bluuebunny/crossref_metadata_2025 huggingface dataset:
Prostate Cancer in Transplant Receivers—A Narrative Review on Oncological Outcomes
Authors: Hanusz Karolina , Domański Piotr , Strojec Kacper , Zapała Piotr , Zapała Łukasz , Radziszewski Piotr
Published: October 2023

Prostate cancer (PCa) is a low tumor mutational burden (TMB) cancer with a poor response to immunotherapy. Nonetheless, immunotherapy can be useful, especially in metastatic castration-resistant PCa (mCRPC). Increased cytotoxic T lymphocytes (CTLs) density is correlated with a shorter overall survival (OS), an early biochemical relapse, and a generally poor PCa prognosis. An increased number of CCR4+ regulatory T cells (CCR4 + Tregs) relates to a higher Gleason score or earlier progression. The same therapeutic options are available for renal transplant recipients (RTRs) as for the population, with a comparable functional and oncological outcome. Radical retropubic prostatectomy (RRP) is the most common method of radical treatment in RTRs. Brachytherapy and robot-assisted radical prostatectomy (RARP) seem to be promising therapies. Further studies are needed to assess the need for prostatectomy in low-risk patients before transplantation. The rate of adverse pathological features in RTRs does not seem to differ from those observed in the non-transplant population and the achieved cancer control seems comparable. The association between PCa and transplantation is not entirely clear. Some researchers indicate a possible association between a more frequent occurrence of PCa and a worse prognosis in advanced or metastatic PCa. However, others claim that the risk and survival prognosis is comparable to the non-transplant population.
Novel Pathogenic Variants in the Gene Encoding Stereocilin (STRC) Causing Non-Syndromic Moderate Hearing Loss in Spanish and Argentinean Subjects
Authors: Domínguez-Ruiz María , Ruiz-Palmero Laura , Buonfiglio Paula I. , García-Vaquero Irene , Gómez-Rosas Elena , Goñi Marina , Villamar Manuela , Morín Matías , Moreno-Pelayo Miguel A. , Elgoyhen Ana B. , del Castillo Francisco J. , Dalamón Viviana , del Castillo Ignacio
Published: October 2023

Non-syndromic hearing impairment (NSHI) is a very heterogeneous genetic condition, involving over 130 genes. Mutations in GJB2, encoding connexin-26, are a major cause of NSHI (the DFNB1 type), but few other genes have significant epidemiological contributions. Mutations in the STRC gene result in the DFNB16 type of autosomal recessive NSHI, a common cause of moderate hearing loss. STRC is located in a tandem duplicated region that includes the STRCP1 pseudogene, and so it is prone to rearrangements causing structural variations. Firstly, we screened a cohort of 122 Spanish familial cases of non-DFNB1 NSHI with at least two affected siblings and unaffected parents, and with different degrees of hearing loss (mild to profound). Secondly, we screened a cohort of 64 Spanish sporadic non-DFNB1 cases, and a cohort of 35 Argentinean non-DFNB1 cases, all of them with moderate hearing loss. Amplification of marker D15S784, massively parallel DNA sequencing, multiplex ligation-dependent probe amplification and long-range gene-specific PCR followed by Sanger sequencing were used to search and confirm single-nucleotide variants (SNVs) and deletions involving STRC. Causative variants were found in 13 Spanish familial cases (10.7%), 5 Spanish simplex cases (7.8%) and 2 Argentinean cases (5.7%). In all, 34 deleted alleles and 6 SNVs, 5 of which are novel. All affected subjects had moderate hearing impairment. Our results further support this strong genotype–phenotype correlation and highlight the significant contribution of STRC mutations to moderate NSHI in the Spanish population.
Identification of Potential Drug Targets for Antiplatelet Therapy Specifically Targeting Platelets of Old Individuals through Proteomic Analysis
Authors: Lee Seung Hee , Cho Suyeon , Lee Jong Youl , Hong Jung Yeon , Kim Suji , Jeong Myong-Ho , Kim Won-Ho
Published: October 2023

Aging is a growing problem worldwide, and the prevalence and mortality of arterial and venous thromboembolism (VTE) are higher in the elderly than in the young population. To address this issue, various anticoagulants have been used. However, no evidence can confirm that antithrombotic agents are suitable for the elderly. Therefore, this study aims to investigate the platelet proteome of aged mice and identify antithrombotic drug targets specific to the elderly. Based on the proteome analysis of platelets from aged mice, 308 increased or decreased proteins were identified. Among these proteins, three targets were selected as potential antithrombotic drug targets. These targets are membrane proteins or related to platelet function and include beta-2-glycoprotein 1 (β2GP1, ApolipoproteinH (ApoH)), alpha-1-acid glycoprotein2 (AGP2, Orosomucoid-2 (Orm2)), and Ras-related protein (Rab11a).
Multi-Disciplinary Approach to Skull Base Paragangliomas
Authors: Curry Steven D. , Kocharyan Armine , Lekovic Gregory P.
Published: October 2023

