bluuebunny/crossref_metadata_2025 huggingface dataset:
The dsRNA Delivery, Targeting and Application in Pest Control
Authors: Lu Yuzhen , Deng Xinyue , Zhu Qijun , Wu Denghui , Zhong Jielai , Wen Liang , Yu Xiaoqiang
Published: February 2023

RNA interference (RNAi) is a simple and rapid method for silencing genes in various organisms, and it is widely used in gene function and genetics research. RNAi has been developed as a novel pest management strategy. Double-stranded RNAs (dsRNAs) delivered via microinjection, ingestion, or soaking are effective for silencing genes in insect pests, whereas oral and topical delivery methods are feasible for field applications. Here, we summarize oral and topical delivery, in pests, of dsRNA target genes, including those involved in energy metabolism, synthesis of essential cellular components, hormone homeostasis, chitin metabolism, the digestive system, immunity, detoxification, insecticide resistance, and other processes. RNAi pesticides have been developed in the form of genetically modified (GM) crops expressing dsRNAs as well as applied as foliar sprays. In this review, RNAi-based products are also summarized.
Effect of Foliar Treatments with Calcium and Nitrogen on Oregano Yield
Authors: Farruggia Davide , Iacuzzi Nicolò , La Bella Salvatore , Sabatino Leo , Consentino Beppe Benedetto , Tuttolomondo Teresa
Published: February 2023

Oregano, Origanum vulgare L., is a perennial herbaceous plant belonging to the Lamiaceae family. Oregano shows variations in biomass yield and essential oil (EO) content due to the influence of abiotic and biotic factors. The aim of this study was to assess the effect of different foliar applications based on calcium (Ca) and nitrogen (N) on morphological and productive parameters in oregano. Tests were carried out in Sicily (Italy) in 2020–2021. In each year, eight foliar applications were applied. Only flowers and leaves were used for the extraction of the EO. For all parameters in the study, except for plant height and inflorescence length, the highest values were found in treated plants with respect to the control. In plants treated with calcium and nitrogen, an increase of between 0.6 and 1.6 t ha−1 was observed for fresh yield, and an increase of between 0.5 and 0.9 t ha−1 was observed for dry yield. The increase in biomass yield led to an increase in EO yield of between 4 and 12 kg ha−1. The results highlight that foliar treatments with Ca in combination with N enable growth in crop production in environments that show poor water availability.
Acute Cholecystitis from Biliary Lithiasis: Diagnosis, Management and Treatment
Authors: Costanzo Maria Ludovica , D’Andrea Vito , Lauro Augusto , Bellini Maria Irene
Published: February 2023

Biliary lithiasis is a global disorder affecting nearly 20% of the world’s population, although most cases occur without symptoms. Gallbladder stones could move into the common bile duct after gallbladder contraction, causing acute cholecystitis. The progression of the acute disease can take different forms, from mild inflammation, treatable with oral antibiotics, to the most severe forms with septic shock or biliary peritonitis, requiring specific treatment. Liver function tests and abdominal ultrasound are generally sufficient for diagnostic purposes. The most commonly used antibiotic is penicillin, with piperacillin achieving the best results; alternatively, fluoroquinolones could also be used, although there is no univocal consensus and surgery remains the only definitive treatment. A prolonged antibiotic therapy after cholecystectomy seems inadvisable, except in severe cases and/or in the immuno-compromised patient, where it should be periodically evaluated to avoid antibiotic resistance and unnecessary use. This review presents an evidence-based analysis to describe the advantages and disadvantages of the available options for the treatment of biliary lithiasis and cholecystitis, from the pathophysiological mechanisms behind lithiasis formation and also covering the main diagnostic findings for biliary stones, recommending an approach tailored to the patient’s characteristics and to the team’s expertise.
A Force Identification Method for Geometric Nonlinear Structures
Authors: Guo Lina , Ding Yong
Published: February 2023

Excitation identification for nonlinear structures is still a challenging problem due to the convergence and accuracy in this process. In this study, a load estimation method is proposed with orthogonal decomposition, the order for which can be fairly accurately determined by a regression. In this process, the force time history is represented by the orthogonal basis and the coefficients of the orthogonal decomposition are taken as unknowns and augmented to the state variable, which can be identified recursively in state space. A general energy-conserving method is selected to a step-by-step integration to guarantee the convergence of this integration. The proposed method is first validated by numerical simulation studies of a truss structure considering its geometric property. The identification results of the numerical studies demonstrate that the proposed excitation identification method and the orthogonal decomposition order determination method work well for nonlinear structures. The laboratory work of a 7-story frame is investigated to consider the geometric nonlinearity in impact force identification. The results of experimental studies show that uncertainties such as measurement noise and model error are included in the investigation of the accuracy and robustness of the proposed force identification method, while the time history of external forces could be identified with promising results.
Sustainable Operation of Active Distribution Networks
Authors: Kyriakou Dimitra G. , Kanellos Fotios D.
Published: February 2023

