bluuebunny/crossref_metadata_2025 huggingface dataset:
Hashimoto’s Thyroiditis and the Risk of Papillary Thyroid Cancer in Children
Authors: Gallant Jean-Nicolas , Weiss Vivian L. , Chen Sheau-Chiann , Liang Jiancong , Belcher Ryan H. , Ye Fei , Correa Hernan , Wang Huiying
Published: October 2023

The association between Hashimoto’s thyroiditis (HT) and pediatric thyroid cancer is controversial. Most studies examining this connection have been based on adults, and larger studies in children are lacking. We performed a retrospective study of all sequential pediatric patients who underwent a thyroidectomy for a neoplasm at our institution over a twenty-year period in order to explore the link between HT and pediatric thyroid cancer. A total of 153 patients, median age 16.5 (interquartile range [IQR] 14.2–18.3) years, underwent thyroid surgery for a neoplasm. Patients were mainly female (80%) and White (84%). Median follow-up was 58.6 (IQR 20.7–105.4) months. Thirty-five (23%) patients had HT. Patients who underwent thyroid surgery and had HT were more likely to harbor a malignant neoplasm (p = 0.05); specifically, papillary thyroid carcinoma (PTC, p = 0.02). There was a difference in the distribution of HT among the subtypes of PTC (p = 0.03). Despite this, there was no difference in terms of survival between patients with/without HT. In conclusion, children with a thyroid malignancy, specifically, PTC, are more likely to have HT. The association between HT and pediatric PTC appears to be subtype-specific but does not seem to affect patient survival.
Hematological Toxicities with PARP Inhibitors in Prostate Cancer: A Systematic Review and Meta-Analysis of Phase II/III Randomized Controlled Trials
Authors: Bowling Gartrell C. , Swargaloganathan Piragash , Heintz Carly , Madan Ravi A. , Eldhose Binil , Dobi Albert , Chesnut Gregory T.
Published: October 2023

Background: Poly ADP-ribose polymerase inhibitors (PARPis) are an important class of therapeutics for metastatic castration-resistant prostate cancer (mCRPC). Unlike hormone-based treatments for mCRPC, PARPis are not without drug-related hematological adverse events. Objective: To review the evidence on hematological toxicities, including anemia, thrombocytopenia, and neutropenia from PARPis in prostate cancer. Study Methodology: A systematic review and meta-analysis using the PRISMA guidelines was performed for phase II and III randomized controlled trials (RCTs) of PARPis in prostate cancer. PubMed, Embase, and Ovid All EBM reviews—Cochrane were queried from inception to 9 June 2023. The Mantel–Haenszel method was used to report risk ratios (RR) and 95% confidence intervals (CI) for all-grade and high-grade anemia, thrombocytopenia, and neutropenia toxicities. Results: The systematic review retrieved eight phase II and III RCTs; specifically, eight were included in the anemia, five in the all-grade thrombocytopenia and neutropenia, and four in the high-grade thrombocytopenia and neutropenia outcomes. Compared to a placebo and/or other non-PARPi treatments, PARPi use was associated with an increased risk of all-grade anemia (RR, 3.37; 95% CI, 2.37–4.79; p < 0.00001), thrombocytopenia (RR, 4.54; 95% CI, 1.97–10.44; p = 0.0004), and neutropenia (RR, 3.11; 95% CI, 1.60–6.03; p = 0.0008). High-grade anemia (RR, 6.94; 95% CI, 4.06–11.86; p < 0.00001) and thrombocytopenia (RR, 5.52; 95% CI, 2.80–10.88; p < 0.00001) were also associated with an increased risk, while high-grade neutropenia (RR, 3.63; 95% CI, 0.77–17.23; p = 0.10) showed no significant association. Subgroup stratification analyses showed differences in various all-grade and high-grade toxicities. Conclusion: PARPis were associated with an increased risk of hematological AEs. Future studies with more pooled RCTs will enhance this understanding and continue to inform patient–physician shared decision-making. Future studies may also have a role in improving the current management strategies for these AEs.
Mapping Cell-in-Cell Structures in Oral Squamous Cell Carcinoma
Authors: Siquara da Rocha Leonardo de Oliveira , Souza Bruno Solano de Freitas , Coletta Ricardo Della , Lambert Daniel W. , Gurgel Rocha Clarissa A.
Published: October 2023

Cell-in-cell (CIC) structures contribute to tumor aggressiveness and poor prognosis in oral squamous cell carcinoma (OSCC). In vitro 3D models may contribute to the understanding of the underlying molecular mechanisms of these events. We employed a spheroid model to study the CIC structures in OSCC. Spheroids were obtained from OSCC (HSC3) and cancer-associated fibroblast (CAF) lines using the Nanoshuttle-PLTM bioprinting system (Greiner Bio-One). Spheroid form, size, and reproducibility were evaluated over time (EvosTM XL; ImageJ version 1.8). Slides were assembled, stained (hematoxylin and eosin), and scanned (Axio Imager Z2/VSLIDE) using the OlyVIA System (Olympus Life Science) and ImageJ software (NIH) for cellular morphology and tumor zone formation (hypoxia and/or proliferative zones) analysis. CIC occurrence, complexity, and morphology were assessed considering the spheroid regions. Well-formed spheroids were observed within 6 h of incubation, showing the morphological aspects of the tumor microenvironment, such as hypoxic (core) and proliferative zone (periphery) formation. CIC structures were found in both homotypic and heterotypic groups, predominantly in the proliferative zone of the mixed HSC3/CAF spheroids. “Complex cannibalism” events were also noted. These results showcase the potential of this model in further studies on CIC morphology, formation, and relationship with tumor prognosis.
Age-Dependent Surface Receptor Expression Patterns in Immature Versus Mature Platelets in Mouse Models of Regenerative Thrombocytopenia
Authors: Pirabe Anita , Frühwirth Sabine , Brunnthaler Laura , Hackl Hubert , Schmuckenschlager Anna , Schrottmaier Waltraud C. , Assinger Alice
Published: October 2023

