bluuebunny/crossref_metadata_2025 huggingface dataset:
FLT3-ITD Measurable Residual Disease Monitoring in Acute Myeloid Leukemia Using Next-Generation Sequencing
Authors: Lee Jong-Mi , Park Silvia , Hwang Insik , Kang Dain , Cho Byung Sik , Kim Hee-Je , Ahn Ari , Kim Myungshin , Kim Yonggoo
Published: December 2022

The in-frame internal tandem duplication (ITD) of the FMS-like tyrosine kinase 3 (FLT3) gene is an important negative prognostic marker in acute myeloid leukemia (AML). FLT3-ITD monitoring is essential for patients at relapse or those receiving FLT3-targeted therapies. Fragment analysis (FA) is commonly used to detect and quantify FLT3-ITDs; however, detecting low-burden FLT3-ITDs after a treatment is challenging. We, therefore, developed a customized, next-generation sequencing (NGS)-based FLT3-ITD assay that includes a new ITD-tracing algorithm, “SEED”, optimized for measurable residual disease (MRD) monitoring. NGS-SEED showed an enhanced sensitivity (0.001%) and has a superior performance over conventional fragment analysis. We further investigated the prognostic impact of MRD analyzed by NGS-SEED in AML patients who underwent allogeneic hematopoietic stem cell transplantation (HSCT). Our assay showed that the MRD assessed before and after HSCT were significantly associated with a risk of relapse and a poor overall survival, respectively, in a time-dependent analysis. Thus, this report highlighted the prognostic value of serial MRD monitoring using a sensitive method in a clinical setting of AML patients with FLT3-ITD.
The Prognostic Role of True Radical Resection in Perihilar Cholangiocarcinoma after Improved Evaluation of Radial Margin Status
Authors: De Bellis Mario , Mastrosimini Maria Gaia , Conci Simone , Pecori Sara , Campagnaro Tommaso , Castelli Claudia , Capelli Paola , Scarpa Aldo , Guglielmi Alfredo , Ruzzenente Andrea
Published: December 2022

Background: The evaluation of surgical margins in resected perihilar cholangiocarcinoma (PHCC) remains a challenging issue. Both ductal (DM) and radial margin (RM) should be considered to define true radical resections (R0). Although DM status is routinely described in pathological reports, RM status is often overlooked. Therefore, the frequency of true R0 and its impact on survival might be biased. Objective: To improve the evaluation of RM status and investigate the impact of true R0 on survival. Methods: From 2014 to 2020, 90 patients underwent curative surgery for PHCC at Verona University Hospital, Verona, Italy. Both DM (proximal and distal biliary margin) and RM (hepatic, periductal, and vascular margin) status were evaluated by expert hepatobiliary pathologists. Patients with lymph-node metastases or positive surgical margins (R1) were candidates for adjuvant treatment. Clinicopathological and survival data were retrieved from an institutional database. Results: True R0 were 46% (41) and overall R1 were 54% (49). RM positivity resulted in being higher than DM positivity (48% versus 27%). Overall survival was better in patients with true R0 than in patients with R1 (median survival time: 53 vs. 28 months; p = 0.016). Likewise, the best recurrence-free survival was observed in R0 compared with R1 (median survival time: 32 vs. 15 months; p = 0.006). Multivariable analysis identified residual disease status as an independent prognostic factor of both OS (p = 0.009, HR = 2.68, 95% CI = 1.27–5.63) and RFS (p = 0.009, HR = 2.14, 95% CI = 1.20–3.83). Conclusion: Excellent survival was observed in true R0 patients. The improved evaluation of RM status is mandatory to properly stratify prognosis and select patients for adjuvant treatment.
Co-Targeting the EGFR and PI3K/Akt Pathway to Overcome Therapeutic Resistance in Head and Neck Squamous Cell Carcinoma: What about Autophagy?
Authors: Zaryouh Hannah , Van Loenhout Jinthe , Peeters Marc , Vermorken Jan Baptist , Lardon Filip , Wouters An
Published: December 2022

Resistance to EGFR-targeted therapy is a major obstacle on the road to effective treatment options for head and neck cancers. During the search for underlying mechanisms and regulators of this resistance, there were several indications that EGFR-targeted therapy resistance is (partially) mediated by aberrant signaling of the PI3K/Akt pathway. Genomic alterations in and/or overexpression of major components of the PI3K/Akt pathway are common in HNSCC tumors. Therefore, downstream effectors of the PI3K/Akt pathway serve as promising targets in the search for novel therapeutic strategies overcoming resistance to EGFR inhibitors. As both the EGFR/Ras/Raf/MAPK and the PI3K/Akt pathway are involved in autophagy, combinations of EGFR and PI3K/Akt pathway inhibitors can induce an autophagic response in tumor cells. This activation of autophagy can be seen as a “double-edge sword”, depending on the cellular context. Autophagy is largely known as a cytoprotective mechanism, but it can also be a mechanism of programmed (autophagic) cell death. The activation of autophagy during anti-cancer treatment is, therefore, not necessarily a bad sign. However, in HNSCC, the role of therapy-induced autophagy as an anti-tumor mechanism is still largely unclear. Further research is warranted to understand the potential of combination treatments targeting both the EGFR and PI3K/Akt pathway.
Lipid-Nanoparticle-Mediated Delivery of Docetaxel Prodrug for Exploiting Full Potential of Gold Nanoparticles in the Treatment of Pancreatic Cancer
Authors: Alhussan Abdulaziz , Jackson Nolan , Eaton Sarah , Santos Nancy Dos , Barta Ingrid , Zaifman Josh , Chen Sam , Tam Yuen Yi C. , Krishnan Sunil , Chithrani Devika B.
Published: December 2022

