bluuebunny/crossref_metadata_2025 huggingface dataset:
Decitabine Increases the Transcription of RIG-I Gene to Suppress the Replication of Feline Calicivirus and Canine Influenza Virus
Authors: Ye Shaotang , Wang Zhen , Chen Aolei , Chen Ying , Lou Gaoming , Xie Qingmei , Lu Gang , Li Shoujun
Published: January 2025

Developing novel antiviral drugs has always been a significant forefront in biological medicine research. Antiviral drugs can be extracted, purified, and synthesized from various biological sources and by different methods. However, they are less explored in veterinary medicine for animal viruses. This research primarily selected feline calicivirus (FCV) to screen the novel antiviral drug against animal viruses. A preliminary screening from a natural product library was conducted, with subsequent assessments to ascertain their toxicity levels and antiviral capabilities. The results showed that decitabine and alprostadil were effective in reducing FCV replication. The decitabine (5-aza-2′-deoxycytidine) was selected for antiviral mechanism investigation. Decitabine has been proven to modulate gene expression through its demethylating effect. Thus, we carried out further experiments and found that decitabine inhibited the FCV by enhancing the transcription of the feline Retinoic acid-inducible gene I (RIG-I) gene. Moreover, we also validated the same antiviral effect and mechanism of decitabine against the canine influenza virus (CIV). In summary, this study unveils the antiviral role of decitabine against FCV and CIV and provides evidence and novel insights into the demethylation drug-mediated antiviral effect for animal RNA viruses.
Editorial for Special Issue “Mineral Chemistry of Granitoids: Constraints on Crystallization Conditions and Petrological Evolution”
Authors: de Pinho Guimarães Ignez , de Lima Jefferson Valdemiro
Published: January 2025

The origin of granitoids has fascinated geologists since the famous meeting of the Geological Society of France in 1847 [...]
Solvometallurgical Properties of Choline Chloride-Based Deep Eutectic Solvents for Copper Extraction from Chalcopyrite: Optimization and Analysis
Authors: Ghadamgahi Seyed Mojtaba , Babakhani Abolfazl , Barati Darband Ghasem , Shalchian Hossein , Behmadi Reza
Published: January 2025

This paper focuses on the solvometallurgical properties of choline chloride-based deep eutectic solvents for copper extraction from chalcopyrite concentrate. The study, conducted with scientific rigor, utilized the response surface methodology to optimize the extraction process and investigate the effects of the temperature and contact time on the copper recovery efficiency. The results showed that the ChCl-EG-Ox solvent at 80 °C and 48 h produced the highest copper recovery rate, exceeding 76%. This underscores the potential of deep eutectic solvents for sustainable metal extraction. Kinetic studies revealed the influence of temperature on dissolution kinetics, with higher temperatures leading to faster reaction rates. The mineralogical analysis demonstrated the changes in the chalcopyrite concentrate after dissolution, while spectroscopy and mass spectrometry highlighted the esterification reactions in the solvent. The study also examined the effects of adding water and heating on the solvent’s behavior, providing insights into the chemical interactions and structural changes. Ultimately, the research demonstrated that ChCl-based deep eutectic solvents present a promising avenue for environmentally friendly and efficient copper extraction processes in the metallurgical industry.
Furan-Indole-Chromenone-Based Organic Photocatalyst for α-Arylation of Enol Acetate and Free Radical Polymerization Under LED Irradiation
Authors: Galibert-Guijarro Aurélien , Noon Adel , Toufaily Joumana , Hamieh Tayssir , Besson Eric , Gastaldi Stéphane , Lalevée Jacques , Feray Laurence
Published: January 2025

In this study we report on the efficiency of a furane-indole-chromenone-based organic derivative (FIC) as a photocatalyst in the α-arylation of enol acetate upon LED irradiation at 405 nm, and as a photoinitiator/photocatalyst in the free radical polymerization of an acrylate group in the presence of bis-(4-tert-butylphenyl)iodonium hexafluorophosphate (Iod) as an additive, or in the presence of both Iod and ethyl-4-(dimethyl amino) benzoate (EDB) under LED irradiation at 365 nm. The photochemical properties of this new light-sensitive compound are described, and the wide redox window (3.27 eV) and the high excited-state potentials FIC*/FIC●− (+2.64 V vs. SCE) and FIC●+/FIC* (−2.41 V vs. SCE) offered by this photocatalyst are revealed. The chemical mechanisms that govern the radical chemistry are discussed by means of different techniques, including fluorescence-quenching experiments, UV-visible absorption and fluorescence spectroscopy, and cyclic voltammetry analysis.
Construction of a Library of Fatty Acid Esters of Hydroxy Fatty Acids
Authors: Mountanea Olga G. , Batsika Charikleia S. , Mantzourani Christiana , Kokotos Christoforos G. , Kokotos George
Published: January 2025

