bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Developments and Future Directions in Energy-Efficient Buildings from the Perspective of Building Construction Materials and Enclosure Systems
Authors: Azari Rahman , Kamel Ehsan , Memari Ali M.
Published: June 2024

The need to design buildings in compliance with the Paris Agreement goal requirements is urgent, and architects and engineers need to consider energy use and operational and embodied carbon requirements in doing so. Building envelopes will be an important element in the next generation of high-performance buildings and there have been significant advancements in recent years to develop building envelopes that help mitigate the building carbon emissions through energy-conserving low-embodied carbon or carbon-sequestering solutions. The key objective of this article is to present an overview of the state-of-the-art in the field of energy-efficient low-carbon buildings with a focus on envelope systems. This article provides a survey of the literature on energy use and carbon emissions of the United States building stock, presents recent advancements in energy-conserving building envelopes, and highlights reuse–reduce–sequester strategies that mitigate the embodied carbon of buildings. As materials are critical in reducing the energy consumption and carbon emissions of buildings, this paper also presents developments on diverse materials and building envelope solutions that have been effective in creating high-performance buildings, from insulation materials to phase-change materials and aerogels. Finally, the characteristics of a selected number of progressive net-zero-energy guidelines such as Passive House Institute (PHI) standards, Passive House Institute US (Phius) standards, the PowerHouse standard, and the BENG standard are discussed. The findings of this work highlight the increased focus on the design, construction, and engineering strategies that aim to mitigate the carbon emissions of buildings based on a holistic whole-life carbon mitigation approach.
Adapting the Historic Urban Landscape Approach to Study Slums in a Historical City: The Mae Kha Canal Informal Settlements, Chiang Mai
Authors: Duangputtan Patcharaporn , Mishima Nobuo
Published: June 2024

Beyond conserving urban heritage, the concept of historic urban landscapes (HULs) aims to tackle poverty and inequality, as well as to improve the quality of human settlements, through a people-centered approach in the context of rapid urbanization. This paper demonstrates the adaption of HUL tools and methodologies to investigate a slum in a historical city—the informal settlements along the Mae Kha Canal in Chiang Mai. An on-site field survey of the characteristics of the settlement’s composition and interviews with stakeholders, local authorities, and inhabitants were conducted. The analysis revealed that there is a gap between the desired strategy of the Mae Kha Canal agenda and the actual conditions of the location. The aforementioned contrast is discussed to suggest alternate options for upgrading the informal community while preserving its ancient walls, in line with HUL principles. The conclusion highlights the benefits of introducing the HUL approach in a slum setting and provides recommendations for deteriorated neighborhoods elsewhere that are either surrounded by or adjacent to historical features needing resilience.
Medullary Thyroid Cancer: Molecular Drivers and Immune Cellular Milieu of the Tumour Microenvironment—Implications for Systemic Treatment
Authors: Papachristos Alexander J. , Serrao-Brown Hazel , Gill Anthony J. , Clifton-Bligh Roderick , Sidhu Stanley B.
Published: June 2024

In this review, we explore the underlying molecular biology of medullary thyroid carcinoma (MTC) and its interplay with the host immune system. MTC is consistently driven by a small number of specific pathogenic variants, beyond which few additional genetic events are required for tumorigenesis. This explains the exceedingly low tumour mutational burden seen in most MTC, in contrast to other cancers. However, because of the low tumour mutational burden (TMB), there is a correspondingly low level of tumour-associated neoantigens that are presented to the host immune system. This reduces tumour visibility and vigour of the anti-tumour immune response and suggests the efficacy of immunotherapy in MTC is likely to be poor, acknowledging this inference is largely based on the extrapolation of data from other tumour types. The dominance of specific RET (REarranged during Transfection) pathogenic variants in MTC tumorigenesis rationalizes the observed efficacy of the targeted RET-specific tyrosine kinase inhibitors (TKIs) in comparison to multi-kinase inhibitors (MKIs). Therapeutic durability of pathway inhibitors is an ongoing research focus. It may be limited by the selection pressure TKI treatment creates, promoting survival of resistant tumour cell clones that can escape pathway inhibition through binding-site mutations, activation of alternate pathways, and modulation of the cellular and cytokine milieu of the tumour microenvironment (TME).
Head-to-Head Comparison: P-POSSUM and ACS-NSQIP® in Predicting Perioperative Risk in Robotic Surgery for Gynaecological Cancers
Authors: Sevinyan Lusine , Asaalaarchchi Hasanthi , Tailor Anil , Williams Peter , Evans Matthew , Hodnett Darragh , Arakkal Darshana , Prabhu Pradeep , Flint Melanie S. , Madhuri Thumuluru Kavitha
Published: June 2024