Aging is a multifaceted process that unfolds at both the individual and cellular levels, resulting in changes in platelet count and platelet reactivity. These alterations are influenced by shifts in platelet production, as well as by various environmental factors that affect circulating platelets. Aging also triggers functional changes in platelets, including a reduction in RNA content and protein production capacity. Older individuals and RNA-rich immature platelets often exhibit hyperactivity, contributing significantly to pathologic conditions such as cardiovascular diseases, sepsis, and thrombosis. However, the impact of aging on surface receptor expression of circulating platelets, particularly whether these effects vary between immature and mature platelets, remains largely unexplored. Thus, we investigated the expression of certain surface and activation receptors on platelets from young and old mice as well as on immature and mature platelets from mouse models of regenerative thrombocytopenia by flow cytometry. Our findings indicate that aged mice show an upregulated expression of the platelet endothelial cell adhesion molecule-1 (CD31), tetraspanin-29 (CD9), and Toll-like receptor 2 (TLR2) compared to their younger counterparts. Interestingly, when comparing immature and mature platelets in both young and old mice, no differences were observed in mature platelets. However, immature platelets from young mice displayed higher surface expression compared to immature platelets from old mice. Additionally, in mouse models of regenerative thrombocytopenia, the majority of receptors were upregulated in immature platelets. These results suggest that distinct surface receptor expressions are increased on platelets from old mice and immature platelets, which may partially explain their heightened activity and contribute to an increased thrombotic risk.
Gastronomy: An Overlooked Arena for the Cultivation of Sustainable Meaning?
Authors: Östergren Daniel , Walter Ute , Gustavsson Bernt , Jonsson Inger M.
Published: October 2023

This article explores sustainable development from a gastronomic perspective. Humanistic perspectives on food offered by gastronomy are explored as an asset in cultivating self-awareness capacities needed for sustainable transformations of society. The purpose is to explore how gastronomes can cultivate understandings and explanations of sustainability to be conveyed to individuals via meals. In semi-annually recurring dialogic interviews, four university-educated gastronomes cultivated their understandings and explanations of sustainability, and modeled how these could be communicated to other individuals. The dialogues gradually brought the ideas of the researcher and the participants toward a common explanation of the potential ways gastronomic competency could advance sustainable development. The results highlight two ways of understanding gastronomic sustainability: functionally as practical communication, and formally as a cultural issue. Based on H.G. Gadamer’s idea of bildung as hermeneutic interpretation, we argue that self-awareness is a process which is rooted in how knowledge is interpreted, understood, and explained by the individual. Practical participation in culturally influenced meals makes gastronomy a bridge between individual and societal issues, whereby gastronomic competencies can cultivate sustainable commitment, judgment, and community. In this way, gastronomic sustainability represents an approach to sustainable development that, significantly, also involves the cultivation of sustainable meaning.
Engineering Branched Au@Ag Nanostar Plasmonic Array for Coupling Electromagnetic Enhancement and SERS Trace Detection of Polystyrene in Aquatic Environments
Authors: Wu Mingzhu , Lin Jianhang , Zheng Da , Yang Yirui , Li Zhihao , Zhu Zhengdong , Shen Yonghui , Ni Gang , Zhang Maofeng
Published: October 2023

Micro/nanoplastics are widespread in the environment and may cause severe damage to creatures and human beings. Micro/nanoplastic pollution has become a global focus issue; hence, the rapid and accurate detection of micro/nanoplastics is an essential step to ensure health. Herein, we report a surface-enhanced Raman scattering (SERS) technique to sensitively and quantitatively identify micro/nanoplastics in environmental water samples. A three-dimensional hierarchical Au@Ag nanostar (NSs) was synthesized and employed as an efficient SERS substrate. The “lightning rod effect” generated by tip branches of the nanostars and the coupling effect of the neighboring branches of the nanostar array enabled the ultra-trace detection of crystal violet (CV) down to 10−9 M, even with a portable Raman device. Moreover, the hydrophobic property of the SERS substrate endowed it with a desirable enrichment effect, which meant an increase in the concentration or quantity of the micro/nanoplastic particles. And thereafter, the SERS sensor achieved a highly sensitive detection of polystyrene (PS) particle standard solution at a low concentration of 25 μg/mL or 2.5 μg/mL. Importantly, the detected concentration and the SERS intensity followed a nearly linear relationship, indicating the capability of quantitative analysis of micro/nanoplastics. In addition, the SERS sensor was successfully extended to detect PS particles in environmental water samples, including tap water, sea water, and soil water, and the detection concentration was determined to be 25 μg/mL, 2.5 μg/mL, and 25 μg/mL, respectively. The present Au@AgNSs array substrate with a two-order magnitude signal amplification further exhibited significant advantages in the label-free analysis of micro/nanoplastics in real water samples.
Nasal Nitric Oxide in Children: A Review of Current Outreach in Pediatric Respiratory Medicine
Authors: Mrkić Kobal Iva , Turkalj Mirjana , Plavec Davor
Published: October 2023

