bluuebunny/crossref_metadata_2025 huggingface dataset:
Preferential Expansion of HPV16 E1-Specific T Cells from Healthy Donors’ PBMCs after Ex Vivo Immunization with an E1E2E6E7 Fusion Antigen
Authors: Daradoumis Joana , Müller Mikkel Dons , Neckermann Patrick , Asbach Benedikt , Schrödel Silke , Thirion Christian , Wagner Ralf , thor Straten Per , Holst Peter Johannes , Boilesen Ditte
Published: December 2023

Persistent human papillomavirus (HPV) infection is responsible for practically all cervical and a high proportion of anogenital and oropharyngeal cancers. Therapeutic HPV vaccines in clinical development show great promise in improving outcomes for patients who mount an anti-HPV T-cell response; however, far from all patients elicit a sufficient immunological response. This demonstrates a translational gap between animal models and human patients. Here, we investigated the potential of a new assay consisting of co-culturing vaccine-transduced dendritic cells (DCs) with syngeneic, healthy, human peripheral blood mononuclear cells (PBMCs) to mimic a human in vivo immunization. This new promising human ex vivo PBMC assay was evaluated using an innovative therapeutic adenovirus (Adv)-based HPV vaccine encoding the E1, E2, E6, and E7 HPV16 genes. This new method allowed us to show that vaccine-transduced DCs yielded functional effector T cells and unveiled information on immunohierarchy, showing E1-specific T-cell immunodominance over time. We suggest that this assay can be a valuable translational tool to complement the known animal models, not only for HPV therapeutic vaccines, and supports the use of E1 as an immunotherapeutic target. Nevertheless, the findings reported here need to be validated in a larger number of donors and preferably in patient samples.
Relevance of Molecular Pathology for the Diagnosis of Sex Cord–Stromal Tumors of the Ovary: A Narrative Review
Authors: Trecourt Alexis , Donzel Marie , Alsadoun Nadjla , Allias Fabienne , Devouassoux-Shisheboran Mojgan
Published: December 2023

Ovarian sex cord–stromal tumors (SCSTs) account for 8% of all primary ovarian neo-plasms. Accurate diagnosis is crucial since each subtype has a specific prognostic and treatment. Apart from fibrosarcomas, stromal tumors are benign while sex cord tumors may recur, sometimes with a significant time to relapse. Although the diagnosis based on morphology is straightforward, in some cases the distinction between stromal tumors and sex cord tumors may be tricky. Indeed, the immunophenotype is usually nonspecific between stromal tumors and sex cord tumors. Therefore, molecular pathology plays an important role in the diagnosis of such entities, with pathognomonic or recurrent alterations, such as FOXL2 variants in adult granulosa cell tumors. In addition, these neoplasms may be associated with genetic syndromes, such as Peutz–Jeghers syndrome for sex cord tumors with annular tubules, and DICER1 syndrome for Sertoli–Leydig cell tumors (SLCTs), for which the pathologist may be in the front line of syndromic suspicion. Molecular pathology of SCST is also relevant for patient prognosis and management. For instance, the DICER1 variant is associated with moderately to poorly differentiated SLCTS and a poorer prognosis. The present review summarizes the histomolecular criteria useful for the diagnosis of SCST, using recent molecular data from the literature.
Effect of High-Energy Milling on Ceria-Zirconia’s Redox Properties
Authors: Bortun Anatoly , Bortun Mila , Brown Benjamin , Madynski Jeremy
Published: December 2023

Series of ceria-zirconia (CZ)-based nano-materials with a d50 in the range of 0.2 to 1.3 microns were made using the jar milling, Eiger milling, and steam jet milling (SJM) techniques. The effect of the milling conditions on the morphology and textural properties was studied. High-energy steam jet milling in a quasi-hydrothermal environment (with potential local temperature spikes over 500 °C) significantly impacted the CZ crystal structure by inducing lattice distortions. It was shown that the acquired lattice stress resulted in a significant increase in oxygen mobility, which was manifested by a TPR-H2 Tmax shift from 450–550 to 150–250 °C. CZ materials with fast oxygen mobility are metastable phases, and re-slurring nano-CZ powders in water and impregnation with precious metals had stabilizing effects on fast oxygen mobility. Efficiently enhancing the CZ redox activity milling process took place in the following order: Steam jet milling > Eiger milling > jar milling.
Modified Gasification-Slag-Driven Persulfate Activation for Highly Efficient Degradation of Acetaminophen: N/O Active Site Regulation and Nonradical Oxidation
Authors: Si Wenhao , Qi Fei , Wang Kangjun , Wang Qiang , Zeng Zequan , Niu Yuting , Huang Zhanggen
Published: December 2023

