bluuebunny/crossref_metadata_2025 huggingface dataset:
7-O-Carboxylic Acid-Substituted 3-O-Alkyl Difluoroquercetin; An Aztreonam-Potentiating Agent Against Carbapenemase-Producing Pseudomonas aeruginosa Through Simultaneous Inhibition of Metallo-β-Lactamase and Efflux Pump
Authors: Lee Seongyeon , Lee Taegum , Kim Mi Kyoung , Ahn Joong Hoon , Jeong Seri , Park Ki-Ho , Chong Youhoon
Published: December 2024

Background/Objectives: Previously, we reported that 3-O-alkyl difluoroquercetins (di-F-Q) potentiates the antimicrobial activity of aztreonam (ATM) against metallo-β-lactamase (MBL)-producing P. aeruginosa through simultaneous inhibition of MBLs and efflux pumps. However, the ATM-potentiating activity of the 3-O-alkyl di-F-Q was observed only at high and potentially toxic concentrations (32 mg/L). Methods: As both MBLs and efflux pumps reside in the periplasm of Gram-negative bacteria, their inhibitors should accumulate in the periplasmic space. However, the outer membrane porins, the major entry pathway in Gram-negative bacteria, allow the passive diffusion of hydrophilic polar molecules across the outer membrane. Thus, we reasoned that the introduction of a polar substituent at 7-OH position of 3-O-alkyl di-F-Q would enhance its periplasmic concentration to result in potentiation of ATM at lower concentrations. Results: The title compound 5 exhibited inhibitory activity against NDM-1 as well as the efflux pump of P. aeruginosa, which resulted in synergistical potentiation of ATM. A combination of ATM (8 mg/L) and 5 (8 mg/L) inhibited 80% of the ATM-resistant CPPA, while ATM alone did not show any inhibition. In addition, only 4 mg/L of 5 was needed to reduce the MIC90 of ATM four-fold in ATM-resistant CPPA (n = 15). The time–kill data further supported the effectiveness of the combined treatment of ATM with 5, and the combination of ATM (1xMIC) with 8 mg/L of 5 showed bactericidal effects in every bacterial strain tested (PA-002, blaIMP, PA-003, blaVIM, PA-014, blaGES, and PA-017, blaNDM) by reducing the bacterial loads by 5.1 log10~8.9 log10. Conclusions: The title compound 5 exhibited inhibitory activity against NDM-1 as well as the efflux pump of P. aeruginosa, and the combined inhibitory activity resulted in synergistical potentiation of ATM. It should be noted that most CPPA isolates tested were sensitized to 8 mg/L of ATM upon combination with 4~8 mg/L of 5.
Artificial Intelligence and Machine Learning Applications to Pharmacokinetic Modeling and Dose Prediction of Antibiotics: A Scoping Review
Authors: Varela-Rey Iria , Bandín-Vilar Enrique , Toja-Camba Francisco José , Cañizo-Outeiriño Antonio , Cajade-Pascual Francisco , Ortega-Hortas Marcos , Mangas-Sanjuan Víctor , González-Barcia Miguel , Zarra-Ferro Irene , Mondelo-García Cristina , Fernández-Ferreiro Anxo
Published: December 2024

Background and Objectives: The use of artificial intelligence (AI) and, in particular, machine learning (ML) techniques is growing rapidly in the healthcare field. Their application in pharmacokinetics is of potential interest due to the need to relate enormous amounts of data and to the more efficient development of new predictive dose models. The development of pharmacokinetic models based on these techniques simplifies the process, reduces time, and allows more factors to be considered than with classical methods, and is therefore of special interest in the pharmacokinetic monitoring of antibiotics. This review aims to describe the studies that use AI, mainly oriented to ML techniques, for dose prediction and analyze their results in comparison with the results obtained by classical methods. Furthermore, in the review, the techniques employed and the metrics to evaluate the precision are described to improve the compression of the results. Methods: A systematic search was carried out in the EMBASE, OVID, and PubMed databases and the results obtained were analyzed in detail. Results: Of the 13 articles selected, 10 were published in the last three years. Vancomycin was monitored in seven and none of the studies were performed on new antibiotics. The most used techniques were XGBoost and neural networks. Comparisons were conducted in most cases against population pharmacokinetic models. Conclusions: AI techniques offer promising results. However, the diversity in terms of the statistical metrics used and the low power of some of the articles make the overall assessment difficult. For now, AI-based ML techniques should be used in addition to classical population pharmacokinetic models in clinical practice.
Multitarget Effects of Nrf2 Signalling in the Brain: Common and Specific Functions in Different Cell Types
Authors: Navarro Elisa , Esteras Noemí
Published: December 2024

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a crucial regulator of cellular defence mechanisms, essential for maintaining the brain’s health. Nrf2 supports mitochondrial function and protects against oxidative damage, which is vital for meeting the brain’s substantial energy and antioxidant demands. Furthermore, Nrf2 modulates glial inflammatory responses, playing a pivotal role in preventing neuroinflammation. This review explores these multifaceted functions of Nrf2 within the central nervous system, focusing on its activity across various brain cell types, including neurons, astrocytes, microglia, and oligodendrocytes. Due to the brain’s vulnerability to oxidative stress and metabolic challenges, Nrf2 is emerging as a key therapeutic target to enhance resilience against oxidative stress, inflammation, mitochondrial dysfunction, and demyelination, which are central to many neurodegenerative diseases.
Speech Emotion Recognition Using Multi-Scale Global–Local Representation Learning with Feature Pyramid Network
Authors: Wang Yuhua , Huang Jianxing , Zhao Zhengdao , Lan Haiyan , Zhang Xinjia
Published: December 2024

