biosynthetic genes for endoglucanase (B42, B43, B50), surfactin (B43, B44, B46), fengycin (B44, B46), bacillomycin D (B42, B50), and iturin (B42), and were able to produce indole-3-acetic acid (IAA), siderophores, and cellulase. Two isolates, B. subtilis B43 and B. amyloliquefaciens B50, had the highest effect on final germination, shoot length, root length, shoot dry weight, root dry weight, and seedling vigor index of garden peas as compared to the control. Their individual or combined application reduced seed infection and increased seed germination in the presence of F. proliferatum PS1 and F. equiseti PS18, both after seed inoculation and seed bio-priming. The most promising results were obtained in the cases of the bacterial consortium, seed bio-priming, and the more pathogenic strain PS18. The novel Bacillus isolates may be potential biocontrol agents intended for the management of Fusarium seed-borne diseases.
Academic Performance of Excellence: The Impact of Self-Regulated Learning and Academic Time Management Planning
Authors: Lourenço Abílio Afonso , Paiva Maria Olímpia
Published: May 2024

The Program for International Student Assessment highlights the persistent lack of commitment and motivation among students worldwide in their school activities, which are resulting in decreased proficiency levels in reading, mathematics, and science. The magnitude of this phenomenon, with its clear social implications, suggests that we are facing a concerning quest for immediate answers and results. This research focuses on the impact of the relationships between self-regulated learning processes and the planning of time management that is dedicated to school activities on student performance, specifically in the subjects of the Mother Tongue and Mathematics. The instruments used for analysis included the Inventory of Self-Regulated Learning Processes, the Inventory of Time Management Planning, a personal data sheet, and a school data sheet. The sample in this study consisted of 688 students from primary schools in northern Portugal. The results reveal that self-regulated learning has a positive influence on how students plan time management, both in the short and long term. Additionally, a positive and statistically significant relationship is observed between short-term and long-term time management planning and students’ academic performance. This study provides an in-depth perspective on the dynamics between these elements, shedding light on the crucial nuances that shape students’ academic journeys.
The Syntax of Speech Acts: Deictic Inversion as an Evidential Strategy in English
Authors: Ojea Ana
Published: May 2024

This paper presents empirical evidence to support the so-called syntactization of discourse, that is, the projection of relevant pragmatic features in the narrow syntax. In particular, it analyses deictic inversion in English, a construction which is used by the speaker to point at a proximal or distal location and bring the addressee’s attention to an entity related to that location (e.g., Here comes the bus). It offers a novel account of this construction, which takes it to be an evidential strategy in a language that does not have standard evidential markers; this evidential status explains its main differences with locative inversion, a construction with which it is pragmatically and structurally related. Deictic inversion therefore receives a natural explanation in a framework that maps syntax with the speech act and introduces in the derivation pragmatic information about the participants in the communicative exchange and about the source of the information for the proposition asserted.
A Review of Chemical Modification of Vegetable Oils and Their Applications
Authors: Zeng Yongjing , Shang Zichen , Zheng Zeni , Shi Ning , Yang Bo , Han Sheng , Yan Jincan
Published: May 2024

In order to cope with the shortage of non-renewable energy and the increasingly environmental pollution, sustainable vegetable oils, as competitive alternatives, have widely been held in the good graces of the researchers. Vegetable oils are suitable for a wide range of applications such as biofuels and biodiesel. However, the development of vegetable oils is limited due to the characteristics of unsatisfactory oxidation stability and poor cold-flow properties. Chemical modification is considered as an effective solution to enhance the performance. The research progress of the chemical modification methods and applications of vegetable oils in recent years are summarized in this review. Reducing the content of carbon–carbon double bonds and increasing the degree of saturation are the keys to improve the physicochemical properties of vegetable oils. The prospects for the development direction and challenges of vegetable oils are proposed. Future research may focus on the use of multifunctional catalysts to optimize reaction conditions or to introduce active groups with lubricating properties in epoxidation reactions and explore the combination of chemical and auxiliary methods.
Effect of Graphene Oxide Nanomaterials on the Durability of Concrete: A Review on Mechanisms, Provisions, Challenges, and Future Prospects
Authors: Udumulla Danula , Ginigaddara Thusitha , Jayasinghe Thushara , Mendis Priyan , Baduge Shanaka
Published: May 2024

