bluuebunny/crossref_metadata_2025 huggingface dataset:
Managing the Risk of Lung Toxicity with Trastuzumab Deruxtecan (T-DXd): A Canadian Perspective
Authors: Henning Jan-Willem , Brezden-Masley Christine , Gelmon Karen , Chia Stephen , Shapera Shane , McInnis Micheal , Rayson Daniel , Asselah Jamil
Published: August 2023

Ongoing advances in precision cancer therapy have increased the number of molecularly targeted and immuno-oncology agents for a variety of cancers, many of which have been associated with a risk of pulmonary complications, among the most concerning being drug-induced interstitial lung disease/pneumonitis (DI-ILD). As the number of patients undergoing treatment with novel anticancer agents continues to grow, DI-ILD is expected to become an increasingly significant clinical challenge. Trastuzumab deruxtecan (T-DXd) is an antibody–drug conjugate targeting human epidermal growth factor receptor 2 that is gaining widespread use in the metastatic breast cancer setting and is undergoing exploration for other oncologic indications. ILD/pneumonitis is an adverse event of special interest associated with T-DXd, which has potentially fatal consequences if left untreated and allowed to progress. When identified in the asymptomatic stage (grade 1), T-DXd-related ILD can be monitored and treated effectively with the possibility of treatment continuation. Delayed diagnosis and/or treatment, however, results in progression to grade 2 or higher toxicity and necessitates immediate and permanent discontinuation of this active agent. Strategies are, therefore, needed to optimize careful monitoring during treatment to ensure patient safety and optimize outcomes. Several guidance documents have been developed regarding strategies for the early identification and management of T-DXd-related ILD, although none have been within the context of the Canadian health care environment. A Canadian multidisciplinary steering committee was, therefore, convened to evaluate existing recommendations and adapt them for application in Canada. A multidisciplinary approach involving collaboration among medical oncologists, radiologists, respirologists, and allied health care professionals is needed to ensure the proactive identification and management of T-DXd-related ILD and DI-ILD associated with other agents with a similar toxicity profile.
Is It Time to Anticipate the Use of PARP Inhibition in Prostate Cancer Patients?
Authors: Sciarra Alessandro , Santarelli Valerio , Santodirocco Lorenzo , Frisenda Marco , Salciccia Stefano , Casale Paolo , Forte Flavio , Mariotti Gianna , Moriconi Martina , Cattarino Susanna , Sciarra Beatrice , Bevilacqua Giulio , Gentilucci Alessandro
Published: August 2023

The increasing diffusion of genetic analysis regarding the pathogenetic variants (PVs) of genes involved in DNA Damage Repair (DDR) mechanisms and the development of Poly ADP ribose polymerase (PARP) inhibitors (PARPis) led to the first valid precision medicine option tailored toward metastatic prostate cancer (mPC). The concept of anticipation in the systemic treatment of mPC was initially adopted for androgen receptor signaling inhibitors (ARSIs) to describe the expansion of their indications, from the setting of the late-stage second-line treatment of metastatic castration-resistant prostate cancer (mCRPC) to first-line therapy in selected cases. There is already mounting evidence in favor of the anticipation of PARPis in the first line of mCRPC therapy, and further evidence in favor of mHSPC is emerging. Many studies have demonstrated the synergism between ARSIs and PARP inhibitors. Recent discoveries regarding the crosstalk between the androgen receptor (AR) and DNA repair mechanisms are disconnecting the use of PARPis from genetic analysis. The new message emerging is that the combination of PARPis with ARSIs may work independently of DDR mutational status. As a matter of fact, most of the recent trials analyzing the combination of PARPis with abiraterone or enzalutamide as a first-line therapy enrolled mCRPC patients irrespective of their mutational status. The PROPEL trial concluded that the advantage of the combination was independent of PV status, despite a higher advantage being reported in the BRCA1/2 mutated subgroup. The MAGNITUDE trial, however, showed a significant advantage only in the DDR mutated subgroup, and the DDR non-mutated cohort was closed for further enrollment. The combination of PARPis with ARSIs represents a significant strategy with a view to the anticipation and intensification of care in mPC. However, it should not nullify the advantages of precision medicine linked to the genetic analysis of DDR genes.
Seeding African Forest and Landscape Restoration: Evaluating Native Tree Seed Systems in Four African Countries
Authors: Giacomini Fiona L. , Prempeh John A. , Jalonen Riina , Vinceti Barbara , Ekue Marius , Bosshard Ennia , Burslem David F. R. P. , Kettle Chris J.
Published: August 2023