Speech emotion recognition (SER) is important in facilitating natural human–computer interactions. In speech sequence modeling, a vital challenge is to learn context-aware sentence expression and temporal dynamics of paralinguistic features to achieve unambiguous emotional semantic understanding. In previous studies, the SER method based on the single-scale cascade feature extraction module could not effectively preserve the temporal structure of speech signals in the deep layer, downgrading the sequence modeling performance. To address these challenges, this paper proposes a novel multi-scale feature pyramid network. The enhanced multi-scale convolutional neural networks (MSCNNs) significantly improve the ability to extract multi-granular emotional features. Experimental results on the IEMOCAP corpus demonstrate the effectiveness of the proposed approach, achieving a weighted accuracy (WA) of 71.79% and an unweighted accuracy (UA) of 73.39%. Furthermore, on the RAVDESS dataset, the model achieves an unweighted accuracy (UA) of 86.5%. These results validate the system’s performance and highlight its competitive advantage.
Determining Effective Color Combinations for Enhanced Legibility Presented on Print and Digital Formats
Authors: Buljat Petra , Kovačević Dorotea , Kulčar Rahela
Published: December 2024

This study explores the impact of different color hue combinations and medium types (print and digital) on reading performance and comprehension. The purpose is to understand how these factors may influence text legibility and to offer practical insights for designers on optimizing visual design in presenting promotional content. Fifty-two participants read texts with various color palettes presented on both print and digital formats. The following color combinations were used in the experiment: achromatic (black on gray), achromatic–chromatic (black on green), and chromatic (purple on green). Reading time and comprehension score were measured to identify any significant differences between these conditions. The results show that the color combinations significantly affected reading time, regardless of the medium type. However, neither color nor medium had a significant effect on text comprehension. The main outcome is that the combination of achromatic text on a chromatic background appeared to be the most effective combination for enhancing the legibility of promotional text. Our findings suggest that graphic designers can choose particular color combinations to optimize reading speed without worrying about negative effects on the comprehension of the texts used in promotional materials across various mediums.
The Effects of the Guide Cone on the Flow Field and Key Classification Performance of an Industrial-Scale Micron Air Classifier
Authors: Ho Nang Xuan , Dinh Hoi Thi , Dau Nhu The
Published: December 2024

In this study, the effects of the structural parameters (SPs) of the guide cone, such as the surface inclination and the material recirculation gap size, on the two-phase flow field and classification performance of a real-sized industrial-scale micron air classifier were investigated. This was achieved using the two-way coupling of a computational fluid dynamics–discrete phase model in ANSYS 2022 R2, with the assistance of a high-performance system (HPC). The objective of this study was to determine the optimal SPs of the guide cone so as to achieve the best classification efficiency and satisfy the required particle size distribution curve, named the know-how curve (KHC), for the particle size range (0 ÷ 400 μm) used in producing quartz-based artificial stone. The bottom diameter (d) of the guide cone (CHL) was altered while keeping the outer diameter of the feeding tube unchanged. As a consequence, the material recirculation gap size was changed, and the size, shape, position, and rotational direction of the vortices formed in the secondary classification space and classification chamber were also changed. These vortices significantly affected the classification performance. Specifically, the classifiers with different guide cone structures, named CHL1, CHL2, CHL3, and CHL4, yielded Newton efficiencies of 75.06%, 87.26%, 95.5%, and 94.02%, respectively. According to the simulation results, the best guide cone structure is recommended to satisfy objectives such as (i) the highest classification efficiency, the smallest cut size, and the smallest classification sharpness index and (ii) those in (i) under the constraint of the required KHC.
Post-Hoc Categorization Based on Explainable AI and Reinforcement Learning for Improved Intrusion Detection
Authors: Larriva-Novo Xavier , Pérez Miguel Luis , Villagra Victor A. , Álvarez-Campana Manuel , Sanchez-Zas Carmen , Jover Óscar
Published: December 2024

The massive usage of Internet services nowadays has led to a drastic increase in cyberattacks, including sophisticated techniques, so that Intrusion Detection Systems (IDSs) need to use AP technologies to enhance their effectiveness. However, this has resulted in a lack of interpretability and explainability from different applications that use AI predictions, making it hard to understand by cybersecurity operators why decisions were made. To address this, the concept of Explainable AI (XAI) has been introduced to make the AI’s decisions more understandable at both global and local levels. This not only boosts confidence in the AI but also aids in identifying different attributes commonly used in cyberattacks for the exploitation of flaws or vulnerabilities. This study proposes two developments: first, the creation and evaluation of machine learning models for an IDS with the objective to use Reinforcement Learning (RL) to classify malicious network traffic, and second, the development of a methodology to extract multi-level explanations from the RL model to identify, detect, and understand how different attributes affect uncertain types of attack categories.
Comparison of Physical, Sensorial, and Microstructural Properties to Assess the Similarity Between Plant- and Animal-Based Meat Products
Authors: Abdullah Fouad Ali Abdullah , Pospiech Matej , Dordevic Dani , Kabourkova Eliska
Published: December 2024