Fatty Acid Esters of Hydroxy Fatty Acids (FAHFAs) have emerged as extraordinary bioactive lipids, exhibiting diverse bioactivities, from the enhancement of insulin secretion and the optimization of blood glucose absorption to anti-inflammatory effects. The intricate nature of FAHFAs’ structure reflects a synthetic challenge that requires the strategic introduction of ester bonds along the hydroxy fatty acid chain. Our research seeks to create an effective methodology for generating varied FAHFA derivatives. Our primary approach centers on a photochemical hydroacylation reaction, merging terminal alkenes, either ω-alkenoic acids or ω-alkenyl alcohols, with commercially available aldehydes. This transformative, environmentally friendly process, orchestrated by phenylglyoxylic acid as the photoinitiator, serves as the linchpin in establishing a practical and relatively simple method for constructing a library of racemic FAHFAs. The ketones produced by the photochemical reactions are easily converted to hydroxy derivatives, which are coupled with caproic, palmitic, or oleic acid, providing a large set of FAHFAs, which broaden our ability for future structure–activity relationship studies.
Cross-Sectional Study on the Influence of Religion on the Consumption of Ultra-Processed Food in Spanish Schoolchildren in North Africa
Authors: Mohatar-Barba Miriam , González-Jiménez Emilio , López-Olivares María , Fernández-Aparicio Ángel , Schmidt-RioValle Jacqueline , Enrique-Mirón Carmen
Published: January 2025

(1) Background: The consumption of ultra-processed foods (UPFs) constitutes a public health problem given their high availability and easy accessibility among children and young people and their influence on the development of non-communicable diseases in the long term. In this context, culture and religion may be modulating factors for the consumption of processed food. The aim of this study is to assess the consumption of UPFs in Spanish schoolchildren living in Melilla (North Africa), together with the possible impact of religion on this. (2) Methods: A cross-sectional study of 590 Christian and Muslim schoolchildren aged 15–17 years was conducted. The NOVA food classification was used to identify UPFs. Associations between religion and daily consumption were identified using risk analysis (Odds Ratio). (3) Results: Muslim schoolchildren had a higher consumption of industrial juices [OR = 2.700, 95%CI = 1.830–4.037], milkshakes [OR = 2.925, 95% = 1.850–4.748], industrial pastries [OR = 2.217, 95% = 1.440–3.510], sweets [OR = 2.197, 95%CI = 1.437–3.541], chocolates [OR = 2.272, 95%CI = 1.482–3.606] and savory snacks [OR = 3.431, 95%CI = 1.844–6.579] compared to that observed among Christians. (4) Conclusions: Both Muslim and Christian schoolchildren had a high consumption of UPFs. Regarding the potential impact of religion on the consumption of UPF, we observed that Muslim schoolchildren consumed three to four times more UPF than Christian schoolchildren. These results show a shift away from a healthy eating pattern, especially among Muslim schoolchildren. Thus, it is necessary to implement nutritional education strategies in order to understand and control the consumption of UPF in adolescents, thereby reducing the occurrence of non-communicable diseases in the long term.
Dietary Surveys and Nutritional Epidemiology
Authors: Liz Martins Margarida , Abreu Sandra
Published: January 2025

As the prevalence of lifestyle-related diseases continues to increase globally [...]
Polyphenolic Hispolon Derived from Medicinal Mushrooms of the Inonotus and Phellinus Genera Promotes Wound Healing in Hyperglycemia-Induced Impairments
Authors: Liu Yi-Shan , Lai Mei-Chou , Tzeng Yu-Cheng , Liu I-Min
Published: January 2025

Background: This study investigated the wound-healing potential of hispolon, a polyphenolic pigment derived from medicinal mushrooms, under diabetic conditions using both in vitro and in vivo models. Methods: In the in vitro assays, L929 fibroblast cells exposed to high glucose (33 mmol/L) were treated with hispolon at concentrations of 2.5, 5, 7.5, or 10 μmol/L. In the in vivo assays, streptozotocin-induced diabetic rats with excision wounds received daily topical applications of 0.2 g of 5% (w/w) hispolon ointment. Results: Hispolon improved cell viability; suppressed oxidative stress by reducing reactive oxygen species, lipid peroxidation, and oxidative DNA damage; and restored the reduced glutathione/oxidized glutathione ratio. The scratch assay demonstrated that hispolon at 10 μmol/L enhanced fibroblast migration impaired by high-glucose conditions. Treatment with 5% (w/w) hispolon ointment accelerated wound contraction, reduced the epithelialization time, and enhanced tissue regeneration with an efficacy comparable to that of Fespixon® cream, as shown by histological findings of increased fibroblast activity, collagen deposition, and capillary growth. Hispolon ointment also modulated macrophage polarization in diabetic wounds by reducing M1 markers and enhancing M2 markers. In a diabetic rat dead-space-wound model, 5% (w/w) hispolon ointment reduced the levels of pro-inflammatory cytokines, increased those of anti-inflammatory cytokines and growth factors, and stimulated Type I and III collagen synthesis, effectively promoting wound healing. In incisional wounds, hispolon ointment improved the wound-breaking strength, showing results comparable to that of Fespixon® cream. Safety assessments confirmed that hispolon ointment showed no acute dermal toxicity. These findings underscore hispolon’s potential as a promising candidate for diabetic wound management by mitigating oxidative stress, enhancing tissue regeneration, and accelerating wound healing.
Amino Acid Patterns in Children with Autistic Spectrum Disorder: A Preliminary Biochemical Evaluation
Authors: Ferraro Simona , Saielli Laura , Biganzoli Davide , Tosi Martina , Guidi Laura , Longo Roberto , Severino Francesca , Carelli Stephana , Rossi Maura , Pisciotta Livia , Ricci Emilia , Brustia Francesca , Verduci Elvira , Zuccotti Gianvincenzo , Mussap Michele , Cereda Cristina
Published: January 2025