Commitments to Forest and Landscape Restoration are rapidly growing and being implemented globally to tackle the climate and biodiversity crises. Restoration initiatives largely based on tree planting necessitate an increased supply of high-quality and suitably adapted tree planting material. We evaluated the native tree seed supply systems in Burkina Faso, Cameroon, Ghana, and Kenya, four countries with large commitments to increase tree cover. We applied an established indicator framework to assess the adequacy of any current tree seed system to meet national needs. The study aimed to analyse (i) how well-established the native tree seed supply systems are, (ii) how public and non-public actors differ regarding the perception of existing seed systems, and (iii) the main barriers to strengthening current seed systems. Our findings identified significant gaps in the native tree seed supply systems of the four countries, arising particularly from shortfalls in the enabling environment. We found a lack of involvement of local community members in the seed systems, with a crucial need for strengthening policy, capacity building and investment in seed systems. We propose a multi-stakeholder approach and the application of online tools to improve seed systems to meet the demand for high-quality native tree seeds.
The Geographical Differences in the Bird Prey of the Great Evening Bat (Ia io)
Authors: Liu Yu , Wu Hui , Gong Lixin , Liu Yingying , Jiang Tinglei , Feng Jiang
Published: August 2023

Geographic variation in diet can indicate if species have unique ecological roles or feeding strategies in different environments. Bats have a unique nocturnal ecological niche and a diverse diet, making them an ideal model for studying changes in feeding. Some bats have adapted to reduced food resources caused by environmental changes and human disturbances by expanding their dietary ecological niche. As one of the typical species whose dietary niche has expanded from invertebrates (insects) to vertebrates (birds), the feeding habits of the great evening bat (Ia io) have attracted much attention from researchers. Unfortunately, little is known about how the diet of Ia io varies in different regions. Therefore, in this study, the diversity and composition of the bird prey of the great evening bat from two populations were examined using cytochrome C oxidase subunit I (COI) amplicon sequencing. The results showed that the great evening bat in both populations preyed on a variety of passerine birds, with the Phylloscopidae being the dominant family. Although most birds preyed upon by these two populations are the same, there are significant differences in predation on Cettiidae between the two populations. Both populations prey on migratory birds more than resident birds. Both populations of bats can prey on finch birds weighing more than 15 g, but they preyed on more birds weighing less than 10 g. The results of this study provide an important addition to the study of changes in bat diets under the conditions of expanding dietary ecological niches.
Cutaneous Syncytial Myoepithelioma with Positive CD34 Immunohistochemical Staining: An Unusual Tumor and a Challenging Diagnosis
Authors: Ariasi Cesare , Romanò Carola , Ghini Iacopo , Licata Gaetano , Rubelli Luca , Artelli Grazia Linda , Calzavara-Pinton Piergiacomo , Arisi Mariachiara
Published: August 2023

Cutaneous syncytial myoepithelioma (CSM) is a rare type of cutaneous neoplasm that typically presents as a solitary and well-circumscribed nodule on the skin. It predominantly occurs on the upper and lower extremities of adult patients. Immunohistochemically, CSM is characterized by the co-expression of smooth muscle and epithelial markers. Fluorescence in situ hybridization (FISH) targeting the EWSR1 gene rearrangement is an important diagnostic tool for CSM. In our case report, we found the focal positivity for CD34, which has never been previously observed; this was mostly confined to a central area of the neoplasm.
Experience of “One Stop TB Diagnostic Solution” Model in Engaging a Private Laboratory for End-to-End Diagnostic Services in the National TB Elimination Program in Hisar, India
Authors: Raju Rajesh , Prasad Banuru Muralidhara , Alavadi Umesh , Saini Sanjeev , Sabharwal Mukesh , Duhan Akshay , Anand Sridhar , Lal Manohar , Kaur Harpreet , Arora Neerja , Jaju Jyoti , Moore Moe , Ramachandran Ranjani , Kumar Nishant , Joshi Rajendra P.
Published: August 2023

The complete diagnostic evaluation of tuberculosis based on its drug-resistance profile is critical for appropriate treatment decisions. The TB diagnostic landscape in India has been transformed with the scaling-up of WHO-recommended diagnostics, but challenges remain with specimen transportation, completing diagnostic assessment, turnaround time (TAT), and maintaining laboratories. Private laboratories have demonstrated efficiencies for specimen collection, transportation, and the timely testing and issue of results. A one-stop TB diagnostic model was designed to assess the feasibility of providing end-to-end diagnostic services in the Hisar district of Haryana state, India. A NTEP-certified private laboratory was engaged to provide the services, complementing the existing public sector diagnostic services. A total of 10,164 specimens were collected between May 2022 and January 2023 and these were followed for the complete diagnostic assessment of Drug-Susceptible TB (DS-TB) and Drug-Resistant TB (DR-TB) and the time taken for issuing results. A total of 2152 (21%) patients were detected with TB, 1996 (93%) Rifampicin-Sensitive and 134 (6%) with Rifampicin-Resistant TB. Nearly 99% of the patients completed the evaluation of DS-TB and DR-TB within the recommended TAT. The One-Stop TB/DR-TB Diagnostic Solution model has demonstrated that diagnostic efficiencies could be enhanced through the strategic purchase of private laboratory services.
The Difficulty Detecting Tuberculosis in a Child with Post-COVID-19 and Cerebral Palsy
Authors: Stojkovic Andjelka , Ilic Irena , Kostic Andrijana , Dajic Katerina , Raskovic Zorica , Nestorovic Jelena , Ilic Milena
Published: August 2023