Current chemoradiation therapy suffers from normal tissue toxicity. Thus, we are proposing incorporating gold nanoparticles (GNPs) and docetaxel (DTX), as they have shown very promising synergetic radiosensitization effects. Here, we explored the effect of a DTX prodrug encapsulated in lipid nanoparticles (LNPDTX-P) on GNP uptake in pancreatic cancer models in vitro and in vivo. For the in vitro experiment, a pancreatic cancer cell line, MIA PaCa-2, was cultured and dosed with 1 nM GNPs and 45 nM free DTX or an equivalent dose of LNPDTX-P. For the in vivo experiment, MIA PaCa-2 cells were implanted subcutaneously in NRG mice, and the mice were dosed with 2 mg/kg of GNPs and 6 mg/kg of DTX or an equivalent dose of LNPDTX-P. The results show that LNPDTX-P-treated tumour samples had double the amount GNPs compared to control samples, both in vitro and in vivo. The results are very promising, as LNPDTX-P have superior targeting of tumour tissues compared to free DTX due to their nanosize and their ability to be functionalized. Because of their minimal toxicity to normal tissues, both GNPs and LNPDTX-P could be ideal radiosensitization candidates in radiotherapy and would produce very promising synergistic therapeutic outcomes.
Accurate Traceability of Stable C, H, O, N Isotope Ratios and Multi-Element Analysis Combined with Chemometrics for Chrysanthemi Flos ‘Hangbaiju’ from Different Origins
Authors: Bai Xiuyun , Chen Hengye , Long Wanjun , Lan Wei , Wang Siyu , Lei Guanghua , Guan Yuting , Yang Jian , Fu Haiyan
Published: December 2022

Chrysanthemi Flos ‘Hangbaiju’ (HBJ) is a common Chinese medicinal material with the same origin as the medicinal and edible cognate plant in China, whose quality is seriously affected by the place of origin. In this study, four stable isotope ratios (δ15N, δ2H, δ13C, and δ18O) and 44 elements were detected and analyzed in 191 HBJ flower samples from six locations in China to trace the origin of HBJ. An ANOVA analysis of δ15N, δ2H, δ13C, and δ18O values, as well as milti-elements, showed that there were significant differences among the six places of origin. Partial least squares discriminant analysis (PLSDA) and one-class partial least squares discriminant analysis (OPLS-DA) models were established to trace the origin of HBJ from these six locations. The results showed that the classification effect of the PLSDA model is poor; however, the established OPLS-DA model can distinguish between products of national geographic origin (Tongxiang City, Zhejiang Province, China) and samples from other origins, among which Ni, Mo, δ13C, Cu, and Ce elements (VIP > 1) contribute the most to this classification. Therefore, this study provides a new method for tracing the origins of HBJ, which is of great significance for the protection of origin labeling of products.
Prediction of Slip Velocity at the Interface of Open-Cell Metal Foam Using 3D Printed Foams
Authors: Mustapha Khairul Azhar , Shikh Anuar Fadhilah , Mohd Saat Fatimah Al-Zahrah
Published: December 2022

An open-cell metal foam gains a lot of interest from researchers due to its unique porous structure, which provides high surface area and good tortuosity, as well as being lightweight. However, the same structure also induces a massive pressure drop which requires an optimum design to suit applications, for example, a partially filled setup or staggered design. Thus, better attention to the slip velocity at the interface between the porous structure and non-porous region is required to maximize its potential, especially in thermal fluid applications. This study proposed a slip velocity model of an open-cell metal foam by using a reverse engineering method and 3D printing technology. A series of experiments and a dimensionless analysis using the Buckingham-Pi theorem were used to compute the slip velocity model. Results show that the pressure drop increases with decreasing pore size. However, the blockage ratio effects would be more significant on the pressure drop with foams of smaller pore sizes. The proposed slip velocity model for an open-cell metal foam agrees with the experimental data, where the predicted values fall within measurement uncertainty.
Rosmarinic Acid Multifunctional Sunscreen: Comet Assay and In Vivo Establishment of Cutaneous Attributes
Authors: Cândido Thalita Marcílio , Ariede Maíra Bueno , Pinto Claudinéia Aparecida Sales de Oliveira , Lima Fabiana Vieira , Magalhães Wagner Vidal , Pedro Natália Mencacci Esteves , Padovani Giovana , Sufi Bianca da Silva , Rijo Patrícia , Velasco Maria Valéria Robles , Rosado Catarina , Baby André Rolim
Published: December 2022