With the development of coal chemical technology, a large amount of gasification slag and wastewater are produced through coal gasification. Efficient gasification slag utilization and wastewater treatment have attracted much attention. In this study, gasification slag was modified and used as a low-cost and efficient catalyst to activate persulfate for acetaminophen degradation. Via the analysis of high-resolution X-ray photoelectron spectroscopy, the surfaces of nitric acid and calcined modified gasification slag retained a considerable number of carbonyl and graphite N functional groups. These proved to be effective active sites for the activation of persulfate. X-ray diffraction analysis revealed that the gasification slag was composed of carbon and SiO2. The evaluation of catalytic activity and application of density functional theory proved that the interaction between carbonyl and graphitic nitrogen significantly affected the catalyst activity. When the ratio of graphitic nitrogen to carbonyl was 1:3, the adsorption and activation of persulfate were significantly enhanced. The results of the quenching experiments also confirmed that the non-free radical pathway is the main pathway to activate persulfate using the gasification slag. This study provides a new approach to industrial waste utilization in wastewater treatment.
Heterogeneous Catalysts for Carbon Dioxide Methanation: A View on Catalytic Performance
Authors: Memon Mazhar , Jiang Yanan , Hassan Muhammad , Ajmal Muhammad , Wang Hong , Liu Yuan
Published: December 2023

CO2 methanation offers a promising route for converting CO2 into valuable chemicals and energy fuels at the same time as hydrogen is stored in methane, so the development of suitable catalysts is crucial. In this review, the performance of catalysts for CO2 methanation is presented and discussed, including noble metal-based catalysts and non-noble metal-based catalysts. Among the noble metal-based catalysts (Ru, Rh, and Pd), Ru-based catalysts show the best catalytic performance. In the non-noble metal catalysts, Ni-based catalysts are the best among Ni-, Co-, and Fe-based catalysts. The factors predominantly affecting catalytic performance are the dispersion of the active metal; the synergy of the active metal with support; and the addition of dopants. Further comprehensive investigations into (i) catalytic performance under industrial conditions, (ii) stability over a much longer period and (iii) activity enhancement at low reaction temperatures are anticipated to meet the industrial applications of CO2 methanation.
Immunogenic Cell Stress and Death Sensitize Tumors to Immunotherapy
Authors: Kepp Oliver , Kroemer Guido
Published: December 2023

The efficacy of chemotherapy with cytotoxicants and that of targeted therapies with more sophisticated agents is limited due to the plasticity of malignant cells, which leads to the inevitable development of resistance [...]
Microwave-Assisted Synthesis of Titanosilicates Using a Precursor Produced from Titanium Ore Concentrate
Authors: Kalashnikova Galina O. , Gryaznova Darya V. , Baranchikov Alexander E. , Britvin Sergey N. , Yakovenchuk Victor N. , Samburov Gleb O. , Veselova Varvara O. , Pulyalina Aleksandra Y. , Pakhomovsky Yakov A. , Bazai Ayya V. , Glazunova Margarita Y. , Shirokaya Anna A. , Kozerozhets Irina V. , Nikolaev Anatoly I. , Ivanov Vladimir K.
Published: December 2023

Titanosilicates comprise a broad class of materials with promising technological applications. The typical obstacle that restricts their industrial applicability is the high manufacturing cost due to the use of specific organotitanium precursors. We herein report a new approach to the synthesis of titanosilicates using an inexpensive inorganic precursor, ammonium titanyl sulfate (ATS or STA), (NH4)2TiO(SO4)2∙H2O. The latter is an intermediate in the processing of titanium-bearing concentrates produced from apatite-nepheline ores. In this paper, the new synthetic approach is exemplified by the microwave-assisted synthesis of IONSIVE-911, one of the most effective Cs-ion scavengers. The method can be modified to synthesize various titanosilicate compounds.
Comparative GIS Analysis of Public Transport Accessibility in Metropolitan Areas
Authors: Biswas Arnab , Adhinugraha Kiki , Taniar David
Published: December 2023

With urban areas facing rapid population growth, public transport plays a key role to provide efficient and economic accessibility to the residents. It reduces the use of personal vehicles leading to reduced traffic congestion on roads and reduced pollution. To assess the performance of these transport systems, prior studies have taken into consideration the blank spot areas, population density, and stop access density; however, very little research has been performed to compare the accessibility between cities using a GIS-based approach. This paper compares the access and performance of public transport across Melbourne and Sydney, two cities with a similar size, population, and economy. The methodology uses spatial PostGIS queries to focus on accessibility-based approach for each residential mesh block and aggregates the blank spots, and the number of services offered by time of day and the frequency of services at the local government area (LGA) level. The results of the study reveal an interesting trend: that with increase in distance of LGA from city centre, the blank spot percentage increases while the frequency of services and stops offering weekend/night services declines. The results conclude that while Sydney exhibits a lower percentage of blank spots and has better coverage, performance in terms of accessibility by service time and frequency is better for Melbourne’s LGAs, even as the distance increases from the city centre.
Pavement Analysis with the Consideration of Unbound Granular Material Nonlinearity
Authors: Gkyrtis Konstantinos
Published: December 2023