Background: The metabolism of plasma amino acid (AA) in children with autism spectrum disorder (ASD) has been extensively investigated, yielding inconclusive results. This study aims to characterize the metabolic alterations in AA profiles among early-diagnosed children with ASD and compare the findings with those from non-ASD children. Methods: We analyzed plasma AA profiles, measured by ion exchange chromatography, from 1242 ASD children (median age = 4 years; 81% male). Additionally, we studied AA profiles from 488 children, matched for age and free of ASD (control group). Principal component and cluster analysis were employed to explore potential associations within the ASD group and to identify subgroups. Results: We observed lower plasma levels of glutamine in children with ASD compared to non-ASD children (p < 0.001). Six essential, two conditionally essential, and four non-essential AA were found to be increased in children with ASD. The clustering analysis revealed two groups, labeled Neurological (NEU) and Nutritional (NUT), which included a majority of ASD children (94% and 78%, respectively). The NEU group exhibited high levels of taurine, aspartate, glutamic acid, and ornithine, while the NUT group showed elevated levels of branched-chain AA. Conclusions: In children with ASD, we identified some heterogeneous AA patterns that may serve as biochemical signatures of neurological impairment in some individuals, while in others they may indicate nutritional dysregulation.
First Detection of Alphacoronavirus in Bats from the World’s Largest Wetland, the Pantanal, Brazil
Authors: Magalhães Tayane B. S. , Viana Amanda de O. , Semedo Thiago B. F. , Saldanha Juliane S. , Reis Nicole A. dos , Pereira Nathalia de A. , Barros Rachel V. P. de , Miranda Hannah R. , Almeida Gabriella C. , Ozaki Desyrée Y. S. R. , Caleiro Giovana S. , Fenner Gustavo O. , Vizu Fernanda P. , Kraiser Theo , Carvalho Thais P. , Thomazelli Luciano M. , Dorlass Erick G. , Arns Clarice W. , Ferreira Helena L. , Hingst-Zaher Erika , Rossi Rogério Vieira , Garbino Guilherme S. T. , Durigon Edison L. , Araujo Jansen de , Aguiar Daniel M. de
Published: January 2025

Coronaviruses (CoV) infect a wide variety of hosts, causing epidemics in humans, birds, and mammals over the years. Bats (order Chiroptera) are one of the natural hosts of the Coronaviridae family. They represent 40% of the total number of mammal species in the Pantanal, a biodiversity hotspot in South America. Given the recent SARS-CoV-2 pandemic, we investigated the presence of CoV in bats captured in the Brazilian Pantanal. Oral and rectal swabs collected in 2021 from 419 bats were analyzed using Pancoronavirus-nested PCR targeting the RNA-dependent RNA-polymerase (RdRp) gene. Orthocoronavirinae was detected in 16.7% (70/419) of the bats; nine samples were sequenced, confirming that Carollia perspicillata (4), Phyllostomus hastatus (2), Desmodus rotundus (1), Molossus rufus (1), and Myotis cf. nigricans (1) collected in buildings formally used by humans were infected by Alphacoronavirus genera. This is the first description of Alphacoronavirus in bats from the Pantanal. As they are natural reservoirs of CoVs, constant monitoring of bats is important to comprehend the epidemiology of emerging viruses, especially in the Pantanal biome.
Optimization of Carrier-Based Dry Powder Inhaler Performance: A Review
Authors: Mehta Tanu , Najafian Saeed , Patel Komalkumar , Lacombe Justin , Chaudhuri Bodhisattwa
Published: January 2025

Dry powder inhalers (DPI’s) are becoming increasingly popular due to growing interest in pulmonary drug delivery and their performance is the net result of a series of processes carried out during the formulation development and manufacturing process such as excipient selection, blending, milling, filling, and spray drying. To reach the small airways of the deep lung, the active pharmaceutical ingredients (API) particles need to have an aerodynamic diameter of 1–5 μm to avoid impaction and particle sedimentation in the upper respiratory tract, and due to this small particle size, the powder becomes highly cohesive resulting in poor flow. Therefore, API is usually blended with a coarse carrier to improve flowability, and due to its large size, it is more fluidizable than the micronized drug. Carrier-based DPI formulations usually consist of micronized drugs, a coarse carrier, and additional components, such as micronized lactose and force control agents, including magnesium stearate or leucine. Additionally, the manufacturing process of DPIs relies heavily on powder processing technologies, such as the micronization of API, blending, and powder filling. The aerosol performance of a DPI is significantly affected by the selection of formulation components and the processing of the formulation and, therefore, it is crucial to evaluate these parameters. This review will discuss different factors influencing the aerosol performance of carrier-based DPIs, including formulation components, device considerations, and manufacturing parameters. Additionally, novel technologies pertaining to the optimization of DPI performance are also discussed.
The Construction of a Standard Karyotype of Intermediate Wheatgrass and Its Potential Progenitor Species
Authors: Wang Lin , Liang Shuang , Qi Fei , Bao Yinguang , Wang Richard R.-C. , Li Xingfeng
Published: January 2025

