bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Mobilized Strength Design Method for Multi-Support Excavation Deformation Analysis
Authors: Tu Bingxiong , Han Meng , Jia Jinqing , Xiao Zhaoyun , Liu Lulu
Published: November 2024

The safe and reliable design of underground spaces ensures the safety of a structure itself and its surroundings. The traditional Mobilized Strength Design (MSD) method for a multi-support excavation deformation analysis ignores the effects of soil parameters and excavation boundary conditions. Therefore, to compensate for the shortcomings of the existing MSD method, this paper proposes an improved mobilized strength design (IMSD) method for a multi-support excavation deformation analysis. The improved incremental deformation mechanism further considers the effect of the soil friction angle, and the effect of excavation depth and the first support on deformation energy are also considered. Further, the excavation calculation process based on the IMSD method is given, and the effects of different calculation parameters on the IMSD solution of excavation deformation are discussed. The results show that the IMSD method can effectively consider the effect of boundary conditions and the excavated process on the excavation deformation. The traditional MSD method underestimates the excavation deformation and surface settlement by an average of 15–23%, while the IMSD solution is more consistent with the measured values. The study results can provide a theoretical reference for the design of multi-support excavation.
High Serum Irisin Concentration Is Associated with More Disturbed Behavioural Eating Pattern in Adolescent Rhythmic Gymnasts
Authors: Remmel Liina , Jürimäe Jaak , Tamm Anna-Liisa , Purge Priit , Tillmann Vallo
Published: November 2024

Background/Objectives: There are strict demands on body weight and shape in highly trained adolescent female athletes, and they are in the highest risk group for the development of eating disorders. This study aims to compare the behavioural eating patterns between highly trained female adolescent athletes and untrained controls (UCs), and to describe the associations between behavioural eating patterns and different energy homeostasis hormones. Methods: A total of 33 rhythmic gymnasts (RGs), 20 swimmers (SWs), and 20 UCs (n = 20) that were 14 to 18 years old participated in this investigation. Anthropometric measurements, body composition, training volume, 3-consecutive-day energy intake, and different energy homeostasis hormones were measured. For the evaluation of the individual behavioural eating pattern, an eating disorders assessment scale (EDAS) questionnaire with different subscales was used. Results: The mean EDAS subscale of restrained eating score was significantly higher in the RG group compared to the UC group (17.2 ± 7.4 vs. 11.5 ± 5.8; p < 0.05). The EDAS total score (r = 0.380) and the subscale score of preoccupation with body image and body weight (r = 0.371) were both positively correlated (p < 0.05) with serum irisin concentrations in the RG group. Conclusions: In conclusion, female rhythmic gymnasts reported a more often restrained eating pattern than untrained controls, and their more disturbed behavioural eating pattern was associated with a higher serum irisin concentration.
Risk Factors for Postoperative Intra-Abdominal Abscess in Pediatric Perforated Appendicitis Following Laparoscopic Appendectomy: A Multicenter Analysis
Authors: Son Joonhyuk , Han Ji-Won , Oh Chaeyoun
Published: November 2024

Background: Perforated appendicitis in children is a frequently encountered and significant surgical condition. The treatment of choice is laparoscopic appendectomy, but this carries a risk of postoperative intra-abdominal abscess (IAA). The purpose of this study was to determine risk factors linked to the occurrence of IAA following laparoscopic surgery in pediatric perforated appendicitis. Methods: This retrospective cohort study analyzed 137 children with perforated appendicitis who received laparoscopic appendectomy at four tertiary hospitals between March 2018 and December 2022. Data on patient demographics, preoperative clinical characteristics, and surgical details were collected. Independent risk factors for IAA formation were determined using logistic regression analysis. Results: The overall incidence of postoperative IAA was 10.9%. Prolonged symptom duration and elevated CRP levels were associated with higher IAA rates. Patients who developed IAAs experienced prolonged postoperative fevers and longer hospital stays. Significant risk factors for IAA identified through multivariable analysis included a higher severity grade of appendicitis (≥Grade IV, OR 5.9, p = 0.034) and the presence of a free appendicolith during surgery (OR 5.549, p = 0.01). Of the patients who developed IAAs, nine (60%) improved with conservative treatment, while six (40%) required invasive procedures. Conclusions: A higher severity grade of appendicitis (≥Grade IV) and the presence of a free appendicolith are significant predictors of postoperative IAAs in pediatric perforated appendicitis. Recognizing these factors can help guide clinical management and postoperative care, potentially reducing the incidence of this complication.
Is There an Association Between Cesarean Section Delivery with Specific Learning Disabilities (SLD) or/and Attention-Deficit/Hyperactivity Disorder (ADHD)? A Cross-Sectional Study in Greek Population
Authors: Makri Maria A. , Chaniotis Dimitrios , Vivilaki Victoria G. , Papageorgiou Effie G.
Published: November 2024