The present and future conditions in the energy market impose extremely high standards to the operation of building energy systems. Moreover, distribution networks face new operational and technical challenges as a result of the rapid penetration of renewable energy sources (RES) and other forms of distributed generation. Consequently, active distribution networks (ADNs) will play a crucial role in the exploitation of smart building prosumers, smart grids, and RES. In this paper, an optimization method for the sustainable operation of active distribution networks hosting smart residential building prosumers, plug-in electric vehicle (PEV) aggregators, and RES was developed. The thermal and electrical loads of the residential buildings were modeled in detail and an aggregation method was implemented to the hosted PEVs. Moreover, smart power dispatch techniques were applied at each building prosumer and PEV aggregator hosted by the active distribution network. Simultaneously, all the operational limitations of the active distribution network, building energy systems, and the hosted PEVs were satisfied. The constrained optimal power flow (OPF) algorithm was exploited to keep the voltages of the hosting distribution network between the permissible bounds. A significant operation cost reduction of 17% was achieved. The developed models were verified through detailed simulation results.
Quantum Fisher Information of Three-Level Atom under the Influence of the Stark Effect and Intrinsic Dechorence
Authors: Anwar S. Jamal , Ramzan M. , Khan M. Khalid
Published: February 2023

We study the dynamical evolution of quantum Fisher information (QFI) and von Neumann entropy (VNE) for a three-level atomic system interacting with the single-mode coherent field in the presence of the Stark effect and intrinsic decoherence (ID) with and without atomic motion. The effect of the ID is significant on the VNE and QFI for a three-level atom in the absence of atomic motion. It is observed that in the case of a three-level atomic system in the presence of ID, the decay of QFI and VNE is rapid and significant but no prominent effect of the Stark effect is observed. Hence, for a three-level atom, the decay of quantum entanglement (QE) with respect to time is very fast and rapid in the absence of atomic motion with an increasing value of ID. Moreover, ID is not suitable to maintain the QE for three-level atomic systems in the absence of atomic motion. The Stark effect has no significant effect on the QE. In the case of three-level atoms, ID and the Stark do not affect the periodic nature of QFI and VNE with time evolution in the presence of atomic motion. The periodic response of QFI and VNE is observed under the effect of the Stark effect and ID in the presence of a motion of a three-level atom. The QE sudden death and birth is observed in the presence of atomic motion. Therefore, the ID with the Stark effect is suitable to sustain and maintain the QE in the presence of atomic motion for three-level atomic systems. These results show the strong dependence of QFI and VNE on the Stark effect and ID.
Lithium-Ion Battery Management System for Electric Vehicles: Constraints, Challenges, and Recommendations
Authors: Habib A. K. M. Ahasan , Hasan Mohammad Kamrul , Issa Ghassan F. , Singh Dalbir , Islam Shahnewaz , Ghazal Taher M.
Published: February 2023

Flexible, manageable, and more efficient energy storage solutions have increased the demand for electric vehicles. A powerful battery pack would power the driving motor of electric vehicles. The battery power density, longevity, adaptable electrochemical behavior, and temperature tolerance must be understood. Battery management systems are essential in electric vehicles and renewable energy storage systems. This article addresses concerns, difficulties, and solutions related to batteries. The battery management system covers voltage and current monitoring; charge and discharge estimation, protection, and equalization; thermal management; and battery data actuation and storage. Furthermore, this study characterized the various cell balancing circuit types, their components, current and voltage stresses, control reliability, power loss, efficiency, size and cost, and their benefits and drawbacks. Secondly, we review concerns and challenges in battery management systems. Furthermore, we identify problems and obstacles that need additional attention for optimal and sustainable battery management systems for electric vehicles and renewable energy storage systems. Our last topic will be on issues for further research.
Green Synthesis of Magnesium Oxide Nanoparticles by Using Abrus precatorius Bark Extract and Their Photocatalytic, Antioxidant, Antibacterial, and Cytotoxicity Activities
Authors: Ali Saheb , Sudha Kattakgoundar Govindaraj , Thirumalaivasan Natesan , Ahamed Maqusood , Pandiaraj Saravanan , Rajeswari Vijayarangan Devi , Vinayagam Yamini , Thiruvengadam Muthu , Govindasamy Rajakumar
Published: February 2023

The current research is concerned with the synthesis of magnesium oxide (MgO) nanoparticles (NPs) from Abrus precatorius L. bark extract via the green chemistry method. The synthesized MgO NPs was confirmed by using several characterization methods like XRD, FTIR, SEM, TEM, and UV-visible analysis. The synthesized MgO NPs displayed a small particle size along with a specific surface area. Abrus precatorius bark synthesized MgO NPs with a higher ratio of dye degradation, and antioxidant activity showed a higher percentage of free radical scavenging in synthesized MgO NPs. Zebrafish embryos were used as a model organism to assess the toxicity of the obtained MgO nanoparticles, and the results concluded that the MgO NPs were nontoxic. In addition, the anticancer properties of MgO nanoparticles were analyzed by using a human melanoma cancer cell line (A375) via MTT, XTT, NRU, and LDH assessment. MgO NPs treated a human melanoma cancer cell line and resulted in apoptosis and necrosis based on the concentration, which was confirmed through a genotoxicity assay. Moreover, the molecular mechanisms in necrosis and apoptosis were conferred to depict the association of magnesium oxide nanoparticles with the human melanoma cancer cell line. The current study on MgO NPs showed a broad-scope understanding of the use of these nanoparticles as a medicinal drug for melanoma cancer via its physiological mechanism and also a novel route to obtain MgO NPs by using the green chemistry method.
Efficacy of Platelet-Rich Plasma in Women with a History of Embryo Transfer Failure: A Systematic Review and Meta-Analysis with Trial Sequential Analysis
Authors: Anitua Eduardo , Allende Mikel , de la Fuente María , Del Fabbro Massimo , Alkhraisat Mohammad Hamdan
Published: February 2023

