bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonlinear Modeling and Transient Stability Analysis of Grid-Connected Voltage Source Converters during Asymmetric Faults Considering Multiple Control Loop Coupling
Authors: Guo Jingkuan , Zhai Denghui , Li Xialin , Wang Zhi
Published: September 2024

As large-scale renewable energy sources are increasingly integrated into AC grids via voltage source converters (VSCs), the transient synchronization stability of phase-locked loop (PLL)-based VSCs during fault ride-through is gaining more attention. Most existing studies assume that the positive and negative sequence separation and current control dynamics are much faster than the PLL dynamics, thereby neglecting their impact on the transient synchronization stability of the system. However, when the PLL bandwidth is relatively large, ignoring the positive and negative sequence separation and current control dynamics may result in incorrect stability assessments. To address this issue, this paper first considers the multiple control loop coupling, including positive and negative sequence separation, current control, and PLL, to construct a full-order nonlinear mathematical model of the VSC grid-connected system under asymmetric fault conditions. Based on this, the phase trajectory method is employed to analyze the transient synchronization stability of the system. Additionally, this full-order mathematical model is used to determine the PLL bandwidth boundary beyond which the effects of positive and negative sequence separation and current control dynamics cannot be neglected. Finally, PSCAD/EMTDC simulation results validate the effectiveness of the theoretical analysis presented in this paper.
Rolling Shutter-Based Underwater Optical Camera Communication (UWOCC) with Side Glow Optical Fiber (SGOF)
Authors: Li Jia-Fu , Chang Yun-Han , Chen Yung-Jie , Chow Chi-Wai
Published: September 2024

Nowadays, a variety of underwater activities, such as underwater surveillance, marine monitoring, etc., are becoming crucial worldwide. Underwater sensors and autonomous underwater vehicles (AUVs) are widely adopted for underwater exploration. Underwater communication via radio frequency (RF) or acoustic wave suffers high transmission loss and limited bandwidth. In this work, we present and demonstrate a rolling shutter (RS)-based underwater optical camera communication (UWOCC) system utilizing a long short-term memory neural network (LSTM-NN) with side glow optical fiber (SGOF). SGOF is made of poly-methyl methacrylate (PMMA) SGOF. It is lightweight and flexibly bendable. Most importantly, SGOF is water resistant; hence, it can be installed in an underwater environment to provide 360° “omni-directional” uniform radial light emission around its circumference. This large FOV can fascinate the optical detection in underwater turbulent environments. The proposed LSTM-NN has the time-memorizing characteristics to enhance UWOCC signal decoding. The proposed LSTM-NN is also compared with other decoding methods in the literature, such as the PPB-NN. The experimental results demonstrated that the proposed LSTM-NN outperforms the PPB-NN in the UWOCC system. A data rate of 2.7 kbit/s can be achieved in UWOCC, satisfying the pre-forward error correction (FEC) condition (i.e., bit error rate, BER ≤ 3.8 × 10−3). We also found that thin fiber also allows performing spatial multiplexing to enhance transmission capacity.
Improved Subsynchronous Oscillation Parameter Identification Based on Eigensystem Realization Algorithm
Authors: Chen Gang , Zeng Xueyang , Liu Yilin , Zhang Fang , Shi Huabo
Published: September 2024

Subsynchronous oscillation (SSO) is the resonance between a new energy generator set and a weak power grid, and the resonance frequency is usually the sub-/super-synchronous frequency. The eigensystem realization algorithm (ERA) is a classic algorithm for extracting modal parameters based on matrix decomposition. By leveraging the ERA’s simplicity and low computational cost, an enhanced methodology for identifying the key parameters of SSO is introduced. The enhanced algorithm realizes SSO angular frequency extraction by constructing an angular frequency fitting equation, enabling efficient identification of SSO parameters using only a 200 ms synchrophasor sequence. In the process of identification, the fitting-based ERA effectively addresses the limitation of the existing ERA. The accuracy of SSO parameter identification is improved, thereby realizing that SSO parameter identification can be carried out using a 200 ms data window. The fitting-based ERA is verified using synthetic and actual data from synchrophasor measurement terminals. The research results show that the proposed algorithm can accurately extract fundamental and subsynchronous or supersynchronous oscillation parameters, effectively realizing dynamic real-time monitoring of subsynchronous oscillations.
Creep Model and Experimental Verification of Sandstone under the Coupled Effect of Chemical Corrosion and Temperature
Authors: Xiu Xia , Wang Yong , Zhou Ye , Niu Geng , Zhao Shijun , Chang Degong
Published: September 2024