Nasal nitric oxide (nNO) is a gas synthesized by the inducible and constitutive NO synthase (NOS) enzyme in the airway cells of the nasal mucosa. Like lung nitric oxide, it is thought to be associated with airway inflammation in various respiratory diseases in children. The aim of our review was to investigate the current state of use of nNO measurement in children. A comprehensive search was conducted using the Web of Science and PubMed databases specifically targeting publications in the English language, with the following keywords: nasal NO, children, allergic rhinitis, chronic rhinosinusitis, acute rhinosinusitis, primary ciliary dyskinesia (PCD), and cystic fibrosis (CF). We describe the use of nNO in pediatric allergic rhinitis, chronic rhinosinusitis, acute rhinosinusitis, PCD, and CF based on the latest literature. nNO is a noninvasive, clinically applicable test for use in pediatric allergic rhinitis, chronic rhinosinusitis, acute rhinosinusitis, PCD, and CF. It can be used as a complementary method in the diagnosis of these respiratory diseases and as a monitoring method for the treatment of allergic rhinitis and acute and chronic rhinosinusitis.
Design and Performance Analysis of Hardware Realization of 3GPP Physical Layer for 5G Cell Search
Authors: Lodhi Khalid , Chhillar Jayant , Darak Sumit J. , Sharma Divisha
Published: October 2023

5G Cell Search (CS) is the first step for user equipment (UE) to initiate communication with the 5G node B (gNB) every time it is powered ON. In cellular networks, CS is accomplished via synchronization signals (SS) broadcasted by gNB. 5G 3rd generation partnership project (3GPP) specifications offer a detailed discussion on the SS generation at gNB, but a limited understanding of their blind search and detection is available. Unlike 4G, 5G SS may not be transmitted at the center of carrier frequency, and their frequency location is unknown to UE. In this work, we demonstrate the 5G CS by designing 3GPP compatible hardware realization of the physical layer (PHY) of the gNB transmitter and UE receiver. The proposed SS detection explores a novel down-sampling approach resulting in a 60% reduction in on-chip memory and 50% lower search time. Via detailed performance analysis, we analyze the functional correctness, computational complexity, and latency of the proposed approach for different word lengths, signal-to-noise ratio (SNR), and down-sampling factors. We demonstrate end-to-end 5G CS using GNU Radio-based RFNoC framework on the USRP-FPGA platform and achieve 66% faster SS search compared to software. The 3GPP compatibility and demonstration on hardware strengthen the commercial significance of the proposed work.
Evaluating the Impact of Redox Potential on the Corrosion of Q125, 316L, and C276 Steel in Low-Temperature Geothermal Systems
Authors: Bowman Samuel , Agrawal Vikas , Sharma Shikha
Published: October 2023

Time series experiments were used to explore the fluid redox impact on the corrosion of Q125, 316L, and C276 steels in low-ionic-strength and neutral water at temperature and pressure conditions associated with low-temperature geothermal systems. After exposing polished samples of each steel grade to an oxidizing (H2O2) and a reducing (Zn-doped) fluid for intervals of 24 h, 1 week, and 6 weeks, the atomic force microscopy results revealed general corrosion for Q125, while 316L and C276 exhibited pitting, crevice expansion, and edge attack corrosion. Secondary depositional features are frequently found as topographic highs, adjacent to pitting corrosion. These features may be identified as there is a very strong spatial correlation between the height retrace and phase retrace surface maps. All steels became progressively rougher over time after exposure to both fluids, while the corrosion rates were more complex. Samples exposed to the reducing fluid experienced an increase in the corrosion rate over time, while C276 and 316L experienced a decrease in the corrosion rate. Finally, a novel data validation technique was developed to address the intrinsic scalability of corrosion. The results indicate that the AFM scan area does not affect the measured surface roughness over nearly three orders of magnitude.
The Effects of Ti/Ni Doping on the Friction and Wear Properties of DLC Coatings
Authors: Zhang Shuling , Wu Shuaizheng , Huang Tenglong , Yang Xiangdong , Guo Feng , Zhang Bo , Ding Wenjie
Published: October 2023