The aim of this study was to compare the physical, sensorial, and microstructural properties of selected meat products with their plant-based alternatives to assess how closely the alternatives mimic the original products. Six meat analogue products, including Frankfurter sausage (SuA), steak (StA), Hungarian sausage (KA), minced meat (MA), salami (SaA), and burger (BA), were compared with their corresponding meat products (SuM, StM, KM, MM, SaM, and BM, respectively). The study measured colour indicators, texture parameters, sensory attributes, and microstructural properties. The redness values (a*) of the external surfaces of SuM and KM, as well as the hardness of MM, were similar to those of their alternative products, with no statistically significant differences (p > 0.05). Sensory evaluation revealed similar ratings for two attributes: product similarity and overall appearance. However, significant differences were found in the descriptors for animal character and meat taste.
Multivariantism of Auditory Perceptions as a Significant Element of the Auditory Scene Analysis Concept
Authors: Rosiński Adam
Published: December 2024

The concept of auditory scene analysis, popularized in scientific experiments by A. S. Bregman, the primary architect of the perceptual streaming theory, and his research team, along with more recent analyses by subsequent researchers, highlights a specific scientific gap that has not been thoroughly explored in previous studies. This article seeks to expand on this concept by introducing the author’s observation of the multivariant nature of auditory perception. This notion suggests that listeners focusing on different components of an auditory image (such as a musical piece) may perceive the same sounds but interpret them as distinct sound structures. Notably, even the same listener may perceive various structures (different mental figures) when re-listening to the same piece, depending on which musical elements they focus on. The thesis of multivariantism was examined and confirmed through the analysis of selected classical music pieces, providing concrete evidence of different interpretations of the same sound stimuli. To enhance clarity and understanding, the introduction to multivariantism was supplemented with graphic examples from the visual arts, which were then related to musical art through score excerpts from the works of composers such as C. Saint-Saëns, F. Liszt, and F. Mendelssohn Bartholdy.
Random Traveling Wave Equations for the Heisenberg Ferromagnetic Spin Chain Model and Their Optical Stochastic Solutions in a Ferromagnetic Materials
Authors: Mohammed Wael W. , Gassem Fakhr , Sidaoui Rabeb
Published: December 2024

In this paper, we investigate the stochastic Heisenberg ferromagnetic equation (SHFE) derived by a multiplicative Wiener process. We use a suitable transformation to change the SHF equation into another Heisenberg ferromagnetic equation with random variable coefficients (HFE-RVCs). We employ the mapping approach to obtain novel rational, trigonometric, elliptic and hyperbolic function solutions for HFE-RVCs. Following that, we can attain the solutions of the SHFE. For the first time in the Heisenberg ferromagnetic equation, we postulate that the solution to the wave equation is stochastic, whereas all previous investigations supposed that it was deterministic. Moreover, we give various visual representations to demonstrate the impact of the multiplicative Wiener process on the exact solutions to the stochastic Heisenberg ferromagnetic equation.
Akkermansia muciniphila- and Pathogenic Bacteria-Derived Endotoxins Differently Regulate Human Dendritic Cell Generation and γδ T Lymphocyte Activation
Authors: Fertitta Veronica , Varano Barbara , Del Cornò Manuela , Fortini Paola , Aureli Anna , Conti Lucia
Published: December 2024

Lipopolysaccharide (LPS) is a potent endotoxin released at high concentrations in acute infections, causing massive host inflammatory response. Accumulating evidence indicates that dysbiosis-associated chronic low levels of circulating LPS can sustain a prolonged sterile low-grade inflammation that increases the risk of several non-communicable diseases. Interventions aimed at increasing the abundance of beneficial/probiotic bacteria, including Akkermansia muciniphila, result in reduced inflammation, favoring metabolic and immune health. Immunosuppression is a common feature in conditions of chronic inflammation, and dendritic cells (DCs) represent key targets given their ability to shift the balance toward immunity or tolerance. In this study, the effects of low concentrations of LPS from pathogenic (Escherichia coli and Salmonella enterica) and probiotic (Akkermansia muciniphila) bacterial species on human DC generation and functions were compared. We report that monocyte precursor priming with Escherichia coli and Salmonella enterica LPS forces the differentiation of PD-L1-expressing DCs, releasing high levels of IL-6 and IL-10, and impairs their capacity to drive full TCR-Vδ2 T cell activation. Conversely, comparable concentrations of Akkermansia muciniphila promoted the generation of DCs with preserved activating potential and immunostimulatory properties. These results shed light on potential mechanisms underlying the impact of low endotoxemia on disease risk and pathogenesis, and increase our understanding of the immunomodulatory effects of Akkermansia muciniphila.
APOL1 Modulates Renin–Angiotensin System
Authors: Kumar Vinod , Kaur Prabhjot , Ayasolla Kameshwar , Jha Alok , Wiqas Amen , Vashistha Himanshu , Saleem Moin A. , Popik Waldemar , Malhotra Ashwani , Gebeshuber Christoph A. , Skorecki Karl , Singhal Pravin C.
Published: December 2024