The Nishihara creep model is an extremely effective method in the field of sandstone creep model research. However, the Nishihara creep model curve for sandstone under the marine environment (the coupled effect of chemical corrosion and temperature) does not fit the actual creep test data well. Based on the Nishihara creep model, we discovered that, on the one hand, the viscoelastic elements in the Nishihara model are replaced by the viscoelastic elements containing temperature and pH factors, which can accurately describe the influence of temperature and pH on rock creep characteristics; on the other hand, the viscoplastic elements in the Nishihara model are replaced by nonlinear viscoplastic elements, which can accurately describe the accelerated creep stage of the rock mass. After modifying Nishihara’s creep model twice, a new temperature–pH damage nonlinear creep model is established. The creep curve of the temperature–pH damage nonlinear creep model is compared with the creep test data of sandstone. The comparison results indicate that the creep curve of the nonlinear creep model has a high degree of fit with the creep test data of sandstone (accuracy > 92%). This validates the correctness of the newly established temperature–pH damage nonlinear creep model presented in this paper, demonstrating that the new model can effectively reflect the influence of temperature and pH on the creep characteristics of sandstone.
An Age-Based Size-Specific Dose Estimate for Pediatric Computed Tomography Head Examinations Performed at Songklanagarind Hospital, Thailand, from 2017 to 2019
Authors: Poosiri Saowapark , Chuboonlap Kanokkwan , Kaewlaied Nuttita
Published: September 2024

Computed tomography (CT) is the primary source of diagnostic radiation in pediatric patients. Patient head size and tissue attenuation are critical factors for estimating CT radiation doses. This study aimed to determine a size-specific dose estimate based on the water-equivalent diameter (SSDEDw) for pediatric CT head examinations, categorized by age group, and to investigate the parameters influencing the SSDEDw. This retrospective analysis included 274 pediatric patients aged 0 to 15 years who underwent non-contrast CT head examinations using an age-based protocol without automatic exposure control systems. The SSDEDw was calculated using the CTDIvol, and the conversion factor was derived from AAPM Report No. 293, based on the water-equivalent diameter (Dw). We found that the SSDEDw of age groups of 0 to 6 months, 6 months to 3 years, 3 to 6 years, 6 to 12 years, and 12 to 15 years were 15.4 (14.8, 15.8), 20.1 (19.6, 20.6), 25.3 (24.6, 25.7), 28.1 (27.3, 28.8), and 35.1 (34.6, 36) mGy, respectively. Age and body weight significantly affected the SSDEDw, with high R-squared values of 0.87 and 0.63, respectively (p < 0.001). The SSDE, particularly when based on the water-equivalent diameter (SSDEDW), is a valuable supplement to the DLP and the CTDIvol as it closely relates to patient dose, especially for pediatric head scans of different patient sizes.
Three-Dimensional Fuzzy Modeling for Nonlinear Distributed Parameter Systems Using Simultaneous Perturbation Stochastic Approximation
Authors: Zhang Xianxia , Wang Tangchen , Cheng Chong , Wang Shaopu
Published: September 2024

Many systems in the manufacturing industry have spatial distribution characteristics, which correlate with both time and space. Such systems are known as distributed parameter systems (DPSs). Due to the spatiotemporal coupling characteristics, the modeling of such systems is quite complex. The paper presents a new approach for three-dimensional fuzzy modeling using Simultaneous Perturbation Stochastic Approximation (SPSA) for nonlinear DPSs. The Affinity Propagation clustering approach is utilized to determine the optimal number of fuzzy rules and construct a collection of preceding components for three-dimensional fuzzy models. Fourier space base functions are used in the resulting components of three-dimensional fuzzy models, and their parameters are learned by the SPSA algorithm. The proposed three-dimensional fuzzy modeling technique was utilized on a conventional DPS within the semiconductor manufacturing industry, with the simulation experiments confirming its efficacy.
Enhancing User Acceptance of an AI Agent’s Recommendation in Information-Sharing Environments
Authors: Kehat Rebecca , Hirschprung Ron S. , Alkoby Shani
Published: September 2024

Information sharing (IS) occurs in almost every action daily. IS holds benefits for its users, but it is also a source of privacy violations and costs. Human users struggle to balance this trade-off. This reality calls for Artificial Intelligence (AI)-based agent assistance that surpasses humans’ bottom-line utility, as shown in previous research. However, convincing an individual to follow an AI agent’s recommendation is not trivial; therefore, this research’s goal is establishing trust in machines. Based on the Design of Experiments (DOE) approach, we developed a methodology that optimizes the user interface (UI) with a target function of maximizing the acceptance of the AI agent’s recommendation. To empirically demonstrate our methodology, we conducted an experiment with eight UI factors and n = 64 human participants, acting in a Facebook simulator environment, and accompanied by an AI agent assistant. We show how the methodology can be applied to enhance AI agent user acceptance on IS platforms by selecting the proper UI. Additionally, due to its versatility, this approach has the potential to optimize user acceptance in multiple domains as well.
Development of Wet Scavenging Process of Particles in Air Quality Modeling
Authors: Park Da-Som , Choi Yongjoo , Sunwoo Young , Jung Chang Hoon
Published: September 2024

