bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Knowledge and Self-Awareness of Polish Soldiers Regarding Exposure to Chemical and Physical Factors in Their Place of Service/Work
Authors: Ejchman-Pac Ewelina , Rzepka Małgorzata , Gierlach Małgorzata , Szymański Paweł , Zawadzka Magdalena
Published: February 2024

Introduction: Soldiers constitute a professional group carrying out their duties in variable, often challenging environmental conditions, including harmful and burdensome ones. Materials and Methods: This study was conducted on a nationwide sample of 1331 soldiers. The research tool was an anonymous questionnaire comprising 48 questions. Descriptive statistics were used to describe the characteristics of the studied group. The chi-square test was employed to examine the relationship between variables. A 95% confidence interval was adopted, with a significance level of p = 0.05. Results: One in four soldiers work with low and one in five with moderate exposure to harmful chemical factors. Almost 10% of respondents lack knowledge about the types of chemical factors present during their service. One in five soldiers work with low and one in eight with moderate exposure to ionizing radiation. Approximately 5% of survey participants lack knowledge about the types of physical factors. One in three soldiers are unaware of the carcinogenic and mutagenic effects of the aforementioned factors. Conclusions: The systematic enhancement of knowledge and awareness among army members will help minimize the consequences of exposure to harmful conditions.
Indigenous Knowledge in Post-Pandemic Cultural Tourism: Discussion from Arauco Territories, Chile
Authors: Carrasco Henríquez Noelia , Cid Aguayo Beatriz , Neves Guzmán Camila , Orellana Ojeda Juanita
Published: February 2024

In the last two decades, cultural tourism has transformed the aesthetics and the relationship between the actors of the Arauco territories. In the post-COVID context, these transformations could be reinforced, especially considering the actual legal scenario about indigenous rights and the global ecological crisis. In most cases, the indigenous people, with cultural tourism initiatives, highlight their world vision, including the relations with nature. For this reason, we propose to study this scientific problem from the relational ontology perspective. In this study, we describe the situation of cultural tourism in Arauco Province, Chile, where Mapuche people, the Chilean State, and the international market coexist in permanent friction. The main objective is to analyze how the pandemic influenced Mapuche cultural tourism, from the Mapuche cultural perspective and the global conditions for their development. The methods of research mixed historical and ethnographic approaches with a sample of key actors of Mapuche cultural tourism. As results, we can show the Mapuche way of understanding cultural tourism and the new conditions derived from the pandemic and post-pandemic contexts.
Identification of Candidate Genes Controlling Red Seed Coat Color in Cowpea (Vigna unguiculata [L.] Walp)
Authors: Herniter Ira A. , Muñoz-Amatriaín María , Lo Sassoum , Guo Yi-Ning , Lonardi Stefano , Close Timothy J.
Published: February 2024

Seed coat color is an important consumer-related trait of the cowpea (Vigna unguiculata [L.] Walp.) and has been a subject of study for over a century. Utilizing newly available resources, including mapping populations, a high-density genotyping platform, and several genome assemblies, the red seed coat color has been mapped to two loci, Red-1 (R-1) and Red-2 (R-2), on Vu03 and Vu07, respectively. A gene model (Vigun03g118700) encoding a dihydroflavonol 4-reductase, a homolog of anthocyanidin reductase 1, which catalyzes the biosynthesis of epicatechin from cyanidin, has been identified as a candidate gene for R-1. Possible causative variants have also been identified for Vigun03g118700. A gene model on Vu07 (Vigun07g118500), with predicted nucleolar function and high relative expression in the developing seed, has been identified as a candidate for R-2. The observed red color is believed to be the result of a buildup of cyanidins in the seed coat.
Acerola (Malpighia emarginata) Anti-Inflammatory Activity—A Review
Authors: Olędzki Remigiusz , Harasym Joanna
Published: February 2024

The manuscript provides an overview of recent scientific reports on the properties and range of health-promoting effects of acerola (Malpighia emarginata DC) fruits and leaves. Acerola is a natural raw material that, in its unprocessed form, is known to be a rich source of vitamin C and polyphenolic compounds. For this reason, the consumption of acerola may provide a number of health-promoting benefits, particularly related to its strong anti-free radical effects. The review discusses anti-inflammatory and anticancer effects of acerola fruit and leaves as well as its therapeutic effects on selected physiological processes in the human system. Their biochemical mechanisms are also explained. Recommendations for the consumption of acerola in the prevention of inflammatory and free radical diseases are presented. The part of the article devoted to anticancer effects of acerola describes the possibilities of using the edible parts of this raw material to obtain products and preparations of potential use in cancer prevention and therapy.
Bioactive Compounds from Plant Origin as Natural Antimicrobial Agents for the Treatment of Wound Infections
Authors: Pacyga Katarzyna , Pacyga Paweł , Topola Ewa , Viscardi Szymon , Duda-Madej Anna
Published: February 2024

