bluuebunny/crossref_metadata_2025 huggingface dataset:
Present and Future of Immunotherapy for Triple-Negative Breast Cancer
Authors: Sriramulu Sushmitha , Thoidingjam Shivani , Speers Corey , Nyati Shyam
Published: September 2024

Triple-negative breast cancer (TNBC) lacks the expression of estrogen receptors (ERs), human epidermal growth factor receptor 2 (HER2), and progesterone receptors (PRs). TNBC has the poorest prognosis among breast cancer subtypes and is more likely to respond to immunotherapy due to its higher expression of PD-L1 and a greater percentage of tumor-infiltrating lymphocytes. Immunotherapy has revolutionized TNBC treatment, especially with the FDA’s approval of pembrolizumab (Keytruda) combined with chemotherapy for advanced cases, opening new avenues for treating this deadly disease. Although immunotherapy can significantly improve patient outcomes in a subset of patients, achieving the desired response rate for all remains an unmet clinical goal. Strategies that enhance responses to immune checkpoint blockade, including combining immunotherapy with chemotherapy, molecularly targeted therapy, or radiotherapy, may improve response rates and clinical outcomes. In this review, we provide a short background on TNBC and immunotherapy and explore the different types of immunotherapy strategies that are currently being evaluated in TNBC. Additionally, we review why combination strategies may be beneficial, provide an overview of the combination strategies, and discuss the novel immunotherapeutic opportunities that may be approved in the near future for TNBC.
Benchmarking of Approaches for Gene Copy-Number Variation Analysis and Its Utility for Genetic Aberration Detection in High-Grade Serous Ovarian Carcinomas
Authors: Grebnev Pavel Alekseevich , Meshkov Ivan Olegovich , Ershov Pavel Viktorovich , Makhotenko Antonida Viktorovna , Azarian Valentina Bogdanovna , Erokhina Marina Vyacheslavovna , Galeta Anastasiya Aleksandrovna , Zakubanskiy Aleksandr Vladimirovich , Shingalieva Olga Sergeevna , Tregubova Anna Vasilevna , Asaturova Aleksandra Vyacheslavovna , Yudin Vladimir Sergeevich , Yudin Sergey Mihaylovich , Makarov Valentin Vladimirovich , Keskinov Anton Arturovich , Makarova Anna Sergeevna , Snigir Ekaterina Andreevna , Skvortsova Veronika Igorevna
Published: September 2024

Objective: The goal of this study was to compare the results of CNV detection by three different methods using 13 paired carcinoma samples, as well as to perform a statistical analysis of the agreement. Methods: CNV was studied using NanoString nCounter v2 Cancer CN Assay (Nanostring), Illumina Infinium CoreExome microarrays (CoreExome microarrays) and digital droplet PCR (ddPCR). Results: There was a good level of agreement (PABAK score > 0.6) between the CoreExome microarrays and the ddPCR results for finding CNVs. There was a moderate level of agreement (PABAK values ≈ 0.3–0.6) between the NanoString Assay results and microarrays or ddPCR. For 83 out of 87 target genes studied (95%), the agreement between the CoreExome microarrays and NanoString nCounter was characterized by PABAK values < 0.75, except for MAGI3, PDGFRA, NKX2-1 and KDR genes (>0.75). The MET, HMGA2, KDR, C8orf4, PAX9, CDK6, and CCND2 genes had the highest agreement among all three approaches. Conclusions: Therefore, to get a better idea of how to genotype an unknown CNV spectrum in tumor or normal tissue samples that are very different molecularly, it makes sense to use at least two CNV detection methods. One of them, like ddPCR, should be able to quantitatively confirm the results of the other.
Prognostic Implications of Maintaining the Target Thyroid-Stimulating Hormone Status Based on the 2015 American Thyroid Association Guidelines in Patients with Low-Risk Papillary Thyroid Carcinoma after Lobectomy: A 5-Year Landmark Analysis
Authors: Jeon Ye Won , Suh Young Jin , Lim Seung Taek
Published: September 2024

Background: The 2015 American Thyroid Association guidelines recommend the maintenance of serum thyroid stimulating hormone (TSH) levels ≤2 mIU/L in patients with low-risk papillary thyroid carcinoma (PTC) who underwent lobectomy; however, the evidence is insufficient. We investigated the association between maintaining the TSH status at ≤2 mIU/L and tumor recurrence in patients with low-risk PTC who underwent lobectomy through a 5-year landmark analysis. Methods: Between 2010 and 2016, 662 patients with low-risk PTC were included. The postoperative TSH status was determined using the ‘TSH > 2 ratio’, which was calculated using the TSH test results during the 5-year follow-up. The optimal cutoff value of ‘TSH > 2 ratio’ for tumor recurrence was determined using a receiver operating characteristic curve analysis. Recurrence-free survival (RFS) was compared between the groups using Kaplan–Meier and Cox proportional hazard regression analyses. Results: Patients with ‘TSH > 2 ratio’ > 0.1833 (n = 498) had a worse RFS outcome compared to patients with ‘TSH > 2 ratio’ ≤ 0.1833 (n = 164; p < 0.001). ‘TSH > 2 ratio’ > 0.1833 was a significant risk factor for tumor recurrence after the 5-year landmark (hazard ratio: 4.795, 95% confidence interval: 2.102–10.937, p < 0.001). Conclusions: Maintaining TSH levels ≤ 2 mIU/L below a certain percentage among the total TSH tests during the 5-year follow-up period has a negative impact on tumor recurrence.
Promoting Electricity Production and Cr (VI) Removal Using a Light–Rutile–Biochar Cathode for Microbial Fuel Cells
Authors: Sun Baoyin , Xie Wenqing , Zhang Xiangwen , Zhou Yunzhu , Yang Zhaolin , Wang Lei , Zhou Jiqiang , Ren Guiping
Published: September 2024