Background/Objective: Learning difficulties (LDs) are lifelong neurodevelopmental disorders with multifactorial causes, including perinatal factors like mode of delivery. This study aims to explore whether cesarean section (CS) delivery is linked to the occurrence of specific learning disabilities (SLDs), attention-deficit/hyperactivity disorder (ADHD), or their comorbidity. Methods: An online questionnaire was distributed via Google Forms to Greek mothers and parents of children with and without diagnoses, shared through school-related groups and various Greek pages focused on child development, special education, and learning difficulties. Conducted over eight months (October 2023–May 2024), this cross-sectional study involved 256 children, 137 with LDs diagnoses, and 119 controls. Results: In total, 59.9% of CS-born children had a diagnosis, compared to 40.1% of those born vaginally (X²(1) = 4.19, p = 0.045). CS delivery was associated with a 68% increased likelihood of LDs (OR = 1.68, 95% CI [1.02, 2.76]), with higher risks for ADHD (OR = 2.25, 95% CI [1.06, 4.79]) and comorbid SLD/ADHD diagnoses (OR = 2.75, 95% CI [1.17, 6.46]). Stratified analyses showed birthweight and gestational age as effect modifiers rather than confounders. Key postnatal risk factors identified were family history (OR = 4.65, 95% CI [2.41, 8.94]) and language acquisition difficulties (OR = 5.28, 95% CI [1.36, 20.47]). Conclusions: The findings suggest a possible association between CS and LDs, along with a novel link between CS and increased comorbidities. These results underscore the need for further research and provide valuable insights into how CS delivery may influence the risk of LDs, depending on the type of diagnosis.
In Silico and In Vitro Studies to Explore the Effect of Thymoquinone on Isocitrate Lyase, Biofilm Formation, and the Expression of Some Virulence Genes in Candida albicans
Authors: Khan Masood Alam , Azam Mohd , Younus Hina
Published: November 2024

Thymoquinone (TQ), a bioactive compound from black cumin (Nigella sativa), has demonstrated a broad range of therapeutic effects. The aim of this study is to evaluate the antifungal efficacy of TQ by targeting key virulence factors in Candida albicans, specifically focusing on isocitrate lyase (ICL) activity, biofilm formation, and gene expression. This study explored TQ’s impact on ICL, a decisive enzyme in the glyoxylate cycle, along with its effect on hyphal formation, biofilm development, and the virulent gene expression of C. albicans through in silico and in vitro studies. Molecular docking revealed a binding energy of −6.4 kcal/mol between TQ and ICL, indicating moderate affinity. The stability of the ICL-TQ complex was validated through 50 ns molecular dynamics simulations, showing the root mean square deviation (RMSD) values of 0.35 nm for ICL and 0.38 nm for the complex. In vitro studies further validated these findings, showing a dose-dependent inhibition of ICL activity. TQ at 2 µg/mL reduced enzyme activity by 57%, and at 4 µg/mL, by 91.4%. Additionally, TQ disrupted the yeast-to-hyphae switch, a key virulence factor, with 1 and 2 µg/mL doses significantly inhibiting hyphal formation. The biofilm formation was similarly affected, with a 58% reduction at 2 µg/mL and an 83% reduction at 4 µg/mL. TQ also downregulated the ALS1 and HWP1 genes that are associated with adhesion and biofilm development, demonstrating its broad-spectrum antifungal activity. These findings suggest that TQ is a promising candidate for antifungal therapies, targeting multiple virulence factors in C. albicans and potentially overcoming biofilm-associated drug resistance. Future research should focus on in vivo validation, optimization for clinical applications, and expanding its spectrum against other drug-resistant fungal species.
Micropulse Laser Therapy in Central Serous Chorioretinopathy
Authors: Bodea Flaviu , Radu Andrei-Flavius , Bodog Ruxandra-Florina , Bodog Teodora Maria , Nicula Cristina Ariadna
Published: November 2024

Background: Central serous chorioretinopathy (CSCR) is a retinal condition characterized by the accumulation of subretinal fluid, often linked to elevated levels of endogenous corticosteroids and stress-related hormones, which can lead to visual disturbances. This connection may explain the association of CSCR with high stress levels and the use of corticosteroid medications. Although many cases resolve spontaneously, persistent or severe instances may require intervention. Case Description: Our report presents a case of acute CSCR in a 33-year-old male who developed the condition following corticosteroid treatment for acute parotiditis and left submandibular lymphadenopathy. Initial presentation was 6 weeks after corticosteroid treatment was initiated. Diagnostic evaluation with optical coherence tomography (OCT) and fluorescein angiography confirmed the presence of subretinal fluid at the retinal pigment epithelium–Bruch’s membrane complex. Micropulse laser therapy (MPLT) was applied to address the leakage points, leading to significant fluid reduction at a two-week follow-up. By six weeks, the complete resolution of subretinal fluid was documented, with substantial visual recovery. Conclusions: This case confirms MPLT as an effective treatment for CSCR, particularly when conservative management is insufficient. Unlike traditional photocoagulation, MPLT offers a safer alternative, minimizing the risk of retinal damage, such as permanent scotomas. Clinical Significance: This case underscores the importance of carefully monitoring patients undergoing corticosteroid therapy for potential ocular complications and highlights the role of MPLT as a safe and effective option for managing persistent CSCR, protecting the surrounding retinal tissue from damage while achieving significant therapeutic outcomes.
Creating a Foundation for the Visualization of Intracranial Cerebrospinal Fluid Using Photon-Counting Technology in Spectral Imaging for Cranial CT
Authors: Klempka Anna , Neumayer Philipp , Schröder Alexander , Ackermann Eduardo , Hetjens Svetlana , Clausen Sven , Groden Christoph
Published: November 2024

