bluuebunny/crossref_metadata_2025 huggingface dataset:
MCIDN: Deblurring Network for Metal Corrosion Images
Authors: Wang Jiaxiang , Wan Meng , Zhang Pufen , Chang Sijie , Du Hao , Shi Peng , Yu Hongying , Sun Dongbai , Wang Jue , Wang Yangang
Published: December 2024

The analysis of corrosion images is crucial in materials science, where acquiring clear images is fundamental for subsequent analysis. The goal of deblurring metal corrosion images is to reconstruct clear images from degraded ones. To the best of our knowledge, this study introduces the first paired blurry-sharp image dataset specifically designed for the metal corrosion domain, filling a critical gap in the existing research. This innovative approach effectively addresses the unique challenges associated with deblurring metal corrosion images. We propose a novel metal corrosion images deblurring network (MCIDN) that employs a dual-domain attention mechanism, integrating both spatial and frequency domains to enhance image clarity. This innovative approach effectively addresses the unique challenges associated with deblurring metal corrosion images. While self-attention is widely used in visual tasks, its quadratic complexity often leads to high computational costs. To address this issue, we introduce a new spatial channel attention module (SCAM) that employs dynamic group convolutions to achieve self-attention, effectively integrating information from local regions and enhancing representation learning capabilities. Recognizing the critical role of frequency components in image restoration, we develop a frequency channel attention module (FCAM) that selectively focuses on different frequency components of images, thereby enhancing deblurring performance. These two attention modules are seamlessly integrated into our network. Compared to existing methods, our approach demonstrates superior performance on datasets of blurry metal corrosion images, achieving a peak signal-to-noise ratio (PSNR) of 32.8645 dB and a structural similarity (SSIM) of 0.9768. These metrics indicate that our method provides clearer and more detailed reconstructions, significantly enhancing the image quality.
Leather Defect Detection Based on Improved YOLOv8 Model
Authors: Peng Zirui , Zhang Chen , Wei Wei
Published: December 2024

Addressing the low accuracy and slow detection speed experienced by algorithms based on deep learning for a leather defect detection task, a lightweight and improved leather defect detection algorithm, dubbed YOLOv8-AGE, has been proposed based on YOLOv8n. In the backbone network, the EMA attention mechanism and C2f module have been fused into the C2f-EMA module, achieving performance enhancement with lower computational overhead. In the neck, the AFPN structure has been combined with the VoV-GSCSP module constructed using GSConv, to reduce the number of parameters while enhancing the model’s multi-scale detection capability. Finally, a shared convolutional layer has been introduced for simplifying the design of the detection head. Experimental results demonstrate that the improved algorithm achieves an improvement of 1.39% in mAP50 and reduces the number of parameters and GFLOPs by 9.3% and 7.41%, respectively, as compared to the original YOLOv8 model. On the dataset in this paper, there is an improvement in accuracy and detection speed over mainstream algorithms.
Risk Prioritizing with Weighted Failure Mode and Effects Analysis and Fuzzy Step-Wise Weight Assessment Ratio Analysis: An Application Software Service Provider Company in the Defense Industry
Authors: Korkusuz Polat Tulay , Pamuk Candan Işılay
Published: December 2024

With the development of technology, the need for software and software products to manage, control, and develop activities in many sectors is increasing daily. In order to create suitable software that will meet the needs of businesses and customers, the software application must be tested in detail before reaching the end user. For this reason, software testing processes are gaining importance in software development activities. This article discusses which errors are critical to solve in complex situations for the reliability and quality of the software product and the relationship between errors. In this study, the classical FMEA method was primarily used to identify and prioritize errors in an ongoing project of a company that provides software services in the defense industry. Later, to eliminate the shortcomings of the classical FMEA method, a new model, the weighted FMEA method (which calculates the risk priority score with five sub-severity components), was developed and applied. In the newly developed weighted FMEA method, the weights were determined by the fuzzy SWARA (Step-Wise Weight Assessment Ratio Analysis) method since the weights of the severity subcomponents were not the same. The risk priority number (RPN) of error types was calculated using classical FMEA and weighted FMEA. Since the RPNs calculated with weighted FMEA are calculated with more subcomponents, the chances of the RPNs’ errors appearing the same are much less than the RPNs calculated with classical FMEA. This situation indicates that the RPNs calculated with weighted FMEA are obtained from a more profound analysis.
Spindle Bearing Preload Control Using NI MyRIO
Authors: Turek Paweł
Published: December 2024

The article presents an application for controlling the preload of bearings in a model spindle system. The bearing preload will be implemented using piezoelectric elements, which allow for changing the preload of bearings during spindle operation, which results in a change in the stiffness of the entire system. Such a change in stiffness allows for effective reduction of the vibration amplitudes of the spindle tip. The use of the MyRIO 1900 device from National Instruments, which was programmed using LabVIEW 2021 SP1 (32 bit), is described in detail. The effectiveness of the control algorithm was confirmed on the basis of actual measurements of the vibration amplitude of the front spindle tip on which three different substitute masses (model grinding wheels) were placed. The values for the system without and with the operating control system were compared. The results were recorded five times for each state of the device and each substitute mass. The value of the maximum amplitude was taken into account after averaging it from all five tests without control and with control. The effectiveness of the control algorithm was the greater the heavier the substitute mass, which allowed for reducing the vibration amplitude by up to 20%.
Enhanced Conformer-Based Speech Recognition via Model Fusion and Adaptive Decoding with Dynamic Rescoring
Authors: Geng Junhao , Jia Dongyao , He Zihao , Wu Nengkai , Li Ziqi
Published: December 2024