Microbial fuel cell (MFC) technology holds significant promise for the production of clean energy and treatment of pollutants. Nevertheless, challenges such as low power generation efficiency and the high cost of electrode materials have impeded its widespread adoption. The porous microstructure of biochar and the exceptional photocatalytic properties of rutile endow it with promising catalytic potential. In this investigation, we synthesized a novel Rutile–Biochar (Rut-Bio) composite material using biochar as a carrier and natural rutile, and explored its effectiveness as a cathode catalyst to enhance the power generation efficiency of MFCs, as well as its application in remediating heavy metal pollution. Furthermore, the impact of visible light conditions on its performance enhancement was explored. The X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) analysis validated the successful fabrication of rutile composites loaded with biochar. The maximum current density and power density achieved by the MFCs were 153.9 mA/m2 and 10.44 mW/m2, respectively, representing a substantial increase of 113.5% and 225% compared to the control group. In addition, biochar-supported rutile MFCs showed excellent degradation performance of heavy metal pollutants under light conditions. Within 7 h, the Cr6+ degradation rate reached 95%. In contrast to the blank control group, the removal efficiency of pollutants exhibited increases of 630.8%. The cyclic degradation experiments also showcased the remarkable stability of the system over multiple cycles. This study successfully integrated natural rutile and biochar to fabricate highly efficient cathode photocatalyst composites, which not only enhanced the power generation performance of MFCs but also presented an environmentally sustainable and economically viable method for addressing heavy metal pollution.
Evaluation of Cobalt, Nickel, and Palladium Complexes as Catalysts for the Hydrogenation and Improvement of Oxidative Stability of Biodiesel
Authors: Sejie Fortunate P. , Oyetunji Olayinka A. , Makhubela Banothile C. E. , Darkwa James , de Leeuw Nora H.
Published: September 2024

Developing effective catalysts that can selectively hydrogenate C=C bonds in biodiesel samples is vital as it tackles the major problem of oxidative stability, which greatly limits the utilization of biodiesel as an alternative fuel. In this work, Co, Ni, and Pd catalysts stabilized with the bidentate nitrogen ligands N-(3-(triethoxysilyl)propyl)pyridin-2-ylmethylimine and N-(3-(triethoxysilyl)propyl)picolinamide were synthesized, characterized, and used as pre-catalysts in the transfer hydrogenation of C=C bonds in fatty acid methyl esters. The active catalysts from the Co, Ni, and Pd complexes sequentially hydrogenate the C18:2 chains to C18:1, which is further converted to C18:0 in the FAMEs of both methyl linoleate and jatropha biodiesel. The hydrogenation process was kinetically controlled, and after 3 h it yielded a biodiesel sample that contained 25.83% C16:0, 12.52% C18:2, 41.54% C18:1, 14.47% C18:0 and 3.0% C18:2 isomers. The un-hydrogenated jatropha diesel, hydrogenated jatropha diesel, and a B20 blend of jatropha were tested for susceptibility to oxidation reactions using the Rancimat method and FTIR spectroscopy, and the partial hydrogenation had improved the induction period by 3 h.
Genetic Variations in the NRF2 Microsatellite Contribute to the Regulation of Bovine Sperm-Borne Antioxidant Capacity
Authors: Anwar Khurshaid , Thaller Georg , Saeed-Zidane Mohammed
Published: September 2024

Nuclear factor (erythroid-derived 2)-like 2 (NRF2) is a transcription factor protein-coding gene, considered a master regulator of the cellular stress response. The genetic variations of the NRF2 could influence its transcriptional profile and, subsequently, the stress resilience in all cell types, including sperm cells. Therefore, the sperm-borne antioxidants abundance in association with the genetic variation of a GCC microsatellite located at the 5′ upstream region of the NRF2 gene was investigated in young (n = 8) and old (n = 8) Holstein bulls’ sperm cells at different seasons. The sperm DNA was sequenced using Sanger sequencing, while- the sperm-borne mRNA analysis was carried out using the synthesized cDNA and qPCR. The data were statistically analyzed using GraphPad Prism 10.0.2 software. The results showed that two bulls had a heterozygous genotype of eight and nine GCC repeats, while biallelic of eight, nine, and fifteen repeats were identified in two, ten, and two bulls, respectively. The computational in silico analysis revealed that the NRF2 upstream sequence with 15, 9, and 8 GCC repeats bound with 725, 709, and 707 DNA-binding transcription factor proteins, respectively. Lower quality of sperm DNA was detected in the spring season compared to other seasons and in young bulls compared to old ones, particularly in the summer and autumn seasons. The mRNA expression analysis revealed that the PRDX1 gene was the abundant transcript among the studied sperm-borne antioxidants and was significantly determined in old bulls’ spermatozoa. Moreover, two transcripts of the NRF2 gene and antioxidant (SOD1, CAT, GPX1, TXN1, NQO1) genes displayed differential expression patterns between the age groups across seasons in an antioxidant-dependent manner. The bulls with a heterozygous GCC sequence exhibited elevated sperm-borne mRNA levels of NRF2 and PRDX1 transcripts. Taken together, the findings suggest that the NRF2-GCC microsatellite may contribute to the transcription regulation of NRF2 transcripts and their subsequent downstream antioxidants in bovine sperm cells.
General Properties of Conventional and High-Temperature Superconductors
Authors: Shaginyan Vasily R. , Msezane Alfred Z. , Artamonov Stanislav A.
Published: September 2024

