bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Radiation Damage and Reinforcement of Control and Sensing Systems in Nuclear Robots
Authors: Chang Yinlin , Zou Shuliang , Lin Guang , Tang Dewen , Wei Cuiyue , Xu Shoulong
Published: March 2024

This study investigates the radiation damage and radiation reinforcement of the control and sensing systems of nuclear robots. Radiation experiments were conducted on key electronic devices to study their radiation resistance, and a shielding structure for radiation reinforcement was designed to meet the radiation resistance performance requirements of the system. The results show that at doses exceeding 1300 Gy, Hall sensors, pressure transducers, and temperature transducers exhibit radiation damage. At doses exceeding 170 Gy, transformers and controllers also show radiation damage. Lithium batteries remain largely unaffected, but packs experience voltage decline. When using Pb and W as shielding materials for Super MC simulation, it was found that at a thickness of 15 mm, the shielding efficiency of the controller and transformer under Pb shielding increased by approximately 84.99% and 52.00%, respectively, compared to 92.23% and 74.47% under W, which had the best shielding effect benefits. By adopting radiation-resistant shielding reinforcement, we can effectively improve the radiation resistance of the controller and transformer. This is crucial for ensuring the reliable operation of nuclear robots in high-radiation environments and providing important data and theoretical support for the development of related technologies.
Solving Confirmation Time in Sharded Blockchain with PFQN
Authors: Wu Junting , Du Haotian , Chen Jin , Ren Wei
Published: March 2024

Sharding shows great potential for extending the efficiency of blockchains. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workloads, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a product-form queue network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between the network load and consensus efficiency in sharded blockchains, offering a meaningful perspective for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.
Lightweight Privacy Protection via Adversarial Sample
Authors: Xie Guangxu , Hou Gaopan , Pei Qingqi , Huang Haibo
Published: March 2024

Adversarial sample-based privacy protection has its own advantages compared to traditional privacy protections. Previous adversarial sample privacy protections have mostly been centralized or have not considered the issue of hardware device limitations when conducting privacy protection, especially on the user’s local device. This work attempts to reduce the requirements of adversarial sample privacy protections on devices, making the privacy protection more locally friendly. Adversarial sample-based privacy protections rely on deep learning models, which generally have a large number of parameters, posing challenges for deployment. Fortunately, the model structural pruning technique has been proposed, which can be employed to reduce the parameter count of deep learning models. Based on the model pruning technique Depgraph and existing adversarial sample privacy protections AttriGuard and MemGuard, we design two structural pruning-based adversarial sample privacy protections, in which the user obtains the perturbed data through the pruned deep learning model. Extensive experiments are conducted on four datasets, and the results demonstrate the effectiveness of our adversarial sample privacy protection based on structural pruning.
Dynamic Modeling Approach in View of Vector Control and Behavior Analysis of a Multi-Three-Phase Star Permanent Magnet Synchronous Motor Drive
Authors: Mo Shu , Ziane Djamel , Oukrid Mouna , Benkhoris Mohamed Fouad , Bernard Nicolas
Published: March 2024

In order to fully utilize the control degrees of freedom of a multi-three-phase-star smooth-pole permanent magnet synchronous motor (PMSM), this paper first develops a modeling approach using a new matrix transformation method. The proposed transformation produces decoupled and independent star windings, removing the inductive couplings and preserving the model and torque control’s consistency as the number of phases increases. The model, together with a new vector control scheme, is superior for studying the effect of the winding phase angle shift on motor performance. Based on a numerical simulation, this paper focuses on the quality analysis of phase currents, non-sequential currents, and torque ripple with different phase angles for double- and triple-star PMSM drives. The control of a triple-star PMSM is validated, and the behavior analysis is investigated by OPAL-RT.
Integrating Compressed CO2 Energy Storage in an Integrated Energy System
Authors: Huang Qingxi , Song Yongxin , Sun Qie , Ren Xiaohan , Wang Wei
Published: March 2024

The integration of an energy storage system into an integrated energy system (IES) enhances renewable energy penetration while catering to diverse energy loads. In previous studies, the adoption of a battery energy storage (BES) system posed challenges related to installation capacity and capacity loss, impacting the technical and economic performance of the IES. To overcome these challenges, this study introduces a novel design incorporating a compressed CO2 energy storage (CCES) system into an IES. This integration mitigates the capacity loss issues associated with BES systems and offers advantages for configuring large-scale IESs. A mixed integer linear programming problem was formulated to optimize the configuration and operation of the IES. With an energy storage capacity of 267 MWh, the IES integrated with a CCES (IES–CCES) system incurred an investment cost of MUSD 161.9, slightly higher by MUSD 0.5 compared to the IES integrated with a BES (IES–BES) system. When not considering the capacity loss of the BES system, the annual operation cost of the IES–BES system was 0.5 MUSD lower than that of the IES–CCES system, amounting to MUSD 766.6. However, considering the capacity loss of the BES system, this study reveals that the operation cost of the IES–BES system surpassed that of the IES–CCES system beyond the sixth year. Over the 30-year lifespan of the IES, the total cost of the IES–CCES system was MUSD 4.4 lower than the minimum total cost of the IES–BES system.
Systematic Review of Bidirectional, Multiport Converter Structures and Their Derivatives: A Case Study of Bidirectional Dual Input Dual Output Converters
Authors: Alrubaie Ali Jawad , Swadi Mahmood , Salem Mohamed , Richelli Anna , Bughneda Ali , Kamarol Mohamad
Published: March 2024