The skin acts as a protective barrier, guarding the body against microorganisms, chemicals, and several environmental factors. Accordingly, this all-important organ must be kept healthy to maintain its optimal functionality. One approach to maintain skin health is the application of multifunction bioactive sunscreens containing antioxidant molecule(s). Rosmarinic acid (RA), a phenolic compound, is known for its antioxidant activity. Herein, the safety and efficacy of a multifunction prototype sunscreen were investigated, aiming to evaluate the performance of this polyphenol with two known and widely used UV filters (bemotrizinol and octyl p-methoxycinnamate). Samples protected the DNA fragmentation compared to UV control, by the comet assay, and showed good skin compatibility in subjects. Formulations F1 and F3 were able to increase skin hydration, and, possibly, the RA interfered with this attribute. An increase in transepidermal water loss was observed for formulations F1, F2, and F4, which may be related to the vehicle, containing the RA or not. No decreases were observed in the inflammatory reaction caused by the ethyl nicotinate with any of the samples. As a perspective, we suggest trials with a greater number of subjects or protocol modifications. Altering the vehicle qualitative and quantitative composition is also a pertinent perspective.
An Overview of Iron Oxide (Fe3O4) Nanoparticles: From Synthetic Strategies, Characterization to Antibacterial and Anticancer Applications
Authors: Rukhsar Muhammad , Ahmad Zubair , Rauf Abdur , Zeb Hassan , Ur-Rehman Mujeeb , Hemeg Hassan A.
Published: December 2022

Magnetic nanoparticles have been discovered to be promising materials for various biomedical applications; for example, they have been used for cancer detection, screening, and chemotherapy studies during the last few decades. Likewise, magnetic nanoparticles have significant antibacterial properties, and similarly, they can be applied for magnetic resonance imaging purposes. These sensors are meant to detect certain biomarkers, which are substances that can be linked to the beginning or progression of cancer both during and after therapy. Magnetic nanoparticles have several unique properties that are being employed widely in cancer therapy as drug delivery agents to precisely target the targeted spot using an external magnetic field in vivo. Magnetic resonance imaging can also be used in conjunction with antineoplastic drug treatment personalized to the individual. We have presented an overview of the different applications of magnetic nanoparticles as well as current breakthroughs in their development as antibacterial and cancer therapies in this review. In addition, the cancer targeting, possible toxicity, and degradability of these nanomaterials are briefly discussed.
Contextual Features and Information Bottleneck-Based Multi-Input Network for Breast Cancer Classification from Contrast-Enhanced Spectral Mammography
Authors: Li Xinmeng , Cui Jia , Song Jingqi , Jia Mingyu , Zou Zhenxing , Ding Guocheng , Zheng Yuanjie
Published: December 2022

In computer-aided diagnosis methods for breast cancer, deep learning has been shown to be an effective method to distinguish whether lesions are present in tissues. However, traditional methods only classify masses as benign or malignant, according to their presence or absence, without considering the contextual features between them and their adjacent tissues. Furthermore, for contrast-enhanced spectral mammography, the existing studies have only performed feature extraction on a single image per breast. In this paper, we propose a multi-input deep learning network for automatic breast cancer classification. Specifically, we simultaneously input four images of each breast with different feature information into the network. Then, we processed the feature maps in both horizontal and vertical directions, preserving the pixel-level contextual information within the neighborhood of the tumor during the pooling operation. Furthermore, we designed a novel loss function according to the information bottleneck theory to optimize our multi-input network and ensure that the common information in the multiple input images could be fully utilized. Our experiments on 488 images (256 benign and 232 malignant images) from 122 patients show that the method’s accuracy, precision, sensitivity, specificity, and f1-score values are 0.8806, 0.8803, 0.8810, 0.8801, and 0.8806, respectively. The qualitative, quantitative, and ablation experiment results show that our method significantly improves the accuracy of breast cancer classification and reduces the false positive rate of diagnosis. It can reduce misdiagnosis rates and unnecessary biopsies, helping doctors determine accurate clinical diagnoses of breast cancer from multiple CESM images.
Circulating Biomarkers for Laboratory Diagnostics of Atherosclerosis—Literature Review
Authors: Bordeianu Gabriela , Mitu Ivona , Stanescu Raluca Stefania , Ciobanu Corina Paraschiva , Petrescu-Danila Elena , Marculescu Afrodita Doina , Dimitriu Daniela Cristina
Published: December 2022

Atherosclerosis is still considered a disease burden with long-term damaging processes towards the cardiovascular system. Evaluation of atherosclerotic stages requires the use of independent markers such as those already considered traditional, that remain the main therapeutic target for patients with atherosclerosis, together with emerging biomarkers. The challenge is finding models of predictive markers that are particularly tailored to detect and evaluate the evolution of incipient vascular lesions. Important advances have been made in this field, resulting in a more comprehensible and stronger linkage between the lipidic profile and the continuous inflammatory process. In this paper, we analysed the most recent data from the literature studying the molecular mechanisms of biomarkers and their involvement in the cascade of events that occur in the pathophysiology of atherosclerosis.
Hidden Hippos: Using Photogrammetry and Multiple Imputation to Determine the Age, Sex, and Body Condition of an Animal Often Partially Submerged
Authors: Inman Victoria L. , Leggett Keith E. A.
Published: December 2022