This review focuses on recent advances in concrete durability using graphene oxide (GO) as a nanomaterial additive, with a goal to fill the gap between concrete technology, chemical interactions, and concrete durability, whilst providing insights for the adaptation of GO as an additive in concrete construction. An overview of concrete durability applications, key durability failure mechanisms of concrete, transportation mechanisms, chemical reactions involved in compromising durability, and the chemical alterations within a concrete system are discussed to understand how they impact the overall durability of concrete. The existing literature on the durability and chemical resistance of GO-reinforced concrete and mortar was reviewed and summarized. The impacts of nano-additives on the durability of concrete and its mechanisms are thoroughly discussed, particularly focusing on GO as the primary nanomaterial and its impact on durability. Finally, research gaps, future recommendations, and challenges related to the durability of mass-scale GO applications are presented.
Progress Made in Non-Metallic-Doped Materials for Electrocatalytic Reduction in Ammonia Production
Authors: Quoie Jr Gerald D. S. , Jiao Mingshuo , Lászlód Krisztina , Wang Ying
Published: May 2024

The electrocatalytic production of ammonia has garnered considerable interest as a potentially sustainable technology for ammonia synthesis. Recently, non-metallic-doped materials have emerged as promising electrochemical catalysts for this purpose. This paper presents a comprehensive review of the latest research on non-metallic-doped materials for electrocatalytic ammonia production. Researchers have engineered a variety of materials, doped with non-metals such as nitrogen (N), boron (B), phosphorus (P), and sulfur (S), into different forms and structures to enhance their electrocatalytic activity and selectivity. A comparison among different non-metallic dopants reveals their distinct effects on the electrocatalytic performance for ammonia production. For instance, N-doping has shown enhanced activity owing to the introduction of nitrogen vacancies (NVs) and improved charge transfer kinetics. B-doping has demonstrated improved selectivity and stability, which is attributed to the formation of active sites and the suppression of competing reactions. P-doping has exhibited increased ammonia generation rates and Faradaic efficiencies, likely due to the modification of the electronic structure and surface properties. S-doping has shown potential for enhancing electrocatalytic performance, although further investigations are needed to elucidate the underlying mechanisms. These comparisons provide valuable insights for researchers to conduct in-depth studies focusing on specific non-metallic dopants, exploring their unique properties, and optimizing their performance for electrocatalytic ammonia production. However, we consider it a priority to provide insight into the recent progress made in non-metal-doped materials and their potential for enabling long-term and efficient electrochemical ammonia production. Additionally, this paper discusses the synthetic procedures used to produce non-metal-doped materials and highlights the advantages and disadvantages of each method. It also provides an in-depth analysis of the electrochemical performance of these materials, including their Faradaic efficiencies, ammonia yield rate, and selectivity. It examines the challenges and prospects of developing non-metallic-doped materials for electrocatalytic ammonia production and suggests future research directions.
Influence of Hf Doping on the Oxygen Behaviors on ZrCo(110) Surface Using First-Principles Calculation
Authors: Qian Ruijun , Habibullah  , Ye Meitong , Cen Wanglai , Wu Chaoling
Published: May 2024

