bluuebunny/crossref_metadata_2025 huggingface dataset:
CX-5461 Preferentially Induces Top2α-Dependent DNA Breaks at Ribosomal DNA Loci
Authors: Cameron Donald P. , Sornkom Jirawas , Alsahafi Sameerh , Drygin Denis , Poortinga Gretchen , McArthur Grant A. , Hein Nadine , Hannan Ross , Panov Konstantin I.
Published: July 2024

While genotoxic chemotherapeutic agents are among the most effective tools to combat cancer, they are often associated with severe adverse effects caused by indiscriminate DNA damage in non-tumor tissue as well as increased risk of secondary carcinogenesis. This study builds on our previous work demonstrating that the RNA Polymerase I (Pol I) transcription inhibitor CX-5461 elicits a non-canonical DNA damage response and our discovery of a critical role for Topoisomerase 2α (Top2α) in the initiation of Pol I-dependent transcription. Here, we identify Top2α as a mediator of CX-5461 response in the murine Eµ-Myc B lymphoma model whereby sensitivity to CX-5461 is dependent on cellular Top2α expression/activity. Most strikingly, and in contrast to canonical Top2α poisons, we found that the Top2α-dependent DNA damage induced by CX-5461 is preferentially localized at the ribosomal DNA (rDNA) promoter region, thereby highlighting CX-5461 as a loci-specific DNA damaging agent. This mechanism underpins the efficacy of CX-5461 against certain types of cancer and can be used to develop effective non-genotoxic anticancer drugs.
Injectable Biomimetic Gels for Biomedical Applications
Authors: Omidian Hossein , Wilson Renae , Dey Chowdhury Sumana
Published: July 2024

Biomimetic gels are synthetic materials designed to mimic the properties and functions of natural biological systems, such as tissues and cellular environments. This manuscript explores the advancements and future directions of injectable biomimetic gels in biomedical applications and highlights the significant potential of hydrogels in wound healing, tissue regeneration, and controlled drug delivery due to their enhanced biocompatibility, multifunctionality, and mechanical properties. Despite these advancements, challenges such as mechanical resilience, controlled degradation rates, and scalable manufacturing remain. This manuscript discusses ongoing research to optimize these properties, develop cost-effective production techniques, and integrate emerging technologies like 3D bioprinting and nanotechnology. Addressing these challenges through collaborative efforts is essential for unlocking the full potential of injectable biomimetic gels in tissue engineering and regenerative medicine.
Disrupted Brain Network Measures in Parkinson’s Disease Patients with Severe Hyposmia and Cognitively Normal Ability
Authors: Siva Karthik , Ponnusamy Palanisamy , Ramanathan Malmathanraj
Published: July 2024

Neuroscience has revolved around brain structural changes, functional activity, and connectivity alteration in Parkinson’s Disease (PD); however, how the network topology organization becomes altered is still unclear, specifically in Parkinson’s patients with severe hyposmia. In this study, we have examined the functional network topological alteration in patients affected by Parkinson’s Disease with normal cognitive ability (ODN), Parkinson’s Disease with severe hyposmia (ODP), and healthy controls (HCs) using resting-state functional magnetic resonance imaging (rsfMRI) data. We have analyzed brain topological organization using popular graph measures such as network segregation (clustering coefficient, modularity), network integration (participation coefficient, path length), small-worldness, efficiency, centrality, and assortativity. Then, we used a feature ranking approach based on the diagonal adaptation of neighborhood component analysis, aiming to determine a graph measure that is sensitive enough to distinguish between these three different groups. We noted significantly lower segregation and local efficiency and small-worldness in ODP compared to ODN and HCs. On the contrary, we did not find differences in network integration in ODP compared to ODN and HCs, which indicates that the brain network becomes fragmented in ODP. At the brain network level, a progressive increase in the DMN (Default Mode Network) was observed from healthy controls to ODN to ODP, and a continuous decrease in the cingulo-opercular network was observed from healthy controls to ODN to ODP. Further, the feature ranking approach has shown that the whole-brain clustering coefficient and small-worldness are sensitive measures to classify ODP vs. ODN, as well as HCs. Looking at the brain regional network segregation, we have found that the cerebellum and limbic, fronto-parietal, and occipital lobes have higher ODP reductions than ODN and HCs. Our results suggest network topological measures, specifically whole-brain segregation and small-worldness decreases. At the network level, an increase in DMN and a decrease in the cingulo-opercular network could be used as biomarkers to characterize ODN and ODP.
Performance Evaluation of Soybean Oil/SBR Reclaimed Asphalt and Mixtures
Authors: Chen Yu , Li Xiao , Tian Xiaoge
Published: July 2024