Demographic Information on threatened species is important to plan conservation actions. Due to their aquatic lifestyle, the subtle nature of hippo sexual dimorphism, and their occurrence in inaccessible areas, it is difficult to visually determine hippo ages and sexes. Previously, hippo body lengths have been measured from drone images and used to estimate age. However, due to hippos’ propensity to be partially submerged, it is often difficult to obtain the required measurements. We used the novel technique of multiple imputation to estimate missing body measurements. Further, we explored if male and female hippos could be differentiated in drone images based on body proportions, also examining body condition indices and how these varied seasonally. Multiple imputation increased the number of hippos that we aged threefold, and the body lengths we obtained fell within the range provided in literature, supporting their validity. We provide one of the first age structure breakdowns of a hippo population not from culled hippos. Accounting for overall size, males had wider necks and snouts than females. Hippo body condition varied seasonally, indicating responses to resources and reproduction. We provide a new technique and demonstrate the utility of drones to determine age and sex structures of hippo populations.
Universal Behavior of the Coulomb-Coupled Fermionic Thermal Diode
Authors: Ghosh Shuvadip , Gupt Nikhil , Ghosh Arnab
Published: December 2022

We propose a minimal model of a Coulomb-coupled fermionic quantum dot thermal diode that can act as an efficient thermal switch and exhibit complete rectification behavior, even in the presence of a small temperature gradient. Using two well-defined dimensionless system parameters, universal characteristics of the optimal heat current conditions are identified. It is shown to be independent of any system parameter and is obtained only at the mean transitions point “−0.5”, associated with the equilibrium distribution of the two fermionic reservoirs, tacitly referred to as “universal magic mean”.
Performance Evaluation of Complex Equipment Considering Resume Information
Authors: Zhou Xiangyi , Zhou Zhijie , Hu Guanyu , Han Xiaoxia , Chen Leiyu
Published: December 2022

It is of great significance to obtain the performance state of complex equipment to protect equipment and maintain its normal operation. The majority of the performance evaluation methods are based on test data, but resume information is not considered. With its wide applicability and completeness, the resume information can be used in the comprehensive evaluation of equipment in various non-testing situations. By incorporating resume information into the performance evaluation of complex equipment, the flexible use of test data and resume information can result in a more comprehensive and accurate evaluation. Therefore, this paper focuses on the evaluation method of complex equipment performance based on evidential reasoning (ER) considering resume information. In order to unify the test data and resume information in the same framework, a novel method is proposed to transform them into the ER-based performance evaluation. On this basis, according to the index types, different reliability calculation methods are put forward, with one being based on the first-order fitting coefficient of variation, and the other being based on average time to failure; the index weight is analyzed based on the method of expert weight construction. Then, the transformed information with reliability and weight are fused by the ER rule. Finally, a performance evaluation case of a certain inertial measurement unit (IMU) is conducted to verify the effectiveness of the proposed method.
Classroom-Integrated Movement and Music Interventions and Children’s Ability to Recognize Social Interaction Based on Body Motion
Authors: Ginman Karolina , Anttila Eeva , Juntunen Marja-Leena , Tiippana Kaisa
Published: December 2022

Music and movement activities have been found to be beneficial for learning in childhood. The current study was part of the Arts@School project examining the effect of classroom-integrated arts-based interventions (music, movement, music-movement) on various student outcomes. The outcome of interest in the current report is the ability to recognize social interaction, which is one aspect of social cognition, an important but often ignored factor contributing to well-being and learning. The ability to recognize social interaction was studied using a test with two human figures either interacting with each other or moving separately. Children aged 10–11 completed the test pre and post intervention. The intervention groups and an inactive control group were four classes in a school. The interventions were delivered by teachers. The music intervention included listening, singing, and joint music making. The movement intervention was based on a creative dance approach and contained developmental movement patterns. The music-movement intervention focused on bodily experiences arising through activities combining music and movement. All intervention groups improved at the test, whereas the difference between the pre and post measurement did not reach significance in controls. This trend suggests that music and movement interventions integrated in the school learning environment may support children’s ability to interpret body motion, an important aspect of social interaction.
Low-Resource Malware Family Detection by Cross-Family Knowledge Transfer
Authors: Lin Yan , Xu Guoai , Du  Chunlai , Xu  Guosheng , Liu  Shucen
Published: December 2022

Low-resource malware families are highly susceptible to being overlooked when using machine learning models or deep learning models for automated detection because of the small amount of data samples. When we target to train a classifier for a low-resource malware family, the training data using the family itself is not sufficient to train a good classifier. In this work, we study the relationship between different malware families and improve the performance of the malware detection model based on machine learning method in low-resource malware family detection. First, we propose an empirical supportive score to measure the transfer quality and find that transferring performance varies a lot between different malware families. Second, we propose a Sequential Family Selection (SFS) algorithm to select multiple families as the training data. With SFS, we only transfer knowledge from several supportive families to target low-resource families. We conduct experiments on 16 families and 4 malware detection models, the results show that our model could outperform best baselines by 2.29% on average and our algorithm achieves 14.16% improvement in accuracy at the highest. Third, we study the transferred knowledge and find that our algorithm could capture the common characteristics between different malware families by proposing a supportive score and achieve good detection performance in the low-resource malware family. Our algorithm could also be applicable to image detection and signal detection.
Fault Estimation of Rack-Driving Motor in Electrical Power Steering System Using an Artificial Neural Network Observer
Authors: Kim Seulgi , Jung Dae-Yi
Published: December 2022