The rising prevalence of drug-resistant bacteria underscores the need to search for innovative and nature-based solutions. One of the approaches may be the use of plants that constitute a rich source of miscellaneous compounds with a wide range of biological properties. This review explores the antimicrobial activity of seven bioactives and their possible molecular mechanisms of action. Special attention was focused on the antibacterial properties of berberine, catechin, chelerythrine, cinnamaldehyde, ellagic acid, proanthocyanidin, and sanguinarine against Staphylococcus aureus, Enterococcus spp., Klebsiella pneumoniae, Acinetobacter baumannii, Escherichia coli, Serratia marcescens and Pseudomonas aeruginosa. The growing interest in novel therapeutic strategies based on new plant-derived formulations was confirmed by the growing number of articles. Natural products are one of the most promising and intensively examined agents to combat the consequences of the overuse and misuse of classical antibiotics.
Gene Expression-Based Cancer Classification for Handling the Class Imbalance Problem and Curse of Dimensionality
Authors: Al-Azani Sadam , Alkhnbashi Omer S. , Ramadan Emad , Alfarraj Motaz
Published: February 2024

Cancer is a leading cause of death globally. The majority of cancer cases are only diagnosed in the late stages of cancer due to the use of conventional methods. This reduces the chance of survival for cancer patients. Therefore, early detection consequently followed by early diagnoses are important tasks in cancer research. Gene expression microarray technology has been applied to detect and diagnose most types of cancers in their early stages and has gained encouraging results. In this paper, we address the problem of classifying cancer based on gene expression for handling the class imbalance problem and the curse of dimensionality. The oversampling technique is utilized to overcome this problem by adding synthetic samples. Another common issue related to the gene expression dataset addressed in this paper is the curse of dimensionality. This problem is addressed by applying chi-square and information gain feature selection techniques. After applying these techniques individually, we proposed a method to select the most significant genes by combining those two techniques (CHiS and IG). We investigated the effect of these techniques individually and in combination. Four benchmarking biomedical datasets (Leukemia-subtypes, Leukemia-ALLAML, Colon, and CuMiDa) were used. The experimental results reveal that the oversampling techniques improve the results in most cases. Additionally, the performance of the proposed feature selection technique outperforms individual techniques in nearly all cases. In addition, this study provides an empirical study for evaluating several oversampling techniques along with ensemble-based learning. The experimental results also reveal that SVM-SMOTE, along with the random forests classifier, achieved the highest results, with a reporting accuracy of 100%. The obtained results surpass the findings in the existing literature as well.
TGF-β Isoforms and GDF-15 in the Development and Progression of Atherosclerosis
Authors: Liuizė (Abramavičiūtė) Agnė , Mongirdienė Aušra
Published: February 2024

The effect of oxidised lipoproteins on the endothelium, monocytes, platelets, and macrophages is a key factor in the initiation and development of atherosclerosis. Antioxidant action, lipoprotein metabolism, and chronic inflammation are the fields of research interest for better understanding the development of the disease. All the fields are related to inflammation and hence to the secretion of cytokines, which are being investigated as potential diagnostic markers for the onset of atherosclerosis. Pathways of vascular damage are crucial for the development of new laboratory readouts. The very early detection of endothelial cell damage associated with the onset of atherosclerosis, allowing the initiation of therapy, remains a major research goal. This article summarises the latest results on the relationship of tumour growth factor beta (TGF-β) isoforms and growth differentiation factor 15 (GDF-15) to the pathogenesis of atherosclerosis: which cells involved in atherosclerosis produce them, which effectors stimulate their synthesis and secretion, how they influence atherosclerosis development, and the relationship between the levels of TGF-β and GDF-15 in the blood and the development and extent of atherosclerosis.
Bacteriophages—Dangerous Viruses Acting Incognito or Underestimated Saviors in the Fight against Bacteria?
Authors: Podlacha Magdalena , Węgrzyn Grzegorz , Węgrzyn Alicja
Published: February 2024

The steadily increasing number of drug-resistant bacterial species has prompted the search for alternative treatments, resulting in a growing interest in bacteriophages. Although they are viruses infecting bacterial cells, bacteriophages are an extremely important part of the human microbiota. By interacting with eukaryotic cells, they are able to modulate the functioning of many systems, including the immune and nervous systems, affecting not only the homeostasis of the organism, but potentially also the regulation of pathological processes. Therefore, the aim of this review is to answer the questions of (i) how animal/human immune systems respond to bacteriophages under physiological conditions and under conditions of reduced immunity, especially during bacterial infection; (ii) whether bacteriophages can induce negative changes in brain functioning after crossing the blood–brain barrier, which could result in various disorders or in an increase in the risk of neurodegenerative diseases; and (iii) how bacteriophages can modify gut microbiota. The crucial dilemma is whether administration of bacteriophages is always beneficial or rather if it may involve any risks.
ApoE Isoforms Inhibit Amyloid Aggregation of Proinflammatory Protein S100A9
Authors: Ghosh Shamasree , Tamilselvi Shanmugam , Williams Chloe , Jayaweera Sanduni W. , Iashchishyn Igor A. , Šulskis Darius , Gilthorpe Jonathan D. , Olofsson Anders , Smirnovas Vytautas , Svedružić Željko M. , Morozova-Roche Ludmilla A.
Published: February 2024