In our review, we analyze the scaling of the condensation energy EΔ divided by γ, EΔ/γ≃N(0)Δ12/γ, and quasiparticles of both conventional and unconventional superconductors, where N(0) is the density of states at zero temperature T=0, Δ1 is the maximum value of the superconducting gap, and γ is the Sommerfeld coefficient. It is shown that Bogoliubov quasiparticles act in superconducting states of unconventional and conventional superconductors. At the same time, quasiparticles are also present in the normal state of unconventional superconductors. We briefly describe the difference between unconventional superconductors and conventional ones, such as the resistivity in normal states and the difference in superfluid density in superconducting states. For the first time, we theoretically show that the universal scaling of EΔ/γ∝Tc2 applies equally to both conventional and unconventional superconductors. Our consideration is based on two experimental facts: Bogoliubov quasiparticles act in conventional and non-conventional superconductors and the corresponding flat band is deformed by the non-conventional superconducting state. As a result, our theoretical observations based on the theory of fermion condensation agree well with the experimental facts.
Imaging in Renal Cell Carcinoma Detection
Authors: Woon Dixon , Qin Shane , Al-Khanaty Abdullah , Perera Marlon , Lawrentschuk Nathan
Published: September 2024

Introduction: Imaging in renal cell carcinoma (RCC) is a constantly evolving landscape. The incidence of RCC has been rising over the years with the improvement in image quality and sensitivity in imaging modalities resulting in “incidentalomas” being detected. We aim to explore the latest advances in imaging for RCC. Methods: A literature search was conducted using Medline and Google Scholar, up to May 2024. For each subsection of the manuscript, a separate search was performed using a combination of the following key terms “renal cell carcinoma”, “renal mass”, “ultrasound”, “computed tomography”, “magnetic resonance imaging”, “18F-Fluorodeoxyglucose PET/CT”, “prostate-specific membrane antigen PET/CT”, “technetium-99m sestamibi SPECT/CT”, “carbonic anhydrase IX”, “girentuximab”, and “radiomics”. Studies that were not in English were excluded. The reference lists of selected manuscripts were checked manually for eligible articles. Results: The main imaging modalities for RCC currently are ultrasound, computed tomography (CT) and magnetic resonance imaging (MRI). Contrast-enhanced US (CEUS) has emerged as an alternative to CT or MRI for the characterisation of renal masses. Furthermore, there has been significant research in molecular imaging in recent years, including FDG PET, PSMA PET/CT, 99mTc-Sestamibi, and anti-carbonic anhydrase IX monoclonal antibodies/peptides. Radiomics and the use of AI in radiology is a growing area of interest. Conclusions: There will be significant change in the field of imaging in RCC as molecular imaging becomes increasingly popular, which reflects a shift in management to a more conservative approach, especially for small renal masses (SRMs). There is the hope that the improvement in imaging will result in less unnecessary invasive surgeries or biopsies being performed for benign or indolent renal lesions.
Factors Related to Bracket Bond Failure during Orthodontic Treatment: A Single-Centre Single-Operator Study
Authors: Quinty Olivier , Antonarakis Gregory S. , Kiliaridis Stavros , Mavropoulos Anestis
Published: September 2024

This study aimed to investigate the influence of various patient-specific and bracket location-specific factors on bracket survival rates during comprehensive fixed appliance orthodontic treatment. A total of 197 patients (116 females, 81 males; mean age 16.3 years) having completed orthodontic treatment were included in this retrospective cohort study. Patients were treated using stainless steel non-self-ligating brackets, and the treatment duration was 23.7 months on average. The primary outcome was bracket bond failure. Potential predictors for bracket bond failure recorded included age, sex, oral hygiene, treatment duration, and several pre-treatment cephalometric characteristics such as overjet, overbite, and sagittal and vertical skeletal relationships. Factors associated with bracket failure were analysed with Cox regression, and proportional hazard assumptions were assessed using Kaplan–Meier tests. The overall failure rate was 4.4%. Bracket bond failure rates varied among tooth types and seemed to occur more on posterior teeth and on the right side of the arch. Bracket failure was more common in male patients and those with poor oral hygiene. Concerning dentofacial characteristics, bracket failure of anterior teeth was more common in those with an increased overjet and overbite.
Transient GI/MSP/1/N Queue
Authors: Chydzinski Andrzej
Published: September 2024

A non-zero correlation between service times can be encountered in many real queueing systems. An attractive model for correlated service times is the Markovian service process, because it offers powerful fitting capabilities combined with analytical tractability. In this paper, a transient study of the queue length in a model with MSP services and a general distribution of interarrival times is performed. In particular, two theorems are proven: one on the queue length distribution at a particular time t, where t can be arbitrarily small or large, and another on the mean queue length at t. In addition to the theorems, multiple numerical examples are provided. They illustrate the development over time of the mean queue length and the standard deviation, along with the complete distribution, depending on the service correlation strength, initial system conditions, and the interarrival time variance.
The Application of Pinch Technology to a Novel Closed-Loop Spray Drying System with a Condenser and Reheater
Authors: Lei Zexin , O’Neill Thomas , Langrish Timothy
Published: September 2024