Speech recognition is widely applied in fields like security, education, and healthcare. While its development drives global information infrastructure and AI strategies, current models still face challenges such as overfitting, local optima, and inefficiencies in decoding accuracy and computational cost. These issues cause instability and long response times, hindering AI’s competitiveness. Therefore, addressing these technical bottlenecks is critical for advancing national scientific progress and global information infrastructure. In this paper, we propose improvements to the model structure fusion and decoding algorithms. First, based on the Conformer network and its variants, we introduce a weighted fusion method using training loss as an indicator, adjusting the weights, thresholds, and other related parameters of the fused models to balance the contributions of different model structures, thereby creating a more robust and generalized model that alleviates overfitting and local optima. Second, for the decoding phase, we design a dynamic adaptive decoding method that combines traditional decoding algorithms such as connectionist temporal classification and attention-based models. This ensemble approach enables the system to adapt to different acoustic environments, improving its robustness and overall performance. Additionally, to further optimize the decoding process, we introduce a penalty function mechanism as a regularization technique to reduce the model’s dependence on a single decoding approach. The penalty function limits the weights of decoding strategies to prevent over-reliance on any single decoder, thus enhancing the model’s generalization. Finally, we validate our model on the Librispeech dataset, a large-scale English speech corpus containing approximately 1000 h of audio data. Experimental results demonstrate that the proposed method achieves word error rates (WERs) of 3.92% and 4.07% on the development and test sets, respectively, significantly improving over single-model and traditional decoding methods. Notably, the method reduces WER by approximately 0.4% on complex datasets compared to several advanced mainstream models, underscoring its superior robustness and adaptability in challenging acoustic environments. The effectiveness of the proposed method in addressing overfitting and improving accuracy and efficiency during the decoding phase was validated, highlighting its significance in advancing speech recognition technology.
“Choreographing Empathy” in Walking Miracles, an Original Dance/Theater Work Created from Stories Told by Six Adult Survivors of Child Sexual Abuse
Authors: Dickinson Barbara
Published: December 2024

Walking Miracles, a dance/theater project, was created from the stories of six adult survivors of child sexual abuse and completed due to the conscientious work of many collaborators. A psychotherapy group of fourteen sessions was audiotaped and attended by the six survivors, three dancer/choreographers, and one psychotherapist. Our goals were to provide positive psychotherapeutic experiences for the survivors and the foundation for a dance/theater piece that would then be presented to the public at the conclusion of the group sessions. Our hope was that audiences would gain a deeper empathetic understanding of child sexual abuse and would become stronger allies for the survivors and stronger advocates for child abuse prevention. Empathetic abilities were critical for this project—in the psychotherapy process, in the care taken to protect the trust and confidentiality of the survivors, and in the creation of the script, choreography, music, and poetry. I will examine the nature of empathy and the processes for creating specific movements from such dark experiences. How does one approach a work about issues so intensely personal? What care do we need to provide for the participants during the progression of the work? What are the ethical aspects of such projects that use the personal narratives of hidden communities?
Exposure to Extreme Temperatures and Change in Dietary Patterns in Korea
Authors: Cho Seungyeon
Published: December 2024

Climate change has led to increased volatility in extreme temperatures, which poses a significant threat to human health. One way in which extreme temperatures impact health is through changes in dietary patterns, particularly food consumption and nutrient intake. This study uses a restricted-access version of 24 h dietary recall data from the 2018–2021 Korea National Health and Nutrition Examination Survey and meteorological data to examine the effect of heat and cold waves on food consumption and nutrient intake. The results suggest that cold waves increase individuals’ intake of key nutrients such as calories, protein, fat, saturated fat, and sodium. In contrast, heat waves have little to no significant effect on nutrient intake. Aside from the significant increase in the consumption of beer and chicken, the effects of heat or cold waves on overall food consumption are minimal. Depending on age and income level, cold and heat waves have different effects on food consumption and nutrient intake. This study suggests that temperature, particularly extreme heat and cold, plays a significant role in shaping individuals’ dietary patterns. Therefore, special attention is needed to maintain a balanced and healthy diet during extreme temperatures.
Neutrosophic Strongly Preopen Sets and Neutrosophic Strong Precontinuity
Authors: Açikgöz Ahu , Esenbel Ferhat
Published: December 2024