Increasing evidence suggests that the calcium-binding and proinflammatory protein S100A9 is an important player in neuroinflammation-mediated Alzheimer’s disease (AD). The amyloid co-aggregation of S100A9 with amyloid-β (Aβ) is an important hallmark of this pathology. Apolipoprotein E (ApoE) is also known to be one of the important genetic risk factors of AD. ApoE primarily exists in three isoforms, ApoE2 (Cys112/Cys158), ApoE3 (Cys112/Arg158), and ApoE4 (Arg112/Arg158). Even though the difference lies in just two amino acid residues, ApoE isoforms produce differential effects on the neuroinflammation and activation of the microglial state in AD. Here, we aim to understand the effect of the ApoE isoforms on the amyloid aggregation of S100A9. We found that both ApoE3 and ApoE4 suppress the aggregation of S100A9 in a concentration-dependent manner, even at sub-stoichiometric ratios compared to S100A9. These interactions lead to a reduction in the quantity and length of S100A9 fibrils. The inhibitory effect is more pronounced if ApoE isoforms are added in the lipid-free state versus lipidated ApoE. We found that, upon prolonged incubation, S100A9 and ApoE form low molecular weight complexes with stochiometric ratios of 1:1 and 2:1, which remain stable under SDS-gel conditions. These complexes self-assemble also under the native conditions; however, their interactions are transient, as revealed by glutaraldehyde cross-linking experiments and molecular dynamics (MD) simulation. MD simulation demonstrated that the lipid-binding C-terminal domain of ApoE and the second EF-hand calcium-binding motif of S100A9 are involved in these interactions. We found that amyloids of S100A9 are cytotoxic to neuroblastoma cells, and the presence of either ApoE isoforms does not change the level of their cytotoxicity. A significant inhibitory effect produced by both ApoE isoforms on S100A9 amyloid aggregation can modulate the amyloid-neuroinflammatory cascade in AD.
Bovine Pluripotent Stem Cells: Current Status and Prospects
Authors: Chen Lanxin , Tang Bo , Xie Guanghong , Yang Rui , Zhang Boyang , Wang Yueqi , Zhang Yan , Jiang Daozhen , Zhang Xueming
Published: February 2024

Pluripotent stem cells (PSCs) can differentiate into three germ layers and diverse autologous cell lines. Since cattle are the most commonly used large domesticated animals, an important food source, and bioreactors, great efforts have been made to establish bovine PSCs (bPSCs). bPSCs have great potential in bovine breeding and reproduction, modeling in vitro differentiation, imitating cancer development, and modeling diseases. Currently, bPSCs mainly include bovine embryonic stem cells (bESCs), bovine induced pluripotent stem cells (biPSCs), and bovine expanded potential stem cells (bEPSCs). Establishing stable bPSCs in vitro is a critical scientific challenge, and researchers have made numerous efforts to this end. In this review, the category of PSC pluripotency; the establishment of bESCs, biPSCs, and bEPSCs and its challenges; and the application outlook of bPSCs are discussed, aiming to provide references for future research.
Evaluation of Antitumor Activity of Xanthones Conjugated with Amino Acids
Authors: Barbosa Flávia , Araújo Joana , Gonçalves Virgínia M. F. , Palmeira Andreia , Cunha Andrea , Silva Patrícia M. A. , Fernandes Carla , Pinto Madalena , Bousbaa Hassan , Queirós Odília , Tiritan Maria Elizabeth
Published: February 2024

Cancer is a complex disease characterized by several alterations, which confer, to the cells, the capacity to proliferate uncontrollably and to resist cellular death. Multiresistance to conventional chemotherapy drugs is often the cause of treatment failure; thus, the search for natural products or their derivatives with therapeutic action is essential. Chiral derivatives of xanthones (CDXs) have shown potential inhibitory activity against the growth of some human tumor cell lines. This work reports the screening of a library of CDXs, through viability assays, in different cancer cell lines: A375-C5, MCF-7, NCI-H460, and HCT-15. CDXs’ effect was analyzed based on several parameters of cancer cells, and it was also verified if these compounds were substrates of glycoprotein-P (Pgp), one of the main mechanisms of resistance in cancer therapy. Pgp expression was evaluated in all cell lines, but no expression was observed, except for HCT-15. Also, when a humanized yeast expressing the human gene MDR1 was used, no conclusions could be drawn about CDXs as Pgp substrates. The selected CDXs did not induce significant differences in the metabolic parameters analyzed. These results show that some CDXs present promising antitumor activity, but other mechanisms should be triggered by these compounds.
Developing Folate-Conjugated miR-34a Therapeutic for Prostate Cancer: Challenges and Promises
Authors: Li Wen (Jess) , Wang Yunfei , Liu Xiaozhuo , Wu Shan , Wang Moyi , Turowski Steven G. , Spernyak Joseph A. , Tracz Amanda , Abdelaal Ahmed M. , Sudarshan Kasireddy , Puzanov Igor , Chatta Gurkamal , Kasinski Andrea L. , Tang Dean G.
Published: February 2024