Purpose: In this retrospective pilot study, we aim to evaluate the accuracy and reliability of the P-POSSUM and ACS-NSQIP surgical risk calculators in predicting postoperative complications in gynaecological–oncological (GO) robotic surgery (RS). Methods: Retrospective data collection undertaken through a dedicated GO database and patient notes at a tertiary referral cancer centre. Following data lock with the actual post-op event/complication, the risk calculators were used to measure predictive scores for each patient. Baseline analysis of 153 patients, based on statistician advice, was undertaken to evaluate P-POSSUM and ACS-NSQIP validity and relevance in GO patients undergoing RS performed. Results: P-POSSUM reports on mortality and morbidity only; ACS-NSQIP reports some individual complications as well. ACS-NSQIP risk prediction was most accurate for venous thromboembolism (VTE) (area under the curve (AUC)-0.793) and pneumonia (AUC-0.657) and it showed 90% accuracy in prediction of five major complications (Brier score 0.01). Morbidity was much better predicted by ACS-NSQIP than by P-POSSUM (AUC-0.608 vs. AUC-0.551) with the same result in mortality prediction (Brier score 0.0000). Moreover, a statistically significant overestimation of morbidity has been shown by the P-POSSUM calculator (p = 0.018). Conclusions: Despite the limitations of this pilot study, the ACS-NSQIP risk calculator appears to be a better predictor of major complications and mortality, making it suitable for use by GO surgeons as an informed consent tool. Larger data collection and analyses are ongoing to validate this further.
Inhibition of Histone Deacetylase Activity Increases Cisplatin Efficacy to Eliminate Metastatic Cells in Pediatric Liver Cancers
Authors: Gulati Ruhi , Fleifil Yasmeen , Jennings Katherine , Bondoc Alex , Tiao Greg , Geller James , Timchenko Lubov , Timchenko Nikolai
Published: June 2024

The pediatric liver cancers, hepatoblastoma and hepatocellular carcinoma, are dangerous cancers which often spread to the lungs. Although treatments with cisplatin significantly improve outcomes, cisplatin may not eliminate metastasis-initiating cells. Our group has recently shown that the metastatic microenvironments of hepatoblastoma contain Cancer Associated Fibroblasts (CAFs) and neuron-like cells, which initiate cancer spread from liver to lungs. In this study, we found that these cells express high levels of HDAC1; therefore, we examined if histone deacetylase inhibition improves cisplatin anti-proliferative effects and reduces the formation of tumor clusters in pediatric liver cancer metastatic microenvironments. Methods: New cell lines were generated from primary hepatoblastoma liver tumors (hbl) and lung metastases (LM) of HBL patients. In addition, cell lines were generated from hepatocellular neoplasm, not otherwise specified (HCN-NOS) tumor samples, and hcc cell lines. Hbl, LM and hcc cells were treated with cisplatin, SAHA or in combination. The effect of these drugs on the number of cells, formation of tumor clusters and HDAC1-Sp5-p21 axis were examined. Results: Both HBL and HCC tissue specimens have increased HDAC1-Sp5 pathway activation, recapitulated in cell lines generated from the tumors. HDAC inhibition with vorinostat (SAHA) increases cisplatin efficacy to eliminate CAFs in hbl and in hcc cell lines. Although the neuron-like cells survive the combined treatments, proliferation was inhibited. Notably, combining SAHA with cisplatin overcame cisplatin resistance in an LM cell line from an aggressive case with multiple metastases. Underlying mechanisms of this enhanced inhibition include suppression of the HDAC1-Sp5 pathway and elevation of an inhibitor of proliferation p21. Similar findings were found with gemcitabine treatments suggesting that elimination of proliferative CAFs cells is a key event in the inhibition of mitotic microenvironment. Conclusions: Our studies demonstrate the synergistic benefits of HDAC inhibition and cisplatin to eliminate metastasis-initiating cells in pediatric liver cancers.
Pan-Cancer, Genome-Scale Metabolic Network Analysis of over 10,000 Patients Elucidates Relationship between Metabolism and Survival
Authors: Bucksot Jesse , Ritchie Katherine , Biancalana Matthew , Cole John A. , Cook Daniel
Published: June 2024

Despite the high variability in cancer biology, cancers nevertheless exhibit cohesive hallmarks across multiple cancer types, notably dysregulated metabolism. Metabolism plays a central role in cancer biology, and shifts in metabolic pathways have been linked to tumor aggressiveness and likelihood of response to therapy. We therefore sought to interrogate metabolism across cancer types and understand how intrinsic modes of metabolism vary within and across indications and how they relate to patient prognosis. We used context specific genome-scale metabolic modeling to simulate metabolism across 10,915 patients from 34 cancer types from The Cancer Genome Atlas and the MMRF-COMMPASS study. We found that cancer metabolism clustered into modes characterized by differential glycolysis, oxidative phosphorylation, and growth rate. We also found that the simulated activities of metabolic pathways are intrinsically prognostic across cancer types, especially tumor growth rate, fatty acid biosynthesis, folate metabolism, oxidative phosphorylation, steroid metabolism, and glutathione metabolism. This work shows the prognostic power of individual patient metabolic modeling across multiple cancer types. Additionally, it shows that analyzing large-scale models of cancer metabolism with survival information provides unique insights into underlying relationships across cancer types and suggests how therapies designed for one cancer type may be repurposed for use in others.
Perioperative Immunosuppressive Factors during Cancer Surgery: An Updated Review
Authors: Bezu Lucillia , Akçal Öksüz Dilara , Bell Max , Buggy Donal , Diaz-Cambronero Oscar , Enlund Mats , Forget Patrice , Gupta Anil , Hollmann Markus W. , Ionescu Daniela , Kirac Iva , Ma Daqing , Mokini Zhirajr , Piegeler Tobias , Pranzitelli Giuseppe , Smith Laura ,   The EuroPeriscope Group
Published: June 2024