The genome composition of intermediate wheatgrass (IWG; Thinopyrum intermedium (Host) Barkworth and D.R. Dewey; 2n = 6x = 42) is complex and remains to be a subject of ongoing investigation. This study employed fluorescence in situ hybridization (FISH) to analyze the karyotype of Th. intermedium and its related species. With the St2-80 probe derived from Pseudoroegneria strigosa and the pDb12H probe from Dasypyrum breviaristatum, FISH analysis classified the chromosomes of Th. intermedium as JvsJvsJrJrStSt. FISH karyotype was established using pSc119.2-1, (GAA)10, AFA-3, AFA-4, pAs1-1, pAs1-3, pAs1-4, and pAs1-6 as a combined multiplex oligonucleotide probe. MATO software was used to analyze chromosome length, arm ratio, and karyotype structure. The karyotype formula of Th. intermedium is K(2n) = 6X = 42 = 36m + 6sm, and that of Th. junceiforme is K(2n) = 4X = 28 = 22m + 6sm. The karyotype formula of Th. elongatum and Th. bessarabicum is K(2n) = 2X = 14 = 12m + 2sm, of Ps. spicata is K(2n) = 2X = 14 = 2M + 12m, and of Da. villosum is K(2n) = 2X = 14 = 12m + 2sm. Based on the results of FISH, standard karyotypes of Th. intermedium and its potential progenitor species were constructed. These standard karyotypes revealed that there was evolutionary parallelism between genome and karyotype, but due to the complexity of evolution, the FISH signal of Th. intermedium was abundant and asymmetrical.
The Function of Two Brassica napus β-Ketoacyl-CoA Synthases on the Fatty Acid Composition
Authors: Zhao Dongfang , Zhou Bingqian , Hong Bo , Mao Jiajun , Chen Hu , Wu Junjie , Liao Li , Guan Chunyun , Guan Mei
Published: January 2025

Rapeseed (Brassica napus L.) is one of the four major oilseed crops in the world and is rich in fatty acids. Changes in the fatty acid composition affect the quality of rapeseed. Fatty acids play various roles in plants, but the functions of the genes involved in the fatty acid composition during plant development remain unclear. β-Ketoacyl-CoA synthase (KCS) is a key enzyme involved in the elongation of fatty acids. Various types of fatty acid products are used to build lipid molecules, such as oils, suberin, wax, and membrane lipids. In B. napus, BnaKCSA8 and BnaKCSC3 belong to the KCS family, but their specific functions remain unclear. This study cloned BnaKCSA8 and BnaKCSC3 from Brassica napus L. and analyzed their functions. The gene structures of BnaKCSA8 and BnaKCSC3 were similar and they were localized to the endoplasmic reticulum (ER). In yeast, overexpression of BnaKCSA8 increased the ratios of palmitoleic acid and oleic acid, while BnaKCSC3 decreased the ratios of oleic acid. In Arabidopsis, overexpression of BnaKCSA8 and BnaKCSC3 lead to an increase in the proportion of linoleic acid and a decrease in the erucic acid. In summary, BnaKCSA8 and BnaKCSC3 altered the composition ratios of fatty acids. These findings lay the foundation for an understanding of the role of KCS in the fatty acids in rapeseed, potentially improving its health and nutritional qualities.
Study on the Improvement Effect of Polypropylene Fiber on the Mechanical Properties and Freeze–Thaw Degradation Performance of High Fly Ash Content Alkali-Activated Fly Ash Slag Concrete
Authors: Yuan Zhu , Jia Yanmin , Xu Junming
Published: January 2025

This article systematically investigated the improvement effect of polypropylene fiber (PPF) on the mechanical and freeze–thaw properties of alkali-activated fly ash slag concrete (AAFSC) with high fly ash content and cured at room temperature. Fly ash and slag were used as precursors, with fly ash accounting for 80% of the total mass. A mixed solution of sodium hydroxide and sodium silicate was used as alkali activator, and short-cut PPF was added to improve the performance of AAFSC. Firstly, the strength characteristics of AAFSC at different curing ages were studied. Then, key indicators such as morphology, residual compressive strength, weight loss, relative dynamic modulus of elasticity (RDME), and pore characteristics of AAFSC after different freeze–thaw cycles were tested and analyzed. The strength performance analysis showed that the optimal dosage of PPF was 0.90%. When the alkali equivalent of the alkali activator was increased from 4% to 6%, the frost resistance of AAFSC could be improved. Furthermore, adding 0.90% PPF could increase the freeze–thaw cycle number of AAFSC by about 50 times (measured by RDME). With the increase in freeze–thaw cycles, the porosity of AAFSC increased, the fractal dimension decreased, and the proportion of harmless and less harmful pores decreased, while the proportion of harmful and multiple harmful pores increased. The relationship model between the porosity and compressive strength of AAFSC after freeze–thaw cycles was established.
Coal Tar Naphtha Refining: Phenol Alkylation with 1-Hexene and the Impact of Pyridine
Authors: Xia Yuhan , de Klerk Arno
Published: January 2025

