bluuebunny/crossref_metadata_2025 huggingface dataset:
Four-Dimensional Trajectory Planning Algorithm for Fixed-Wing Aircraft Formation Based on Improved Hunter—Prey Optimization
Authors: Wei Jianli , Fan Hongjia , Li Jinghao
Published: June 2023

The aircraft four-dimensional trajectory planning is an important technology for multiple aircraft to achieve cooperation. However, the current four-dimensional trajectory planning technology is mainly used for civil aviation and helicopters and is difficult to meet the requirements of fixed-wing aircraft. This paper proposed a four-dimensional trajectory planning algorithm for a fixed-wing aircraft formation, considering the speed range, turning radius and maximum overload. The improved tau-J strategy (ITJS) is used to generate the four-dimensional trajectory of the aircraft. This strategy is a bio-inspired trajectory planning algorithm that can generate a four-dimensional trajectory with continuous acceleration. Furthermore, the improved hunter–prey optimization (IHPO) algorithm is used to optimize the trajectory to make the generated trajectory meet the constraints and speed up the algorithm convergence. This algorithm improves the updated strategy and initialization strategy based on the hunter–prey optimization (HPO) algorithm, which prevents the algorithm from falling into local optima. The results of the benchmark test function show that the optimization result of the algorithm is improved by more than 10% compared with the original HPO algorithm. The simulation results show that the proposed algorithm jumps out of local optima and generates a trajectory that meets the constraints.
YOLO-MBBi: PCB Surface Defect Detection Method Based on Enhanced YOLOv5
Authors: Du Bowei , Wan Fang , Lei Guangbo , Xu Li , Xu Chengzhi , Xiong Ying
Published: June 2023

Printed circuit boards (PCBs) are extensively used to assemble electronic equipment. Currently, PCBs are an integral part of almost all electronic products. However, various surface defects can still occur during mass production. An enhanced YOLOv5s network named YOLO-MBBi is proposed to detect surface defects on PCBs to address the shortcomings of the existing PCB surface defect detection methods, such as their low accuracy and poor real-time performance. YOLO-MBBi uses MBConv (mobile inverted residual bottleneck block) modules, CBAM attention, BiFPN, and depth-wise convolutions to substitute layers in the YOLOv5s network and replace the CIoU loss function with the SIoU loss function during training. Two publicly available datasets were selected for this experiment. The experimental results showed that the mAP50 and recall values of YOLO-MBBi were 95.3% and 94.6%, which were 3.6% and 2.6% higher than those of YOLOv5s, respectively, and the FLOPs were 12.8, which was much smaller than YOLOv7’s 103.2. The FPS value reached 48.9. Additionally, after using another dataset, the YOLO-MBBi metrics also achieved satisfactory accuracy and met the needs of industrial production.
Joint Packet Length and Power Optimization for Covert Short-Packet D2D Communications
Authors: Zhang Xiaolong , Liu Jie , Huang Yuzhen
Published: June 2023

This paper proposes a joint optimization mechanism for packet length and power in the scenario of covert short packet D2D communication, so as to effectively improve the communication performance between D2D pairs subject to the covert constraint. Specifically, we construct a short-packet D2D communication model assisted by covert communication, and further propose the notion of effective covert throughput (ECT) to quantitatively characterize the trade-off between the covertness and reliability of IoT state monitoring information transmission. Secondly, in the constructed communication scenario, we analyze the detection error probability of the warden and clarify that the existing equal power transmission of pilot and data signals can minimize the detection performance of the warden. However, this strategy is achieved by compromising the transmission performance of the system, which means that the ECT of D2D pair may not be optimal. Thirdly, we aim to maximize the ECT of D2D pair and construct a joint optimization problem for pilot transmission power, data transmission power, and packet length. Furthermore, a joint optimization algorithm based on the 2D search is adopted to obtain the optimal solution of the established optimization problem. Simulation results demonstrated that the transmission performance of the joint optimization algorithm is better than that of the scheme of the equal power scheme on the premise of ensuring the covertness.
Medium-Voltage Testbed for Comparing Advanced Power Line Sensors vs. Measurement Transformers with Electrical Grid Events
Authors: Piesciorovsky Emilio C. , Warmack R. J. Bruce , Polsky Yarom
Published: June 2023