Surgical excision of the primary tumor represents the most frequent and curative procedure for solid malignancies. Compelling evidence suggests that, despite its beneficial effects, surgery may impair immunosurveillance by triggering an immunosuppressive inflammatory stress response and favor recurrence by stimulating minimal residual disease. In addition, many factors interfere with the immune effectors before and after cancer procedures, such as malnutrition, anemia, or subsequent transfusion. Thus, the perioperative period plays a key role in determining oncological outcomes and represents a short phase to circumvent anesthetic and surgical deleterious factors by supporting the immune system through the use of synergistic pharmacological and non-pharmacological approaches. In line with this, accumulating studies indicate that anesthetic agents could drive both protumor or antitumor signaling pathways during or after cancer surgery. While preclinical investigations focusing on anesthetics’ impact on the behavior of cancer cells are quite convincing, limited clinical trials studying the consequences on survival and recurrences remain inconclusive. Herein, we highlight the main factors occurring during the perioperative period of cancer surgery and their potential impact on immunomodulation and cancer progression. We also discuss patient management prior to and during surgery, taking into consideration the latest advances in the literature.
Low Anterior Resection Syndrome following Restorative Proctectomy for Rectal Cancer: Can the Surgeon Have Any Meaningful Impact?
Authors: Garfinkle Richard C. , McKenna Nicholas P.
Published: June 2024

Postoperative bowel dysfunction following restorative proctectomy, commonly referred to as Low Anterior Resection Syndrome (LARS), is a common long term sequela of rectal cancer treatment. While many of the established risk factors for LARS are non-modifiable, others may be well within the surgeon’s control. Several pre-, intra-, and postoperative decisions may have a significant impact on postoperative bowel function. Some of these factors include the extent of surgical resection, surgical approach, choice of anastomotic reconstruction, and use of fecal diversion. This review article summarizes the available evidence regarding how surgical decision-making can affect postoperative bowel function.
Exploring Extravasation in Cancer Patients
Authors: Pham Tuan D. , Tsunoyama Taichiro
Published: June 2024

Extravasation, the unintended leakage of intravenously administered substances, poses significant challenges in cancer treatment, particularly during chemotherapy and radiotherapy. This comprehensive review explores the pathophysiology, incidence, risk factors, clinical presentation, diagnosis, prevention strategies, management approaches, complications, and long-term effects of extravasation in cancer patients. It also outlines future directions and research opportunities, including identifying gaps in the current knowledge and proposing areas for further investigation in extravasation prevention and management. Emerging technologies and therapies with the potential to improve extravasation prevention and management in both chemotherapy and radiotherapy are highlighted. Such innovations include advanced vein visualization technologies, smart catheters, targeted drug delivery systems, novel topical treatments, and artificial intelligence-based image analysis. By addressing these aspects, this review not only provides healthcare professionals with insights to enhance patient safety and optimize clinical practice but also underscores the importance of ongoing research and innovation in improving outcomes for cancer patients experiencing extravasation events.
The Negative Impact of Sarcopenia on Hepatocellular Carcinoma Treatment Outcomes
Authors: Cespiati Annalisa , Smith Daniel , Lombardi Rosa , Fracanzani Anna Ludovica
Published: June 2024

Introduction: Hepatocellular carcinoma (HCC) represents a major global health concern, characterized by evolving etiological patterns and a range of treatment options. Among various prognostic factors, sarcopenia, characterized by loss of skeletal muscle mass, strength, and function, has emerged as a pivotal contributor to HCC outcomes. Focusing on liver transplantation, surgical resection, locoregional treatments, and systemic therapies, this review aims to analyze the impact of sarcopenia on HCC treatment outcomes, shedding light on an underexplored subject in the pursuit of more personalized management. Methods: A comprehensive literature review was conducted by searching peer-reviewed articles on sarcopenia and treatment outcomes in patients with HCC from inception up to October 2023. Results: Sarcopenia was found to be prevalent among HCC patients, exhibiting different occurrence, possibly attributable to diverse diagnostic criteria. Notably, despite variations in studies utilizing skeletal muscle indices, sarcopenia independently correlated with lower overall survival (OS), recurrence-free survival (RFS), and progression-free survival (PFS) across surgical (both transplantation and resection), locoregional, and systemic therapies, including tyrosine-kinase inhibitors (TKIs) and immune-checkpoint inhibitors (ICIs). Moreover, a link between sarcopenia and increased rate and severity of adverse events, particularly in surgery and TKIs recipients, and larger tumor size at diagnosis was observed. While baseline sarcopenia negatively influenced treatment outcomes, alterations in muscle mass post-treatment emerged as primary determinants of reduced OS. Conclusions: Sarcopenia, either present before or after HCC treatment, negatively correlates with response to it, across all etiologies and therapeutic strategies. Although only a few studies have evaluated the impact of supervised physical activity training on muscle mass and OS after HCC treatment, it is crucial to evaluate the presence of sarcopenia before treatment initiation, to better stratify patients’ prognosis, thus performing a more tailored approach, and identify therapies able to restore muscle mass in HCC patients. Conversely, the impact of sarcopenia on HCC recurrence and extrahepatic spread remains inadequately explored.
Predicting Longitudinal Cognitive Decline and Alzheimer’s Conversion in Mild Cognitive Impairment Patients Based on Plasma Biomarkers
Authors: Park Min-Koo , Ahn Jinhyun , Kim Young-Ju , Lee Ji-Won , Lee Jeong-Chan , Hwang Sung-Joo , Kim Keun-Cheol
Published: June 2024