Assisted reproductive technology (ART) is used to enhance pregnancy in infertile women. In this technique, the eggs are removed from the ovary and fertilized and injected with sperm to make embryos. Unfortunately, embryo implantation failures still occur in many of these women. Platelet-rich plasma (PRP) therapies use a patient’s own platelets to promote tissue healing and growth, including endometrium. The growth factors provided by the platelets play a criterial role on the regenerative ability of PRP. In the last years, PRP treatments have been gaining a lot of popularity to treat women with repeated ART failures. In this study, we collected and summarized all information published in the scientific literature to assess the evidence of the PRP effect on pregnancy. We only considered randomized controlled trials (RCT), a type of study designed to be unbiased and considered at the highest level of evidence. Our analysis indicates that PRP therapies might be an effective treatment in cases of poor responsiveness to conventional ART. However, additional studies (well-designed) are necessary to confirm this beneficial effect of PRP.
Intracycle Velocity Variation in Swimming: A Systematic Scoping Review
Authors: Fernandes Aléxia , Afonso José , Noronha Francisco , Mezêncio Bruno , Vilas-Boas João Paulo , Fernandes Ricardo J.
Published: February 2023

Intracycle velocity variation is a swimming relevant research topic, focusing on understanding the interaction between hydrodynamic propulsive and drag forces. We have performed a systematic scoping review to map the main concepts, sources and types of evidence accomplished. Searches were conducted in the PubMed, Scopus and Web of Science databases, as well as the Biomechanics and Medicine in Swimming Symposia Proceedings Book, with manual searches, snowballing citation tracking, and external experts consultation. The eligibility criteria included competitive swimmers’ intracycle velocity variation assessment of any sex, distance, pace, swimming technique and protocol. Studies’ characteristics were summarized and expressed in an evidence gap map, and the risk of bias was judged using RoBANS. A total of 76 studies, corresponding to 68 trials involving 1440 swimmers (55.2 and 34.1% males and females), were included, with only 20 (29.4%) presenting an overall low risk of bias. The front crawl was the most studied swimming technique and intracycle velocity variation was assessed and quantified in several ways, leading to extremely divergent results. Researchers related intracycle velocity variation to coordination, energy cost, fatigue, technical proficiency, velocity, swimming techniques variants and force. Future studies should focus on studying backstroke, breaststroke and butterfly at high intensities, in young, youth and world-class swimmers, as well as in IVV quantification.
CFD Computation of Flow Fractional Reserve (FFR) in Coronary Artery Trees Using a Novel Physiologically Based Algorithm (PBA) Under 3D Steady and Pulsatile Flow Conditions
Authors: Alzhanov Nursultan , Ng Eddie Y. K. , Su Xiaohui , Zhao Yong
Published: February 2023

A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA was based on an extension of Murray’s law and additional inlet conditions prescribed iteratively and was implemented in OpenFOAM v1912 for testing and validation. 3D models of CATs were created using CT scans and computational meshes, and the results were compared to invasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between the calculated and experimental FFR was within 2.33–5.26% in the steady-state and transient simulations, respectively, when convergence was reached. The PBA was a reliable and physiologically sound technique compared to a current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for convergence. The accuracy of the PBA method was further confirmed using an FDA nozzle, which demonstrated good alignment with the CFD-validated values.
On the Kinematics of the Forward-Facing Venetian-Style Rowing Technique
Authors: Grima Joseph N. , Cerasola Dario , Sciriha Anabel , Sillato Darren , Formosa Cynthia , Gatt Alfred , Gauci Michael , Xerri de Caro John , Needham Robert , Chockalingam Nachiappan , Agius Tonio P.
Published: February 2023

This work presents a qualitative and quantitative pilot study which explores the kinematics of Venetian style forward-facing standing rowing as practised by able-bodied competitive athletes. The technique, made famous by the gondoliers, was replicated in a biomechanics laboratory by a cohort of four experienced rowers who compete in this style at National Level events in Malta. Athletes were marked with reflective markers following the modified Helen Hayes model and asked to row in a manner which mimics their on-water practise and recorded using a Vicon optoelectronic motion capture system. Data collected were compared to its equivalent using a standard sliding-seat ergometer as well as data collated from observations of athletes rowing on water, thus permitting the documentation of the manner of how this technique is performed. It was shown that this rowing style is characterised by rather asymmetric and complex kinematics, particularly upper-body movements which provides the athlete with a total-body workout involving all major muscle groups working either isometrically, to provide stability, or actively.
Nonsense-Mediated mRNA Decay Factor Functions in Human Health and Disease
Authors: Sun Lingling , Mailliot Justine , Schaffitzel Christiane
Published: February 2023