: In this study, we introduce a novel class of generalized neutrosophic open sets, referred to as neutrosophic strongly preopen sets. Building on this foundation, we propose a new type of continuity and several new types of mappings. These concepts aim to inspire future research in the scientific community and are rooted in this newly defined class. Additionally, we explore the properties and characteristics of these concepts within neutrosophic spaces. Furthermore, this study investigates the connections between the newly introduced types of mappings and those defined in earlier research, thereby establishing relationships that can serve as a foundation for further scientific exploration.
Fitness of Mythimna separata (Lepidoptera: Noctuidae) on Cultivated Wheat and a Weed, Wild Oat (Avena fatua), and Its Implications for Pest Management
Authors: Pan Qinjian , Shen Junyu , Su Lvming , Nie Zexiang , Shikano Ikkei , Liu Tong-Xian , Chen Lin
Published: December 2024

Mythimna separata (Walker), a significant migratory pest in many Asian countries, can cause severe damage to wheat crops. Understanding whether wild oat can serve as an alternate host is important for informing predictive models of M. separata infestation levels in wheat fields and can improve pest and weed management strategies. We first conducted both choice and no-choice experiments and found that M. separata readily laid eggs on both wheat and wild oat, with no significant oviposition preference. However, newly hatched larvae exhibited a strong preference for wheat, with 53.34% more larvae feeding on wheat compared to wild oat. Development time from egg to adult emergence was significantly shorter in M. separata fed on wheat than on wild oat, although the durations of the larval and pupal stages varied depending on the host plant. Despite these differences in development time, host plants did not significantly affect larval survival, pupal weight, fecundity, and adult longevity. The mean number of eggs laid by females that fed on wheat and wild oat were 1202.12 and 1270.54 eggs/female, and larval survival rates were 81% and 84%, respectively. Our findings suggest that wild oat can serve as a suitable host for M. separata and may act as a refuge when wheat fields are treated with insecticides. The high larval preference for wheat over wild oat indicates that M. separata on wild oat may easily disperse to wheat, complicating pest control and highlighting the need to include wild oat in pest management strategies.
Genome-Wide Identification and Expression of Neuropeptides and Their Expression Patterns After RNAi of CHH Genes in Pacific White Shrimp Litopenaeus vannamei
Authors: Zhang Long , Sun Lichao , Song Guanghao , Wang Beibei , Cui Yanting , Liu Fei , Li Yuquan , Wang Zhongkai
Published: December 2024

Neuropeptides are pivotal in regulating a broad spectrum of developmental, physiological, and behavioral processes throughout the life cycle of crustaceans. In this comprehensive study, we utilized a multiomics approach to characterize neuropeptide precursors and to assess the expression profiles of neuropeptide-encoding genes across various tissues and developmental stages in the Pacific white shrimp, Litopenaeus vannamei. Additionally, we explored the differential expression of neuropeptide genes in the eyestalk before and after the RNA interference-mediated suppression of crustacean hyperglycemic hormone (CHH) and vitellogenesis-inhibiting hormone (VIH) gene expression. Our study identified a total of 125 neuropeptide-encoding genes in L. vannamei, with 54 of these genes previously uncharacterized in the genome. Notably, certain neuropeptide-encoding gene families showed significant expansion, as demonstrated by the discovery of 10 adipokinetic hormone/corazonin-like peptide (ACP) genes, 55 CHH superfamily genes, and 13 pigment-dispersing hormone (PDH) genes. Alternative splicing was also found to play a crucial role in generating functionally diverse neuropeptides; for example, the agatoxin and calcitonin genes undergo alternative splicing that leads to the production of three distinct agatoxin neuropeptides and two distinct calcitonin neuropeptides, respectively. Neuropeptide genes are predominantly expressed in neuroendocrine tissues, including the eyestalk, cerebral ganglia, thoracic ganglia, and ventral ganglia. During the embryonic development of L. vannamei, with the exception of the molt-inhibiting hormone (MIH) gene, all monitored genes display minimal expression from the zygote stage through to the larval in membrane (Lim) stage. In contrast, the majority of these genes exhibit a steady uptick in expression from the nauplius stage onwards, culminating in the post-larval stage. Furthermore, comparative transcriptomic analysis of the eyestalk revealed that the expression of the majority of neuropeptide genes was downregulated following the suppression of CHH and VIH gene expression. This downregulation was significantly associated with the enrichment of pathways related to amino acid metabolism and hormone synthesis. The findings of this study provide valuable insights for future research aimed at elucidating the role of neuropeptides in regulating physiological functions in L. vannamei, potentially leading to advancements in shrimp aquaculture practices.
Inhibitory Effects of Cenobamate on Multiple Human Cardiac Ion Channels and Possible Arrhythmogenic Consequences
Authors: Mateias Andreea Larisa , Armasescu Florian , Amuzescu Bogdan , Corlan Alexandru Dan , Radu Beatrice Mihaela
Published: December 2024