Electrical utilities have relied upon potential transformers (PTs) and current transformers (CTs) for very accurate metering and to provide reliable signals for protective relays. Less expensive alternative sensing technologies offer the possibility of wider deployment, particularly in grids that employ distributed energy resources. In this work, the performance of an advanced medium-voltage sensor is compared with that of a reference PT and a CT and experimentally evaluated for different power grid scenarios on an advanced outdoor power line sensor testbed at the U.S. Department of Energy’s Oak Ridge National Laboratory. The sensor is based on a capacitive divider for voltage monitoring and a Rogowski coil with an integrator for current monitoring. The advanced outdoor power line sensor testbed has a real-time simulator that is used to generate transient scenarios (e.g., electrical faults, capacitor bank operation, and service restoration), while the analog signals are recorded by the same high-resolution power meter. The behaviors of analog signals, harmonic components, total harmonic distortion, and crest factors are assessed for this power line sensor and compared with those of the reference PT/CT because of the absence of testing standards for advanced outdoor power line sensors.
Can Xylose Be Fermented to Biofuel Butanol in Continuous Long-Term Reactors: If Not, What Options Are There?
Authors: Qureshi Nasib , Lin Xiaoqing , Tao Shunhui , Liu Siqing , Huang Haibo , Nichols Nancy N.
Published: June 2023

This study applied concentrated xylose (60–250 g/L) medium to produce butanol (acetone butanol ethanol, or ABE). A control batch fermentation of 61 g/L initial glucose using Clostridium beijerinckii P260 resulted in a productivity and yield of 0.33 g/L·h and 0.43 g/g, respectively. Use of 60 g/L xylose in a batch system resulted in productivity and yield of 0.26 g/L·h, and 0.40 g/g, respectively. In these two experiments, the culture fermented 89.3% glucose and 83.6% of xylose, respectively. When ABE recovery was coupled with fermentation for continuous solvent removal, the culture fermented all the added xylose (60 g/L). This system resulted in a productivity and yield of 0.66 g/L·h and 0.44 g/g, respectively. When the sugar concentration was further increased above 100 g/L, only a small fraction of the sugar was fermented in batch cultures without product removal. However, with simultaneous product removal, all the xylose (150 g/L) was fermented provided the culture was fed with nutrients intermittently. In this system, 66.32 g/L ABE was produced from 150 g/L xylose with a productivity of 0.44 g/L·h and yield of 0.44 g/g. Using the integrated culture system allowed sugar consumption to be increased by 300% (150 g/L). The continuous system using xylose as a feed did not sustain and after 36 days (864 h) of fermentation, it produced only 2–3 g/L ABE. Rather, the culture became acidogenic and produced 4–5 g/L acids (acetic and butyric). This study suggested that xylose be fermented in batch reactors coupled with simultaneous product recovery rather than in continuous reactors.
A One-Dimensional Numerical Model for High-Performance Two-Stroke Engines
Authors: Ortenzi Fernando , Bossaglia Andrea
Published: June 2023

Computer software that simulates the thermodynamic and gas dynamic properties of internal combustion engines can play a significant role in the design and optimization of internal combustion engines. In the present work, a quasi-dimensional numerical model for two-stroke engines is presented. Particular attention was paid to reporting in-cylinder models, combustion (turbulent with flame development and flame–wall interaction), and turbulence (K-k-ϵ model), with the addition of tumble- and squish-generated turbulence that is quite common in such engines. The aim was to reduce the role of the calibration constants, which are fundamental for correlating the models with the experiments, and relations for calculating the tumble ratio and turbulent scales were reported. A one-dimensional model for manifolds is also presented (solving the Euler equations), using the second-order Roe Riemann solver with some improvements, paying particular attention to the source terms, such as area variation. Additionally, a new approach to the end-pipe boundaries, which would reduce the mass conservation error, is reported. The engines tested were two kart two-stroke engines, used for racing purposes: the IAME X30 engine and the IAME Screamer III KZ engine. A comparison between the model results and the experimental data was made, and good accordance was observed, with a root mean square error of about 0.5 kW and providing good accuracy in evaluating changes, such as the combustion chamber squish area and the exhaust pipe length.
Impedance Spectroscopy Analysis of Perovskite Solar Cell Stability
Authors: Matacena Ilaria , Guerriero Pierluigi , Lancellotti Laura , Alfano Brigida , De Maria Antonella , La Ferrara Vera , Mercaldo Lucia V. , Miglietta Maria Lucia , Polichetti Tiziana , Rametta Gabriella , Sannino Gennaro V. , Delli Veneri Paola , Daliento Santolo
Published: June 2023