This study presents an improved wet scavenging process for particles in air quality modeling, focusing on the Korean Peninsula. New equations were incorporated into the air quality chemical transport model (CTM) to enhance the simulation of particulate matter (PM) concentrations. The modified air quality CTM module, utilizing size-dependent scavenging formulas, was applied to simulate air quality for April 2018, a month characterized by significant precipitation. Results showed that the modified model produced more accurate predictions of PM10 and PM2.5 concentrations compared to the original air quality CTM model. The maximum monthly average differences were 5.46 µg/m3 for PM10 and 2.87 µg/m3 for PM2.5, with pronounced improvements in high-concentration regions. Time-series analyses for Seoul and Busan demonstrated better agreement between modeled and observed values. Spatial distribution comparisons revealed enhanced accuracy, particularly in metropolitan areas. This study highlights the importance of incorporating region-specific, size-dependent wet scavenging processes in air quality models. The improved model shows promise for more accurate air quality predictions, potentially benefiting environmental management and policy-making in the region. Future research should focus on integrating more empirical data to further refine the wet scavenging process in air quality modeling.
Morse Thoery of Saddle Point Reduction with Applications
Authors: Yang Ran , Xing Qin
Published: September 2024

In this paper, we demonstrate that when saddle point reduction is applicable, there is a clear relationship between the Morse index and the critical groups before and after the reduction. As an application of this result, we use saddle point reduction along with the critical point theorem to show the existence of periodic solutions in second-order Hamiltonian systems.
A Nanobody of PEDV S1 Protein: Screening and Expression in Escherichia coli
Authors: Hao Zhipeng , Dong Xufeng , Zhang Zhongtao , Qin Zhihua
Published: September 2024

Porcine epidemic diarrhea virus (PEDV) has caused significant economic losses to the pig farming industry in various countries for a long time. Currently, there are no highly effective preventive or control measures available. Research into the pathogenic mechanism of PEDV has shown that it primarily causes infection by binding the S protein to the CD13 (APN) receptor on the membrane of porcine intestinal epithelial cells. The S1 region contains three neutralization epitopes and multiple receptor-binding domains, which are closely related to viral antigenicity and ad-sorption invasion. Nanobodies are a type of single-domain antibody that have been discovered in recent years. They can be expressed on a large scale through prokaryotic expression systems, which makes them cost-effective, stable, and less immunogenic. This study used a phage display library of nanobodies against the PEDV S1 protein. After three rounds of selection and enrichment, the DNA sequence of the highly specific nanobody S1Nb1 was successfully obtained. To obtain soluble nanobody S1Nb1, its DNA sequence was inserted into the vector Pcold and a solubility-enhancing SUMO tag was added. The resulting recombinant vector, Pcold-SUMO-S1Nb1, was then transformed into E. coli BL21(DE3) to determine the optimal expression conditions for the nanobody. Following purification using Ni-column affinity chromatography, Western blot analysis confirmed the successful purification of S1Nb1 carrying the solubility-enhancing tag. ELISA results demonstrated a strong affinity between the S1Nb1 nanobody and PEDV S1 protein.
The Role of DNMT Methyltransferases and TET Dioxygenases in the Maintenance of the DNA Methylation Level
Authors: Davletgildeeva Anastasiia T. , Kuznetsov Nikita A.
Published: September 2024

This review deals with the functional characteristics and biological roles of enzymes participating in DNA methylation and demethylation as key factors in epigenetic regulation of gene expression. The set of enzymes that carry out such processes in human cells is limited to representatives of two families, namely DNMT (DNA methyltransferases) and TET (DNA dioxygenases). The review presents detailed information known today about each functionally important member of these families and describes the catalytic activity and roles in the mammalian body while also providing examples of dysregulation of the expression and/or activity of these enzymes in conjunction with the development of some human disorders, including cancers, neurodegenerative diseases, and developmental pathologies. By combining the up-to-date information on the dysfunction of various enzymes that control the DNA “methylome” in the human body, we hope not only to draw attention to the importance of the maintenance of a required DNA methylation level (ensuring epigenetic regulation of gene expression and normal functioning of the entire body) but also to help identify new targets for directed control over the activity of the enzymes that implement the balance between processes of DNA methylation and demethylation.
Membrane Activity of Melittin and Magainin-I at Low Peptide-to-Lipid Ratio: Different Types of Pores and Translocation Mechanisms
Authors: Volovik Marta V. , Batishchev Oleg V.
Published: September 2024

Antimicrobial peptides (AMPs) are believed to be a prominent alternative to the common antibiotics. However, despite decades of research, there are still no good clinical examples of peptide-based antimicrobial drugs for system application. The main reasons are loss of activity in the human body, cytotoxicity, and low selectivity. To overcome these challenges, a well-established structure–function relationship for AMPs is critical. In the present study, we focused on the well-known examples of melittin and magainin to investigate in detail the initial stages of AMP interaction with lipid membranes at low peptide-to-lipid ratio. By combining the patch-clamp technique with the bioelectrochemical method of intramembrane field compensation, we showed that these peptides interact with the membrane in different ways: melittin inserts deeper into the lipid bilayer than magainin. This difference led to diversity in pore formation. While magainin, after a threshold concentration, formed the well-known toroidal pores, allowing the translocation of the peptide through the membrane, melittin probably induced predominantly pure lipidic pores with a very low rate of peptide translocation. Thus, our results shed light on the early stages of peptide–membrane interactions and suggest new insights into the structure–function relationship of AMPs based on the depth of their membrane insertion.
Research on Landscape Perception of Urban Parks Based on User-Generated Data
Authors: Ren Wei , Zhan Kaiyuan , Chen Zhu , Hong Xin-Chen
Published: September 2024