Prostate cancer (PCa) remains a common cancer with high mortality in men due to its heterogeneity and the emergence of drug resistance. A critical factor contributing to its lethality is the presence of prostate cancer stem cells (PCSCs), which can self-renew, long-term propagate tumors, and mediate treatment resistance. MicroRNA-34a (miR-34a) has shown promise as an anti-PCSC therapeutic by targeting critical molecules involved in cancer stem cell (CSC) survival and functions. Despite extensive efforts, the development of miR-34a therapeutics still faces challenges, including non-specific delivery and delivery-associated toxicity. One emerging delivery approach is ligand-mediated conjugation, aiming to achieve specific delivery of miR-34a to cancer cells, thereby enhancing efficacy while minimizing toxicity. Folate-conjugated miR-34a (folate–miR-34a) has demonstrated promising anti-tumor efficacy in breast and lung cancers by targeting folate receptor α (FOLR1). Here, we first show that miR-34a, a TP53 transcriptional target, is reduced in PCa that harbors TP53 loss or mutations and that miR-34a mimic, when transfected into PCa cells, downregulated multiple miR-34a targets and inhibited cell growth. When exploring the therapeutic potential of folate–miR-34a, we found that folate–miR-34a exhibited impressive inhibitory effects on breast, ovarian, and cervical cancer cells but showed minimal effects on and targeted delivery to PCa cells due to a lack of appreciable expression of FOLR1 in PCa cells. Folate–miR-34a also did not display any apparent effect on PCa cells expressing prostate-specific membrane antigen (PMSA) despite the reported folate’s binding capability to PSMA. These results highlight challenges in the specific delivery of folate–miR-34a to PCa due to a lack of target (receptor) expression. Our study offers novel insights into the challenges and promises within the field and casts light on the development of ligand-conjugated miR-34a therapeutics for PCa.
Differential Photosensitivity of Fibroblasts Obtained from Normal Skin and Hypertrophic Scar Tissues
Authors: Kusumoto Junya , Akashi Masaya , Terashi Hiroto , Sakakibara Shunsuke
Published: February 2024

It is unclear whether normal human skin tissue or abnormal scarring are photoreceptive. Therefore, this study investigated photosensitivity in normal skin tissue and hypertrophic scars. The expression of opsins, which are photoreceptor proteins, in normal dermal fibroblasts (NDFs) and hypertrophic scar fibroblasts (HSFs) was examined. After exposure to blue light (BL), changes in the expression levels of αSMA and clock-related genes, specifically PER2 and BMAL1, were examined in both fibroblast types. Opsins were expressed in both fibroblast types, with OPN3 exhibiting the highest expression levels. After peripheral circadian rhythm disruption, BL induced rhythm formation in NDFs. In contrast, although HSFs showed changes in clock-related gene expression levels, no distinct rhythm formation was observed. The expression level of αSMA was significantly higher in HSFs and decreased to the same level as that in NDFs upon BL exposure. When OPN3 knocked-down HSFs were exposed to BL, the reduction in αSMA expression was inhibited. This study showed that BL exposure directly triggers peripheral circadian synchronization in NDFs but not in HSFs. OPN3-mediated BL exposure inhibited HSFs. Although the current results did not elucidate the relationship between peripheral circadian rhythms and hypertrophic scars, they show that BL can be applied for the prevention and treatment of hypertrophic scars and keloids.
Genomic Analysis of Romanian Lycium Genotypes: Exploring BODYGUARD Genes for Stress Resistance Breeding
Authors: Ciceoi Roxana , Asanica Adrian , Luchian Vasilica , Iordachescu Mihaela
Published: February 2024

Goji berries, long valued in Traditional Chinese Medicine and Asian cuisine for their wide range of medicinal benefits, are now considered a ‘superfruit’ and functional food worldwide. Because of growing demand, Europe and North America are increasing their goji berry production, using goji berry varieties that are not originally from these regions. European breeding programs are focusing on producing Lycium varieties adapted to local conditions and market demands. By 2023, seven varieties of goji berries were successfully registered in Romania, developed using germplasm that originated from sources outside the country. A broader project focused on goji berry breeding was initiated in 2014 at USAMV Bucharest. In the present research, five cultivated and three wild L. barbarum genotypes were compared to analyse genetic variation at the whole genome level. In addition, a case study presents the differences in the genomic coding sequences of BODYGUARD (BDG) 3 and 4 genes from chromosomes 4, 8, and 9, which are involved in cuticle-related resistance. All three BDG genes show distinctive differences between the cultivated and wild-type genotypes at the SNP level. In the BDG 4 gene located on chromosome 8, 69% of SNPs differentiate the wild from the cultivated genotypes, while in BDG 3 on chromosome 4, 64% of SNPs could tell the difference between the wild and cultivated goji berry. The research also uncovered significant SNP and InDel differences between cultivated and wild genotypes, in the entire genome, providing crucial insights for goji berry breeders to support the development of goji berry cultivation in Romania.
Correction: Zhang et al. An Integrated Access and Backhaul Approach to Sustainable Dense Small Cell Network Planning. Information 2024, 15, 19
Authors: Zhang Jie , Wang Qiao , Mitchell Paul , Ahmadi Hamed
Published: February 2024