Spray drying is an energy-intensive process in industrial use, making energy recovery a critical focus for improving overall efficiency. This study investigates the potential of integrating heat-recovery systems, including an innovative air reheater, into a closed-loop spray-drying unit to maximise energy savings. Through detailed pinch analysis, the system achieved a very low approach temperature, averaging 3.48 K, which is significantly lower than that of conventional open-loop systems. The study quantifies the energy-recovery potential by demonstrating that the integration of heat-recovery components can reduce the external heating demand by up to 30%. This not only enhances heat-transfer efficiency but also lowers operational costs and reduces the system’s environmental impact. The results suggest that closed-loop systems with air reheaters offer a scalable solution for improving energy efficiency across different industrial applications. The research highlights a new paradigm: focusing on latent energy within the system rather than adjusting individual operational variables.
Improving the Light Extraction Efficiency of GaN-Based Thin-Film Flip-Chip Micro-LEDs through Inclined Sidewall and Photonic Crystals
Authors: Liu Meng , Zheng Xuan
Published: September 2024

Low light extraction efficiency (LEE) remains a critical bottleneck in the performance of contemporary micro-light-emitting diodes (micro-LEDs). This study presents an innovative approach to improve the LEE of Gallium nitride (GaN)-based thin-film flip-chip (TFFC) micro-LEDs by integrating an inclined sidewall with photonic crystals (PhCs). Three-dimensional finite-difference time-domain (FDTD) simulations reveal that the inclined sidewall design significantly increases the escape probability of light, thereby improving LEE. Additionally, the PhCs’ structure further improves LEE by enabling more light to propagate into the escape cones through diffraction. Optimal results are achieved when the inclined sidewall angle (θ) is 28° and the PhCs exhibit a period (a) of 220 nm, a filling factor (f) of 0.8, and a depth (d) of 3 μm, resulting in a maximum LEE of 36.47%, substantially surpassing the LEE of conventional planar TFFC micro-LEDs. These results provide valuable design guidelines for the development of high-efficiency GaN-based micro-LEDs.
Efficient Convolutional Neural Networks Utilizing Fine-Grained Fast Fourier Transforms
Authors: Zhang Yulin , Li Feipeng , Xu Haoke , Li Xiaoming , Jiang Shan
Published: September 2024

Convolutional Neural Networks (CNNs) are among the most prevalent deep learning techniques employed across various domains. The computational complexity of CNNs is largely attributed to the convolution operations. These operations are computationally demanding and significantly impact overall model performance. Traditional CNN implementations convert convolutions into matrix operations via the im2col (image to column) technique, facilitating parallelization through advanced BLAS libraries. This study identifies and investigates a significant yet intricate pattern of data redundancy within the matrix-based representation of convolutions, a pattern that, while complex, presents opportunities for optimization. Through meticulous analysis of the redundancy inherent in the im2col approach, this paper introduces a mathematically succinct matrix representation for convolution, leading to the development of an optimized FFT-based convolution with finer FFT granularity. Benchmarking demonstrates that our approach achieves an average speedup of 14 times and a maximum speedup of 17 times compared to the regular FFT convolution. Similarly, it outperforms the Im2col+GEMM approach from NVIDIA’s cuDNN library, achieving an average speedup of three times and a maximum speedup of five times. Our FineGrained FFT convolution approach, when integrated into Caffe, a widely used deep learning framework, leads to significant performance gains. Evaluations using synthetic CNNs designed for real-world applications show an average speedup of 1.67 times. Furthermore, a modified VGG network variant achieves a speedup of 1.25 times.
A Voltage Equalization Strategy for Series-Connected SiC MOSFET Applications
Authors: Li Peng , Liu Jialin , Sun Shikai , Yang Wenhao , Sun Yuyin , Zhang Yuming
Published: September 2024

A novel clamped voltage equalization strategy is presented for series-connected Silicon Carbide (SiC) Metal–Oxide semiconductor Field-Effect transistors (MOSFETs) in this paper. Differences in device parameters and circuit asymmetry result in the uneven voltage distribution of series-connected SiC MOSFETs, which threatens the safe operation of the circuit. Dynamic voltage equalization is difficult to achieve due to the fast switching speed of SiC MOSFETs. This paper analyzes the switching characteristics and dynamic voltage equalization characteristics of SiC MOSFETs. Based on the analysis, an energy recovery strategy based on the clamping auxiliary circuit is proposed. A 2.8 kW (50 KHz) prototype is fabricated and tested to verify the strategy. Measurement results show that the maximum voltage stress is suppressed from 600 V to less than 320 V in the experimental condition.
Eddy Current Mechanism Model for Dynamic Magnetic Field in Ferromagnetic Metal Structures
Authors: Zuo Chao , Lai Zhipeng , Wang Zuoshuai , Wang Jianxun , Xiao Hanchen , Yang Wentie , Geng Pan , Chen Meng
Published: September 2024