Diamond-like carbon (DLC) coatings doped with Ti and Ni elements were deposited on 316 L stainless steel substrate using magnetron sputtering technology. The morphology, microstructures, and performances of the coatings were detected using scanning electron microscopy, a Raman spectrometer, nanoindenter, scratch tester, and a tribological machine. The effects of element doping on the microstructures, friction and wear properties of DLC coatings were analyzed. The results revealed that Ti/Ni doping ensures the uniform cover and tight fit of DLC coatings on the substrate. Additionally, Ni-doped DLC coatings have a much smoother surface and denser texture with higher bonding strength and enhanced hardness (7.5 GPa) though Ti doping also can improve the bond strength to some extent. The presence of Ni both in the 316 L substrate and in Ni-doped DLC coatings improves interface matching, decreases structural differences, and increases bonding strength. Moreover, the presence of Ni effectively inhibits oxidation and corrosion in friction interfaces, stabilizes the friction coefficient, and enhances wear resistance. Therefore, based on this study, it was concluded that reasonable matching between the dopant elements and the substrates can effectively improve the performance of DLC coatings.
What Insight Does the Alien Plant Species Richness in Greece Offer for the Different Invasion Biology Hypotheses?
Authors: Kallimanis Athanasios , Kokkoris Ioannis P. , Bazos Ioannis , Raus Thomas , Strid Arne , Dimopoulos Panayotis
Published: October 2023

Biological invasions are one of the main threats to biodiversity, but they also offer insights on different ecological processes, as highlighted by the hypotheses posited to explain the phenomenon. We explore the relative importance of different hypotheses using biotic (native diversity) and abiotic factors (climate and landscape configuration) as proxies driving the spatial pattern of alien plant biodiversity in Greece. The strongest predictor of alien species richness is native species richness. Landscape heterogeneity boosts this relationship, but native and alien species prefer different conditions. Landscape composition and configuration explain more of the variance of alien diversity than of native diversity, with native diversity increasing at more naturally vegetated areas and alien diversity at agricultural lands. Climate is associated more strongly with native diversity than with alien diversity, with native diversity increasing in colder regions and alien diversity in warmer regions. The transportation network was associated with higher alien species richness but not with native species richness, highlighting the importance of propagule/colonization pressure. These differences might indicate that aliens occupy part of the niche space that is not preferred by the natives and thus allow us to speculate on the role of limiting similarity as a driving force.
The Diverse Reticulate Genetic Set-Up of Endangered Gladiolus palustris in Southern Germany Has Consequences for the Development of Conservation Strategies
Authors: Koch Marcus A.
Published: October 2023

Gladiolus palustris (marsh Gladiolus) of wet grasslands is an extremely rare and highly endangered species in Central Europe. Ongoing loss of habitat, population fragmentation, drought, and higher mean annual temperatures caused by global warming have all contributed to a severe decline in its population over the past few decades. Additionally, hybridization with other species, such as G. imbricatus and G. illyricus, and genetic depletion may pose a significant threat to the species’ survival. The focus of this study is to characterize major gene pools of the species in southern and southwestern Germany. Using molecular AFLP markers and ITS DNA sequencing, this study shows that past hybridization and introgression in Central Europe are more extensive than previously thought, posing a challenge to conservation strategies targeting taxonomically defined species. The region of the Rhine River in southwestern Germany (Upper Rhine Valley) has seen the emergence of various scattered populations of G. palustris over the past three decades, which are believed to have been introduced by humans. Introduced populations in this area (comprising the German Federal States of Baden–Württemberg and Rhineland–Palatinate) likely descend from a large source population near Lake Constance. Therefore, the study suggests promoting and protecting these new populations, given their long-standing presence in the region. Furthermore, the research proposes that naturally occurring hybrids and introgressed populations should also be the primary target of conservation efforts.
Adapted Deep Ensemble Learning-Based Voting Classifier for Osteosarcoma Cancer Classification
Authors: Walid Md. Abul Ala , Mollick Swarnali , Shill Pintu Chandra , Baowaly Mrinal Kanti , Islam Md. Rabiul , Ahamad Md. Martuza , Othman Manal A. , Samad Md Abdus
Published: October 2023

The study utilizes osteosarcoma hematoxylin and the Eosin-stained image dataset, which is unevenly dispersed, and it raises concerns about the potential impact on the overall performance and reliability of any analyses or models derived from the dataset. In this study, a deep-learning-based convolution neural network (CNN) and adapted heterogeneous ensemble-learning-based voting classifier have been proposed to classify osteosarcoma. The proposed methods can also resolve the issue and develop unbiased learning models by introducing an evenly distributed training dataset. Data augmentation is employed to boost the generalization abilities. Six different pre-trained CNN models, namely MobileNetV1, Mo-bileNetV2, ResNetV250, InceptionV2, EfficientNetV2B0, and NasNetMobile, are applied and evaluated in frozen and fine-tuned-based phases. In addition, a novel CNN model and adapted heterogeneous ensemble-learning-based voting classifier developed from the proposed CNN model, fine-tuned NasNetMobile model, and fine-tuned Efficient-NetV2B0 model are also introduced to classify osteosarcoma. The proposed CNN model outperforms other pre-trained models. The Kappa score obtained from the proposed CNN model is 93.09%. Notably, the proposed voting classifier attains the highest Kappa score of 96.50% and outperforms all other models. The findings of this study have practical implications in telemedicine, mobile healthcare systems, and as a supportive tool for medical professionals.
Lung Microbiota in Idiopathic Pulmonary Fibrosis, Hypersensitivity Pneumonitis, and Unclassified Interstitial Lung Diseases: A Preliminary Pilot Study
Authors: Man Milena Adina , Ungur Rodica Ana , Motoc Nicoleta Stefania , Pop Laura Ancuta , Berindan-Neagoe Ioana , Ruta Victoria Maria
Published: October 2023