Background: Recent advancements in computed tomography (CT), notably in photon-counting CT (PCCT), are revolutionizing the medical imaging field. PCCT’s spectral imaging can better visualize tissues based on their material properties. This research aims to establish a fundamental approach for the in vivo visualization of intracranial cerebrospinal fluid (CSF) using PCCT. Methods: PCCT was integrated to distinguish the CSF within the intracranial space with spectral imaging. In this study, we analyzed monoenergetic +67 keV reconstructions alongside virtual non-contrast and iodine phase images. This approach facilitated the assessment of the spectral characteristics of CSF in patients who did not present with intra-axial pathology or inflamation. Results: Our findings illustrate PCCT’s effectiveness in providing distinct and clear visualizations of intracranial CSF structures, building a foundation. The signal-to-noise ratio was quantified across all measurements, to check in image quality. Conclusions: PCCT serves as a robust, non-invasive platform for the detailed visualization of intracranial CSF. This technology is promising in enhancing diagnostic accuracy through different conditions.
Volumetric Analysis of Motor Cortex and Basal Ganglia in Pediatric Celiac Disease Patients Using volBrain: Implications for Neurological Dysfunction-Preliminary Results
Authors: Murn Filip , Loncar Lana , Lenicek Krleza Jasna , Roic Goran , Hojsak Iva , Misak Zrinjka , Tripalo Batos Ana
Published: November 2024

Background/Objectives: Celiac disease (CD) is a common immune-mediated, chronic systemic disorder that is treated with a strict, life-long gluten-free diet (GFD). In addition to gastrointestinal manifestations, CD also presents with a variety of extraintestinal symptoms, including significant neurological and neuropsychiatric symptoms. Among these neurological manifestations, motor dysfunctions are particularly notable. The aim of this study is to investigate the potential volumetric differences in brain structures, particularly the motor cortex and basal ganglia, between pediatric CD patients and healthy controls using the volBrain software AssemblyNet version 1.0. Methods: This prospective study included pediatric patients with CD who complained of neurological symptoms and were scheduled for brain magnetic resonance imaging (MRI). All children had been previously diagnosed with CD and their adherence to GFD was evaluated using the Biagi score. Brain MRIs were performed on all included patients to obtain volumetry at the onset of the disease. For volumetric and segmentation data, the volBrain software was used. Results: In total, 12 pediatric patients with CD were included, with a median duration of a GFD of 5.3 years at the time of the MRI examination. There were no statistically significant differences between patients compliant with the GFD and those non-compliant in terms of age or duration of GFD. Volumetric analysis revealed deviations in all patients analyzed, which involved either a decrease or increase in the volume of the structures studied. Conclusion: Despite the limited number of patients in this study, the initial findings support previously described neurological manifestations in patients with CD. Newly developed MRI tools have the potential to enable a more detailed analysis of disease progression and its impact on the motor cortex.
Policy Options to Support Climate-Conscious Urban Water Planning
Authors: Sowby Robert B. , Jones Daniel R. , George Grant A.
Published: November 2024

Urban water systems are increasingly vulnerable to climate change. Traditional planning, often based on past conditions, fails to address these new challenges. We suggest policy options for integrating climate scenarios into urban water planning, which will enhance the resilience of drinking water, wastewater, and stormwater systems. The policy options are (1) requiring climate scenario analysis in planning processes, (2) developing climate-resilient infrastructure standards, (3) promoting low-impact development and nature-based solutions, (4) creating regional planning bodies, (5) educating professionals for climate-responsive planning, and (6) securing funding for climate adaptation. We discuss our experience in the state of Utah, USA, and summarize case studies in Copenhagen, New York, and Melbourne. The policy options align with Sustainable Development Goals and offer a roadmap for building adaptable, sustainable urban water systems.
Exploring the Stratified Nature of Artificial Intelligence Research Funding in United States Educational Systems: A Bibliometric and Network Analysis
Authors: Taylor Zachary W. , Stan Kayla
Published: November 2024

Little is known about the funding organizations and mechanisms behind artificial intelligence (AI) research conducted in United States (U.S.) educational systems (K12 and higher education). This study therefore performs a bibliometric and network analysis of AI research conducted in U.S. educational systems to explore which types of organizations fund peer-reviewed scholarship, which organizations receive this funding, and how these organizations form funded research networks. The results suggest evidence of institutional stratification, with non-U.S. government organizations (such as in China and Europe) funding many AI studies within U.S. educational systems. Moreover, the data suggest stratified funding networks have marginalized Minority-Serving Institutions, consolidating the influence of AI research conducted in U.S. educational systems among few, elite, and predominately White institutions. The implications for research and policy advocacy are also addressed.
An Exploratory Study to Test the Psychometric Properties of Character Strengths-Semantic Differential Scale (CS-SDS) Among Singaporean Adults
Authors: Ma Cecilia M. S. , Tan Chee Soon , Koh Koon Teck
Published: November 2024

