bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Particle Size of Curcumin Solid Dispersions on Bioavailability and Anti-Inflammatory Activities
Authors: Kato Chihiro , Itaya-Takahashi Mayuko , Miyazawa Taiki , Ito Junya , Parida Isabella Supardi , Yamada Hiroki , Abe Akari , Shibata Mika , Someya Keita , Nakagawa Kiyotaka
Published: March 2023

The delivery of curcumin (CUR) using the solid dispersion system (CUR solid dispersions; C-SDs) has been shown to improve CUR bioavailability. However, it is unclear how different particle sizes of C-SDs affect the bioavailability and biological activities of CUR. Hence, we prepared C-SDs in different sizes using food-grade excipients and evaluated their bioavailability and biological activities. By pulverizing large particle sizes of C-SDs using zirconia beads, we successfully prepared C-SDs I-IV (particle size: (I) 120, (II) 447, (III) 987, (IV) 1910 nm). When administrated orally in rats, the bioavailability of CUR was increased with decreasing C-SDs size, most likely by improving its solubility in micelles. When administrated intravenously in rats, blood concentrations of CUR were increased with increasing particle size, suggesting that larger C-SDs presumably control the metabolic conversion of CUR. In RAW264 cells, more CUR was taken up by cells as their sizes reduced, and the more potent their anti-inflammatory activities were, suggesting that smaller C-SDs were taken up through a number of cellular uptake pathways. Altogether, the present study showed an evident effect of C-SDs size on their bioavailability and anti-inflammatory activities—information that serves as a basis for improving the functionality of CUR.
Bayesian Inference and Data Analysis of the Unit–Power Burr X Distribution
Authors: Fayomi Aisha , Hassan Amal S. , Baaqeel Hanan , Almetwally Ehab M.
Published: March 2023

The unit–power Burr X distribution (UPBXD), a bounded version of the power Burr X distribution, is presented. The UPBXD is produced through the inverse exponential transformation of the power Burr X distribution, which is also beneficial for modelling data on the unit interval. Comprehensive analysis of its key characteristics is performed, including shape analysis of the primary functions, analytical expression for moments, quantile function, incomplete moments, stochastic ordering, and stress–strength reliability. Rényi, Havrda and Charvat, and d-generalized entropies, which are measures of uncertainty, are also obtained. The model’s parameters are estimated using a Bayesian estimation approach via symmetric and asymmetric loss functions. The Bayesian credible intervals are constructed based on the marginal posterior distribution. Monte Carlo simulation research is intended to test the accuracy of various estimators based on certain measures, in accordance with the complex forms of Bayesian estimators. Finally, we show that the new distribution is more appropriate than certain other competing models, according to their application for COVID-19 in Saudi Arabia and the United Kingdom.
End-to-End Direct-Current-Based Extreme Fast Electric Vehicle Charging Infrastructure Using Lithium-Ion Battery Storage
Authors: Powar Vishwas , Singh Rajendra
Published: March 2023

An urgent need to decarbonize the surface transport sector has led to a surge in the electrification of passenger and heavy-duty fleet vehicles. The lack of widespread public charging infrastructure hinders this electric vehicle (EV) transition. Extreme fast charging along interstates and highway corridors is a potential solution. However, the legacy power grid based on alternating current (AC) beckons for costly upgrades that will be necessary to sustain sporadic fast charging loads. The primary goal of this paper is to propose a sustainable, low-loss, extremely fast charging infrastructure based on photovoltaics (PV) and co-located lithium-ion battery storage (BESS). Lithium-ion BESS plays a pivotal role in our proposed design by mitigating demand charges and operating as an independent 16–18 h power source. An end-to-end direct current power network with high voltage direct current interconnection is also incorporated. The design methodology focuses on comprehensive hourly EV-load models generated for different types of passenger vehicles and heavy-duty fleet charging. Appropriate PV-BESS sizing, optimum tilt, and temperature compensation techniques based on 15 years of irradiation data were utilized in the design. The proposed grid-independent DC power networks can significantly improve well-to-wheels efficiency by minimizing total system losses for fast charging networks. The network power savings for low, medium, and high voltage use cases were evaluated. Our results demonstrate 17% to 25% power savings compared to the traditional AC case.
Influence of the Thermal Treatment on the Structure and Cycle Life of Copper Hexacyanoferrate for Aqueous Zinc-Ion Batteries
Authors: Baghodrat Mohsen , Zampardi Giorgia , Glenneberg Jens , La Mantia Fabio
Published: March 2023

Copper hexacyanoferrate (CuHCF) has become an attractive Zn2+ insertion material as a positive electrode in aqueous zinc-ion batteries thanks to its high reversibility towards Zn2+ (de-)insertion, its simple, inexpensive and easily scalable synthesis route, its low toxicity, and its high working potential. It is known that the physiochemical properties of CuHCF can be modified by manipulating its synthesis parameters. However, the effect of these parameters on the material’s electrochemical performance and cycle life needs further investigation. Here, the structure and composition of CuHCF treated at different temperatures are studied through crystallographic, compositional, and thermogravimetric analyses. The resulting CuHCF powders were galvanostatically cycled to assess their electrochemical performance in relation to their annealing temperature. The results showed that the annealed CuHCF electrodes exhibited longer cycle life while maintaining a coulombic efficiency ≥ 99.5%. The longest cycle life was achieved by annealing the CuHCF electrodes at 100 °C.
Prediction of Cognitive Load from Electroencephalography Signals Using Long Short-Term Memory Network
Authors: Yoo Gilsang , Kim Hyeoncheol , Hong Sungdae
Published: March 2023