Patients carrying APOL1 risk alleles (G1 and G2) have a higher risk of developing Focal Segmental Glomerulosclerosis (FSGS); we hypothesized that escalated levels of miR193a contribute to kidney injury by activating renin–angiotensin system (RAS) in the APOL1 milieus. Differentiated podocytes (DPDs) stably expressing vector (V/DPD), G0 (G0/DPDs), G1 (G1/DPDs), and G2 (G2/DPDs) were evaluated for renin, Vitamin D receptor (VDR), and podocyte molecular markers (PDMMs, including WT1, Podocalyxin, Nephrin, and Cluster of Differentiation [CD]2 associated protein [AP]). G0/DPDs displayed attenuated renin but an enhanced expression of VDR and Wilms Tumor [WT]1, including other PDMMs; in contrast, G1/DPDs and G2/DPDs exhibited enhanced expression of renin but decreased expression of VDR and WT1, as well as other PDMMs (at both the protein and mRNA levels). G1/DPDs and G2/DPDs also showed increased mRNA expression for Angiotensinogen and Angiotensin II Type 1 (AT1R) and 2 (AT2R) receptors. Protein concentrations of Brain Acid-Soluble Protein [BASP]1, Enhancer of Zeste Homolog [EZH]2, Histone Deacetylase [HDAC]1, and Histone 3 Lysine27 trimethylated [H3K27me3] in WT1-IP (immunoprecipitated proteins with WT1 antibody) fractions were significantly higher in G0/DPDs vs. G1/DPD and G2/DPDs. Moreover, DPD-silenced BASP1 displayed an increased expression of renin. Notably, VDR agonist-treated DPDs showed escalated levels of VDR and a higher expression of PDMMs, but an attenuated expression of renin. Human Embryonic Kidney (HEK) cells transfected with increasing APOL1(G0) plasmid concentrations showed a corresponding reduction in renin mRNA expression. Bioinformatics studies predicted the miR193a target sites in the VDR 3′UTR (untranslated region), and the luciferase assay confirmed the predicted sites. As expected, podocytes transfected with miR193a plasmid displayed a reduced VDR and an enhanced expression of renin. Renal cortical section immunolabeling in miR193a transgenic (Tr) mice showed renin-expressing podocytes. Kidney tissue extracts from miR193aTr mice also showed reduced expression of VDR and PDMMs, but enhanced expression of Renin. Blood Ang II levels were higher in miR193aTr, APOLG1, and APOL1G1/G2 mice when compared to control mice. Based on these findings, miR193a regulates the activation of RAS and podocyte molecular markers through modulation of VDR and WT1 in the APOL1 milieu.
The Role and Mechanism of Metformin in the Treatment of Nervous System Diseases
Authors: Li Hui , Liu Ruhui , Liu Junyan , Qu Yi
Published: December 2024

Nervous system diseases represent a significant global burden, affecting approximately 16% of the world’s population and leading to disability and mortality. These conditions, encompassing both central nervous system (CNS) and peripheral nervous system (PNS) disorders, have substantial social and economic impacts. Metformin, a guanidine derivative derived from a plant source, exhibits therapeutic properties in various health conditions such as cancer, aging, immune-related disorders, polycystic ovary syndrome, cardiovascular ailments, and more. Recent studies highlight metformin’s ability to cross the blood–brain barrier, stimulate neurogenesis, and provide beneficial effects in specific neurological disorders through diverse mechanisms. This review discusses the advancements in research on metformin’s role and mechanisms in treating neurological disorders within both the central and peripheral nervous systems, aiming to facilitate further investigation, utilization, and clinical application of metformin in neurology.
Differences in Perceived Stress, Subjective Well-Being, and Psychosocial Variables by Game Use Type
Authors: Jeong Goo-Churl , Kim Kwanhyeong , Kim Bee
Published: December 2024

This study examined the differences in perceived stress, subjective well-being, psychosocial variables, and differences in parents’ parenting styles according to game use type among Korean adults. The study involved 300 participants in their 20s and 30s, a demographic typically associated with frequent gaming. Data were collected through an online survey company, and analyses were conducted using SPSS 25.0, including correlation, cluster, ANOVA, and correspondence analyses. The results showed that the general and adaptive game use groups had significantly lower levels of perceived stress than the maladaptive and risky game use groups. Additionally, the adaptive game use group exhibited significantly higher subjective well-being than the maladaptive game use group. In terms of psychosocial characteristics, except for the general game use group, none of the other groups considered online gaming as addictive. Parenting styles showed significant differences in relation to game use in adulthood. Notably, democratic parenting styles were associated with the general and adaptive game use groups, whereas neglectful parenting styles were linked to the risky game use group. These findings suggest that the risky game use group is as vulnerable to stress as the maladaptive game use group, emphasizing the need for targeted screening and social attention for the risky game use group.
Sequential Endoluminal Doxorubicin and Gemcitabine Alternating Weekly with Sequential Mitomycin and Docetaxel for Recurrent Non-Muscle Invasive Urothelial Carcinoma
Authors: McElree Ian M. , Packiam Vignesh T. , Steinberg Ryan L. , Hougen Helen Y. , Abou Chakra Mohamad , Mott Sarah L. , O’Donnell Michael A.
Published: December 2024