Accurate pavement design and evaluation requires the execution of response analysis. Pavement materials’ behavior does not necessarily conform to the assumptions of the multi-linear elastic theory usually adopted during pavement analysis. In particular, the unbound granular materials located in the base and sub-base layers behave in a nonlinear elastic manner, which can be captured through advanced constitutive modeling of their resilient modulus. The finite element method enables us to code constitutive models and quantify potential variations in pavement responses because of different mechanistic assumptions. In this study, variations in response are investigated for a typical structure of a flexible pavement considering the nonlinear anisotropic behavior of the unbound materials together with their initial stress–strain state. To demonstrate the impact of their behavior on the outcome of pavement analysis, variable asphalt concrete layer thicknesses and moduli are assumed, such that they cover a large spectrum of roadways. It was found that pavement responses can be calculated up to 3.5 times higher than those retrieved from the conventional linear analysis. This comparison means that the alterative mechanistic modeling of the unbound granular materials can be proved to be more conservative (i.e., leading to higher strains) in terms of pavement design and analysis. From a practical perspective, this study alerts pavement scientists and engineers engaged in pavement design to a more reliable performance prediction, which is needed to bridge the gap between advanced modeling and routine analysis.
The Challenge to Stabilize, Extract and Analyze Urinary Cell-Free DNA (ucfDNA) during Clinical Routine
Authors: Nel Ivonne , Münch Carolin , Shamkeeva Saikal , Heinemann Mitja L. , Isermann Berend , Aktas Bahriye
Published: December 2023

Background: The “Liquid Biopsy” has become a powerful tool for cancer research during the last decade. Circulating cell-free DNA (cfDNA) that originates from tumors has emerged as one of the most promising analytes. In contrast to plasma-derived cfDNA, only a few studies have investigated urinary cfDNA. One reason might be rapid degradation and hence inadequate concentrations for downstream analysis. In this study, we examined the stability of cfDNA in urine using different methods of preservation under various storage conditions. Methodology: To mimic patient samples, a pool of healthy male and female urine donors was spiked with a synthetic cfDNA reference standard (fragment size 170 bp) containing the T790M mutation in the EGFR gene. Spiked samples were preserved with three different buffers and with no buffer over four different storage periods (0 h; 4 h; 12 h; 24 h) at room temperature vs. 4 °C. The preservatives used were Urinary Analyte Stabilizer (UAS, Novosanis, Wijnegem, Belgium), Urine Conditioning Buffer (UCB, Zymo, Freiburg, Germany) and a self-prepared buffer called “AlloU”. CfDNA was extracted using the QIAamp MinElute ccfDNA Mini Kit (Qiagen, Hilden, Germany). CfDNA concentration was measured using the Qubit™ 4 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA). Droplet digital PCR (ddPCR) was used for detection and quantification of the T790M mutation. Results: Almost no spiked cfDNA was recoverable from samples with no preservation buffer and the T790M variant was not detectable in these samples. These findings indicate that cfDNA was degraded below the detection limit by urinary nucleases. Stabilizing buffers showed varying efficiency in preventing this degradation. The most effective stabilizing buffer under all storage conditions was the UAS, enabling adequate recovery of the T790M variant using ddPCR. Conclusion: From a technical point of view, stabilizing buffers and adequate storage conditions are a prerequisite for translation of urinary cfDNA diagnostics into clinical routine.
Design and Simulate Intracranial Support to Guide Maxillo Surgery: A Study Based on Bioengineering
Authors: Cristofaro Maria Giulia , Kallaverja Elvis , Ferragina Francesco , Barca Ida
Published: December 2023

Background: Intraoperative navigation allows for the creation of a real-time relationship between the anatomy imagined during diagnosis/planning and the site of surgical interest. This procedure takes place by identifying and registering trustworthy anatomical markers on planning images and using a point locator during the operation. The locator is calibrated in the workspace by placing a Dynamic Reference Frame (DRF) sensor. Objective: This study aims to calculate the localization accuracy of an electromagnetic locator of neuro-maxillofacial surgery, moving the standard sensor position to a different position more suitable for maxillofacial surgery. Materials and Methods: The upper dental arch was chosen as an alternative fixed point for the positioning of the sensor. The prototype of a bite support device was designed and generated via 3D printing. CT images of a skull phantom with 10 anatomical landmarks were acquired. The testing procedure consisted of 10 measurements for each position of the sensor: precisely 10 measurements with the sensor placed on the forehead and 10 measurements with the sensor placed on the bite support device. It also evaluated the localization error by comparing the two procedures. Results: The localization error, when the sensor was placed on the bite support device, was lower in the sphere located on the temporal bone. It was the same in the spheres located on the maxillary bone. The test analysis of the data of the new device showed that it is reliable; the tests are reproducible and can be considered as accurate as the traditional ones. In addition, the sensor mounted on this device has proven to be slightly superior in terms of accuracy and accuracy in areas such as the middle third of the face and jaw. Discussion and Conclusion: The realization of the bite support device allowed the sensor to change position concerning its natural site. This procedure allows us to explore structures, such as the frontal site, which were initially difficult to approach with neuronavigation and improves the approach to midface structures, already studied with neuronavigation. The new calibration, with the position of the sensor on the support device in the same reference points sphere, highlighted the reduction in the location error. We can say that the support proposed in this study lays the foundations for a new navigation approach for patients in maxillofacial surgery, by changing the position of the sensor. It has strong points in improving the localization error for some reference points without determining disadvantages both in the calibration and in the surgical impediment.
Recent Advances in Statistical Theory and Applications
Authors: Wong Augustine , Shi Xiaoping
Published: December 2023