Due to an Editorial Office error [...]
Design, Preparation, and Characterization of Polycaprolactone–Chitosan Nanofibers via Electrospinning Techniques for Efficient Methylene Blue Removal from Aqueous Solutions
Authors: Saleh Hind M. , Albukhaty Salim , Sulaiman Ghassan M. , Abomughaid Mosleh M.
Published: February 2024

The effective removal of organic dyes from aqueous solutions is of paramount importance in addressing environmental pollution challenges. Methylene blue (MB), a prevalent cationic dye in various industries, has raised concerns due to its persistence and potential adverse effects on ecosystems. This study explores the design, preparation, and characterization of Polycaprolactone–Chitosan (PCL–CH) nanofibers via electrospinning for the removal of MB. PCL, known for its biodegradability and mechanical properties, serves as the primary matrix, while chitosan (CH), with its biocompatibility and amino functionalities, offers enhanced adsorption potential. The electrospinning process yields nanofibers with tailored compositions and controlled morphology. The synthesized nanofibers are systematically characterized, encompassing structural analysis by Fourier transform infrared (FT–IR), spectroscopy, morphology, and composition assessment via Field emission scanning electron microscopy (FE-SEM) and energy-dispersive X-ray spectroscopy (EDS), zeta potential, as well as rheological behavior evaluation. The adsorption uptake of MB onto these nanofibers is investigated, considering the influence of solution pH and initial dye concentration. The results reveal significant enhancements in adsorption capacity, especially with the incorporation of CH, with the PCL–CH 30% nanofibers exhibiting outstanding performance. The pH-dependent behavior underscores the importance of environmental factors in the adsorption process, while higher dye concentrations provide a stronger driving force for adsorption. These findings position PCL–CH nanofibers as promising adsorbents for the efficient removal of MB and potentially other organic contaminants from aqueous solutions. The study contributes to the development of sustainable materials for environmental remediation, wastewater treatment, and related applications, aligning with ongoing efforts to address water pollution challenges.
Effect of Silicon Nanoparticles on Moisture Absorption and Fracture Toughness of Polymethyl Methacrylate Matrix Nanocomposites
Authors: Golshokouh Mohammad Ali , Refahati Nima , Saffari Pouyan Roodgar
Published: February 2024

The effect of silicon nanoparticles with different percentages (2, 5, 7, and 10 wt.%) on moisture absorption in environments with different pHs (5, 6, 7, 8, 9) as well as fracture toughness of polymethyl methacrylate is discussed. The samples were prepared using pressure molding. Fracture strength was tested via the three-point bending method according to the ASTM D5045 standard and moisture absorption rate according to the absorption test according to the ASTM D570 standard. SEM images show that up to 7%, the dispersion of silica nanoparticles is acceptable, but the homogeneity is not acceptable at 10%. The results indicate that the increase in silica nanoparticles has improved the fracture toughness of the manufactured parts. The highest fracture toughness improvement is about 57% in the optimal state at 5%. Also, increasing silica nanoparticles increased the moisture absorption in the produced samples. In addition, as the acidic or base of the liquid moves to neutral, the reaction between the base polymer molecules and the test liquid decreases and, so, the moisture absorption also increases.
Exploration of Interpretability Techniques for Deep COVID-19 Classification Using Chest X-ray Images
Authors: Chatterjee Soumick , Saad Fatima , Sarasaen Chompunuch , Ghosh Suhita , Krug Valerie , Khatun Rupali , Mishra Rahul , Desai Nirja , Radeva Petia , Rose Georg , Stober Sebastian , Speck Oliver , Nürnberger Andreas
Published: February 2024

The outbreak of COVID-19 has shocked the entire world with its fairly rapid spread, and has challenged different sectors. One of the most effective ways to limit its spread is the early and accurate diagnosing of infected patients. Medical imaging, such as X-ray and computed tomography (CT), combined with the potential of artificial intelligence (AI), plays an essential role in supporting medical personnel in the diagnosis process. Thus, in this article, five different deep learning models (ResNet18, ResNet34, InceptionV3, InceptionResNetV2, and DenseNet161) and their ensemble, using majority voting, have been used to classify COVID-19, pneumoniæ and healthy subjects using chest X-ray images. Multilabel classification was performed to predict multiple pathologies for each patient, if present. Firstly, the interpretability of each of the networks was thoroughly studied using local interpretability methods—occlusion, saliency, input X gradient, guided backpropagation, integrated gradients, and DeepLIFT—and using a global technique—neuron activation profiles. The mean micro F1 score of the models for COVID-19 classifications ranged from 0.66 to 0.875, and was 0.89 for the ensemble of the network models. The qualitative results showed that the ResNets were the most interpretable models. This research demonstrates the importance of using interpretability methods to compare different models before making a decision regarding the best performing model.
Collision-Free Formation-Containment Tracking of Multi-USV Systems with Constrained Velocity and Driving Force
Authors: Wang Jingchen , Shan Qihe , Li Tieshan , Xiao Geyang , Xu Qi
Published: February 2024