(1) Introduction: Although historically, the lung has been considered a sterile organ, recent studies through 16S rRNA gene sequencing have identified a substantial number of microorganisms. The human microbiome has been considered an “essential organ,” carrying about 150 times more information (genes) than are found in the entire human genome. The purpose of the present study is to characterize and compare the microbiome in three different interstitial lung diseases: idiopathic pulmonary fibrosis (IPF), hypersensitivity pneumonitis, and nondifferential interstitial lung disease. (2) Material and methods: This was a prospective cohort study where the DNA of 28 patients with ILD was extracted from the lavage and then processed using the standard technique of 16S RNA gene sequencing. In a tertiary teaching hospital in the northern, western part of Romania, samples were collected through bronchoscopy and then processed. (3) Results: The same four species were found in all the patients but in different quantities and compositions: Firmicutes, Actinobacteria, Proteobacteria and Bacteroides. Streptococcus was the most prevalent genus, followed by Staphylococcus and Prevotella. Statistically significant differences in the OUT count for the ten most abundant taxa were found for the genus: Gemella, Actinobacteria, Prevotella, Neisseria, Haemophilus, and Bifidobacterium. The comparative analysis showed a richer microbiota in patients with IPF, as shown by the alpha diversity index. (4) Conclusions: In interstitial lung diseases, the microorganisms normally found in the lung are reduced to a restricted flora dominated by the Firmicutes family. These changes significantly disrupt the continuity of the observed bacterial pattern from the oropharynx to the bronchial tree and lung, possibly impacting the evolution and severity of interstitial lung diseases.
Clinical Significance of Adropin and Afamin in Evaluating Renal Function and Cardiovascular Health in the Presence of CKD-MBD Biomarkers in Chronic Kidney Disease
Authors: Kaur Rupinder , Krishan Pawan , Kumari Pratima , Singh Tanveer , Singh Varinder , Singh Ravinder , Ahmad Sheikh F.
Published: October 2023

Aim: The study aims to test the hypothesis that concentrations of adropin and afamin differ between patients in various stages of chronic kidney disease when compared with healthy controls. The study also investigates the association of the biomarkers (adropin and afamin) with CKD-MBD and traditional cardiovascular risk parameters in CKD patients. Methodology: The cross-sectional study includes the subjects divided into four groups comprising the control group (healthy volunteers = 50), CKD stages 1–2 patients (n = 50), CKD stages 3–4 patients (n = 50), CKD stage 5 patients (n = 50). Serum concentrations of adropin and afamin were determined using ELISA. Clinical variables (renal, lipid, and CKD-MBD parameters) were correlated to adropin and afamin concentrations. Results: Afamin concentration was found to be higher in group IV, followed by groups III and II when compared to the control group, i.e., (83.243 ± 1.46, 64.233 ± 0.99, and 28.948 ± 0.72 vs. 14.476 ± 0.5) mg/L (p < 0.001), and adropin concentration was found to be lower in group IV as compared to groups III, II, and I (200.342 ± 8.37 vs. 284.682 ± 9.89 vs. 413.208 ± 12.32 vs. 706.542 ± 11.32) pg/mL (p < 0.001), respectively. Pearson correlation analysis showed that afamin was positively correlated with traditional cardiovascular risk biomarkers, while adropin showed a negative correlation. Conclusions: Adropin and afamin may potentially serve as futuristic predictors for the deterioration of renal function and may be involved in the pathological mechanisms of CKD and its associated complications such as CKD-MBD and high lipid levels.
Machine Learning-Based Regression Models for Ironmaking Blast Furnace Automation
Authors: Calix Ricardo A. , Ugarte Orlando , Okosun Tyamo , Wang Hong
Published: October 2023

Computational fluid dynamics (CFD)-based simulation has been the traditional way to model complex industrial systems and processes. One very large and complex industrial system that has benefited from CFD-based simulations is the steel blast furnace system. The problem with the CFD-based simulation approach is that it tends to be very slow for generating data. The CFD-only approach may not be fast enough for use in real-time decisionmaking. To address this issue, in this work, the authors propose the use of machine learning techniques to train and test models based on data generated via CFD simulation. Regression models based on neural networks are compared with tree-boosting models. In particular, several areas (tuyere, raceway, and shaft) of the blast furnace are modeled using these approaches. The results of the model training and testing are presented and discussed. The obtained R2 metrics are, in general, very high. The results appear promising and may help to improve the efficiency of operator and process engineer decisionmaking when running a blast furnace.
Trade Openness and Unemployment in Selected Southern African Development Community (SADC) Countries
Authors: Gonese Dorcas , Sibanda Kin , Ngonisa Phillip
Published: October 2023