Background: After first-line treatment failure, patients with non-muscle invasive urothelial carcinoma (NMIUC) are recommended to undergo radical cystectomy. However, those unable to pursue radical surgery or desiring bladder preservation require effective salvage therapies. Multi-agent treatment regimens are particularly useful for targeting the complex resistance mechanisms of recurrent UC. Herein, we report a regimen of sequential doxorubicin and gemcitabine alternating weekly with sequential docetaxel and mitomycin (Quad Chemo) for patients with recurrent high-risk NMIUC. Materials and Methods: We retrospectively identified all patients sequentially treated with 50 mg of doxorubicin followed by 1000 mg of gemcitabine alternating weekly with sequential 37.5 mg of docetaxel followed by 40 mg mitomycin-C between 2007–2024. Induction consisted of 8 weekly treatments, and, if disease-free, patients were initiated on monthly maintenance treatments for 2 years. Results: In total, 29 patients (39 treated units; 26 lower urinary tract, 13 upper urinary tract) with high-grade NMIUC were included in the final analysis. The cohort had high-risk features with a median of three prior induction therapies and with 38 (97%) units presented with either biopsy-proven CIS or presumed CIS in the context of high-grade urine cytology in the absence of tumorous lesions. There were 26 recurrences during follow-up, 17 in the lower tract and 9 in the upper tract. Among all of the treated units, the complete response rate was 80%, and 1- and 2-year recurrence-free survival was 60% and 43%, respectively. In total, 10 patients experienced disease progression yielding a 5-year progression-free survival of 57%. Five patients ultimately died due to bladder cancer yielding a 5-year cancer-specific survival of 83%. A total of 19 (66%) patients reported side effects during treatment, and 7 (24%) stopped treatment secondary to side effects. Conclusions: In a high-risk heavily pre-treated cohort, Quad Chemo rescued a significant portion of patients with recurrent NMIUC from disease relapse. However, progression events were considerable in the long term. Further prospective evaluation of this treatment regimen is warranted.
Methyl Mercaptan Removal from Methane Using Metal-Oxides and Aluminosilicate Materials
Authors: Martinez-Zuniga Gerson , Antwi Samuel , Soni-Castro Percival , Olayiwola Olatunji , Chuprin Maksym , Holmes William E. , Buchireddy Prashanth , Gang Daniel , Revellame Emmanuel , Zappi Mark E. , Hernandez Rafael
Published: December 2024

Methyl mercaptan is a sulfur-based chemical found as a co-product in produced natural gas and it causes corrosion in pipelines, storage tanks, catalysts, and solid adsorption beds. To improve the quality of methane produced, researchers have studied the use of metal oxides and aluminum silicates as catalysts for removing mercaptan. However, there are restrictive limitations on the efficiency of metal oxides or aluminum silicates as adsorbents for this application. Therefore, this study investigated the performance of these materials in a fixed-bed reactor with simulated natural gas streams under various operating conditions. The testing procedure includes a detailed assessment of the adsorbent/catalysts by several techniques, such as Braeuer–Emmett–Teller (BET), Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Spectrometry (EDS), and X-ray Photoelectron Spectroscopy. The results revealed that metal oxides such as copper, manganese, and zinc performed well in methyl mercaptan elimination. The addition of manganese, copper, and zinc oxides to the aluminum silicate surface resulted in a sulfur capacity of 1226 mg S/g of catalyst. These findings provide critical insights for the development of catalysts that combine metal oxides to increase adsorption while reducing the production of byproducts like dimethyl sulfide (DMS) and dimethyl disulfide (DMDS) during methyl mercaptan removal.
Usability and Safety of the ATLAS 2030 Robotic Gait Device in Children with Cerebral Palsy and Spinal Muscular Atrophy
Authors: Cumplido-Trasmonte Carlos , Barquín-Santos Eva , Aneiros-Tarancón Fernando , Plaza-Flores Alberto , Espinosa-García Sandra , Fernández Roemi , García-Armada Elena
Published: December 2024

Purpose: the purpose of this study was to evaluate the safety and usability of the ATLAS 2030 in children with Cerebral Palsy (CP) and Spinal Muscular Atrophy (SMA). Materials and Methods: the sample consisted of six children, three with CP and three with SMA, who received eight sessions of robot-assisted gait therapy. Safety was measured by the presence of adverse events. Usability was measured by spatiotemporal parameters, the Six-Minute Walking Test (6MWT), and the time needed for donning and doffing, as well as satisfaction questionnaires administered to therapists and patients. Results: no serious adverse events were reported. The average cadence and number of steps per session increased throughout sessions, as well as the distance covered in the 6MWT, both in participants with CP and SMA. The mean donning time at the end of the study was 4.6 ± 1.3 min, and only one therapist was necessary to carry out all of the sessions. Satisfaction was considered high by both children and therapists. Conclusions: the ATLAS 2030 was shown to be safe for children with CP and SMA. The usability of the device was good, since a progression in the spatiotemporal parameters was observed throughout the sessions, and patient and therapist satisfaction were high.
The Relationship of Creativity and Motor Creativity with Physical Activity and Motor Fitness in a Gender Perspective Among 8–9-Year-Old Children
Authors: Khorkova Maryna , Bojkowski Łukasz , Korcz Agata , Łopatka Marlena , Adamczak Dagny , Krzysztoszek Jana , Bronikowski Michał
Published: December 2024