This study thoroughly compares multiple single bidirectional and multiport converters (MPCs), highlighting the significant role of MPCs in multi-input and multi-output (MIMO) systems. MPCs offer a more efficient and cost-effective solution than multiple single converters, especially in applications involving photovoltaic (PV), electric vehicles (EVs) with storage systems, and power grids. This research emphasizes the importance of multi-input converters (MICs) in integrating diverse voltage sources. It notes the rising popularity of multi-output DC-DC converters in portable electronics, owing to their reduced component count, lower costs, and compact design. This paper emphasizes comparisons based on diverse aspects and applications, shedding light on recent developments in basic bidirectional converters. Additionally, it delves into the advancements in MPC topologies, focusing on efficiency, reliability, and modularity improvements. These advancements are crucial for harnessing cost reduction, simplicity, and compactness. Furthermore, this paper introduces an innovative multiport DC-DC converter tailored for integrating and managing renewable sources. This new converter design enhances PV system and battery storage performance by reducing power conversion steps, using fewer components, and improving voltage-boosting capabilities. Its unique bidirectional buck-boost structure allows for versatile connections between sources and loads with varying voltage and power requirements. The performance of this novel converter is evaluated through MATLAB/Simulink simulations under different scenarios. Experimental studies further validate its effectiveness, marking a significant contribution to power conversion and management in integrating renewable sources such as DC microgrids.
Unlocking Geothermal Energy: A Thorough Literature Review of Lithuanian Geothermal Complexes and Their Production Potential
Authors: Memon Abdul , Makauskas Pijus , Kaminskaite-Baranauskiene Ieva , Pal Mayur
Published: March 2024

Lithuania is located on the East of Baltic sedimentary basin and has a geothermal anomaly situated in the southwestern region of the country. There are two primary geothermal complexes within the anomaly, composed of Cambrian and Devonian aquifers. The Cambrian formation is composed of sandstones that have a reservoir temperature reaching up to 96 °C (depth > 2000 m). The Devonian aquifer is composed of unconsolidated sands of Parnu–Kemeri and has a reservoir temperature of up to 46 °C (depth > 1000 m). Historically, both formations have been investigated for geothermal energy production. In this article, we present a detailed literature review of the geothermal work carried out on both formations, including past, present, and some possible future studies. The study presented in this paper highlights the key findings of previous research work, summarizes the research gaps, and then elaborates on the possible applications of emerging technologies to bridge the research gaps and improve our understanding of geothermal complexes in Lithuania. Although it is not the main aim of this article, this article also touches upon the important need to develop 2D/3D numerical models, to quantify uncertainties, in the evaluation of the geothermal potential in Lithuania for commercial development. This study also highlights possibilities of extending geothermal development to depleted hydrocarbon reservoirs through repurposing the high-water-production wells. Moreover, from the literature review, it can be concluded that the Lithuanian geothermal aquifers are hyper-saline in nature and temperature changes lead to the deposition of salts both upstream and downstream of the reservoir. Therefore, there is a need for developing multiphysics thermo-mechanical–chemical (THMC) models for evaluation of reservoir behavior. The literature also describes the potential use and development of the THMC model as a part of future work that must be carried out.
Research on Wave Energy Converters
Authors: Lian Jijian , Wang Xiaowei , Wang Xiaoqun , Wu Dongke
Published: March 2024

With the acceleration of the global warming process, the clean energy crisis is becoming serious; conventional energy is unlikely to solve the current crisis, so people pay attention to new energy. As wave energy is widely distributed, renewable, and clean, hundreds of wave energy converters emerge. In order to understand the research progress of wave energy converters better, this paper divides wave energy converters into overtopping type, oscillating water column type, and oscillating body type according to the working principle and divides the oscillating body type into oscillating float type and oscillating pendulum type by different ways of energy capture. Based on the classification, various types of engineering cases, physical tests and digital simulation, and other academic research results are summarized, especially the generation power and energy conversion efficiency of various devices, and some shortcomings and suggestions are put forward, hoping to provide help for readers to study wave energy generation converters.
Shear Wave Velocity Applications in Geomechanics with Focus on Risk Assessment in Carbon Capture and Storage Projects
Authors: Khalilidermani Mitra , Knez Dariusz
Published: March 2024