Cenobamate is a novel third-generation antiepileptic drug used for the treatment of focal onset seizures and particularly for multi-drug-resistant epilepsy; it acts on multiple targets: GABAA receptors (EC50 42–194 µM) and persistent neuronal Na+ currents (IC50 59 µM). Side effects include QTc interval shortening with >20 ms, but not <300 ms. Our in vitro cardiac safety pharmacology study was performed via whole-cell patch-clamp on HEK293T cells with persistent/inducible expression of human cardiac ion channel isoforms hNav1.5 (INa), hCav1.2 (α1c + β2 + α2δ1) (ICaL), hKv7.1 + minK (IKs), and hKv11.1 (hERG) (IKr). We found IC50 of 87.6 µM (peak INa), 46.5 µM (late INa), and 509.75 µM (ICaL). In experiments on Ncyte® ventricular cardiomyocytes, APD90 was reduced with 28.6 ± 13.5% (mean ± SD) by cenobamate 200 µM. Cenobamate’s marked inhibition of INa raises the theoretical possibility of cardiac arrhythmia induction at therapeutic concentrations in the context of preexisting myocardial pathology, in the presence of action potential conduction and repolarization heterogeneity. This hypothetical mechanism is consistent with the known effects of class Ib antiarrhythmics. In simulations with a linear strand of 50 cardiomyocytes with variable inter-myocyte conductance based on a modified O’Hara–Rudy model, we found a negligible cenobamate-induced conduction delay in normal tissue, but a marked delay and also a block when gap junction conduction was already depressed.
From Molecules to Amoeboid Movement: A New Way for Understanding the Morphology Through Actin-Binding Proteins
Authors: Volkova Ekaterina , Pozdnyakov Igor , Petukhov Mikhail , Polezhaeva Valeriia
Published: December 2024

Amoebozoa is a group of single-celled organisms that change their shape during locomotion. However, there is a taxon-specific complex of morphological characters inherent in the moving amoebae, known as locomotive forms. Actin is one of the proteins most important for amoeboid movement that, together with actin-binding proteins, construct the architecture of the cytoskeleton in the amoeboid cells. One of the actin-binding proteins is the Arp2/3 complex that provides a connection between actin filaments at an angle of 70°. In this paper, we predicted 3D models of bonded subunits Arp2 and Arp3 for 30 species from different taxa of Amoebozoa based on the publicly available transcriptomic data. Moreover, we predicted the binding free energy (ΔG) of bonded subunits Arp2 and Arp3 for 30 species and tried to link it to the morphology of the locomotive forms of amoebae. The ΔG values are the lowest in amoebae with the broad hyaline area, like Vannella spp. Amoebae that produce thin hyaline projections, like Vexillifera abyssalis, are characterized by intermediate ΔG values. Finally, the highest ΔG values are typical for the group of amoebae that have no conspicuous hyaline areas of the cytoplasm, like Pelomyxa shiedti, or have small hyaline caps, like Arcella intermedia. The presented analysis provides new insights into the molecular mechanisms of shape formation in amoeboid cells.
Correction: Wimalawansa, S.J. Physiological Basis for Using Vitamin D to Improve Health. Biomedicines 2023, 11, 1542
Authors: Wimalawansa Sunil J.
Published: December 2024

The publication (Wimalawansa 2023, [...]
Innovative Approaches in Knee Osteoarthritis Treatment: A Comprehensive Review of Bone Marrow-Derived Products
Authors: Lana José Fábio , Purita Joseph , Jeyaraman Madhan , de Souza Bianca Freitas , Rodrigues Bruno Lima , Huber Stephany Cares , Caliari Carolina , Santos Gabriel Silva , da Fonseca Lucas Furtado , Dallo Ignacio , Navani Annu , De Andrade Marco Antônio Percope , Everts Peter Albert
Published: December 2024

Knee osteoarthritis (OA) is a chronic articular disease characterized by the progressive degeneration of cartilage and bone tissue, leading to the appearance of subchondral cysts, osteophyte formation, and synovial inflammation. Conventional treatments consist of non-steroidal anti-inflammatory drugs (NSAIDs), analgesics, and glucocorticoids. However, the prolonged use of these drugs causes adverse effects. NSAIDs, for instance, are known to be nephrotoxic, increasing the damage to articular cartilage. New therapies capable of accelerating the process of tissue regeneration and repair are being discussed, such as the use of orthobiologics that are naturally found in the body and obtained through minimally invasive collection and/or laboratory manipulations. Bone marrow aspirate (BMA) and bone marrow aspirate concentrate (BMAC) are both rich in hematopoietic stem cells, mesenchymal stem cells (MSCs), and growth factors (GFs) that can be used in the healing process due to their anabolic and anti-inflammatory effects. The aim of this literature review is to assess the efficacy of BMA and BMAC in the treatment of knee OA based on the favorable results that researchers have obtained with the use of both orthobiologics envisaging an accelerated healing process and the prevention of OA progression.
The Brain in Context: A Scoping Review and Concept Definition of Neuro-Informed Policy and Practice
Authors: Staton Sally , Coles Laetitia , Normore George , Casey Charlotte , Searle Bonnie , Houen Sandy , Potia Azhar , Crompton Rebecca , Long Deborah , Hogan Michael , Thorpe Karen
Published: December 2024