The aim of this work is to investigate the degradation of perovskite solar cells (PSCs) by means of impedance spectroscopy, a highly sensitive characterization technique used to establish the electrical response of a device in a nondestructive manner. In this paper, PSCs with two different electron transport layers (ETLs) are studied: PSCs with undoped SnO2 as an ETL are compared to PSCs with an ETL composed of graphene-doped SnO2 (G-SnO2). Experimental data were collected immediately after fabrication and after one week, monitoring both impedance spectroscopy and dark current-voltage (I-V) curves. It was observed that, in the case of the undoped PSCs, the degradation of the solar cells affected both the AC behavior of the devices, modifying the associated Nyquist plots, and the DC behavior, observable from the dark I-V measurements. Conversely, the solar cells with G-SnO2 showed no variation. Considering the Nyquist plots, a quantitative analysis was performed by comparing the parameters of a proper equivalent circuit model. The results were coherent with those achieved in the DC analysis, thus proving that the analysis of impedance spectra, supported with dark I-V curves, allows one to gain a deeper knowledge of the degradation phenomena of perovskite solar cells. This study opens the door for further improvement of these devices through a better understanding of their electrical behavior.
Fault Arc Detection Based on Channel Attention Mechanism and Lightweight Residual Network
Authors: Gao Xiang , Zhou Gan , Zhang Jian , Zeng Ying , Feng Yanjun , Liu Yuyuan
Published: June 2023

An arc fault is the leading cause of electrical fire. Aiming at the problems of difficulty in manually extracting features, poor generalization ability of models and low prediction accuracy in traditional arc fault detection algorithms, this paper proposes a fault arc detection method based on the fusion of channel attention mechanism and residual network model. This method is based on the channel attention mechanism to perform global average pooling of information from each channel of the feature map assigned by the residual block while ignoring the local spatial data to enhance the detection and recognition rate of the fault arc. This paper introduces a one-dimensional depth separable convolution (1D-DS) module to reduce the network model parameters and shorten the time of single prediction samples. The experimental results show that the F1 score of the network model for arc fault detection under mixed load conditions is 98.07%, and the parameter amount is reduced by 46.06%. The method proposed in this paper dramatically reduces the parameter quantity, floating-point number and time complexity of the network structure while ensuring a high recognition rate, which improves the real-time response ability to detect arc fault. It has a guiding significance for applying arc fault on the edge side.
Techno-Economic Analysis of Solid Oxide Fuel Cell-Gas Turbine Hybrid Systems for Stationary Power Applications Using Renewable Hydrogen
Authors: Chan Chun , Rosner Fabian , Samuelsen Scott
Published: June 2023

Solid oxide fuel cell (SOFC)–gas turbine (GT) hybrid systems can produce power at high electrical efficiencies while emitting virtually zero criteria pollutants (e.g., ozone, carbon monoxide, oxides of nitrogen and sulfur, and particulate matters). This study presents new insights into renewable hydrogen (RH2)-powered SOFC–GT hybrid systems with respect to their system configuration and techno-economic analysis motivated by the need for clean on-demand power. First, three system configurations are thermodynamically assessed: (I) a reference case with no SOFC off-gas recirculation, (II) a case with cathode off-gas recirculation, and (III) a case with anode off-gas recirculation. While these configurations have been studied in isolation, here we provide a detailed performance comparison. Moreover, a techno-economic analysis is conducted to study the economic competitiveness of RH2-fueled hybrid systems and the economies of scale by offering a comparison to natural gas (NG)-fueled systems. Results show that the case with anode off-gas recirculation, with 68.50%-lower heating value (LHV) at a 10 MW scale, has the highest efficiency among the studied scenarios. When moving from 10 MW to 50 MW, the efficiency increases to 70.22%-LHV. These high efficiency values make SOFC–GT hybrid systems highly attractive in the context of a circular economy as they outcompete most other power generation technologies. The cost-of-electricity (COE) is reduced by about 10% when moving from 10 MW to 50 MW, from USD 1976/kW to USD 1668/kW, respectively. Renewable H2 is expected to be economically competitive with NG by 2030, when the U.S. Department of Energy’s target of USD 1/kg RH2 is reached.
Techno-Economic and Environmental Perspectives of Solar Cell Technologies: A Comprehensive Review
Authors: Nazir Shoaib , Ali Asjad , Aftab Abdullah , Muqeet Hafiz Abdul , Mirsaeidi Sohrab , Zhang Jian-Min
Published: June 2023