This study evaluated the properties of soybean oil/SBR reclaimed asphalt (SSRA). The optimal preparation method for SSRA was determined. Additionally, the feasibility of the optimal SSRA scheme was verified through asphalt mixture performance tests. With the soybean oil dosage enhanced, the penetration and low-temperature rheological performance of SSRA were improved. The incorporation of soybean oil lowered the softening point, viscosity, and rutting index of aged asphalt. The softening points of SBR-4%+Oil-7.5% and SBR-6%+Oil-7.5% were 79.4 °C and 82.9 °C, respectively. The stiffness modulus of SBR-6%+oil-10% decreased by 35.37%. When the soybean oil dosage was 10% and the SBR dosage was 6% (SBR-6%+oil-10%), the properties of RTFOT+PAV aged asphalt were restored to those of its original state. The splitting tensile strength ratio of the SBR-6%+oil-10% mixture was 89%, with a decrease of 1.5% compared to the original asphalt mixture. The SBR-6%+oil-10% mixture exhibited improved high-temperature and low-temperature service properties. The total deformation of the SBR-6%+oil-10% mixture decreased by 8.43%, while its dynamic stability increased by 22.21%. This degree of improvement compared to the original asphalt mixture was not significant. The rejuvenation of the aged asphalt and mixture performance can mainly be attributed to the soybean oil supplementing the lost lightweight components of the aged asphalt, while SBR supplemented the degraded polymers. Utilizing soybean oil as a rejuvenating asphalt agent facilitates waste material recycling. Furthermore, this study provides a new idea for the recycling of polymer-modified asphalt and reclaimed asphalt pavement.
A Prediction Model for Soil–Water Characteristic Curve Based on Machine Learning Considering Multiple Factors
Authors: Yang Guangchang , Liu Jianping , Liu Yang , Wu Nan , Liu Tingguang
Published: July 2024

Aiming at the problem of long soil–water characteristic curve (SWCC) testing times and the difficulty of prediction accuracy in complex environments, this paper establishes a SWCC prediction model based on a neural network machine learning algorithm which can take into account the influence of multiple factors such as temperature, deformation, and salinity. The input layer of the model can reflect the physical properties of the soil and the influence of the external environment, while the suction is taken as an input variable, which in turn can directly obtain the water content under the corresponding conditions. The predictive ability of the model is verified by comparing and analyzing the predicted results of the SWCC under different temperature, void ratio, and salinity conditions with the experimental results. The research in this paper provides a new method for predicting the SWCC considering multiple factors, and the prediction accuracy of the model is related to the amount of experimental data.
Fractal Dimension, Circularity, and Solidity of Cell Clusters in Liquid-Based Endometrial Cytology Are Potentially Useful for Endometrial Cancer Detection and Prognosis Prediction
Authors: Onuma Toshimichi , Shinagawa Akiko , Kurokawa Tetsuji , Orisaka Makoto , Yoshida Yoshio
Published: July 2024

Endometrial cancer (EC) in women is increasing globally, necessitating improved diagnostic methods and prognosis prediction. While endometrial histology is the conventional approach, liquid-based endometrial cytology may benefit from novel analytical techniques for cell clusters. A clinical study was conducted at the University of Fukui Hospital from 2012 to 2018, involving 210 patients with endometrial cytology. The liquid-based cytology images were analyzed using cell cluster analysis with Image J software. Logistic regression, ROC analysis, and survival analysis were employed to assess the diagnostic accuracy and prognosis between cell cluster analysis and EC/atypical endometrial hyperplasia (AEH). Circularity and fractal dimension demonstrated significant associations with EC and AEH, regardless of age and cytology results. The ROC analysis revealed improved diagnostic accuracy when combining fractal dimension with cytology, particularly in menopausal age groups. Lower circularity and solidity were independently associated with poor overall survival, while higher fractal dimension values correlated with poorer overall survival in Grades 2 and 3 endometrial cancers. The combination of circularity and fractal dimension with cytology improved diagnostic accuracy for both EC and AEH. Moreover, circularity, solidity, and fractal dimension may serve as prognostic indicators for endometrial cancer, contributing to the development of more refined screening and diagnostic strategies.
Emerging Therapeutic Strategies to Overcome Drug Resistance in Cancer Cells
Authors: Garg Pankaj , Malhotra Jyoti , Kulkarni Prakash , Horne David , Salgia Ravi , Singhal Sharad S.
Published: July 2024

The rise of drug resistance in cancer cells presents a formidable challenge in modern oncology, necessitating the exploration of innovative therapeutic strategies. This review investigates the latest advancements in overcoming drug resistance mechanisms employed by cancer cells, focusing on emerging therapeutic modalities. The intricate molecular insights into drug resistance, including genetic mutations, efflux pumps, altered signaling pathways, and microenvironmental influences, are discussed. Furthermore, the promising avenues offered by targeted therapies, combination treatments, immunotherapies, and precision medicine approaches are highlighted. Specifically, the synergistic effects of combining traditional cytotoxic agents with molecularly targeted inhibitors to circumvent resistance pathways are examined. Additionally, the evolving landscape of immunotherapeutic interventions, including immune checkpoint inhibitors and adoptive cell therapies, is explored in terms of bolstering anti-tumor immune responses and overcoming immune evasion mechanisms. Moreover, the significance of biomarker-driven strategies for predicting and monitoring treatment responses is underscored, thereby optimizing therapeutic outcomes. For insights into the future direction of cancer treatment paradigms, the current review focused on prevailing drug resistance challenges and improving patient outcomes, through an integrative analysis of these emerging therapeutic strategies.
Modulating Tumor Immunity by Targeting Tumor Fibrotic Stroma and Angiogenic Vessels for Lung Cancer Treatment
Authors: Yuan Yi , Mishra Falguni , Li Bin , Peng Guangda , Chan Payton , Yang Jenny , Liu Zhiren
Published: July 2024