In recent years, the development of adaptive models to tailor instructional content to learners by measuring their cognitive load has become a topic of active research. Brain fog, also known as confusion, is a common cause of poor performance, and real-time detection of confusion is a challenging and important task for applications in online education and driver fatigue detection. In this study, we propose a deep learning method for cognitive load recognition based on electroencephalography (EEG) signals using a long short-term memory network (LSTM) with an attention mechanism. We obtained EEG signal data from a database of brainwave information and associated data on mental load. We evaluated the performance of the proposed LSTM technique in comparison with random forest, Adaptive Boosting (AdaBoost), support vector machine, eXtreme Gradient Boosting (XGBoost), and artificial neural network models. The experimental results demonstrated that the proposed approach had the highest accuracy of 87.1% compared to those of other algorithms, including random forest (64%), AdaBoost (64.31%), support vector machine (60.9%), XGBoost (67.3%), and artificial neural network models (71.4%). The results of this study support the development of a personalized adaptive learning system designed to measure and actively respond to learners’ cognitive load in real time using wireless portable EEG systems.
Dopamine Dynamics and Neurobiology of Non-Response to Antipsychotics, Relevance for Treatment Resistant Schizophrenia: A Systematic Review and Critical Appraisal
Authors: Iasevoli Felice , Avagliano Camilla , D’Ambrosio Luigi , Barone Annarita , Ciccarelli Mariateresa , De Simone Giuseppe , Mazza Benedetta , Vellucci Licia , de Bartolomeis Andrea
Published: March 2023

Treatment resistant schizophrenia (TRS) is characterized by a lack of, or suboptimal response to, antipsychotic agents. The biological underpinnings of this clinical condition are still scarcely understood. Since all antipsychotics block dopamine D2 receptors (D2R), dopamine-related mechanisms should be considered the main candidates in the neurobiology of antipsychotic non-response, although other neurotransmitter systems play a role. The aims of this review are: (i) to recapitulate and critically appraise the relevant literature on dopamine-related mechanisms of TRS; (ii) to discuss the methodological limitations of the studies so far conducted and delineate a theoretical framework on dopamine mechanisms of TRS; and (iii) to highlight future perspectives of research and unmet needs. Dopamine-related neurobiological mechanisms of TRS may be multiple and putatively subdivided into three biological points: (1) D2R-related, including increased D2R levels; increased density of D2Rs in the high-affinity state; aberrant D2R dimer or heteromer formation; imbalance between D2R short and long variants; extrastriatal D2Rs; (2) presynaptic dopamine, including low or normal dopamine synthesis and/or release compared to responder patients; and (3) exaggerated postsynaptic D2R-mediated neurotransmission. Future points to be addressed are: (i) a more neurobiologically-oriented phenotypic categorization of TRS; (ii) implementation of neurobiological studies by directly comparing treatment resistant vs. treatment responder patients; (iii) development of a reliable animal model of non-response to antipsychotics.
IFIT2 Depletion Promotes Cancer Stem Cell-like Phenotypes in Oral Cancer
Authors: Lai Kuo-Chu , Regmi Prabha , Liu Chung-Ji , Lo Jeng-Fan , Lee Te-Chang
Published: March 2023

(1) Background: Cancer stem cells (CSCs) are a small cell population associated with chemoresistance, metastasis and increased mortality rate in oral cancer. Interferon-induced proteins with tetratricopeptide repeats 2 (IFIT2) depletion results in epithelial to mesenchymal transition, invasion, metastasis, and chemoresistance in oral cancer. To date, no study has demonstrated the effect of IFIT2 depletion on the CSC-like phenotype in oral cancer cells. (2) Methods: Q-PCR, sphere formation, Hoechst 33,342 dye exclusion, immunofluorescence staining, and flow cytometry assays were performed to evaluate the expression of the CSC markers in IFIT2-depleted cells. A tumorigenicity assay was adopted to assess the tumor formation ability. Immunohistochemical staining was used to examine the protein levels of IFIT2 and CD24 in oral cancer patients. (3) Results: The cultured IFIT2 knockdown cells exhibited an overexpression of ABCG2 and CD44 and a downregulation of CD24 and gave rise to CSC-like phenotypes. Clinically, there was a positive correlation between IFIT2 and CD24 in the patients. IFIT2high/CD24high/CD44low expression profiles predicted a better prognosis in HNC, including oral cancer. The TNF-α blockade abolished the IFIT2 depletion-induced sphere formation, indicating that TNF-α may be involved in the CSC-like phenotypes in oral cancer. (4) Conclusions: The present study demonstrates that IFIT2 depletion promotes CSC-like phenotypes in oral cancer.
Direct Effects of Mifepristone on Mice Embryogenesis: An In Vitro Evaluation by Single-Embryo RNA Sequencing Analysis
Authors: Su Yu-Ting , Chen Jia-Shing , Lan Kuo-Chung , Lee Yung-Kuo , Chu Tian-Huei , Ho Yu-Cheng , Wu Cheng-Chun , Huang Fu-Jen
Published: March 2023