Shear wave velocity (Vs) has significant applications in geoengineering investigations. With the ongoing rise in carbon capture and storage (CCS) initiatives, the role of Vs in monitoring the CO2 sequestration sites is escalating. Although many studies have been conducted to assess CCS-induced risks, no inclusive research has been conducted integrating those investigations. This study strives to collate and integrate the applications of Vs in geoscience with an emphasis on CCS risk assessment. Based on this research, major CCS-induced risks were detected: induced seismicity, caprock failure, groundwater contamination, fault reactivation, and reservoir deformation. These risks were inclusively described, and the mathematical formulations incorporating the Vs parameter in risk analysis were elaborated. It was concluded that Vs applications can be further extended in monitoring CO2 plume migration, optimizing CO2 injection pressures, preventing shallow water contamination, and predicting CCS-induced seismic events. All these applications require fully coupled hydromechanical analysis based on poroelasticity theory. Hence, various factors including pore pressure, in situ stresses, faults distribution, and poroelastic parameters must be carefully determined before the CO2 injection phase. The mathematical formulations presented in the present study are quite applicable for granting the safety and long-term success of subsurface carbon sequestration.
Comparative Analysis of Ground-Based Solar Irradiance Measurements and Copernicus Satellite Observations
Authors: Esposito Elena , Leanza Gianni , Di Francia Girolamo
Published: March 2024

Solar irradiance data provided by the Copernicus program are crucial for several scientific, environmental, and energy management applications, but their validation by means of ground-based measurements may be necessary, especially if daily and hourly data resolutions are required. The validation process not only ensures that reliable information is available for solar energy resource planning, power plant performance assessment, and grid integration, but also contributes to the improvement of the Copernicus system itself. Ground-based stations offer site-specific data, allowing for comprehensive assessments of the system’s performance. This work presents a comparative statistical analysis of solar irradiance data provided by the Copernicus system and ground-based measurements on a seasonal basis at three specific Italian reference sites, showing a maximum average relative error of less than 7% for hourly horizontal global irradiance in the irradiance range defined by the IEC 61724-2.
Artificial Intelligence for Energy Theft Detection in Distribution Networks
Authors: Žarković Mileta , Dobrić Goran
Published: March 2024

The digitization of distribution power systems has revolutionized the way data are collected and analyzed. In this paper, the critical task of harnessing this information to identify irregularities and anomalies in electricity consumption is tackled. The focus is on detecting non-technical losses (NTLs) and energy theft within distribution networks. A comprehensive overview of the methodologies employed to uncover NTLs and energy theft is presented, leveraging measurements of electricity consumption. The most common scenarios and prevalent cases of anomalies and theft among consumers are identified. Additionally, statistical indicators tailored to specific anomalies are proposed. In this research paper, the practical implementation of numerous artificial intelligence (AI) algorithms, including the artificial neural network (ANN), ANFIS, autoencoder neural network, and K-mean clustering, is highlighted. These algorithms play a central role in our research, and our primary objective is to showcase their effectiveness in identifying NTLs. Real-world data sourced directly from distribution networks are utilized. Additionally, we carefully assess how well statistical methods work and compare them to AI techniques by testing them with real data. The artificial neural network (ANN) accurately identifies various consumer types, exhibiting a frequency error of 7.62%. In contrast, the K-means algorithm shows a slightly higher frequency error of 9.26%, while the adaptive neuro-fuzzy inference system (ANFIS) fails to detect the initial anomaly type, resulting in a frequency error of 11.11%. Our research suggests that AI can make finding irregularities in electricity consumption even more effective. This approach, especially when using data from smart meters, can help us discover problems and safeguard distribution networks.
A Review of the Modeling of Parabolic Trough Solar Collectors Coupled to Solar Receivers with Photovoltaic/Thermal Generation
Authors: Chavarría-Domínguez Benjamín , De León-Aldaco Susana Estefany , Velázquez-Limón Nicolás , Ponce-Silva Mario , Aguilar-Jiménez Jesús Armando , Chavarría-Domínguez Fernando
Published: March 2024

This paper is a summary of the last ten years of work on the study of parabolic trough collectors (PTCs) and compound parabolic collectors (CPCs) coupled to photovoltaic and thermal solar receiver collectors (SCR-PVTs). While reviewing the state of the art, numerous review papers were found that focused on conventional solar receiver collector (SRC) technology for solar thermal generation. However, there is a lack of review papers summarizing SRC-PVT hybrid technology for solar electric/thermal generation, which would be beneficial for researchers interested in this area of research. This paper provides a review of SRC-PVT hybrid technologies. The theoretical foundations for analyzing and modeling PTC and CPC concentrators coupled to SRC-PVT are described, with an emphasis on modeling through thermal resistances and energy balances. Additionally, this section provides a concise overview of previous studies that have addressed the modeling of PTC and CPC collectors coupled to SCR-PVT, as well as experimental information useful for the validation of new mathematical models of SRC-PVT.
Research on Decision Optimization and the Risk Measurement of the Power Generation Side Based on Quantile Data-Driven IGDT
Authors: Liao Zhiwei , Wang Bowen , Tao Wenjuan , Liu Ye , Hu Qiyun
Published: March 2024