This paper provides a review of the implementation of different materials and how they have impacted the efficiency of solar cells. This work elaborates on all solar generation methods that have been developed in the past and covers disparate technologies that are being implemented in different generations. A review of the characterization and factors involved in these processes are also discussed briefly. Furthermore, the economic, environmental, and technical perspectives related to solar cells have also been expounded. This paper also provides some insights into potential research directions that can be pursued in the field of solar energy. Energy demands are increasing all over the world, and substantial amounts of fossil fuels are currently exhausted all over the world in order to meet those needs, which in turn contaminates our environment; moreover, non-renewable sources of energy are diminishing at higher rates as well. Solar energy is of prime importance in all renewable energy sources as the Sun shines at the Earth for 8 to 10 h on average. Thus, heat can be harnessed to generate electricity, but solar cells are not substantially efficient because the materials used in them are quite costly and waste a considerable amount of energy, mostly as heat, which subsequently reduces the efficiency of the cell and increases the overall price as well. These challenges can be dealt with by designing more efficient, economical systems of storage and manufacturing PV cells with high efficacy. Scientists and engineers are more inclined toward advanced technologies and material manipulation to enhance the efficiency of solar energy and reduce its cost. In this regard, substantial research is being carried out, especially on the structure of materials and advanced materials like nanomaterials and quantum dots. Due to their distinct electromechanical and material properties, carbon-based nanomaterials like carbon nanotubes, graphene, fullerene, and nanohybrids are being employed as the electrodes, transport layers, active layers, or intermediate (interfacial) layers of solar cells in this regard.
Analysis of the Energy and Economic Effects of Green Remodeling for Old Buildings: A Case Study of Public Daycare Centers in South Korea
Authors: Cho Jeong-Heum , Bae Sangmu , Nam Yujin
Published: June 2023

In South Korea, green remodeling policies have been promoted to improve the energy performance of buildings, especially old buildings. Moreover, simultaneous improvement of both energy and structural performance has emerged as an important issue. Although several proposals have been made by different governments for the improvement of energy and structural performance, most were related to technological development or construction methods. Therefore, to simultaneously improve the energy and structural performance of old buildings, in this study, we performed an analysis to evaluate the feasibility of improvement based on an actual case of green remodeling of an old building. In addition, the expected social effects were analyzed by examining the effect of fiscal expenditure on employment, considering personnel and operating expenses. As a result, primary energy consumption was reduced by approximately ≥48% after green remodeling, and CO2 emissions during the building operation stage were reduced by approximately ≥46%. When green remodeling and structural retrofitting were performed concurrently, the construction cost was reduced by approximately ≥27% when overlapping items in the construction schedule were optimized. These findings are relevant to the setting of goals and the establishment of strategies during green remodeling and structural retrofitting of old buildings.
Event-Triggered Communication in Cooperative, Adaptive Model Predictive Control of a Nuclear Power Plant’s Turbo–Generator Set
Authors: Sokólski Paweł , Rutkowski Tomasz A. , Ceran Bartosz , Złotecka Daria , Horla Dariusz
Published: June 2023