When hypostatic pneumonia is present at the same time as COVID-19 pneumonia, the clinical course is almost always prolonged (prolonged-COVID-19) due to persistent inflammation, long-term anti-inflammatory syndrome, followed by immune exhaustion, i.e., by immunosuppression and catabolic syndrome. In the immunosuppression phase, viral reactivation can be accompanied by a secondary infection, which, in this case, is pulmonary tuberculosis. Pulmonary tuberculosis in post-COVID-19 patients and in patients with spastic quadriplegic cerebral palsy does not have a typical clinical course nor laboratory, radiological, immunological, microbiological, or fiberbronchoscopic pathohistological confirmation. Due to this, the treatment of pulmonary tuberculosis was not carried out on time, postponed after the unsuccessful treatment of sepsis, post-COVID-19, and other accompanying viral (adenovirus, RSV) and bacterial (streptococcus viridans) infections. The treatment of pulmonary tuberculosis was possible only “ex juvantibus” (trial) post-COVID-19. It becomes imperative to search for a new, more precise and reliable diagnostic test for the detection of tuberculosis bacillus.
Assessing the Use of Telepresence-Guided Video-Based Head and Neck Ultrasound Training: A Step towards Minimizing Dependence on Human Resources?
Authors: Kulas Philipp , Schick Bernhard , Helfrich Johanna , Bozzato Alessandro , Hecker Dietmar J. , Pillong Lukas
Published: August 2023

The acquisition of ultrasound skills is an essential part of any medical student’s education. University access restrictions in the context of the COVID-19 pandemic have highlighted the need for digitization in teaching. However, teaching manual skills in online courses has proven to be challenging, not least in terms of human resources. Therefore, the aim of this study was to set up a hybrid head and neck ultrasound course consisting of a preface of video-based self-study followed by supportive instruction by a tutor in telepresence and to evaluate the quality, effectiveness, and feasibility of this teaching method. Thirty-five students were shown video tutorials on systematic ultrasound of the neck course. Learning outcomes were analyzed using self-assessment questionnaires and external assessment by an experienced ultrasonographer. All participants demonstrated statistically significant learning improvement (p < 0.001) when comparing self-assessment scores before and after training. The mean self-assessment scores increased from 13.8 to 26.6 for the telepresence-guided group, from 16.6 to 27.3 for the web-based group, and from 14.0 to 26.2 for the in-person group. The external observer assessment also showed improvement, with mean scores of 46.7, 48.1, and 46.5, respectively. Overall results did not significantly differ when comparing different instruction modalities. A telepresence-guided video-based ultrasound course is well suited to teaching ultrasound skills similar to in-person courses and allows a more resource-efficient targeting of student needs.
Comparison of the Accuracy of a Mounting Fixture for Dental Implants for Implant Position Transfer and Open-Tray Implant Level Impression—An In Vitro Study
Authors: Becker Alexander , Dirksen Dieter , Runte Christoph
Published: August 2023

The accuracy for the implant position transfer of a mounting fixture and a standardized open-tray implant level impression was compared. Ten aluminum master models with four implant analogs placed in different angulations were fabricated. By performing an open-tray implant level impression stone casts were produced. The master models and stone casts were scanned (comparison group one) using a laboratory scanner. Deviations in the scan body surface were determined in the form of mean (absolute) point distances and (signed) surface distances. The same procedure was performed with a screwed transfer and by fixing the posts of the mounting fixture (comparison group two). The mounting device was applied to each master model and scanned in a fixed and detached state (comparison group three). In a point comparison, the open-tray implant level impression showed mean deviations of 43.6 µm and a mounting fixture of 44.6 µm with no significant differences (p < 0.05). There were significant differences between groups two and three. The angulation of the implants had no effect on the accuracy. In a surface comparison, the open-tray implant level impression showed mean deviations of 36.0 µm and a mounting fixture of 2.0 µm (p > 0.05). Within the limits of this study, the mounting fixture transferred the implant position with the same accuracy as the open-tray implant level impression with respect to point deviations.
Origins of Genetic Coding: Self-Guided Molecular Self-Organisation
Authors: Wills Peter R.
Published: August 2023

The origin of genetic coding is characterised as an event of cosmic significance in which quantum mechanical causation was transcended by constructive computation. Computational causation entered the physico-chemical processes of the pre-biotic world by the incidental satisfaction of a condition of reflexivity between polymer sequence information and system elements able to facilitate their own production through translation of that information. This event, which has previously been modelled in the dynamics of Gene–Replication–Translation systems, is properly described as a process of self-guided self-organisation. The spontaneous emergence of a primordial genetic code between two-letter alphabets of nucleotide triplets and amino acids is easily possible, starting with random peptide synthesis that is RNA-sequence-dependent. The evident self-organising mechanism is the simultaneous quasi-species bifurcation of the populations of information-carrying genes and enzymes with aminoacyl-tRNA synthetase-like activities. This mechanism allowed the code to evolve very rapidly to the ~20 amino acid limit apparent for the reflexive differentiation of amino acid properties using protein catalysts. The self-organisation of semantics in this domain of physical chemistry conferred on emergent molecular biology exquisite computational control over the nanoscopic events needed for its self-construction.
Student’s Choice: In-Person, Online, or on Demand? A Comparison of Instructional Modality Preference and Effectiveness
Authors: Larson Melissa , Davies Randall , Steadman Anna , Cheng Wai Man
Published: August 2023