The increasing burden of Alzheimer’s disease (AD) emphasizes the need for effective diagnostic and therapeutic strategies. Despite available treatments targeting amyloid beta (Aβ) plaques, disease-modifying therapies remain elusive. Early detection of mild cognitive impairment (MCI) patients at risk for AD conversion is crucial, especially with anti-Aβ therapy. While plasma biomarkers hold promise in differentiating AD from MCI, evidence on predicting cognitive decline is lacking. This study’s objectives were to evaluate whether plasma protein biomarkers could predict both cognitive decline in non-demented individuals and the conversion to AD in patients with MCI. This study was conducted as part of the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD), a prospective, community-based cohort. Participants were based on plasma biomarker availability and clinical diagnosis at baseline. The study included MCI (n = 50), MCI-to-AD (n = 21), and cognitively unimpaired (CU, n = 40) participants. Baseline plasma concentrations of six proteins—total tau (tTau), phosphorylated tau at residue 181 (pTau181), amyloid beta 42 (Aβ42), amyloid beta 40 (Aβ40), neurofilament light chain (NFL), and glial fibrillary acidic protein (GFAP)—along with three derivative ratios (pTau181/tTau, Aβ42/Aβ40, pTau181/Aβ42) were analyzed to predict cognitive decline over a six-year follow-up period. Baseline protein biomarkers were stratified into tertiles (low, intermediate, and high) and analyzed using a linear mixed model (LMM) to predict longitudinal cognitive changes. In addition, Kaplan–Meier analysis was performed to discern whether protein biomarkers could predict AD conversion in the MCI subgroup. This prospective cohort study revealed that plasma NFL may predict longitudinal declines in Mini-Mental State Examination (MMSE) scores. In participants categorized as amyloid positive, the NFL biomarker demonstrated predictive performance for both MMSE and total scores of the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease Assessment Packet (CERAD-TS) longitudinally. Additionally, as a baseline predictor, GFAP exhibited a significant association with cross-sectional cognitive impairment in the CERAD-TS measure, particularly in amyloid positive participants. Kaplan–Meier curve analysis indicated predictive performance of NFL, GFAP, tTau, and Aβ42/Aβ40 on MCI-to-AD conversion. This study suggests that plasma GFAP in non-demented participants may reflect baseline cross-sectional CERAD-TS scores, a measure of global cognitive function. Conversely, plasma NFL may predict longitudinal decline in MMSE and CERAD-TS scores in participants categorized as amyloid positive. Kaplan–Meier curve analysis suggests that NFL, GFAP, tTau, and Aβ42/Aβ40 are potentially robust predictors of future AD conversion.
Effect of Sodium Oxide on Structure of Lanthanum Aluminosilicate Glass
Authors: Mabrouk Assia , Bachar Ahmed , Vaills Yann , Canizarès Aurélien , Hampshire Stuart
Published: June 2024

Rare earth (RE) aluminosilicate glasses exhibit several favorable chemical, mechanical and thermal properties. As such, they are considered to be model systems for long-half-life actinides and are candidate containment materials for long-term immobilization of radioactive wastes. The aim of the present study was to investigate the effect of the substitution of sodium oxide on the glass transition temperature and structure of lanthanum aluminosilicate glasses. The primary objective was to elucidate the relationship between the substitution of Na2O for La2O3 on the Tg reduction and structural characteristics of lanthanum aluminosilicate glass, including identifying changes in the main Qn species and local environments of Si and Al. The structure of SiO2–Al2O3–La2O3–Na2O glasses has not been studied previously, and, thus, this investigation is the first to assess the structural changes occurring when La2O3 is substituted by Na2O. Three glasses were prepared with general composition (mol.%): 55SiO2–25Al2O3–20M2On (M = La or Na; n = 3 or 1). Glass G1 contains 20 mol.% La2O3; in G2, 15 mol.% of La2O3 was substituted by 15 mol.% Na2O; and Glass G3 contains 20 mol.% Na2O. The glasses were characterized by DSC to determine glass transition temperatures. As expected, as Na is substituted for La, Tg decreases substantially. Structural studies were carried out by FTIR spectroscopy, 29Si, and 27Al MAS NMR. As Na is substituted for La in these aluminosilicate glasses, the main goals that were achieved were the identification of Qn species and also changes in the local environments of Si and Al: {QnSi(mAl)} and {QnAl(mSi)}.
Machine Learning Algorithms for the Diagnosis of Class III Malocclusions in Children
Authors: Zhao Ling , Chen Xiaozhi , Huang Juneng , Mo Shuixue , Gu Min , Kang Na , Song Shaohua , Zhang Xuejun , Liang Bohui , Tang Min
Published: June 2024