User-generated data can reflect various viewpoints and experiences derived from people’s perception outcomes. The perceptual results can be obtained, often by combining subjective public perceptions of the landscape with physiological monitoring data. Accessing people’s perceptions of the landscape through text is a common method. It is hard to fully render nuances, emotions, and complexities depending only on text by superficial emotional tendencies alone. Numerical representations may lead to misleading conclusions and undermine public participation. In addition, the use of physiological test data does not reflect the subjective reasons for the comments made. Therefore, it is essential to deeply parse the text and distinguish between segments with different semantic differences. In this study, we propose a perceptual psychology-based workflow to extract and visualize multifaceted views from user-generated data. The analysis methods of FCN, LDA, and LSTM were incorporated into the workflow. Six areas in Fuzhou City, China, with 12 city parks, were selected as the study object. Firstly, 9987 review data and 1747 pictures with corresponding visitor trajectories were crawled separately on the Dianping and Liangbulu websites. For in-depth analysis of comment texts and making relevant heat maps. Secondly, the process of clauses was added to get a more accurate representation of the sentiment of things based on the LSTM sentiment analysis model. Thirdly, various factors affecting the perception of landscapes were explored. Based on such, the overall people’s perception of urban parks in Fuzhou was finally obtained. The study results show that (1) the texts in terms of ‘wind’, ‘temperature’, ‘structures’, ‘edge space (spatial boundaries)’, and ‘passed space’ are the five most representative factors of the urban parks in Fuzhou; (2) the textual analyses further confirmed the influence of spatial factors on perception in the temporal dimension; and (3) environmental factors influence people’s sense of urban parks concerning specificity, clocking behavior, and comfort feelings. These research results provide indispensable references for optimizing and transforming urban environments using user-generated data.
Enhancing Building Services in Higher Education Campuses through Participatory Science
Authors: Itair Mohammed , Shahrour Isam , El Meouche Rani , Hattab Nizar
Published: September 2024

This paper explores how participatory science can enhance building services on a higher education campus. The use of participatory science aims to involve students, faculty members, and technical teams in improving the management of the campus through their participation in data collection and evaluation of the building services. It represents a valuable alternative for campuses needing more building monitoring. The paper also shows how the performance of participatory science could be improved by combining digital technologies such as Building Information Modeling (BIM) and artificial intelligence (AI). The framework is applied to the Faculty of Engineering at An-Najah National University to improve the building services of the campus. A combination of users’ feedback and AI-generated synthetic data is used to explore the performance of the proposed method. Results confirm the high potential of participatory science for improving the services and quality of life on higher education campuses. This is achieved through students’ active participation and involvement in data collection and reporting on their individual experiences.
Enhancing Underground Thermal Environments in Cairo: The Role of Subway Entrance Geometry in Optimizing Natural Ventilation
Authors: Abdelaziz Omar Mohamed , Cui Xu , Sun Xiaozheng
Published: September 2024

In rapidly urbanizing regions, enhancing passenger comfort in subway systems through sustainable methods is a critical challenge. This study introduces an innovative exploration of the impact of subway entrance geometry on natural ventilation and its subsequent effects on the thermal environment within Cairo’s subway system. The primary objective is to identify optimal entrance configurations that maximize natural airflow, thereby improving passenger comfort and reducing energy consumption. Focusing on the newly constructed segments of the Cairo subway, the research employs a mixed-methods approach that integrates computational fluid dynamics (CFD) simulations with a questionnaire survey to evaluate interactions between various entrance designs and urban wind flow patterns. This dual approach allows for a comprehensive assessment of how different geometrical configurations influence the capture and distribution of prevailing winds. The results indicate that specific entrance geometries can significantly enhance ventilation efficiency by optimizing wind capture and distribution. The most effective designs demonstrated substantial improvements in air quality and thermal comfort, providing practical insights for subway systems in similar hot arid climates. The novelty of this research lies in its detailed analysis of architectural elements to leverage natural environmental conditions for improving indoor air quality and thermal comfort in public transit systems. The significance of this study is its contribution to the field of sustainable urban transport, offering a valuable framework for urban planners and engineers. By demonstrating how thoughtful design can lead to energy savings and enhanced passenger experiences, this research advances the discourse on sustainable urban infrastructure. This work not only enhances theoretical understanding but also provides actionable recommendations for creating more sustainable and comfortable public transit infrastructures.
Effect of Rubber Aggregates on Early-Age Mechanical Properties and Deformation Behaviors of Cement Mortar
Authors: Zhang Gaowang , Du Hao , Li Junmin , Yuan Jie
Published: September 2024