Character strengths encompass a set of positive traits that can be manifested through thoughts, feelings, and behaviors. To measure the 24 character strengths, the Character Strengths-Semantic Differential Scale (CS-SDS) was used. The aim of the study was to (a) test the factor structure of CS-CDS and (b) test the convergent validity of CS-CDS with life satisfaction and positive affect, and the divergent validity of CS-SDS with negative affect. In total, 283 Singaporean students (96 males, 35.3%), with a median age of 24–26 years old (42.9%), participated in this study. Exploratory (EFA) and confirmatory factor analyses (CFA) showed the multi-dimensional nature of CS-SDS. Specifically, EFA demonstrated a four-factor model, while CFA identified a five-factor model, showing the dimensions of interpersonal, emotional, restraint, theological, and intellectual. All factors were significantly related to life satisfaction, positive affect, and negative affect. It was concluded that CS-SDS is a psychometrically sound instrument for measuring character strengths in the Asian context. This tool can be used for designing strength-based interventions aimed at promoting well-being and character among students in higher education.
Near-Data Source Graph Partitioning
Authors: Chang Furong , Guo Hao , Ullah Farhan , Wang Haochen , Zhao Yue , Zhang Haitian
Published: November 2024

Recently, numerous graph partitioning approaches have been proposed to distribute a big graph to machines in a cluster for distributed computing. Due to heavy communication overhead, these graph partitioning approaches always suffered from long ingress times. Also, heavy communication overhead not only limits the scalability of distributed graph-parallel computing platforms but also reduces the overall performance of clusters. In order to address this problem, this work proposed a near-data source parallel graph partitioning approach noted as NDGP. In NDGP, an edge was preferentially distributed to the machine where it was stored. We implemented NDGP over two classic graph partitioning approaches, Random and Greedy, and one most recently proposed graph partitioning approach, OLPGP, and evaluated its effectiveness. Extensive experiments conducted on real-world data sets verified the effectiveness of NDGP on reducing the communication overhead in the graph partitioning process and demonstrated that NDGP does not induce additional communication and computing workload to the graph-distributed computing that follows.
ANFIS-PSO-Based Optimization for THD Reduction in Cascaded Multilevel Inverter UPS Systems
Authors: Sánchez Vargas Oscar , Vela Valdés Luis Gerardo , Borunda Monica , Lozoya-Ponce Ricardo Eliú , Aguayo Alquicira Jesus , De León Aldaco Susana Estefany
Published: November 2024

Uninterruptible Power Supplies (UPSs) protect electronic equipment by delivering consistent power. Among the core components of a UPS is the inverter, which converts stored DC energy from batteries into AC power. This work focuses on a cascaded multilevel inverter topology for its ability to reduce voltage Total Harmonic Distortion (THD), which is essential for maintaining UPS efficiency and power quality. Using an ANFIS (Adaptive Neuro-Fuzzy Inference System) model, enhanced with the Particle Swarm Optimization (PSO) algorithm, the switching angles were optimized to minimize THD. This work focused on an online UPS with a seven-level inverter structure powered by three LifePo4 S17 batteries, with critical load levels (100%, 95%, 50%, 15%, and 5%) represented in 35 experimental cases. The experimental design allowed the ANFIS-PSO model to adapt to varying voltages, achieving robust THD reduction. The results demonstrated that this combination of ANFIS and PSO provided effective angle optimization, with a low standard deviation of 0.06 between the training and simulated %THD, highlighting the process’s accuracy. The analysis showed that, in most cases, the simulated THD values closely aligned with, or even improved upon, the calculated values, with discrepancies not exceeding 0.2%. These findings support the ANFIS-PSO model’s potential in enhancing power electronics applications, particularly in critical sectors like renewable energy and power transmission, where THD minimization is crucial.
Directorial Editing: A Hybrid Deep-Learning Approach to Content-Aware Image Retargeting and Resizing
Authors: Dickman Elliot , Diefenbach Paul
Published: November 2024

Image retargeting is a common computer graphics task which involves manipulating the size or aspect ratio of an image. This task often presents a challenge to the artist or user, because manipulating the size of an image necessitates some degree of data loss as pixels need to be removed to accommodate a different image size. We present an image retargeting framework which implements a confidence map generated by a segmentation model for content-aware resizing, allowing users to specify which subjects in an image to preserve using natural language prompts much like the role of an art director conversing with their artist. Using computer vision models to detect object positions also provides additional control over the composition of the retargeted image at various points in the image-processing pipeline. This object-based approach to energy map augmentation is incredibly flexible, because only minor adjustments to the processing of the energy maps can provide a significant degree of control over where seams—paths of pixels through the image—are removed, and how seam removal is prioritized in different sections of the image. It also provides additional control with techniques for object and background separation and recomposition. This research explores how several different types of deep-learning models can be integrated into this pipeline in order to easily make these decisions, and provide different retargeting results on the same image based on user input and compositional considerations. Because this is a framework based on existing machine-learning models, this approach will benefit from advancements in the rapidly developing fields of computer vision and large language models and can be extended for further natural language directorial controls over images.
Mapping Computer Vision Syndrome: An Engineering Problem in Human–Computer Interaction
Authors: Viduka Dejan , Dimitrijević Vanja , Rastovac Dragan , Gligorijević Milan , Bašić Ana , Maričić Srđan , Jokić Stevan
Published: November 2024

