bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding the Clinical Use of Levosimendan and Perspectives on its Future in Oncology
Authors: Ribeiro Eduarda , Vale Nuno
Published: August 2023

Drug repurposing, also known as repositioning or reprofiling, has emerged as a promising strategy to accelerate drug discovery and development. This approach involves identifying new medical indications for existing approved drugs, harnessing the extensive knowledge of their bioavailability, pharmacokinetics, safety and efficacy. Levosimendan, a calcium sensitizer initially approved for heart failure, has been repurposed for oncology due to its multifaceted pharmacodynamics, including phosphodiesterase 3 inhibition, nitric oxide production and reduction of reactive oxygen species. Studies have demonstrated that levosimendan inhibits cancer cell migration and sensitizes hypoxic cells to radiation. Moreover, it exerts organ-protective effects by activating mitochondrial potassium channels. Combining levosimendan with traditional anticancer agents such as 5-fluorouracil (5-FU) has shown a synergistic effect in bladder cancer cells, highlighting its potential as a novel therapeutic approach. This drug repurposing strategy offers a cost-effective and time-efficient solution for developing new treatments, ultimately contributing to the advancement of cancer therapeutics and improved outcomes for patients. Further investigations and clinical trials are warranted to validate the effectiveness of levosimendan in oncology and explore its potential benefits in a clinical setting.
A Lysine Residue at the C-Terminus of MHC Class I Ligands Correlates with Low C-Terminal Proteasomal Cleavage Probability
Authors: Schmalen Adrian , Kammerl Ilona E. , Meiners Silke , Noessner Elfriede , Deeg Cornelia A. , Hauck Stefanie M.
Published: August 2023

The majority of peptides presented by MHC class I result from proteasomal protein turnover. The specialized immunoproteasome, which is induced during inflammation, plays a major role in antigenic peptide generation. However, other cellular proteases can, either alone or together with the proteasome, contribute peptides to MHC class I loading non-canonically. We used an immunopeptidomics workflow combined with prediction software for proteasomal cleavage probabilities to analyze how inflammatory conditions affect the proteasomal processing of immune epitopes presented by A549 cells. The treatment of A549 cells with IFNγ enhanced the proteasomal cleavage probability of MHC class I ligands for both the constitutive proteasome and the immunoproteasome. Furthermore, IFNγ alters the contribution of the different HLA allotypes to the immunopeptidome. When we calculated the HLA allotype-specific proteasomal cleavage probabilities for MHC class I ligands, the peptides presented by HLA-A*30:01 showed characteristics hinting at a reduced C-terminal proteasomal cleavage probability independently of the type of proteasome. This was confirmed by HLA-A*30:01 ligands from the immune epitope database, which also showed this effect. Furthermore, two additional HLA allotypes, namely, HLA-A*03:01 and HLA-A*11:01, presented peptides with a markedly reduced C-terminal proteasomal cleavage probability. The peptides eluted from all three HLA allotypes shared a peptide binding motif with a C-terminal lysine residue, suggesting that this lysine residue impairs proteasome-dependent HLA ligand production and might, in turn, favor peptide generation by other cellular proteases.
A Comprehensive Review of Natural Products as Therapeutic or Chemopreventive Agents against Head and Neck Squamous Cell Carcinoma Cells Using Preclinical Models
Authors: Liew Yoon Xuan , Karen-Ng Lee Peng , Vincent-Chong Vui King
Published: August 2023

Head and neck squamous cell carcinoma (HNSCC) is a type of cancer that arises from the epithelium lining of the oral cavity, hypopharynx, oropharynx, and larynx. Despite the advancement of current treatments, including surgery, chemotherapy, and radiotherapy, the overall survival rate of patients afflicted with HNSCC remains poor. The reasons for these poor outcomes are due to late diagnoses and patient-acquired resistance to treatment. Natural products have been extensively explored as a safer and more acceptable alternative therapy to the current treatments, with numerous studies displaying their potential against HNSCC. This review highlights preclinical studies in the past 5 years involving natural products against HNSCC and explores the signaling pathways altered by these products. This review also addresses challenges and future directions of natural products as chemotherapeutic and chemoprevention agents against HNSCC.
Calcium, Phosphorus and Magnesium Abnormalities Associated with COVID-19 Infection, and Beyond
Authors: Anghel Lucreția , Manole Corina , Nechita Aurel , Tatu Alin Laurențiu , Ștefănescu Bogdan Ioan , Nechita Luiza , Bușilă Camelia , Zainea Pușica , Baroiu Liliana , Mușat Carmina Liana
Published: August 2023

The coronavirus disease (COVID-19) pandemic caused by the novel coronavirus SARS-CoV-2 has had a profound impact on global health, leading to a surge in research to better understand the pathophysiology of the disease. Among the various aspects under investigation, disruptions in mineral homeostasis have emerged as a critical area of interest. This review aims to provide an overview of the current evidence linking calcium, phosphorus and magnesium abnormalities with COVID-19 infection and explores the potential implications beyond the acute phase of the disease. Beyond the acute phase of COVID-19, evidence suggests a potential impact of these mineral abnormalities on long-term health outcomes. Persistent alterations in calcium, phosphorus and magnesium levels have been linked to increased cardiovascular risk, skeletal complications and metabolic disorders, warranting continuous monitoring and management in post-COVID-19 patients.
Uncovering the Role of Epstein–Barr Virus Infection Markers for Remission in Rheumatoid Arthritis
Authors: Banko Ana , Cirkovic Andja , Jeremic Ivica , Basaric Milica , Grk Milka , Miskovic Rada , Lazarevic Ivana , Miljanovic Danijela
Published: August 2023