The treatment of skull base paragangliomas has moved towards the use of cranial nerve preservation strategies, using radiation therapy and subtotal resection in instances when aiming for gross total resection would be expected to cause increased morbidity compared to the natural history of the tumor itself. The goal of this study was to analyze the role of surgery in patients with skull base paragangliomas treated with CyberKnife stereotactic radiosurgery (SRS) for definitive tumor control. A retrospective review identified 22 patients (median age 65.5 years, 50% female) treated with SRS from 2010–2022. Fourteen patients (63.6%) underwent microsurgical resection. Gross total resection was performed in four patients for tympanic paraganglioma (n = 2), contralateral paraganglioma (n = 1), and intracranial tumor with multiple cranial neuropathies (n = 1). Partial/subtotal resection was performed for the treatment of pulsatile tinnitus and conductive hearing loss (n = 6), chronic otitis and otorrhea (n = 2), intracranial extension (n = 1), or episodic vertigo due to perilymphatic fistula (n = 1). Eighteen patients had clinical and imaging follow-up for a mean (SD) of 4.5 (3.4) years after SRS, with all patients having clinical and radiological tumor control and no mortalities. Surgery remains an important component in the multidisciplinary treatment of skull base paraganglioma when considering other outcomes besides local tumor control.
Chinese Private Preschool Teachers’ Teaching Readiness and Teacher–Child Relationships: The Chain Mediation Effects of Motivation to Teach and Self-Efficacy
Authors: Li Hui , Chen Wei , He Huihua , Luo Wenwei
Published: October 2023

The teacher–child relationship is a key element in measuring the quality of childcare institutions and is essential to the current and future physical and mental developmental outcomes of children. The purpose of this study is to investigate the role of private preschool teachers’ readiness to teach in influencing the teacher–child relationship, and to explore the mechanisms by which teachers’ motivation and self-efficacy mediate their readiness to teach and the teacher–child relationship. Online questionnaires were administered to 289 early-childhood teachers in Shanghai, China. The findings of the study indicated a significant and positive correlation between early-childhood teachers’ readiness to teach and the quality of the teacher–child relationship. In addition, early-childhood teachers’ internal motivation to teach and self-efficacy mediated their readiness to teach and the teacher–child relationship, respectively. However, teachers’ external motivation did not mediate the effect of teaching readiness on the quality of the teacher–child relationship. Moreover, teachers’ motivation to teach (encompassing both internal and external factors) and their self-efficacy played chained roles in mediating the relationships between teaching readiness and the teacher–child relationship. This study highlights the significant roles of teaching readiness and instructional motivation, along with self-efficacy, in cultivating positive teacher–child relationships within early-childhood education settings.
The Effectiveness of Spraying nTiO2 on Coating Mortars in Historical Buildings Aimed at Reducing Fungal Growth
Authors: Guerra Fernanda Lamego , Giordani Caroline , Zucchetti Lais , Ribas Rodolfo , Masuero Angela Borges , Dal Molin Denise Carpena Coitinho , Bento Fatima Menezes
Published: October 2023

In historic mortars, the main binder used are calcitic or dolomitic lime. However, these mortars are also susceptible to the biochemical action of fungi causing undesirable changes in those materials. Nanotechnology has been investigated as a strategy to mitigate the deterioration of the cultural heritage. Photocatalysis has proven effective as an agent of degradation of organic contamination by inhibiting the recolonization of substrates affected by biological growth. This study verifies the effectiveness of a nanometric photocatalyst (nTiO2-P25, 3% in deionized water) sprayed on the surface of simple lime–sand mortar (1:4 mass trace), typically used in historical buildings, against the growth of Aspergillus niger fungal isolates, inoculated with a 106 spore/mL suspension. The samples were exposed to the incidence of artificial radiation of UVA light with a wavelength of 285 nm to activate the nTiO2. We observed a reduction in fungal colonies, especially after four hours of exposure per day, reaching 100% in the staining reduction in one case. Another aspect observed was that the previous application of nTiO2 on the mortar samples caused alterations in the morphology of the A. niger fungus structures, evidence of a disturbance in the growth of the colonies or even their reduction over time.
Effect of Nano-Clay Dispersion on Pore Structure and Distribution of Hardened Cement Paste
Authors: Wu Hongjuan , Chen Chengqin , Zhang Wei , Wang Rui , Zhang Wengang
Published: October 2023

Nano-clay has the potential to improve the properties of cement-based materials. However, the effectiveness of this improvement is influenced by the dispersion of the nano-clay. The effects of different nano-clay dispersion techniques on cement-based material properties and pore structure complexity were studied. The samples were prepared using manual and mechanical dispersion methods. The mechanical properties of the specimens were evaluated, and the pore characteristics of the cement-based materials were analysed using mercury intrusion porosimetry. The study investigated the effect of the dispersion method on the nano-clay dispersion. The complexity of the pore structure was evaluated using a fractal model, and the relationship between the fractal dimension, mechanical properties, and pore structure was analysed. The findings indicate that mechanical dispersion results in better dispersion than manual dispersion, and the mechanical properties of mechanical dispersion are superior to those of manual dispersion. Nano-clay particles can improve the internal pore structure of cement materials. Through mathematical calculation, the surface fractal dimension is between 2.90 and 2.95, with good fractal characteristics. There is a good correlation between the surface fractal dimension and the mechanical properties. The addition of nano-clay can reduce the complexity of the pore structure, and the fractal dimension has an excellent linear relationship with the pore structure.
Empirical Case Study on Applying Artificial Intelligence and Unmanned Aerial Vehicles for the Efficient Visual Inspection of Residential Buildings
Authors: Shin Hyunkyu , Kim Jonghoon , Kim Kyonghoon , Lee Sanghyo
Published: October 2023