This paper discusses the issue of optimizing the communication between the components of a cooperating control system formed by a pair of MPC controllers of a nuclear power plant turbine set using online recursive least squares identification. It is proposed to use event-triggered communication, i.e., sending information only at selected time instants, as opposed to the standard approach where communication is triggered by time (time-triggered approach). The aim of this paper is to propose a change in the method of information exchange in the case of asynchronous communication between control system components and to prove its suitability for the selected application. Resignation from continuous communication in favor of sending information only at selected moments allows the load on the communication network to be reduced by approximately 90% while maintaining the quality of control.
Performance of Polymer Electrolyte Membrane Water Electrolysis Systems: Configuration, Stack Materials, Turndown and Efficiency
Authors: Wang Xiaohua , Star Andrew G. , Ahluwalia Rajesh K.
Published: June 2023

A cell model is developed and validated to analyze the performance of polymer electrolyte membrane water electrolysis (PEMWE) stacks and systems. It is used to characterize the oxygen evolution reaction (OER) activity on a TiO2-supported IrO2 catalyst and an unsupported IrO2 powder catalyst. Electrochemical, stack, and system thermoneutral potentials are defined and determined for isothermal and non-isothermal stack operation. Conditions are determined under which the system thermoneutral potential or flammability of H2 in the O2 anode stream limits the stack turndown and operating temperature. Performance is analyzed of a complete PEMWE system with an electrolyzer stack containing an IrO2/TiO2 anode catalyst (2 mg/cm2 Ir loading) and N117-like membrane mitigated for H2 crossover, anode balance-of-plant (BOP) components, cathode BOP system with temperature swing adsorption for H2 purification, and electrical BOP system with transformer and rectifier. At the rated power condition, defined as 2 A/cm2 at 1.9 V, 80 °C, and 30 bar H2 pressure, the stack/system efficiency is 65.3%/60.3% at beginning of life (BOL), decreasing to 59.3%/53.9% at end of life (EOL). The peak stack/system efficiency is 76.3%/70.2% at BOL, decreasing to 71.2%/65.6% at EOL. Improvements in catalyst activity and membrane are identified for a 50% increase in current to 3 A/cm2 at 1.8 V.
Combustion Chemistry of Unsaturated Hydrocarbons Mixed with NOx: A Review with a Focus on Their Interactions
Authors: Tang Ruoyue , Cheng Song
Published: June 2023

Unsaturated hydrocarbons are major components of transportation fuels, combustion intermediates, and unburnt exhaust emissions. Conversely, NOx species are minor species present in the residual and exhaust gases of gasoline-fueled engines and gas turbines. Their co-existence in transportation engines is quite common, particularly with exhaust gas recirculation, which can greatly influence engine combustion characteristics. Therefore, this paper presents a review on the combustion chemistry of unsaturated hydrocarbons and NOx mixtures, with a focus on their chemical kinetic interactions. First, a comprehensive overview of fundamental combustion experiments is provided, covering mixtures of C2–C5 unsaturated/oxygenated species (namely alkenes, alkynes, dienes, alcohols, ethers, ketones, and furans) and three major NOx species (namely NO, NO2, and N2O), as well as reactors including jet-stirred reactors, flow reactors, burners, shock tubes, and rapid compression machines. Then, two widely adopted nitrogen chemistry models are evaluated in conjunction with a core chemistry model (i.e., NUIGMech1.1) via detailed chemical kinetic modeling, and the model similarities and differences across broad temperature ranges are highlighted. Thereafter, the unique interconversions between the three major NOx species are presented. In particular, the controversy regarding the pathways governing NO and NO2 conversion is discussed. Following this, the key direct interaction reactions between unsaturated species and NOx species are overviewed. Finally, the distinguishing features of the combustion chemistry for unsaturated hydrocarbon and NOx mixtures are summarized, and recommendations for future research on this topic are highlighted.
Reservoir Characteristics and Development Model of Subaqueous Pyroclastic Rocks in a Continental Lacustrine Basin: A Case Study of the Chaganhua Subsag in the Changling Fault Depression, Songliao Basin
Authors: Shi Yunqian , Yi Jian , Bian Weihua , Shan Xuanlong , Liu Yuhu , Hao Guoli , Li Ang , Leng Qinglei , Lu Junjie , Pang He , Zhang Ruichen
Published: June 2023