Coal tar naphtha is produced from coal carbonization, moving bed coal gasification, and thermal liquefaction of coal. The naphtha can contain up to 60% aromatics and 15% olefins, as well as nitrogen-, oxygen-, and sulfur-containing compounds. Usually only hydrotreating is considered, but when producing motor gasoline, olefin–aromatic alkylation could reduce the associated octane number loss due to olefin hydrogenation by converting olefins to alkylated phenols and aromatics. The plausibility of using acid-catalyzed alkylation with coal tar naphtha, which contains nitrogen bases, was investigated by studying a model system comprising phenol and 1-hexene in the absence and presence of pyridine. It was found that pyridine only inhibited conversion over a range of amorphous silica–alumina catalysts. The most effective catalyst was Siral 30 (30% silica, 70% alumina) and at 315 °C, 0.05 wt% pyridine caused a 35% inhibition of phenol conversion compared to conversion in the absence of pyridine. Catalyst activity could be restored by rejuvenating the catalyst with clean feed at a higher temperature. The results supported a description of phenol alkylation with olefins that took place by at least two pathways, one involving protonation of the olefin (typical for Friedel–Crafts alkylation) and one where the olefin is the nucleophile.
Enhancing Sustainability with LCA: A Comparative Analysis of Design and Manufacturing Processes
Authors: Val Sonia , Lambán María Pilar
Published: January 2025

This study evaluates the feasibility and effectiveness of the Life Cycle Assessment (LCA) methodology. Two widely used products with the same functionality but different designs and production processes were selected for comparative analysis. SimaPro 9.6.0 software was used for the calculations and LCA of both assemblies. The analysis covered all phases of the life cycle, taking into account factors such as energy, materials and water consumption. The results allowed a comparison of the environmental impacts of the two assemblies, identifying the life cycle phases with the highest impact and the most relevant impact categories. The analysis revealed that the metal trolley exhibited a 40% higher environmental impact during production compared to the polypropylene trolley, primarily due to the material extraction and processing phases. Additionally, the polypropylene trolley showed higher long-term impacts in landfill scenarios due to carcinogenic substance emissions. These findings highlight the significance of design and material selection in reducing environmental impacts. Applying the LCA methodology to the two mechanical assemblies allowed us to identify opportunities for improvement in the design and manufacturing processes, with the aim of reducing the environmental impact and increasing the competitiveness of the products. By considering the full life cycle of a product from the early design phases, more sustainable design and manufacturing decisions can be made, and by using this analysis, companies can develop more sustainable products and reduce costs.
Detection Method of Key Ship Parts Based on YOLOv11
Authors: Wang Yao , Jiang Yi , Xu Huiqi , Xiao Chuanliang , Zhao Ke
Published: January 2025

The current ship target detection algorithm is not adaptable to changes in target size and position, and its detection accuracy and speed are difficult to balance in the process of algorithm improvement. In particular, there is little research on the detection of key parts of ships. In this paper, an improved YOLOv11 ship key location detection algorithm is proposed. It is difficult to balance the relationship between detection efficiency and model complexity using current key parts detection algorithms. The processing performance of deforming key parts according to the algorithms is not strong. Moreover, the algorithms’ detection performance of occluding overlapping targets and small-size targets is not high. In view of the practical problems existing in the algorithms and the realistic demand for real-time and accurate detection of key parts of targets on dynamic ships at sea, three aspects of improvement on YOLOv11 are proposed. The visible light ship key position dataset is then constructed for the experiment. The experimental results show that the improved YOLOv11 network in this paper can detect the key position information of ships more accurately and efficiently, effectively balance the relationship between model accuracy and speed, overcome the interference of dynamic factors, improve the fine interpretation of dynamic ship information at sea, and provide a feasible technical approach for accurately and precisely mastering ship information at sea and realizing real-time sea area detection.
DAE-BiLSTM Model for Accurate Diagnosis of Bearing Faults in Escalator Principal Drive Systems
Authors: Jiang Xiyang , Zhang Zhuangzhuang , Yuan Hongbing , He Jing , Tong Yifei
Published: January 2025

The extensive deployment of escalators has greatly improved travel convenience; however, significant concerns have been raised due to the increasing frequency of safety incidents in recent years. Ensuring the safe operation of escalators and detecting faults in a timely manner have become critical concerns for both manufacturers and maintenance personnel. Traditional periodic inspections are resource-intensive and increasingly deemed inadequate due to the growing diversity and number of escalators. In this article, a data acquisition and transmission system for the main drive shaft bearing of the escalator, based on the Internet of Things (IoT), is designed using the main drive shaft bearing as an example. Additionally, a fault classification model combining a deep autoencoder (DAE) and Bidirectional Long Short-Term Memory Network (BiLSTM) is proposed. The experimental results of this study demonstrate that the DAE-BiLSTM-based fault diagnosis model provides accurate fault detection and early warnings, achieving an accuracy rate exceeding 99%, while significantly reducing the computational costs and training time.
Lemierre’s Syndrome Presenting with Multisystem Complications in a Child: A Case Report and Literature Review
Authors: AlEed Ashwaq
Published: January 2025