The clinical use of mifepristone for medical abortions has been established in 1987 in France and since 2000 in the United States. Mifepristone has a limited medical period that lasts <9 weeks of gestation, and the incidence of mifepristone treatment failure increases with gestation time. Mifepristone functions as an antagonist for progesterone and glucocorticoid receptors. Studies have confirmed that mifepristone treatments can directly contribute to endometrium disability by interfering with the endometrial receptivity of the embryo, thus causing decidual endometrial degeneration. However, whether mifepristone efficacy directly affects embryo survival and growth is still an open question. Some women choose to continue their pregnancy after mifepristone treatment fails, and some women express regret and seek medically unapproved mifepristone antagonization with high doses of progesterone. These unapproved treatments raise the potential risk of embryonic fatality and developmental anomalies. Accordingly, in the present study, we collected mouse blastocysts ex vivo and treated implanted blastocysts with mifepristone for 24 h. The embryos were further cultured to day 8 in vitro to finish their growth in the early somite stage, and the embryos were then collected for RNA sequencing (control n = 3, mifepristone n = 3). When we performed a gene set enrichment analysis, our data indicated that mifepristone treatment considerably altered the cellular pathways of embryos in terms of viability, proliferation, and development. The data indicated that mifepristone was involved in hallmark gene sets of protein secretion, mTORC1, fatty acid metabolism, IL-2-STAT5 signaling, adipogenesis, peroxisome, glycolysis, E2F targets, and heme metabolism. The data further revealed that mifepristone interfered with normal embryonic development. In sum, our data suggest that continuing a pregnancy after mifepristone treatment fails is inappropriate and infeasible. The results of our study reveal a high risk of fetus fatality and developmental problems when pregnancies are continued after mifepristone treatment fails.
Machine Learning Models to Forecast Outcomes of Pituitary Surgery: A Systematic Review in Quality of Reporting and Current Evidence
Authors: Rech Matheus M. , de Macedo Filho Leonardo , White Alexandra J. , Perez-Vega Carlos , Samson Susan L. , Chaichana Kaisorn L. , Olomu Osarenoma U. , Quinones-Hinojosa Alfredo , Almeida Joao Paulo
Published: March 2023

Background: The complex nature and heterogeneity involving pituitary surgery results have increased interest in machine learning (ML) applications for prediction of outcomes over the last decade. This study aims to systematically review the characteristics of ML models involving pituitary surgery outcome prediction and assess their reporting quality. Methods: We searched the PubMed, Scopus, and Web of Knowledge databases for publications on the use of ML to predict pituitary surgery outcomes. We used the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) to assess report quality. Our search strategy was based on the terms “artificial intelligence”, “machine learning”, and “pituitary”. Results: 20 studies were included in this review. The principal models reported in each article were post-surgical endocrine outcomes (n = 10), tumor management (n = 3), and intra- and postoperative complications (n = 7). Overall, the included studies adhered to a median of 65% (IQR = 60–72%) of TRIPOD criteria, ranging from 43% to 83%. The median reported AUC was 0.84 (IQR = 0.80–0.91). The most popular algorithms were support vector machine (n = 5) and random forest (n = 5). Only two studies reported external validation and adherence to any reporting guideline. Calibration methods were not reported in 15 studies. No model achieved the phase of actual clinical applicability. Conclusion: Applications of ML in the prediction of pituitary outcomes are still nascent, as evidenced by the lack of any model validated for clinical practice. Although studies have demonstrated promising results, greater transparency in model development and reporting is needed to enable their use in clinical practice. Further adherence to reporting guidelines can help increase AI’s real-world utility and improve clinical practice.
CDK4/6 Inhibitors—Overcoming Endocrine Resistance Is the Standard in Patients with Hormone Receptor-Positive Breast Cancer
Authors: Nabieva Naiba , Fasching Peter
Published: March 2023