This paper studied the collision avoidance issue in the formation-containment tracking control of multi-USVs (unmanned surface vehicles) with constrained velocity and driving force. Specifically, based on a dual-layer control framework, it designed a multi-USV formation-containment tracking control strategy that accounts for constrained motion velocity and input driving force and validated the stability of this strategy using the Lyapunov method. Then, by utilizing zeroing control barrier function certificates, it considered collision avoidance among USVs with various roles as well as between each USV and static obstacles. A collision-free multi-USV formation-containment tracking control strategy considering constrained motion velocity and driving force was thus established, and its effectiveness was validated through the proposed simulation.
Optimization of Combustion Cycle Energy Efficiency and Exhaust Gas Emissions of Marine Dual-Fuel Engine by Intensifying Ammonia Injection
Authors: Drazdauskas Martynas , Lebedevas Sergejus
Published: February 2024

The capability of operational marine diesel engines to adapt to renewable and low-carbon fuels is considered one of the most influential methods for decarbonizing maritime transport. In the medium and long term, ammonia is positively valued among renewable and low-carbon fuels in the marine transport sector because its chemical elemental composition does not contain carbon atoms which lead to the formation of CO2 emissions during fuel combustion in the cylinder. However, there are number of problematic aspects to using ammonia in diesel engines (DE): in-tensive formation of GHG component N2O; formation of toxic NOx emissions; and unburnt toxic NH3 slip to the exhaust system. The aim of this research was to evaluate the changes in combustion cycle parameters and exhaust gas emissions of a medium-speed Wartsila 6L46 marine diesel engine operating with ammonia, while optimizing ammonia injection intensity within the limits of Pmax, Tmax, and minimal engine structural changes. The high-pressure dual-fuel (HPDF) injection strategy for the D5/A95 dual-fuel ratio (5% diesel and 95% ammonia by energy value) was investigated within the liquid ammonia injection pressure range of 500 to 2000 bar at the identified optimal injection phases (A −10° CAD and D −3° CAD TDC). Increasing ammonia injection pressure from 500 bar (corresponding to diesel injection pressure) in the range of 800–2000 bar determines the single-phase heat release characteristic (HRC). Combustion duration decreases from 90° crank angle degrees (CAD) at D100 to 20–30° CAD, while indicative thermal efficiency (ITE) increases by ~4.6%. The physical cyclic deNOx process of NOx reduction was identified, and its efficiency was evaluated in relation to ammonia injection pressure by relating the dynamics of NOx formation to local combustion temperature field structure. The optimal ammonia injection pressure was found to be 1000 bar, based on combustion cycle parameters (ITE, Pmax, and Tmax) and exhaust gas emissions (NOx, NH3, and GHG). GHG emissions in a CO2 equivalent were reduced by 24% when ammonia injection pressure was increased from 500 bar to 1000 bar. For comparison, GHG emissions were also reduced by 45%, compared to the diesel combustion cycle.
A Phylogenetic and Taxonomic Revision of Discula theae-sinensis, the Causal Agents of Anthracnose on Camellia sinensis
Authors: Guo Meijun , Zhao Shiyi , Gao Yue , Shen Xiaoye , Hou Chenglin
Published: February 2024

Tea (Camellia sinensis (L.) Kuntze) is one of the most important economic plants in China, and has many benefits for human health. Anthracnose is one of the most serious diseases of tea in China, and control of the fungus is important since most Chinese cultivars are susceptible to it. The agent of tea anthracnose was initially described as Gloeosporium theae-sinensis I. Miyake in Japan, which was later transferred to Discula, but this taxonomic position remains problematic. To shed light on these taxonomic and phylogenetic issues, the tea anthracnose pathogens were re-studied. Combining the morphological characteristics and a multigene phylogenetic analysis of nrITS, nrLSU, rpb2, and tef1 sequence data, a new genus Sinodiscula was proposed to accommodate the causal fungi of tea anthracnose, including a new species Sinodiscula camellicola and a new combination Sinodiscula theae-sinensis. Furthermore, the pathogenicity of the pathogens was determined according to Koch’s postulates. This study thoroughly resolves the long-standing taxonomic and phylogenetic problems of the tea anthracnose pathogens.
Multifaceted Beauveria bassiana and Other Insect-Related Fungi
Authors: Pedrini Nicolás , Fernandes Éverton K. K. , Dubovskiy Ivan M.
Published: February 2024

Since Agostino Bassi first isolated the fungal pathogenic agent of the white muscardine in insects (later named Beauveria bassiana in his honor), and Ilya Mechnikov cultivated Metarhizium anisopliae as a first approach to use fungi as pest control agents, many other entomopathogenic fungi have been studied over the last two centuries [...]
Only 26% of Native Knees Show an Identical Coronal Functional Knee Phenotype in the Contralateral Knee
Authors: Sava Manuel-Paul , Leica Alexandra , Amsler Felix , Leles Sotirios , Hirschmann Michael T.
Published: February 2024