Fibrotic stroma and angiogenic tumor vessels play an important role in modulating tumor immunity. We previously reported a rationally designed protein (ProAgio) that targets integrin αvβ3 at a novel site. ProAgio induces the apoptosis of cells that express high levels of the integrin. Both activated cancer-associated fibroblasts (CAFs) and angiogenic endothelial cells (aECs) in tumors express high levels of integrin αvβ3. ProAgio simultaneously and specifically induces apoptosis in CAFs and aECs in tumors. We provide evidence here that the depletion of CAFs and the elimination of leaky tumor angiogenic vessels by ProAgio alter tumor immunity. ProAgio reduces CD4+ Treg and Myeloid-derived suppressor cells (MDSCs), increases CD8+ T-cells, and increases the M1/M2 macrophage ratio in the tumor. The depletion of dense fibrotic stroma (CAFs) by ProAgio decreases the Programmed Death Ligand 1 (PDL-1) levels in the stroma areas surrounding the tumors, and thus strongly increases the delivery of anti-PDL-1 antibody to the target cancer cells. The impact of ProAgio on tumor immunity provides strong synergistical effects of checkpoint inhibitors on lung cancer treatment.
Differential Diagnosis of Pigmented Lesions in the Oral Mucosa: A Clinical Based Overview and Narrative Review
Authors: Abati Silvio , Sandri Giacomo Francesco , Finotello Leonardo , Polizzi Elisabetta
Published: July 2024

This paper examines the clinical differentiation of pigmented lesions in the oral mucosa, which poses significant diagnostic challenges across dental and medical disciplines due to their spectrum from benign to potentially malignant conditions. Through a literature review and analysis of clinical cases, this study clarifies current diagnostic methodologies, with an emphasis on differential diagnosis, to provide a practical guide for clinicians. The classification of pigmented lesions, such as endogenous, focal melanocytic, and multifocal pigmentation, based on clinical and histological features, highlights the necessity for a structured and informed approach. A retrospective examination of cases from our oral medicine and pathology clinic, coupled with analysis of photographic and histological records, aids in classifying these lesions. This fosters a better understanding and promotes informed discussions among clinicians, ultimately aiming to enhance early and precise diagnosis, thus improving patient management and outcomes.
Dependence of the Fluidizing Condition on Operating Parameters for Sorption-Enhanced Methanol Synthesis Catalyst and Adsorbent
Authors: Renda Simona , Lasobras Javier , Soler Jaime , Herguido Javier , Menéndez Miguel
Published: July 2024

The fluidization of two different solids was investigated by varying the temperature and pressure conditions and the fluidizing gas. The solids are a novel catalyst and a water sorbent that could be used to perform sorption-enhanced methanol synthesis; the operating conditions were selected accordingly to this process. The aim of this investigation was to find an expression for predicting the minimum fluidization conditions of a methanol synthesis catalyst and an adsorbent in the presence of their process stream and operating conditions. The findings of this study highlighted how umf (STP) decreases with a rise in temperature and increases with a rise in pressure, according to other works in the literature with different solids. Furthermore, the type of gas was found to influence the minimum fluidization velocity significantly. The experimental results agreed well with a theoretical expression of the minimum fluidization velocity adjusted for temperature, pressure, and viscosity. The choice of the expression for viscosity calculation in the case of gas mixtures was found to be of key importance. These results will be useful for researchers aiming to calculate the minimum fluidization velocity of a catalyst or other solids under reaction conditions using results obtained at ambient conditions with air or inert gas.
Cx40 Levels Regulate Hypoxia-Induced Changes in the Migration, Proliferation, and Formation of Gap Junction Plaques in an Extravillous Trophoblast Cell Model
Authors: Rozas-Villanueva Fernanda M. , Orellana Viviana P. , Alarcón Rodrigo , Maripillan Jaime , Martinez Agustin D. , Alfaro Ivan E. , Retamal Mauricio A.
Published: July 2024

Background: Extravillous trophoblasts (EVTs) form stratified columns at the placenta–uterus interface. In the closest part to fetal structures, EVTs have a proliferative phenotype, whereas in the closest part to maternal structures, they present a migratory phenotype. During the placentation process, Connexin 40 (Cx40) participates in both the proliferation and migration of EVTs, which occurs under hypoxia. However, a possible interaction between hypoxia and Cx40 has not yet been established. Methods: We developed two cellular models, one with “low Cx40” (Jeg-3), which reflected the expression of this protein found in migratory EVTs, and one with “high Cx40” (Jeg-3/hCx40), which reflected the expression of this protein in proliferative cells. We analyzed the migration and proliferation of these cells under normoxic and hypoxic conditions for 24 h. Jeg-3 cells under hypoxia increased their migratory capacity over their proliferative capacity. However, in Jeg-3/hCx40, the opposite effect was induced. On the other hand, hypoxia promoted gap junction (GJ) plaque formation between neighboring Jeg-3 cells. Similarly, the activation of a nitro oxide (NO)/cGMP/PKG-dependent pathway induced an increase in GJ-plaque formation in Jeg-3 cells. Conclusions: The expression patterns of Cx40 play a crucial role in shaping the responses of EVTs to hypoxia, thereby influencing their migratory or proliferative phenotype. Simultaneously, hypoxia triggers an increase in Cx40 gap junction (GJ) plaque formation through a pathway dependent on NO.
Precise Serial Microregistration Enables Quantitative Microscopy Imaging Tracking of Human Skin Cells In Vivo
Authors: Tian Yunxian , Wu Zhenguo , Lui Harvey , Zhao Jianhua , Kalia Sunil , Seo InSeok , Ou-Yang Hao , Zeng Haishan
Published: July 2024