Purpose of review: Tamoxifen and aromatase inhibitors can be considered as some of the first targeted therapies. For the past 30 years, they were the endocrine treatment standard in the advanced and early breast cancer setting. CDK4/6 inhibitors, however, are the first substances in almost two decades to broadly improve the therapeutic landscape of hormone receptor-positive breast cancer patients for the upcoming years. This review is designed to discuss the recent history, current role, future directions and opportunities of this substance class. Recent findings: The CDK4/6 inhibitors abemaciclib, dalpiciclib, palbociclib and ribociclib have all demonstrated a statistically significant improvement in progression-free survival in advanced disease. However, to date, abemaciclib and ribociclib are the only CDK4/6 inhibitors to have shown an improvement in overall survival in patients with metastatic breast cancer. Moreover, abemaciclib is the first CDK4/6 inhibitor to also reduce the risk of recurrence in those with early-stage disease. Further CDK inhibitors, treatment combinations with other drugs and different therapy sequences are in development. Summary: Achieving significant improvements in survival rates in the advanced and early breast cancer treatment setting, CDK4/6 inhibitors have set a new standard of care for patients with advanced breast cancer. It remains important to better understand resistance mechanisms to be able to develop novel substances and treatment sequences.
Young Adult German Breast Cancer Patients Participating in a Three-Week Inpatient Mother–Child Rehab Program Have High Needs for Supportive Care
Authors: Hammersen Friederike , Fischer Dorothea , Pursche Telja , Strobel Angelika M. , Katalinic Alexander , Labohm Louisa , Waldmann Annika
Published: March 2023

A known cut-off problem hampers the interpretation of quality of life (QOL) scores. The purpose of this study was to apply a novel approach for the EORTC QLQ-C30 instrument to identify the proportion of breast cancer (BC) patients in need of supportive care. Changes in QOL during the COVID-19 pandemic were evaluated, as well as changes over time (after treatment termination and up to 4 years later). Data were obtained from a cohort study on young adult BC patients with minor children participating in a mother–child rehab program. Cross-sectional QOL data were collected from 2015 to 2021 (baseline). Follow-up data were available for up to 4 years after diagnosis for a subgroup. The baseline cohort included 853 women (mean age 35 years). More than 50% had a need for supportive care. In the subgroup with follow-up, this proportion remained at a high level up to several years after diagnosis. During the COVID-19 pandemic, changes regarding the proportion with this need were not as high as expected—with the exception of changes on the QLQ-C30 scale ‘role functioning’ (+15%). Even several years after diagnosis, every second BC patient with minor children had a need for supportive care, which is much higher than previously found. Healthcare staff should be aware of this potential need and should address this issue.
Early Disturbance of Lymphatic Transport as a Risk Factor for the Development of Breast-Cancer-Related Lymphedema
Authors: Thomis Sarah , Devoogdt Nele , Bechter-Hugl Beate , Fourneau Inge
Published: March 2023

Introduction: Breast-cancer-related lymphedema (BCRL) is a frequently occurring and debilitating condition. When lymphedema is diagnosed late, treatment can be expected to be less effective. Lymphofluoroscopy can provide details about the superficial lymphatic architecture and can detect an early disturbance of lymphatic transport (i.e., dermal backflow) before the lymphedema is clinically visible. The main objective of this study is to investigate whether this early disturbance of lymphatic transport visualized by lymphofluoroscopy is a risk factor for the development of BCRL. Methodology: All patients scheduled for unilateral breast cancer surgery with axillary lymph node dissection or sentinel node biopsy were considered. Patients were assessed at baseline and 1, 3, 6, 9, 12, 18, 24 and 36 months postoperatively. During each visit, a clinical assessment was performed to determine the volume difference between both arms and hands (through circumference measurements and water displacement). Clinical BCRL was defined as a ≥5% increase in relative arm volume difference compared to the baseline value. Variables related to (1) the disturbance of lymphatic transport (through lymphofluoroscopy), (2) the demographics and general health of the patient and (3) the breast cancer and treatment of the patient were collected. Results: We included data of 118 patients in the present study. Thirty-eight patients (39.8%) developed BCRL. Early disturbance of lymphatic transport was identified as a risk factor for the development of clinical BCRL (HR 2.808). Breast-cancer- and treatment-related variables such as axillary lymph node dissection (ALND) (HR 15.127), tumor stage (HR 1.745), mastectomy (HR 0.186), number of positive lymph nodes (HR 1.121), number of removed lymph nodes (HR 1.055), radiotherapy of the axilla (HR 2.715), adjuvant taxanes (HR 3.220) and postsurgical complications (HR 2.590) were identified as significant risk factors for the development of BCRL. In the multivariate analysis, age and ALND were withheld as independent risk factors for the development of BCRL. Conclusion: Lymphofluoroscopy can identify an early disturbance of lymphatic transport after breast cancer treatment. Patients with an early disturbance of lymphatic transport are considered to be a high-risk group for the development of BCRL. This study also confirms that age and ALND are predictors for the development of BCRL. Therefore, a surveillance program of these patients with lymphofluoroscopy could be useful to identify lymphedema in subclinical stages.
An Image Generation Method of Unbalanced Ship Coating Defects Based on IGASEN-EMWGAN
Authors: Bu Henan , Hu Changzhou , Yuan Xin , Ji Xingyu , Lyu Hongyu , Zhou Honggen
Published: March 2023