The recent increase in online instruction caused by the 2020 pandemic has reignited the debate over the efficacy of online instruction compared to in-person instruction. This study explored the impact various modes of instruction had on student achievement and compared students’ stated modality preference with their actual attendance behavior. Results show that while most students preferred in-person instruction (74%), only 47% of those who indicated they preferred in-person instruction attended class only in-person. Many attended classes utilizing a modality other than in-person, and several students switched their preferred modality away from in-person instruction. In general, students who attended class using a mixed modality or in-person achieved slightly better results than those attending class live online. However, the only statistically significant difference was between those participating predominantly in person and those watching class recordings (88% compared to 84% on average). Overall, many students achieved high grades regardless of their chosen instructional modality. In addition, students reported appreciating the option of multiple modalities when they could not attend class in their preferred modality. These results suggest offering a choice of modalities benefited many students.
A Signal-Denoising Method for Electromagnetic Leakage from USB Keyboards
Authors: Peng Yihua , Zhang Jiemin , Mao Jian , Cui Mengmeng
Published: August 2023

USB keyboards are commonly used as computer input devices and inevitably generate electromagnetic (EM) leakage signals during their operation, which carry input information. However, due to the weak energy of a keyboard’s EM signal and the small amount of effective information, the received leakage signal is often characterized by a low signal-to-noise ratio (SNR). This low SNR affects the subsequent detection and restoration of the information. In order to solve this problem, this paper proposes a denoising method for USB keyboard EM leakage signals and designs a self-attentive denoising adversarial network (SADAN) based on generative adversarial networks (GANs). The denoiser continuously enhances the denoising ability during the generative adversarial process, and the self-attention mechanism enables it to better learn the dependencies of the keyboard EM leak signal sequences, modelling the long-range relationships between the sequence sample points and reducing the impact of the number of network layers on the relationship acquisition. The method achieves noise suppression in the keyboard leakage signal, improving its SNR while preserving the effective information in the leakage signal and finally obtaining a denoised leakage signal that can be effectively restored to the information.
RSLC-Deeplab: A Ground Object Classification Method for High-Resolution Remote Sensing Images
Authors: Yu Zhimin , Wan Fang , Lei Guangbo , Xiong Ying , Xu Li , Ye Zhiwei , Liu Wei , Zhou Wen , Xu Chengzhi
Published: August 2023

With the continuous advancement of remote sensing technology, the semantic segmentation of different ground objects in remote sensing images has become an active research topic. For complex and diverse remote sensing imagery, deep learning methods have the ability to automatically discern features from image data and capture intricate spatial dependencies, thus outperforming traditional image segmentation methods. To address the problems of low segmentation accuracy in remote sensing image semantic segmentation, this paper proposes a new remote sensing image semantic segmentation network, RSLC-Deeplab, based on DeeplabV3+. Firstly, ResNet-50 is used as the backbone feature extraction network, which can extract deep semantic information more effectively and improve the segmentation accuracy. Secondly, the coordinate attention (CA) mechanism is introduced into the model to improve the feature representation generated by the network by embedding position information into the channel attention mechanism, effectively capturing the relationship between position information and channels. Finally, a multi-level feature fusion (MFF) module based on asymmetric convolution is proposed, which captures and refines low-level spatial features using asymmetric convolution and then fuses them with high-level abstract features to mitigate the influence of background noise and restore the lost detailed information in deep features. The experimental results on the WHDLD dataset show that the mean intersection over union (mIoU) of RSLC-Deeplab reached 72.63%, the pixel accuracy (PA) reached 83.49%, and the mean pixel accuracy (mPA) reached 83.72%. Compared to the original DeeplabV3+, the proposed method achieved a 4.13% improvement in mIoU and outperformed the PSP-NET, U-NET, MACU-NET, and DeeplabV3+ networks.
An FPGA Design with High Memory Efficiency and Decoding Performance for 5G LDPC Decoder
Authors: Tran-Thi Bich Ngoc , Nguyen-Ly Thien Truong , Hoang Trang
Published: August 2023

A hardware-efficient implementation of a Low-Density Parity-Check (LDPC) decoder is presented in this paper. The proposed decoder design is based on the Hybrid Offset Min-Sum (HOMS) algorithm. In the check node processing of this decoder, only the first minimum is computed instead of the first two minimum values among all the variable-to-check message inputs as in the conventional approach. Additionally, taking advantage of the unique structure of 5G LDPC codes, layered scheduling and partially parallel structures are employed to minimize hardware costs. Implementation results on the Xilinx Kintex UltraScale+ FPGA platform show that the proposed decoder can achieve a throughput of 2.82 Gbps for 10 decoding iterations with a 5G LDPC codelength of 8832 bits and a code rate of 1/2. Moreover, it yields a check node memory reduction of 10% with respect to the baseline and provides a hardware usage efficiency of 4.96 hardware resources/layer/Mbps, while providing a decoding performance of 0.15 dB better than some of the existing decoders.
The Application of ResNet-34 Model Integrating Transfer Learning in the Recognition and Classification of Overseas Chinese Frescoes
Authors: Gao Le , Zhang Xin , Yang Tian , Wang Baocang , Li Juntao
Published: August 2023