Rubberized cement-based materials are widely utilized because of their good ductility, impact resistance, and fatigue resistance. This research investigated the effect of the rubber aggregates content, particle size of rubber aggregates, and water–cement ratio on the early-age mechanical properties and deformation behaviors of mortar through laboratory tests, and strength reduction coefficient fitting models were established according to the testing results. The results show that the compressive strength growth rate of cement mortar is about 15% slower than that of flexural strength. The existence of rubber aggregates lowers the strength increase rate of mortar. The reduction coefficient of strength decreases with increasing rubber aggregates content and increases with the age of mortar. Increasing rubber aggregates content and decreasing particle size of rubber aggregate can lower the autogenous shrinkage in the initial stage, but the autogenous shrinkage of the later stage increases as the rubber aggregates content increases, with a turning point between 30 h and 50 h. After 3 days, the dry shrinkage of mortar accounts for about 70–80% of the total shrinkage, and it increases with higher rubber aggregate content, smaller particle size of rubber aggregates, and higher water–cement ratios.
WT1 Expression Is Associated with Poor Overall Survival after Azacytidine and DLI in a Cohort of Adult AML and MDS Patients
Authors: Aydin Semra , Schmitz Jennifer , Dellacasa Chiara M. , Dogliotti Irene , Giaccone Luisa , Busca Alessandro
Published: September 2024

Introduction: Post-transplant relapse of acute myeloid leukemia and myelodysplastic syndrome faces restricted effective salvage regimens. We retrospectively analyzed the use of Azacitidine–donor lymphocyte infusion (AZA/DLI) in this setting. Furthermore, data on bone marrow Wilms tumor gene 1 (WT1) expression were collected. Methods: A Cox proportional hazards model, an outcome-oriented approach for the lowest smoothed plot of the martingale residuals, was performed for the cut-point determination of the respective WT1 expression levels. Finally, a Cox proportional hazards model investigated the association of overall survival (OS) with predictors. Results: An overall response of 41.4% with a median duration of 11.9 months for stable disease and 19.5 months for complete response (CR) patients was achieved. The disease risk index (DRI) high-/very high-risk patients had a shorter OS of 4.4 months than intermediate-risk patients, with 14.5 months, p = 0.007. At transplant, WT1-overexpressing patients (>150 copies) had a shorter median OS of 5.3 months than low-WT1-expressing ones, with 13.5 months, p = 0.024. Furthermore, patients with ≤1000 WT1 copies at relapse had a significantly longer OS with 15.3 months than patients overexpressing WT1, with 4.4 months, p = 0.0002. Conclusions: DRI and WT1 expression associate significantly with OS after AZA/DLI. Hence, WT1 may represent an MRD marker, especially in CR patients at high risk.
Mechanistic Insights into the Successful Development of Combination Therapy of Enfortumab Vedotin and Pembrolizumab for the Treatment of Locally Advanced or Metastatic Urothelial Cancer
Authors: Taylor Caroline , Patterson Kamai M. , Friedman Devira , Bacot Silvia M. , Feldman Gerald M. , Wang Tao
Published: September 2024

Antibody–drug conjugates (ADCs) consist of an antibody backbone that recognizes and binds to a target antigen expressed on tumor cells and a small molecule chemotherapy payload that is conjugated to the antibody via a linker. ADCs are one of the most promising therapeutic modalities for the treatment of various cancers. However, many patients have developed resistance to this form of therapy. Extensive efforts have been dedicated to identifying an effective combination of ADCs with other types of anticancer therapies to potentially overcome this resistance. A recent clinical study demonstrated that a combination of the ADC enfortumab vedotin (EV) with the immune checkpoint inhibitor (ICI) pembrolizumab can achieve remarkable clinical efficacy as the first-line therapy for the treatment of locally advanced or metastatic urothelial carcinoma (la/mUC)—leading to the first approval of a combination therapy of an ADC with an ICI for the treatment of cancer patients. In this review, we highlight knowledge and understanding gained from the successful development of EV and the combination therapy of EV with ICI for the treatment of la/mUC. Using urothelial carcinoma as an example, we will focus on dissecting the underlying mechanisms necessary for the development of this type of combination therapy for a variety of cancers.
Abemaciclib Therapy Using the MonarchE Criteria Results in Large Numbers of Excess Axillary Node Clearances—Time to Pause and Reflect?
Authors: Ahari Daniel , Wilkinson Mark , Ali Nisha , Taxiarchi Vicky P. , Dave Rajiv V. , Gandhi Ashu
Published: September 2024