The relationship between trade openness and unemployment in Southern African Development Community (SADC) countries remains an area of significant interest and concern. While trade openness is often advocated for fostering economic growth and development, its potential effects on employment outcomes are complex and multifaceted. Understanding the nature and nuances of this relationship within the SADC region is crucial for policymakers and stakeholders seeking to design effective strategies that balance the benefits of trade openness with the goals of reducing unemployment and promoting inclusive growth. This study evaluates the effect of trade openness on unemployment in SADC from 1980 to 2019 using panel ARDL (pooled mean group—PMG) estimation techniques. The findings of the study show that trade openness and exports negatively impact unemployment, whereas imports positively affect unemployment in the long run. This suggests that while boosting exports and real trade, openness decreases unemployment, and imports increase job losses in the long run in the SADC region. This calls for more caution on trade openness regarding what to export and import when addressing regional unemployment reduction policies.
Mapping the Landscape of Doctoral Research in Technologies in Education: A 25-Year Analysis in Portuguese Universities
Authors: Albuquerque Costa Fernando , Cruz Elisabete
Published: October 2023

In the context of the evolving landscape of doctoral education within the framework of a knowledge society, this study explores the landscape of doctoral research in the field of technologies in education (TE) within Portuguese universities. The investigation places its focus on understanding the composition and evolution of research themes over 25 years (1997–2022), unveiling the landscape’s responsiveness to the challenges of a technologically advanced society. Employing a scientometric approach, we analyse 380 doctoral dissertations, highlighting the authors’ nationalities and genders, as well as the burgeoning themes, research questions, and methodological frameworks. Our results reveal a diverse range of themes, with “Teaching and Learning” and “Professional Development” emerging as predominant areas of exploration. Researchers predominantly derive their problems from real educational contexts, seeking to enhance understanding and intervention. This study underscores a shift from a technology-centric perspective to one focused on pedagogical considerations. Through this article’s objective representation, our findings highlight the multifaceted nature of TE research in Portuguese universities and its implications for innovation and knowledge advancement in education.
RenderBench: The CPU Rendering Benchmark Suite Based on Microarchitecture-Independent Characteristics
Authors: Wang Peng , Yu Zhibin
Published: October 2023

This research addresses the issue of evaluating CPU rendering performance by introducing the innovative benchmark test suite construction method RenderBench. This method combines CPU microarchitecture features with rendering task characteristics to comprehensively assess CPU performance across various rendering tasks. Adhering to principles of representativeness and comprehensiveness, the constructed benchmark test suite encompasses diverse rendering tasks and scenarios, ensuring accurate capture of CPU performance features. Through data sampling and in-depth analysis, this study focuses on the role of microarchitecture-independent features in rendering programs, including instruction-level parallelism, instruction mix, branch prediction capability, register dependency distance, data flow stride, and memory reuse distance. The research findings reveal significant variations in rendering programs across these features. For instance, in terms of instruction-level parallelism, rendering programs demonstrate a high level of ILP (instruction-level parallelism), with an average value of 5.70 for ILP256, surpassing benchmarks such as Mibench and NAS Parallel Benchmark. Furthermore, in aspects such as instruction mix, branch prediction capability, register dependency distance, data flow stride, and memory reuse distance, rendering programs exhibit distinct characteristics. Through the application of the RenderBench method, a scalable and highly representative benchmark test suite was constructed, facilitating an in-depth exploration of CPU performance bottlenecks in rendering tasks. By delving into microarchitecture-independent features, this study provides profound insights into rendering program performance, offering valuable guidance for optimizing CPU rendering performance. The application of ensemble learning models, such as random forest, XGBoost, and ExtraTrees, reveals the significant influence of features like floating-point computation, memory access patterns, and register usage on CPU rendering program performance. These insights not only offer robust guidance for performance optimization but also underscore the importance of feature selection and algorithm choice. In summary, the results of feature importance ranking in this study provide beneficial directions and deep insights for the optimization and enhancement of CPU rendering program performance. These findings are poised to exert a positive impact on future research and development endeavors.
An Empirical Mode Decomposition-Based Method to Identify Topologically Associated Domains from Chromatin Interactions
Authors: Zhao Xuemin , Duan Ran , Yao Shaowen
Published: October 2023

Topologically associated domains (TADs) represent essential units constituting chromatin’s intricate three-dimensional spatial organization. TADs are stably present across cell types and species, and their influence on vital biological processes, such as gene expression, DNA replication, and chromosomal translocation, underscores their significance. Accordingly, the identification of TADs within the Hi-C interaction matrix is a key point in three-dimensional genomics. TADs manifest as contiguous blocks along the diagonal of the Hi-C interaction matrix, which are characterized by dense interactions within blocks and sparse interactions between blocks. An optimization method is proposed to enhance Hi-C interaction matrix data using the empirical mode decomposition method, which requires no prior knowledge and adaptively decomposes Hi-C data into a sum of multiple eigenmodal functions via exploiting the inherent characteristics of variations in the input Hi-C data. We identify TADs within the optimized data and compared the results with five commonly used TAD detection methods, namely the Directionality Index (DI), Interaction Isolation (IS), HiCKey, HiCDB, and TopDom. The results demonstrate the universality and efficiency of the proposed method, highlighting its potential as a valuable tool in TAD identification.
Model of Message Transmission across Parallel Route Groups with Dynamic Alternation of These Groups in a Multichannel Steganographic System
Authors: Ha Muon , Tran Duc-Manh , Shichkina Yulia
Published: October 2023