Epstein–Barr virus (EBV) infection has been shown as a potential risk factor for the development of rheumatoid arthritis (RA). This prospective research aimed to investigate whether EBV infection markers changed during the six-month follow-up period in 133 RA patients (80 newly diagnosed on methotrexate (MTX)—RA-A, and 53 on biologic therapy—RA-B) and whether it was related to a disease outcome. Reduction of disease activity and inflammation was obtained. A significant decline in seroprevalence and titer for anti-VCA-IgM (p = 0.022 and p = 0.026) and anti-EA(D)-IgM (p = 0.022 and p = 0.006) in RA-A, and in seroprevalence and titer of anti-EA(D)-IgG in the RA-B subgroup (p = 0.021 and p = 0.006) were detected after the follow-up. A lower titer of anti-EBNA1-IgG could be considered a significant marker of RA remission in all RA patients regardless of age and gender (OR = 0.99, 95% CI OR = 0.98–0.99, p = 0.038), and also in RA-B patients separately (OR = 0.988, 95% CI OR = 0.98–0.99, p = 0.041). This study supported the basic hypothesis that the immune response to EBV infection is involved in the RA pathogenesis, at the beginning of the disease or during the RA evolution. Moreover, the potential influence of MTX or TNF-alpha inhibitors on the impairment of the host to control EBV infection was indirectly refuted.
A Novel Approach to Monitor the Concentration of Phosphate Buffers in the Range of 1 M to 0.1 M Using a Silicon-Based Impedance Sensor
Authors: Bhat Vinayak J. , Blaschke Daniel , Müller Elke , Ehricht Ralf , Schmidt Heidemarie
Published: August 2023

We present a novel and easy approach using a silicon-based impedance chip to determine the concentration of the given aqueous buffer solution. An accurate determination of the post-dilution concentration of the buffers is necessary for ensuring optimal buffer capacity, pH stability, and to assess solution reproducibility. In this study, we focused on phosphate buffer as the test liquid to achieve precise post-dilution concentration determinations. The impedance chip consisting of a top gold ring electrode, where a test volume of 20 μL to 30 μL of phosphate buffer was introduced for impedance measurements within the frequency range of 40 Hz to 1 MHz. For impedance investigation, we used phosphate buffers with three different pH values, and the impedance was measured after diluting the phosphate buffers to a concentration of 1.00 M, 0.75 M, 0.50 M, 0.25 M, 0.10 M, 0.05 M, and 0.01 M. In order to analyze the distinctive changes in the measured impedance, an equivalent circuit was proposed and modeled. From the impedance modeling, we report that the circuit parameter RAu/Si showed exponential dependence on the concentration of phosphate buffer and no dependence on the pH values of the phosphate buffer and on the added volume inside the ring electrode. The proposed silicon-based impedance chip is quick and uses reduced liquid volume for post-dilution concentration measurements of buffers and has perspective applications in the pharmaceutical and biological domains for regulating, monitoring, and quality control of the buffers.
Two-Step Identification Method and Experimental Verification of Weld Damage at Joints in Spatial Grid Structures
Authors: Liu Hui , Huang Jianwei , Wang Xueliang , Lv Xiuwen
Published: August 2023

Welded joints in grid structures are susceptible to damage and destruction when exposed to random excitation. The complexity of the grid structure poses challenges for realizing the damage recognition of welded joints. In this study, a two-step method is proposed specifically for damage identification of welded joints in grid structures, combining wavelet analysis and fuzzy pattern recognition to accurately identify the location and extent of damage in welded joints. Firstly, the structure is divided based on the analysis of the influence range of joint damage. Key joints are selected within the sub-regions where sensors are installed, and the acceleration response of these key joints is measured. Wavelet analysis is then applied to identify the sub-regions where weld damage occurs. Secondly, an equivalent finite element model is established for joints with varying degrees of damage. The damage index, calculated as the ratio of the absolute value of the difference in the first-order element strain mode of the members, increases with the degree of damage during joint weld damage. By monitoring the changes in the damage index of sensitive members, which exhibit significant changes with varying weld damage degrees, a damage pattern database is constructed for each sub-region. The membership degree between joint damage and the patterns in the pattern database is then calculated to determine the location and degree of weld damage. To validate the effectiveness of the proposed method, an experiment was conducted using a grid structure model with replaceable members. Highly sensitive FBG sensors were designed to measure the acceleration response of the joints, resulting in accurate identification of damaged sub-regions solely through the measurement of key joint acceleration responses. Furthermore, within the damaged sub-regions, the fuzzy pattern recognition method precisely determined the location and degree of weld damage in the joints. The experimental results demonstrate that the proposed method effectively reduces the complexity of the structure by dividing the grid structure into sub-regions, and enables the two-step identification method to achieve successful damage identification for the joints in the grid structure with high efficiency and accuracy.
Promoting Elderly Care Sustainability by Smart Village Facilities Integration—Construction of a Public Service Field with Introduction of Fall Posture Monitoring
Authors: Meng Jingting , Yang Ling , Lei Hao
Published: August 2023