Background/objectives: Among the developmental sciences, discovery in neuroscience has underpinned research innovations and made a significant contribution to knowledge translation. With the growth of neuroscience discovery, policymakers and practitioner workforces have adopted ‘neuro-informed’ in decisions targeting the delivery of human, social, and economic wellbeing. Methods: In this scoping review, we examined the use and conceptualization of neuro-informed policy and practice (NPP) over the last two decades. We aim to establish a working definition of NPP and identify the key knowledge bases underpinning the application of NPP, with a specific focus on children and young people. Results: A total of 116 publications related to NPP were identified across academic and policy sources. Publications derived from diverse fields (e.g., psychology, social policy, medicine, urban planning). Health and Education were the most common target areas for NPP; however, applications of NPP to social services, law, and physical environments were also identified. Despite the growth in NPP, concept definitions of NPP were limited and primarily tautological. A four-stage process of concept definition was used to develop a working definition of NPP applicable to different systems, workforces, and contexts. By applying content analysis, 12 distinct knowledge bases underpinning NPP were identified. Conclusion: Our scoping review highlights the importance of defining the concept of neuro-informed policy and practice, extending beyond the brain or individual in isolation to include consideration of the brain in context.
Student Violence Against Paraprofessionals in Schools: A Social-Ecological Analysis of Safety and Well-Being
Authors: Reddy Linda A. , Perry Andrew H. , Martinez Andrew , McMahon Susan D. , Bare Kailyn , Swenski Taylor , Dudek Christopher M. , Anderman Eric M. , Astor Ron Avi , Espelage Dorothy L. , Worrell Frank C.
Published: December 2024

Violence against teachers has received increasing attention worldwide, with high rates of verbal, threatening, physical, and property violence in schools. Teacher-directed violence contributes to poor mental and physical health, high rates of turnover, and diminished student achievement. Despite these findings, there is a dearth of research on violence experienced by paraprofessionals who play key roles in supporting students with the greatest learning and behavioral needs in schools. Using a sample of 1993 paraprofessionals, this study is one of the first to investigate paraprofessionals’ experiences of violence in school settings. We found that the rate of student violence against paraprofessionals was 37% for property offenses, 49.5% for physical violence, and 54% for verbal and threatening violence. Further, we employed a socio-ecological model of individual, classroom, school, and community factors to predict paraprofessional experiences of violence from students in schools. Negative binomial regression results revealed that student-staff relationship problems and student behavioral concerns were positively related to verbal and threatening, physical, and property violence against paraprofessionals. Paraprofessionals working in elementary schools were more likely to report physical violence compared to those working in middle or high school settings. Implications for research and educational practice are also presented.
Influence of the Bailey Gradation Method on the Mechanical Behavior of Asphalt Mixture Containing Steel Slag as an Alternative Aggregate
Authors: Coelho Lisley Madeira , dos Santos William Wilson , Guimarães Antônio Carlos Rodrigues , Monteiro Sergio Neves
Published: December 2024

This study evaluates the feasibility of reusing steel slag aggregates in asphalt concrete, analyzing the impact of different gradation methods (Bailey method and conventional Brazilian method) on the mechanical properties of the mix. Using the Marshall methodology and Petroleum Asphalt Concrete (PAC) 30/45, parameters such as Marshall stability, indirect tensile strength, resilient modulus, fatigue life through diametral compression, and permanent deformation (Flow Number) were investigated. Additionally, a simulation for a hypothetical section in the city of Rio de Janeiro, Brazil, was performed using the mechanistic-empirical pavement design software, Medina. The results showed that the mixture produced by the Bailey method outperformed the others in all analyses. This method led to a more compact mix, providing significant advantages, including up to a 35% reduction in final pavement thickness and a 110.6% increase in Flow Number (FN), enabling the mix to withstand extremely heavy traffic, as reported in the literature. Regarding fatigue life, the Bailey mixture achieved a fatigue class of 4, compared to the conventional mixture class 1. These findings indicate that using the Bailey gradation method for producing asphalt mixtures with steel slag can optimize binder content and improve resistance to permanent deformation and fatigue, making it a viable and sustainable alternative for asphalt pavements.
Optimizing the Design of Container House Walls Using Argon and Recycled Plastic Materials
Authors: Omle Issa , Askar Ali Habeeb , Kovács Endre
Published: December 2024

Interest in the use of container houses has been increasing in recent years because of their resistance to earthquakes and fires. The incorporation of recyclable materials into these houses will simultaneously reduce energy use and greenhouse gas emission rates. In this context, the thermal performance of an external multi-layer wall of a container house mostly made of recyclable materials is studied and compared to that of a normal wall. The current study proposes a completely new structure, where there are air gaps and plastic layers between the steel sheets to enhance thermal insulation. In these gaps, different gases including argon are tested to reduce the heat loss. Calculations are carried out for a steady-state case in the winter season using the student version of ANSYS 2023 R2 Academic software, and the heat loss is calculated for different materials and different thicknesses of the wall layers. Afterward, based on a life-cycle cost analysis, the optimum air gap materials, optimum thickness of plastic and air gap, and energy savings are determined for a period of 20 years. We found that the optimum number of plastic layers to minimize the heating load is 21, but this reduces to 11 when considering economic factors. Furthermore, if a reflective layer covers the plastic layer, the optimum is just one layer. For an insulation thickness of 2 cm, the maximum total life-cycle savings are 335.14 and 350.52 USD, respectively, and the minimum ones are 16.06 and 31.44 USD, respectively, for multi-layer walls with and without reflective layers compared to conventional walls.
Predicting Extent of Resection and Neurological Outcome for Insular Gliomas: An Analysis of Two Available Classifications
Authors: Guerrini Francesco , Custodi Viola Marta , Giuri Antonio , Caporrimo Maria Claudia , Bini Paola , Imarisio Ilaria , Colombo Sara , Bonzano Elisabetta , Pedrazzoli Paolo , Marchioni Enrico , Chiapparini Luisa , Spena Giannantonio
Published: December 2024