Artificial intelligence has been applied to medical diagnosis and decision-making but it has not been used for classification of Class III malocclusions in children. Objective: This study aims to propose an innovative machine learning (ML)-based diagnostic model for automatically classifies dental, skeletal and functional Class III malocclusions. Methods: The collected data related to 46 cephalometric feature measurements from 4–14-year-old children (n = 666). The data set was divided into a training set and a test set in a 7:3 ratio. Initially, we employed the Recursive Feature Elimination (RFE) algorithm to filter the 46 input parameters, selecting 14 significant features. Subsequently, we constructed 10 ML models and trained these models using the 14 significant features from the training set through ten-fold cross-validation, and evaluated the models’ average accuracy in test set. Finally, we conducted an interpretability analysis of the optimal model using the ML model interpretability tool SHapley Additive exPlanations (SHAP). Results: The top five models ranked by their area under the curve (AUC) values were: GPR (0.879), RBF SVM (0.876), QDA (0.876), Linear SVM (0.875) and L2 logistic (0.869). The DeLong test showed no statistical difference between GPR and the other models (p > 0.05). Therefore GPR was selected as the optimal model. The SHAP feature importance plot revealed that he top five features were SN-GoMe (the ratio of the length of the anterior skull base SN to that of the mandibular base GoMe), U1-NA (maxillary incisor angulation to NA plane), Overjet (the distance between two lines perpendicular to the functional occlusal plane from U1 and L), ANB (the difference between angles SNA and SNB), and AB-NPo (the angle between the AB and N-Pog line). Conclusions: Our findings suggest that ML models based on cephalometric data could effectively assist dentists to classify dental, functional and skeletal Class III malocclusions in children. In addition, features such as SN_GoMe, U1_NA and Overjet can as important indicators for predicting the severity of Class III malocclusions.
Design and Performance Study of Carbon Fiber-Reinforced Polymer Connection Structures with Surface Treatment on Aluminum Alloy (6061)
Authors: Zhang Jianxin , Liu Yang , Cheng Lele , Kang Dongxu , Gao Ruize , Qin Yinle , Mei Zhonghao , Zhang Mengshuai , Yu Muhuo , Sun Zeyu
Published: June 2024

The existing connection methods for aluminum alloy profiles primarily include adhesive bonding and mechanical connections, with metal welding being widely employed. However, metal welding connections exhibit issues such as low joint strength, significant welding deformation, susceptibility to surface oxidation, poor welding surface quality, and challenges in achieving thin-walled metal structures. This paper presents a novel aluminum alloy connection structure that utilizes carbon fiber-reinforced polymer (CFRP) composites to replace welding for connecting aluminum alloy profiles. This innovative aluminum alloy composite connection structure not only enhances connection strength but also addresses the difficulties associated with metal welding. Research indicates that the optimal width of the CFRP structure in the connector is 60 mm, and with synergistic treatment of the aluminum alloy surface, the connection enhancement effect is optimal. Under these conditions, the tensile load can reach 58.71 kN and the bending load can reach 14.33 kN, which are 375.38% and 380.87% higher than those of welded aluminum alloy connections, respectively. The mass-specific strength increases by 106.27% and 134.42%, respectively. Simulations of this connection structure in components demonstrate that it improves strength by 73.99% and mass-specific strength by 71.95% compared to pure metal welded connections. Using ABAQUS 2023 software for simulation and calculation, the difference between the simulation and experimental results is within 5%, verifying the feasibility of the designed structure. This study provides new insights and a theoretical foundation for the development and application of hybrid connection methods involving metal and fiber-reinforced composites.
Pyroelectric Properties and Applications of Lithium Tantalate Crystals
Authors: Si Jiashun , Xiao Xuefeng , Zhang Yan , Huang Yan , Liang Shuaijie , Xu Qingyan , Zhang Huan , Ma Lingling , Yang Cui , Zhang Xuefeng
Published: June 2024

Lithium tantalate crystals, as a type of pyroelectric material, stand out from many other pyroelectric materials due to the advantages of high Curie temperature, large pyroelectric coefficient, high figure of merits, and environmental friendliness. Due to the pyroelectric effect caused by their spontaneous polarization, lithium tantalate crystals have broad application prospects in wide spectral bandwidth and uncooled pyroelectric detectors. This article reviews the pyroelectric properties of lithium tantalate crystals and evaluates methods for pyroelectric properties, methods for modulating pyroelectric properties, and pyroelectric detectors and their applications. The prospects of lithium tantalate thin films, doped lithium tantalate crystals, and near stoichiometric lithium tantalate crystals as response components for pyroelectric detectors are also discussed.
Releasing Dynamic of Serum ST2 and Calprotectin in Patients with Acute Ischemic Stroke
Authors: Sruk Ana , Budinčević Hrvoje , Šimundić Ana-Maria , Dukić Lora , Sučić Radovanović Tena , Čičak Helena , Pašalić Daria
Published: June 2024

This study investigated the releasing dynamics of serum ST2 and calprotectin in patients with acute IS. The study included acute IS patients (N = 20) with an NIH Stroke Scale score ≥8. Sampling was performed at seven time points: after admission (T0) and at the following 24 h consecutive intervals (T1–T6). Primary outcome at 90 days was evaluated using the modified Rankin scale: 0–2 for good and 3–6 for poor functional outcome. The secondary outcome was all-cause mortality after 90 days. Fifteen patients had a poor outcome, and eight died. Results showed a statistically significant difference in ST2 concentrations between good and poor outcomes at T0 (p = 0.04), T1 (p = 0.006), T2 (p = 0.01), T3 (p = 0.021), T4 (p = 0.007), T5 (p = 0.032), and for calprotectin T6 (p = 0.034). Prognostic accuracy was highest for ST2 at T1 for a cut-off > 18.9 µg/L (sensitivity 80% and specificity 100.0%) and for calprotectin at T5 for a cut-off > 4.5 mg/L (sensitivity 64.3% and specificity 100.0%). Serum ST2 and calprotectin-releasing dynamics showed a valuable prognostic accuracy for IS outcomes.
Integration of Localized, Contextual, and Hierarchical Features in Deep Learning for Improved Skin Lesion Classification
Authors: Ramamurthy Karthik , Thayumanaswamy Illakiya , Radhakrishnan Menaka , Won Daehan , Lingaswamy Sindhia
Published: June 2024