In an environment marked by dual carbon goals and substantial fluctuations in coal market prices, coal power generation enterprises face an urgent imperative to make scientifically informed decisions regarding production management amidst significant market uncertainties. To tackle this challenge, this paper proposes a methodology for optimizing electricity generation side market decisions and assessing risks using quantile data-driven information-gap decision theory (QDD-IGDT). Initially, a dual-layer decision optimization model for electricity production is formulated, taking into account coal procurement and blending processes. This model optimizes the selection of spot coal and long-term contract coal prices and simplifies the dual-layer structure into an equivalent single-layer model using the McCormick envelope and Karush–Kuhn–Tucker (KKT) conditions. Subsequently, a quantile dataset is generated utilizing a short-term coal price interval prediction model based on the quantile regression neural network (QRNN). Interval constraints on expected costs are introduced to develop an uncertainty decision risk measurement model grounded in QDD-IGDT, quantifying decision risks arising from coal market uncertainties to bolster decision robustness. Lastly, case simulations are executed by using real production data from a power generation enterprise, and the dual-layer decision optimization model is solved by employing the McCormick–KKT–Gurobi approach. Additionally, decision risks associated with coal market uncertainties are assessed through a one-dimensional search under interval constraints on expected cost volatility. The findings demonstrate the effectiveness of the proposed research methodology in cost optimization within the context of coal market uncertainties, underscoring its validity and economic efficiency.
A Risk Assessment Framework for Cyber-Physical Security in Distribution Grids with Grid-Edge DERs
Authors: Gao Xue , Ali Mazhar , Sun Wei
Published: March 2024

Integration of inverter-based distributed energy resources (DERs) is reshaping the landscape of distribution grids to fulfill the socioeconomic, environmental, and sustainability goals. Addressing the technological challenges of DER grid integration requires an adaptive communication layer for efficient DER management and control. This transition has given rise to a cyberphysical system (CPS) architecture within the distribution system, causing new vulnerabilities for cyberphysical attacks. To better address potential threats, this paper presents a comprehensive risk assessment framework for cyberphysical security in distribution grids with grid-edge DERs. The framework incorporates a detailed CPS model accounting for dynamic DER characteristics within the distribution grid. It identifies vulnerabilities in DER communication systems, models attack scenarios, and addresses communication latency crucial for inverter control timescales. Subsequently, the quantification of attack impacts employs an attack probability model including both the vulnerability and criticality of cyber components. The proposed risk assessment framework was validated through testing on the modified IEEE 13-node and 123-node test feeders.
Determination of Optimum Operating Parameters in a Non-Road Diesel Engine Fueled with 1-Heptanol/Biodiesel at Different Injection Pressures and Advances
Authors: Balki Mustafa Kemal
Published: March 2024

It is important to reduce the negative environmental effects of non-road diesel engines, which are increasingly used in many facilities and machines, without loss of performance. Biodiesel is used as an alternative to fossil-based diesel fuels to eliminate these effects and ensure sustainability in energy. This study focused on the optimization of the operating parameters of a non-road diesel engine operating with a waste frying oil biodiesel mixture at 50% load. Pure biodiesel, 1-heptanol, different injection advances and pressures were determined as input parameters for optimization. The tests were designed according to Taguchi’s L16 orthogonal array. ANOVA analysis was performed to determine the importance of input parameters on engine performance and exhaust emissions. Optimization was made based on the highest brake thermal efficiency (BTE) in addition to the lowest values of brake-specific fuel consumption (BSFC), brake-specific hydrocarbon (BSHC), brake-specific nitrogen oxide (BSNOx) and smoke emissions. In the optimization carried out according to the response surface methodology (RSM), the optimum combinations to obtain the best engine characteristics were determined as 17.27% 1-heptanol, a 226-bar injection pressure, 27 CAD injection advance and B75. These optimization results were verified by engine experiments within the recommended error range.
Assessing the Paradox of Autonomous Vehicles: Promised Fuel Efficiency vs. Aggregate Fuel Consumption
Authors: Mohammed Dilshad , Horváth Balázs
Published: March 2024

As autonomous vehicles (AVs) continue to evolve and approach widespread adoption in the near future, the touted benefits of improved fuel efficiency at an individual level come under scrutiny when considering the overall impact on fuel consumption. This research delves into the paradoxical relationship between the promising technology of AVs, their impact on traffic capacities, travel demand, and the subsequent influence on aggregate fuel consumption. While AVs have demonstrated enhanced fuel efficiency when considered as a singular mode of transportation, our study reveals a contrasting trend when scaled to a broader societal context. Through comprehensive analysis of the literature, we discovered that, at lower limits of energy savings achievable by a single AV, the overall fuel consumption increases by a staggering 42% compared to conventional human-driven vehicles. This counterintuitive outcome is a result of the aggregate effect of increased AV usage, leading to higher traffic volumes and travel demands. Conversely, at higher thresholds of energy savings by individual AVs, the percentage of fuel consumption increment diminishes, but remains notable. Even with advanced energy-saving features, the overall fuel quantity still experiences a substantial 30% increase compared to conventional vehicles when scaled up to widespread AV use. Our findings emphasize the importance of considering the holistic impact of AVs on transportation systems and energy consumption. As society transitions towards AV-dominated traffic, policymakers and stakeholders must address the challenges associated with increased travel demand, potential traffic congestion, and the resultant implications on fuel consumption.
Classification of Highly Imbalanced Supervisory Control and Data Acquisition Data for Fault Detection of Wind Turbine Generators
Authors: Maldonado-Correa Jorge , Valdiviezo-Condolo Marcelo , Artigao Estefanía , Martín-Martínez Sergio , Gómez-Lázaro Emilio
Published: March 2024