Background and Clinical Significance: Lemierre’s syndrome, also known as the “forgotten disease”, is a rare clinical syndrome of septic thrombophlebitis associated with morbidity and mortality. This study reports on a 6-year-old boy diagnosed with Lemierre’s syndrome, providing an in-depth case analysis and a comprehensive review of the current literature on this uncommon condition. Case Presentation: A 6-year-old boy was admitted to the pediatric intensive care unit (PICU) with septic shock, presenting with a high-grade fever of 39.5 °C for 10 days and swelling in the left leg for one week. Additionally, he had a history of swelling in the left mandibular area for five days and a skin rash. His recent medical history was unremarkable, except for decreased activity and oral intake over the past three days. Both his neonatal and past medical histories were unremarkable. Upon admission to the PICU, a multidisciplinary team was assembled to address his condition. Following a comprehensive history, physical examination, and relevant investigations, the child was diagnosed and managed as a case of Lemierre’s syndrome—the first reported case in Saudi Arabia. Treatment included antibiotics, unfractionated heparin infusion, and analgesics. Family members were counseled on the nature, severity, and prognosis of the disease. Despite the optimal treatment given to this patient, the patient died from multiorgan failure as a complication of the disease after an eight-day stay in the PICU. Conclusions: This paper reports the main presenting features and the workup of a 6-year-old male child diagnosed and managed as a case of Lemierre’s syndrome in the Saudi Arabian context. The early recognition of the symptoms of Lemierre’s syndrome and introduction of appropriate treatment in multidisciplinary teamwork are crucial to improve the outcomes of such a life-threating syndrome.
SCM-YOLO for Lightweight Small Object Detection in Remote Sensing Images
Authors: Qiang Hao , Hao Wei , Xie Meilin , Tang Qiang , Shi Heng , Zhao Yixin , Han Xiaoteng
Published: January 2025

Currently, small object detection in complex remote sensing environments faces significant challenges. The detectors designed for this scenario have limitations, such as insufficient extraction of spatial local information, inflexible feature fusion, and limited global feature acquisition capability. In addition, there is a need to balance performance and complexity when improving the model. To address these issues, this paper proposes an efficient and lightweight SCM-YOLO detector improved from YOLOv5 with spatial local information enhancement, multi-scale feature adaptive fusion, and global sensing capabilities. The SCM-YOLO detector consists of three innovative and lightweight modules: the Space Interleaving in Depth (SPID) module, the Cross Block and Channel Reweight Concat (CBCC) module, and the Mixed Local Channel Attention Global Integration (MAGI) module. These three modules effectively improve the performance of the detector from three aspects: feature extraction, feature fusion, and feature perception. The ability of SCM-YOLO to detect small objects in complex remote sensing environments has been significantly improved while maintaining its lightweight characteristics. The effectiveness and lightweight characteristics of SCM-YOLO are verified through comparison experiments with AI-TOD and SIMD public remote sensing small object detection datasets. In addition, we validate the effectiveness of the three modules, SPID, CBCC, and MAGI, through ablation experiments. The comparison experiments on the AI-TOD dataset show that the mAP50 and mAP50-95 metrics of SCM-YOLO reach 64.053% and 27.283%, respectively, which are significantly better than other models with the same parameter size.
A Pine Wilt Disease Detection Model Integrated with Mamba Model and Attention Mechanisms Using UAV Imagery
Authors: Bai Minhui , Di Xinyu , Yu Lechuan , Ding Jian , Lin Haifeng
Published: January 2025

Pine wilt disease (PWD) is a highly destructive worldwide forest quarantine disease that has the potential to destroy entire pine forests in a relatively brief period, resulting in significant economic losses and environmental damage. Manual monitoring, biochemical detection and satellite remote sensing are frequently inadequate for the timely detection and control of pine wilt disease. This paper presents a fusion model, which integrates the Mamba model and the attention mechanism, for deployment on unmanned aerial vehicles (UAVs) to detect infected pine trees. The experimental dataset presented in this paper comprises images of pine trees captured by UAVs in mixed forests. The images were gathered primarily during the spring of 2023, spanning the months of February to May. The images were subjected to a preprocessing phase, during which they were transformed into the research dataset. The fusion model comprised three principal components. The initial component is the Mamba backbone network with State Space Model (SSM) at its core, which is capable of extracting pine wilt features with a high degree of efficacy. The second component is the attention network, which enables our fusion model to center on PWD features with greater efficacy. The optimal configuration was determined through an evaluation of various attention mechanism modules, including four attention modules. The third component, Path Aggregation Feature Pyramid Network (PAFPN), facilitates the fusion and refinement of data at varying scales, thereby enhancing the model’s capacity to detect multi-scale objects. Furthermore, the convolutional layers within the model have been replaced with depth separable convolutional layers (DSconv), which has the additional benefit of reducing the number of model parameters and improving the model’s detection speed. The final fusion model was validated on a test set, achieving an accuracy of 90.0%, a recall of 81.8%, a map of 86.5%, a parameter counts of 5.9 Mega, and a detection speed of 40.16 FPS. In comparison to Yolov8, the accuracy is enhanced by 7.1%, the recall by 5.4%, and the map by 3.1%. These outcomes demonstrate that our fusion model is appropriate for implementation on edge devices, such as UAVs, and is capable of effective detection of PWD.
Evaluation of Sea Ice Motion Estimates from Enhanced Resolution Passive Microwave Brightness Temperatures
Authors: Meier Walter N. , Stewart J. Scott
Published: January 2025