Background/Objectives: Insular gliomas are rare entities whose surgical resection presents a significant challenge due to their close relationship with crucial white matter bundles and deep perforating arteries. The Berger–Sanai classification is a well-established system based on dividing the insula into four quadrants. In contrast, the Kawaguchi grading system focuses on the tumor’s behavior and vascular infiltration. In this study, we compared these two systems in terms of surgical and clinical outcomes. Methods: A retrospective single-center consecutive series of patients treated for insular gliomas was analyzed. Results: A total of 43 patients were analyzed, with a mean age of 47 years. The average preoperative KPS was 92.6, and seizures were the most common presenting symptom. The mean extent of resection (EOR) was 92.2%. Both the Berger–Sanai and Kawaguchi classifications influenced the EOR, but the former showed a moderate-to-strong correlation with expected resection rates. Postoperative clinical outcomes were related to both classification systems, but this association was lost at the 6-month follow-up. Additionally, lower Kawaguchi grades were associated with significant postoperative MRI hyperintensities on DWI sequences and higher rates of intraoperative neuromonitoring (IONM) alterations, which translated into worse postoperative clinical conditions. Conclusions: The Berger–Sanai and Kawaguchi classification systems are both significantly related to the EOR in insular gliomas; however, only the Berger–Sanai system shows strong predictive value regarding resection rates. Both systems serve as good prognostic tools for determining short-term postoperative clinical outcomes, but significant DWI hyperintensities and IONM alterations are specifically associated with the Kawaguchi system.
Application of Carboxymethyl Cellulose (CMC)-Coated Nanoscale Zero-Valent Iron in Chromium-Containing Soil Remediation
Authors: Zhang Bo , Zhan Jiani , Fan Jiaqi , Zhu Bohong , Shen Weili , Zhang Shiwei , Li Weiting , Li Zhaohui , Zeng Fanjun
Published: December 2024

Nanofine zero−valent iron (nZVI) is a new, eco−friendly material with strong reducing and adsorbent properties that can be used to clean up heavy metal−affected soils. Herein, nZVI encapsulated with carboxymethyl cellulose (CMC−nZVI) is synthesized via an aqueous−phase reduction technique and subsequently deployed to evaluate its effectiveness in Cr(VI) soil remediation. The characterization analysis used SEM−EDS, XRD, XPS, and LSV to determine the relevant properties of the material. The results show that at an initial Cr(VI) concentration of 169.5 mg·kg−1, 93.2% of Cr(VI) was removed from the soil after 10 h of treatment with CMC−nZVI at pH 3.3. The kinetic analysis showed that CMC−nZVI had the maximum equilibrium adsorption capacity for removing Cr(VI) from soil at 105.3 mg·g−1. This followed a pseudo−second−order kinetic model. The study shows that CMC−nZVI converts Cr(VI) to Cr(III), which forms complexes with Fe(III) ions in the presence of hydroxide ions (OH−) to form a highly stable compound that eventually adsorbs into the nanomaterial’s surface for efficient removal.
Analysis of the Observed Trends in Rainfall and Temperature Patterns in North-Eastern Nigeria
Authors: Ishaku Deborah , Umaru Emmanuel Tanko , Adebayo Abel Aderemi , Löwner Ralf , Okhimamhe Appollonia Aimiosino
Published: December 2024

The present study offers a comprehensive evaluation of the monthly rainfall and temperature patterns across nine stations and fifty-nine points in North-Eastern Nigeria using NASA’s Prediction of Worldwide Energy Resources data, spanning four decades (1981–2021). By employing the Mann–Kendall (MK) test and inverse distance weighting (IDW) interpolation, the researchers effectively detected and visualized trends in climate variables. The MK test results indicate contrasting rainfall trends, with notable decreases in Akko, Billiri, Maiduguri, Numan, and Yola, and increases in Gombe, Abadam, Biu, and Mubi. The trends in the maximum temperature were found to be statistically significant across all stations, showing a consistent increase, whereas the minimum temperature trends exhibited a slight but insignificant decrease. The application of the Theil–Sen slope estimator quantified these trends, providing nuanced insights into the magnitudes of changes in climate variables. The IDW results further corroborate the general trend of decreasing rainfall (z = −0.442), modest increases in the maximum temperature (z = 0.046), and a marginal decline in the minimum temperature (z = −0.005). This study makes an important contribution by advocating for the proactive dissemination of climate information. Given the evident climate shifts, particularly the increasing temperatures and fluctuating rainfall patterns, timely access to such information is crucial to enhancing climate resilience in the region. The rigorous statistical methods applied and the detailed spatial analysis strengthen the validity of these findings, making this study a valuable resource for both researchers and policymakers aiming to address climate variability in North-Eastern Nigeria. These research results may also be useful for understanding the climate variabilities in different parts of the world.
Research on the Calibration Method of the Bonding Parameters of the EDEM Simulation Model for Asphalt Mixtures
Authors: Li Xiujun , Zhang Zhipeng , Zhao Linhao , Zhang Heng , Shi Fangzhi
Published: December 2024