In recent years, rural communities in China have been actively exploring a novel approach to elderly care that integrates treatment with health preservation. This study aims to contribute to the sustainable development of rural elderly care by introducing smart technology, specifically fall posture monitoring, into public services and facilities within rural communities. The focus of this study is on addressing a critical issue in elderly medical care: the timely feedback and treatment of falls. To begin, we conduct a comprehensive review of the current status and challenges associated with the application of fall posture monitoring technology. Additionally, we examine the environmental factors that contribute to the risk of falls in public spaces for the elderly. These assessments serve as the technical and environmental foundation for developing the proposed service framework. Our research is conducted from two primary perspectives: the supply of service resources that combine treatment with health preservation and the identification of risk factors associated with outdoor public spaces in the community where falls are likely to occur. Data for this study are collected through behavior mapping and field interviews. In conclusion, we present a constructive logic for the development of a public service field that effectively combines treatment with health preservation. This logic encompasses the integration of technology applications, resource coordination, and improvements to the physical environment. The findings from this study provide a scientific basis for the construction of public service fields in “smart villages” and serve as practical references for similar villages striving to adopt this innovative model. By leveraging the insights gained from this research, it is expected that rural communities will be better equipped to address the challenges of elderly care and facilitate the widespread adoption of this integrated care model.
Pricing and Coordinating the Lease-Oriented Closed-Loop Supply Chain for Construction Machinery in the Era of Carbon Tax
Authors: Yin Jing , Fang Yifan , Zhang Hengxi , Wang Tingting , Cai Shunyao
Published: August 2023

Promoting sustainable production and consumption practices in the construction machinery industry is crucial for achieving energy savings and reducing carbon emissions. However, there is a lack of targeted studies addressing the challenge of scaling up leasing and recycling while maximizing economic benefits for enterprises. To fill this gap, this paper presents a lease-oriented closed-loop supply chain model that incorporates a carbon tax policy to investigate the impact of the carbon tax rate and consumer preferences for remanufactured products on the supply chain and introduces a leasing compensation–cost apportioning combined contract to achieve supply chain coordination in the construction machinery sector. The model considers differential selling and leasing prices for new and remanufactured products, as well as the recovery rate, under both centralized and decentralized decision-making approaches. The study explores the interrelationships between various parameters through sensitivity analysis and numerical simulation. The results demonstrate that within a certain range of the cost apportioning proportional coefficient and leasing compensation proportional coefficient, the combined contract can lead the supply chain to achieve Pareto optimality. As the carbon tax rate increases, it was observed that the profits for all parties in the supply chain tend to decrease. However, due to the increased demand for remanufactured products, the product recovery rate improves, resulting in a reduction in total carbon emissions in the closed-loop supply chain of construction machinery. Moreover, the profits of all parties and the total supply chain profits initially decrease and then increase with an increasing preference coefficient for remanufactured products among consumers. By leveraging these factors and adopting effective strategies, such as enhancing consumer recognition of remanufactured products and optimizing pricing and cost allocation, it is indeed possible for the profits of all parties and the total profits in the supply chain to surpass the initial values, even in the face of increasing carbon tax rates. This demonstrates the potential for aligning sustainability objectives with economic benefits in the construction machinery industry.
Optimizing Energy Efficiency in High-Rise Residential Buildings in Abu Dhabi’s Hot Climate: Exploring the Potential of Double Skin Façades
Authors: Hilal Narmeen Abu , Haggag Mahmoud , Saleh Abeer Dar
Published: August 2023

This study investigates energy efficiency in high-rise residential buildings in Abu Dhabi, where the increased use of glass building façades has led to increased air-conditioning costs due to heat gain. The research focuses on evaluating the type of glass and the appropriate cavity between glass façades to minimize energy consumption while incorporating sustainability and innovative design principles. To achieve these objectives, this study employs a Double Skin Façade (DSF), a high-performance façade that adapts to the external climate conditions to fulfill internal cooling load requirements and meet occupants’ needs. Data were collected through an online survey distributed among residents of a selected residential tower, and a combination of qualitative and quantitative approaches was utilized to analyze the gathered information. The selected case study was analyzed using Energy Plus simulation software using the existing data and available details. The analysis aimed to identify the optimal DSF design that significantly enhances energy efficiency. The findings of this study emphasize the substantial impact of the optimum DSF design on energy efficiency in high-rise residential buildings. Through modeling existing data and comparing them with new model results for each variable, this study demonstrates that a DSF with a 35 cm cavity, comprising a double-glazed single skin layer in the interior and a Low-E double-glazed single skin layer as an outer layer, can reduce overall air-conditioning energy consumption by over 25%. These outcomes provide valuable insights into implementing DSF as a solution to address the unique energy challenges presented by high-rise residential buildings in hot climates.
Numerical Simulation of Pressure Wave Propagation and Its Effect on Damage to the Reactor Cavity under TNT Detonation for Steam Explosion
Authors: Ha Seong-Kug , Yoon Yeo-Hoon
Published: August 2023