It is common knowledge that wind energy is a crucial, strategic component of the mix needed to create a green economy. In this regard, optimizing the operations and maintenance (O&M) of wind turbines (WTs) is key, as it will serve to reduce the levelized cost of electricity (LCOE) of wind energy. Since most modern WTs are equipped with a Supervisory Control and Data Acquisition (SCADA) system for remote monitoring and control, condition-based maintenance using SCADA data is considered a promising solution, although certain drawbacks still exist. Typically, large amounts of normal-operating SCADA data are generated against small amounts of fault-related data. In this study, we use high-frequency SCADA data from an operating WT with a significant imbalance between normal and fault classes. We implement several resampling techniques to address this challenge and generate synthetic generator fault data. In addition, several machine learning (ML) algorithms are proposed for processing the resampled data and WT generator fault classification. Experimental results show that ADASYN + Random Forest obtained the best performance, providing promising results toward wind farm O&M optimization.
Anodized TiO2 Nanotubes Sensitized with Selenium Doped CdS Nanoparticles for Solar Water Splitting
Authors: Alfaro Chacón Julián , Cerdán-Pasarán Andrea , Zarazúa Isaac , Ramos-Galicia Lourdes , Hernández-Magallanes J. A. , Sanal K. C. , Lugo Loredo Shadai , Hernández-López Juan Manuel
Published: March 2024

In this research, TiO2 nanotubes (NTs) were produced by electrochemical anodization of a Ti substrate where different NH4F wt.% in the electrolyte was added. NTs with diameter of 65–90 nm and 3.3–4.9 µm length were obtained and sensitized with binary cadmium chalcogenides nanoparticles, CdS and CdSe, by successive ionic layer adsorption and reaction method (SILAR). Additionally, both anions S and Se were deposited onto Cd, labeled as CdSSe and CdSeS, to evaluate the effect of the deposition order of the anion from the precursor solution to form cadmium chalcogenides. The structural, optical, and electrochemical performance were analyzed through the SEM, XRD, XPS, UV-VIS, lineal voltammetry and chronoamperometry characterizations. The increase of NH4F wt.% from 1.5% to 4.5% produced a decrement of the diameter and length attributed to the fluoride ions concentration causing solubility of the NTs. XRD confirmed the TiO2 anatase and hexagonal CdS structures. From the EDS and XPS results, the presence of small amount of Se in the sensitized samples demonstrated the doping effect of Se instead of forming ternary semiconductor. With the sensitization of the TiO2 NTs with the nanoparticles, an improved hydrogen generation was observed (reaching 1.068 mL h−1 cm−2) in the sample with CdSSe. The improvement was associated to a synergetic effect in the light absorption and higher cadmium chalcogenide amount deposited when sulfur ions were deposited before selenium.
Current Progress and Development Trend of Gas Injection to Enhance Gas Recovery in Gas Reservoirs
Authors: Lin Baicen , Wei Yunsheng , Gao Shusheng , Ye Liyou , Liu Huaxun , Zhu Wenqing , Zhang Jianzhong , Han Donghuan
Published: March 2024

Conventional recovery enhancement techniques are aimed at reducing the abandonment pressure, but there is an upper limit for recovery enhancement due to the energy limitation of reservoirs. Gas injection for energy supplementation has become an effective way to enhance gas recovery by reducing hydrocarbon saturation in gas reservoirs. This review systematically investigates progress in gas injection for enhanced gas recovery in three aspects: experiments, numerical simulations and field examples. It summarizes and analyzes the current research results on gas injection for EGR and explores further prospects for future research. The research results show the following: (1) Based on the differences in the physical properties of CO2, N2 and natural gas, effective cushion gas can be formed in bottom reservoirs after gas injection to achieve the effects of pressurization, energy replenishment and gravity differentiation water resistance. However, further experimental evaluation is needed for the degree of increase in penetration ability. (2) It is more beneficial to inject N2 before CO2 or the mixture of N2 and CO2 in terms of EGR effect and cost. (3) According to numerical simulation studies, water drive and condensate gas reservoirs exhibit significant recovery effects, while CO2-EGR in depleted gas reservoirs is more advantageous for burial and storage; current numerical simulations only focus on mobility mass and saturation changes and lack a mixed-phase percolation model, which leads to insufficient analysis of injection strategies and a lack of distinction among different gas extraction effects. Therefore, a mixed-phase-driven percolation model that can characterize the fluid flow path is worth studying in depth. (4) The De Wijk and Budafa Szinfelleti projects have shown that gas injection into water drive and depleted reservoirs has a large advantage for EGR, as it can enhance recovery by more than 10%. More experiments, simulation studies and demonstration projects are needed to promote the development of gas injection technology for enhanced recovery in the future.
Dissolved Iron and Organic Matter in Boreal Rivers across a South–North Transect
Authors: Aleshina Alisa , Rusakova Maria-Anna , Drozdova Olga Y. , Pokrovsky Oleg S. , Lapitskiy Sergey A.
Published: March 2024