Computer Vision Syndrome (CVS) is a highly prevalent syndrome today, yet it remains relatively understudied, leading to limited awareness among users about this syndrome and its preventive measures. This study aims to draw attention to this syndrome among authors and researchers and encourage further research in this area. Data were retrieved from the databases PubMed, Lens, Scopus, and Google Scholar, compiling existing articles and publications from the CVS domain. Analyses cover the period from 1 January to 31 December 2023. Zotero 6.0.27, VOSviewer 1.6.20, and Microsoft Excel software were used for data analysis. A total of 893 papers were reviewed, with 578 papers included in our analysis. The study presents five different analyses showing top authors and publishers, publication trends over the years, as well as papers by source, and, finally, the most frequently used keywords. The results highlight trends in various aspects related to this issue, through the analysis of published articles over the years, along with prominent authors and their respective countries. The focus of this research is on computer vision syndrome and its representation in scientific databases. What is clearly evident from this study is the increasing trend in research over the years, as well as the leading countries in these studies. However, it is also apparent that further research in this area is needed to bring new insights to researchers and raise awareness among users who encounter computers in their daily work.
A Thermal Impedance Model for IGBT Modules Considering the Nonlinear Thermal Characteristics of Chips and Ceramic Materials
Authors: Wang Yingying , Liang Zuhuo , Jin Bolin , Pang Jindi
Published: November 2024

The traditional method of calculating junction temperature does not consider the dependence of a material’s thermal conductivity on temperature, in which the thermal conductivity changes with temperature. However, with an increase in junction temperature, the temperature sensitivity (TS) will have a more significant impact on the actual temperature of chips. This study established an improved IGBT equivalent thermal impedance model that considers the nonlinear characteristics of the TS of chips and ceramic materials. The Fourier series analysis method was used to obtain the heat flux density curve, and then the heat diffusion angles of each layer were solved. Moreover, iterations were performed until the thermal conductivity and temperature of the chip and ceramic layers matched the nonlinear characteristics of the TS. When the power loss was less than 200 W, the maximum error of the junction temperature calculated by the proposed method considering TS was 3%, while the maximum error of the method without considering TS was 9.5%. Compared with the finite element simulation, the proposed method has a faster solving speed and high accuracy. The proposed method only requires the input material parameters, size parameters, and boundary conditions to solve the junction temperature, which has strong practicality and high accuracy.
Hybrid-DC: A Hybrid Framework Using ResNet-50 and Vision Transformer for Steel Surface Defect Classification in the Rolling Process
Authors: Jeong Minjun , Yang Minyeol , Jeong Jongpil
Published: November 2024

This study introduces Hybrid-DC, a hybrid deep-learning model integrating ResNet-50 and Vision Transformer (ViT) for high-accuracy steel surface defect classification. Hybrid-DC leverages ResNet-50 for efficient feature extraction at both low and high levels and utilizes ViT’s global context learning to enhance classification precision. A unique hybrid attention layer and an attention fusion mechanism enable Hybrid-DC to adapt to the complex, variable patterns typical of steel surface defects. Experimental evaluations demonstrate that Hybrid-DC achieves substantial accuracy improvements and significantly reduced loss compared to traditional models like MobileNetV2 and ResNet, with a validation accuracy reaching 0.9944. The results suggest that this model, characterized by rapid convergence and stable learning, can be applied for real-time quality control in steel manufacturing and other high-precision industries, enhancing automated defect detection efficiency.
End-Region Losses in High-Power Electrical Machines: Impact of Material Thickness on Eddy Current Losses in Clamping Structures
Authors: Mohand Oussaid Walid , Tounzi Abdelmounaïm , Romary Raphaël , Benabou Abdelkader , Boughanmi Walid , Laloy Daniel
Published: November 2024

High-power electrical machines often utilize clamping structures composed of various materials with specific geometric dimensions to secure the stator laminations. These structures are exposed to end-region magnetic flux, which induces eddy currents, leading to significant power losses that reduce the machine’s efficiency. This study systematically investigates the impact of clamping plate thickness on eddy current losses across different materials and operating frequencies. A simplified experimental configuration was established to validate the numerical model developed using 3D Finite Element Method (FEM). This model was used to calculate the eddy current losses and analyze the influence of plate thickness under various conditions. A comprehensive parametric analysis was performed, revealing critical insights into the relationship between material properties, plate thickness, and loss generation. The findings indicate that while thinner plates exhibit higher current density, thicker plates provide a larger volume for current flow, resulting in varying loss patterns depending on the material’s electrical and magnetic properties. The study’s results offer valuable guidance for optimizing clamping structure designs in high-power electrical machines by selecting materials and thicknesses that minimize losses while maintaining mechanical integrity.
Study of Ionanofluids Behavior in PVT Solar Collectors: Determination of Thermal Fields and Characteristic Length by Means of HEATT® Platform
Authors: Alarcón Mariano , Luna-Abad Juan-Pedro , Seco-Nicolás Manuel , Moulefera Imane , Víllora Gloria
Published: November 2024