The degaussing process is crucial for ensuring magnetic protection in ships. It involves the application of oscillating and attenuating magnetic fields to eliminate residual magnetism in the ship’s structure. However, this process can lead to the generation of distorted magnetic fields within the ship’s cabin, posing a potential threat to electronic equipment performance. Therefore, it is essential to have a comprehensive understanding of the dynamic magnetic field response in ship structures to develop effective degaussing systems. To address this need, this paper proposes an eddy current model for analyzing the dynamic magnetic field response in ferromagnetic metal structures. This model focuses on the role of eddy currents in shaping the magnetic field response and provides valuable insights into the underlying mechanisms. Using the proposed eddy current model, the effects of key system parameters such as thickness, conductivity, and the length-scale of the ship structure can be analytically investigated. This analysis helps in understanding how these parameters influence the dynamic magnetic field response and aids in the design and optimization of degaussing systems. The effectiveness and applicability of the proposed eddy current model are demonstrated through comprehensive investigations involving two simulation cases of varying complexity. The model accurately predicts the changing trends of the dynamic magnetic field response, as confirmed through finite element simulations. This validation highlights the model’s ability to reproduce simulation results accurately and its potential as a powerful tool for analyzing and optimizing dynamic magnetic field responses. In summary, the proposed eddy current model represents a significant advancement in the field. It provides a valuable theoretical framework for understanding and analyzing the dynamic magnetic field response in ferromagnetic metal structures. By offering insights into the underlying mechanisms and the influence of key parameters, this research contributes to the development of improved degaussing systems and enhances the overall magnetic protection capabilities of ships.
Diagnosis of DC-DC Converter Semiconductor Faults Based on the Second-Order Derivative of the Converter Input Current
Authors: Bento Fernando , Cardoso Antonio J. Marques
Published: September 2024

The deployment of DC microgrids presents an excellent opportunity to enhance energy efficiency in buildings. Among other components, DC-DC converters play a crucial role in ensuring the interface between the microgrid and its energy generation, storage, and consumption components. However, the reliability of these energy conversion solutions remains somewhat limited. Adopting strategies for accurate monitoring and diagnostics of the DC-DC converter topologies that best suit each equipment’s constraints is, therefore, of critical relevance. Solutions available in the literature concerning fault diagnostics on DC-DC converters do not consider the application of such converters in the household and tertiary sector environments and associated constraints—cost effectiveness, robustness against parameter uncertainty of the converter model, and obviation of the need for historical data. On this basis, this paper presents a simple and effective fault diagnostic strategy, based on a time-domain analysis of the second-order derivative of the converter input current. Its implementation is straightforward and can be integrated into the pre-installed converter control unit. The unique features of the fault diagnostic algorithm show good results for a broad range of operating points, along with insensitivity against load transients and supply voltage fluctuations.
Applications of Computer Vision, 2nd Edition
Authors: Cernadas Eva
Published: September 2024

Computer vision (CV) is a broad term mainly used to refer to processing image and video data [...]
Geometry of Textual Data Augmentation: Insights from Large Language Models
Authors: Feng Sherry J. H. , Lai Edmund M-K. , Li Weihua
Published: September 2024

Data augmentation is crucial for enhancing the performance of text classification models when labelled training data are scarce. For natural language processing (NLP) tasks, large language models (LLMs) are able to generate high-quality augmented data. But a fundamental understanding of the reasons for their effectiveness remains limited. This paper presents a geometric and topological perspective on textual data augmentation using LLMs. We compare the augmentation data generated by GPT-J with those generated through cosine similarity from Word2Vec and GloVe embeddings. Topological data analysis reveals that GPT-J generated data maintains label coherence. Convex hull analysis of such data represented by their two principal components shows that they lie within the spatial boundaries of the original training data. Delaunay triangulation reveals that increasing the number of augmented data points that are connected within these boundaries correlates with improved classification accuracy. These findings provide insights into the superior performance of LLMs in data augmentation. A framework for predicting the usefulness of augmentation data based on geometric properties could be formed based on these techniques.
A Novel Feedforward Scheme for Enhancing Dynamic Performance of Vector-Controlled Dual Active Bridge Converter with Dual Phase Shift Modulation for Fast Battery Charging Systems
Authors: Nkembi Armel Asongu , Santoro Danilo , Ahmad Fawad , Kortabarria Iñigo , Cova Paolo , Sacchi Emilio , Delmonte Nicola
Published: September 2024

This paper proposes a novel feedforward control scheme to achieve a very smooth transition from Constant Current (CC) to Constant Voltage (CV) charging modes, the commonly used method for electric vehicle charging applications. Furthermore, a three-loop model-independent Linear Active Disturbance Rejection Control (LADRC)-based system is proposed, replacing the traditional two-loop Proportional-Integral (PI) control system. The extra loop performs a decoupled dq vector control of the inductor current, which is typically not used in single-phase Dual Active Bridge (DAB) systems. This additional loop not only facilitates the optimal determination of both internal and external phase shift angles of a Dual-Phase Shift (DPS) modulator but also lowers the peak input current of the converter, allowing for lower-rated switches. Numerical simulations using MATLAB/Simulink demonstrate the robustness of the proposed control strategy against both input voltage disturbances and load disturbances during the transition from CC to CV charging modes. Hence, the dynamic performance of the charging system is significantly improved with minimal controller effort.
TWPT: Through-Wall Position Detection and Tracking System Using IR-UWB Radar Utilizing Kalman Filter-Based Clutter Reduction and CLEAN Algorithm
Authors: Zhang Jinlong , Dang Xiaochao , Hao Zhanjun
Published: September 2024