The unique characteristics of frescoes on overseas Chinese buildings can attest to the integration and historical background of Chinese and Western cultures. Reasonable analysis and preservation of overseas Chinese frescoes can provide sustainable development for culture and history. This research adopts image analysis technology based on artificial intelligence and proposes a ResNet-34 model and method integrating transfer learning. This deep learning model can identify and classify the source of the frescoes of the emigrants, and effectively deal with problems such as the small number of fresco images on the emigrants’ buildings, poor quality, difficulty in feature extraction, and similar pattern text and style. The experimental results show that the training process of the model proposed in this article is stable. On the constructed Jiangmen and Haikou fresco JHD datasets, the final accuracy is 98.41%, and the recall rate is 98.53%. The above evaluation indicators are superior to classic models such as AlexNet, GoogLeNet, and VGGNet. It can be seen that the model in this article has strong generalization ability and is not prone to overfitting. It can effectively identify and classify the cultural connotations and regions of frescoes.
Wind Power Group Prediction Model Based on Multi-Task Learning
Authors: Wang Da , Yang Mao , Zhang Wei
Published: August 2023

Large-scale wind power grid connection increases the uncertainty of the power system, which reduces the economy and security of power system operations. Wind power prediction technology provides the wind power sequence for a period of time in the future, which provides key technical support for the reasonable development of the power generation plan and the arrangement of spare capacity. For large-scale wind farm groups, we propose a cluster model of wind power prediction based on multi-task learning, which can directly output the power prediction results of multiple wind farms. Firstly, the spatial and temporal feature matrix is constructed based on the meteorological forecast data provided by eight wind farms, and the dimensionality of each attribute is reduced by the principal component analysis algorithm to form the spatial fusion feature set. Then, a network structure with bidirectional gated cycle units is constructed, and a multi-output network structure is designed based on the Multi-gate Mixture-of-Experts (MMoE) framework to design the wind power group prediction model. Finally, the data provided by eight wind farms in Jilin, China, was used for experimental analysis, and the predicted average normalized root mean square error is 0.1754, meaning the prediction precision meets the scheduling requirement, which verifies the validity of the wind power prediction model.
Harmonic Resonance Analysis and Impedance Remodeling Method of Multi-Inverter Grid-Connected System
Authors: Zhang Min , Wang Jinhao , Zhang Shifeng , Gao Le , Guo Xiangyu , Chen Lin , Xu Yonghai
Published: August 2023

The harmonic and resonant characteristics of a multi-inverter grid-connected system can negatively affect power quality when weak grid conditions are present. In this paper, firstly, harmonic currents are modeled for the inverter, the correctness of low-frequency harmonics and high-frequency harmonics are verified in closed loop, and the characteristics of harmonic currents are analyzed when the parameters are varied. Secondly, the resonant characteristics of the inverter with feed-forward link are analyzed, and a multi-inverter grid-connected equivalent model based on the triple-decomposition conductance is developed and analyzed in conjunction with the resonant modal analysis method. Then, a harmonic resonance impedance reshaping method is proposed to suppress the background harmonics using improved weighted average current control (WACC), suppress the system resonance based on the point of common coupling (PCC) paralleling virtual conductance method, and improve the stability margin of the system combined with impedance reshaping resonance suppression method. Finally, simulations and comparison of results with different suppression methods verify the superiority and effectiveness of the proposed method.
Contactless Multi-User Virtual Hair Design Synthesis
Authors: Sung Changjo , Chin Seongah
Published: August 2023

This study introduces a virtual reality (VR)-based remote hair design training system that addresses the limitations of physical presence. By leveraging virtual environments and eliminating the need for tangible tools, this system allows hairstylists and learners to collaborate and master hair-design techniques from a distance. In this approach, a section of a user’s hair was derived from their photograph, and during the training, the most compatible 3D hair model was integrated with the user’s 3D avatar using the recommended matching procedure. This aligned hairstyle was subsequently incorporated into a 3D model for hair simulation. Further, VR HMD interaction mapping was used for hair cutting and styling. A collaborative environment for hair design has been crafted, enabling multiple participants to partake in remote hairstyle education. This system offers cost-effective training, enhances cooperative learning, and aligns with the requirements of contact-free education. In essence, this research has transformed remote hair design training with immersive VR technology. To verify the system’s accuracy, tests were conducted, and the results showcased enhancements in the matching procedure.
Dynamic Overlapping Coalition Formation in Electricity Markets: An Extended Formal Model
Authors: Wolff Torge , Nieße Astrid
Published: August 2023