In this paper, we present the fault estimation of a motor in rack-type electrical power steering (R-EPS) system using an artificial neural network (ANN) observer and the comparison study of estimation performance between ANN observer and model-based ones. For various amplitudes and frequencies of fault, it is not easy to obtain the accurate fault estimation using the model-based observers inherently possessing the accumulated errors and disturbance effect. Such model-based methods often result in undesired consequences; hence, this study employed the “model-free” ANN observer, without using any dynamics and parameters of a motor, to accomplish the better outcomes. Furthermore, the advantages of ANN observer for the fault estimation of the motor have been clearly investigated under several control/fault scenarios, and the effectiveness of proposed work has been validated through an actual experimental study. It is found that the performance of model-based approaches is degraded when the frequencies and amplitudes of fault and control scenarios are changed, but the ANN observer guaranteed performance that was almost the same regardless of fault and control scenarios. Notably, ANN observers showed 84% to 95% of estimation accuracy with almost no delay between estimates and actual faults while model-based approaches did 68% to 86% accuracy along with noticeable delay.
Prediction of Critical Filling of a Storage Area Network by Machine Learning Methods
Authors: Masich Igor S. , Tynchenko Vadim S. , Nelyub Vladimir A. , Bukhtoyarov Vladimir V. , Kurashkin Sergei O. , Gantimurov Andrei P. , Borodulin Aleksey S.
Published: December 2022

The introduction of digital technologies into the activities of companies is based on software and hardware systems, which must function reliably and without interruption. The forecasting of the completion of storage area networks (SAN) is an essential tool for ensuring the smooth operation of such systems. The aim of this study is to develop a system of the modelling and simulation of the further loading of SAN on previously observed load measurements. The system is based on machine learning applied to the load prediction problem. Its novelty relates to the method used for forming input attributes to solve the machine learning problem. The proposed method is based on the aggregation of data on observed loading measurements and the formalization of the problem in the form of a regression analysis problem. The artificial dataset, synthesized stochastically according to the given parameter intervals and simulating SAN behavior, allowed for more extensive experimentation. The most effective algorithm is CatBoost (gradient boosting on decision trees), which surpasses other regression analysis algorithms in terms of R2 scores and MAE. The selection of the most significant features allows for the simplification of the prediction model with virtually no loss of accuracy, thereby reducing the number of confessions used. The experiments show that the proposed prediction model is adequate to the situation under consideration and allows for the prediction of the SAN load for the planning period under review with an R2 value greater than 0.9. The model has been validated on a series of real data on SAN.
A 5.42~6.28 GHz Type-II PLL with Dead-Zone Programmability and Charge Pump Mismatch Trimming
Authors: Kang Li , Lv Juncai , Cheng Xu
Published: December 2022

This paper proposed a 5.42~6.28 GHz type-II phase locked loop (PLL) for the sake of both loop filter switching capability and extensive programmability. An on-chip loop filter is used in conjunction with off-chip one to form a switching filter pair for diverse application scenarios. In order to strike a balance between dead-zone elimination and noise contribution minimization, a 3-bit programmable reset time ranging from 25 ps to 200 ps with a step of 25 ps is brought into PFD (phase frequency detector) design while CP (charge pump) current is programmable from 200 μA to 900 μA with a 100 μA/step digital control. Power management units (PMU) including bandgap and low dropout regulators (LDO) are integrated on-chip with resistor string trimming which effectively counteracts fabrication variations. In addition, a piecewise linear VCO with 3-bit control is designed with a fully digital 6-bit multi-modulus divider (MMD) chain cascaded. The proposed PLL is implemented in a 40-nm bulk CMOS process and the power consumption is 8 mA@1.2 V, in which around 5 mA@1.2 V is consumed by output buffers. The fabricated PLL chip achieves a frequency tuning range of 5.42~6.28 GHz, a phase noise ranging from −107.2~−110.4 dBc/Hz@1 MHz offset from carrier, a reference spur of lower than −70 dBc when on-chip active loop filter bandwidth is set to be around 500 KHz. Its FoM is approximately −176.98~−180.18 dBc/Hz while FoMT is approximately −180.32~−183.52 dBc/Hz@1 MHz offset from carrier. Its most specifications are comparable to or better than most existing literature.
Discharge Characteristics and System Performance of the Ablative Pulsed Plasma Thruster with Different Structural Parameters
Authors: Zhang Rui , Tian Zhiqiang , Xi Wenxiong , He Dongjing
Published: December 2022