During the process of ship coating, various defects will occur due to the improper operation by the workers, environmental changes, etc. The special characteristics of ship coating limit the amount of data and result in the problem of class imbalance, which is not conducive to ensuring the effectiveness of deep learning-based models. Therefore, a novel hybrid intelligent image generation algorithm called the IGASEN-EMWGAN model for ship painting defect images is proposed to tackle the aforementioned limitations in this paper. First, based on a subset of imbalanced ship painting defect image samples obtained by a bootstrap sampling algorithm, a batch of different base discriminators was trained independently with the algorithm parameter and sample perturbation method. Then, an improved genetic algorithm based on the simulated annealing algorithm is used to search for the optimal subset of base discriminators. Further, the IGASEN-EMWGAN model was constructed by fusing the base discriminators in this subset through a weighted integration strategy. Finally, the trained IGASEN-EMWGAN model is used to generate new defect images of the minority classes to obtain a balanced dataset of ship painting defects. The extensive experimental results are conducted on a real unbalanced ship coating defect database and show that, compared with the baselines, the values of the ID and FID scores are significantly improved by 4.92% and decreased by 7.29%, respectively, which prove the superior effectiveness of the proposed model in this paper.
Relation of Mean Platelet Volume (MPV) with Cancer: A Systematic Review with a Focus on Disease Outcome on Twelve Types of Cancer
Authors: Detopoulou Paraskevi , Panoutsopoulos George I. , Mantoglou Marina , Michailidis Periklis , Pantazi Ifigenia , Papadopoulos Spyros , Rojas Gil Andrea Paola
Published: March 2023

Inflammatory proteins activate platelets, which have been observed to be directly related to cancer progression and development. The aim of this systematic review is to investigate the possible association between Mean Platelet Volume (MPV) and cancer (diagnostic capacity of MPV, relation to survival, the severity of the disease, and metastasis). A literature review was performed in the online database PubMed and Google Scholar for the period of 2010–2022. In total, 83 studies including 21,034 participants with 12 different types of cancer (i.e., gastric cancer, colon cancer, esophageal squamous cell carcinoma, renal cancer, breast cancer, ovarian cancer, endometrial cancer, thyroid cancer, lung cancer, bladder cancer, gallbladder cancer, and multiple myeloma) were identified. The role of MPV has been extensively investigated in several types of cancer, such as gastric, colon, breast, and lung cancer, while few data exist for other types, such as renal, gallbladder cancer, and multiple myeloma. Most studies in gastric, breast, endometrium, thyroid, and lung cancer documented an elevated MPV in cancer patients. Data were less clear-cut for esophageal, ovarian, and colon cancer, while reduced MPV was observed in renal cell carcinoma and gallbladder cancer. Several studies on colon cancer (4 out of 6) and fewer on lung cancer (4 out of 10) indicated an unfavorable role of increased MPV regarding mortality. As far as other cancer types are concerned, fewer studies were conducted. MPV can be used as a potential biomarker in cancer diagnosis and could be a useful tool for the optimization of treatment strategies. Possible underlying mechanisms between cancer and MPV are discussed. However, further studies are needed to elucidate the exact role of MPV in cancer progression and metastasis.
Stochastic Thermodynamics of a Finite Quantum System Coupled to Two Heat Baths
Authors: Schmidt Heinz-Jürgen , Gemmer Jochen
Published: March 2023

We consider a situation where an N-level system (NLS) is coupled successively to two heat baths with different temperatures without being necessarily thermalized and approaches a steady state. For this situation we apply a general Jarzynski-type equation and conclude that heat and entropy is flowing from the hot bath to the cold one. The Clausius relation between increase of entropy and transfer of heat divided by a suitable temperature assumes the form of two inequalities. Our approach is illustrated by an analytical example. For the linear regime, i.e., for small temperature differences between the two heat baths, we derive an expression for the heat conduction coefficient.
Comparison of Kalman Filters for State Estimation Based on Computational Complexity of Li-Ion Cells
Authors: Khalid Areeb , Kashif Syed Abdul Rahman , Ain Noor Ul , Awais Muhammad , Ali Smieee Majid , Carreño Jorge El Mariachet , Vasquez Juan C. , Guerrero Josep M. , Khan Baseem
Published: March 2023

Over the last few decades, lithium-ion batteries have grown in importance for the use of many portable devices and vehicular applications. It has been seen that their life expectancy is much more effective if the required conditions are met. In one of the required conditions, accurately estimating the battery’s state of charge (SOC) is one of the important factors. The purpose of this research paper is to implement the probabilistic filter algorithms for SOC estimation; however, there are challenges associated with that. Generally, for the battery to be effective the Bayesian estimation algorithms are required, which are recursively updating the probability density function of the system states. To address the challenges associated with SOC estimation, the research paper goes further into the functions of the extended Kalman filter (EKF) and sigma point Kalman filter (SPKF). The function of both of these filters will be able to provide an accurate estimation. Further studies are required for these filters’ performance, robustness, and computational complexity. For example, some filters might be accurate, might not be robust, and/or not implementable on a simple microcontroller in a vehicle’s battery management system (BMS). A comparison is made between the EKF and SPKF by running simulations in MATLAB. It is found that the SPKF has an obvious advantage over the EKF in state estimation. Within the SPKF, the sub-filter, the central difference Kalman filter (CDKF), can be considered as an alternative to the EKF for state estimation in battery management systems for electric vehicles. However, there are implications to this which include the compromise of computational complexity in which a more sophisticated micro-controller is required.
Exploring Prognostic and Diagnostic Techniques for Jet Engine Health Monitoring: A Review of Degradation Mechanisms and Advanced Prediction Strategies
Authors: De Giorgi Maria Grazia , Menga Nicola , Ficarella Antonio
Published: March 2023