In a severe accident, molten corium may penetrate the reactor pressure vessel and enter the cooling water in the reactor cavity, and then a steam explosion may occur. Steam explosions can initiate pressure waves and threaten the structural integrity of the reactor cavity. To investigate the propagation characteristics of the pressure waves, including the propagation pattern, attenuation, and amplification under TNT detonation, a coupled numerical approach combined with arbitrary Lagrangian–Eulerian and fluid–structure interaction methods are utilized. The peak pressures of the incident and reflected shock waves decrease rapidly with increasing distance from the charge center, whereas the reflected pressure in the reactor cavity can be between 1.30 and 1.67 times the incident pressure. Then, structural analysis is performed to evaluate the damages to the concrete, liner plate, and reinforcements. From the numerical results, localized and superficial concrete damages are observed in the reactor cavity and the basemat; however, the risk of damage to the concrete, resulting in the collapse of these components is very low. The risk of damage to the liner plate and reinforcements is also very low since the maximum strain values are much lower than the failure criteria. Finally, the structural integrity of the reactor cavity will be maintained during the TNT detonation for the steam explosion.
Introduction of SGLT2 Inhibitors and Variations in Other Disease-Modifying Drugs in Heart Failure Patients: A Single-Centre Real-World Experience
Authors: Tabella Erika , Correale Michele , Alcidi Gianmarco , Pugliese Rosanna , Ioannoni Sara , Romano Matteo , Palmieri Gianpaolo , Di Biase Matteo , Brunetti Natale Daniele , Iacoviello Massimo
Published: August 2023

Background: The sodium–glucose cotransporter-2 inhibitors (SGLT2i) have emerged as a crucial therapeutic option for patients with chronic heart failure with reduced ejection fraction (HFrEF). The aim of this study was to evaluate, in a real-world population from a single centre, the feasibility of introducing SGLT2i and their interaction with other recommended drug classes. Methods: Consecutive patients affected by chronic heart failure (CHF) were evaluated beginning in January 2022. At the baseline clinical visit, both the patient’s current medication and the prescribed treatments were recorded. Over a 6- to 12-month follow-up, changes in concomitant therapy were analysed. Results: At baseline, among 350 patients evaluated, only 17 (5%) were already taking SGLT2i: 13 with HFrEF, five with mildly reduced (HFmrEF), preserved (HFpEF) or improved (HFimpEF) ejection fraction. After the baseline assessment, SGLT2i were prescribed to 224 (64%) of the patients, including 179 (84%) with HFrEF, 27 (42%) with HFmrEF/HFimpEF, and 18 (22%) with HFpEF/HFimpEF. After follow-up, SGLT2i therapy was well tolerated and was associated with a significant increase in sacubitril/valsartan prescriptions and a decrease in diuretic use. Finally, a significant improvement in functional status and left ventricular systolic function after SGLT2i therapy was observed. Conclusions: In this single-centre, real-world study, SGLT2i were primarily prescribed to HFrEF patients who were already on other recommended drug classes for their treatment. Additionally, there was a noticeable enhancement in the prescribed therapy during a short-term follow-up. These findings further bolster the inclusion of this therapeutic approach in regular clinical practice.
Rare Complication Post-Conization for Cervical Dysplasia: Rectovaginal Fistula
Authors: Meloni Paolo , Izzo Sara , De Intinis Claudia , Simari Terenzia , Motzo Mariangela , Picazzo Riccardo , Brizio Rodolfo , Vignale Cristina , Molle Marcello , Izzo Luciano , Izzo Paolo
Published: August 2023

(1) Background: High-grade cervical dysplasia is primarily caused by human papillomavirus (HPV) infection. Conservative surgery is the preferred treatment approach for this condition. The most commonly employed technique is the loop electrosurgical excision procedure (LEEP), which involves removing the affected portion of the cervix. Excisional treatments are often curative, and complications are typically rare and minor. (2) Methods: The loop electrosurgical excision procedure (LEEP) is the standard method used for conservative surgery in high-grade cervical dysplasia. It entails the excision of the specific area of the cervix where the abnormal cells are present. The procedure employs a wire loop carrying an electrical current to remove the affected tissue. (3) Results: Excisional treatments, such as LEEP, have shown to be effective in treating high-grade cervical dysplasia. They have a high success rate in eliminating abnormal cells and reducing the risk of cervical cancer. Complications associated with LEEP are infrequent and usually minor. Short-term complications may include bleeding, which can be managed easily. Long-term complications may involve cervical canal stenosis, which can impact fertility. (4) Conclusions: Conservative surgery, particularly the loop electrosurgical excision procedure (LEEP), is the preferred and effective treatment for high-grade cervical dysplasia caused by HPV infection. It offers a high cure rate with rare and minor complications. While short-term bleeding is a common occurrence, it is manageable. Long-term complications such as cervical canal stenosis may impact fertility. However, an extremely rare and possibly unique complication described in this case is the development of a vaginorectal fistula. This complication is likely due to indirect thermal injury resulting from compromised tissue. Further research is needed to better understand and prevent such complications.
Damage Grading Evaluation of Thermal Barrier Coatings under CMAS Corrosion
Authors: Liu Wei , Liu Yangguang , Wang Weize , Yang Ting , Zhang Wenkang , Liu Chen , Zhang Chengcheng , Tu Shantung
Published: August 2023