Skin lesion classification is vital for the early detection and diagnosis of skin diseases, facilitating timely intervention and treatment. However, existing classification methods face challenges in managing complex information and long-range dependencies in dermoscopic images. Therefore, this research aims to enhance the feature representation by incorporating local, global, and hierarchical features to improve the performance of skin lesion classification. We introduce a novel dual-track deep learning (DL) model in this research for skin lesion classification. The first track utilizes a modified Densenet-169 architecture that incorporates a Coordinate Attention Module (CoAM). The second track employs a customized convolutional neural network (CNN) comprising a Feature Pyramid Network (FPN) and Global Context Network (GCN) to capture multiscale features and global contextual information. The local features from the first track and the global features from second track are used for precise localization and modeling of the long-range dependencies. By leveraging these architectural advancements within the DenseNet framework, the proposed neural network achieved better performance compared to previous approaches. The network was trained and validated using the HAM10000 dataset, achieving a classification accuracy of 93.2%.
Quadcopter Modeling Using a System for UAV Parameters Measurement
Authors: Novotňák Jozef , Szőke Zoltán , Kašper Patrik , Šmelko Miroslav
Published: June 2024

This article deals with quadcopter modeling using a system for the measurement of unmanned aerial vehicle (UAV) parameters. UAVs are often equipped with various measurement devices and equipment for measurement, which significantly affects their weight. The currently available technical solutions and inventions do not allow corrections to be made to the on-board control electronics settings without the need to perform a test flight, or without the need to create complex and time-consuming mathematical models of the unmanned aerial vehicle; therefore, it is desirable to create a new method for modeling the characteristics of an UAV based on static laboratory measurements. The goal of this paper is to create a dynamic model of a quadcopter that will be adapted to a system for measuring UAV parameters, specifically the thrust of individual motors, which will be the next step to creating a new method for modeling UAV characteristics. This method can be used in the future for tuning flight control algorithms, based on static laboratory measurements.
Digital Forensic Research for Analyzing Drone and Mobile Device: Focusing on DJI Mavic 2 Pro
Authors: Zhao Ziyu , Wang Yongquan , Liao Genwei
Published: June 2024

With the frequent occurrence of drone-related criminal cases, drone forensics has become a hot spot of concern. During drone-related criminal investigations, the implicated drones are often forcibly brought down, which poses significant challenges in conducting forensic analysis. In order to restore the truth of criminal cases, it is necessary to extract data not only from the external TF card but also from internal chip memory in drone forensics. To address this issue, a drone data parser (DRDP) is proposed to extract internal and external data from criminal-implicated drones. In this paper, we present comprehensive forensics on the DJI Mavic 2 Pro, analyzing the main file structure and encryption model. According to its file structures, three case studies are conducted on various file types (DAT files, TXT files, and default files) to verify the effectiveness and applicability of the designed procedure. The results show that the encrypted data of the implicated drone, such as GPS information, flight time, flight altitude, flight distance, three velocity components (x, y, z) and other information can be extracted and decrypted correctly, which provides evidence for the identification of the case facts.
Influence of an African Indigenous Language on Classroom Interactions and Discourses
Authors: Ntuli Thuli G. , Mudau Awelani V.
Published: June 2024

This qualitative interpretative case study aimed to investigate how the developed isiNdebele scientific language register for Natural Sciences influences learners’ classroom interactions and discourses. Data were collected from stakeholders through interviews and observations. The results indicated that the use of African indigenous languages positively shapes learners’ classroom interactions and discourses. Specifically, when learners were taught Natural Sciences using the isiNdebele register, there was maximum interaction in the classroom in contrast to using the English register, where learners were passive for most of the lesson. This highlights the need for developing scientific registers in African indigenous languages. Therefore, it is recommended that these registers be integrated into teaching and learning as they positively influence interactions and discourses, leading to meaningful learning and better performance.
Outdoor STEAM Education: Opportunities and Challenges
Authors: Correia Marisa , Ribeirinha Teresa , Beirante David , Santos Raquel , Ramos Liliana , Dias Isabel Simões , Luís Helena , Catela David , Galinha Sónia , Arrais Ana , Portelada António , Pinto Paula , Simões Vera , Ferreira Regina , Franco Susana , Martins Maria Clara
Published: June 2024