Nonsense-mediated mRNA decay (NMD) is a cellular surveillance mechanism that degrades mRNAs with a premature stop codon, avoiding the synthesis of C-terminally truncated proteins. In addition to faulty mRNAs, NMD recognises ~10% of endogenous transcripts in human cells and downregulates their expression. The up-frameshift proteins are core NMD factors and are conserved from yeast to human in structure and function. In mammals, NMD diversified into different pathways that target different mRNAs employing additional NMD factors. Here, we review our current understanding of molecular mechanisms and cellular roles of NMD pathways and the involvement of more specialised NMD factors. We describe the consequences of mutations in NMD factors leading to neurodevelopmental diseases, and the role of NMD in cancer. We highlight strategies of RNA viruses to evade recognition and decay by the NMD machinery.
Application of Hybrid Swarming Algorithm on a UAV Regional Logistics Distribution
Authors: Zhang Yi , Yu Hongda
Published: February 2023

This paper proposes a hybrid algorithm based on the ant colony and Physarum Polycephalum algorithms. The positive feedback mechanism is used to find the globally optimal path. The crossover and mutation operations of the genetic algorithm are introduced into the path search mechanism for the first time. The Van der Waals force is applied to the pheromone updating mechanism. Simulation results show that the improved algorithm has advantages in quality and speed of solution compared with other mainstream algorithms. This paper provides fast and accurate route methods for solving the Traveling Salesman Problem first and a delivery scheme is also presented for UAVs to realize “contactless delivery” to users in the Changchun Mingzhu District during the COVID-19 epidemic, which confirms the practicability and robustness of the algorithm.
Renewable Energies and Architectural Heritage: Advanced Solutions and Future Perspectives
Authors: Lucchi Elena
Published: February 2023

The current legislative framework and the recent energy crisis ask for massive applications of renewable energy sources (RES) in the built environment to reduce energy demand, environmental emissions, and energy costs. The uncritical application of these policies, especially on architectural heritage, could generate serious conservation issues, compromising their heritage values, biodiversity, traditional appearance, and materiality. Thus, there is an urgent call to balance architectural heritage preservation with energy production using clear rules, policies, criteria, and heritage-compatible technologies. The present study aims at defining an updated overview of the application of solar, wind, geothermal energy, and bioenergy on architectural heritage. A deep literature review of the studies published in the years 2020–2023 has been performed, identifying main topics, challenges, advanced solutions, and future perspectives. Acceptability, design criteria, and cutting-edge technologies are also illustrated through case studies to better understand practical approaches.
Implications of Hypothalamic Neural Stem Cells on Aging and Obesity-Associated Cardiovascular Diseases
Authors: Plakkot Bhuvana , Di Agostino Ashley , Subramanian Madhan
Published: February 2023

The hypothalamus, one of the major regulatory centers in the brain, controls various homeostatic processes, and hypothalamic neural stem cells (htNSCs) have been observed to interfere with hypothalamic mechanisms regulating aging. NSCs play a pivotal role in the repair and regeneration of brain cells during neurodegenerative diseases and rejuvenate the brain tissue microenvironment. The hypothalamus was recently observed to be involved in neuroinflammation mediated by cellular senescence. Cellular senescence, or systemic aging, is characterized by a progressive irreversible state of cell cycle arrest that causes physiological dysregulation in the body and it is evident in many neuroinflammatory conditions, including obesity. Upregulation of neuroinflammation and oxidative stress due to senescence has the potential to alter the functioning of NSCs. Various studies have substantiated the chances of obesity inducing accelerated aging. Therefore, it is essential to explore the potential effects of htNSC dysregulation in obesity and underlying pathways to develop strategies to address obesity-induced comorbidities associated with brain aging. This review will summarize hypothalamic neurogenesis associated with obesity and prospective NSC-based regenerative therapy for the treatment of obesity-induced cardiovascular conditions.
Vapor-Phase Oxidant-Free Dehydrogenation of 2,3- and 1,4-Butanediol over Cu/SiO2 Catalyst Prepared by Crown-Ether-Assisted Impregnation
Authors: Kurniawan Enggah , Hosaka Shuya , Kobata Masayuki , Yamada Yasuhiro , Sato Satoshi
Published: February 2023

A silica-supported copper (Cu/SiO2) catalyst containing highly dispersed Cu nanoparticles was prepared via a crown-ether-assisted impregnation method. A 12-crown-4-ether-assisted Cu/SiO2 catalyst outperformed several Cu/SiO2 catalysts prepared with various organic additives in the dehydrogenation of 2,3- and 1,4-butanediol. It was found that the catalytic activity, i.e., the formation rate of acetoin from 2,3-butanediol and that of γ-butyrolactone from 1,4-butanediol, was proportional to the copper surface area.
Network Coding Approaches for Distributed Computation over Lossy Wireless Networks
Authors: Fan Bin , Tang Bin , Qu Zhihao , Ye Baoliu
Published: February 2023