We developed an automated microregistration method that enables repeated in vivo skin microscopy imaging of the same tissue microlocation and specific cells over a long period of days and weeks with unprecedented precision. Applying this method in conjunction with an in vivo multimodality multiphoton microscope, the behavior of human skin cells such as cell proliferation, melanin upward migration, blood flow dynamics, and epidermal thickness adaptation can be recorded over time, facilitating quantitative cellular dynamics analysis. We demonstrated the usefulness of this method in a skin biology study by successfully monitoring skin cellular responses for a period of two weeks following an acute exposure to ultraviolet light.
Incidence and Characteristics of Pediatric Patients with Acute Otitis Hospitalized in a Romanian Infectious Diseases Hospital
Authors: Pleșca Vlad Ștefan , Streinu-Cercel Anca , Săndulescu Oana , Drăgănescu Anca Cristina , Hainăroșie Răzvan , Pleșca Anca Doina
Published: July 2024

Background: Otic involvement is common in children during acute infectious diseases, and is an important cause of morbidity and health service utilization. Methods: We performed a retrospective analysis of pediatric cases hospitalized in the largest infectious disease hospital in Romania between 2018 and 2023, with the aim of quantifying the incidence and impact of acute otitis (AO) according to pediatric age subgroups. Results: A total of 1118 cases diagnosed with AO were eligible and included in the analysis. Acute congestive otitis media was the most common subtype, identified in 53.3% of cases, followed by acute purulent otitis media (APOM) in 26.7% of children. The majority of AO cases (69.9%) were diagnosed in the pre-pandemic period (2018–2019), and infants (10.6%), toddlers (49.4%), and preschoolers (29.2%) were the most affected age groups. A viral infection associated with the AO episode was documented in 49.6% of cases. Influenza viruses were most commonly reported (20.5%), followed by SARS-CoV-2 (5.8%), and adenovirus (4.9%). A total of 38 cases of AO were identified in children with measles. In 15.9% of APOM cases, Streptococcus pneumoniae was isolated by culture from otic secretions. The duration of hospitalization was longer in children with APOM and acute otitis externa compared to the other subtypes of AO (p < 0.001). Conclusions: Our study highlights the importance of ENT (ear, nose, and throat) monitoring in children hospitalized for acute infectious diseases, as the majority of AO cases occur in the context of a viral infection. These findings emphasize the necessity for tailored assessment and intervention in suspected cases of AO, especially in young children under 5 years of age.
Biochemical Evaluation and Structural Characteristics of Copper Coating Cellulose Nonwovens Prepared by Magnetron Sputtering Technology
Authors: Świerczyńska Małgorzata , Mrozińska Zdzisława , Lisiak-Kucińska Agnieszka , Walawska Anetta , Kudzin Marcin H.
Published: July 2024

The research aimed to enhance the aqua-jet/spunlace cellulose nonwoven fabric by deposition of copper coating by magnetron sputtering technology. Plasma technology facilitated the efficient distribution of copper particles on the surface of the cellulose nonwoven fabric, while maintaining free airflow and eliminating the need for additional layers. New cellulose-copper composites exhibit potential in biomedical applications, while minimizing their impact on biological processes such as blood plasma coagulation. Consequently, they can be utilized in the production of dressings, bandages, and other medical products requiring effective protection against bacterial infections. The cellulose-copper composite material was subjected to the physiochemical and biological investigations. The physiochemical analysis included the elemental analysis of composites, their microscopic analysis and the surface properties analysis (specific surface area and total pore volume). The biological investigations consisted of biochemical-hematological tests including the evaluation of the activated partial thromboplastin time and pro-thrombin time. Biodegradable materials based on cellulose nonwoven fabrics with the addition of copper offer a promising alternative to conventional materials. Their innovative properties, coupled with environmental friendliness and minimal impact on biological processes, offer vast application possibilities in healthcare and the production of hygiene products.
Smoke Suppression Properties of Fe2O3 on Intumescent Fire-Retardant Coatings of Styrene–Acrylic Emulsion
Authors: Dong Fang , Song Qingfeng , Ma Liyong
Published: July 2024