Complex data pose unique challenges for data processing [...]
Does Gender Equality in Managerial Positions Improve the Gender Wage Gap? Comparative Evidence from Europe
Authors: de Castro Romero Lidia , Martín Barroso Víctor , Santero-Sánchez Rosa
Published: December 2023

In this paper, we analyse the impact of gender equality in managerial positions on wages and the gender wage gap in 22 European countries. We draw on the employer–employee microdata from the European Structure of Earnings Survey (E-SES) for the year 2018, which allows us to include firm fixed effects in our econometric specifications, thus controlling for both observed and unobserved heterogeneity at the firm level. The analysis is carried out not only at the mean but also across the wage distribution through unconditional quantile regressions. The results on the impact of gender equality in management on wages are mixed. However, we find that gender equality has a predominantly positive effect in the upper part of the wage distribution, and a negative effect in the middle and lower parts. The results on the impact on the gender wage gap show that in many cases, a more gender-equal management reduces the gender wage gap. Furthermore, gender equality in management reduces the gender wage gap mainly in the middle and lower part of the wage distribution.
A Study on Undergraduate English Program Modes in China
Authors: Chen Siyu , Zhang Yining , Li Runfeng
Published: December 2023

While English major education is of significant importance in China, there is a lack of comprehensive research that provides a broader perspective, encompassing a thorough exploration and comparison of the diverse program modes employed across different undergraduate English programs in China. The focus of this study is to (1) discern the overarching characteristics of undergraduate English programs in China; (2) identify undergraduate English program modes in China; and (3) delve into the relationship between the identified modes and university discipline evaluation rankings. The dataset includes undergraduate English program handbooks from 50 universities in China and information on 2942 courses extracted from these handbooks. The findings suggest that English programs in universities and colleges in China exhibit a predominantly application-oriented approach. In addition, three modes were identified: Literature and Linguistics, Balanced, and High English Skills. The High English Skill mode was found to be linked with a lower ranking compared to the High Literature and Linguistics mode. The study concludes by offering implications for the design of a future English program based on the insights gained from the analysis.
A Secure and Efficient Dynamic Analysis Scheme for Genome Data within SGX-Assisted Servers
Authors: Li Bao , Zhou Fucai , Wang Qiang , Feng Da
Published: December 2023

With the rapid development of the Internet of Things (IoT), more and more user devices access the network and generate large amounts of genome data. These genome data possess significant medical value when researched. However, traditional genome analysis confronts security and efficiency challenges, including access pattern leakage, low efficiency, and single analysis methods. Thus, we propose a secure and efficient dynamic analysis scheme for genome data within a Software Guard Extension (SGX)-assisted server, called SEDASGX. Our approach involves designing a secure analysis framework based on SGXs and implementing various analysis methods within the enclave. The access pattern of genome data is always obfuscated during the analysis and update process, ensuring privacy and security. Furthermore, our scheme not only achieves higher analysis efficiency but also enables dynamic updating of genome data. Our results indicate that the SEDASGX analysis method is nearly 2.5 times more efficient than non-SGX methods, significantly enhancing the analysis speed of large-scale genome data.
Prototypical Network with Residual Attention for Modulation Classification of Wireless Communication Signals
Authors: Zang Bo , Gou Xiaopeng , Zhu Zhigang , Long Lulan , Zhang Haotian
Published: December 2023

Automatic modulation classification (AMC) based on data-driven deep learning (DL) can achieve excellent classification performance. However, in the field of electronic countermeasures, it is difficult to extract salient features from wireless communication signals under scarce samples. Aiming at the problem of modulation classification under scarce samples, this paper proposes a few-shot learning method using prototypical network (PN) with residual attention (RA), namely PNRA, to achieve the AMC. Firstly, the RA is utilized to extract the feature vector of wireless communication signals. Subsequently, the feature vector is mapped to a new feature space. Finally, the PN is utilized to measure the Euclidean distance between the feature vector of the query point and each prototype in this space, determining the type of the signals. In comparison to mainstream few-shot learning (FSL) methods, the proposed PNRA can achieve effective and robust AMC under the data-hungry condition.
Intelligent Visual Representation for Java Code Data in the Field of Software Engineering Based on Remote Sensing Techniques
Authors: Li Dian , Wang Weidong , Zhao Yang
Published: December 2023