Solar electric and solar thermal energies are often considered as part of the solution to the current energy emergency. The pipes of flat plate solar devices are normally heated by their upper surfaces giving rise to an asymmetric temperature field in the bulk of the fluid, which influences the heat transfer process. In the present work, a study of the characteristic length of tubes, or most efficient distance at which heat transfer occurs, in flat photovoltaic-thermal (PVT) hybrid solar devices has been carried out using three heat transfer fluids: water, [Emim]Ac ionic liquid and ionanofluid of graphene nanoparticles suspended in the former ionic liquid. The mean objective of the study was to know whether the heat transfer occurs in optimal conditions. Experimental measurements have been made on a commercial PVT device, and numerical simulations have been performed using the HEATT® platform to determine the characteristic length of the process. The tests conducted showed a clear improvement in the temperature jump of the fluid inside the collector when INF is used compared to water and ionic liquid and even a higher overall energy efficiency. Electricity generation is not greatly affected by the fluid used, although it is slightly higher when water is used. Slower fluid velocities are recommended if high fluid outlet temperatures are the goal of the application, but this penalizes the overall thermal energy production. The characteristic process length is not typically achieved in parallel tube PVT collectors with ordinary flow rates, which would require a speed, and consequently, a flow rate, about 10 times lower, which penalizes the performance (up to four times), although it increases the fluid outlet temperature by 234%, which can be very interesting in certain applications. Ionanofluids may in the medium term become an alternative to water in flat plates or vacuum solar collectors for applications with temperatures close to or above 100 °C, when their costs will hopefully fall. The results and methodology developed in this work are applicable to solar thermal collectors other than PVT collectors.
Effect of Mixed Culture and Organic Loading Rate over Butanol Production from Biodiesel Waste in an Upflow Packed-Bed Reactor
Authors: Alves Tottoli e Silva Cristina Aglaia , Adorno Maria Ângela Tallarico , Ferreira Filipe Vasconcelos , Peixoto Guilherme
Published: November 2024

In this study, an upflow anaerobic packed-bed reactor (UAPB) produced biobutanol from the main byproduct of biodiesel plants, commonly known as glycerol. Currently, butanol production is mostly limited to pure cultures and sterilized feedstocks. Using glycerol wastes from biodiesel production demands a new paradigm because sterilization is not economically feasible for the elevated amount of glycerol generated by the biodiesel industry. Different microbial consortia were evaluated as inoculum sources to convert glycerol to butanol. In the first stage, operations were carried out with an average organic loading rate (OLR) of 13 g COD L−1 d−1. Kefir grains, sucrose auto-fermentation consortium, and heat-treated anaerobic sludge produced 16.7, 48.5, and 12.8 mg of butanol per gram of chemical oxygen demand (COD), respectively. Besides butanol production, a significant amount of ethanol (241.5 mg g−1 COD), acetate (30.3 mg g−1 COD), and butyrate (183.4 mg g−1 COD) were generated with glycerol processed by sucrose auto-fermentation consortium. In the second stage, the organic loading rates of 6.5, 13.0, and 26.0 g COD L−1 d−1 were applied to the UAPB reactor inoculated with sucrose auto-fermentation consortium. The OLR of 13.0 g COD L−1 d−1 yielded the highest production of butanol (41.5 mg g−1 COD) and generated other valuable co-products such as butyrate (246.1 mg g−1 COD), acetate (37.3 mg g−1 COD), and propionate (19.6 mg g−1 COD).
Interactions Between Corn Starch and Ethyl Maltol Under Heat-Moisture Treatment and Its Application in Fried Chicken Nuggets
Authors: Xu Meijuan , Liu Tianwen , Gao Xueqin , Shi Yuran , Zhao Xiaodong , Zou Jian
Published: November 2024

This study delved into the interaction between corn starch and ethyl maltol during innovative repeated continuous heat-moisture treatment (RCHMT) and its impact on the quality of fried chicken nuggets. The results reveal that the complexation ratio of ethyl maltol is about 31.6%, and the complex creates dense microporous structures. Native starch and complex samples exhibited an A-type crystal structure, while the physical mixture sample showed superposition peaks of starch and ethyl maltol. Additionally, the peak of C-O-H def., CH2 of the complex sample was blue-shifted to the larger wave number, and the hydrogen bond structure was enhanced. Moreover, the complex exhibited a higher resistant starch content and lower hydrolysis rate and amylose content than the physical mixture sample. The starch–ethyl maltol complex has been demonstrated to be a non-inclusion compound. It has been shown to reduce oil absorption and enhance the crispness of fried chicken nuggets, matching that of commercial products. This finding provides a direction for the development of innovative coating powders.
Spore-Forming Clostridia in Raw Cow Milk from Northern Italy: A Trend Analysis over the Past 20 Years
Authors: Guaita Arianna , Gambi Lorenzo , Baresi Pierluigi , Paterlini Franco , Bolzoni Giuseppe , Zanardi Giorgio , Daminelli Paolo
Published: November 2024