The intumescent flame-retardant coatings were prepared using ammonium polyphosphate (APP), pentaerythritol (PER), melamine (MEL), styrene–acrylic emulsion, and iron oxide yellow (FeOOH) as the base material. A cone calorimeter (CCT), smoke density meter (SDA), and scanning electron microscope (SEM) were employed to investigate the smoke suppression and flame retardancy of FeOOH in intumescent fire-retardant coatings. The thermal degradation performance of intumescent fireproofing coatings with varying FeOOH content was investigated through thermogravimetric analysis (TGA). The structure of the carbon slag in the CCT test was analyzed using a scanning electron microscope (SEM). The results of the cone calorimeter (CCT) experiments demonstrated that FeOOH significantly reduced the heat release rate (HRR), total heat release rate (THR), smoke production rate (SPR), and total smoke release rate (TSR) of the coating, while simultaneously increasing the carbon residue rate of the coating. The smoke density analysis (SDA) results demonstrate that adding FeOOH can effectively reduce smoke generation, regardless of whether a pilot flame is used. TGA results demonstrate that FeOOH can enhance the weight of coke residue at elevated temperatures. SEM results indicate that incorporating FeOOH resulted in a more compact coke residue. According to these findings, among all the samples, those containing 2 wt% FeOOH showed low levels of HRR, THR, SPR, and TSR and high levels of SOD, which proves that FeOOH can be used as a smoke inhibitor in flame-retardant coatings.
Study of the Adsorption of Anionic Surfactants on Carbonate Rocks: Characterizations, Experimental Design, and Parameter Implementation
Authors: Borges Valdivino Francisco dos Santos , Monteiro Mayra Kerolly Sales , Filho Ernani Dias da Silva , Silva Dennys Correia da , Fonseca José Luís Cardozo , Neto Alcides O. Wanderley , Braga Tiago Pinheiro
Published: July 2024

Controlling or reducing the adsorption of surfactants on reservoir rock surfaces has been a challenging task in enhanced oil recovery (EOR) methods, as it directly affects the cost-effectiveness of the projects. The adsorption of surfactants on rock surfaces can modify their hydrophobicity, surface charge, and other important parameters that govern EOR processes, such as reducing the interfacial tension between water and oil and increasing permeability. Therefore, understanding the adsorption mechanism on rocks is essential for developing alternatives that improve the effectiveness of these processes. In this work, the adsorption of surfactants on carbonate materials was evaluated considering variations in temperature, contact time, and surfactant concentration. The surfactants used were derived from vegetable oils, aiming for a sustainable approach: saponified coconut oil (SCO), saponified babassu coconut oil (SBCO), and saponified castor oil (SMO). The finite bath method was used, resulting in adsorption efficiencies of 85.74%, 82.52%, and 45.30% for SCO, SBCO, and SMO, respectively. The Sips isotherm and the pseudo-second-order model were found to be suitable for characterizing these systems. The simulation of SCO adsorption isotherms on limestone by the Langmuir model was more accurate than that using the Freundlich model. The limestone showed a negative surface charge of approximately −35.0 mV at pH 6.5; this negative charge varied over a wide pH range. These zeta potential data for the samples confirmed that hydrophobic interactions played an important role in the adsorption of the surfactants. Thermodynamic evaluation indicated spontaneous and endothermic adsorption of SCO on limestone. The systems were also characterized by FTIR, TG/DTG, XRD, XRF, SEM, and zeta potential.
One-Dimensional and Two-Dimensional Nanomaterials for Sensor Applications
Authors: Zhou Andrew F. , Feng Peter X.
Published: July 2024

The significance of 1D and 2D nanomaterials in sensor technology lies in their unique properties and the potential for high-performance sensing [...]
Neurofibromatosis Type 1—Retinal Alterations Detectable with Optical Coherence Tomography Angiography
Authors: Târtea Anca Elena , Mocanu Carmen Luminița , Ștefănescu Dima Alin Ștefan , Tănasie Andreea Cornelia , Maria Veronica , Dan Alexandra Oltea , Bălășoiu Andrei Theodor
Published: July 2024

Neurofibromatosis type 1 (NF 1) is a multisystemic genetic disorder involving aberrant proliferation of multiple tissues of a neural crest origin. It represents a tumor predisposition syndrome characterized by a wide range of clinical manifestations, such as benign tumors, which primarily affect the skin and the nervous system. The most frequent clinical signs of NF 1 include café-au-lait spots all over the surface of the skin and axillary freckling; however, these signs can be accompanied by more severe manifestations such as the growth of both benign and malignant nervous system tumors and skeletal dysplasia, as well as a wide range of ocular manifestations. We report the rare case of retinal microvascular alterations and choroidal nodules in a 15 year old male patient with NF 1, detectable on optical coherence tomography angiography (OCTA). The hyperreflective choroidal nodules modified the profile of the choroidal vasculature. The retinal microvascular alterations in the form of clustered capillaries were detected in the superficial capillary plexus located nasally to the macular region. Retinal vascular abnormalities undetectable on fundus photography or fundoscopy can be present in patients with NF 1. Indirect ophthalmoscopy of our study patient was unremarkable. However, retinal vascular abnormalities were seen on OCTA scans in the superficial capillary plexus and choroidal nodules were detected on raster OCT scans. OCTA represents a useful imaging technique for detecting retinal microvascular abnormalities, which can be considered additional distinctive signs of NF 1.
A Rare Case of Invasive Thyroid Aspergillosis Revealed on 18F-FDG-PET/CT
Authors: Jaafari Ayoub , Mansour Sohaïb , Lebrun Laetitia , Kaefer Keitiane , Attou Rachid
Published: July 2024