Against the backdrop of rapidly advancing Artificial Intelligence of Things (AIOT) and sensing technologies, there is a growing demand for indoor location-based services (LBSs). This paper proposes a through-the-wall localization and tracking (TWPT) system based on an improved ultra-wideband (IR-UWB) radar to achieve more accurate localization of indoor moving targets. The TWPT system overcomes the limitations of traditional localization methods, such as multipath effects and environmental interference, using the high penetration and high accuracy of IR-UWB radar based on multi-sensor fusion technology. In the study, an improved Kalman filter (KF) algorithm is used for clutter reduction, while the CLEAN algorithm, combined with a compensation mechanism, is utilized to increase the target detection probability. Finally, a three-point localization estimation algorithm based on multi-IR-UWB radar is applied for the precise position and trajectory estimation of the target. Experimental validation indicates the TWPT system achieves a high positioning accuracy of 96.91%, with a root mean square error (RMSE) of 0.082 m and a Maximum Position Error (MPE) of 0.259 m. This study provides a highly accurate and precise solution for indoor TWPT based on IR-UWB radar.
Multi-Objective Short-Term Operation of Hydro–Wind–Photovoltaic–Thermal Hybrid System Considering Power Peak Shaving, the Economy and the Environment
Authors: Liu Yongqi , Li Yuanyuan , Hou Guibing , Qin Hui
Published: September 2024

In recent years, renewable, clean energy options such as hydropower, wind energy and solar energy have been attracting more and more attention as high-quality alternatives to fossil fuels, due to the depletion of fossil fuels and environmental pollution. Multi-energy power systems have replaced traditional thermal power systems. However, the output of solar and wind power is highly variable, random and intermittent, making it difficult to integrate it directly into the grid. In this context, a multi-objective model for the short-term operation of wind–solar–hydro–thermal hybrid systems is developed in this paper. The model considers the stability of the system operation, the operating costs and the impact in terms of environmental pollution. To solve the model, an evolutionary cost value region search algorithm is also proposed. The algorithm is applied to a hydro–thermal hybrid system, a multi-energy hybrid system and a realistic model of the wind–solar–hydro experimental base of the Yalong River Basin in China. The experimental results demonstrate that the proposed algorithm exhibits superior performance in terms of both convergence and diversity when compared to the reference algorithm. The integration of wind and solar energy into the power system can enhance the economic efficiency and mitigate the environment impact from thermal power generation. Furthermore, the inherent unpredictability of wind and solar energy sources introduces operational inconsistencies into the system loads. Conversely, the adaptable operational capacity of hydroelectric power plants enables them to effectively mitigate peak loads, thereby enhancing the stability of the power system. The findings of this research can inform decision-making regarding the economic, ecological and stable operation of hybrid energy systems.
Attention-Based Load Forecasting with Bidirectional Finetuning
Authors: Kamalov Firuz , Zicmane Inga , Safaraliev Murodbek , Smail Linda , Senyuk Mihail , Matrenin Pavel
Published: September 2024

Accurate load forecasting is essential for the efficient and reliable operation of power systems. Traditional models primarily utilize unidirectional data reading, capturing dependencies from past to future. This paper proposes a novel approach that enhances load forecasting accuracy by fine tuning an attention-based model with a bidirectional reading of time-series data. By incorporating both forward and backward temporal dependencies, the model gains a more comprehensive understanding of consumption patterns, leading to improved performance. We present a mathematical framework supporting this approach, demonstrating its potential to reduce forecasting errors and improve robustness. Experimental results on real-world load datasets indicate that our bidirectional model outperforms state-of-the-art conventional unidirectional models, providing a more reliable tool for short and medium-term load forecasting. This research highlights the importance of bidirectional context in time-series forecasting and its practical implications for grid stability, economic efficiency, and resource planning.
Dielectric Constant Predictions for Jet-Range Hydrocarbons: Evaluating the Clausius–Mossotti Relation and Correcting for Molecular Dipole Moments
Authors: Faulhaber Conor , Bell David C. , Boehm Randall , Heyne Joshua
Published: September 2024

The dielectric constant of aviation turbine fuel is leveraged by aircraft fuel quantity indicator systems (FQISs) using the Clausius–Mossotti relation, which assumes no significant dipole moments. For fossil-derived jet fuel containing relatively consistent fractions of polar aromatic molecules, this is appropriate. However, the interest in sustainable aviation fuels (SAFs) to reduce the carbon intensity of commercial aviation has brought attention to the uncertainty of the FQISs’ compatibility for low- or zero-aromatic fuels exhibiting dielectric constant values outside of the conventional Jet-A range. A dielectric constant model accounting for the varying dipole moments of both aromatic and non-aromatic jet-range hydrocarbons improves the community’s understanding of fuel composition on FQISs’ operability and provides a tool suitable for fuel performance property optimizations while maintaining compatibility with current aircraft systems. Here, the Clausius–Mossotti relation is first evaluated against a training dataset of 240 dielectric constant and density measurements (48 neat hydrocarbons each measured at five temperatures). Then, the dipole moment is calculated for each species of interest using open-source computational chemistry software, and a second-degree binomial regression is performed over the training data to correct for the error in the Clausius–Mossotti relation. The Clausius–Mossotti relation exhibited an R2 value of 0.54, which increased to 0.92 when terms for the dipole correction were added to the model. The improved accuracy from this model establishes a computationally inexpensive framework for modeling theoretical fuel compositions that demonstrate improved performance characteristics (sooting propensity, thermal management, aircraft efficiency, etc.) while remaining within key limiting property constraints, such as the dielectric constant.
Hot Topics at the 18th SDEWES Conference in 2023: A Conference Report
Authors: Chu Wenxiao , Vicidomini Maria , Calise Francesco , Duić Neven , Østergaard Poul Alberg , Wang Qiuwang , da Graça Carvalho Maria
Published: September 2024