The future power system will be characterized by many small decentralized power plants—so-called distributed energy resources (DERs). The integration of these DERs is vital from an economic and grid operation point of view. One approach to this is the aggregation of such DERs. The formation of coalitions as an aggregation method has already been examined in the literature and applied in virtual power plants, active distribution networks, and microgrids. The spread of DERs also increases the need for flexibility and dynamics in the power grid. One approach to address this can be overlapping coalitions. Therefore, in this paper, we first performed an analysis of related work and, in this context, found no work on overlapping coalitions for energy use cases in the literature. We then described a method for dynamic coalition formation, called dynamic coalition in electricity markets (DYCE), and analyzed how DYCE would need to be extended to include overlapping coalition formation. The extension includes the phases of product portfolio optimization and the actual coalition formation. Our analysis of DYCE shows that the methods used for the optimization of the DYCE sub-tasks are not suitable for overlapping coalitions and would have to be replaced by other methods in order to be able to form overlapping coalitions.
A Review on AC Voltage Variation Compensators in Low Voltage Distribution Network
Authors: Sztajmec Elżbieta , Szcześniak Paweł
Published: August 2023

Power quality is one of the most important aspects of the power system, especially in the distribution system. This system can be affected by such disturbances as short-term voltage sags/swells, long-term voltage increases/decreases over the normative limits, harmonic distortion, interruptions, etc. Maintaining the electricity quality parameters in accordance with the applicable standards in the power distribution system will require the use of additional devices. The scientific literature on the subject indicates a very wide range of different topologies of AC voltage compensators. In this paper, different power electronics-based AC voltage compensator topologies are reviewed that are typically used with distribution energy systems. A summary of the properties and functionalities of the selected topologies has been presented. This review focuses mainly on the different topologies of the Unified Power Quality Controllers (UPQC) and Hybrid Transformers (HT). This review is divided into several sections. The first section presents the topologies used in UPQC and HT. The second section discusses selected control methods for these systems. The third section presents the basic properties of the systems related to compensating changes in the supply voltage and improvement of power quality. The fourth section presents the use of UPQC and HT systems. Finally, a summary and conclusions are presented.
Study of the Rheological Properties and Flow Process of High-Viscosity Oil Using Depressant Additives
Authors: Nikolaev Alexander , Plotnikova Kristina
Published: August 2023

This article analyzes the dependence of the choice of the method of transportation of high-viscosity oil on the rheological characteristics of the oil in question. An analysis of existing rheological models of high-viscosity oil was carried out, and it was found that a number of models have certain features (model coefficients, their purpose, quantity) that affect the choice of a rheological model of oil. The dependences for determining the coefficient of dynamic viscosity when pumping high-viscosity oil with the addition of pour-point depressants were studied, and the dependence of the hydraulic resistance coefficient when depressants are added to the oil was obtained. A method for choosing a rational oil heating temperature and diluent concentration to achieve the maximum pipeline performance is substantiated.
Physical and Numerical Simulations of Steam Drive and Gravity Drainage Using the Confined Bottom Oil–Water Transition Zone to Develop Super Heavy Oil
Authors: Xie Qian , Liang Guangyue , Liu Shangqi , Wang Ruifeng , Feng Min , Liao Changlin
Published: August 2023

The existence of the bottom oil–water transition zone (BTZ) greatly impairs the performance of the conventional steam-assisted gravity drainage (SAGD) process and its mitigation measures are very limited. In order to accelerate oil production and decrease the Steam-to-Oil Ratio (SOR), a promising technology involving a steam drive and gravity drainage (SDGD) process by placing dual-horizontal wells with high permeability in the BTZ was systematically studied. This paper conducted two-dimensional (2D) and three-dimensional (3D) physical simulations as well as 2D numerical simulation of the SDGD process to explore the mechanism, potential, and application conditions. The research findings indicate that the SDGD process in the BTZ with enhanced permeability through dilation stimulation can achieve higher oil production and lower SOR than the SAGD process. This process fully leverages the advantage of the BTZ to quickly establish inter-well thermal and hydraulic connectivity. The steam chamber first forms around the injector and then spreads towards the producer. By exerting the horizontal displacement of drained oil, oil production rapidly ramps up and keeps at a high rate under the synergistic effect of steam drive and gravity drainage. These insights enhance our understanding of the mechanism, potential, and application conditions of the SDGD process in the confined BTZ to develop super heavy oil or oil sands.
Impact of Influent Composition and Operating Conditions on Carbon and Nitrogen Removal from Urban Wastewater in a Continuous-Upflow (Micro)Aerobic Granular Sludge Blanket Reactor
Authors: Lanzetta Anna , Di Capua Francesco , Panneerselvam Balamurugan , Mattioli Davide , Esposito Giovanni , Papirio Stefano
Published: August 2023