Background: A comprehensive exploration evaluating left-to-right knee symmetry across all anatomical planes utilizing three-dimensional (3D) scans stands absent from the existing body of research. Therefore, the primary objectives of this investigation involved examining potential differences and resemblances in alignment and structure between left and right non-osteoarthritic (native) knees in various planes (coronal, sagittal, and axial) using three-dimensional single-photon emission computed tomography/computed tomography (SPECT/CT) images. Methods: A total of 282 native knees from 141 patients were retrospectively gathered from the hospital’s records. Patients, aged between 16 and 45, who underwent Tc99m-methyl diphosphonate SPECT/CT scans for both knees, adhering to the Imperial Knee Protocol, were included. A statistical analysis was conducted, including 23 knee morphometric parameters, comparing left and right knees, and classifying them based on functional knee phenotypes across the coronal, sagittal, and axial planes. Results: Regarding the functional coronal knee phenotype, 26% of patients (n = 37) exhibited identical phenotypes in both knees (p < 0.001). Significant correlated similarities between the left and right knees were observed in the coronal plane (Pearson’s r = 0.76, 0.68, 0.76, 0.76, p < 0.001) and in several morphometric measures in the sagittal plane (Pearson’s r = 0.92, 0.72, 0.64, p < 0.001). Moderately correlated similarities were noted in the axial plane (Pearson’s r = 0.43, 0.44, 0.43, p < 0.001). Conclusions: Only 26% of native knees exhibit an identical coronal phenotype in their contralateral knee, whereas 67% have the adjacent coronal phenotype. Strongly correlated resemblances were established across various left and right knee morphometric parameters in the coronal, sagittal, and axial planes. These findings could enhance decisions in procedures like total knee arthroplasties or osteotomies, where alignment is key to outcomes, and reveal a potential for future artificial intelligence-driven models to improve our understanding and improve personalized treatment strategies for knee osteoarthritis.
Digital Financial Inclusion in Emerging Economies: Evidence from Jordan
Authors: Al Khub Abdalla , Saeudy Mohamed , Gerged Ali Meftah
Published: February 2024

This study explores the role of digital financial inclusion in mitigating poverty and bolstering economic growth, with a special focus on developing nations during the COVID-19 era. Centering on Jordan, it seeks to identify key influencers of financial access by analyzing data from 260 participants using a non-linear probit regression model. The research uncovers a significant disparity in financial inclusion between Jordanian adult males and females, attributable to differences in education, wealth, employment, and income levels. These findings point to the necessity of prioritizing financial accessibility for marginalized groups such as women, the elderly, and those with lower income to effectively combat poverty and facilitate economic advancement and sustainable development in emerging markets.
Dual-Dataset Deep Learning for Improved Forest Fire Detection: A Novel Hierarchical Domain-Adaptive Learning Approach
Authors: El-Madafri Ismail , Peña Marta , Olmedo-Torre Noelia
Published: February 2024

This study introduces a novel hierarchical domain-adaptive learning framework designed to enhance wildfire detection capabilities, addressing the limitations inherent in traditional convolutional neural networks across varied forest environments. The framework innovatively employs a dual-dataset approach, integrating both non-forest and forest-specific datasets to train a model adept at handling diverse wildfire scenarios. The methodology leverages a novel framework that combines shared layers for broad feature extraction with specialized layers for forest-specific details, demonstrating versatility across base models. Initially demonstrated with EfficientNetB0, this adaptable approach could be applicable with various advanced architectures, enhancing wildfire detection. The research’s comparative analysis, benchmarking against conventional methodologies, showcases the proposed approach’s enhanced performance. It particularly excels in accuracy, precision, F1-score, specificity, MCC, and AUC-ROC. This research significantly reduces false positives in wildfire detection through a novel blend of multi-task learning, dual-dataset training, and hierarchical domain adaptation. Our approach advances deep learning in data-limited, complex environments, offering a critical tool for ecological conservation and community protection against wildfires.
An Efficient GNSS Coordinate Classification Strategy with an Adaptive KNN Algorithm for Epidemic Management
Authors: Chen Jong-Shin , Kuo Chun-Ming
Published: February 2024

In times of widespread epidemics, numerous individuals are at risk of contracting viruses, such as COVID-19, monkeypox, and pneumonia, leading to a ripple effect of impacts on others. Consequently, the Centers for Disease Control (CDC) typically devises strategies to manage the situation by monitoring and tracing the infected individuals and their areas. For convenience, “targets” and “areas” represent the following individuals and areas. A global navigation satellite system (GNSS) can assist in evaluating the located areas of the targets with pointing-in-polygon (PIP) related technology. When there are many targets and areas, relying solely on PIP technology for classification from targets to areas could be more efficient. The classification technique of k-nearest neighbors (KNN) classification is widely utilized across various domains, offering reliable classification accuracy. However, KNN classification requires a certain quantity of targets with areas (training dataset) for execution, and the size of the training dataset and classification time often exhibit an exponential relationship. This study presents a strategy for applying KNN technology to classify targets into areas. Additionally, within the strategy, we propose an adaptive KNN algorithm to enhance the efficiency of the classification procedure.
A Fault Detection System for Wiring Harness Manufacturing Using Artificial Intelligence
Authors: Song Jinwoo , Kumar Prashant , Kim Yonghawn , Kim Heung Soo
Published: February 2024