The present paper reviews the hot topics at the 18th Conference on Sustainable Development of Energy, Water, and Environment Systems (SDEWES) held from 24 to 29 September 2023 in Dubrovnik, Croatia. The selected papers, including aspects of biomass energy application, energy saving in building, low-carbon development and climate change adaptation, hybrid application of sustainable energy, energy storage system, and other measures in sustainable development, are published in this Special Issue of Energies. The 12 selected papers in Energies and corresponding literature that relates to the above topics and has been published in the most recent year are reviewed. In particular, diversifying energy applications are trending towards comprehensive integration with more efficient clean energy capacities for global energy procurement, which can also offer increased resilience and sustainability, reduce reliance on fossil fuels, mitigate environmental impacts, and enhance energy security through a mix of renewable sources and innovative technologies. Meanwhile, energy storage has become increasingly important, which can manage the intermittent of renewable energy, stabilize the grid, and improve energy security and resilience against disruptions. In addition to conventional solar energy storage, biomass energy storage, building energy storage, water storage, etc., can also reduce the overall energy costs, deferring investments in additional transmission infrastructure.
Sustainable Biomethanol and Biomethane Production via Anaerobic Digestion, Oxy-Fuel Gas Turbine and Amine Scrubbing CO2 Capture
Authors: Gholizadeh Towhid , Ghiasirad Hamed , Skorek-Osikowska Anna
Published: September 2024

Energy policies around the world are increasingly highlighting the importance of hydrogen in the evolving energy landscape. In this regard, the use of hydrogen to produce biomethanol not only plays an essential role in the chemical industry but also holds great promise as an alternative fuel for global shipping. This study evaluates a system for generating biomethanol and biomethane based on anaerobic digestion, biogas upgrading, methanol synthesis unit, and high-temperature electrolysis. Thermal integration is implemented to enhance efficiency by linking the oxy-fuel gas turbine unit. The integrated system performance is evaluated through thermodynamic modeling, and Aspen Plus V12.1 is employed for the analysis. Our findings show that the primary power consumers are the Solid Oxide Electrolysis Cell (SOEC) and Methanol Synthesis Unit (MSU), with the SOEC system consuming 824 kW of power and the MSU consuming 129.5 kW of power, corresponding to a production scale of 23.2 kg/h of hydrogen and 269.54 kg/h of biomethanol, respectively. The overall energy efficiency is calculated at 58.09%, considering a production output of 188 kg/h of biomethane and 269 kg/h of biomethanol. The amount of carbon dioxide emitted per biofuel production is equal to 0.017, and the proposed system can be considered a low-carbon emission system. Key findings include significant enhancements in biomethanol capacity and energy efficiency with higher temperatures in the methanol reactor.
Integrated Energy System Dispatch Considering Carbon Trading Mechanisms and Refined Demand Response for Electricity, Heat, and Gas
Authors: Gao Lihui , Yang Shuanghao , Chen Nan , Gao Junheng
Published: September 2024

To realize a carbon-efficient and economically optimized dispatch of the integrated energy system (IES), this paper introduces a highly efficient dispatch strategy that integrates demand response within a tiered carbon trading mechanism. Firstly, an efficient dispatch model making use of CHP and P2G technologies is developed to strengthen the flexibility of the IES. Secondly, an improved demand response model based on the price elasticity matrix and the capacity for the substitution of energy supply modes is constructed, taking into account three different kinds of loads: heat, gas, and electricity. Subsequently, the implementation of a reward and penalty-based tiered carbon trading mechanism regulates the system’s carbon trading costs and emissions. Ultimately, the goal of the objective function is to minimize the overall costs, encompassing energy purchase, operation and maintenance, carbon trading, and compensation. The original problem is reformulated into a mixed-integer linear programming problem, which is solved using CPLEX. The simulation results from four example scenarios demonstrate that, compared with the conventional carbon trading approach, the aggregate system costs are reduced by 2.44% and carbon emissions are reduced by 3.93% when incorporating the tiered carbon trading mechanism. Subsequent to the adoption of demand response, there is a 2.47% decrease in the total system cost. The proposed scheduling strategy is validated as valuable to ensure the low-carbon and economically efficient functioning of the integrated energy system.
Thermodynamic Comparative Analysis of Cascade Refrigeration System Pairing R744 with R404A, R448A and R449A with Internal Heat Exchanger: Part 2—Exergy Characteristics
Authors: Jeon Min-Ju , Lee Joon-Hyuk
Published: September 2024