Aerobic granular sludge is an interesting alternative to the conventional activated sludge (CAS) system and modified-Ludzack–Ettinger (MLE) process for biological wastewater treatment, as it allows a more cost-effective and simultaneous removal of carbon (C) and nitrogen (N) compounds in a single stage. In this study, (micro)aerobic C and N removal from synthetic urban wastewater was investigated in a continuous-double-column-upflow aerobic granular sludge blanket (UAGSB) system. The UAGSB reactor was operated under different dissolved oxygen (DO) ranges (0.01–6.00 mg∙L−1), feed C/N ratios (4.7–13.6), and hydraulic retention times (HRTs) (6–24 h). At a DO range of 0.01–0.30 mg∙L−1, feed C/N ratio of 13.6, and HRT of 24 h, the UAGSB achieved the highest chemical oxygen demand (COD), N-NH4+, and total inorganic nitrogen (TIN) removal efficiencies of 86, 99, and 84%, respectively. A preliminary assessment of the energy and economic savings associated with the process investigated was also carried out. The impact of capital and operating costs mainly related to the energy consumption of the aeration was taken into account. The assessment reveals that the capital and energy expenses of the UAGSB reactor would result in cost savings of around 14 and 7%, respectively, compared with a MLE system.
A Review of Current Advances in Ammonia Combustion from the Fundamentals to Applications in Internal Combustion Engines
Authors: Ma Fei , Guo Lingyan , Li Zhijie , Zeng Xiaoxiao , Zheng Zhencao , Li Wei , Zhao Feiyang , Yu Wenbin
Published: August 2023

The energy transition from hydrocarbon-based energy sources to renewable and carbon-free energy sources such as wind, solar and hydrogen is facing increasing demands. The decarbonization of global transportation could come true via applying carbon-free fuel such as ammonia, especially for internal combustion engines (ICEs). Although ammonia has advantages of high hydrogen content, high octane number and safety in storage, it is uninflammable with low laminar burning velocity, thus limiting its direct usage in ICEs. The purpose of this review paper is to provide previous studies and current research on the current technical advances emerging in assisted combustion of ammonia. The limitation of ammonia utilization in ICEs, such as large minimum ignition energy, lower flame speed and more NOx emission with unburned NH3, could be solved by oxygen-enriched combustion, ammonia–hydrogen mixed combustion and plasma-assisted combustion (PAC). In dual-fuel or oxygen-enriched NH3 combustion, accelerated flame propagation speeds are driven by abundant radicals such as H and OH; however, NOx emission should be paid special attention. Furthermore, dissociating NH3 in situ hydrogen by non-noble metal catalysts or plasma has the potential to replace dual-fuel systems. PAC is able to change classical ignition and extinction S-curves to monotonic stretching, which makes low-temperature ignition possible while leading moderate NOx emissions. In this review, the underlying fundamental mechanism under these technologies are introduced in detail, providing new insight into overcoming the bottleneck of applying ammonia in ICEs. Finally, the feasibility of ammonia processing as an ICE power source for transport and usage highlights it as an appealing choice for the link between carbon-free energy and power demand.
Cooperative Voltage and Frequency Regulation with Wind Farm: A Model-Based Offline Optimal Control Approach
Authors: Li Hua , Li Xudong , Xiong Weichen , Yan Yichen , Zhang Yuanhang , Kou Peng
Published: August 2023

Converter blocking is a serious malfunction encountered in high voltage direct current (HVDC) transmission systems. During sending-end converter blocking, the resultant active power and reactive power surplus in the sending-end power system lead to a severe increase in bus voltage and grid frequency. Consequently, this poses a substantial threat to the stability of the power system. Traditional control techniques generally control the frequency and voltage separately, which makes it challenging to regulate them jointly. This research paper introduces a collaborative approach for optimal control of voltage and frequency to address this issue. State space models for converter bus voltage and grid frequency prediction are developed using the bus voltage sensitivity matrices and system swing equation. The regulation of the converter bus voltage and grid frequency are intrinsically integrated using the explicit model predictive control (EMPC). When blocking occurs and results in an increase in the converter bus voltage and grid frequency, the EMPC controller regulates the output of active power and reactive power from the wind farm to realize the cooperative regulation of the converter bus voltage and grid frequency. The applicability and effectiveness of this strategy have been confirmed through simulation studies.
Hydrodynamic and Electrochemical Analysis of Compression and Flow Field Designs in Vanadium Redox Flow Batteries
Authors: Saha Snigdha , Maniam Kranthi Kumar , Paul Shiladitya , Patnaikuni Venkata Suresh
Published: August 2023

This numerical study investigates compression and flow field design effects on electrode behaviour in vanadium redox flow batteries (VRFBs). Through 3D simulations and analysis of various flow field designs, including conventional, serpentine, interdigitated, and parallel configurations, this study investigates three compression scenarios: uncompressed, non-homogeneously compressed, and homogeneously compressed electrodes. Hydrodynamic and electrochemical analyses reveal the impact on velocity, pressure, current density, overpotential, and charge–discharge performance. Interdigitated flow field is found to display the lowest charging potential and highest discharging potential among all flow fields under all three compression scenarios. Moreover, uncompressed electrode condition shows the conservative estimates of an average charging potential of 1.3647 V and average discharging potential of 1.3231 V in the case of interdigitated flow field, while compressed electrode condition and the non-homogeneously compressed electrode condition show an average charging potential of 1.3922 V and 1.3777 V, and an average discharging potential of 1.3019 V and 1.3224 V, respectively. Results highlight the significance of non-uniform compression while modelling and analysing the performance of VRFBs as it is a more realistic representation compared to the no-compression or homogeneous compression of the electrodes. The findings of this work provide insights for optimising VRFB performance by considering compression and flow field design.
An Agent-Based Decision Support Framework for a Prospective Analysis of Transport and Heat Electrification in Urban Areas
Authors: Bustos-Turu Gonzalo , van Dam Koen H. , Acha Salvador , Shah Nilay
Published: August 2023