The subject of this study is steganographic systems that are able to hide not only the content of the transmitted information but also the fact of its transmission. In this paper, we present a novel data transmission model within such systems, combining a modified Dijkstra’s algorithm with the dynamic utilization of multiple transmission routes. Consequently, this allows the simultaneous transmission of messages through parallel groups of routes with the dynamic alternation of these groups during the information exchange process between the sender and the receiver in the steganographic network. Thus, the speed, reliability, and security of message transmission are improved. Moreover, to increase the security level, the proposed model uses a route–time matrix that is available only to the sender and receiver. Additionally, the data transmission model has been tested on synthetic data and data obtained from real devices. The evaluation of the effectiveness of the proposed model on the example of various structured steganographic systems shows the significant effectiveness of our model. As a result, in comparison with existing similar methods, the secrecy index was increased five times and the violation index was decreased four times.
Design and Analysis of Complementary Metal–Oxide–Semiconductor Single-Pole Double-Throw Switches for 28 GHz 5G New Radio
Authors: Lin Yo-Sheng , Huang Chin-Yi , Huang Chung-Ta , Chang Jin-Fa , Tien Nai-Wen , Chuang Yu-Hao
Published: October 2023

We propose a single-pole double-throw (SPDT) switch with low insertion loss (IL), high isolation, and high linearity for a 28 GHz 5G new radio. The transmit (TX) path is a π-network consisting of a parallel dynamic-threshold metal–oxide–semiconductor (DTMOS) transistor, M1, with large body-floating resistance, RB (DTMOS-R M1), a series one-eighth-wavelength (λ/8) transmission line (TL), and a parallel capacitance, Cant. The series λ/8-TL in conjunction with the parallel Cant and transistors’ capacitance constitute an equivalent λ/4-TL with a characteristic impedance of 50 Ω. This leads to low IL in the TX mode and decent isolation in the receive (RX) mode. The RX path is an L-network constituting a series impedance (of parallel inductance L1 and DTMOS-R M2) and a parallel DTMOS-R M3. This leads to a decent IL in the RX mode and isolation in the TX mode. The first SPDT switch (SPDT SW1) is designed and implemented in a 90 nm complementary metal–oxide–semiconductor (CMOS) with a top metal thickness (TMT) of 3.4 μm. A comparative SPDT switch (SPDT SW2) in a 0.18 μm CMOS with a thinner TMT of 2.34 μm is also designed and implemented. In the TX mode, SPDT SW1 achieves a measured IL of 0.67 dB at 28 GHz and 0.58–1 dB for 17–34.9 GHz and a measured isolation of 44.3 dB at 28 GHz and 25.6–62.3 dB for 17–34.9 GHz, one of the best IL and isolation results ever reported for millimeter-wave CMOS SPDT switches. The measured input 1 dB compression point (P1dB) is 28.5 dBm at 28 GHz. Moreover, in the RX mode, SPDT SW1 attains a measured IL of 1.9 dB at 28 GHz and 1.83–2.1 dB for 25–38.3 GHz and an isolation of 25 dB at 28 GHz and 24.5–27 dB for 25–38.3 GHz. The measured P1dB is 24 dBm at 28 GHz.
Numerical Feature Selection and Hyperbolic Tangent Feature Scaling in Machine Learning-Based Detection of Anomalies in the Computer Network Behavior
Authors: Protić Danijela , Stanković Miomir , Prodanović Radomir , Vulić Ivan , Stojanović Goran M. , Simić Mitar , Ostojić Gordana , Stankovski Stevan
Published: October 2023

Anomaly-based intrusion detection systems identify the computer network behavior which deviates from the statistical model of typical network behavior. Binary classifiers based on supervised machine learning are very accurate at classifying network data into two categories: normal traffic and anomalous activity. Most problems with supervised learning are related to the large amount of data required to train the classifiers. Feature selection can be used to reduce datasets. The goal of feature selection is to select a subset of relevant input features to optimize the evaluation and improve performance of a given classifier. Feature scaling normalizes all features to the same range, preventing the large size of features from affecting classification models or other features. The most commonly used supervised machine learning models, including decision trees, support vector machine, k-nearest neighbors, weighted k-nearest neighbors and feedforward neural network, can all be improved by using feature selection and feature scaling. This paper introduces a new feature scaling technique based on a hyperbolic tangent function and damping strategy of the Levenberg–Marquardt algorithm.
Optimization Algorithm for Steel Surface Defect Detection Based on PP-YOLOE
Authors: Qu Yi , Wan Boyu , Wang Cheng , Ju Haijuan , Yu Jiabo , Kong Yakang , Chen Xiancong
Published: October 2023

The fast and accurate detection of steel surface defects has become an important goal of research in various fields. As one of the most important and effective methods of detecting steel surface defects, the successive generations of YOLO algorithms have been widely used in these areas; however, for the detection of tiny targets, it still encounters difficulties. To solve this problem, the first modified PP-YOLOE algorithm for small targets is proposed. By introducing Coordinate Attention into the Backbone structure, we encode channel relationships and long-range dependencies using accurate positional information. This improves the performance and overall accuracy of small target detection while maintaining the model parameters. Additionally, simplifying the traditional PAN+FPN components into an optimized FPN feature pyramid structure allows the model to skip computationally expensive but less relevant processes for the steel surface defect dataset, effectively reducing the computational complexity of the model. The experimental results show that the overall average accuracy (mAP) of the improved PP-YOLOE algorithm is increased by 4.1%, the detection speed is increased by 2.06 FPS, and the accuracy of smaller targets (with a pixel area less than 322) that are more difficult to detect is significantly improved by 13.3% on average, as compared to the original algorithm. The detection performance is also higher than that of the mainstream target detection algorithms, such as SSD, YOLOv3, YOLOv4, and YOLOv5, and has a high application value in industrial detection.
FusionNet: An End-to-End Hybrid Model for 6D Object Pose Estimation
Authors: Ye Yuning , Park Hanhoon
Published: October 2023