Continuous inspections and observations are required to preserve the safety and condition of buildings. Although the number of deteriorated buildings has increased over the years, traditional inspection methods are still used. However, this approach is time-consuming, costly, and carries the risk of poor inspection owing to the subjective intervention of the inspector. To overcome these limitations, many recent studies have developed advanced inspection methods by integrating unmanned aerial vehicles (UAVs) and artificial intelligence (AI) methods during the visual inspection stage. However, the inspection approach using UAV and AI can vary in operation and data acquisition methods depending on the building structures. Notably, in the case of residential buildings, it is necessary to consider how to operate UAVs and how to apply AI due to privacy issues of residents and various exterior contour shapes. Thus, an empirical case study was adopted in this study to explore the integration of UAVs and artificial intelligence (AI) technology to inspect the condition of structures, focusing on residential buildings. As a result, this study proposed the field-adopted UAV operation method and AI-based defect detection model for adopting the residential buildings. Moreover, the lessons learned from holistic and descriptive analyses, which include drone application limitations, points of improvement of data collection, and items to be considered when AI and UAV based inspection for residential buildings, are summarized in this paper. The discussed problems and results derived from this study can contribute to future AI- and UAV-based building inspections.
The Effects of Entrepreneurship Leadership on Youth Entrepreneurial Intentions Post-COVID-19: The Case of Gauteng
Authors: Lekutle Neo Titus , Ebewo Patrick Ebong , Shambare Richard
Published: October 2023

The purpose of this research was to assess the effects of entrepreneurship leadership on youth’s entrepreneurial intentions in Gauteng province, South Africa. To test this relationship and attempt to answer the research question, “To what extent does entrepreneurship leadership influence youth entrepreneurial intentions post-COVID-19?” a conceptual model supported by the theory of Planned Behaviour was adopted. Data were collected from 825 youths in Gauteng province, South Africa, through a self-administered questionnaire. The Likert scale was applied to the questionnaire. Entrepreneurship leadership was observed to directly relate to attitude towards entrepreneurship and perceived environmental support and entrepreneurial intentions and entrepreneurial action. Furthermore, the results provide evidence that the three antecedents of entrepreneurial intention: attitude towards entrepreneurship, perceived entrepreneurial abilities and perceived COVID-19 environment influence entrepreneurial intention. Participation in entrepreneurship leadership was observed to positively influence youth intentions to become entrepreneurs. Furthermore, policymakers are encouraged to ensure the implementation of regulations that are conducive to business operations and stimulate youth participation in entrepreneurial activities. The obtained results suggest that attitude towards entrepreneurship and perceived environmental support are observed to completely and partially mediate (respectively) the relationship between three independent variables (entrepreneurship leadership, perceived post-COVID-19 environment and entrepreneurship education) and entrepreneurship intention. Leadership in entrepreneurship is crucial as it creates direction for the business in the post-COVID-19 era. This study attempts to address the gap in the literature concerning the effects of entrepreneurial factors on entrepreneurial intentions through the use of Ajzen’s Theory of Planned Behaviour.
Cyclophilin E (CypE) Functions as a Positive Regulator in Osteoblast Differentiation by Regulating the Transcriptional Activity of Runx2
Authors: Piao Meiyu , Lee Sung Ho , Li Yuankuan , Choi Joong-Kook , Yeo Chang-Yeol , Lee Kwang Youl
Published: October 2023

Cyclophilin E (CypE) belongs to the cyclophilin family and exhibits peptidyl-prolyl cis-trans isomerase (PPIase) activity. It participates in various biological processes through the regulation of peptidyl-prolyl isomerization. However, the specific role of CypE in osteoblast differentiation has not yet been elucidated. In this study, we first discovered the positive impact of CypE on osteoblast differentiation through gain or loss of function experiments. Mechanistically, CypE enhances the transcriptional activity of Runx2 through its PPIase activity. Furthermore, we identified the involvement of the Akt signaling pathway in CypE’s function in osteoblast differentiation. Taken together, our findings indicate that CypE plays an important role in osteoblast differentiation as a positive regulator by increasing the transcriptional activity of Runx2.
Signaling Pathways Controlling Axonal Wrapping in Drosophila
Authors: Baldenius Marie , Kautzmann Steffen , Nanda Suchet , Klämbt Christian
Published: October 2023