The cascade refrigeration systems (CRS) used in hypermarkets and supermarkets, which are used by many people, have been employing R744 for the low-temperature cycle (LTC) and R404A for the high-temperature cycle (HTC) due to environmental and public safety issues. However, the use of R404A is limited due to its high GWP, and therefore research on alternative refrigerants is necessary. Nevertheless, there is no detailed study in the literature that compares and analyzes the three refrigerants for practical design by applying R744 for LTC and R404A, R448A, and R449A for HTC in CRS. Therefore, this study aims to provide data for the practical detailed design of an alternative system to R744/R404A CRS. Under standard conditions, we analyzed how the exergy destruction rate (EDR) and exergy efficiency (EE) of the system and the EDR of each component change when the important factors affecting CRS (degree of superheating (DSH), degree of subcooling (DSC), and internal heat exchanger (IHX) efficiency of HTC, DSH of LTC, condensation temperature (CT), evaporation temperature (ET), cascade evaporation temperature (CET), and temperature difference of CHX) are varied over a wide range. The main conclusions are as follows. (1) Under the given constant conditions, the smallest change in system EDR based on R448A is DSH of HTC (decreased by 0.07–0.1 kW), followed by IHX of HTC (decreased by 0.12–0.3 kW), DSH of LTC (increased by 0.19–0.25 kW), DSC of HTC (decreased by 0.59–0.69 kW), temperature difference of CHX (increased by 1.57–1.83 kW), CET (decreased and then increased by 0.67–4.43 kW), CT (increased by 1.49–3.9 kW), ET (decreased by 2.39–4.61 kW). (2) The highest change rate of system EE based on R448A is CET (increased and then decreased by 1.38–8.28%), followed by temperature difference of CHX (decreased by 2.96–3.16%), ET (increased and then decreased by 0.63–2.75%), DSC of HTC (increased by 1.26–1.34%), CT (increased and then decreased by 0.24–1.12%), IHX of HTC (increased by 0.11–1.02%), DSH of LTC (decreased by 0.35–0.49%), and DSH of HTC (increased by 0.14–0.19%).
Possibilities of Changes in Energy Intensity of Production Depending on the Scale of Farm Investments in a Polish Region
Authors: Czubak Wawrzyniec , Zmyślona Jagoda
Published: September 2024

The purpose of this paper was to analyze the possibility of changes in energy intensity of production in the context of farm investment scale. The empirical section relies on unpublished FADN microdata. The study answers the question of whether investments and fixed capital growth can contribute to improvements in environmental performance of agricultural production. As it turns out, the group of farms with the greatest amount of investments saw an increase in energy consumption costs, though at a much slower rate than growth in production value. As a result, there was a drop in energy intensity of production, defined as the ratio between energy costs and production value. These findings corroborate the hypothesis advanced in this study, namely that upon reaching a sufficiently large amount of investments, farms can become capable of reducing the energy intensity of their production activity. Hence, higher levels of capital productivity are attained when the farms invest in more energy-efficient fixed assets. Conclusions cannot be universal, as the analysis involved a portion of selected farms. However, the research indicates a trend in the study of energy intensity of production depending on the scale of investment and the validity of the investment comprehensiveness approach. These conclusions provide a basis for recommendations for an agricultural policy which should include support for investments that are large and comprehensive (in relation to the farm’s assets) and go beyond the simple renewal of assets. Therefore, in its investment-oriented measures, the agricultural policy should take the innovativeness (including energy efficiency) criterion into account.
Technology Progress in High-Frequency Electromagnetic In Situ Thermal Recovery of Heavy Oil and Its Prospects in Low-Carbon Situations
Authors: Yang Yang , Liu Wenchao , Yu Jifei , Liu Chen , Cao Yanfeng , Sun Mingkai , Li Menglong , Meng Zicheng , Yan Xinjiang
Published: September 2024

Heavy oil resources are abundant globally, holding immense development potential. However, conventional thermal recovery methods such as steam injection are plagued by high heat loss, substantial carbon emissions, and significant water consumption, making them incompatible with carbon reduction goals and the sustainable socioeconomic development demands. A new method of high-frequency electromagnetic in situ heating, which targets polar molecules, can convert electromagnetic energy into heat so as to achieve rapid volumetric heating of the reservoir. This method has the potential to overcome the drawbacks of traditional techniques. Nevertheless, it faces significant drawbacks such as limited heating range and inadequate energy supply during later production stages, which necessitates auxiliary enhancement measures. Various enhancement measures have been reported, including nitrogen injection, hydrocarbon solvent injection, or the use of nano-metal oxide injections. These methods are hindered by issues such as pure nitrogen being easy to breakthrough, high costs, and metal pollution. Through extensive literature review, this article charts the evolution of high-frequency electromagnetic in situ heating technology for heavy oil and the current understanding of the coupled heat and mass transfer mechanisms underlying this technology. Moreover, based on a profound analysis of the technology’s progression trends, this work introduces a new direction: CO2-N2 co-injection as an enhancement strategy for high-frequency electromagnetic in situ heavy oil recovery. There is promising potential for the development of new technologies in the future that combine high efficiency, low carbon emissions, environmental friendliness, economic viability, and energy conservation. Furthermore, some research prospects in low-carbon situations and challenges for the new technology in future are presented in detail. All in all, the contribution of the paper lies in the summarizing of some main drawbacks of current enhanced electromagnetic in situ thermal recovery methods, and presents a novel research direction of using CO2-N2 co-injection as an enhancement strategy based on its current research status in low-carbon situations.