Maintenance is crucial for aircraft engines because of the demanding conditions to which they are exposed during operation. A proper maintenance plan is essential for ensuring safe flights and prolonging the life of the engines. It also plays a major role in managing costs for aeronautical companies. Various forms of degradation can affect different engine components. To optimize cost management, modern maintenance plans utilize diagnostic and prognostic techniques, such as Engine Health Monitoring (EHM), which assesses the health of the engine based on monitored parameters. In recent years, various EHM systems have been developed utilizing computational techniques. These algorithms are often enhanced by utilizing data reduction and noise filtering tools, which help to minimize computational time and efforts, and to improve performance by reducing noise from sensor data. This paper discusses the various mechanisms that lead to the degradation of aircraft engine components and the impact on engine performance. Additionally, it provides an overview of the most commonly used data reduction and diagnostic and prognostic techniques.
The Performance of a Thermal Protection System for the Accessories of a TBCC Engine
Authors: Lian Wenlei , Zhang Jinhua , Lin Dengke
Published: March 2023

A theoretical model for describing the heat transfer characteristics of a turbine-based combined cycle (TBCC) engine cabin was established in Matlab/Simulink to quickly predict the thermal protection performance for engine accessories. The model’s effectiveness was verified by comparing the numerical results with the experimental data. The effects of different heat insulation layer thicknesses and fuel temperatures on the thermal protection performance are discussed; based on these effects, the heat insulation layer of 5 mm and fuel of 353 K were chosen to design the thermal protection cases. Nineteen different thermal protection cases were proposed and evaluated by using the model. Two representative accessories were chosen for the evaluation of the thermal protection performance of these cases. For accessory 1 with an internal heat source of 1000 W and internal fuel access, the thermal protection effect of adding a heat insulation layer and ventilation was the best, which decreased the accessory temperature by 43 K. For accessory 2 without an internal heat source, the thermal protection effect of adding a heat insulation layer to the casing and fuel cooling was the most ideal, which decreased the accessory temperature by 190 K. In addition, a comprehensive assessment was made to compare the performances of thermal protection cases.
Saturation and Pressure Prediction for Multi-Layer Irregular Reservoirs with Variable Well Patterns
Authors: Wang Haochen , Ju Yafeng , Zhang Kai , Liu Chengcheng , Yin Hongwei , Wang Zhongzheng , Yu Zhigang , Qi Ji , Wang Yanzhong , Zhou Wenzheng
Published: March 2023

The well pattern and boundary shape of reservoirs determine the distribution of the remaining oil distribution to a large extent, especially for small-scale reservoir blocks. However, it is difficult to replicate experiences from other reservoirs directly to predict the remaining oil distribution because of the variety of irregular boundary shapes and corresponding well patterns. Meanwhile, the regular well pattern can hardly suit irregular boundary shapes. In this paper, we propose a well placement method for undeveloped irregular reservoirs and a multi-step prediction framework to predict both oil saturation and pressure fields for any reservoir shape and well pattern. To boost the physical information of input characteristics, a feature amplification approach based on physical formulae is initially presented. Then, 3D convolution technology is employed for the first time in 3D reservoir prediction to increase the spatial information in the vertical direction of the reservoir in the input. Moreover, to complete the two-field prediction, the concept of multi-task learning is adopted for the first time, improving the rationality of the forecast. Through the loss-based ablation test, we found that the operation we adopt will increase the accuracy of prediction to some extent. By testing on both manually designed and real irregular-shape reservoirs, our method is proven to be an accurate and fast oil saturation prediction method with its prediction loss less than 0.01 and calculation time less than 10 s in the future one year.
Simulation of Triple-Cation Perovskite Solar Cells: Key Design Factors for Efficiency Promotion
Authors: Alanazi Tarek I. , Eid Omer I.
Published: March 2023

Compositional engineering is considered one of the recent interesting techniques used in the field of perovskite solar cells (PSCs). In this method, more than one material was used in a specific cation in the perovskite structure. This work aims to simulate the cesium-containing triple-cation perovskite (TCP) via the SCAPS-1D simulation program with a device structure of ITO/SnO2/TCP/Spiro-OMeTAD/Au. First, we studied the effect of interface defects on the PCSs with respect to experimental results and found that when no interface defects occur, the power conversion efficiency (PCE) reaches a value of 22.16% which is higher than the reported PCE, implying that the fabricated cell suffers from the interface defects as a main effect on cell degradation. Incorporating interface defects into the simulation results in a very good match between the experimental and simulated data with a PCE of 17.92%. Further, to provide possible routes to enhance the performance of the solar cell under investigation, impacts of absorber layer thickness, conduction band offset (CBO), surface recombination velocity, and light intensity were explored. In addition, hole transport layer (HTL)-free design was investigated to alleviate the instability issues associated to the organic HTL, leading to a PCE of 18.28%, for a surface velocity of 104 cm/s, which is interestingly higher than the initial cell. The provided study reveals the critical role of interface defects and other key design factors and suggests potential solutions to alleviate the subsequent degradation mechanisms, thereby enhancing the overall cell performance.
Energy Hub Gas: A Modular Setup for the Evaluation of Local Flexibility and Renewable Energy Carriers Provision
Authors: Poppenborg Rafael , Chlosta Malte , Ruf Johannes , Hotz Christian , Düpmeier Clemens , Kolb Thomas , Hagenmeyer Veit
Published: March 2023