To enhance the accuracy and reliability of the discrete element simulation software EDEM 2023 for pavement asphalt mixture simulation, three representative coarse aggregate particles were modeled in 3D using the SolidWorks 2018 software and imported into the EDEM 2023 software for particle filling. The Hertz–Mindlin with bonding contact model was used to construct the EDEM simulation model of asphalt mixtures, and the quadratic regression model of asphalt mixtures’ splitting tensile strength and four bonding parameters, namely, normal stiffness per unit area, shear stiffness per unit area, critical normal stress, and critical shear stress, was found by the response surface methodology. The results show that the relationship between the significance magnitude of the four bonding parameters on the splitting tensile strength of the asphalt mixture simulation model is as follows: critical normal stress > shear stiffness per unit area > normal stiffness per unit area > critical shear stress. The calibration results of the bonding parameters were used for simulation verification, and the relative error between the simulation and actual splitting tensile strength was only −2.48%. The feasibility of this bonding parameter calibration method is demonstrated, and it can lay a foundation for EDEM to simulate the performance of asphalt mixtures on pavements with high-precision simulation.
Longitudinal Follow-Up of the Psychological Well-Being of Patients with Colorectal Cancer: Final Analysis of PICO-SM
Authors: Kamposioras Konstantinos , Ntellas Panagiotis , Dadouli Katerina , Christodoulis Eleftherios , Adamou Marios , Anderson Daniel , Shanthappa Anup , Connell Jacqueline , Williams Joseph , Simpson Lilly , Germetaki Theodora , Braun Michael , Barriuso Jorge , Hasan Jurjees , Mullamitha Saifee , Marti Kalena , Saunders Mark , Lim Kok Haw Jonathan
Published: December 2024

PICO-SM was a prospective longitudinal study investigating the psychological impact of the COVID-19 pandemic on patients with colorectal cancer treated in a large UK tertiary cancer centre. Here, we present the impact of the third wave of the pandemic (December 2021 to February 2022), when the Omicron variant became prevalent in the UK, and the complete longitudinal comparison across the entire duration of this study. Patients were invited to complete a questionnaire, including screening psychometric tools. In total, n = 312 patients were included in the final analysis. Specifically, in this Omicron-predominant wave, n = 96 patients were studied in detail: the mean age was 64 years, 64% were male, 33% reported poor well-being, 27% anxiety, 11% depressive symptoms, and 3% trauma-related symptoms. The participants who had investigations cancelled (OR 9.22, 95% CI 1.09–77.85; p = 0.041) or felt that the pandemic would affect their mental health (OR 3.82, 95% CI 1.96–7.44; p < 0.001) had an increased risk of anxiety according to a multivariate analysis. Similarly, independent predictors of poor well-being included concern that the pandemic would affect their cancer treatment (OR 4.59, 95% CI 1.03–20.56; p = 0.046) or mental health (OR 3.90, 95% CI 1.38–11.03; p = 0.010). The psychological distress experienced by patients, particularly anxiety, remained high during the third wave of the COVID-19 pandemic. These results align with our previously reported findings, emphasising the importance of continuing cancer treatment amidst an ongoing humanitarian emergency.
Evaluation of the Relationship Between Air Pollutants and Emergency Department Admissions with Childhood Asthma
Authors: Söğütlü Yakup , Altaş Uğur , Altıntaş Tuğba , Altaş Zeynep Meva , Akova Sevgi , Özkars Mehmet Yaşar
Published: December 2024

Background: This study aims to evaluate the relationship between the number of visits to a pediatric emergency department due to asthma attacks and air pollutants. Methods: In this ecological study, all pediatric patients who visited the pediatric emergency department of a tertiary hospital in Istanbul with asthma between January 2016 and December 2023 were included. The effect of air pollution on the number of patient visits was analyzed using a negative binomial regression model. Results: Based on the negative binomial model, a one-unit increase in SO2 leads to a 0.020-unit decrease in the logarithm of the number of patient visits (p < 0.05). A one-unit increase in NO leads to a 0.040-unit increase in the logarithm of the number of patient visits (p < 0.05). According to factor analysis, as the levels of NO, NOx, PM2.5, NO2, and PM10 in the air increase, the number of patient visits also increases; however, as the level of SO2 increases, the number of patient visits decreases. Conclusions: Families should be informed about environmental exposures for disease management of children with asthma. The confounding factors may also play a role in SO2 level and the decrease in admissions due to asthma. Further studies are needed in this regard.
Cell-Type-Specific ROS–AKT/mTOR–Autophagy Interplay—Should It Be Addressed in Periimplantitis?
Authors: Butucescu Mihai , Imre Marina , Rus-Hrincu Florentina , Voicu-Balasea Bianca , Popa Alexandra , Moisa Mihai , Ripszky Alexandra , Neculau Cristina , Pituru Silviu Mirel , Pârvu Simona
Published: December 2024