In the field of software engineering, large and complex code bases may lead to some burden of understanding their structure and meaning for developers. To reduce the burden on developers, we consider a code base visualization method to visually express the meaning of code bases. Inspired by remote sensing imagery, we employ graphical representations to illustrate the semantic connections within Java code bases, aiming to help developers understand its meaning and logic. This approach is segmented into three distinct levels of analysis. First, at the project-level, we visualize Java projects by portraying each file as an element within a code forest, offering a broad overview of the project’s structure. This macro-view perspective aids in swiftly grasping the project’s layout and hierarchy. Second, at the file-level, we concentrate on individual files, using visualization techniques to highlight their unique attributes and complexities. This perspective enables a deeper understanding of each file’s structure and its role within the larger project. Finally, at the component-level, our focus shifts to the detailed analysis of Java methods and classes. We examine these components for complexity and other specific characteristics, providing insights that are crucial for the optimization of code and the enhancement of software quality. By integrating remote sensing technology, our method offers software engineers deeper insights into code quality, significantly enhancing the software development lifecycle and its outcomes.
Cross-Chain Asset Transaction Method Based on Ring Signature for Identity Privacy Protection
Authors: Zhang Shuhui , Zhou Ruiyao , Wang Lianhai , Xu Shujiang , Shao Wei
Published: December 2023

In recent years, the rapid development of blockchain technology has facilitated the transfer of value and asset exchange between different blockchains. However, achieving interoperability among various blockchains necessitates the exploration of cross-chain technology. While cross-chain technology enables asset flow between different blockchains, it also introduces the risk of identity privacy leakage, thus posing a significant threat to user security. To tackle this issue, this article proposes a cross-chain privacy protection scheme that leverages ring signature and relay chain technology. Specifically, this scheme utilizes RCROSS contracts based on ring signatures to handle cross-chain transactions, thereby ensuring the privacy of both parties involved in the transaction. This cross-chain solution demonstrates practicality and efficiency in facilitating cross-chain asset trading. Furthermore, it effectively combats reuse attacks and man-in-the-middle attacks at the application layer while also providing resistance against denial-of-service attacks at the network layer. To validate the proposed cross-chain solution, we conducted tests by constructing a specific cross-chain scenario and by focusing on the natural gas consumption values generated by the RCROSS contract function used in the application chain. The findings indicate that our proposed solution is highly practical in safeguarding the identity privacy of transaction participants. This article’s framework guarantees reliability, security, and efficiency in cross-chain asset transactions. By incorporating ring-based signatures and relay chain technology, users can confidently protect their identity privacy, thus ensuring secure and smooth cross-chain transactions.
Super-Regenerative Receiver Wake-Up Radio Solution for 5G New Radio Communications
Authors: Moncunill-Geniz Francesc Xavier , del-Águila-López Francisco , Demirkol Ilker , Bonet-Dalmau Jordi , Palà-Schönwälder Pere
Published: December 2023

Wake-up radio is a promising solution to reduce the energy wasted by mobile devices during an idle state. In this paper, we propose a new wake-up radio solution for 5G mobile devices based on a super-regenerative receiver characterized by its low cost and low power consumption and investigate how to build on the orthogonal frequency-division multiplexing (OFDM) modulation capability at the base station to generate optimal wake-up signals. After presenting the relevant features and limitations of super-regenerative receivers operating in different 5G New Radio (NR) frequency bands, we evaluate how the numerology, the number of resource blocks, and the quadrature amplitude modulation (QAM) scheme used affect the sensitivity of the super-regenerative wake-up receiver. The results show that a 256-QAM modulation scheme, together with the highest numerology values, achieves optimal receiver sensitivity with a minimal number of resource blocks, yielding higher duty cycle pulses that also facilitate symbol synchronization tasks.
Implementation of High-Speed Compact Level-Up Shifter for Nano-Scale Applications
Authors: Sudhakar Muppidi Venkata , Stan Ovidiu Petru
Published: December 2023

The objective of this study is to present a level shifter architecture that utilizes a pair of inverters and a Wilson current mirror to reduce power consumption while improving voltage shifting capabilities. We introduce novel components such as super-cut-off pull-down and stacked pull-up networks to effectively minimize leakage power. Our design leverages multi-threshold CMOS (MTCMOS) technology, incorporating sleep transistors to boost operational speed, decrease power consumption, and reduce the physical footprint. The proposed circuit is engineered to step up voltage levels, ranging from a mere 0.4 V to a substantial 1.2 V. Through extensive optimization of performance parameters, including power efficiency, delay, and area utilization, we have tailored this design to cater specifically to the demands of nano-scale applications. Key results from our research reveal that the average active power consumption for “level-up” shifts is impressively low at 48.5 nW, with an average latency of a mere 1.58 ns for 1 MHz transmission frequencies. Post-layout modeling demonstrates that our suggested design occupies a compact area of just 9.97 µm2. These findings were meticulously modeled using Cadence Virtuoso with 45 nm processes. Furthermore, our research highlights the substantial advancements achieved when compared to previous methods. The proposed design boasts a threefold increase in operational speed and delivers significant savings in both area and power consumption. These outcomes have far-reaching implications for emerging technologies and applications in the field.
Personalized Federated Learning Based on Bidirectional Knowledge Distillation for WiFi Gesture Recognition
Authors: Geng Huan , Deng Dongshang , Zhang Weidong , Ji Ping , Wu Xuangou
Published: December 2023