Background: In this study, we aimed to determine the presence of any potential gender differences and relationships in terms of creativity, physical activity (PA), motor fitness, and motor creativity in children aged 8–9 years. Methods: The study included 195 primary school children (92 girls and 103 boys) aged 8–9 years old from grade 2. To determine creativity, the Test for Creative Thinking-Drawing Production was used, while motor creativity was assessed using Torrance’s ‘Thinking Creatively in Action and Movement’ test. Motor fitness was assessed with the selected items from the Eurofit battery and Piórkowski tests. The level of moderate-to-vigorous PA was determined with the Physical Activity Screening Measure. The Mann–Whitney U test was employed for in-between group comparison and Spearman’s correlation to determine relationships between the variables. Results: The results of the research showed the presence of differences in motor fitness between boys and girls, but no differences in PA, creativity, as well as motor creativity between genders. Moreover, it was found there was no association between PA and motor fitness and creativity or motor creativity in either boys or girls at this age. Conclusions: Thus, it can be assumed that to develop creativity through PA in children aged 8–9 years, it might be necessary to create an appropriate environment and strategy that will strengthen, inspire, and promote children’s creativity through movement. Having established that there is no difference in creativity between genders at this age, it was pointed out that it is necessary to look for teaching methods that would effectively awaken this ability in a co-educational setting.
Factors Contributing to Effective Climate Change Adaptation Projects in Water Management: Implications from the Developing Countries
Authors: Shiga Yuki , Shaw Rajib
Published: December 2024

The adaptation finance gap is widening as the impact of climate change grows more disruptive around the globe. Although progress in adaptation planning and implementation has been observed across all sectors and regions, this trend of a widening resource gap calls for more ‘effective’ climate adaptation projects. Therefore, the purpose of this paper is to provide a comprehensive analysis to explore potential factors contributing to the effectiveness of climate change projects in developing countries with a particular focus on water management financed under multilateral funds that have been implemented on the ground, completed and documented. Thirty-five projects from the multilateral funds were collected and analyzed for this purpose. Project evaluation documents have been studied, and the effectiveness rating at completion has been assessed against possible contributing factors through regression analysis. The results showed that the factors contributing to project effectiveness converge around several elements: (i) capacity building and education (|r| > 0.3); (ii) healthy and resilient livelihoods (|r| > 0.2); and (iii) climate data and a robust theory of change (stated by >30% of projects). The implications from this study can provide a useful quantitative ground for discussion around the effective adaptation projects in water management as well as inform relevant international processes such as the Global Goal on Adaptation and global stocktake.
Evolution from Microstructure to Macroscopic Properties: Zirconium Alloys Under Irradiation
Authors: Liu Shuiqing , Liang Jiahao , Zhang Yang , Duan Shuyong , Han Xu
Published: December 2024

The application of zirconium alloy in nuclear reactors is supported by its excellent performance and corrosion resistance, but under the action of high-energy neutrons, the atoms in the lattice will change, resulting in the accumulation of lattice defects and the evolution of the microstructure, which not only affect the strength and shape of the material but also affect the tensile resistance, impact resistance and other mechanical properties of the zirconium alloy. Common industrial processes for the preparation of nuclear-grade zirconium sponges are discussed, the advantages, disadvantages and applications of the main production processes are summarised, and the characteristics of irradiation-induced loops are comprehensively examined, encompassing their formation mechanisms, interactions with dislocations, and the range of potential microscopic defects during irradiation. In addition, the phenomena of irradiation growth and irradiation creep and their relationship with microstructure evolution are also discussed. The effect of oxidative corrosion under irradiation has also been explored. Specifically, irradiation can aggravate the corrosion process of zirconium alloy and lead to the thickening of the corrosion layer, but the specific degree of influence is closely related to the working temperature and irradiation conditions. The comprehensive study of zirconium alloy under irradiation conditions aims to provide a scientific basis for the future design of long-life and high-reliability nuclear reactor materials and support the sustainable development of the nuclear industry.
Correction: Adardour et al. Crystal Structure, DFT Calculation, and Hirshfeld Surface Analysis of the 1-(Cyclohex-1-en-1-yl)-3-(prop-2-yn-1-yl)-1,3-dihydro-2H-benzimidazol-2-one. Crystals 2023, 13, 1661
Authors: Adardour Mohamed , Ait Lahcen Marouane , Hdoufane Ismail , Alanazi Mohammed M. , Loughzail Mohamed , Bouzidi Mousser Henia , Fleutot Solenne , François Michel , Cherqaoui Driss , Baouid Abdesselam
Published: December 2024

In the published work [...]
First-Line (1L) Treatment Decision Patterns and Survival of Hormone Receptor (HR)-Positive/HER2-Negative Advanced Breast Cancer (ABC) Patients in a Latin American (LATAM) Public Institution
Authors: Valencia Guillermo , Rioja Patricia , Chirito Miguel , Peralta Olenka , Sánchez Jorge , Rabanal Connie , Mantilla Raúl , Morante Zaida , Fuentes Hugo , Castaneda Carlos , Vidaurre Tatiana , Pacheco Cristian , Neciosup Silvia , Gomez Henry L.
Published: December 2024