There is a consensus that students should be involved in interdisciplinary activities that promote a solid education in STEAM subjects from an early age. The outdoor settings of schools present an advantageous context for STEAM education, allowing for a myriad of learning experiences. To understand how teachers perceive the pedagogical use of the school’s outdoor space, a study was carried out in a cluster of schools in a Portuguese city, including one middle school and 10 kindergarten and elementary schools. A mixed methods approach was used, combining a questionnaire for teachers (N = 49) with interviews (N = 8). The results indicate that teachers’ perceptions of the characteristics of their school’s outdoor spaces either facilitate or hinder the implementation of outdoor pedagogical activities. Most teachers concur that the outdoors provides contact with nature and encourages interdisciplinary and collaborative activities. However, the teachers surveyed admit to using the school’s outdoor spaces only occasionally, and this use decreases as the educational level at which they teach increases. The most common use of outdoor spaces is for physical and motor activities, promoting the well-being of children and youth. Although interdisciplinary activities in outdoor spaces are recognised, their implementation is limited and hampered by factors such as the length of curricula and the lack of training for teachers in these approaches. In this sense, there is an urgent need to train teachers in the interdisciplinary use of outdoor spaces to promote a solid education in STEAM subjects.
Online Games and Cognitive Distortions: A Comparative Analysis in Students with and without Disabilities
Authors: Suriá-Martínez Raquel , García-Castillo Fernando , López-Sánchez Carmen , Villegas Esther , Carretón Carmen
Published: June 2024

Online games have experienced significant growth in recent years, with gaming becoming a popular form of entertainment for people of all ages. However, their impact on cognition, especially among vulnerable groups such as students with disabilities, is a topic that requires deeper exploration. The objectives of this study are twofold: firstly, to understand the typology of risk players (non-risk players, players with problems, and pathological players); and secondly, to compare cognitive distortions among students with problematic profiles. Both objectives will be analyzed based on the presence or absence of disability. A total of 704 students from various Spanish universities (135 with disabilities and 569 without disabilities), aged between 18 and 38, participated in the study by completing the Gamblers Belief Questionnaire (GBQ), aimed at measuring cognitive distortions related to gambling problems, as well as the Massachusetts Gambling Screen questionnaire, aimed at measuring gambling addiction. The results indicate a higher percentage of students with disabilities showing a greater risk profile for addiction. Additionally, this group of students exhibits more cognitive distortions. These findings underscore the need for a comprehensive approach to addressing online gaming addiction and cognitive distortions among university students, with and without disabilities. Preventive measures are necessary, such as education on responsible technology use and the promotion of alternative activities. Moreover, specific intervention strategies need to be developed, including access to psychological health services for this student population.
Tear Film Break-Up Time before and after Watching a VR Video: Comparison between Naked Eyes and Contact Lens Wearers
Authors: Kim Hyunjin , Gil Minji , Kang Hyungoo
Published: June 2024

The impact of viewing VR videos using a head-mounted display (HMD) on tear film dynamics is examined by comparing the viewing experience of individuals using their naked eyes with that of viewers wearing contact lenses. While the impact of VR on eye dryness has been studied, there is limited research on the risks for contact lens wearers. This study aims to investigate eye dryness associated with VR use in individuals wearing soft contact lenses. Seventeen adults in their 20s (7 male, 10 female) with uncorrected visual acuity of 0.8+ participated. The non-invasive tear film break-up time (NIBUT) was assessed before and after a 20 min VR video session under two conditions: with and without soft contact lenses. The results indicated a decrease in the initial tear film break-up time and an increase in the average tear film break-up time when viewing with naked eyes, whereas viewing with contact lenses led to decreases in both parameters, with statistically significant changes observed. Although the alteration in the tear film break-up time was insignificant during VR video viewing with naked eyes, the tear film stability of individuals wearing soft contact lenses tended to decrease. Caution is advised when using soft contact lenses during VR video sessions to mitigate potential eye dryness.
Secure Task Offloading and Resource Allocation Strategies in Mobile Applications Using Probit Mish-Gated Recurrent Unit and an Enhanced-Searching-Based Serval Optimization Algorithm
Authors: Sindi Ahmed Obaid N. , Si Pengbo , Li Qi
Published: June 2024

Today, with the presence of 5G communication systems, including Internet of Things (IoT) technology, there is a high demand for mobile devices (especially smartphones, tablets, wearable technology, and so on). Regarding this proliferation and high demand, the massive adoption of mobile devices (MDs) has led to an exponential increase in network latency; the heavy demand for cloud servers causes the degradation of data traffic, which considerably impacts the real-time communication and computing aspects of mobile devices. As a result, mobile edge computing (MEC), an efficient framework capable of enhancing processing, optimizing energy usage, and offloading computation tasks, is considered a promising solution. In current research, numerous models have been implemented to achieve resource allocation and task offloading. However, these techniques are ineffective due to privacy issues and a lack of sufficient resources. Hence, this study proposes secure task offloading and resource allocation strategies in mobile devices using the Probit Mish–Gated Recurrent Unit (PM-GRU) and Entropic Linear Interpolation-Serval Optimization Algorithm (ELI-SOA). Primarily, the tasks to be offloaded and their attributes are gathered from mobile users and passed to a local computing model to identify the edge server. Here, the task attributes and the server attributes are compared with a cache table using the Sorensen–Dice coefficient. If the attributes match, then details about the appropriate edge server are produced. If the attributes do not match, then they are inputted into a global scheme that analyzes the attributes and predicts the edge server based on the Probit Mish-Gated Recurrent Unit (PM-GRU). Then, the server information is preserved and updated in the cache table in the local scheme. Further, the attributes, along with the predicted edge server, are inputted into a system for privacy-preserving smart contract creation by using Exponential Earth Mover’s Distance Matrix-Based K-Anonymity (EEMDM-KA) to develop a secure smart contract. Subsequently, the traffic attributes in the smart contract are extracted, and the request load is balanced by using HCD-KM. Load-balanced requests are assigned to the edge server, and the optimal resources are allocated in the cloud server by using the Entropic Linear Interpolation-Serval Optimization Algorithm (ELI-SOA). Finally, the created smart contract is hashed based on KECCAK-512 and stored in the blockchain. With a high accuracy of 99.84%, the evaluation results showed that the proposed approach framework performed better than those used in previous efforts.
Intelligent Substation Noise Monitoring System: Design, Implementation and Evaluation
Authors: Chen Wenchen , Liu Yingdong , Gao Yayu , Hu Jingzhu , Liao Zhenghai , Zhao Jun
Published: June 2024