Clostridium species are known for their impact on animal and human health, but also for the spoilage of foodstuffs. Their spores contaminate milk and result in germination and gas production, the latter being particularly evident in the cheeses that suffer severe depreciation. To address this issue, the Primary Production Department of the IZSLER institute in Brescia, Italy conducts the Most Probable Number (MPN) method on bovine milk samples collected from Northern Italian dairies between 2004 and 2023. This approach leverages two semi-quantitative protocols, S2 and S3, to detect Clostridium species spore forms upon customer request. Here, we would like to present an a-posteriori analysis on the results of the S2 and S3 protocols. The goal of this study is to highlight the differences between these two methods and provide evidence of the actual decrease in Clostridium species in raw cow milk over a 20-year period. Our analysis shows that client demand for S2 has progressively decreased, while S3’s has remained constant, and both protocols reveal a significant reduction in positives; furthermore, S3’s greater sensitivity made it more responsive to environmental changes. This highlights the necessity of choosing the appropriate testing protocol that accounts for both regulatory standards and environmental factors. Overall, our findings underscore the importance of continued monitoring to manage Clostridium species contamination and ensure milk quality.
Delayed Healthcare Due to Cost Among Adults with Multimorbidity in the United States
Authors: Azubuike Chidimma Doris , Alawode Oluwatobi Abel
Published: November 2024

Background/Objectives: Multimorbidity, defined as two or more chronic diseases co-occurring in an individual, has been linked to elevated healthcare utilization and out-of-pocket expenses. Yet, the barriers to healthcare access due to the health profile of multimorbid adults are underexplored. This study investigates the differences in delayed healthcare due to cost among adults with multimorbidity and those with one chronic disease condition. Methods: Data from the National Health Interview Survey from the years 2016–2018 and 2020–2021 were examined. The sample included 13,439 adults with at least one of the chronic disease conditions outlined by the US Department of Health and Human Services. Logistic regression models were used to estimate odd ratios of delayed healthcare due to cost among participants. Results: Multimorbid adults were 1.29 times more likely to delay healthcare compared to adults living with one chronic disease (p < 0.01). Other influencing factors include being female, Asian, unmarried, uninsured, age, worsening self-rated health, region, and poverty threshold of 100–199%. Conclusions: Our findings highlight the disparities in healthcare success experienced by adults living with multimorbidity and indicate the need for policymakers to implement targeted measures such as subsidized costs for comorbidities to alleviate the financial burdens experienced by this population.
Exploring the Insider–Outsider Status of Postgraduate Students in Leading Lesson Study
Authors: Calleja James , Formosa Laura
Published: November 2024

Lesson study, a collaborative teacher professional development approach, has gained popularity internationally and leading the process with teachers plays a key role in making it sustainable in schools. This paper, which draws on a postgraduate university course for prospective school leaders, examines the dynamic roles in leading lesson study. Drawing on the literature on lesson study and leadership, we analyse how postgraduate students lead lesson study while navigating their status as an insider–outsider. Using a theoretical lens informed by the insider–outsider researcher debate, we propose a classification framework to understand lesson study leaders’ statuses. Presenting two case studies, we explore the strategies for the selection of LS participants, communication, and trust-building, as well as the leaders’ dilemmas and learning opportunities. Drawing on the findings, we highlight the central role of reflective practice in leading lesson study and offer insights for practitioners. This study sheds light on the nuanced dynamics of leading lesson study and its implications for the preparation of prospective leaders.
Classifying the Shapes of Buildings by Combining Distance Field Enhancement and a Convolution Neural Network
Authors: Zou Xinyan , Yang Min , Li Siyu , Hu Hai
Published: November 2024

The shape classification of building objects is crucial in fields such as map generalization and spatial queries. Recently, convolutional neural networks (CNNs) have been used to capture high-level features and classify building shape patterns based on raster representations. However, this raster-based deep learning method binarizes the areas into building and non-building zones and does not account for the distance information between these areas, potentially leading to the loss of shape feature information. To address this limitation, this study introduces a building shape classification method that incorporates distance field enhancement with a CNN. In this approach, the distance from various pixels to the building boundary is fused into the image data through distance field enhancement computation. The CNN model, specifically InceptionV3, is then employed to learn and classify building shapes using these enhanced images. The experimental results indicate that the accuracy of building shape classification improved by more than 2.5% following distance field enhancement. Notably, the classification accuracies for F-shaped and T-shaped buildings increased significantly by 4.34% and 11.76%, respectively. Moreover, the proposed method demonstrated a strong performance in classifying other building datasets, suggesting its substantial potential for enhancing shape classification in various applications.
Prevalence of Neoplasms in Patients with Acromegaly—A Single-Center Polish Study
Authors: Strzelec Martyna , Rolla Małgorzata , Kuliczkowska-Płaksej Justyna , Kałużny Marcin , Słoka Natalia , Wronowicz Jakub , Bolanowski Marek , Jawiarczyk-Przybyłowska Aleksandra
Published: November 2024