The rapid transmission of action potentials is an important ability that enables efficient communication within the nervous system. Glial cells influence conduction velocity along axons by regulating the radial axonal diameter, providing electrical insulation as well as affecting the distribution of voltage-gated ion channels. Differentiation of these wrapping glial cells requires a complex set of neuron–glia interactions involving three basic mechanistic features. The glia must recognize the axon, grow around it, and eventually arrest its growth to form single or multiple axon wraps. This likely depends on the integration of numerous evolutionary conserved signaling and adhesion systems. Here, we summarize the mechanisms and underlying signaling pathways that control glial wrapping in Drosophila and compare those to the mechanisms that control glial differentiation in mammals. This analysis shows that Drosophila is a beneficial model to study the development of even complex structures like myelin.
A Themed Issue in Honor of Prof. Dr. Vicente Rives
Authors: Vicente Miguel Angel , Trujillano Raquel , Labajos Francisco M.
Published: October 2023

Professor Vicente Rives developed a very long and fruitful career as a teacher of Inorganic Chemistry and Materials Chemistry and has been a dedicated researcher in these and related fields [...]
2D vs. 3D Ultrasound Diagnosis of Pediatric Supracondylar Fractures
Authors: Knight Jessica , Alves-Pereira Fatima , Keen Christopher E. , Jaremko Jacob L.
Published: October 2023

Supracondylar fractures are common injuries in children. Diagnosis typically relies on radiography, which can involve long wait times in the ED, emits ionizing radiation, and can miss non-displaced fractures. Ultrasound (US) has the potential to be a safer, more convenient diagnostic tool, especially with new highly portable handheld 2D point of care US (POCUS). This study aimed to determine the reliability of 2D POCUS for the detection of supracondylar fractures and elbow joint effusions, to contrast the accuracy of 2D POCUS vs. 3DUS vs. radiographs, and to determine whether blinded image interpretation could produce similar results to non-blinded real-time imaging. Fifty-seven children were scanned with 2D POCUS and 3DUS on the affected elbow. US scans were then read by three blinded readers, and the results were compared to gold-standard radiographs. Compared to a gold standard of 30-day radiographic diagnosis, readers of 2D POCUS detected supracondylar fracture and effusion with sensitivities of 0.91 and 0.97, respectively, which were both higher than with 3DUS. Inter-rater reliability of fracture detection was moderate for 2D POCUS (k = 0.40) and 3DUS (k = 0.53). Consensus sensitivities, although high, were lower than reports from some non-blinded studies, indicating that clinical presentation serves as an important factor in detection rates. Our results from consensus US diagnosis support the validity of using 2D POCUS in children for supracondylar fracture and elbow effusion diagnosis.
Pediatric Hyperglycemic Hyperosmolar Syndrome: A Comprehensive Approach to Diagnosis, Management, and Complications Utilizing Novel Summarizing Acronyms
Authors: Zahran Naser Amin , Jadidi Shaheen
Published: October 2023

This paper focuses on hyperglycemic hyperosmolar syndrome (HHS), a unique hyperglycemic state requiring divergent diagnosis and treatment approaches from diabetic ketoacidosis (DKA) despite some shared characteristics. We introduce the mnemonic DI-FF-ER-EN-CE-S to encapsulate unique HHS management and complications. ‘DI’ emphasizes the need to delay and decrease initial insulin therapy until serum glucose decline is managed by fluid resuscitation alone. ‘FF’ stresses the importance of double fluid replacement compared to DKA due to severe dehydration and ‘ER’ electrolyte replacement due to profound losses and imbalances. ‘EN’ denotes the potential for encephalopathy and the requirement for a controlled serum osmolality reduction. ‘CE’ indicates cerebral edema, a rare complication in HHS. ‘S’ signifies systemic multiorgan failure. We categorize the associated risks into three mnemonic groups: the 3Rs (renal failure, respiratory distress, rhabdomyolysis), the 3Hs (heart failure, hypercoagulation, hyperthermia), and AP (arrhythmias, pancreatitis) to facilitate awareness and screening of HHS.
A Population Description of Young Women with Breast Cancer in Newfoundland and Labrador
Authors: Mahoney Meghan , Sriranganathan Saranga , Dowden Jeff , Seal Melanie
Published: October 2023

It has been well established in the literature that young women tend to carry more aggressive subtypes of breast cancer than their older-aged counterparts. The objective of this study was to describe the characteristics and outcomes of young women with breast cancer. In this retrospective analysis, data were collected for women under the age of 40 years who were diagnosed with breast cancer between 2008 and 2018 in the province of Newfoundland and Labrador. Specifically, data were collected on demographics, staging, pathological characteristics, treatment, and survival outcomes for young women with this disease. Results demonstrate that most of these women were diagnosed between the age of 35 and 39 years (91.2%). Most women presented with early-stage disease (stage I and II—66.4%), while 24% were stage III and 9.6% presented with stage IV metastatic disease. The prevalence of hormone-receptor-positive disease represented 41.9% of the cohort, with triple-negative and HER2+ measuring 27.7% and 30.4%, respectively. Five-year disease-free survival was 80.5% and overall survival was 82.7%. These findings provoke discussion regarding the intersecting roles of genetics, environment, and lifestyle in a region with some of the highest rates of malignancy in the country.
Bryophytes Present in the Nests of Birds in Yanayacu Biological Station, Ecuador
Authors: Benítez Ángel , Jaramillo Edison , Yangua-Solano Erika , Greeney Harold F.
Published: October 2023