Advanced breast cancer is an incurable disease, with a median overall survival of 3 years, including in countries without access problems. Although chemotherapy is reserved in some cases, it is still used in many countries as a first-line therapy. The aim of our study is to evaluate the first-line treatment choices and the factors that influence therapeutic decisions. A retrospective analysis was conducted of hormone receptor (+)/HER2 (−) advanced breast cancer patients classified into three groups according to the first-line and second-line treatment received: endocrine therapy–chemotherapy, endocrine therapy–endocrine therapy and chemotherapy–endocrine therapy. Additionally, we explored the overall survival of sequencing therapy groups. First-line chemotherapy was chosen in 34% of patients. Also, around 60% of our patients met the “aggressive disease” criteria from the RIGHT Choice trial, justifying the use of chemotherapy in a population with poor prognosis. Furthermore, de novo and progressive disease were prognostic factors that influenced the use of chemotherapy as a first-line treatment. Regarding overall survival, the sequencing treatment groups in this trial saw an increase in survival compared with patients of the MONALEESA trials (endocrine therapy alone arms). No significant differences in progression-free survival or overall survival were found in the treatment sequencing groups. There was a higher use of chemotherapy as a first-line therapy, with de novo and “aggressive disease” criteria being the main factors to influence the decision.
Long-Term Outcomes of Patients with Pre-Existing Essential Tremor After SARS-CoV-2 Infection
Authors: Pakan Rachel , Hadidchi Roham , Al-Ani Yousef , Piskun Hannah , Duong Katie S. , Henry Sonya , Wang Stephen , Maurer Carine W. , Duong Tim Q.
Published: December 2024

Background/Objectives: Although COVID-19 has been linked to worse outcomes in patients with neurological disorders, its impact on those with essential tremor (ET) remains unclear. To investigate clinical outcomes of ET patients with and without COVID-19 three and a half years post-pandemic. Methods: 1074 ET patients were evaluated in this retrospective study in the Montefiore Health System from January 2016 to July 2023. Comparisons between ET patients with and without a positive SARS-CoV-2 polymerase chain reaction test were made. Outcomes included post-index date major adverse cardiovascular events (MACEs), new-onset sleep disturbances, fatigue, dyspnea, first-time fall, new-onset anxiety, new-onset depression, headache, new-onset imbalance, new-onset mild cognitive impairment, and all-cause mortality, adjusted hazard ratios (aHR) adjusting for covariates were calculated. Results: ET patients with COVID-19 had higher prevalence of pre-existing type-2 diabetes, depression, and anxiety compared to ET patients without COVID-19. COVID-19 was significantly associated with higher risk of MACEs, (aHR = 2.39 [1.49, 3.82]), new-onset sleep disturbance, (aHR = 2.12 [1.44, 3.13]), fatigue, (aHR = 1.83 [1.27, 2.65]), dyspnea, (aHR = 1.98 [1.40, 2.80]), first-time fall, (aHR = 4.76 [2.24, 10.14]), new-onset anxiety, (aHR = 3.66 [2.02, 6.64]), and new-onset depression, (aHR = 2.38 [1.20, 4.70]). COVID-19 was not associated with all-cause mortality. Conclusions: In patients with ET, COVID-19 significantly increases the risk of several long-term adverse health outcomes, but not mortality.
Cancer Risk in Thyroid Nodules: An Analysis of Over 1000 Consecutive FNA Biopsies Performed in a Single Canadian Institution
Authors: Smit Elsabe J. , Samadi Sana , Wilson Mitchell P. , Low Gavin
Published: December 2024

Objective: To determine the cancer risk in thyroid nodules using ACR TI-RADS. Methods: A retrospective analysis of all thyroid biopsies was performed over a 3-year period (2021 to 2023). Variables including gender, age, history of thyroid cancer or neck irradiation, nodule size and location, TR level, and sonographic features such as punctate echogenic foci (PEF), a very hypoechoic appearance, taller-than-wide shape, and suspected extrathyroidal extension were analyzed. Results: A total of 1140 nodules were assessed in 993 patients, including 740 females (74.5%) and 253 males (25.5%). The mean patient age was 57.1 ± 15.4 years. Variables significantly associated with nodule malignancy included (1) younger age, (2) a prior history of thyroid cancer or neck irradiation, (3) a higher TR level, (4) a taller-than-wide shape in nodules <1 cm, (5) PEF, (6) a very hypoechoic appearance, and (5) suspected extrathyroidal extension (p < 0.05). Gender, nodule location and size were not associated with a higher cancer risk (p > 0.05). Malignancy was found in 40.7% of TR5, 4.8% of TR4, 0.3% of TR3, and 0% of TR1 and 2 nodules. The odds ratios (ORs) for cancer were as follows: TR4 or 5, OR = 19; PEF, OR = 11; a very hypoechoic appearance, OR = 13.3; and suspected extrathyroidal extension, OR = 27.2 (p < 0.01). Conclusions: Higher TR levels, PEF, a very hypoechoic appearance, and suspected extrathyroidal extension are important features for predicting cancer risk. These findings affirm the effectiveness of ACR TI-RADS in nodule risk stratification.
A Neural Network Based on Supervised Multi-View Contrastive Learning and Two-Stage Feature Fusion for Face Anti-Spoofing
Authors: Li Jin , Sun Wenyun
Published: December 2024