Periimplantitis represents an inflammatory disease of the soft and hard tissues surrounding the osseointegrated dental implant, triggering progressive damage to the alveolar bone. Cumulative data have revealed that periimplantitis plays a crucial part in implant failure. Due to the strategic roles of autophagy and its upstream coordinator, the AKT/mTOR pathway, in inflammatory responses, the crosstalk between them in the context of periimplantitis should become a key research target, as it opens up an area of interesting data with clinical significance. Therefore, in this article, we aimed to briefly review the existing data concerning the complex roles played by ROS in the interplay between the AKT/mTOR signaling pathway and autophagy in periimplantitis, in each of the main cell types involved in periimplantitis pathogenesis and evolution. Knowing how to modulate specifically the autophagic machinery in each of the cellular types involved in the healing and osseointegration steps post implant surgery can help the clinician to make the most appropriate post-surgery decisions. These decisions might be crucial in order to prevent the occurrence of periimplantitis and ensure the proper conditions for effective osseointegration, depending on patients’ clinical particularities.
Data Poisoning Attack on Black-Box Neural Machine Translation to Truncate Translation
Authors: Li Lingfang , Hu Weijian , Luo Mingxing
Published: December 2024

Neural machine translation (NMT) systems have achieved outstanding performance and have been widely deployed in the real world. However, the undertranslation problem caused by the distribution of high-translation-entropy words in source sentences still exists, and can be aggravated by poisoning attacks. In this paper, we propose a new backdoor attack on NMT models by poisoning a small fraction of parallel training data. Our attack increases the translation entropy of words after injecting a backdoor trigger, making them more easily discarded by NMT. The final translation is part of target translation, and the position of the injected trigger poison affects the scope of the truncation. Moreover, we also propose a defense method, Backdoor Defense by Sematic Representation Change (BDSRC), against our attack. Specifically, we selected backdoor candidates based on the similarity between the semantic representation of words in a sentence and the overall sentence representation. Then, the injected backdoor is identified through computing the semantic deviation caused by backdoor candidates. The experiments show that our attack strategy can achieve a nearly 100% attack success rate, and the functionality of main translation tasks is almost unaffected in models having performance degradation that is less than 1 BLEU. Nonetheless, our defense method can effectively identify backdoor triggers and alleviate performance degradation.
Advancing Generative Intelligent Tutoring Systems with GPT-4: Design, Evaluation, and a Modular Framework for Future Learning Platforms
Authors: Liu Siyang , Guo Xiaorong , Hu Xiangen , Zhao Xin
Published: December 2024

Generative Intelligent Tutoring Systems (ITSs), powered by advanced language models like GPT-4, represent a transformative approach to personalized education through real-time adaptability, dynamic content generation, and interactive learning. This study presents a modular framework for designing and evaluating such systems, leveraging GPT-4’s capabilities to enable Socratic-style interactions and personalized feedback. A pilot implementation, the Socratic Playground for Learning (SPL), was tested with 30 undergraduate students, focusing on foundational English skills. The results showed significant improvements in vocabulary, grammar, and sentence construction, alongside high levels of engagement, adaptivity, and satisfaction. The framework employs lightweight JSON structures to ensure scalability and versatility across diverse educational contexts. Despite its promise, challenges such as computational demands and content validation highlight the main areas for future refinement. This research establishes a foundational approach for advancing Generative ITSs, offering key insights into personalized learning and the broader potential of Generative AI in education.
Design of Grid-Connected Solar PV Power Plant in Riyadh Using PVsyst
Authors: Alkahtani Mubarak M. , Kamari Nor A. M. , Zainuri Muhammad A. A. M. , Syam Fathy A.
Published: December 2024

Solar energy is a quick-producing source of energy in Saudi Arabia. Solar photovoltaic (PV) energy accounts for 0.5% of electricity output, with a total installed capacity of 9.425 GW and 9353 solar power plants of various types globally. Many solar power stations will be established on different sites in the coming years. The capacity of these stations reaches hundreds of megawatts. The primary aim of this study is to facilitate the strategic and systematic assessment of the solar energy resource potential that impacts both large and small-scale solar power projects in Saudi Arabia. This study describes in detail the analysis, simulation, and sizing of a 400 MW grid-connected solar project for the Riyadh, Saudi Arabia site using the PVSyst 8 software program. The software-generated trajectories primarily represent the performance of a PV system at a certain location. It provides data for the geographical position used by maps for component sizing, projecting the installation under extremely realistic conditions. The report further examines the system’s behavior with various tilt and orientation settings of the PV panel, which yields superior simulation results at equivalent latitudes for any practical sizing. Three types of PV modules with different sizes are used to design the solar plant. The main project was designed using 580 WP and was compared with 330 WP and 255 WP power modules. This study confirmed that high-power PV modules are more efficient than small modules.