Background/Objectives: Neoplasms are one of the three most common causes of death in patients with acromegaly. Our study aimed to assess the incidence of benign and malignant neoplasms among patients with acromegaly and the associations between this prevalence and the disease activity, the time of acromegaly diagnosis, and the time of its first symptoms. The correlation between neoplasm occurrence and pituitary somatotropic axis hormone levels was also studied, and the prevalence of different types of neoplasms was compared between the patients with acromegaly and the Polish population. Methods: A retrospective study included a statistical analysis of the medical documentation of 230 patients with acromegaly diagnosed and treated in the Department of Endocrinology, Diabetes, and Isotope Therapy in Wrocław (Poland) between 1976 and 2023. Results: We observed 171 cases of neoplasms (144 benign and 27 malignant). All types of neoplasms and benign tumors were diagnosed more frequently, in both the short and long term, after a diagnosis of acromegaly, but, after a long time, only malignant neoplasms were more frequently diagnosed. In the cases of controlled acromegaly, all types of neoplasms and benign neoplasms were more common than in cases of cured acromegaly. The incidence of neoplasms was higher, regardless of type, in patients with active acromegaly compared to the cured disease. Malignant neoplasms of the thyroid, renal, and stomach type were more common among our subjects compared to the Polish population. Conclusions: This study confirms the association between acromegaly, as well as its activity level and the time from its diagnosis, and the prevalence of neoplasms.
Evaluation of Dental Panoramic Radiographs by Artificial Intelligence Compared to Human Reference: A Diagnostic Accuracy Study
Authors: Turosz Natalia , Chęcińska Kamila , Chęciński Maciej , Sielski Marcin , Sikora Maciej
Published: November 2024

Background/Objectives: The role of artificial intelligence (AI) in dentistry is becoming increasingly significant, particularly in diagnosis and treatment planning. This study aimed to assess the sensitivity, specificity, accuracy, and precision of AI-driven software in analyzing dental panoramic radiographs (DPRs) in patients with permanent dentition. Methods: Out of 638 DPRs, 600 fulfilled the inclusion criteria. The radiographs were analyzed by AI software and two researchers. The following variables were assessed: (1) missing tooth, (2) root canal filling, (3) endodontic lesion, (4) implant, (5) abutment, (6) pontic, (7) crown, (8) and sound tooth. Results: The study revealed very high performance metrics for the AI algorithm in detecting missing teeth, root canal fillings, and implant abutment crowns, all greater than 90%. However, it demonstrated moderate sensitivity and precision in identifying endodontic lesions and the lowest precision (65.30%) in detecting crowns. Conclusions: AI software can be a valuable tool in clinical practice for diagnosis and treatment planning but may require additional verification by clinicians, especially for identifying endodontic lesions and crowns. Due to some limitations of the study, further research is recommended.
Comparison of Refractive Outcomes After Phacoemulsification and Combined 25-Gauge Phacovitrectomy with Implantation of Plate-Haptic Toric Intraocular Lenses
Authors: Buhl Lara , Langer Julian , Kruse Franziska , Mohr Niklas , Kreutzer Thomas , Mayer Wolfgang , Kassumeh Stefan , Priglinger Siegfried
Published: November 2024

Objectives: To compare intraocular lens (IOL) position and refractive outcomes between eyes that underwent sole phacoemulsification with those that underwent combined 25-gauge phacovitrectomy with a plate-haptic toric IOL implantation. Methods: This retrospective study included 60 eyes of 60 patients. Of these, 30 eyes underwent 25-gauge phacovitrectomy, while the other 30 eyes received phacoemulsification alone. In both groups, a plate-haptic toric intraocular lens (AT Torbi 709M, Carl Zeiss Meditec AG) was implanted. The main outcome measures were the refractive outcome, the refraction prediction error (PE), the difference in the postoperative anatomical lens position (ALP) change, and rotational stability. Results: The mean spherical equivalent decreased considerably from −2 ± 4.4 diopters (D) to −0.6 ± 1.4 D after phacovitrectomy (p = 0.05) and −0.7 D ± 5.5 D to −0.1 ± 1.1 D after phacoemulsification (p = 0.5). The prediction error (PE) was comparable between the two groups for all formulas (Haigis-T: p = 0.8, Barrett TK Toric: p = 0.8, Z CALC: p = 0.7). No significant difference in absolute ALP change and postoperative rotational stability was observed between the phacovitrectomy and phacoemulsification group (1.4 mm vs. 1.4 mm, p = 0.96; 2.9° vs. 2.1°, p = 0.5). Conclusions: The implantation of plate-haptic toric IOLs in the combined phacovitrectomy group resulted in refraction and IOL positioning outcomes comparable to those in the phacoemulsification-only group.
Correction: Liu et al. (2023). Testing the Reciprocal Effect between Value of Education, Time Investment, and Academic Achievement in a Large Non-Western Sample. Journal of Intelligence 11: 1333
Authors: Liu Meimei , Vu TuongVan , van Atteveldt Nienke , Meeter Martijn
Published: November 2024

In a recent paper, while our overall conclusion remains valid, one specific finding—that there are reciprocal relationships between how Korean students value education, the time they invest in their studies, and their academic achievements—requires correction (Liu et al [...]