WiFi-based human gesture recognition has a wide range of applications in smart homes. Existing methods train gesture classification models by collecting large amounts of WiFi signal data in a centralized manner. However, centralized training faces challenges, including high communication overhead and the risk of data privacy leakage. Federated learning (FL) provides an opportunity to collaboratively train and share models without compromising data privacy. One of the main challenges FL faces is data that is non-Independent and Identically Distributed (non-IID) across clients. Specifically, in the gesture recognition scenario, since the transmission of WiFi signals is susceptible to cross-environment and cross-person interference, non-IID mainly manifests itself as a cross-domain problem. Cross-domain makes the knowledge learned between client models incompatible. Therefore, in the cross-domain scenario, effectively extracting and combining the knowledge learned by the client is a challenge. To solve this problem, we propose pFedBKD, a novel personalized federated learning scheme via bidirectional distillation. First, the knowledge that is beneficial to the client is extracted from the shared server model through knowledge distillation in the client, which helps train the personalized model of the client. Second, the server adaptively adjusts the aggregation weights according to the deviation between the shared model and the client’s local model so that the server’s shared model can extract more public knowledge. We conduct experiments on multiple open-source datasets. Experimental results show that our method is superior to existing methods and effectively alleviates the problem of reduced model recognition accuracy caused by cross-domain challenges.
Active Disturbance Rejection Control of Full-Bridge DC–DC Converter for a Pulse Power Supply with Controllable Charging Time
Authors: Kang Zhongjian , Li Yuntong
Published: December 2023

In this paper, a control method of a full-bridge DC–DC converter for a pulse power supply with controllable charging time based on Active Disturbance Rejection Control (ADRC) is presented. For this application, the scheme objective is to achieve a flexible charging current to adjust the charging time of the pulse power supply. Due to the existence of switching devices in the system, the dynamic characteristics of the control system are complicated; an LADRC (Linear Active Disturbance Rejection Control) controller is constructed to regulate the charging of the converter current so as to improve the flexibility and dynamic performance of high-voltage pulse power supply. LADRC linearizes the extended state observer and links its parameters to the observer bandwidth to simplify the design of ESO. The proportional coefficient or differential coefficient is connected with the bandwidth of the controller to simplify its tuning, simplify the nonlinear function, more parameters, and complicated adjustment of the ADRC in practical application. The inner loop current regulator assembled is beneficial to the dynamic performance of the loop. The resulting double closed-loop structure improves steady-state and transient current-tracking performance. In addition, stability analysis of the proposed strategy is also performed. The proposed control approach is compared with PI. To verify the feasibility of the proposed scheme, an experimental prototype was constructed and tested to confirm the superiority of the proposed method in terms of dynamic performance.
Next-Generation IoT: Harnessing AI for Enhanced Localization and Energy Harvesting in Backscatter Communications
Authors: Nesbitt Rory , Shah Syed Tariq , Wagih Mahmoud , Imran Muhammad A. , Abbasi Qammer H. , Ansari Shuja
Published: December 2023

Ongoing backscatter communications and localisation research have been able to obtain incredibly accurate results in controlled environments. The main issue with these systems is faced in complex RF environments. This paper investigates concurrent localization and ambient radio frequency (RF) energy harvesting using backscatter communication systems for Internet of Things networks. Dynamic real-world environments introduce complexity from multipath reflection and shadowing, as well as interference from movements. A machine learning framework leveraging K-Nearest Neighbors and Random Forest classifiers creates robustness against such variability. Historically, received signal measurements construct a location fingerprint database resilient to perturbations. The Random Forest model demonstrates precise localization across customized benches with programmable shuffling of chairs outfitted with RF identification tags. Average precision accuracy exceeds 99% despite deliberate placement modifications, inducing signal fluctuations emulating mobility and clutter. Significantly, directional antennas can harvest over −3 dBm, while even omnidirectional antennas provide −10 dBm—both suitable for perpetually replenishing low-energy electronics. Consequently, the intelligent backscatter platform localizes unmodified objects to customizable precision while promoting self-sustainability.
A Personalized Motion Planning Method with Driver Characteristics in Longitudinal and Lateral Directions
Authors: Zeng Di , Zheng Ling , Li Yinong , Zeng Jie , Wang Kan
Published: December 2023