Bryophytes are one of the main resources for bird nest construction; however, studies are limited and have been oriented to preliminary species lists. We evaluated for the first time in Ecuador the changes in the richness and composition of bryophytes in 17 nests of the species Myadestes ralloides and Catharus fuscater, of the family Turdidae. The presence/absence of bryophytes was recorded in each nest. A total of 25 bryophyte species were recorded (13 mosses and 12 liverworts). The most frequent species in the nests of the two species were the mosses Thuidium tomentosum and Meteoridium remotifolium and the liverworts Trichocolea flaccida and Frullania peruviana. The results indicated that bryophyte species’ richness and composition did not differ between the nests of the two studied bird species, because they select similar bryophyte species for nest elaboration. In general, our study showed that for the two species of birds of the family Turdidae, mosses and liverworts are key components in the elaboration of nests both internally and externally. On the other hand, we would suggest that further investigations should focus on analyzing the relation between bird nests and bryophyte phytochemistry, as well as the functional traits of bryophytes.
Fractional Flow Reserve-Based Patient Risk Classification
Authors: Stanojević Pirković Marijana , Pavić Ognjen , Filipović Filip , Saveljić Igor , Geroski Tijana , Exarchos Themis , Filipović Nenad
Published: October 2023

Cardiovascular diseases (CVDs) are a leading cause of death. If not treated in a timely manner, cardiovascular diseases can cause a plethora of major life complications that can include disability and a loss of the ability to work. Globally, acute myocardial infarction (AMI) is responsible for about 3 million deaths a year. The development of strategies for prevention, but also the early detection of cardiovascular risks, is of great importance. The fractional flow reserve (FFR) is a measurement used for an assessment of the severity of coronary artery stenosis. The goal of this research was to develop a technique that can be used for patient fractional flow reserve evaluation, as well as for the assessment of the risk of death via gathered demographic and clinical data. A classification ensemble model was built using the random forest machine learning algorithm for the purposes of risk prediction. Referent patient classes were identified by the observed fractional flow reserve value, where patients with an FFR higher than 0.8 were viewed as low risk, while those with an FFR lower than 0.8 were identified as high risk. The final classification ensemble achieved a 76.21% value of estimated prediction accuracy, thus achieving a mean prediction accuracy of 74.1%, 77.3%, 78.1% and 83.6% over the models tested with 5%, 10%, 15% and 20% of the test samples, respectively. Along with the machine learning approach, a numerical approach was implemented through a 3D reconstruction of the coronary arteries for the purposes of stenosis monitoring. Even with a small number of available data points, the proposed methodology achieved satisfying results. However, these results can be improved in the future through the introduction of additional data, which will, in turn, allow for the utilization of different machine learning algorithms.
The Calculation and Evaluation of an Ultrasound-Estimated Fat Fraction in Non-Alcoholic Fatty Liver Disease and Metabolic-Associated Fatty Liver Disease
Authors: Kaposi Pál Novák , Zsombor Zita , Rónaszéki Aladár D. , Budai Bettina K. , Csongrády Barbara , Stollmayer Róbert , Kalina Ildikó , Győri Gabriella , Bérczi Viktor , Werling Klára , Maurovich-Horvat Pál , Folhoffer Anikó , Hagymási Krisztina
Published: October 2023

We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (UEFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. We measured and retrospectively collected the ultrasound attenuation coefficient (AC), backscatter-distribution coefficient (BSC-D), and liver stiffness (LS) using shear wave elastography (SWE) in 90 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD), and 51 patients with clinically suspected metabolic-associated fatty liver disease (MAFLD). The MRI-PDFF was also measured in all patients within a month of the ultrasound scan. In the linear regression analysis, only AC and BSC-D showed a significant association with MRI-PDFF. Therefore, we developed prediction models using non-linear least squares analysis to estimate MRI-PDFF based on the AC and BSC-D parameters. We fitted the models on the NAFLD dataset and evaluated their performance in three-fold cross-validation repeated five times. We decided to use the model based on both parameters to calculate UEFF. The correlation between UEFF and MRI-PDFF was strong in NAFLD and very strong in MAFLD. According to a receiver operating characteristics (ROC) analysis, UEFF could differentiate between <5% vs. ≥5% and <10% vs. ≥10% MRI-PDFF steatosis with excellent, 0.97 and 0.91 area under the curve (AUC), accuracy in the NAFLD and with AUCs of 0.99 and 0.96 in the MAFLD groups. In conclusion, UEFF calculated from QUS parameters is an accurate method to quantify liver fat fraction and to diagnose ≥5% and ≥10% steatosis in both NAFLD and MAFLD. Therefore, UEFF can be an ideal non-invasive screening tool for patients with NAFLD and MAFLD risk factors.
Parameters of State in the Global Thermodynamics of Binary Ideal Gas Mixtures in a Stationary Heat Flow
Authors: Maciołek Anna , Hołyst Robert , Makuch Karol , Giżyński Konrad , Żuk Paweł J.
Published: October 2023