Iron (Fe) is one of the main nutrients present in dissolved, suspended, and colloidal states in river water. Predicting the composition and size of dissolved Fe compounds is crucial for assessing water quality. In this stud, we used a combination of physical methods (filtration), chemical techniques (ion exchange chromatography), and thermodynamic modeling (Visual MINTEQ) to characterize dissolved Fe speciation in boreal organic-rich rivers across a sizable south–north transect. We chose contrasting rivers with a predominance of either allochthonous or autochthonous organic compounds. We found that the dissolved organic matter (DOM) in the studied rivers varies in molecular weights and the degree of humification. Regardless of the climate parameters of the river watershed, the dominant status of dissolved Fe during the summer low-water period was essentially colloidal and dominated by anionic complexes of the type [MeL]n−.
Insights into the Paulownia Shan tong (Fortunei × Tomentosa) Essential Oil and In Silico Analysis of Potential Biological Targets of Its Compounds
Authors: Jianu Călin , Mioc Marius , Mioc Alexandra , Șoica Codruța , Lukinich-Gruia Alexandra Teodora , Bujancă Gabriel , Rădulescu Matilda
Published: March 2024

The volatile composition of Paulownia Shan tong (Fortunei × Tomentosa) essential oil isolated by steam distillation (yielding 0.013% v/w) from flowers (forestry wastes) was investigated by gas chromatography–mass spectrometry. Thirty-one components were identified, with 3-acetoxy-7, 8-epoxylanostan-11-ol (38.16%), β-monoolein (14.4%), lycopene, 1,2-dihydro-1-hydroxy- (10.21%), and 9,12-octadecadienoic acid, 2-phenyl-1,3-dioxan-5-yl ester (9.21%) as main compounds. In addition, molecular docking was employed to identify potential protein targets for the 31 quantified essential oil components. Inhibition of these targets is typically associated with antibacterial or antioxidant properties. Molecular docking revealed that six of these components, namely, 13-heptadecyn-1-ol, ascabiol, geranylgeraniol, anethole, and quinol dimethyl ether, outperformed the native ligand (hypoxanthine) of xanthine oxidase in terms of theoretical binding affinity, therefore implying a significant in silico inhibitory potential against xanthine oxidase. These findings suggest that the essential oil extracted from Paulownia Shan tong flowers could be valuable for developing protein-targeted antioxidant compounds with applications in the food, pharmaceutical, and cosmetic industries.
Metabolic and Bioprocess Engineering of Clostridium tyrobutyricum for Butyl Butyrate Production on Xylose and Shrimp Shell Waste
Authors: Wang Hao , Chen Yingli , Yang Zhihan , Deng Haijun , Liu Yiran , Wei Ping , Zhu Zhengming , Jiang Ling
Published: March 2024

Microbial conversion of agri-food waste to valuable compounds offers a sustainable route to develop the bioeconomy and contribute to sustainable biorefinery. Clostridium tyrobutyricum displays a series of native traits suitable for high productivity conversion of agri-food waste, which make it a promising host for the production of various compounds, such as the short-chain fatty acids and their derivative esters products. In this study, a butanol synthetic pathway was constructed in C. tyrobutyricum, and then efficient butyl butyrate production through in situ esterification was achieved by the supplementation of lipase into the fermentation. The butyryl-CoA/acyl-CoA transferase (cat1) was overexpressed to balance the ratio between precursors butyrate and butanol. Then, a suitable fermentation medium for butyl butyrate production was obtained with xylose as the sole carbon source and shrimp shell waste as the sole nitrogen source. Ultimately, 5.9 g/L of butyl butyrate with a selectivity of 100%, and a productivity of 0.03 g/L·h was achieved under xylose and shrimp shell waste with batch fermentation in a 5 L bioreactor. Transcriptome analyses exhibited an increase in the expression of genes related to the xylose metabolism, nitrogen metabolism, and amino acid metabolism and transport, which reveal the mechanism for the synergistic utilization of xylose and shrimp shell waste. This study presents a novel approach for utilizing xylose and shrimp shell waste to produce butyl butyrate by using an anaerobic fermentative platform based on C. tyrobutyricum. This innovative fermentation medium could save the cost of nitrogen sources (~97%) and open up possibilities for converting agri-food waste into other high-value products.
Evaluation of Potential Probiotic Properties and In Vivo Safety of Lactic Acid Bacteria and Yeast Strains Isolated from Traditional Home-Made Kefir
Authors: Maione Angela , Imparato Marianna , Buonanno Annalisa , Salvatore Maria Michela , Carraturo Federica , de Alteriis Elisabetta , Guida Marco , Galdiero Emilia
Published: March 2024