Invasive aspergillosis (IA) represents a common form of fungal infection caused by various species of Aspergillus that most frequently affect immunocompromised patients. Typically, this disease occurs preferentially in high-risk groups including patients infected with the human immunodeficiency virus (HIV), patients with leukemia, patients with autoimmune diseases, and organ transplant patients undergoing medical immunosuppression. Considered the second most common cause of opportunistic fungal infection in humans after Candida albicans, this pathogen predominantly affects the lungs, but it may also spread by a hematogenous route to various organs and have a heterogeneous presentation. Owing to its high iodine levels, high perfusion, and enclosed capsule, the thyroid gland is considered to have a lower susceptibility to microbial invasion, and it is fairly uncommon to find associated infectious nodules. In metabolic imaging, 18F-FDG-PET/CT has become increasingly useful for detecting a wide range of infectious and inflammatory diseases and is already the gold standard for certain indications. According to the literature, no studies of hypermetabolic nodular thyroid aspergillosis on 18F-FDG-PET/CT confirmed on histology have yet been reported. Here, we report the first case of a patient with a heterogeneous presentation of IA and the presence of a hypermetabolic nodule in the thyroid with a surprising result.
Aspects of Occlusal Recordings Performed with the T-Scan System and with the Medit Intraoral Scanner
Authors: Popa Angelica Diana , Vlăduțu Diana Elena , Turcu Adina Andreea , Târtea Daniel Adrian , Ionescu Mihaela , Păunescu Cătălin , Stan Răzvan Sabin , Mercuț Veronica
Published: July 2024

Introduction: Dental occlusion refers to the static and dynamic relationships that are established between the teeth of the two arches and is an important factor in the homeostasis of the dento-maxillary system. The objective of the present study was to compare two digital occlusal analysis systems: the T-Scan III system and the Medit I600 intraoral scanner. Materials and Methods: The study was carried out on 20 students from the Faculty of Dental Medicine Craiova, whose dental occlusion was assessed with the T-Scan III system and with the Medit I600 intraoral scanner. Dental occlusion was assessed in the maximum intercuspation position, the edge-to-edge protrusion position, and the edge-to-edge position in right and left laterotrusion. The images of the 2D occlusal contact areas obtained by both methods were converted to .jpeg format and then transferred to Adobe Photoshop CS6 2021 (Adobe Systems, San Jose, CA, USA) for comparison. The recorded data were statistically processed. Results: Analyzing the data provided by the two digital occlusal analysis systems, it was found that the T-Scan III system provided data related to the amplitude of the occlusal forces, the surface on which they were distributed (the contact surface), the dynamics of the occlusal contacts, and the proportion in which they were distributed at the level of the two hemiarches, and the Medit I600 intraoral scanner performed an evaluation of the occlusal interface of the two arches, highlighting the extent of the contact areas with the degree of overlapping of the occlusal components. Although both methods of occlusal analysis recorded the highest values for the maximum intercuspation position, the results could not be compared. Conclusions: The two digital systems provide different data in occlusal analysis. As the T-Scan III system is considered the gold standard for occlusal analysis, more studies are needed to understand the data provided by the Medit I600 intraoral scanner and their significance.
Multi-Level Switching Control Scheme for Folding Wing VTOL UAV Based on Dynamic Allocation
Authors: Lin Zehuai , Yan Binbin , Zhang Tong , Li Shaoyi , Meng Zhongjie , Liu Shuangxi
Published: July 2024

A folding wing vertical take-off and landing (VTOL) UAV is capable of transitioning between quadrotor and fixed-wing modes, but significant alterations occur in its dynamics model and maneuvering mode during the transformation process, thereby imposing greater demands on the adaptability of its control system. In this paper, a multi-level switching control scheme based on dynamic allocation is proposed for the deformation stage. Firstly, according to the physical characteristics of the wing folding mechanism, a dynamic model is established. The influence of the incoming flow on the rotors is considered, and the dynamic coupling characteristics in its transition process are analyzed. Secondly, by inverting the changes in rotor position and axial direction, a dynamic allocation algorithm for the rotors is designed. Then, the quadrotor controller and the fixed-wing controller are switched and mixed in multiple loops to form a multi-level switching control scheme. Finally, the simulation results show that the designed multi-level switching control scheme is effective and robust in forward and backward deformation processes, and its anti-interference ability is stronger compared with that of the control scheme without dynamic allocation.
What’s the Difference? A Comparison of Student-Centered Teaching Methods
Authors: Goodwin Joshua R.
Published: July 2024

Many approaches to teaching and learning are classified as student-centered. The current literature evaluates these methods in-depth either individually or by comparing two or three at a time. This article provides a comparison of multiple student-centered teaching methods, with examples, employed in contemporary education. The aim is to assess the key characteristics associated with different approaches by investigating five popular student-centered teaching methodologies: activity-based learning, inquiry-based learning, cooperative learning, problem-based learning, and project-based learning. The results enable educators to make informed decisions about instructional strategies and provide a stepping stone for further research.
Variables Linked to Academic Stress Related to the Psychological Well-Being of College Students Inside and Outside the Context of the COVID-19 Pandemic
Authors: Wong Aitken Higinio Guillermo , Rabanal-León Helen Catalina , Saldaña-Bocanegra Jesús Catherine , Carranza-Yuncor Nelly Roxana , Rondon-Eusebio Rafael Fernando
Published: July 2024