In wireless distributed computing systems, worker nodes connect to a master node wirelessly and perform large-scale computational tasks that are parallelized across them. However, the common phenomenon of straggling (i.e., worker nodes often experience unpredictable slowdown during computation and communication) and packet losses due to severe channel fading can significantly increase the latency of computational tasks. In this paper, we consider a heterogeneous, wireless, distributed computing system performing large-scale matrix multiplications which form the core of many machine learning applications. To address the aforementioned challenges, we first propose a random linear network coding (RLNC) approach that leverages the linearity of matrix multiplication, which has many salient properties, including ratelessness, maximum straggler tolerance and near-ideal load balancing. We then theoretically demonstrate that its latency converges to the optimum in probability when the matrix size grows to infinity. To combat the high encoding and decoding overheads of the RLNC approach, we further propose a practical variation based on batched sparse (BATS) code. The effectiveness of our proposed approaches is demonstrated by numerical simulations.
Lossy Micromaser Battery: Almost Pure States in the Jaynes–Cummings Regime
Authors: Shaghaghi Vahid , Singh Varinder , Carrega Matteo , Rosa Dario , Benenti Giuliano
Published: February 2023

We consider a micromaser model of a quantum battery, where the battery is a single mode of the electromagnetic field in a cavity, charged via repeated interactions with a stream of qubits, all prepared in the same non-equilibrium state, either incoherent or coherent, with the matter–field interaction modeled by the Jaynes–Cummings model. We show that the coherent protocol is superior to the incoherent one, in that an effective pure steady state is achieved for generic values of the model parameters. Finally, we supplement the above collision model with cavity losses, described by a Lindblad master equation. We show that battery performances, in terms of stored energy, charging power, and steady-state purity, are slightly degraded up to moderated dissipation rate. Our results show that micromasers are robust and reliable quantum batteries, thus making them a promising model for experimental implementations.
MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images
Authors: Wang Shuihua , Abdelaty Ahmed M. S. E. K. , Parke Kelly , Arnold Jayanth Ranjit , McCann Gerry P. , Tyukin Ivan Y.
Published: February 2023

Myocardial infarction (MI) occurs when an artery supplying blood to the heart is abruptly occluded. The “gold standard” method for imaging MI is cardiovascular magnetic resonance imaging (MRI) with intravenously administered gadolinium-based contrast (with damaged areas apparent as late gadolinium enhancement [LGE]). However, no “gold standard” fully automated method for the quantification of MI exists. In this work, we propose an end-to-end fully automatic system (MyI-Net) for the detection and quantification of MI in MRI images. It has the potential to reduce uncertainty due to technical variability across labs and the inherent problems of data and labels. Our system consists of four processing stages designed to maintain the flow of information across scales. First, features from raw MRI images are generated using feature extractors built on ResNet and MoblieNet architectures. This is followed by atrous spatial pyramid pooling (ASPP) to produce spatial information at different scales to preserve more image context. High-level features from ASPP and initial low-level features are concatenated at the third stage and then passed to the fourth stage where spatial information is recovered via up-sampling to produce final image segmentation output into: (i) background, (ii) heart muscle, (iii) blood and (iv) LGE areas. Our experiments show that the model named MI-ResNet50-AC provides the best global accuracy (97.38%), mean accuracy (86.01%), weighted intersection over union (IoU) of 96.47%, and bfscore of 64.46% for the global segmentation. However, in detecting only LGE tissue, a smaller model, MI-ResNet18-AC, exhibited higher accuracy (74.41%) than MI-ResNet50-AC (64.29%). New models were compared with state-of-the-art models and manual quantification. Our models demonstrated favorable performance in global segmentation and LGE detection relative to the state-of-the-art, including a four-fold better performance in matching LGE pixels to contours produced by clinicians.
The Evolution of the Field of Learning Environments Research
Authors: Fraser Barry J.
Published: February 2023

This article reviews half a century of remarkable expansion and internationalisation in the field of learning environments research, including milestones such as the creation of the American Educational Research Association’s Special Interest Group on Learning Environments and Springer’s Learning Environments Research: An International Journal. Several widely used, extensively validated and economical questionnaires for assessing learning environments (e.g., What Is Happening In this Class? WIHIC) are discussed. A review of research identifies how learning environment researchers have generated robust knowledge about how to improve student outcomes through creating positive learning environments; demonstrated the value of including learning environment dimensions as process criteria of effectiveness when evaluating educational programmes and teaching methods; and provided teachers with straightforward approaches to use in action research aimed at improving their students’ learning environments. To facilitate and motivate future research and practical applications, the 56-item WIHIC is included in an appendix, and some newer and emerging lines of research are identified (e.g., cross-national studies; the physical environments of educational buildings and learning spaces; and advances in methods of statistical analysis for learning environment studies).
Control of Cuk-Based Microinverter Topology with Energy Storage for Residential PV Applications
Authors: Alharbi Yousef , Darwish Ahmed
Published: February 2023