In this paper, we formulate the first law of global thermodynamics for stationary states of the binary ideal gas mixture subjected to heat flow. We map the non-uniform system onto the uniform one and show that the internal energy U(S*,V,N1,N2,f1*,f2*) is the function of the following parameters of state: a non-equilibrium entropy S*, volume V, number of particles of the first component, N1, number of particles of the second component N2 and the renormalized degrees of freedom. The parameters f1*,f2*, N1,N2 satisfy the relation (N1/(N1+N2))f1*/f1+(N2/(N1+N2))f2*/f2=1 (f1 and f2 are the degrees of freedom for each component respectively). Thus, only 5 parameters of state describe the non-equilibrium state of the binary mixture in the heat flow. We calculate the non-equilibrium entropy S* and new thermodynamic parameters of state f1*,f2* explicitly. The latter are responsible for heat generation due to the concentration gradients. The theory reduces to equilibrium thermodynamics, when the heat flux goes to zero. As in equilibrium thermodynamics, the steady-state fundamental equation also leads to the thermodynamic Maxwell relations for measurable steady-state properties.
Project-Based Inquiry (PBI) Global during a Pandemic: A New Learning Ecology Perspective
Authors: Himes Marie P. , Spires Hiller A. , Krupa Erin E. , Borden Margaret L. , Eagle Jessica L.
Published: October 2023

Building on new learning ecology theory and situated in the COVID-19 pandemic context, a qualitative research design was used to examine student and teacher perspectives on Project-Based Inquiry (PBI) Global. Drawing on Problem-Based Learning (PBL) and Project-Based Learning (PjBL), PBI Global supports participants toward engaging in inquiry-to-action aligned with the UN Sustainable Development Goals (SDGs). Data sources for this study included transcripts from student and teacher focus groups conducted before, during, and after the PBI Global process. Three themes emerged (1) creating global awareness of water issues, (2) learning to collaborate in remote and hybrid contexts, and (3) enhancing self-efficacy through iterative learning. The discussion focuses on the affordances and challenges of engaging in PBL during non-voluntary online learning, as well as study limitations and directions for future research.
Maintaining Tensions: Braiding as an Analogy for Mathematics Teacher Educators’ Political Work
Authors: Myers Marrielle , Kokka Kari , Gutiérrez Rochelle
Published: October 2023

Although the field of mathematics education has made gains in centering the need for justice-oriented approaches and antiracist teaching practices in teacher education, much of this work remains in its infancy. Moreover, research focused on this area highlights teacher candidates’ knowledge and dispositions and often ignores the role of the mathematics teacher educators facilitating the process. We contend that mathematics teacher educators must pay more attention to how intersectional identities, contexts, Mirror Tests, and principles of Rehumanizing Mathematics manifest in teacher education to better understand how teacher candidates develop political knowledge in teaching mathematics. To this end, we introduce a framework of considerations, which we call a compass, that identifies four dimensions (or strands) and offers guiding questions for mathematics teacher educators to consider. We offer examples from a multi-site research study to illuminate each dimension and build the case for the necessity of braiding the four strands together as we engage in this line of work. Implications for practice and future research are discussed.
Correlation between High School Students’ Computational Thinking and Their Performance in STEM and Language Courses
Authors: Bounou Aikaterini , Lavidas Konstantinos , Komis Vassilis , Papadakis Stamatis , Manoli Polyxeni
Published: October 2023

According to numerous researchers, a clear and direct correlation exists between Computational Thinking (CT) and courses falling under the purview of Science, Technology, Engineering, and Mathematics (STEM), thereby advocating for the integration of CT into the curricula of STEM courses. Nonetheless, it is noteworthy that only a few studies have scrutinized this correlation in-depth. Most such studies connect the correlation tacitly and predominantly concentrate on the empirical assessment of CT within the curriculum of one STEM discipline. This research seeks to evaluate the Computational Thinking abilities of 80 high school students in Greece and discern the extent of correlation with their academic performance in STEM and Greek language courses. A longitudinal survey was executed to accomplish this objective, commencing with administering a test designed to gauge the fundamental components of Computational Thinking. It is worth noting that this test draws its inspiration from internationally recognized computer competitions and serves as a credible assessment tool. Subsequently, an assessment was carried out to ascertain the degree of correlation between students’ Computational Thinking aptitude and their written performance in the subjects encompassed by the STEM category and the Greek language courses. The outcomes of this investigation revealed the presence of a statistically significant correlation between students’ Computational Thinking proficiency and their performance in these academic subjects, further extending to the academic direction of study chosen by the students. Based on the findings of this research, implications and pedagogical recommendations are delineated while concurrently acknowledging the limitations encountered during this study.
Federated Learning Based on Mutual Information Clustering for Wireless Traffic Prediction
Authors: Zhang Jianwei , Hu Xinhua , Cai Zengyu , Zhu Liang , Feng Yuan
Published: October 2023