ZrCo alloy is easily poisoned by impurity gases such as O2, CO, and CO2, resulting in a deterioration in hydrogen storage performance. In this study, we conducted a comprehensive investigation into the adsorption and dissociation characteristics of oxygen on the ZrCo(110) surface using first-principles calculations. Previous studies indicated that the anti-disproportionation properties of ZrCo alloy can be significantly improved by Hf substitution, but the effect of Hf doping on the anti-poisoning properties has not been reported. We also examined the effect of Hf doping on the adsorption, dissociation, and diffusion characteristics of oxygen. It is found that on the ZrCo(110) surface, O2 molecules are easily dissociated and then stably adsorbed at the hollow site. Oxygen atoms will fill the surface preferentially and then diffuse inward. The doping of Hf has an insignificant impact on the adsorption or dissociation behavior of oxygen in comparison to the pure ZrCo surface. However, a notable observation is that the doping of Hf resulted in a reduction in the diffusion barrier for oxygen from the surface to the subsurface by 0.61 eV. Consequently, our study suggests that doping Hf is not an advisable strategy for improving the ZrCo(110) surface’s resistance to O2 poisoning because of improved oxygen permeability.
Artificial Neuron Based on the Bloch-Point Domain Wall in Ferromagnetic Nanowires
Authors: Sánchez Carlos , Caso Diego , Aliev Farkhad G.
Published: May 2024

Nanomagnetism and spintronics are currently active areas of research, with one of the main goals being the creation of low-energy-consuming magnetic memories based on nanomagnet switching. These types of devices could also be implemented in neuromorphic computing by crafting artificial neurons (ANs) that emulate the characteristics of biological neurons through the implementation of neuron models such as the widely used leaky integrate-and-fire (LIF) with a refractory period. In this study, we have carried out numerical simulations of a 120 nm diameter, 250 nm length ferromagnetic nanowire (NW) with the aim of exploring the design of an artificial neuron based on the creation and destruction of a Bloch-point domain wall. To replicate signal integration, we applied pulsed trains of spin currents to the opposite faces of the ferromagnetic NW. These pulsed currents (previously studied only in the continuous form) are responsible for inducing transitions between the stable single vortex (SV) state and the metastable Bloch point domain wall (BP-DW) state. To ensure the system exhibits leak and refractory properties, the NW was placed in a homogeneous magnetic field of the order of mT in the axial direction. The suggested configuration fulfills the requirements and characteristics of a biological neuron, potentially leading to the future creation of artificial neural networks (ANNs) based on reversible changes in the topology of magnetic NWs.
Novel Hybrid Ferromagnetic Fe–Co/Nanodiamond Nanostructures: Influence of Carbon on Their Structural and Magnetic Properties
Authors: Ziogas Panagiotis G. , Bourlinos Athanasios B. , Chatzopoulou Polyxeni , Dimitrakopulos George P. , Markou Anastasios , Douvalis Alexios P.
Published: May 2024

This study introduces a novel magnetic nanohybrid material consisting of ferromagnetic (FM) bcc Fe–Co nanoparticles (NPs) grown on nanodiamond (ND) nanotemplates. A combination of wet chemistry, which produces chemical precursors and their subsequent thermal treatment under vacuum, was utilized for its development. The characterization and study of the prepared samples performed with a range of specialized experimental techniques reveal that thermal treatment of the as-prepared hybrid precursors under a range of annealing conditions leads to the development of Co-rich Fe–Co alloy NPs, with average sizes in the range of 6–10 nm, that exhibit uniform distribution on the surfaces of the ND nanotemplates and demonstrate FM behavior throughout a temperature range from 2 K to 400 K, with maximum magnetization values ranging between 18.9 and 21.1 emu/g and coercivities ranging between 112 and 881 Oe. Moreover, 57Fe Mössbauer spectroscopy reveals that apart from the predominant bcc FM Fe–Co phase, iron atoms also participate in the formation of a secondary martensitic-type Fe–Co phase. The emergence of this distinctive phase is attributed to the diffusion of carbon atoms within the Fe–Co lattices during their formation at elevated temperatures. The source of these carbon atoms is related to the unique morphological properties of the ND growth matrices, which facilitate surface sp2 formations. Apart from their diffusion within the Fe–Co NP lattice, the carbon atoms also reconstruct layered graphitic-type nanostructures enveloping the metallic alloy NPs. These non-typical nanohybrid materials, reported here for the first time in the literature, hold significant potential for use in applications related, but not limited to, biomedicine, biopharmaceutics, catalysis, and other various contemporary technological fields.
Robustness of Real-World Networks after Weight Thresholding with Strong Link Removal
Authors: John Jisha Mariyam , Bellingeri Michele , Lekha Divya Sindhu , Cassi Davide , Alfieri Roberto
Published: May 2024