Under the given initial discharge energy level, altering the electrode structural parameters of the Ablative Pulse Plasma Thruster (APPT) is an effective way to improve the performance of the thruster. The purpose of this study is to reveal the underlying mechanism of the effect of changing the electrode structure parameters on the performance of the APPT system and to offer targeted support for researchers to optimize the design of APPT structure. With rectangular and tongue-shaped electrode configurations at various electrode flare angles, electrode lengths, and electrode spacings, the discharge characteristics, propellant ablation characteristics, and thruster performance of the APPT are systematically investigated. The underlying mechanism of how changing the electrode’s configuration parameter affects the performance of the thruster is identified by fitting and predicting the parameters of the APPT discharge circuit and system performance under various operating conditions. The results show that using tongue-shaped electrodes is more effective than using rectangular electrodes in terms of enhancing the inductive gradient of the electrodes, transferring more energy to the discharge channel, and increasing the squared integral value of the discharge current. As a result, the tongue-shaped electrode APPT performs better than the APPT with rectangular electrodes, as a consequence. The thruster’s performance can be enhanced for the same electrode configuration by increasing the electrode flare angle within a certain angle range; however, the improvement is extremely limited. Additionally, in the case of small electrode spacing, increasing the electrode flare angle can enhance the thruster’s performance more effectively.
Biofuel Production from Seaweeds: A Comprehensive Review
Authors: Zhao Yiru , Bourgougnon Nathalie , Lanoisellé Jean-Louis , Lendormi Thomas
Published: December 2022

Seaweeds represent a promising and sustainable feedstock for biofuel production which raises increasing research interests. Their high availability, easy fermentable composition, and good degradation potential make them a suitable candidate for alternating fossil fuels as an advantageous energy resource. This comprehensive review aims to summarize and discuss data from the literature on the biochemical composition of seaweeds and its potential for biomethane and biohydrogen production, as well as to investigate the effect of the common pretreatment methods. Satisfactory yields comparable to terrestrial biomass could be obtained through anaerobic digestion; concerning dark fermentation, the challenge remains to better define the operating conditions allowing a stable production of biohydrogen. Finally, we propose a potential energy production scheme with the seaweed found by the Caribbean Islands of Guadeloupe and Martinique, as well as current techno-economic challenges and future prospects. An annual energy potential of 66 GWh could be attained via a two-stage biohythane production process, this tends to be promising in terms of energetic valorization and coastal management.
Machine Learning Based Protection Scheme for Low Voltage AC Microgrids
Authors: Uzair Muhammad , Eskandari Mohsen , Li Li , Zhu Jianguo
Published: December 2022

The microgrid (MG) is a popular concept to handle the high penetration of distributed energy resources, such as renewable and energy storage systems, into electric grids. However, the integration of inverter-interfaced distributed generation units (IIDGs) imposes control and protection challenges. Fault identification, classification and isolation are major concerns with IIDGs-based active MGs where IIDGs reveal arbitrary impedance and thus different fault characteristics. Moreover, bidirectional complex power flow creates extra difficulties for fault analysis. This makes the conventional methods inefficient, and a new paradigm in protection schemes is needed for IIDGs-dominated MGs. In this paper, a machine-learning (ML)-based protection technique is developed for IIDG-based AC MGs by extracting unique and novel features for detecting and classifying symmetrical and unsymmetrical faults. Different signals, namely, 400 samples, for wide variations in operating conditions of an MG are obtained through electromagnetic transient simulations in DIgSILENT PowerFactory. After retrieving and pre-processing the signals, 10 different feature extraction techniques, including new peaks metric and max factor, are applied to obtain 100 features. They are ranked using the Kruskal–Wallis H-Test to identify the best performing features, apart from estimating predictor importance for ensemble ML classification. The top 18 features are used as input to train 35 classification learners. Random Forest (RF) outperformed all other ML classifiers for fault detection and fault type classification with faulted phase identification. Compared to previous methods, the results show better performance of the proposed method.
Optimization of Low Salinity Water/Surfactant Flooding Design for Oil-Wet Carbonate Reservoirs by Introducing a Negative Salinity Gradient
Authors: Shakeel Mariam , Samanova Aida , Pourafshary Peyman , Hashmet Muhammad Rehan
Published: December 2022

Engineered water surfactant flooding (EWSF) is a novel EOR technique to reduce residual oil saturation; however, it becomes quite challenging to obtain Winsor Type III microemulsion and the lowest IFT under actual reservoir conditions if only low salinity water is used. The main objective of this study was to design a negative salinity gradient to optimize the performance of the hybrid method. Three corefloods were performed on carbonate outcrop samples. The injection sequence in the first test was conventional waterflooding followed by optimum engineered water injection (2900 ppm) and finally an EWSF stage. The second and third tests were conducted using a varying negative salinity gradient. Engineered water for this study was designed by 10 times dilution of Caspian Sea water and spiking with key active ions. A higher salinity gradient was used for the first negative salinity gradient test. A total of 4300 ppm brine with 1 wt% surfactant was injected as a pre-flush after waterflooding followed by a further reduced salinity brine (~1400 ppm). The second negative salinity gradient test consisted of three post-waterflooding injection stages with salinities of 4600, 3700, and 290 ppm, respectively. Up to 8% and 16% more incremental oil recovery after waterflooding was obtained in the second and third tests, respectively, as compared to the first test. The descending order of brine salinity helped to create an optimum salinity environment for the surfactant despite surfactant adsorption. This study provided an optimum design for a successful LSSF test by adjusting the brine salinity and creating a negative salinity gradient during surfactant flooding. A higher reduction in residual oil saturation can be achieved by carefully designing an LSSF test, improving project economics.
Experimental Investigations of the LED Lamp with Heat Sink Inside the Synthetic Jet Actuator
Authors: Gil Paweł , Wilk Joanna , Smolen Slawomir , Gałek Rafał , Markowicz Marek , Kucharski Piotr
Published: December 2022