Probiotics are known for their health-promoting resources and are considered as beneficial microorganisms. The current study focuses on the isolation, and on a complete in vitro and in vivo characterization, of yeast and lactic acid bacteria acquired from traditional homemade kefir in order to assess their potentiality as probiotic candidates. In particular, the isolates Pichia kudriavzevii Y1, Lactococcus lactis subsp. hordniae LAB1 and Lactococcus lactis subsp. lactis LAB2 were subjected to in vitro characterization to evaluate their suitability as probiotics. Resistance to acid and bile salts, auto-aggregation, co-aggregation, hydrophobicity, and biofilm production capability were examined, as well as their antioxidant activity. A safety assessment was also conducted to confirm the non-pathogenic nature of the isolates, with hemolysis assay and antibiotic resistance assessment. Moreover, mortality in the invertebrate model Galleria mellonella was evaluated. Current findings showed that P. kudriavzevii exhibited estimable probiotic properties, placing them as promising candidates for functional foods. Both lactic acid bacteria isolated in this work could be classified as potential probiotics with advantageous traits, including antimicrobial activity against enteric pathogens and good adhesion ability on intestinal cells. This study revealed that homemade kefir could be a beneficial origin of different probiotic microorganisms that may enhance health and wellness.
Development of Green Disaster Management Toolkit to Achieve Carbon Neutrality Goals in Flood Risk Management
Authors: Cheong Tae Sung , Jeong Sangman
Published: March 2024

Current flood risk management projects have been criticized for their high carbon emissions, raising the need for carbon emission reduction and carbon absorption efforts to mitigate environmental impacts and achieve carbon neutrality goals. The research develops a comprehensive green disaster risk management toolkit to calculate the carbon emissions and absorption quantitatively based on the unit volume of materials and processes employed in a flood risk management project. As a result of applying the developed toolkit to a about 22,300 small stream restoration projects in Korea, the total carbon emissions were estimated to be 1,158,840.7 tons of CO2, of which 89.4% of the total carbon emissions originated from concrete-related construction activities, such as cement and ready-mixed concrete pouring. As a result of evaluating the nationwide carbon absorption results of all small stream restoration projects, total absorption by 2030 is expected to be 3.0 to 10.2 times higher than carbon emissions. The comprehensive toolkits are expected to support the selection of customized processes, materials, and methods by providing a systematic approach to calculate and minimize carbon emissions, ultimately contributing to the achievement of carbon neutrality goals in flood risk management projects.
The PD-1/PD-L1 Axis in the Biology of MASLD
Authors: Pipitone Rosaria Maria , Lupo Giulia , Zito Rossella , Javed Ayesha , Petta Salvatore , Pennisi Grazia , Grimaudo Stefania
Published: March 2024

Metabolic Dysfunction-Associated Steatotic Liver (MASL), previously named nonalcoholic fatty liver (NAFL), is a multifactorial disease in which metabolic, genetic, and environmental risk factors play a predominant role. Obesity and type 2 diabetes act as triggers of the inflammatory response, which contributes to the progression of MASL to Metabolic Dysfunction-Associated Steatohepatitis and the development of hepatocellular carcinoma. In the liver, several parenchymal, nonparenchymal, and immune cells maintain immunological homeostasis, and different regulatory pathways balance the activation of the innate and adaptative immune system. PD-1/PD-L1 signaling acts, in the maintenance of the balance between the immune responses and the tissue immune homeostasis, promoting self-tolerance through the modulation of activated T cells. Recently, PD-1 has received much attention for its roles in inducing an exhausted T cells phenotype, promoting the tumor escape from immune responses. Indeed, in MASLD, the excessive fat accumulation dysregulates the immune system, increasing cytotoxic lymphocytes and decreasing their cytolytic activity. In this context, T cells exacerbate liver damage and promote tumor progression. The aim of this review is to illustrate the main pathogenetic mechanisms by which the immune system promotes the progression of MASLD and the transition to HCC, as well as to discuss the possible therapeutic applications of PD-1/PD-L1 target therapy to activate T cells and reinvigorate immune surveillance against cancer.
The Cellular Respiration of Endometrial Biopsies from Patients with Various Forms of Endometriosis
Authors: Toniyan Konstantin A. , Malkov Artyom A. , Biryukov Nikolay S. , Gorbacheva Elena Yu. , Boyarintsev Valery V. , Ogneva Irina V.
Published: March 2024

Endometriosis is one of the leading pathologies of the reproductive system of women of fertile age, which shows changes in cell metabolism in the lesions. We conducted a study of the cellular respiration according to the polarography and the mRNA content of the main metabolic proteins using qRT-PCR of intraoperative endometrial biopsies from patients in the control group and with different localizations of endometriosis (adenomyosis, endometrioma, pelvic peritoneum). In biopsy samples of patients with endometriomas and pelvic peritoneum endometriotic lesions, the rate of oxygen absorption was significantly reduced, and, moreover, in the extragenital case, there was a shift to succinate utilization. The mRNA content of the cytochrome c, cytochrome c oxidase, and ATP synthase was also reduced, but hexokinase HK2 as well as pyruvate kinase were significantly higher than in the control. These oxidative phosphorylation and gene expression profiles suggest the Warburg effect and a shift in metabolism toward glycolysis. For adenomyosis, on the contrary, cellular respiration was significantly higher than in the control group due to the terminal region of the respiratory chain, ATP synthase, and its mRNA was increased as well. These data allow us to suggest that the therapeutic strategies of endometriosis based on modulation energy metabolism should take lesion localization into account.
Mapping of a Major-Effect Quantitative Trait Locus for Seed Dormancy in Wheat
Authors: Gao Yu , Qiao Linyi , Mei Chao , Nong Lina , Li Qiqi , Zhang Xiaojun , Li Rui , Gao Wei , Chen Fang , Chang Lifang , Zhang Shuwei , Guo Huijuan , Cheng Tianling , Wen Huiqin , Chang Zhijian , Li Xin
Published: March 2024