This paper proposes a modular inverter based on Cuk converters for solar photovoltaic (PV) systems to mitigate the voltage and current mismatch issue at the PV module level. The proposed modular Cuk inverter (MCI) is formed by connecting several low-voltage (LV) microinverters (MIs) in series and linking their output sides to the distribution network. This architecture does not require a central inverter, and hence, it eliminates the need for large dc-link intermediate capacitors. The proposed MCI provides more controllability over the PV system by having a decentralized structure. The MCI will improve the PV system efficiency by reducing the voltage and current stresses in the MIs and will enable better voltage regulation due to the provided controllability. Since the proposed MI topology is based on the Cuk converter, it offers continuous input and output currents that will reduce the required filtering capacitance and will provide a wide range of voltage regulation for either supplying the loads or charging the storage batteries. The paper presents the associated control scheme for the proposed MCI that employs two controlling loops. The input loop at the PV side is designed and tuned to eliminate the ripples from the input current, while the outer loop at the grid side will control the output ac current and hence the MCI power. Computer simulations are presented using MATLAB/SIMULINK software to examine the validity of the suggested inverter for distributed generation PV residential applications. A scaled-down experimental prototype controlled by TMS320F28335 DSP was built and used to validate the mathematical analyses and simulation results.
Month-Wise Investigation on Residential Load Consumption Impact during COVID-19 Period on Distribution Transformer and Practical Mitigation Solution
Authors: Alam S. M. Mahfuz , Abuhussein Ahmed , Sadi Mohammad Ashraf Hossain
Published: February 2023

This paper investigates the month-wise impact of COVID-19 conditions on residential load due to people’s presence at home during office hours in Memphis city, Tennessee, USA. The energy consumption patterns of four consumers are analyzed based on the data available from pre-COVID to continuing COVID-19 situations. It is observed that the energy consumptions from April 2020 to June 2021 for all families have increased during office hours than that of pre-COVID months. Therefore, the impacts of the increased loads on distribution transformer are analyzed in terms of hottest spot, top-oil temperature, and loss of transformer life. Moreover, an experimental setup is made to produce the harmonics in currents of non-linear residential load which has detrimental effects on temperature rise of distribution transformer. In addition, this work proposes implementation of harmonic filter at the load side considering the impact of harmonics produced by loads to reduce the temperature rise due to the increased load consumption and presence of harmonics in currents produced by the load. The rise in temperatures and the loss of life of distribution transformer with and without the proposed solutions are simulated in MATLAB to show the efficacy of the proposed solution. Moreover, cost value analysis among different methods, which can be implemented to reduce the adverse impact on distribution transformer, are provided to rank the available methods.
Organic Geochemical Features of the Upper Paleozoic Coal-Bearing Deposits in Ordos Basin, North-Central China
Authors: Li Zonglin , Li Hong , Li Wenhou , Sun Jiaopeng , Li Keyong
Published: February 2023

The exploration of hydrocarbon resources plays a critical role in fulfilling the world’s increasing demand for energy. In this regard, the distribution and source rock characteristics of coal measure stratum in the whole basin are important and must be studied. However, systematic research has not been conducted yet. In this study, organic geochemical data, drilling data, and fieldwork were used to examine the source rock distribution of the Upper Paleozoic stratum. The results revealed that Upper Paleozoic coal-bearing rock series are mostly present in the Benxi, Taiyuan, and Shanxi formations, and mudstones and coals are formed frequently in tidal flat deposits. The layers of the coal and mudstone are primarily thick on the western sides, eastern sides, and northern sides, thin in the middle region, and gradually thinner from north to south. The source rocks are mostly enriched in the east and west of the basin. The results of the Rock-Eval pyrolysis analysis indicated that the overwhelming majority of the coal comprises excellent source rocks, all limestones are poor source rocks, and most mudstones are good–excellent source rocks. The kerogen type of most of the rock samples is type Ⅲ, suggesting typical “gas source” kerogen. Humus is derived from terrestrial organism and aquatic algae remnants, indicating a diversified parent material input. These results evidence that studied source rocks are at the postmature-dry gas stage.
Protection and Communication Techniques in Modern Power Systems
Authors: Kauhaniemi Kimmo
Published: February 2023

The protection systems of modern grids are facing new challenges and opportunities due to the development of future Smart Grids [...]
A Comprehensive Review of Shipboard Power Systems with New Energy Sources
Authors: Yin He , Lan Hai , Hong Ying-Yi , Wang Zhuangwei , Cheng Peng , Li Dan , Guo Dong
Published: February 2023

A new energy ship is being developed to address energy shortages and greenhouse gas emissions. New energy ships feature low operational costs and zero emissions. This study discusses the characteristics and development of solar-powered ships, wind-powered ships, fuel cell-powered ships, and new energy hybrid ships. Three important technologies are used for the power system of the new energy ship: new-energy spatio-temporal prediction, ship power scheduling, and Digital Twin (DT). Research shows that new energy spatio-temporal prediction reduces the uncertainty for a ship power system. Ship power scheduling technology guarantees safety and low-carbon operation for the ship. DT simulates the navigational environment for the new energy ship to characterize the boundary of the shipboard’s new energy power generation. The future technical direction for new energy ship power systems is also being discussed.
Dynamic Simulation of MFT and BT Processes on a 660 MW Ultra-Supercritical Circulating Fluidized Bed Boiler
Authors: Li Guo , Tao Xiangyu , Zhang Zonglong , Yang Chen , Deng Qigang , Nie Li , He Wei , Li Weicheng , Lu Jiayi , Gong Liming
Published: February 2023