Due to its simplicity, accuracy, and adaptability, Crimp Force Monitoring (CFM) has long been the standard for fault detection in wiring harness manufacturing. However, it necessitates frequent reconfigurations based on the variability in materials, dependency on operator skill, and high costs of implementation, and thus reconfiguration presents significant challenges. To solve these problems, this paper introduces a fault detection system that employs an Artificial Intelligence (AI) classification model to enhance the performance and cost-efficiency of the quality control process of wiring harness manufacturing. Since there are no labeled data to train the classification model at the onset of manufacturing, a small number of normal data from each production run are manually extracted to train the model. To address the constraint of the limited available data, the system generates synthetic data from normal data, simulating potential defects by using Regional Selective Data Scaling (RSDS). This innovative method performs upscaling or downscaling on specific regions of the original data to produce synthetic abnormal data, which enables the fault detection system to efficiently train its classification model with a dataset consisting solely of normal operation data.
Decision-Making on the Diagnosis of Oncological Diseases Using Cost-Sensitive SVM Classifiers Based on Datasets with a Variety of Features of Different Natures
Authors: Demidova Liliya A.
Published: February 2024

This paper discusses the problem of detecting cancer using such biomarkers as blood protein markers. The purpose of this research is to propose an approach for making decisions in the diagnosis of cancer through the creation of cost-sensitive SVM classifiers on the basis of datasets with a variety of features of different nature. Such datasets may include compositions of known features corresponding to blood protein markers and new features constructed using methods for calculating entropy and fractal dimensions, as well as using the UMAP algorithm. Based on these datasets, multiclass SVM classifiers were developed. They use cost-sensitive learning principles to overcome the class imbalance problem, which is typical for medical datasets. When implementing the UMAP algorithm, various variants of the loss function were considered. This was performed in order to select those that provide the formation of such new features that ultimately allow us to develop the best cost-sensitive SVM classifiers in terms of maximizing the mean value of the metric MacroF1−score. The experimental results proved the possibility of applying the UMAP algorithm, approximate entropy and, in addition, Higuchi and Katz fractal dimensions to construct new features using blood protein markers. It turned out that when working with the UMAP algorithm, the most promising is the application of a loss function on the basis of fuzzy cross-entropy, and the least promising is the application of a loss function on the basis of intuitionistic fuzzy cross-entropy. Augmentation of the original dataset with either features on the basis of the UMAP algorithm, features on the basis of the UMAP algorithm and approximate entropy, or features on the basis of approximate entropy provided the creation of the three best cost-sensitive SVM classifiers with mean values of the metric MacroF1−score increased by 5.359%, 5.245% and 4.675%, respectively, compared to the mean values of this metric in the case when only the original dataset was utilized for creating the base SVM classifier (without performing any manipulations to overcome the class imbalance problem, and also without introducing new features).
Investigating Behavior of Slider–Crank Mechanisms with Bearing Failures Using Vibration Analysis Techniques
Authors: Ghazwani Mofareh Hassan , Pham Van Vinh
Published: February 2024

This study focuses on investigating the behavior of slider–crank mechanisms with different bearing failures using a vibration analysis technique. The reliability and lifespan of bearings are crucial for such mechanisms, which convert rotary motion to reciprocating motion. Previous research primarily addressed ball-bearing failures, neglecting needle bearings due to their specific applications. To bridge this gap, our experimental setup integrated both roller and ball bearings within a slider–crank mechanism. Vibration data were collected during normal operation, as well as under failure conditions of the ball and roller bearings. By analyzing the vibration signatures during simultaneous multiple failures, we gained insights into the nature of vibrations in the system. Furthermore, a mathematical model based on Hertzian contact was employed to calculate the theoretical frequency of ball bearings; however, due to the variable motion of the needle bearing, a novel mathematical model was proposed to estimate the defective impulse frequency, considering the inter-impact time between two impacts. The experimental results were compared with the healthy crank mechanism setup to draw meaningful conclusions. This research contributes to a comprehensive understanding of bearing failures in slider–crank mechanisms and provides valuable insights for designing reliable and long-lasting systems.
Structure and Binding Properties to Blood Co-Factors of the Least Sulfated Galactan Found in the Cell Wall of the Red Alga Botryocladia occidentalis
Authors: Maurya Antim K. , Ahmed Hoda Al. , DeWitt Anderson , Shami Anter A. , Misra Sandeep K. , Pomin Vitor H.
Published: February 2024

Three different populations of sulfated polysaccharides can be found in the cell wall of the red alga Botryocladia occidentalis. In a previous work, the structures of the two more sulfated polysaccharides were revised. In this work, NMR-based structural analysis was performed on the least sulfated polysaccharide and its chemically modified derivatives. Results have revealed the presence of both 4-linked α- and 3-linked β-galactose units having the following chemical features: more than half of the total galactose units are not sulfated, the α-units occur primarily as 3,6-anhydrogalactose units either 2-O-methylated or 2-O-sulfated, and the β-galactose units can be 4-O-sulfated or 2,4-O-disulfated. SPR-based results indicated weaker binding of the least sulfated galactan to thrombin, factor Xa, and antithrombin, but stronger binding to heparin cofactor II than unfractionated heparin. This report together with our previous publication completes the structural characterization of the three polysaccharides found in the cell wall of the red alga B. occidentalis and correlates the impact of their composing chemical groups with the levels of interaction with the blood co-factors.