Industrial oil and gas eruptions underwater have been found in the pyroclastic rocks of the Huoshiling Formation in the continental lacustrine basin of the Changling fault depression, Songliao Basin. This paper investigates the reservoir space characteristics, physical characteristics, and pore structure differences of subaqueous pyroclastic reservoirs in the Huoshiling Formation, and the causes of physical property differences of different types of reservoirs and their formation and evolution processes are analyzed. (1) The content of volcanic glass in tuff is higher, the reservoir space is dominated by devitrification pores and dissolution pores, and the coarser the grain size, the more favorable the physical properties, with larger pore sizes and higher porosities. The content of clay minerals in sedimentary tuff is high, the pores between clay minerals are the main pores, and the physical properties of sedimentary tuff are poor. The content of soluble components such as feldspar, debris, and laumontite is high in tuffaceous sandstone, which is dominated by dissolution pores. (2) Primary pores are not developed in the pyroclastic reservoirs in the study area, and the reservoirs are relatively dense, with an average porosity of 2.43% and an average permeability of 0.076 mD. The coarse-grained tuff has the highest porosity, followed by tuffaceous sandstone and fine-grained tuff, and the sedimentary tuff has the least favorable physical properties. (3) Devitrification was an important cause of the high-porosity and ultralow permeability of tuff reservoirs. Two oil and gas charges in the middle diagenetic stage led to the organic acid dissolution of rocks. In addition, fractures can provide migration channels for organic acids and deep hydrothermal fluids, leading to late dissolution, and can connect various scattered dissolution pores to improve the effectiveness of the reservoir space. (4) Coarse-grained tuff reservoirs that developed in the proximal facies are favorable targets for hydrocarbon exploration.
HyMOTree: Automatic Hyperparameters Tuning for Non-Technical Loss Detection Based on Multi-Objective and Tree-Based Algorithms
Authors: Coelho Francisco Jonatas Siqueira , Feitosa Allan Rivalles Souza , Alcântara André Luís Michels , Li Kaifeng , Lima Ronaldo Ferreira , Silva Victor Rios , da Silva-Filho Abel Guilhermino
Published: June 2023

The most common methods to detect non-technical losses involve Deep Learning-based classifiers and samples of consumption remotely collected several times a day through Smart Meters (SMs) and Advanced Metering Infrastructure (AMI). This approach requires a huge amount of data, and training is computationally expensive. However, most energy meters in emerging countries such as Brazil are technologically limited. These devices can measure only the accumulated energy consumption monthly. This work focuses on detecting energy theft in scenarios without AMI and SM. We propose a strategy called HyMOTree intended for the hyperparameter tuning of tree-based algorithms using different multiobjective optimization strategies. Our main contributions are associating different multiobjective optimization strategies to improve the classifier performance and analyzing the model’s performance given different probability cutoff operations. HyMOTree combines NSGA-II and GDE-3 with Decision Tree, Random Forest, and XGboost. A dataset provided by a Brazilian power distribution company CPFL ENERGIA™ was used, and the SMOTE technique was applied to balance the data. The results show that HyMOTree performed better than the random search method, and then, the combination between Random Forest and NSGA-II achieved 0.95 and 0.93 for Precision and F1-Score, respectively. Field studies showed that inspections guided by HyMOTree achieved an accuracy of 76%.
Influence of Spark Gap Parameters on the Strength of the Surge Protection Device and the Method of Its Selection
Authors: Borecki Michał
Published: June 2023

The paper aims to analyze the factors affecting the parameters of surge protection devices with a spark gap and assess the impact of changing these parameters on the level of overhead line strength. For this purpose, this paper contains the results of tests that show the assessment of the impact of changing the spark gap parameters on the voltage–time characteristics of selected protection devices in the range of negative and positive polarity. The paper presents how the change in the parameters of the component element of the surge protection device, which is the spark gap, may affect the selection of the line surge protection method. In addition, the paper presents a method of assessing the strength of an overhead line, taking into account the case of installing surge protection devices at the insulators. The implementation of these tests supports further activities aimed at the actual values of parameters affecting the strength of overhead lines.
Transcriptomic Determination of the Core Genes Regulating the Growth and Physiological Traits of Quercus mongolica Fisch. ex Ledeb
Authors: Li Xinman , Jiang Min , Ren Junjie , Liu Zhaohua , Zhang Wanying , Li Guifen , Wang Jinmao , Yang Minsheng
Published: June 2023