In order to study the dynamic characteristics of the 660 MW ultra-supercritical circulating fluidized bed (CFB) boiler when the main fuel trip (MFT) and boiler trip (BT) are triggered, a dynamic simulation model of the 660 MW ultra-supercritical circulating fluidized bed boiler was established on the Apros simulation platform. The model dynamically simulated the MFT and BT processes at 100% BMCR, 75% THA, and 50% THA conditions, respectively. The steady-state simulation results showed a high accuracy compared with the designed parameters. The dynamic simulation results showed that after triggering the MFT and BT, owing to the huge thermal inertia, the bed temperature and steam temperature decreased lowly. For 100% BMCR and 75% THA conditions, the moisture separator always worked in dry state during the MFT and BT processes. For the 50% THA condition, the moisture separator quickly switched from dry to wet operation after the boiler triggers MFT and BT and gradually switched from wet to dry operation after MFT and BT were reset.
LSTM-Pearson Gas Concentration Prediction Model Feature Selection and Its Applications
Authors: Liu Chao , Zhang Ailin , Xue Junhua , Lei Chen , Zeng Xiangzhen
Published: February 2023

Gas disasters threaten the safe operation of coal mines. Improving the accuracy of gas concentration predictions can effectively prevent gas disasters and reduce disaster losses. Traditional gas concentration prediction methods poorly couple the gas concentration and its influencing factors when dealing with a great number of features and data, which results in low prediction accuracy and poor efficiency. To solve this problem, we used an innovative Pearson-LSTM prediction model, which uses the Pearson coefficient to select features of gas concentration data. It then uses long short-term memory (LSTM) that has been optimized using adaptive moment estimation (Adam) to predict a time series. In the process of model establishment, the optimal prediction model was obtained by constantly adjusting the number of network layers and batch size based on the fitting effect, performance issues, and result errors. Taking monitoring data from the 2407 working face at Yuhua Coal Mine as the sample, we compared our method with the traditional Bi-RNN and GRU machine learning methods. The results show that, compared with the Bi-RNN and GRU models, the mean square error of the Pearson-LSTM model can be reduced to 0.015 with an error range of 0.005 to 0.04, which has higher prediction accuracy. This method has excellent precision and robustness for forecasting gas concentration time series. The model was able to make predictions 15 min in advance for the 2409 working face of the Yuhua Coal Mine, and the mean square error could be lowered to 0.008, which verifies the applicability and reliability of the model and provides a reference for ensuring the safety of coal mine operations. In summary, Pearson-LSTM models have higher accuracy and robustness and can effectively predict changes in gas concentration, thus allowing for more response time for accidents, which is important for coal mine production safety.
Environmental and Health Benefits Assessment of Reducing PM2.5 Concentrations in Urban Areas in Developing Countries: Case Study Cartagena de Indias
Authors: Aldegunde José Antonio Álvarez , Bolaños Edgar Quiñones , Fernández-Sánchez Adrián , Saba Manuel , Caraballo Luis
Published: February 2023

High concentrations of particulate matter (PM) could significantly reduce the quality of useful life and human life expectancy. The origin, control, and management of the problem has made great steps in recent decades. However, the problem is still prominent in developing countries. In fact, often the number and spatial distribution of the air quality monitoring stations does not have an appropriate design, misleading decision makers. In the present research, an innovative assessment is proposed of the environmental, health and economic benefits corresponding to a 20% reduction in the PM2.5 concentration in the urban area of Cartagena de Indias, Colombia. Cases of mortality and morbidity attributable to fine particles (PM2.5) were estimated, with particular emphasis on mortality, emergency room visits and hospitalizations from respiratory diseases, in addition to their economic assessment using BenMAP-CE®. The novelty of using BenMAP-CE® in studying respiratory diseases and PM2.5 exposure in developing countries lies in its ability to provide a comprehensive assessment of the health impacts of air pollution in these regions. This approach can aid in the development of evidence-based policy and intervention strategies to mitigate the impact of air pollution on respiratory health. Several concentration-response (C-R) functions were implemented to find PM2.5 attributable mortality cases of ischemic heart and cardiopulmonary disease, lung cancer, respiratory and cardiovascular disease, as well as cases of morbidity episodes related to asthma exacerbation and emergency room/hospitalization care for respiratory disease. A 20% reduction would have avoided 104 cases of premature death among the population older than 30 in Cartagena, and around 65 cases of premature mortality without external causes.
Characterization of Limosilactobacillus reuteri KGC1901 Newly Isolated from Panax ginseng Root as a Probiotic and Its Safety Assessment
Authors: Yu Hye-Young , Kwon Mijin , Lee Yun-Seok , Lee Seung-Ho , Kim Sang-Kyu
Published: February 2023