The excavation and utilization of dormancy loci in breeding are effective endeavors for enhancing the resistance to pre-harvest sprouting (PHS) of wheat varieties. CH1539 is a wheat breeding line with high-level seed dormancy. To clarify the dormant loci carried by CH1539 and obtain linked molecular markers, in this study, a recombinant inbred line (RIL) population derived from the cross of weak dormant SY95-71 and strong dormant CH1539 was genotyped using the Wheat17K single-nucleotide polymorphism (SNP) array, and a high-density genetic map covering 21 chromosomes and consisting of 2437 SNP markers was constructed. Then, the germination percentage (GP) and germination index (GI) of the seeds from each RIL were estimated. Two QTLs for GP on chromosomes 5A and 6B, and four QTLs for GI on chromosomes 5A, 6B, 6D and 7A were identified. Among them, the QTL on chromosomes 6B controlling both GP and GI, temporarily named QGp/Gi.sxau-6B, is a major QTL for seed dormancy with the maximum phenotypic variance explained of 17.66~34.11%. One PCR-based diagnostic marker Ger6B-3 for QGp/Gi.sxau-6B was developed, and the genetic effect of QGp/Gi.sxau-6B on the RIL population and a set of wheat germplasm comprising 97 accessions was successfully confirmed. QGp/Gi.sxau-6B located in the 28.7~30.9 Mbp physical position is different from all the known dormancy loci on chromosomes 6B, and within the interval, there are 30 high-confidence annotated genes. Our results revealed a novel QTL QGp/Gi.sxau-6B whose CH1539 allele had a strong and broad effect on seed dormancy, which will be useful in further PHS-resistant wheat breeding.
Discrimination of Etiologically Different Cholestasis by Modeling Proteomics Datasets
Authors: Guerrero Laura , Vindel-Alfageme Jorge , Hierro Loreto , Stark Luiz , Vicent David , Sorzano Carlos Óscar S. , Corrales Fernando J.
Published: March 2024

Cholestasis is characterized by disrupted bile flow from the liver to the small intestine. Although etiologically different cholestasis displays similar symptoms, diverse factors can contribute to the progression of the disease and determine the appropriate therapeutic option. Therefore, stratifying cholestatic patients is essential for the development of tailor-made treatment strategies. Here, we have analyzed the liver proteome from cholestatic patients of different etiology. In total, 7161 proteins were identified and quantified, of which 263 were differentially expressed between control and cholestasis groups. These differential proteins point to deregulated cellular processes that explain part of the molecular framework of cholestasis progression. However, the clustering of different cholestasis types was limited. Therefore, a machine learning pipeline was designed to identify a panel of 20 differential proteins that segregate different cholestasis groups with high accuracy and sensitivity. In summary, proteomics combined with machine learning algorithms provides valuable insights into the molecular mechanisms of cholestasis progression and a panel of proteins to discriminate across different types of cholestasis. This strategy may prove useful in developing precision medicine approaches for patient care.
Harnessing Graphene-Modified Electrode Sensitivity for Enhanced Ciprofloxacin Detection
Authors: Mǎgeruşan Lidia , Pogǎcean Florina , Cozar Bogdan-Ionuţ , Tripon Septimiu-Cassian , Pruneanu Stela
Published: March 2024

Increased evidence has documented a direct association between Ciprofloxacin (CFX) intake and significant disruption to the normal functions of connective tissues, leading to severe health conditions (such as tendonitis, tendon rupture and retinal detachment). Additionally, CFX is recognized as a potential emerging pollutant, as it seems to impact both animal and human food chains, resulting in severe health implications. Consequently, there is a compelling need for the precise, swift and selective detection of this fluoroquinolone-class antibiotic. Herein, we present a novel graphene-based electrochemical sensor designed for Ciprofloxacin (CFX) detection and discuss its practical utility. The graphene material was synthesized using a relatively straightforward and cost-effective approach involving the electrochemical exfoliation of graphite, through a pulsing current, in 0.05 M sodium sulphate (Na2SO4), 0.05 M boric acid (H3BO3) and 0.05 M sodium chloride (NaCl) solution. The resulting material underwent systematic characterization using scanning electron microscopy/energy dispersive X-ray analysis, X-ray powder diffraction and Raman spectroscopy. Subsequently, it was employed in the fabrication of modified glassy carbon surfaces (EGr/GC). Linear Sweep Voltammetry studies revealed that CFX experiences an irreversible oxidation process on the sensor surface at approximately 1.05 V. Under optimal conditions, the limit of quantification was found to be 0.33 × 10−8 M, with a corresponding limit of detection of 0.1 × 10−8 M. Additionally, the developed sensor’s practical suitability was assessed using commercially available pharmaceutical products.