Humanlike driving is significant in improving the safety and comfort of automated vehicles. This paper proposes a personalized motion planning method with driver characteristics in longitudinal and lateral directions for highway automated driving. The motion planning is decoupled into path optimization and speed optimization under the framework of the Baidu Apollo EM motion planner. For modeling driver behavior in the longitudinal direction, a car-following model is developed and integrated into the speed optimizer based on a weight ratio hypothesis model of the objective functional, whose parameters are obtained by Bayesian optimization and leave-one-out cross validation using the driving data. For modeling driver behavior in the lateral direction, a Bayesian network (BN), which maps the physical states of the ego vehicle and surrounding vehicles and the lateral intentions of the surrounding vehicles to the driver’s lateral intentions, is built in an efficient and lightweight way using driving data. Further, a personalized reference trajectory decider is developed based on the BN, considering traffic regulations, the driver’s preference, and the costs of the trajectories. According to the actual traffic scenarios in the driving data, a simulation is constructed, and the results validate the human likeness of the proposed motion planning method.
Design Optimization of an Automotive Permanent-Magnet Synchronous Motor by Combining DOE and NMGWO
Authors: Cui Junguo , Cui Fanqiang , Zhang Jun , Huang Hongsheng , Tan Liping , Xiao Wensheng
Published: December 2023

This study proposes an optimization methodology for automotive permanent-magnet synchronous motors (PMSMs) to achieve maximum efficiency, maximum average torque, and minimum torque ripple. Many geometrical parameters can be used to define the PMSM of an automobile. To identify the most significant parameters for optimization, the fractional factorial design of the design of experiment (DOE) was employed for screening, considering the interaction effects. The central composite design was used to construct the proxy model between the optimization target and optimization variable, and the effectiveness of the model was judged. Aiming at the multi-objective optimization problem of a motor, a new mechanism for grey wolf optimizer (NMGWO) algorithm combining an elite reverse learning strategy, a local search strategy, and a nonlinear control parameter strategy is innovatively proposed. This algorithm was applied to solve the multi-objective optimization model. The numerical calculation results show that this is an effective optimization design method that can improve the performance of automotive PMSMs. The effectiveness of the NMGWO algorithm on the optimization results of permanent-magnet synchronous motors is verified by the experimental results.
Upward Shift of Wind Turbine Wakes in Large Wind Farms
Authors: Wang Zewei , Yang Xiaolei
Published: December 2023

A detailed description of wake characteristics is essential for optimizing wind farm performance. Compared with the wake of a stand-alone wind turbine, less attention has been paid to wind turbine wakes in large wind farms. In this work, we investigate the vertical position of wakes for wind turbines in large wind farms with different streamwise turbine spacings and ground roughness lengths using large-eddy simulation with an actuator disk model. The simulation results reveal an upward shift of the wake center (defined as the position with the maximum velocity deficit) for the wind turbine deeply arrayed in the wind farm. Larger upward shifts of the wake center are observed for wind turbines in further downstream rows and wind turbines installed on the ground with higher roughness, for which the wake expands at a higher rate. It is conjectured that the upward shift of the wake center is caused by the upward shift of the turbulence-dominated momentum entrainment region and the constraint of ground on wake expansion. An analytical wake model incorporating the upward-shifting wake center was developed. In the proposed model, different expansion rates are employed for the lower and upper wake regions. The upward shift of the wake center is directly taken into account using the large-eddy simulation results. The comparison with the large-eddy simulation results demonstrates the importance of accounting for the upward shift of the wake center in analytical wake models.
Renewable Energy Transition Task Solution for the Oil Countries Using Scenario-Driven Fuzzy Multiple-Criteria Decision-Making Models: The Case of Azerbaijan
Authors: Nuriyev Mahammad , Nuriyev Aziz , Mammadov Jeyhun
Published: December 2023

The renewable energy transition of oil- and gas-producing countries has specific peculiarities due to the ambivalent position of these countries in the global energy market, both as producers and consumers of energy resources. This task becomes even more challenging when the share of oil and gas in the country’s GDP is very high. These circumstances pose serious challenges for long-term energy policy development and require compromising decisions to better align the existing and newly created energy policies of the country. The scale, scope, and pace of changes in the transition process must be well balanced, considering the increasing pressure of economic and environmental factors. The objective of this paper is to develop models that allow the selection of the most appropriate scenario for renewable energy transition in an oil- and gas-producing country. The distinguishing feature of the proposed model is that alternatives in the decision matrix are presented as scenarios, composed of a set of energy resources and the level of their use. Linguistic descriptions of the alternative scenarios are formalized in the form of fuzzy statements. For the problem solution, four different Multiple-Criteria Decision-Making (MCDM) methods were used: the fuzzy simple additive weighting (F-SAW) method, the distance-based fuzzy TOPSIS method (Technique of Order Preference Similarity to the Ideal Solution), the ratio-analysis-based fuzzy MOORA method (Multi-Objective Optimization Model Based on the Ratio Analysis), and the fuzzy multi-criteria optimization and compromise solution method VIKOR (Serbian: VIekriterijumsko Kompromisno Rangiranje). This approach is illustrated using the example of the energy sector of Azerbaijan. The recommended solution for the country involves increasing natural gas (NG) moderately, maintaining hydro, and increasing solar notably and wind moderately.
Detailed Controller Synthesis and Laboratory Verification of a Matching-Controlled Grid-Forming Inverter for Microgrid Applications
Authors: Gomez Anccas Edgar Diego , Pourhossein Kazem , Becker Daniel , Schulz Detlef
Published: December 2023