Thermal barrier coatings (TBCs) material has excellent high-temperature resistance and heat insulation performance, which plays a vital role in improving the working efficiency and running life of the engine. During the flight, the engine will inhale dust particles in the air. These particles are mostly from siliceous debris, which are usually called calcium magnesium aluminum silicate (CMAS). At present, CMAS corrosion has become one of the important problems affecting the service life of thermal barrier coatings. In this study, conventional yttrium oxide stabilized zirconia (YSZ) coatings and ytterbium oxide and yttrium oxide co-stabilized zirconia (YbYSZ) coatings were prepared by atmospheric plasma spraying. The two coatings were examined under thermal cycling-CMAS coupling conditions and divided into six life stages. The failure modes, CMAS permeation behavior, crack characteristics and mechanical properties of the two coatings at different life stages were evaluated systematically. The experimental results show that the YbYSZ coating has a longer life than YSZ coating under the thermal cycling and CMAS coupling condition, which increases by about 83% compared with the conventional YSZ coating. In the whole life stage, the porosity of YbYSZ coating is always higher than that of YSZ coating. The phase transition is not the reason for the failure and spalling of the coatings. The crack length of the two coatings showed an increasing trend, but the crack length of the YSZ coating was higher than that of the YbYSZ coating, and the crack density of the two coatings showed a “saddle shape”, which was more obvious for the YSZ coating. The YbYSZ coating shows better mechanical properties under the thermal cycling-CMAS coupling condition with the evolution of life.
Observation of Metal–Insulator Transition (MIT) in Vanadium Oxides V2O3 and VO2 in XRD, DSC and DC Experiments
Authors: Polak Paweł , Jamroz Jan , Pietrzak Tomasz K.
Published: August 2023

Due to metal–insulator transitions occurring in those compounds, materials and devices based on vanadium (III) and (IV) oxides draw increasing scientific attention. In this paper, we observed the transitions in both oxides using contemporary laboratory equipment. Changes in the crystallographic structure were precisely investigated as a function of the temperature with a step of 2 °C. Thermal effects during transitions were observed using differential scanning calorimetry. The DC conductivity of the materials was measured quasi-continuously as a function of the temperature. All the experiments were consistent and showed considerable hysteresis of the metal–insulator transition in both vanadium oxides.
A Novel Machine Learning Model for Predicting Orthodontic Treatment Duration
Authors: Volovic James , Badirli Sarkhan , Ahmad Sunna , Leavitt Landon , Mason Taylor , Bhamidipalli Surya Sruthi , Eckert George , Albright David , Turkkahraman Hakan
Published: August 2023

In the field of orthodontics, providing patients with accurate treatment time estimates is of utmost importance. As orthodontic practices continue to evolve and embrace new advancements, incorporating machine learning (ML) methods becomes increasingly valuable in improving orthodontic diagnosis and treatment planning. This study aimed to develop a novel ML model capable of predicting the orthodontic treatment duration based on essential pre-treatment variables. Patients who completed comprehensive orthodontic treatment at the Indiana University School of Dentistry were included in this retrospective study. Fifty-seven pre-treatment variables were collected and used to train and test nine different ML models. The performance of each model was assessed using descriptive statistics, intraclass correlation coefficients, and one-way analysis of variance tests. Random Forest, Lasso, and Elastic Net were found to be the most accurate, with a mean absolute error of 7.27 months in predicting treatment duration. Extraction decision, COVID, intermaxillary relationship, lower incisor position, and additional appliances were identified as important predictors of treatment duration. Overall, this study demonstrates the potential of ML in predicting orthodontic treatment duration using pre-treatment variables.
A Modified LeNet CNN for Breast Cancer Diagnosis in Ultrasound Images
Authors: Balasubramaniam Sathiyabhama , Velmurugan Yuvarajan , Jaganathan Dhayanithi , Dhanasekaran Seshathiri
Published: August 2023

Convolutional neural networks (CNNs) have been extensively utilized in medical image processing to automatically extract meaningful features and classify various medical conditions, enabling faster and more accurate diagnoses. In this paper, LeNet, a classic CNN architecture, has been successfully applied to breast cancer data analysis. It demonstrates its ability to extract discriminative features and classify malignant and benign tumors with high accuracy, thereby supporting early detection and diagnosis of breast cancer. LeNet with corrected Rectified Linear Unit (ReLU), a modification of the traditional ReLU activation function, has been found to improve the performance of LeNet in breast cancer data analysis tasks via addressing the “dying ReLU” problem and enhancing the discriminative power of the extracted features. This has led to more accurate, reliable breast cancer detection and diagnosis and improved patient outcomes. Batch normalization improves the performance and training stability of small and shallow CNN architecture like LeNet. It helps to mitigate the effects of internal covariate shift, which refers to the change in the distribution of network activations during training. This classifier will lessen the overfitting problem and reduce the running time. The designed classifier is evaluated against the benchmarking deep learning models, proving that this has produced a higher recognition rate. The accuracy of the breast image recognition rate is 89.91%. This model will achieve better performance in segmentation, feature extraction, classification, and breast cancer tumor detection.
Designing a MOOC on Computational Thinking, Programming and Robotics for Early Childhood Educators and Primary School Teachers: A Pilot Test Evaluation
Authors: Amante Lúcia , Souza Elizabeth Batista , Quintas-Mendes António , Miranda-Pinto Maribel
Published: August 2023