The ambitious targets for the reduction of Greenhouse Gas (GHG) emissions force the enhanced integration and installation of Renewable Energy Sources (RESs). Furthermore, the increased reliance of multiple sectors on electrical energy additionally challenges the electricity grid with high volatility from the demand side. In order to keep the transmission system operation stable and secure, the present approach adds local flexibility into the distribution system using the modular Energy Hub Gas (EHG) concept. For this concept, two different test cases are configured and evaluated. The two configured EHGs demonstrate the ability to provide flexibility and adaptability by reducing the difference between maximal and minimal load in the surrounding grid infrastructure by 30% in certain time periods. Furthermore, the average energy exchange is reduced by 8%. Therefore, by relieving the grid infrastructure in the local surroundings, the additional potential of RES is enabled and the curtailment of existing ones can be reduced.
Production of Sustainable Aviation Fuels from Lignocellulosic Residues in Brazil through Hydrothermal Liquefaction: Techno-Economic and Environmental Assessments
Authors: Deuber Raquel de Souza , Bressanin Jéssica Marcon , Fernandes Daniel Santos , Guimarães Henrique Real , Chagas Mateus Ferreira , Bonomi Antonio , Fregolente Leonardo Vasconcelos , Watanabe Marcos Djun Barbosa
Published: March 2023

Decarbonization of the aviation sector relies on deployment of sustainable aviation fuels (SAF) at commercial scale. Hydrothermal liquefaction (HTL) has been recognized as a promising technology to help supply the increasing projected SAF demand. High availability of agro-industrial residues, combined with a well-established biorefinery system, makes the sugarcane industry in Brazil a good option for HTL technology deployment. Moreover, challenges regarding the economic feasibility of SAF from HTL could be partially addressed by the RenovaBio policy, a market-driven incentive mechanism of carbon credits implemented in Brazil. This study investigated both the techno-economic and life cycle assessment of SAF production from sugarcane lignocellulosic residues, considering HTL integrated to a first-generation ethanol distillery and a HTL stand-alone facility. The evaluated scenarios showed great climate mitigation potential, reaching a reduction of up to 73–82% when compared to fossil jet fuel. The minimum fuel selling price of SAF at 15.4 USD/GJ indicated potential of economic competitiveness with fossil jet fuel in the best integrated scenario. The economic benefits obtained from carbon credits are not enough to enable feasibility of HTL in the stand-alone scenarios, even with carbon prices projected at 125 USD/tonne CO2-eq avoided.
Integrated Assessment of Economic Supply and Environmental Effects of Biomass Co-Firing in Coal Power Plants: A Case Study of Jiangsu, China
Authors: Wang Weiwei
Published: March 2023

The technical supply potential of biomass and the associated greenhouse gas (GHG) emissions are widely studied in the literature. However, relatively few studies have examined the role of biomass co-firing for future electricity in China by integratedly considering the economic supply potential and GHG effects. To fill this gap, we choose the Jiangsu Province in China as a case study and build up a partial equilibrium model with multiple agricultural commodities. Using this model combined with a life cycle assessment, we jointly determine the economic potential of the biomass supply for a biomass co-firing purpose and social benefits, including the agricultural producers’ surplus and GHG mitigation potential. The simulation incorporates the county-level biomass market of various crop residues as well as endogenous crop prices and transportation costs. We find that 0.7–12.5 M MT of residue-based biomass are economically viable for co-firing in coal-based power plants (up to 20%) at biomass prices between USD 50 and USD 100/MT. The net GHG savings achieved at these biomass prices are from 3.2 to 59 M MTCO2e. Our findings indicate that biomass co-firing with coal in power plants would be a feasible low-carbon energy transition pathway if the biomass price is above USD 50/MT. In addition to biomass prices, other factors such as crop yields, production costs of residues, and transportation costs are found to be impactful on the economic viability of biomass and GHG savings. Our results can inform policy to develop localized carbon reduction strategies in provinces with abundant biomass resources and a high share of coal-fired electricity.
Component-Oriented Modeling Method for Real-Time Simulation of Power Systems
Authors: Jin Zhao , Zhang Jie , Wang Shuyuan , Zhang Bingda
Published: March 2023