Sea ice motion plays an important role in the seasonal and interannual evolution of the polar sea ice cover. Satellite imagery can be used to track the motion of sea ice via cross-correlation feature tracking algorithms. Such a method has been used for the National Snow and Ice Data Center (NSIDC) sea ice motion product, based largely on passive microwave imagery. This study investigates the use of a new enhanced resolution passive microwave brightness temperature (TB) product to derive ice motion products. The results demonstrate that the new imagery source provides useful daily motion estimates that provide denser spatial coverage and reduced errors. The enhanced TBs yield motions that have a 30% lower Root Mean Square (RMS) difference with motion estimates from buoys. The enhanced resolution TBs will be used in the new version of the NSIDC motion product that is currently in development.
Haptic Shared Control Framework with Interaction Force Constraint Based on Control Barrier Function for Teleoperation
Authors: Qin Wenlei , Yi Haoran , Fan Zhibin , Zhao Jie
Published: January 2025

Current teleoperated robotic systems for retinal surgery cannot effectively control subtle tool-to-tissue interaction forces. This limitation may lead to patient injury caused by the surgeon’s mistakes. To improve the safety of retinal surgery, this paper proposes a haptic shared control framework for teleoperation based on a force-constrained supervisory controller. The supervisory controller leverages Control Barrier Functions (CBFs) and the interaction model to modify teleoperated inputs when they are deemed unsafe. This method ensures that the interaction forces at the slave robot’s end-effector remain within the safe range without the robot’s dynamic model and the safety margin. Additionally, the master robot provides haptic feedback to enhance the surgeon’s situational awareness during surgery, reducing the risk of misjudgment. Finally, simulated membrane peeling experiments are conducted in a controlled intraocular surgical environment using a teleoperated robotic system controlled by a non-expert. The experimental results demonstrate that the proposed control framework significantly reduces the rate of force constraint violation.
Opportunities and Challenges for Clinical Practice in Detecting Depression Using EEG and Machine Learning
Authors: Mulc Damir , Vukojevic Jaksa , Kalafatic Eda , Cifrek Mario , Vidovic Domagoj , Jovic Alan
Published: January 2025

Major depressive disorder (MDD) is associated with substantial morbidity and mortality, yet its diagnosis and treatment rates remain low due to its diverse and often overlapping clinical manifestations. In this context, electroencephalography (EEG) has gained attention as a potential objective tool for diagnosing depression. This study aimed to evaluate the effectiveness of EEG in identifying MDD by analyzing 140 EEG recordings from patients diagnosed with depression and healthy volunteers. Using various machine learning (ML) classification models, we achieved up to 80% accuracy in distinguishing individuals with MDD from healthy controls. Despite its promise, this approach has limitations. The variability in the clinical and biological presentations of depression, as well as patient-specific confounding factors, must be carefully considered when integrating ML technologies into clinical practice. Nevertheless, our findings suggest that an EEG-based ML model holds potential as a diagnostic aid for MDD, paving the way for further refinement and clinical application.
RWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT
Authors: Jia Guanwei , Shen Zhaoyu , Sun Hongye , Xin Jingbo , Wang Dongyu
Published: January 2025

This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. Traditional centralized IoT architectures often face issues such as single points of failure and insufficient reliability, while blockchain, with its decentralized and tamper-resistant properties, offers a promising solution. However, existing blockchain consensus mechanisms struggle to meet the high throughput, low latency, and scalability demands of IoT applications. To address these limitations, RWA-BFT adopts a two-layer blockchain architecture; the first layer leverages reputation-based filtering to reduce computational complexity by excluding low-reputation nodes, while the second layer employs an asynchronous consensus mechanism to ensure efficient and secure communication among high-reputation nodes, even under network delays. This dual-layer design significantly improves performance, achieving higher throughput, lower latency, and enhanced scalability, while maintaining strong fault tolerance even in the presence of a substantial proportion of malicious nodes. Experimental results demonstrate that RWA-BFT outperforms HB-BFT and PBFT algorithms, making it a scalable and secure blockchain solution for decentralized IoT applications.
Graphene-Based, Flexible, Wearable Piezoresistive Sensors with High Sensitivity for Tiny Pressure Detection
Authors: Li Rui , Hu Jiahao , Li Yalong , Huang Yi , Wang Lin , Huang Mohan , Wang Zhikun , Chen Junlang , Fan Yan , Chen Liang
Published: January 2025

Flexible, wearable, piezoresistive sensors have significant potential for applications in wearable electronics and electronic skin fields due to their simple structure and durability. Highly sensitive, flexible, piezoresistive sensors with the ability to monitor laryngeal articulatory vibration supply a new, more comfortable and versatile way to aid communication for people with speech disorders. Here, we present a piezoresistive sensor with a novel microstructure that combines insulating and conductive properties. The microstructure has insulating polystyrene (PS) microspheres sandwiched between a graphene oxide (GO) film and a metallic nanocopper-graphene oxide (n-Cu/GO) film. The piezoresistive performance of the sensor can be modulated by controlling the size of the PS microspheres and doping degree of the copper nanoparticles. The sensor demonstrates a high sensitivity of 232.5 kPa−1 in a low-pressure range of 0 to 0.2 kPa, with a fast response of 45 ms and a recovery time of 36 ms, while also exhibiting excellent stability. The piezoresistive performance converts subtle laryngeal articulatory vibration into a stable, regular electrical signal; in addition, there is excellent real-time monitoring capability of human joint movements. This work provides a new idea for the development of wearable electronic devices, healthcare, and other fields.
Polarization-Insensitive, High-Efficiency Metasurface with Wide Reception Angle for Energy Harvesting Applications
Authors: Amer Abdulrahman Ahmed Ghaleb , Othman Nurmiza , Bait-Suwailamn Mohammed M. , Sapuan Syarfa Zahirah , Salem Ali Ahmed Ali , Salh Adeb
Published: January 2025