The monarchE study added the CDK4/6 inhibitor abemaciclib to the care of women with oestrogen-positive (ER+) breast cancers. Eligibility required meeting monarchE criteria—either >3 positive axillary nodes, or 1–3 positive sentinel nodes (SNB+) with tumour size >50 mm or grade 3 cancers. Women were advised to proceed to completion axillary node clearance (cANC) if size/grade criteria were not fulfilled for >3 positive nodes to be identified. However, cANC is associated with significant morbidity, conflicting with the potential benefits of abemaciclib. We analysed data of 229 consecutive women (2016-2022) with ER+ breast cancer and SNB+ who proceeded to cANC, keeping with contemporary treatment guidelines. We used this cohort to assess numbers that, under national guidance in place currently, would be advised to undergo cANC solely to check eligibility for abemaciclib treatment. Using monarchE criteria, 90 women (39%) would have accessed abemaciclib based on SNB+ and size/grade, without cANC. In total, 139 women would have been advised to proceed to cANC to check eligibility, with only 15/139 (11%) having >3 positive nodes after sentinel node biopsy and cANC. The remaining 124 (89%) would have undergone cANC but remained ineligible for abemaciclib. Size, age, grade, and Ki67 did not predict >3 nodes at cANC. Following cANC, a large majority of women with ER+, <50 mm, and grade 1–2 tumours remain ineligible for abemaciclib yet are subject to significant morbidity including lifelong lymphoedema risk. The monarchE authors state that 15 women need abemaciclib therapy for 1 to clinically benefit. Thus, in our cohort, 139 women undergoing cANC would lead to one woman benefitting.
Case Report of Concomitant Diagnosis of Locally Advanced Intrahepatic Cholangiocarcinoma and Solitary Plasmacytoma of T11 Vertebra: Impact on Diagnostic and Clinical Management
Authors: Touchefeu Yann , Barbaud Matthieu , Prin-Felix Laura , Samarut Edouard , Jamet Bastien , Ollivier Luc , Bouda Damien
Published: September 2024

A solitary bone plasmacytoma is a rare tumor. Intrahepatic cholangiocarcinoma is the second most common primary liver cancer after hepatocellular carcinoma. We present the case of a 48-year-old female patient who consulted for recent back pain, with a final diagnosis of T10 solitary plasmacytoma and synchronous intrahepatic cholangiocarcinoma. Imaging suggested cholangiocarcinoma with bone metastasis. The patient underwent neurosurgical management with laminectomy, arthrodesis, and arthrectomy, with biopsies revealing monotypic kappa plasmacytic proliferation. Liver biopsies revealed an adenocarcinoma with expression of cytokeratin 19, cytokeratin 7, N-cadherin, and high expression of carbonic anydrase IX. The plasmacytoma was treated with external radiotherapy. The cholangiocarcinoma was treated with selective internal radiation therapy and concomitant systemic treatment with combinations of cisplatin and durvalumab, with capecitabine during radiotherapy, switched for gemcitabine after completion of irradiation. One year after initial management, imaging revealed a partial metabolic response of the intrahepatic cholangiocarcinoma, and a complete metabolic response of the plasmacytoma. This case illustrates the importance of not ignoring two primary tumors and the management of two concomitant treatments exploiting potential therapeutic synergies and limiting expected toxicities.
Correction: Xie et al. AliasClassifier: A High-Performance Router Alias Classifier. Electronics 2024, 13, 1747
Authors: Xie Yuancheng , Zhang Zhaoxin , Chen Enhao , Li Ning
Published: September 2024

In the original publication [...]
Geometry-Aware Weight Perturbation for Adversarial Training
Authors: Jiang Yixuan , Chiang Hsiao-Dong
Published: September 2024

Adversarial training is one of the most successful approaches to improve model robustness against maliciously crafted data. Instead of training on a clean dataset, the model is trained on adversarial data generated on the fly. Based on that, a group of geometry-aware methods are proposed to further enhance the model robustness by assigning higher weights to the data points that are closer to the decision boundary during training. Although the robustness against the adversarial attack seen in the training process is significantly improved, the model becomes more vulnerable to unseen attacks, and the reason for the issue remains unclear. In this paper, we investigate the cause of the issue and claim that such geometry-aware methods lead to a sharp minimum, which results in poor robustness generalization for unseen attacks. Furthermore, we propose a remedy for the issue by imposing the adversarial weight perturbation mechanism and further develop a novel weight perturbation strategy called Geometry-Aware Weight Perturbation (GAWP). Extensive results demonstrate that the proposed method alleviates the robustness generalization issue of geometry-aware methods while consistently improving model robustness compared to existing weight perturbation strategies.
Differential Privacy-Based Location Privacy Protection for Edge Computing Networks
Authors: Zhang Guowei , Du Jiayuan , Yuan Xiaowei , Zhang Kewei
Published: September 2024

Mobile Edge Computing (MEC) has been widely applied in various Internet of Things (IoT) scenarios due to its advantages of low latency and low energy consumption. However, the offloading of tasks generated by terminal devices to edge servers inevitably raises privacy leakage concerns. Given the limited resources in MEC networks, this paper proposes a task scheduling strategy, named DQN-DP, to minimize location privacy leakage under the constraint of offloading costs. The strategy is based on a differential privacy location obfuscation probability density function. Theoretical analysis demonstrates that the probability density function employed in this study is valid and satisfies ϵ-differential privacy in terms of security. Numerical results indicate that, compared to existing baseline approaches, the proposed DQN-DP algorithm effectively balances privacy leakage and offloading cost. Specifically, DQN-DP reduces privacy leakage by approximately 20% relative to baseline approaches.
New Insights into Remote Sensing of Vegetation Structural Parameters
Authors: Yan Kai , Ding Chao , Qi Jianbo
Published: September 2024

The accurate and efficient estimation of vegetation structural parameters from remote sensing is a pivotal subject within the field of remote sensing [...]
Bursaphelenchus xylophilus in Pinus sylvestris—The First Report in Europe
Authors: Fonseca Luís , Silva Hugo , Cardoso Joana M. S. , Esteves Ivânia , Maleita Carla , Lopes Sónia , Abrantes Isabel
Published: September 2024