The paper presents the experimental research on the thermal management of a 150 W LED lamp with heat sink inside a synthetic jet actuator. The luminous flux was generated by 320 SMD LEDs with a nominal luminous efficacy equal to 200 lm/W mounted on a single PCB. Characteristic temperatures were measured with three different measurement techniques: thermocouples, infrared camera, and an estimation of the junction temperature from its calibrated dependence on the LED forward voltage. The temperature budget between the LED junction and ambient as well as the thermal resistance network was determined and analyzed. The energy balance of the LED lamp is presented along with the values of the heat flow rate and heat transfer coefficient in different regions of the LED lamp surface. For an input power supplied to the SJA equal to 4.50 W, the synthetic jet dissipated approximately 89% of the total heat generated by the LED lamp. The heat from the PCB was transferred through the front and rear surfaces of the board. For the input power of 4.50 W, approximately 91% of the heat generated by LEDs was conducted by the PCB substrate to the heat spreading plate, while the remaining 9% was dissipated by the front surface of the PCB, mostly by radiation. The thermal balance revealed that for the luminous efficacy of the investigated LEDs, approximately 60% of the electrical energy supplied to the LED lamp was converted into heat, while the rest was converted into light.
Modeling and Simulation of Silicon Solar Cells under Low Concentration Conditions
Authors: Dosymbetova Gulbakhar , Mekhilef Saad , Saymbetov Ahmet , Nurgaliyev Madiyar , Kapparova Ainur , Manakov Sergey , Orynbassar Sayat , Kuttybay Nurzhigit , Svanbayev Yeldos , Yuldoshev Isroil , Zholamanov Batyrbek , Koshkarbay Nursultan
Published: December 2022

Today’s research on concentrated photovoltaic (CPV) cells focuses on creating multi-junction semiconductor solar cells capable of withstanding high temperatures without losing their properties. This paper investigated silicon low concentrated photovoltaic (LCPV) devices using Fresnel lenses. The parameters of the silicon CPV cell were measured to simulate its operation based on a single-diode model with four and five parameters. The most optimal position of the Fresnel lens relative to the solar cell was shown, and the dependence of the CPV efficiency on the concentration ratio, incident solar power, and temperature was studied. Experiments on heating of a solar cell were conducted to build a model of heating of a solar cell under different solar radiation based on machine learning. Additionally, a cooling system was developed, and experiments were conducted for one LCPV cell. The resulting LCPV model was used to predict electrical power output and temperature change pattern using clear day data. Results of modeling show increase in generated energy by 27% compared with non-concentrated solar cells. Cooling system energy consumption was simulated, and the optimum cooling regime was determined. The proposed LCPV system can be used as a hybrid heat and electricity source, increase power generation, and does not require new solar cell production technologies.
Multi-Criteria Future Energy System Planning and Analysis for Hot Arid Areas of Iran
Authors: Yousefi Hossein , Ghodusinejad Mohammad Hasan , Ghodrati Armin
Published: December 2022

An increase in energy demand in the coming years is inevitable, and therefore it is necessary to provide optimal solutions for this future need. This paper examines the future energy demands of the southern regions of Iran (with a hot and dry climate and high energy needs). In this regard, the overall structure of the research has been divided into three parts. In the first part, using historical energy consumption data, the energy demand in 2030 is predicted. This is carried out utilizing a time series analysis method, namely Holt–Winters. Then, relying on the plans of the Iran Ministry of Energy, various energy plans have been designed and energy modeling has been carried out for both base and forecast years. Finally, regarding a multi-criteria decision-making approach, energy plans are ranked and the best scenarios are selected and analyzed. The results of modeling and multi-criteria analysis showed that comprehensive and simultaneous development in the construction of thermal and renewable power plants is the best option to meet future energy needs.
Study on Unblocking and Permeability Enhancement Technology with Rotary Water Jet for Low Recharge Efficiency Wells in Sandstone Geothermal Reservoirs
Authors: Yu Chao , Tian Tian , Hui Chengyu , Huang Haochen , Zhang Yiqun
Published: December 2022

In China, sandstone geothermal reservoirs are large in scale and widely distributed, but their exploitation is hindered by low recharge efficiency. In this paper, an unblocking and permeability enhancement technology using a rotary water jet for low recharge efficiency wells in sandstone geothermal reservoirs is proposed to solve this problem. This paper presents a series of studies about the proposed technology, including experiments, simulation and field application. Firstly, an experiment was carried out to verify the scale removal effect of a high-pressure water jet on the inner wall of the screen tube and its impact on sandstone. Secondly, the numerical models of the rotary jet flow field in the wellbore were established by ANSYS Fluent to study the influence of parameters. Finally, based on the simulation and experiment results, a rotary jet tool applicable to unblocking and descaling low-efficiency wells was designed, and a field application for low-efficiency wells in sandstone thermal reservoirs was conducted. The study results show that the unblocking and permeability enhancement technology using a rotary water jet is effective in removing the blockages and improving the permeability near the well. In conclusion, the presented technology can solve the problem of low efficiency during the reinjection of cooled thermal waters back into sandstone geothermal reservoirs and has great effectiveness in field application.
Analysis of the Productivity Dynamics of Electricity Distribution Regions in Ghana
Authors: Tengey Clement , Nwulu Nnamdi Ikechi , Adepoju Omoseni , Longe Omowunmi Mary
Published: December 2022