This paper proposes a component-oriented modeling method for power system simulation, which optimizes the modeling process of the FPGA-based real-time digital simulator (FRTDS) to enhance its computational efficiency. In this paper, a component modeling method for various types of elements in the power system is presented, which makes the modeling process in FRTDS more user-friendly and highly scalable. By applying the concepts of combination and reconstruction of components to electrical components, the component-oriented modeling method becomes better suited for combined elements with fixed connection modes and elements that require online model replacement in the power system. Utilizing the characteristics of component-oriented modeling, the variable declaration structure and node elimination strategy in the simulation script are optimized, enabling the simulation script to fit better with the hardware structure of FRTDS. Additionally, a substation is simulated in FRTDS with a simulation step size of 50 µs, thus verifying the correctness of the component-oriented modeling method and its ability to improve the computational power of FRTDS.
Forecasting Energy Recovery from Municipal Waste in a Closed-Loop Economy
Authors: Marciniuk-Kluska Anna , Kluska Mariusz
Published: March 2023

Tackling climate change, implementing the principles of sustainable development and a closed-loop economy, and creating an economically and environmentally efficient waste management system are the most serious environmental and economic challenges today. One of the biggest problems with waste is that it causes water, soil, and air pollution. The combination of precipitation and septic processes produces leachates containing heavy metals and acids, which negatively affect surface and groundwater, changing their composition and pH, among other things. According to the Polish waste database, there are more than 2500 waste incineration plants operating worldwide, including more than 500 in Europe, while there are 8 in Poland. The concept of a closed-loop economy is based on the rational use of resources, i.e., less consumption of raw materials and energy by creating a closed loop of processes in which waste becomes raw materials in subsequent production stages. The aim of this study was to develop forecasts of electricity recovery from municipal waste using a prediction method based on an approximating function. The predictions made show that in 2023, the forecast of energy recovery from biodegradable municipal waste will be 6566 TJ. Projections of energy recovery from municipal waste for the future are steadily increasing, with planned recovery in 2030 at 9943 TJ.
Biocontrol Potential of Entomopathogenic Nematodes against Odontotermes obesus (Blattodea: Termitidae) under Laboratory and Field Conditions
Authors: Aslam Asad , Chi De-Fu , Abbasi Asim , Arshad Muhammad
Published: March 2023

Odontotermes obesus (Blattodea: Termitidae) is a prevalent subterranean wood-eating termite species that causes damage to mature trees, saplings and seedlings. The efficacy of most synthetic insecticides against this notorious pest has been compromised primarily because of its enigmatic feeding behavior and development of resistance to a number of insecticides. It has therefore become necessary to explore other alternative biologically sound and low-impact termite control methods, particularly for use in forests. Hence, this study was designed to verify the efficacy of different indigenous EPN isolates (Steinernema carpocapsae, Heterorhabditis bacteriophora and Heterorhabditis indica) against workers of Odontotermes obesus. The pathogenicity of each nematode isolate was assessed in laboratory conditions using filter paper and sawdust bioassay at two different temperatures (16 ± 1 and 26 ± 1 °C). Additionally, the efficacy of the nematode species was also assessed in field conditions. The results of the experiments revealed that the mortality of termite workers was more pronounced in sawdust bioassay in comparison with filter paper bioassay at both the tested temperatures. The mortality response in both bioassays was more pronounced at the higher temperature. A significantly higher mortality was recorded at both tested temperatures for S. carpocapsae followed by H. bacteriophora and H. indica. A dose-dependent positive mortality response was also recorded at both tested temperatures. Similar to the laboratory trials, the field applications of the three tested nematode species showed that maximum mortality was recorded for S. carpocapsae followed by H. bacteriophora and H. indica. It was therefore concluded that indigenous EPNs can provide more effective control of termites, possibly because of their direct interaction with pest species in the soil and the possibility of causing secondary infection through infected cadavers.
The Trade-Offs and Synergies of Ecosystem Services in Pinus massoniana Lamb. Plantations in Guangxi, China
Authors: Mo Rongjian , Wang Yongqi , Mo Yanhua , Li Lu , Ma Jiangming
Published: March 2023

A scientific understanding of the synergistic and trade-off relationships among ecosystem services (ESs) is essential for maintaining the structure, function, and health of plantation forest ecosystems. This understanding facilitates effective ecosystem management practices, and helps identify the types, intensities, and spatial and temporal distribution characteristics of interactions among ESs, which is critical for regional development planning, ecological supplementation, and the maximization of economic benefits. In this study, we used correlation analysis, bivariate spatial autocorrelation, and hot spot analysis to comprehensively analyze the synergistic and trade-off relationships between ESs in Pinus massoniana (PM) plantations in Guangxi Paiyang Forest Farm from 2009 to 2018, across both time and space. The study showed that the ESs in PM plantations in Guangxi Paiyang Forest Farm maintained significant positive correlation (synergy), with a mutually reinforcing relationship among services. Notably, the regulating services shifted from weak synergy to weak trade-off relationships over time. From the bivariate spatial autocorrelation analysis, it is clear that the overall trade-off synergistic relationship among the four ESs is basically consistent with the correlation analysis results. From the distribution of multiple ES hot spots, we determined that the number of small groups that can provide three to four service hot spots in Guangxi Paiyangshan Forest Farm is greater. The spatial distribution of cold–hot spots of various ESs varied, and the distribution of cold–hot spots of supply services and regulation services of carbon sequestration and oxygen release was similar.