Wireless traffic prediction can help operators accurately predict the usage of wireless networks, and it plays an important role in the load balancing and energy saving of base stations. Currently, most traffic prediction methods are centralized learning strategies, which need to transmit a large amount of traffic data and have timeliness and data privacy issues. Federated learning, as a distributed learning framework with no client data sharing and multi-client collaborative training, can solve such problems. We propose a federated learning wireless traffic prediction framework based on mutual information clustering (FedMIC). First, a sliding window scheme is used to construct the raw data into adjacent and periodic dual-traffic sequences and capture their traffic characteristics separately to enhance the client model learning capability. Second, clients with similar traffic data distributions are clustered together using a mutual information-based spectral clustering algorithm to facilitate the capture of the personalized features of each clustered model. Then, models are aggregated using a hierarchical aggregation architecture of intra-cluster model aggregation and inter-cluster model aggregation to address the statistical heterogeneity challenge of federated learning and to improve the prediction accuracy of models. Finally, an attention mechanism-based model aggregation algorithm is used to improve the generalization ability of the global model. Experimental results show that our proposed method minimizes the prediction error and has superior traffic prediction performance compared to traditional distributed machine learning methods and other federated learning methods.
A Multichannel-Based CNN and GRU Method for Short-Term Wind Power Prediction
Authors: Gao Jian , Ye Xi , Lei Xia , Huang Bohao , Wang Xi , Wang Lili
Published: October 2023

Incorporating wind energy on a large scale into power systems presents challenges for the operation and control of the grid. To enhance the safety of power grid operation, accurate short-term forecasting of wind power is necessary, as it minimizes the impact of randomness. Considering the uncertainty and prediction issues associated with wind power, this paper introduces a CNN–GRU ultra-short-term wind power prediction model. This model relies on multichannel signals, including data such as wind speed, wind direction, climate conditions, and historical power outputs collected from wind farms. These data types contribute to the formation of a comprehensive multichannel signal for wind power. Following that, the CNN method extracts both global and partial features from these signals. Concurrently, features are extracted from past power outputs based on their time series. These features are then combined with the ones obtained from the convolution process. Subsequently, these combined features are input into a fully connected network. This step is crucial for blending multichannel information and generating forecast results. To validate the model, it was tested using data from a wind farm located in a specific region of Sichuan Province. According to our experimental results, the model demonstrates a high level of accuracy in computation and robust generalization ability.
Optimized Quantum Circuit for Quantum Security Strength Analysis of Argon2
Authors: Song Gyeongju , Eum Siwoo , Kwon Hyeokdong , Sim Minjoo , Lee Minwoo , Seo Hwajeong
Published: October 2023

This paper explores the optimization of quantum circuits for Argon2, a memory-hard function used in password hashing applications. With the rise of quantum computers, the security of classical cryptographic systems is at risk. This paper emphasizes the need to accurately measure the quantum security strength of cryptographic schemes through highly optimized quantum circuits for the target cryptography algorithm. The proposed method focuses on two perspectives: qubit reduction (qubit-optimized quantum circuit) and depth reduction (depth-optimized quantum circuit). The qubit-optimized quantum circuit was designed to find a point where an appropriate inverse is possible and reuses the qubit through the inverse to minimize the number of qubits. The start and end points of the inverse are determined by identifying a point where qubits can be reused with minimal computation. The depth-optimized quantum circuit reduces the depth of the quantum circuit by using the minimum number of qubits necessary without performing an inverse operation. The trade-off between qubit and depth is confirmed by modifying the internal structure of the circuits and the quantum adders. The qubit optimization achieved up to a 12,229 qubit reduction, while the depth optimization resulted in an approximately 196,741 (approximately 69.02%) depth reduction. In conclusion, this research demonstrates the importance of implementing and analyzing quantum circuits from multiple optimization perspectives. The results contribute to the post-quantum strength analysis of Argon2 and provide valuable insights for future research on optimized quantum circuit design, considering the appropriate trade-offs of quantum resources in response to advancements in quantum computing technology.
Resonator-Loaded Waveguide Notch Filters with Broad Tuning Range and Additive-Manufacturing-Based Operating Frequency Adjustment Procedure
Authors: Haq Tanveerul , Koziel Slawomir , Pietrenko-Dabrowska Anna
Published: October 2023

This article presents a new class of ring-resonator-loaded waveguide notch filters with a broad tuning range, low cost, and improved performance. The proposed approach employs a complementary asymmetric split-ring resonator coupled to a microstrip transmission line and excited in a rectangular waveguide. An equivalent circuit model is proposed to explain the working principle of the proposed notch filter. The adjustment of the operating frequency is based on the additive manufacturing of a metallic copper patch allocated on the microstrip transmission line, which enables extensive tuning capabilities and consistent performance with minimum variations across the tuning window. For demonstration purposes, a filter employing a WR-28 waveguide and photolithography-manufactured resonator is prototyped and experimentally validated. The measured results indicate a broad 8 GHz tuning range with a consistent insertion loss, ranging from 23.4 to 31.4 GHz. An inverse regression model is constructed using measurement data obtained for tuning patches of various sizes, which allows for determining the relationships between the operating frequency and the copper patch size. The resulting calibration curve enables rapid filter tuning to the required frequency by inserting metallic patches of the model-predicted size.
Design of a Multi-Standard UWB-LoRa Antenna Structure and Transceiver Board for High-Accuracy and Long-Range Localization Applications
Authors: Benouakta Amina , Nguyen Thao Manh , Ferrero Fabien , Lizzi Leonardo , Staraj Robert
Published: October 2023