The pinewood nematode (PWN), Bursaphelenchus xylophilus, is the causal agent of pine wilt disease and is considered an A2 quarantine organism by the European Plant Protection Organisation. In Europe, this nematode has been reported in Pinus pinaster, P. radiata, and P. nigra. In May 2024, severe wilting symptoms were observed in P. sylvestris trees at Serra da Lousã (Coimbra, the central area of continental Portugal). Wood samples were collected from six wilted trees, and the presence of PWN was investigated. From these, B. xylophilus specimens were detected in five out of the six trees. Species identification was performed based on species-specific morphological diagnostic characters, and this was confirmed by real-time PCR using species-specific primers targeting the B. xylophilus satellite DNA region. This study presents the first detection of B. xylophilus in P. sylvestris in Portugal and in Europe.
A Micro-Segmentation Method Based on VLAN-VxLAN Mapping Technology
Authors: Li Di , Yang Zhibang , Yu Siyang , Duan Mingxing , Yang Shenghong
Published: September 2024

As information technology continues to evolve, cloud data centres have become increasingly prominent as the preferred infrastructure for data storage and processing. However, this shift has introduced a new array of security challenges, necessitating innovative approaches distinct from traditional network security architectures. In response, the Zero Trust Architecture (ZTA) has emerged as a promising solution, with micro-segmentation identified as a crucial component for enabling continuous auditing and stringent security controls. VxLAN technology is widely utilized in data centres for tenant isolation and virtual machine interconnection within tenant environments. Despite its prevalent use, limited research has focused on its application in micro-segmentation scenarios. To address this gap, we propose a method that leverages VLAN and VxLAN many-to-one mapping, requiring that all internal data centre traffic routes through the VxLAN gateway. This method can be implemented cost-effectively, without necessitating business modifications or causing service disruptions, thereby overcoming the challenges associated with micro-segmentation deployment. Importantly, this approach is based on standard public protocols, making it independent of specific product brands and enabling a network-centric framework that avoids software compatibility issues. To assess the effectiveness of our micro-segmentation approach, we provide a comprehensive evaluation that includes network aggregation and traffic visualization. Building on the implementation of micro-segmentation, we also introduce an enhanced asset behaviour algorithm. This algorithm constructs behavioural profiles based on the historical traffic of internal network assets, enabling the rapid identification of abnormal behaviours and facilitating timely defensive actions. Empirical results demonstrate that our algorithm is highly effective in detecting anomalous behaviour in intranet assets, making it a powerful tool for enhancing security in cloud data centres. In summary, the proposed approach offers a robust and efficient solution to the challenges of micro-segmentation in cloud data centres, contributing to the advancement of secure and reliable cloud infrastructure.
Ongoing Excess Hospitalizations for Severe Pediatric Group A Streptococcal Disease in 2023–2024—A Single-Center Report
Authors: Schöbi Nina , Duppenthaler Andrea , Horn Matthias , Bartenstein Andreas , Keitel Kristina , Kopp Matthias V. , Agyeman Philipp K. A. , Aebi Christoph
Published: September 2024

A Europe-wide outbreak of invasive pediatric group A streptococcal infections (iGAS) began in fall 2022. Here, we report the evolution of GAS hospitalizations in children and adolescents during the second outbreak year in 2023–2024 at a tertiary center in Switzerland. Using prospective monitoring of all in-patient GAS cases below 16 years of age, including those with iGAS, we compared case frequencies and clinical characteristics in three time periods (2013–2020; 2022–2023; 2023–2024). Annual GAS hospitalizations increased from a median of 25 cases (range 11–28) in 2013–2020 to 89 and 63 cases, respectively, in 2022–2023 and 2023–2024. iGAS cases evolved similarly (2013–2020, 4 cases (3–8); 2022–2023, 32 cases; 2023–2024, 21 cases). The decline in cases from 2022–2023 to 2023–2024 included all types of GAS organ involvement, except suppurative infections in the head area, which remained largely unchanged (48 vs. 45 cases). Pleural empyema declined from 13 to 7 cases, possibly explained by a poor overlap of the GAS and influenza curves, respectively, in 2023–2024 compared to 2022–2023. These data document the prolongation of the GAS outbreak into its second winter season in 2023–2024.
Pertussis Notification Rate and Tdpa Vaccine/Booster Coverage in Adults: An Opportunity for an Epidemiological Observatory in Primary Care
Authors: Lapi Francesco , Marconi Ettore , Cricelli Iacopo , Rossi Alessandro , Mastronuzzi Tecla , Gabutti Giovanni , Cricelli Claudio
Published: September 2024