As one of the most crucial parts of face detection, the accuracy and the generalization of face anti-spoofing are particularly important. Therefore, it is necessary to propose a multi-branch network to improve the accuracy and generalization of the detection of unknown spoofing attacks. These branches consist of several frequency map encoders and one depth map encoder. These encoders are trained together. It leverages multiple frequency features and generates depth map features. High-frequency edge texture is beneficial for capturing moiré patterns, while low-frequency features are sensitive to color distortion. Depth maps are more discriminative than RGB images at the visual level and serve as useful auxiliary information. Supervised Multi-view Contrastive Learning enhances multi-view feature learning. Moreover, a two-stage feature fusion method effectively integrates multi-branch features. Experiments on four public datasets, namely CASIA-FASD, Replay–Attack, MSU-MFSD, and OULU-NPU, demonstrate model effectiveness. The average Half Total Error Rate (HTER) of our model is 4% (25% to 21%) lower than the Adversarial Domain Adaptation method in inter-set evaluations.
Design and Analysis of a Direct Current–Based Ice Melting System for an Overhead Contact System in Electrified Railways
Authors: Huang Guosheng , Wu Mingli , Cao Guotao , Fu Songping , Pei Xiaojuan , Wu Liran , Liu Qiujiang
Published: December 2024

In recent years, extremely low-temperature weather conditions have resulted in the formation of ice on the contact network of electrified railways, significantly affecting the security of these systems. To address the issue of icing on the overhead contact system, this paper proposes a direct current–based ice melting system. This paper outlines the topological structure of the contact network ice melting system and examines its operational principles. A finite element model was established to investigate the characteristics of the ice melting process on the contact line, and a quantitative analysis was conducted to assess the impact of four critical variables: temperature, ice thickness, direct current, and conductor configuration. Ultimately, a simulation model of the contact line ice melting system for the traction power supply system was developed, and the output/input characteristics of the ice melting system were analyzed to validate its feasibility.
Siamese-RCNet: Defect Detection Model for Complex Textured Surfaces with Few Annotations
Authors: Guo Dandan , Zhang Chunying , Yang Guanghui , Xue Tao , Ma Jiang , Liu Lu , Ren Jing
Published: December 2024

The surface texture of objects in industrial scenes is complex and diverse, and the characteristics of surface defects are often very similar to the surrounding environment and texture background, so it is difficult to accurately detect the defect area. However, when deep learning technology is used to detect complex texture surface defects, the detection accuracy is not high, due to the lack of large-scale pixel-level label datasets. Therefore, a defect detection model Siamese-RCNet for complex texture surface with a small number of annotations is proposed. The Cascade R-CNN target detection network is used as the basic framework, making full use of unlabeled image feature information, and fusing the nonlinear relationship learning ability of Siamese network and the feature extraction ability of the Res2Net backbone network to more effectively capture the subtle features of complex texture surface defects. The image difference measurement method is used to calculate the similarity between different images, and the attention module is constructed to weight the feature map of the feature extraction pyramid, so that the model can focus more on the defect area and suppress the influence of complex background texture area, so as to improve the accuracy of detection. To verify the effectiveness of the Siamese-RCNet model, a series of experiments were carried out on the DAGM2007 dataset of weakly supervised learning texture surface defects for industrial optical inspection. The results show that even if only 20% of the labeled datasets are used, the mAP@0.5 of the Siamese-RCNet model can still reach 96.9%. Compared with the traditional Cascade R-CNN and Faster R-CNN target detection networks, the Siamese-RCNet model has high accuracy, can reduce the workload of manual labeling, and provides strong support for practical applications.
Artificial Intelligence-Enabled Metaverse for Sustainable Smart Cities: Technologies, Applications, Challenges, and Future Directions
Authors: Lifelo Zita , Ding Jianguo , Ning Huansheng , Qurat-Ul-Ain  , Dhelim Sahraoui
Published: December 2024

Rapid urbanisation has intensified the need for sustainable solutions to address challenges in urban infrastructure, climate change, and resource constraints. This study reveals that Artificial Intelligence (AI)-enabled metaverse offers transformative potential for developing sustainable smart cities. AI techniques, such as machine learning, deep learning, generative AI (GAI), and large language models (LLMs), enhance the metaverse’s capabilities in data analysis, urban decision making, and personalised user experiences. The study further examines how these advanced AI models facilitate key metaverse technologies such as big data analytics, natural language processing (NLP), computer vision, digital twins, Internet of Things (IoT), Edge AI, and 5G/6G networks. Applications across various smart city domains—environment, mobility, energy, health, governance, and economy, and real-world use cases of virtual cities like Singapore, Seoul, and Lisbon are presented, demonstrating AI’s effectiveness in the metaverse for smart cities. However, AI-enabled metaverse in smart cities presents challenges related to data acquisition and management, privacy, security, interoperability, scalability, and ethical considerations. These challenges’ societal and technological implications are discussed, highlighting the need for robust data governance frameworks and AI ethics guidelines. Future directions emphasise advancing AI model architectures and algorithms, enhancing privacy and security measures, promoting ethical AI practices, addressing performance measures, and fostering stakeholder collaboration. By addressing these challenges, the full potential of AI-enabled metaverse can be harnessed to enhance sustainability, adaptability, and livability in smart cities.