The present study examines the impact of academic stress on the psychological well-being of college students during and after the COVID-19 pandemic. The purpose of this study is to investigate similarities and differences in both scenarios. As a method, a review of the scientific literature was carried out following the PRISMA methodology. The Scopus and Web of Science databases were used by applying eligibility criteria and multiple filtering stages. Thirty-seven studies were selected for a qualitative content analysis. The results allowed for five groups of variables associated with academic stress to be categorized: (1) adaptation to change; (2) study modality; (3) learning resources; (4) academic–life balance; and (5) socio-emotional variables. The comparative analysis evidenced the exacerbation of academic stress and the comprehensive affectation of psychological well-being during the social restriction measures put in place due to the COVID-19 pandemic. In post-pandemic contexts, responses were mitigated by available social and affective resources. It was concluded that academic stress and its associated variables had more unfavorable consequences on the psychological well-being of college students due to social isolation measures with remote education during the pandemic.
Exploring the Integration of Artificial Intelligence-Based ChatGPT into Mathematics Instruction: Perceptions, Challenges, and Implications for Educators
Authors: Egara Felix Oromena , Mosimege Mogege
Published: July 2024

This research investigates how secondary school mathematics educators in the Nsukka Education Zone, Enugu State, Nigeria, perceive the incorporation of artificial intelligence-based ChatGPT into teaching mathematics. The study employed a sequential exploratory mixed-methods strategy, starting with a systematic survey and followed by detailed interviews. The Mathematics Teachers’ Awareness and Perceptions of AI-based ChatGPT Questionnaire (MTAPACQ) used in this study was adapted from an existing online survey and administered to 80 mathematics teachers, who were selected using stratified random sampling to ensure varied representation across different local government areas. The survey explored teachers’ awareness, utilisation, and perceptions of ChatGPT. Following the quantitative phase, in-depth qualitative interviews were conducted with a subset of five teachers who were familiar with ChatGPT to gain deeper insights into their experiences. The findings indicate limited awareness of ChatGPT, with only 17% demonstrating familiarity with the technology. The infrequent utilisation of ChatGPT in mathematics teaching is mainly associated with this limited awareness. Teachers who integrate ChatGPT report positive outcomes, including improved teaching effectiveness, heightened student engagement, and enhanced comprehension of complex concepts. Nevertheless, the overall perceptions of the tool’s impact on mathematics teaching and learning are moderate. The identified challenges in relation to integration include technical adaptability, curriculum alignment, and the need for customisation to accommodate diverse learning styles. This study emphasises the significance of continuous professional development and ongoing support for teachers to integrate AI-based ChatGPT into mathematics instruction proficiently. The insights derived from the findings hold value for educators, policymakers, and technology developers aspiring to elevate the role of artificial intelligence in mathematics education.
Digital Forensics for Analyzing Cyber Threats in the XR Technology Ecosystem within Digital Twins
Authors: Oh Subin , Shon Taeshik
Published: July 2024

Recently, advancements in digital twin and extended reality (XR) technologies, along with industrial control systems (ICSs), have driven the transition to Industry 5.0. Digital twins mimic and simulate real-world systems and play a crucial role in various industries. XR provides innovative user experiences through virtual reality (VR), augmented reality (AR), and mixed reality (MR). By integrating digital twin simulations into XR devices, these technologies are utilized in various industrial fields. However, the prevalence of XR devices has increased the exposure to cybersecurity threats in ICS and digital twin environments. Because XR devices are connected to networks, the control and production data they process are at risk of being exposed to cyberattackers. Attackers can infiltrate XR devices through malicious code or hacking attacks to take control of the ICS or digital twin or paralyze the system. Therefore, this study emphasizes the cybersecurity threats in the ecosystem of XR devices used in ICSs and conducts research based on digital forensics. It identifies potentially sensitive data and artifacts in XR devices and proposes secure and reliable security response measures in the Industry 5.0 environment.
Automatic Generation and Evaluation of French-Style Chinese Modern Poetry
Authors: Zuo Li , Zhang Dengke , Zhao Yuhai , Wang Guoren
Published: July 2024

Literature has a strong cultural imprint and regional color, including poetry. Natural language itself is part of the poetry style. It is interesting to attempt to use one language to present poetry in another language style. Therefore, in this study, we propose a method to fine-tune a pre-trained model in a targeted manner to automatically generate French-style modern Chinese poetry and conduct a multi-faceted evaluation of the generated results. In a five-point scale based on human evaluation, judges assigned scores between 3.29 and 3.93 in seven dimensions, which reached 80.8–93.6% of the scores of the Chinese versions of real French poetry in these dimensions. In terms of the high-frequency poetic imagery, the consistency of the top 30–50 high-frequency poetic images between the poetry generated by the fine-tuned model and the French poetry reached 50–60%. In terms of the syntactic features, compared with the poems generated by the baseline model, the distribution frequencies of three special types of words that appear relatively frequently in French poetry increased by 12.95%, 15.81%, and 284.44% per 1000 Chinese characters in the poetry generated by the fine-tuned model. The human evaluation, poetic image distribution, and syntactic feature statistics show that the targeted fine-tuned model is helpful for the spread of language style. This fine-tuned model can successfully generate modern Chinese poetry in a French style.
An Improved Lightweight YOLOv5s-Based Method for Detecting Electric Bicycles in Elevators
Authors: Zhang Ziyuan , Yang Xianyu , Wu Chengyu
Published: July 2024