This study focuses on developing and evaluating an online course aimed at preschool educators and primary school teachers. It presents a Massive Open Online Course (MOOC) on computational thinking, programming and robotics developed as part of the project “Laboratory for Technology and Programming and Robotics Learning in Primary and Preschool Education in Portugal (KML II)” The MOOC design was inspired by a blended learning model used in teacher professional development at the project’s inception and incorporates theoretical-pedagogical models of MOOC design as well as theoretical models of online interaction in virtual educational environments. The course will be offered on the NAU platform, a Portuguese MOOC platform. A pilot test was conducted with a purposive sample that included both participants from the target audience of the course as well as national and international experts specialised in these domains. The evaluation included a Likert scale questionnaire survey and open-ended questions. The results aim to validate the MOOC’s quality, including its structure, content relevance, proposed activities, and learning design. The findings provide evidence to improve the final version of the MOOC, contributing to its effectiveness and adequacy to the target audience.
One Font Doesn’t Fit All: The Influence of Digital Text Personalization on Comprehension in Child and Adolescent Readers
Authors: Sheppard Shannon M. , Nobles Susanne L. , Palma Anton , Kajfez Sophie , Jordan Marjorie , Crowley Kathy , Beier Sofie
Published: August 2023

Reading comprehension is an essential skill. It is unclear whether and to what degree typography and font personalization may impact reading comprehension in younger readers. With advancements in technology, it is now feasible to personalize digital reading formats in general technology tools, but this feature is not yet available for many educational tools. The current study aimed to investigate the effect of character width and inter-letter spacing on reading speed and comprehension. We enrolled 94 children (kindergarten–8th grade) and compared performance with six font variations on a word-level semantic decision task (Experiment 1) and a passage-level comprehension task (Experiment 2). Reading speed and comprehension were analyzed using generalized linear mixed-effects regression models. Independent samples t-tests compared speed and comprehension accuracy on personal best vs. worst font variation. A stability analysis was conducted to determine if participants had a stable personal best font variation within Experiment 1. The Experiment 1 stability analysis was statistically significant, and 58% of participants had a stable personal best font variation. Personal best font variations yielded significantly higher comprehension accuracy in both Experiments 1 and 2 and faster reading in Experiment 2. Using digital technology to personalize font may have important implications for school-aged readers.
Hybrid Spiking Fully Convolutional Neural Network for Semantic Segmentation
Authors: Zhang Tao , Xiang Shuiying , Liu Wenzhuo , Han Yanan , Guo Xingxing , Hao Yue
Published: August 2023

The spiking neural network (SNN) exhibits distinct advantages in terms of low power consumption due to its event-driven nature. However, it is limited to simple computer vision tasks because the direct training of SNNs is challenging. In this study, we propose a hybrid architecture called the spiking fully convolutional neural network (SFCNN) to expand the application of SNNs in the field of semantic segmentation. To train the SNN, we employ the surrogate gradient method along with backpropagation. The accuracy of mean intersection over union (mIoU) for the VOC2012 dataset is higher than that of existing spiking FCNs by almost 30%. The accuracy of mIoU can reach 39.6%. Moreover, the proposed hybrid SFCNN achieved excellent segmentation performance for other datasets such as COCO2017, DRIVE, and Cityscapes. Our hybrid SFCNN is a valuable and interesting contribution to extending the functionality of SNNs, especially for power-constrained applications.
A Dynamic Addressing Hybrid Routing Mechanism Based on Static Configuration in Urban Rail Transit Ad Hoc Network
Authors: Han Zijie , Liu Liu , Guo Zhibin , Su Zhaoyang , Suo Lei , Cai Shiyuan , Han Haitao
Published: August 2023

With the rapid development of urban rail transit, the traditional urban rail wireless network based on fixed infrastructure is not in a position to meet the increasingly complex communication demand. At the same time, Ad Hoc network, as a special wireless mobile network, is developing rapidly. Applying this self-organized networking architecture to the urban rail vehicle–ground communication network can overcome the problems existing in the traditional urban rail communication system. The routing protocols that can achieve low delay and highly reliable data transmission are important in the urban rail transit scenario. Therefore, combined with the wireless Ad Hoc network and the characteristics of the urban rail transit scenario, this paper proposes a dynamic addressing hybrid routing mechanism based on static configuration. Using an improved AODV routing discovery algorithm and then writing the routing table into the router in advance for static configuration not only reduces network overhead but also prolongs the network’s lifetime. It also saves the delay of routing discovery. Then, the cluster head node dynamically monitors the link status, dynamically finds the path when the link needs to be replaced, and selects different update paths according to different types of communication services. Finally, each algorithm’s network performance parameters, like the routing discovery overhead, residual link lifetime, packet delivery rate, throughput, and end-to-end delay, are analyzed and compared.
Fault-Tolerant Hardware Acceleration for High-Performance Edge-Computing Nodes
Authors: Barbirotta Marcello , Cheikh Abdallah , Mastrandrea Antonio , Menichelli Francesco , Angioli Marco , Jamili Saeid , Olivieri Mauro
Published: August 2023