Long-Range Wide-Area Networks (LoRaWAN) allow the transmission of data via radio link from sensors, which are potentially isolated or difficult to access, to gateways and servers that are connected to cellular networks for data processing, exchange, or relay, with low transmission power. This concept employs Long-Range (LoRa) modulation and has led to the emergence of many applications for the monitoring and tracking of objects. However, due to its characteristic of a low data rate for low-power communication, the transmission of information with LoRa technology is not suitable for the fast real-time monitoring of data. Additionally, due to its narrow bandwidth, an attempt to perform localization through the LoRa modulation technique will result in very limited accuracy because of its inability to resolve multipath problems. Thus, in this paper, we propose a multi-standard Ultra-Wide Bandwidth (UWB) and LoRa end-device that is capable of measuring location with high accuracy using UWB technology and then transmitting the location information through LoRa method to gateways and the Internet of Things Network. The results of measurements in indoor and outdoor scenarios show a UWB localization accuracy that is of sub-meter level, being between 10 and 33 cm, and a UWB range of 124 m in Line-of-Sight (LOS) and 55 m in Non-Line-of-Sight (NLOS) applications, respectively.
Influence of Interface Morphology on the Thermal Stress Distribution of SOFC under Inhomogeneous Temperature Field
Authors: Xie Jiamiao , Li Jingyang , Hao Wenqian , Wang Fenghui
Published: October 2023

Excessive thermal stress can cause the failure of a solid oxide fuel cell (SOFC), and an inhomogeneous temperature field is one of the reasons for thermal stress in the cell. In the present work, the bi-dimensional thermo-mechanical coupling models of SOFCs with different interface morphologies including planar and corrugated cells are proposed. The temperature distribution of two types of cells under the action of heat conduction is analyzed. Further, the inhomogeneous temperature field caused by gas flow is used as the thermal load to compare the thermal stress distribution of planar and corrugated cells. The influence of interface morphology on the temperature distribution, stress distribution and the contribution of the temperature gradient to stress distribution are investigated. This research provides a reference for reducing thermal stress and improving the stability of SOFC.
Measurement Data-Based Estimation of the Suitability of Existing Properties for the Operation of x to Water Heat Pumps Using a Seed of 100 Multi-Family Houses and Different Power Shifting Approaches
Authors: Jurkschat Simon , Sehr Florian Felix , Fransen Karsten , Beblek Andre , Grinewitschus Viktor
Published: October 2023

The German government’s ambitious goal of achieving CO2 neutrality by 2045 has prompted a focus on improving building insulation as a vital step toward energy efficiency. However, in this process, existing radiators and boilers are often left unchanged. Moreover, during the construction of buildings, heating systems are often designed with excess capacity to ensure there is no risk of insufficient heat supply during operation. This research presents various approaches to reduce the required radiator supply temperature, utilizing data from a study conducted in 100 multifamily buildings. The approaches encompass reducing the heat reserve, shifting the heat output, optimizing radiator utilization, and conducting heat demand analysis. The findings reveal that in pre-existing buildings equipped with radiators, it is possible to significantly lower supply temperatures without affecting the indoor temperature. Applied on the seed, reducing the heat reserve could reduce the median temperature by 18.5 K, thus curtailed by the most utilized radiator in the median to 7 K. Furthermore, the heat demand analysis showed that the consumption could decrease in the median by 13%, the peaks in median even by 29%. While each approach is analyzed individually, their combined implementation has the potential to considerably enhance the efficiency of water-to-water heat pumps, thanks to the reduced requirement for high supply temperatures.
Optimizing Instrument Transformer Performance through Adaptive Blind Equalization and Genetic Algorithms
Authors: Resende Denise Fonseca , Silva Leandro Rodrigues Manso , Nepomuceno Erivelton Geraldo , Duque Carlos Augusto
Published: October 2023

In real-world scenarios, deviations in the frequency response of instrumentation transformers can lead to distorted harmonic measurements, highlighting the critical role harmonic measurement plays in assessing power quality. The blind channel equalization technique offers a potential solution to improve the frequency response of a large number of instrumentation transformers already installed in substations. These transformers were designed to accurately measure only the fundamental phasor component. Therefore, in order to use them for harmonic phasor measurement, methodologies for reducing frequency distortion must be applied. In this work, we propose a novel approach to improve the frequency response of the instrument transformer using adaptive blind equalization. The blind technique can compensate for distortions caused by voltage and current transducers without requiring prior knowledge of input signals or circuit characteristics. The proposed methodology uses a Linear Prediction Filter to convert the colored noise present at the channel output into white noise. Furthermore, a genetic algorithm is used to find a pole to cancel possible zeroes present in the frequency response of some transducers. The main advantage of blind equalization with the genetic algorithm is its independence, operating without clear information about the channel or the input signal. Through extensive experimentation, we demonstrate the effectiveness of the proposed methodology in significantly reducing the absolute error in ratio and phase caused by current and voltage transformers. Simulated and laboratory experiments are presented in this paper.