This research presents an innovative polarization-insensitive metasurface (MS) harvester designed for energy harvesting applications at 5 GHz, capable of operating efficiently over wide reception angles. The proposed MS features a novel wheel-shaped resonator array whose symmetrical structure ensures insensitivity to the polarization of incident electromagnetic (EM) waves, enabling efficient energy absorption and minimizing reflections. Unlike conventional designs, the metasurface achieves near-unity harvesting efficiency, exceeds 94% under normal incidence, and maintains superior performance across various incident angles for TE and TM polarizations. To validate the design, a 5 × 5-unit cell array of the MS structure was fabricated and experimentally tested, demonstrating excellent agreement between simulation and measurement results. This work significantly advances metasurface-based energy harvesting by combining polarization insensitivity, wide-angle efficiency, and high absorption, making it a compelling solution for powering wireless sensor networks in next-generation applications.
Squat Motion of a Humanoid Robot Using Three-Particle Model Predictive Control and Whole-Body Control
Authors: Chen Hongxiang , Zhang Xiuli , Zhao Mingguo
Published: January 2025

Squatting is a fundamental and crucial movement, often employed as a basic test during robot commissioning, and it plays a significant role in some service industries and in cases when robots perform high-dynamic movements like jumping. Therefore, achieving continuous and precise squatting actions is of great importance for the future development of humanoid robots. In this paper, we apply three-particle model predictive control (TP-MPC) combined with weight-based whole-body control (WBC) to a humanoid robot. In this approach, the arms, legs, and torso are simplified into three particles. TP-MPC is utilized to optimize the rough planning’s reference trajectory, while WBC is employed to follow the optimized trajectory. The algorithm is tested through simulations of a humanoid robot performing continuous squatting motions. It demonstrates the ability to achieve more accurate trajectory tracking compared to using WBC alone and also optimizes the issue of excessive knee torque spikes that occur with WBC alone during squatting. Moreover, the algorithm is less computationally intensive, and it is capable of operating at a frequency of 100 Hz.
Terrain Traversability via Sensed Data for Robots Operating Inside Heterogeneous, Highly Unstructured Spaces
Authors: Gholami Amir , Ramirez-Serrano Alejandro
Published: January 2025

This paper presents a comprehensive approach to evaluating the ability of multi-legged robots to traverse confined and geometrically complex unstructured environments. The proposed approach utilizes advanced point cloud processing techniques integrating voxel-filtered cloud, boundary and mesh generation, and dynamic traversability analysis to enhance the robot’s terrain perception and navigation. The proposed framework was validated through rigorous simulation and experimental testing with humanoid robots, showcasing the potential of the proposed approach for use in applications/environments characterized by complex environmental features (navigation inside collapsed buildings). The results demonstrate that the proposed framework provides the robot with an enhanced capability to perceive and interpret its environment and adapt to dynamic environment changes. This paper contributes to the advancement of robotic navigation and path-planning systems by providing a scalable and efficient framework for environment analysis. The integration of various point cloud processing techniques into a single architecture not only improves computational efficiency but also enhances the robot’s interaction with its environment, making it more capable of operating in complex, hazardous, unstructured settings.
Connecting Cities: A Case Study on the Application of Morphological Shortest Paths
Authors: Perez-Ramos Jorge L. , Ramirez-Rosales Selene , Canton-Enriquez Daniel , Diaz Jimenez Luis A. , Hernandez-Ramirez Herlindo , Herrera-Navarro Ana M. , Jimenez-Hernandez Hugo
Published: January 2025

Navigatingdensely connected networks can be complex due to the different connection structures present within a network. No explicit algorithms are designed specifically for this navigation, so heuristic approaches and existing network systems are often employed. However, this task can become computationally asymmetrical, as the complexity of creating a representation of the city is lower than the complexity involved in identifying a set of feasible paths in a combinatorial order. This paper extends the applicability of morphological approaches to compute the shortest path in smart cities, driven by the complexity and size of the vital communication infrastructure. As is well known, this communication infrastructure changes dynamically, particularly with the evolving connection paths due to continuous population growth. Consequently, efficient communication trajectories can quickly become obsolete. The challenge of computing the best trajectories to respond more quickly to the growing population comes with high computational complexity. This paper presents an application that uses a discrete algorithm designed to compute the shortest path through a morphological approach. Specifically, it seeks to identify the best trajectory within a densely populated city based on a complex density graph. By incorporating morphological approaches into path-search algorithms, we can define a new family of methods that operate in discrete spaces with a morphological representation, resulting in approaches that have lower computational requirements. Other well-known applications in this context include the delivery of resources, such as managing electrical power consumption or minimizing time delays in resource delivery. This task is essential but classified as an NP problem, making it an appropriate scenario for applying the proposed algorithm to navigate a dense graph. The paper highlights the well-known problem of finding the shortest path as one of the potential applications of the introduced algorithm. The algorithm aims to identify the optimal path trajectory within a graph representing a dense city’s real scenario. This discussion compares and contrasts the proposal with other established approaches, highlighting the advantages and characteristics of the proposed method.