In recent years, the State Grid of China has placed significant emphasis on the monitoring of noise in substations, driven by growing environmental concerns. This paper presents a substation noise monitoring system designed based on an end-network-cloud architecture, aiming to acquire and analyze substation noise, and report anomalous noise levels that exceed national standards for substation operation and maintenance. To collect real-time noise data at substations, a self-developed noise acquisition device is developed, enabling precise analysis of acoustic characteristics. Moreover, to subtract the interfering environmental background noise (bird/insect chirping, human voice, etc.) and determine if noise exceedances are originating from substation equipment, an intelligent noise separation algorithm is proposed by leveraging the convolutional time-domain audio separation network (Conv-TasNet), dual-path recurrent neural network (DPRNN), and dual-path transformer network (DPTNet), respectively, and evaluated under various scenarios. Experimental results show that (1) deep-learning-based separation algorithms outperform the traditional spectral subtraction method, where the signal-to-distortion ratio improvement (SDRi) and the scale-invariant signal-to-noise ratio improvement (SI-SNRi) of Conv-TasNet, DPRNN, DPTNet and the traditional spectral subtraction are 12.6 and 11.8, 13.6 and 12.4, 14.2 and 12.9, and 4.6 and 4.1, respectively; (2) DPTNet and DPRNN exhibit superior performance in environment noise separation and substation equipment noise separation, respectively; and (3) 91% of post-separation data maintains sound pressure level deviations within 1 dB, showcasing the effectiveness of the proposed algorithm in separating interfering noises while preserving the accuracy of substation noise sound pressure levels.
Simulation and Suppression Measure Analysis of Electromagnetic Radiation Interference Due to Frequency Converters in Coal Mines
Authors: Xin Zhonghua , Wang Huijuan , Sui Longpeng , Lu Yujia , Zhang Xiaodong , Chen Rui
Published: June 2024

Nowadays, due to their characteristics of high efficiency and energy saving, frequency converters are used in coal mine excavation machines and ventilation machines. They can cause serious electromagnetic radiation interference with the surrounding monitoring, sensing and other equipment. Therefore, it is necessary to explore the electromagnetic interference characteristics of mining converters. By choosing a ZJT-75/660SF mine frequency converter as the research object, an antenna model was established, and the method of moments was used to solve the problem. The electromagnetic radiation characteristics of the frequency converter were analyzed, and a field experiment was conducted to verify the effectiveness of the model by comparing the simulation and experimental data. According to the analysis of the electromagnetic intensity distribution characteristics of the near field and far field, the near-field intensity is concentrated in the inner part of the converter, but the far-field intensity has obvious directional characteristics, which are found to provide a reference value for the location of the underground mining converter. Finally, a method is proposed to improve electromagnetic radiation disturbance by changing the structure of the converter’s heat dissipation hole, and the feasibility of this method is verified.
Enhancing Energy Supply Reliability for University Lecture Halls Using Photovoltaic-Battery Microgrids: A South African Case Study
Authors: Showers Obu Samson , Chowdhury Sunetra
Published: June 2024

Institutions of higher learning in South Africa are grappling with occasional power outages in lecture halls, leading to disruptions in academic activities and occasional loss of lecture hours. Therefore, this study presents a comprehensive evaluation of a grid-connected solar PV/Li-ion battery microgrid (μG) system aimed at maintaining a constant power supply to selected lecture halls at a university in the Western Cape, South Africa. The microgrid design, modelling, and simulations, conducted in the MATLAB/Simulink environment, include the solar PV, Li-ion battery, energy consumption of the lecture halls (load profile), boost converter, bidirectional converter, and grid. Using the detailed design, modelling, and simulation, the study evaluates the economic and environmental impacts of integrating μGs, focusing on enhancing energy reliability, reducing operational costs, and mitigating CO2 emissions. The results indicate that integrating the microgrid resulted in a significant 51% reduction in energy cost and a decrease in greenhouse gas emissions by 530 kgCO2e per hour. In Cases 2 and 4, where the battery supplied power, the annual battery degradation costs are 6.08% and 14.9% of the initial cost, respectively. The μG ensures an uninterrupted power supply and improves the overall reliability of the university’s energy infrastructure. It promotes environmental sustainability goals of zero emissions and maintains continuous academic activities during grid outages. Furthermore, it fosters a conducive learning environment, supports innovation and creativity in sustainable energy technologies, and sets a standard for other higher education institutions to integrate renewable energy-powered μGs.