High-performance embedded systems with powerful processors, specialized hardware accelerators, and advanced software techniques are all key technologies driving the growth of the IoT. By combining hardware and software techniques, it is possible to increase the overall reliability and safety of these systems by designing embedded architectures that can continue to function correctly in the event of a failure or malfunction. In this work, we fully investigate the integration of a configurable hardware vector acceleration unit in the fault-tolerant RISC-V Klessydra-fT03 soft core, introducing two different redundant vector co-processors coupled with the Interleaved-Multi-Threading paradigm on which the microprocessor is based. We then illustrate the pros and cons of both approaches, comparing their impacts on performance and hardware utilization with their vulnerability, presenting a quantitative large-fault-injection simulation analysis on typical vector computing benchmarks, and comparing and classifying the obtained results. The results demonstrate, under specific conditions, that it is possible to add a hardware co-processor to a fault-tolerant microprocessor, improving performance without degrading safety and reliability.
Time and Energy Benefits of Using Automatic Optimization Compilers for NPDP Tasks
Authors: Palkowski Marek , Gruzewski Mateusz
Published: August 2023

In this article, we analyze the program codes generated automatically using three advanced optimizers: Pluto, Traco, and Dapt, which are specifically tailored for the NPDP benchmark set. This benchmark set comprises ten program loops, predominantly from the field of bioinformatics. The codes exemplify dynamic programming, a challenging task for well-known tools used in program loop optimization. Given the intricacy involved, we opted for three automatic compilers based on the polyhedral model and various loop-tiling strategies. During our evaluation of the code’s performance, we meticulously considered locality and concurrency to accurately estimate time and energy efficiency. Notably, we dedicated significant attention to the latest Dapt compiler, which applies space–time loop tiling to generate highly efficient code for the NPDP benchmark suite loops. By employing the aforementioned optimizers and conducting an in-depth analysis, we aim to demonstrate the effectiveness and potential of automatic transformation techniques in enhancing the performance and energy efficiency of dynamic programming codes.
Decentralized Biogas Production in Urban Areas: Studying the Feasibility of Using High-Efficiency Engines
Authors: González Rubén , García-Cascallana José , Gutiérrez-Bravo Javier , Gómez Xiomar
Published: August 2023

The study examines decentralized waste treatment in an urban setting with a high-density population of 2500 inhab./km2. The co-digestion of food and garden waste was assumed by using several mid-size digesters, while centralized biogas and digestate valorization was considered. The studied configuration generates electricity and thermal energy, covering 1.3% of the residential electricity demand and 3.2% of thermal demand. The use of double-turbocharged engines under the most favorable scenario aids cities in reaching sustainability goals. However, the location of treatment plants is a factor that may raise social discomfort and cause a nuisance to citizens. Locating waste plants near residential areas causes discomfort due to possible odors, gaseous emissions, and housing market distortions. Such problematic aspects must be addressed for the decentralized alternative to work. These factors are of great relevance and must be given a practical solution if the circular economic model is to be implemented by considering the insertion of waste streams into the production system and generating local energy sources and raw materials.
Visible to Mid-IR Supercontinuum Generation in Cascaded PCF-Germanate Fiber Using Femtosecond Yb-Fiber Pump
Authors: Koptev Maksim Yu. , Zaprialov Alexander E. , Kosolapov Alexey F. , Denisov Alexander N. , Muravyeva Maria S. , Semjonov Sergey L. , Muravyev Sergey V. , Kim Arkady V.
Published: August 2023

Broadband supercontinuum (SC) fiber sources covering the mid-IR range have many significant applications, largely due to their compactness, reliability, and ease of use. However, most of the existing SC fiber sources cannot boast of either high reliability or a wide bandwidth. Thus, supercontinuum sources based on silica fibers are robust, but are not capable of generating SC in the mid-IR range. Sources based on soft glasses (tellurite, chalcogenide, etc.) generate broadband SC in the mid-IR range but are not used commercially, due to the poor mechanical and chemical characteristics of such fibers. In this work, we propose a new approach consisting of cascade generation of a supercontinuum sequentially in a silica photonic crystal fiber (PCF) and a germanate fiber. Using a standard ytterbium chirped-pulse amplification (CPA) laser system for pumping, we have demonstrated a supercontinuum in the range of 450–2950 nm in PCF and germanate fiber firmly connected by a standard fusion splicing technique. Further optimization of the cascade pump will make it possible to create a compact and reliable all-fiber SC source from the visible to mid-IR range.
Analysis of Fire-Induced Circulations during the FireFlux2 Experiment
Authors: Benik Jeremy T. , Farguell Angel , Mirocha Jeffrey D. , Clements Craig B. , Kochanski Adam K.
Published: August 2023