The increase in fire accidents caused by indoor charging of electric bicycles has raised concerns among people. Monitoring EBs in elevators is challenging, and the current object detection method is a variant of YOLOv5, which faces problems with calculating the load and detection rate. To address this issue, this paper presents an improved lightweight method based on YOLOv5s to detect EBs in elevators. This method introduces the MobileNetV2 module to achieve the lightweight performance of the model. By introducing the CBAM attention mechanism and the Bidirectional Feature Pyramid Network (BiFPN) into the YOLOv5s neck network, the detection precision is improved. In order to better verify that the model can be deployed at the edge of an elevator, this article deploys it using the Raspberry Pi 4B embedded development board and connects it to a buzzer for application verification. The experimental results demonstrate that the model parameters of EBs are reduced by 58.4%, the computational complexity is reduced by 50.6%, the detection precision reaches 95.9%, and real-time detection of electric vehicles in elevators is achieved.
Cost-Efficient Approximation for Magnitude of a Complex Signal
Authors: Wu Chih-Feng , Shiue Muh-Tian
Published: July 2024

In this paper, a signal model and a mathematical analysis of an efficient approach are derived to acquire the approximate magnitude of a complex signal by inducing a pre-biased or a pre-scaled factor in the design criteria. According to the deductive results, the pre-biased or pre-scaled factor can be 2∼3 dB, which is determined through its application. The numerical evaluations show that the mean square error (MSE) of the proposed efficient approach for the random signal is around −33 dB. Based on the design templates for the considered approaches, the occupied areas of the proposed type-1 and -2 approaches are merely 0.13 and 0.09 times the area of the direct-method, respectively. As a result, the proposed efficient approach is certainly a cost-efficient method for obtaining the approximate magnitude of a complex signal.
Inherently Decoupled Dc-Link Capacitor Voltage Control of Multilevel Neutral-Point-Clamped Converters
Authors: Garcia-Rojas Gabriel , Busquets-Monge Sergio , Griñó Robert , Campos-Salazar José M.
Published: July 2024

This letter derives and discusses the superiority of a simple dc-link capacitor voltage control configuration for multilevel neutral-point-clamped converters with any number of levels. The control involves n − 2 control loops regulating the difference between the voltage of neighbor capacitors. These control loops are inherently decoupled, i.e., they are independent and the control action of one loop does not affect the others. This method is proven to be equivalent to previously published approaches, with the added advantages of increased simplicity and scalability to a higher number of levels, all while imposing a lower computational burden. The good performance of such control is confirmed through simulations and experiments.
Software-Defined Virtual Private Network for SD-WAN
Authors: Fu Chunle , Wang Bailing , Liu Hongri , Wang Wei
Published: July 2024

Software-Defined Wide Area Networks (SD-WANs) are an emerging Software-Defined Network (SDN) technology to reinvent Wide Area Networks (WANs) for ubiquitous network interconnections in cloud computing, edge computing, and the Internet of Everything. The state-of-the-art overlay-based SD-WANs are simply conjunctions of Virtual Private Network (VPN) and SDN architecture to leverage the controllability and programmability of SDN, which are only applicable for specific platforms and do not comply with the extensibility of SDN. This paper motivates us to refactor traditional VPNs with SDN architecture by proposing an overlay-based SD-WAN solution named Software-Defined Virtual Private Network (SD-VPN). An SDN-based auto-constructed VPN model and its evaluating metrics are put forward to automatically construct overlay WANs by node placement and service orchestration of SD-VPN. Therefore, a joint placement algorithm of VPN nodes and algorithms for overlay WAN service loading and offloading are proposed for SD-VPN controllers. Finally, a three-layer SD-VPN system is implemented and deployed in actual network environments. Simulation experiments and system tests are conducted to prove the high-efficiency controllability, real-time programmability, and auto-constructed deployability of the proposed SD-VPN. Performance trade-off between SD-VPN control channels and data channels is evaluated, and SD-VPN controllers are proven to be extensible for other VPN protocols and advanced services.
Enhanced Remote Sensing Image Compression Method Using Large Network with Sparse Extracting Strategy
Authors: Li Hui , Pan Tianpeng , Zhang Lili
Published: July 2024

Deep neural networks based on hyper-encoders play a critical role in estimating prior distributions in remote sensing image compression issues. However, most of the existing encoding methods suffer from a problem on the hyper-encoding side, namely the mismatch of extraction ability with the encoder. This ability bias results in likelihood features that fail to extract sufficient information from latent representations. To solve this problem, the feature extraction capabilities of the hyper-encoder are enhanced to better estimate the Gaussian likelihood of the latent representation in end-to-end network optimization. Specifically, residual blocks and a parameter estimation module are incorporated to balance the performance of the encoder and the hyper-encoder. Furthermore, it is observed that the well-trained compression model tends to generate a fixed pattern of latent representations. Therefore, we incorporate a nonlocal cross-channel graph (NCG) on the backside of the encoder. Specifically, it aggregates features between similar latent representations in a graphical manner to further enhance the side information extraction capability of the hyper-encoder. Considering the computational cost, a sparse graph strategy is further developed to dynamically select the most relevant latent representations for aggregation operations, which greatly reduces the computational effort. The proposed algorithm is named nonlocal cross-channel efficient graph (NCEG). A long-dependent residual network is selected as the backbone, and a sparse attention module is inserted into the encoder/decoder side to enhance the perceptual field of the network. The experimental results on two evaluation datasets demonstrate that the proposed method achieves satisfactory results compared to other learning-based methods.