One of the main pathways that cities are taking to reduce greenhouse gas emissions is the decarbonisation of the electricity supply in conjunction with the electrification of transport and heat services. Estimating these future electricity demands, greatly influenced by end-users’ behaviour, is key for planning energy systems. In this context, support tools can help decision-makers assess different scenarios and interventions during the design of new planning guidelines, policies, and operational procedures. This paper presents a novel bottom-up decision support framework using an agent-based modelling and simulation approach to evaluate, in an integrated way, transport and heat electrification scenarios in urban areas. In this work, an open-source tool named SmartCityModel is introduced, where agents represent energy users with diverse sociodemographic and technical attributes. Based on agents’ behavioural rules and daily activities, vehicle trips and building occupancy patterns are generated together with electric vehicle charging and building heating demands. A representative case study set in London, UK, is shown in detail, and a summary of more than ten other case studies is presented to highlight the flexibility of the framework to generate high-resolution spatiotemporal energy demand profiles in urban areas, supporting decision-makers in planning low-carbon and sustainable cities.
Developing a Comprehensive Mathematical Model for Aluminium Production in a Soderberg Electrolyser
Authors: Ilyushin Yury Valeryevich , Kapostey Ekaterina Ivanovna
Published: August 2023

The technological process of aluminium electrolysis is a complex scientific and technical task. This is due to a large number of internal, external and resultant factors. The aim of this work is to analyse these factors, assess them and their influence on the technological process of electrolysis and develop a comprehensive and mathematical model of aluminium production in the Soderberg electrolyser. The work analyses the technological process of primary aluminium production on the basis of the Bayer method and then on the basis of the Hall–Eru method. The existing methods and technologies for computer modelling of the technological process are analysed. The modern methods of analysis for thermal and electromagnetic fields in electrolysers are considered. On the basis of an in-depth analysis, a number of factors influencing the process of primary aluminium production are identified. Using the methods of system analysis to analyse the identified factors, a ranked list of factors according to the degree of influence is obtained. Using the Pareto diagram, we obtain a list of factors with maximum impact. A conceptual model of the technological process is derived. Based on the obtained conceptual model, the mathematical model of the technological process is derived. The conducted research may be useful to specialists in the field of metallurgy for the analysis of the technological processes of primary aluminium production.
Battery Energy Storage Systems for the New Electricity Market Landscape: Modeling, State Diagnostics, Management, and Viability—A Review
Authors: Carrasco Ortega Pablo , Durán Gómez Pablo , Mérida Sánchez Julio César , Echevarría Camarero Fernando , Pardiñas Ángel Á.
Published: August 2023

Renewable energy penetration and distributed generation are key for the transition towards more sustainable societies, but they impose a substantial challenge in terms of matching generation with demand due to the intermittent and unpredictable nature of some of these renewable energy sources. Thus, the role of energy storage in today’s and future electricity markets is undisputed. Batteries stand out among the different alternatives for energy storage. The R&D effort into different battery chemistries contributes to reducing the investment associated with battery systems. However, optimizing their operation according to the users’ and the electricity markets’ needs is the turning point to finally make these systems attractive. This review delves into the topic of battery management systems from a battery-technology-independent perspective, and it also explores more fundamental but related aspects, such as battery modeling or state estimation. The techno-economic part of battery energy storage systems is also covered in this document to understand their real potential and viability.
Analysis of the Seismic Performance of ±500 kV Flexible DC Converter Valves
Authors: Ding Can , Liu Yifan , Zhu Pingjie , Li Jinqi , Pu Guang
Published: August 2023

The converter valve is the core equipment of flexible DC transmission, but it has been severely damaged in previous earthquakes. Therefore, the seismic performance of its structure has a significant impact on the safety and reliability of power transmission. To study the seismic performance of ±500 kV flexible DC converter valves and identify weak links in the supporting valve tower, this article first established a refined finite-element model of a valve tower based on its physical structure; then modal analysis on the valve tower was conducted; finally, time-domain analysis of the valve tower under three seismic excitations, namely Wenchuan, EI Centro, and artificial, was conducted, and the equivalent stress and directional displacement cloud maps of the key parts of the valve tower were obtained. The research results indicate that the dynamic characteristics of the valve tower are relatively complex, with low fundamental frequency and diverse natural vibration modes. Under earthquake action, the predominant frequency of EI Centro waves is close to the fundamental frequency of the valve tower, which is prone to resonance and causes significant damage to the valve structure. The improved design of the valve tower meets the seismic strength requirements of level 8 seismic intensity.