In this study, we propose a hybrid model for Perspective-n-Point (PnP)-based 6D object pose estimation called FusionNet that takes advantage of convolutional neural networks (CNN) and Transformers. CNN is an effective and potential tool for feature extraction, which is considered the most popular architecture. However, CNN has difficulty in capturing long-range dependencies between features, and most CNN-based models for 6D object pose estimation are bulky and heavy. To address these problems, we propose a lighter-weight CNN building block with attention, design a Transformer-based global dependency encoder, and integrate them into a single model. Our model is able to extract dense 2D–3D point correspondences more accurately while significantly reducing the number of model parameters. Followed with a PnP header that replaces the PnP algorithm for general end-to-end pose estimation, our model showed better or highly competitive performance in pose estimation compared with other state-of-the-art models in experiments on the LINEMOD dataset.
Evaluation of Electromagnetic Fields of Extremely Low-Frequency Horizontal Electric Dipoles at Sea–Air Boundaries
Authors: Hu Sumou , Xie Hui , Li Zhangming
Published: October 2023

The technologies of undersea detection and communication, seabed sensor networks, and geophysical detection using electromagnetic waves have emerged as research focal points within the field of marine science and engineering. However, most studies have focused on the propagation of electromagnetic fields over long distances within the shallow “sea-seabed” environment. This paper introduces a quasi-static approximation method to address the Sommerfeld numerical integration challenge within the near-field region, employing the horizontal electric dipole (HED) as a model. It derives the Sommerfeld numerical integral expressions under conditions where the wave-number ratio at the “seawater-air” boundary does not adhere to the requirement of |k0/k1| << 1 (where subscripts 0 and 1 denote seawater and air media, respectively). Building upon this, the paper simplifies the Bessel-Fourier infinite integral term within the integral expression to obtain Sommerfeld numerical integral approximations for the propagation of electromagnetic fields in the near region of extremely low frequency (ELF) within seawater. The study further conducts simulations and calculations to determine amplitude variations in electromagnetic field intensity generated by an ELF HED at different frequencies, dipole heights, and observation point depths. It concludes with an analysis of electromagnetic field propagation characteristics at the seawater-air boundary. Experimental findings highlight the lateral wave as the primary mode of electromagnetic wave propagation at this interface.
A Neural Multi-Objective Capacitated Vehicle Routing Optimization Algorithm Based on Preference Adjustment
Authors: Wang Liting , Song Chao , Sun Yu , Lu Cuihua , Chen Qinghua
Published: October 2023

The vehicle routing problem (VRP) is a common problem in logistics and transportation with high application value. In the past, many methods have been proposed to solve the vehicle routing problem and achieved good results, but with the development of neural network technology, solving the VRP through neural combinatorial optimization has attracted more and more attention by researchers because of its short inference time and high parallelism. PMOCO is the most state-of-the-art multi-objective vehicle routing optimization algorithm. However, in PMOCO, preferences are often uniformly selected, which may lead to uneven Pareto sets and may reduce the quality of solutions. To solve this problem, we propose a multi-objective vehicle routing optimization algorithm based on preference adjustment, which is improved from PMOCO. We incorporate the weight adjustment method in PMOCO that is able to adapt to different approximate Pareto fronts and to find solutions with better quality. We treat the weight adjustment as a sequential decision process and train it through deep reinforcement learning. We find that our method could adaptively search for a better combination of preferences and have strong robustness. Our method is experimented on multi-objective vehicle routing problems and obtained good results (about 6% improvement compared with PMOCO with 20 preferences).
On Autonomous Phase Balancing of the Coplanar Stripline as a Feedline for a Quasi-Yagi Antenna
Authors: Lee Jung-Seok , Min Byung-Cheol , Kumar Sachin , Choi Hyun-Chul , Kim Kang-Wook
Published: October 2023

This paper provides a clear demonstration that a coplanar stripline (CPS) as a balanced line can act to re-establish the phase balance in the presence of phase deviation from a 180° distance between two input signal lines connected to the CPS. A half-wave delay line splitter connected to a CPS works as a balun to feed a balanced antenna, such as a quasi-Yagi antenna. This type of balun structure has been widely used to feed balanced antennas with a frequency bandwidth of up to 60%. Nevertheless, no clear explanation has been given regarding how the broadband antennas could be implemented with this type of balun structure. In this paper, through 3D EM simulations and measurements, it is shown that the half-wave delay line splitter indeed only results in the 180° phase balance at one frequency, but the subsequently connected CPS acts to recover the phase balance between the signal lines. The CPS can recover the phase balance within a phase imbalance of ~π/3, which determines the usable bandwidth of this structure. For a demonstration, with a center frequency of 10 GHz, samples of the half-wave delay line splitter connected to a CPS are fabricated and measured.