Background: In recent years, Europe has experienced a significant increase in pertussis cases. One reason behind this rise is the decline in diphtheria–tetanus–pertussis (dTap) booster coverage among adults. Currently, Italy lacks a reliable monitoring system to track pertussis infections and vaccine coverage among adults. We therefore evaluated the reliability of a primary care framework to respond to this need. Methods: Using an Italian primary care database for individuals aged 15 or above, we determined the pertussis infection notification rate and dTap vaccine/booster coverage for the timeframe of 2009–2022. Results: In the overall population, we obtained a lifetime occurrence rate of pertussis infections of 7.52 per 10,000 individuals. The annual incidence rates of pertussis infections ranged from 0.008 to 0.001 per 10,000 person-years between 2009 and 2022. A rising trend in dTap vaccine coverage rate (ranging from 8.72 to 16.54 vaccines per 10,000 individuals) was observed during the same period. Notably, those aged 65 or older, smokers, and/or individuals with immunodeficiencies were more likely to receive the dTap vaccine compared to the general population. Conclusions: Given the organization of the Italian public health system, this primary care network might act as a reliable epidemiological monitoring system to keep track of pertussis infections and dTap vaccine coverage in adults. Pertussis cases were underreported, and there was a low uptake of vaccines and boosters. Therefore, it is crucial to closely monitor pertussis notifications and dTap administrations and develop intervention strategies at the national level to enhance vaccine-related prevention.
Dominant Chemical Interactions Governing the Folding Mechanism of Oligopeptides
Authors: Larocca Michele , Floresta Giuseppe , Verderese Daniele , Cilibrizzi Agostino
Published: September 2024

The hydrophobic effect is the main factor that drives the folding of polypeptide chains. In this study, we have examined the influence of the hydrophobic effect in the context of the main mechanical forces approach, mainly in relation to the establishment of specific interplays, such as hydrophobic and CH–π cloud interactions. By adopting three oligopeptides as model systems to assess folding features, we demonstrate herein that these finely tuned interactions dominate over electrostatic interactions, including H-bonds and electrostatic attractions/repulsions. The folding mechanism analysed here demonstrates cooperation at the single-residue level, for which we propose the terminology of “single residues cooperative folding”. Overall, hydrophobic and CH–π cloud interactions produce the main output of the hydrophobic effect and govern the folding mechanism, as demonstrated in this study with small polypeptide chains, which in turn represent the main secondary structures in proteins.
Innovative Strategies in 3D Bioprinting for Spinal Cord Injury Repair
Authors: Kim Daniel Youngsuk , Liu Yanting , Kim Gyubin , An Seong Bae , Han Inbo
Published: September 2024

Spinal cord injury (SCI) is a catastrophic condition that disrupts neurons within the spinal cord, leading to severe motor and sensory deficits. While current treatments can alleviate pain, they do not promote neural regeneration or functional recovery. Three-dimensional (3D) bioprinting offers promising solutions for SCI repair by enabling the creation of complex neural tissue constructs. This review provides a comprehensive overview of 3D bioprinting techniques, bioinks, and stem cell applications in SCI repair. Additionally, it highlights recent advancements in 3D bioprinted scaffolds, including the integration of conductive materials, the incorporation of bioactive molecules like neurotrophic factors, drugs, and exosomes, and the design of innovative structures such as multi-channel and axial scaffolds. These innovative strategies in 3D bioprinting can offer a comprehensive approach to optimizing the spinal cord microenvironment, advancing SCI repair. This review highlights a comprehensive understanding of the current state of 3D bioprinting in SCI repair, offering insights into future directions in the field of regenerative medicine.
Word Sense Disambiguation for Morphologically Rich Low-Resourced Languages: A Systematic Literature Review and Meta-Analysis
Authors: Masethe Hlaudi Daniel , Masethe Mosima Anna , Ojo Sunday Olusegun , Giunchiglia Fausto , Owolawi Pius Adewale
Published: September 2024

In natural language processing, word sense disambiguation (WSD) continues to be a major difficulty, especially for low-resource languages where linguistic variation and a lack of data make model training and evaluation more difficult. The goal of this comprehensive review and meta-analysis of the literature is to summarize the body of knowledge regarding WSD techniques for low-resource languages, emphasizing the advantages and disadvantages of different strategies. A thorough search of several databases for relevant literature produced articles assessing WSD methods in low-resource languages. Effect sizes and performance measures were extracted from a subset of trials through analysis. Heterogeneity was evaluated using pooled effect and estimates were computed by meta-analysis. The preferred reporting elements for systematic reviews and meta-analyses (PRISMA) were used to develop the process for choosing the relevant papers for extraction. The meta-analysis included 32 studies, encompassing a range of WSD methods and low-resourced languages. The overall pooled effect size indicated moderate effectiveness of WSD techniques. Heterogeneity among studies was high, with an I2 value of 82.29%, suggesting substantial variability in WSD performance across different studies. The (τ2) tau value of 5.819 further reflects the extent of between-study variance. This variability underscores the challenges in generalizing findings and highlights the influence of diverse factors such as language-specific characteristics, dataset quality, and methodological differences. The p-values from the meta-regression (0.454) and the meta-analysis (0.440) suggest that the variability in WSD performance is not statistically significantly associated with the investigated moderators, indicating that the performance differences may be influenced by factors not fully captured in the current analysis. The absence of significant p-values raises the possibility that the problems presented by low-resource situations are not yet well addressed by the models and techniques in use.