Weight thresholding (WT) is a method intended to decrease the number of links within weighted networks that may otherwise be excessively dense for network science applications. WT aims to remove links to simplify the network by holding most of the features of the original network. Here, we test the robustness and the efficacy of the node attack strategies on real-world networks subjected to WT that remove links of higher weight (strong links). We measure the network robustness along node removal with the largest connected component (LCC). We find that the real-world networks under study are generally robust when subjected to WT. Nonetheless, WT with strong link removal changes the efficacy of the attack strategies and the rank of node centralities. Also, WT with strong link removal may trigger a more significant change in the node centrality rank than WT by removing weak links. Network science research with the aim to find important/influential nodes in the network has to consider that simplifying the network with WT methodologies may change the node centrality.
Markov Chains and Kinetic Theory: A Possible Application to Socio-Economic Problems
Authors: Carbonaro Bruno , Menale Marco
Published: May 2024

A very important class of models widely used nowadays to describe and predict, at least in stochastic terms, the behavior of many-particle systems (where the word “particle” is not meant in the purely mechanical sense: particles can be cells of a living tissue, or cars in a traffic flow, or even members of an animal or human population) is the Kinetic Theory for Active Particles, i.e., a scheme of possible generalizations and re-interpretations of the Boltzmann equation. Now, though in the literature on the subject this point is systematically disregarded, this scheme is based on Markov Chains, which are special stochastic processes with important properties they share with many natural processes. This circumstance is here carefully discussed not only to suggest the different ways in which Markov Chains can intervene in equations describing the stochastic behavior of any many-particle system, but also, as a preliminary methodological step, to point out the way in which the notion of a Markov Chain can be suitably generalized to this aim. As a final result of the discussion, we find how to develop new very plausible and likely ways to take into account possible effects of the external world on a non-isolated many-particle system, with particular attention paid to socio-economic problems.
Novel Automatic Classification of Human Adult Lung Alveolar Type II Cells Infected with SARS-CoV-2 through the Deep Transfer Learning Approach
Authors: Turki Turki , Al Habib Sarah , Taguchi Y-h.
Published: May 2024

Transmission electron microscopy imaging provides a unique opportunity to inspect the detailed structure of infected lung cells with SARS-CoV-2. Unlike previous studies, this novel study aims to investigate COVID-19 classification at the lung cellular level in response to SARS-CoV-2. Particularly, differentiating between healthy and infected human alveolar type II (hAT2) cells with SARS-CoV-2. Hence, we explore the feasibility of deep transfer learning (DTL) and introduce a highly accurate approach that works as follows: First, we downloaded and processed 286 images pertaining to healthy and infected hAT2 cells obtained from the electron microscopy public image archive. Second, we provided processed images to two DTL computations to induce ten DTL models. The first DTL computation employs five pre-trained models (including DenseNet201 and ResNet152V2) trained on more than one million images from the ImageNet database to extract features from hAT2 images. Then, it flattens and provides the output feature vectors to a trained, densely connected classifier with the Adam optimizer. The second DTL computation works in a similar manner, with a minor difference in that we freeze the first layers for feature extraction in pre-trained models while unfreezing and jointly training the next layers. The results using five-fold cross-validation demonstrated that TFeDenseNet201 is 12.37× faster and superior, yielding the highest average ACC of 0.993 (F1 of 0.992 and MCC of 0.986) with statistical significance (P<2.2×10−16 from a t-test) compared to an average ACC of 0.937 (F1 of 0.938 and MCC of 0.877) for the counterpart (TFtDenseNet201), showing no significance results (P=0.093 from a t-test).