Grid-forming inverters are the essential components in the effort to integrate renewable energy resources into stand-alone power systems and microgrids. Performance of these inverters directly depends on their control parameters embodied in the controller. Even the most conscientiously designed controller will exhibit suboptimal performance upon implementation due to the presence of parasitic elements in the existing hardware. Hence, the controller has to be tuned and optimized. In the present article, the process of implementation, laboratory verification, and tuning of a matching-controlled grid-forming inverter is presented. In order to assess the efficiency of the grid-forming controller, its operation has been tested and analyzed in blackstart, steady state, and transient operation. For this purpose, a systematic sensitivity analysis has been conducted and the control parameters have been tuned in laboratory tests. The laboratory results verify proper operation of a 7 kW grid-forming inverter in all three test scenarios. After applying the proposed method on the tested grid-forming inverter in steady state operation, total harmonic distortion (THD) of the output voltage is less than 0.5% for its practical loading range (maximum THD is less than 1% in no-load condition). The system is able to blackstart and supply the loads. Finally, the studied grid-forming inverter is stable in the presence of severe step load changes and disturbances, i.e., voltage overshoot is managed well and compensated for with a low settling time using this approach.
The Creation of the Hydrogen Supply Chain Decision Database
Authors: Li Lei , Msaadi Souhayl , Manier Hervé , Manier Marie-Ange
Published: December 2023

In the evolving landscape of sustainable energy, efficient management of the hydrogen supply chain is paramount. This study addressed the critical need for decision-making support in this sector, highlighting the development and potential impact of a comprehensive hydrogen supply chain decision database. Utilizing a combination of qualitative and quantitative research methods, the study involved the collection and analysis of data across various stages of the hydrogen supply chain. Emphasis was placed on identifying key decision-making factors, integrating diverse data sources, and employing advanced analytical techniques to enhance the database’s utility. The findings revealed significant insights into the hydrogen supply chain, including bottlenecks, efficiency parameters, and potential areas for optimization. The developed database demonstrated its capability to aid in strategic decision making, offering a tool for stakeholders to navigate the complexities of hydrogen supply and distribution. The creation of the hydrogen supply chain decision database marks a step forward in the field, providing a valuable resource for researchers, policymakers, and industry professionals. It underscores the necessity of data-driven approaches in optimizing the hydrogen supply chain, potentially contributing to the acceleration of sustainable energy initiatives.
Concentrating Solar Power: The State of the Art, Research Gaps and Future Perspectives
Authors: Ferruzzi Gabriella , Delcea Camelia , Barberi Antonino , Di Dio Vincenzo , Di Somma Marialaura , Catrini Pietro , Guarino Stefania , Rossi Federico , Parisi Maria Laura , Sinicropi Adalgisa , Longo Sonia
Published: December 2023

In recent decades, the fight against climate change and the commitment to reduce greenhouse gases have shed a light on the production of energy from renewable sources, in particular those derived from solar energy. This has required the involvement of all stakeholders (producers, but also energy operators, authorities, distributors, and final consumers) which has led to the outline of a new scenario characterized by more efficient technologies, dedicated strategies and business models, and the research of alternatives solutions. Within solar technology, great attention has been given in recent years to concentrating solar power (CSP) technologies, both from research studies and technological development sides. This paper provides a theoretical framework based on a CSP literature review to define the state of the art and to identify research gaps and future research steps related to this technology. The work is based on an innovative bibliometric study to explore technical fields related to CSP, providing both a comprehensive framework with reference to the state of the art of the technology investigated, and a detailed analysis on CSP commercial applications, making the review a very useful tool for stakeholders and decision makers The results of the analysis: (1) help to clarify the technological advances of CSP, the strengths and weaknesses of the current technologies used (parabolic and tower systems are the most widespread), and indications of the prospects for dish systems; (2) identify an alternative to the economic problem that represents an obstacle to the diffusion of CSP, for example, by identifying the ability to couple it with thermal storage as a valid method to increase the flexibility of the system and reduce costs; (3) suggested hybrids, both with renewable and non-renewable technologies, identifying strengths and weaknesses for all the proposed proposals; (4) show that it is possible to identify new ongoing research such as that related to hydrogen production. This paper represents the first part of a larger research study developed within the SOLARGRID Project, which promotes and supports the development of innovative solutions for systems and components for CSP and concentrated photovoltaics (CPV) technologies, with the aim to enhance their energetic performances and economic competitiveness in applications for the distributed generation of both electric and thermal energy frameworks. The main findings of our study highlight that, though there is an increasing number of papers on the topic of CSP, several issues remain neglected.