Despite recent advances in both coupled fire modeling and measurement techniques to sample the fire environment, the fire–atmosphere coupling mechanisms that lead to fast propagating wildfires remain poorly understood. This knowledge gap adversely affects fire management when wildland fires propagate unexpectedly rapidly and shift direction due to the fire impacts on local wind conditions. In this work, we utilized observational data from the FireFlux2 prescribed burn and numerical simulations performed with a coupled fire–atmosphere model WRF-SFIRE to assess the small-scale impacts of fire on local micrometeorology under moderate wind conditions (10–12 m/s). The FireFlux2 prescribed burn provided a comprehensive observational dataset with in situ meteorological observations as well as IR measurements of fire progression. To directly quantify the effects of fire–atmosphere interactions, two WRF-SFIRE simulations were executed. One simulation was run in a two-way coupled mode in which the heat and moisture fluxes emitted from the fire were injected into the atmosphere, and the other simulation was performed in a one-way coupled mode for which the atmosphere was not affected by the fire. The difference between these two simulations was used to analyze and quantify the fire impacts on the atmospheric circulation at different sections of the fire front. The fire-released heat fluxes resulted in vertical velocities as high as 10.8 m/s at the highest measurement level (20 m above ground level) gradually diminishing with height and dropping to 7.9 m/s at 5.77 m. The fire-induced horizontal winds indicated the strongest fire-induced flow at the lowest measurement levels (as high as 3.3 m/s) gradually decreasing to less than 1 m/s at 20 m above ground level. The analysis of the simulated flow indicates significant differences between the fire-induced circulation at the fire head and on the flanks. The fire-induced circulation was much stronger near the fire head than at the flanks, where the fire did not produce particularly strong cross-fire flow and did not significantly change the lateral fire progression. However, at the head of the fire the fire-induced winds blowing across the front were the strongest and significantly accelerated fire progression. The two-way coupled simulation including the fire-induced winds produced 36.2% faster fire propagation than the one-way coupled run, and more realistically represented the fire progression.
Investigating the Impact of Dietary Fibers on Mycotoxin Bioaccessibility during In Vitro Biscuit Digestion and Metabolites Identification
Authors: López-Ruiz Rosalía , Marin-Saez Jesús , Cunha Sara. C. , Fernandes Ana , de Freitas Victor , Viegas Olga , Ferreira Isabel M. P. L. V. O.
Published: August 2023

Mycotoxins contamination is a real concern worldwide due to their high prevalence in foods and high toxicity; therefore, strategies that reduce their gastrointestinal bioaccessibility and absorption are of major relevance. The use of dietary fibers as binders of four mycotoxins (zearalenone (ZEA), deoxynivalenol (DON), HT-2, and T-2 toxins) to reduce their bioaccessibility was investigated by in vitro digestion of biscuits enriched with fibers. K-carrageenan is a promising fiber to reduce the bioaccessibility of ZEA, obtaining values lower than 20%, while with pectin a higher reduction of DON, HT-2, and T-2 (50–88%) was achieved. Three metabolites of mycotoxins were detected, of which the most important was T-2-triol, which was detected at higher levels compared to T-2. This work has demonstrated the advantages of incorporating dietary fibers into a biscuit recipe to reduce the bioaccessibility of mycotoxins and to obtain healthier biscuits than when a conventional recipe is performed due to its high content of fiber.
Optimization of the Processing Conditions for the Production of a Gluten-Free Bread from Sour Cassava Starch (Manihot esculenta) and Some Legumes (Arachis hypogaea, Vigna unguiculata, and Glycine max)
Authors: Ndjang Marie Madeleine Nanga , Klang Julie Mathilde , Njapndounke Bilkissou , Foko Marius Edith Kouam , Dongmo Jean Roger , Kamdem Michael Hermann Kengne , Tonga Jordan Lembe , Mmutlane Edwin Mpho , Ndinteh Derek Tantoh , Kayitesi Eugenie , Zambou François Ngoufack
Published: August 2023

Background: Sour cassava starch is used as an alternative to wheat flour in breadmaking. However, its nutritional and technological properties are limited. To remedy this, the use of legumes has proved to be very successful. Thus, the present study aimed to determine the optimal condition for the production of bread made from sour cassava starch, peanut, cowpea and soybean flour. Methods: The I-optimal design was employed to obtain an optimal proportion of the mixture with the variables sour cassava starch, cowpea, soy and peanut flour. The responses evaluated were overall acceptability, specific volume and protein content. Results: It resulted that the incorporation of sour cassava starch positively influenced the volume but negatively influenced the protein content and overall acceptability. While the addition of legumes increased protein content and overall consumer acceptability, the specific volume was reduced. The optimal proportions of sour cassava starch, cowpea, soybean and peanut flour were 64.11%, 18.92%, 0% and 16.96%, respectively. Under this condition, it led to a desirability of 1, specific volume of 1.35, overall acceptability of 6.13, protein content of 9.72%, carbohydrate content of 67.89%, fat content of 9.39%, fiber content of 2.10% and ash content of 1.04%. Conclusions: The findings suggest that cowpea and peanut can be used for the improvement of the technological, nutritional and sensory properties of sour cassava starch bread and thus increase its consumption and application in the food processing industry.