Electrical power distribution is the most important division in the power supply chain. However, its sustainability in terms of efficiency is very important for the growth of every country. This main objective of the paper is to assess the productivity dynamics of this process using the data envelopment analysis (DEA) methodology to analyse the effectiveness of the electricity distribution regions (EDRs) over a period of 7 years. The paper adapts the biennial Malmquist productivity index by infusing it with the slacks-based measure (SBM) to assess the productivity dynamics of EDRs in Ghana. Productivity dynamics were assessed by decomposing the SBM-BMPI productivity scores into the efficiency, technology, and scale change. It was discovered that the productivity of EDRs in Ghana progressed by 16.23% per annum over the sample period. Productivity was driven mainly by technological change and not the efficiency changes and scale changes.
TiO2–Graphene Oxide and TiO2–Reduced Graphene Oxide Composite Thin Films for Solar Photocatalytic Wastewater Treatment
Authors: Tismanar Ioana , Obreja Alexandru Cosmin , Buiu Octavian , Duta Anca
Published: December 2022

This research reports on Vis- and solar-active photocatalytic bi-layered films of TiO2 (layer 1) and a composite with TiO2 matrix and graphene oxide or reduced graphene oxide filler (layer 2) obtained by coupling two methods: spray pyrolysis deposition followed by spraying a diluted sol. The thin films crystallinity degree, surface morphology and elemental composition were recorded and the composites were tested in photo-degradation processes, using the standard 10 ppm methylene blue solution, under simulated UV + VIS irradiation conditions using an irradiance measured to be close to the natural one, in continuous flow process, at demonstrator scale; these results were compared with those recorded when using low irradiance values in static regime. The effect of the increase in the graphene oxide content was investigated in the concentration range 1.4%w...10%w and was found to increase the process efficiency. However, the photocatalytic efficiencies increased only by 15% at high irradiance values compared with the values recorded at low irradiance as result of the electron-hole recombination in the composite-thin film. Similar experiments were run using composites having reduced graphene oxide as filler. The interfaces developed between the matrix and the filler were discussed outlining the influence of the filler’s polarity. The thin films stability in aqueous medium was good, confirmed by the results that outlined no significant differences in the surface aspect after three successive photocatalytic cycles.
Renewable Energy Resources Technologies and Life Cycle Assessment: Review
Authors: Hemeida Mahmoud , Hemeida Ashraf , Senjyu Tomonobu , Osheba Dina
Published: December 2022

Moving towards RER has become imperative to achieve sustainable development goals (SDG). Renewable energy resources (RER) are characterized by uncertainty whereas, most of them are unpredictable and variable according to climatic conditions. This paper focuses on RER-based electrical power plants as a base to achieve two different goals, SDG7 (obtaining reasonably priced clean energy) and SDG13 (reducing climate change). These goals in turn would support other environmental, social, and economic SDG. This study is constructed based on two pillars which are technological developments and life cycle assessment (LCA) for wind, solar, biomass, and geothermal power plants. To support the study and achieve the main point, many essential topics are presented in brief such as fossil fuels’ environmental impact, economic sustainability linkage to RER, the current contribution of RER in energy consumption worldwide and barriers and environmental effects of RER under consideration. As a result, solar and wind energy lead the RER electricity market with major contributions of 27.7% and 26.92%, respectively, biomass and geothermal are still of negligible contributions at 4.68% and 0.5%, respectively, offshore HAWT dominated other WT techniques, silicon-based PV cells dominated other solar PV technologies with 27% efficiency, combustion thermochemical energy conversion process dominated other biomass energy systems techniques, due to many concerns geothermal energy system is not preferable. Many emerging technologies need to receive more public attention, intensive research, financial support, and governmental facilities including effective policies and data availability.
Review, Challenges and Potential of AC/AC Matrix Converters CMC, MMMC, and M3C
Authors: Gili Luiz Carlos , Dias Julio Cesar , Lazzarin Telles Brunelli
Published: December 2022

This article presents a review and a comparison of the conventional matrix converter (CMC), multimodular matrix converter (MMMC), and multilevel matrix modular converter (M3C) topologies, which are three of the main topologies of the matrix family. The study of the CMC supplies basic knowledge for these structures and then the concept of multilevel matrix converters used in MMMC and M3C topologies is approached. The study addresses modulation strategies and switching sequences for the topologies to provide implementation guidelines and harmonic content reduction. The design is also carried out and results of the three topologies are shown to exemplify their operation. Finally, the article presents a comparison between the topologies to highlight the advantages and challenges of each one. This study contributes information on the three topologies, which are not easily found in the literature, especially in terms of modulation and switching strategies. It also highlights applications and research points that have to improve.