In this study, we determined the probiotic properties and safety of Limosilactobacillus reuteri KGC1901 isolated from Korean Panax ginseng root. This strain was identified based on its 16s rRNA sequence, and the absence of genes related to antibiotic resistance and virulence was confirmed through whole genome analysis in terms of safety. Moreover, this strain had no antibiotic resistance to eight antibiotics as proposed by the European Food Safety Authority, did not show hemolytic activity on blood agar, and did not produce biogenic amines. L. reuteri KGC1901 also showed the capability to survive at low pH and in presence of bile salts and sufficiently adhered to HT-29 cells and mucin. The adhesion ability to HT-29 was confirmed by immunofluorescence staining. These results indicated the excellent viability of L. reuteri KGC1901 in the human gastrointestinal tract. Additionally, L. reuteri KGC1901 had antimicrobial activity against Clostridium difficile, and the presence of the reuterin (3-HPA) biosynthetic gene cluster in the genome was revealed. Furthermore, the cell-free supernatant of KGC1901 had DPPH scavenging activity and reduced the nitric oxide production in LPS-stimulated RAW 264.7 cells. Based on these results, it was confirmed that L. reuteri KGC1901 derived from ginseng has sufficient potential to be used as a probiotic.
The Role of Fermented Dairy Products on Gut Microbiota Composition
Authors: Okoniewski Adam , Dobrzyńska Małgorzata , Kusyk Paulina , Dziedzic Krzysztof , Przysławski Juliusz , Drzymała-Czyż Sławomira
Published: February 2023

Milk and dairy products are among the most important foods in the human diet. They are natural and culturally accepted and supply the human body with microorganisms that modulate the intestinal microflora. Improper lifestyles, highly processed diets, and certain drugs may contribute to adverse changes in the composition of the gut microflora. These changes may lead to dysbiosis, which is associated with the pathogenesis of many gastrointestinal diseases. This review aims to determine the effect of fermented milk products on the composition of the gut microbiota and their possible support in the treatment of dysbiosis and gastrointestinal diseases. While most research concerns isolated strains of bacteria and their effects on the human body, our research focuses on whole fermented products that contain complex mixtures of bacterial strains.
Improvement of Flesh Quality of Farmed Silver Carp (Hypophthalmichthys molitrix) by Short-Term Stocked in Natural Water
Authors: Miao Xiaomin , Guo Hui , Song Yong , Du Chunying , Feng Jingyun , Tao Yixi , Xu Hao , Li Yun
Published: February 2023

To investigate the effects of different raising environments on the flesh quality, the study set up three groups of silver carp (Hypophthalmichthys molitrix), that is, pond-farmed; short-term stocked; and ranched, grown in a natural water ranch. This study compared the differences in muscle proximate composition and amino acid composition among three groups. The results showed that there was no difference between the ranched and the stocked groups in content of crude protein, ash, total amino acids (TAA), essential amino acids (EAA), and umami-flavored amino acids (UAA), with both groups being significantly higher than the farmed group. This shows that, in terms of flesh quality, the stocked group was closer to the ranched group and better than the farmed group after being stocked in natural water for 30 days. The results suggest that the flesh quality of farmed fish was improved by short-term stocking in natural water. To elucidate the reasons of flesh quality change in the stocked group, this study compared the food composition and intestinal digestive enzyme activity in three groups, demonstrating that the ranched and stocked groups had similar food composition, with their detritus proportion lower than that of the farmed group, consuming easily digestible phytoplankton diatoms rich in amino acids and fatty acids. No significant difference was seen between the ranched group and the stocked group, for which amylase, lipase, and trypsin activities were lower than that of the farmed group. It is hypothesized that differences in environmental and food composition resulted in lower digestive enzyme activity in the ranched group and the stocked group. In summary, the short-term stocking of farmed fish in a natural water ranch can effectively improve the nutrient content, quality and flavor, and promote value of fish products.
Comparative Transcriptome Analysis Identifies MAPK Signaling Pathway Associated with Regulating Ovarian Lipid Metabolism during Vitellogenesis in the Mud Crab, Scylla paramamosain
Authors: Ren Yuanhao , Wang Wei , Fu Yin , Liu Zhiqiang , Zhao Ming , Xu Likun , Zhan Tianyong , Huang Ting , Luo Minghao , Chen Wei , Ma Chunyan , Zhang Fengying , Jiang Keji , Ma Lingbo
Published: February 2023

The mud crab, Scylla paramamosain, has abundant nutrients in the ovary, where numerous lipids accumulate during ovarian maturation. However, the mechanism behind the accumulation of lipids in the ovary of mud crab during ovarian maturation is largely unknown. This study conducted a comparative transcriptome analysis of the ovaries of mud crabs at various stages of ovarian maturation. A total of 63.69 Gb of clean data was obtained, with a Q30 of 93.34%, and 81,893 unigenes were identified, including 10,996 differentially expressed genes (DEGs). After KEGG enrichment of these DEGs, MAPK signaling pathway was significantly enriched during vitellogenesis. Moreover, the expression levels of genes involved in carbohydrate, amino acid, and lipid metabolism were found to be higher during vitellogenesis. The two genes (Sp-Eip75B and Sp-Eip78C) that are homologous to the vertebrate gene PPARγ in the PPAR signaling pathway, were identified. Additionally, genes in MAPK signaling pathway might regulate lipid metabolism through PPAR signaling pathway based on Protein-Protein Interaction (PPI) network. These findings suggest that MAPK signaling pathway plays a critical role in lipid metabolism in the ovary during vitellogenesis, which provides new insights into the mechanism of lipid accumulation during ovarian maturation in mud crabs.