Quercus mongolica is a multipurpose forest species of high economic value that also plays an important role in the maintenance and protection of its environment. Consistent with the wide geographical distribution of Q. mongolica, differences in the growth and physiological traits of populations of different provenances have been identified. In this study, the molecular basis for these differences was investigated by examining the growth, physiological traits, and gene expression of Q. mongolica seedlings from six provenances in northern China. The results showed that there were significant differences in growth and physiological traits, except for the ground diameter (p < 0.05), and identified abscisic acid (ABA), indole-3-acetic acid (IAA), and soluble sugar contents as important physiological traits that distinguish Q. mongolica of different provenances. The transcriptome analysis showed that the largest difference in the total number of differentially expressed genes (DEGs) was between trees from Jilin and Shandong (6918), and the smallest difference was between trees from Heilongjiang and Liaoning (1325). The DEGs were concentrated mainly in the Gene Ontology entries of metabolic process, catalytic activity, and cell, and in the Kyoto Encyclopedia of Genes and Genomes metabolic pathways of carbohydrate metabolism, biosynthesis of other secondary metabolites, signal transduction, and environmental adaptation. These assignments indicated that Q. mongolica populations of different provenances adapt to changes in climate and environment by regulating important physiological, biochemical, and metabolic processes. A weighted gene co-expression network analysis revealed highly significant correlations of the darkmagenta, grey60, turquoise, and plum1 modules with ABA content, IAA content, soluble sugar content, and soluble protein content, respectively. The co-expression network also indicated key roles for genes related to the stress response (SDH, WAK5, APA1), metabolic processes (UGT76A2, HTH, At5g42100, PEX11C), signal transduction (INPS1, HSD1), and chloroplast biosynthesis (CAB13, PTAC16, PNSB5). Functional annotation of these core genes implies that Q. mongolica can adapt to different environments by regulating photosynthesis, plant hormone signal transduction, the stress response, and other key physiological and biochemical processes. Our results provide insight into the adaptability of plants to different environments.
Biosynthesis of Nicotinamide Mononucleotide: Current Metabolic Engineering Strategies, Challenges, and Prospects
Authors: Luo Shiqi , Zhao Juntao , Zheng Yangyang , Chen Tao , Wang Zhiwen
Published: June 2023

Nicotinamide mononucleotide (NMN) is an essential precursor of nicotinamide adenine dinucleotide (NAD+), which is widely applied in the pharmaceutical and biotech industries. The biosynthesis of NMN is currently attracting much attention because it has non-toxic reaction conditions and low amounts of isomers, whereas chemical synthesis has low yields and is not environmentally friendly. This review systematically describes the two biosynthetic pathways of NMN in detail for the first time and introduces the latest studies on NMN production through different pathways using metabolic engineering strategies. NMN accumulation can be improved by optimizing the activity of key enzymes, enhancing the supply of precursors and co-factors, inhibiting the synthesis of byproducts, and promoting product export. Finally, we also discuss the current challenges of producing NMN and possible solutions for the future.
Prognostic Metamodel Development for Waste-Derived Biogas-Powered Dual-Fuel Engines Using Modern Machine Learning with K-Cross Fold Validation
Authors: Alruqi Mansoor , Hanafi H. A. , Sharma Prabhakar
Published: June 2023

Attention over greenhouse gas emissions has driven interest in cleaner energy sources including alternative fuels. Waste-derived biogas, which is produced by the anaerobic digestion of organic waste such as municipal solid waste, agricultural residues, and wastewater sludge, is an intriguing biofuel source due to its abundant availability and promise of lowering emissions. We investigate the potential of waste-derived biogas as an alternative fuel for a dual-fuel engine that also uses diesel as a secondary fuel in this study. We suggest using a modern machine learning XGBoost model to forecast engine performance. Data acquired with thorough lab-based text will be used to create prognostic models for each output in this effort. Control factors impacting engine performance, including pilot fuel injection pressure, engine load, and pilot fuel injection time, will be employed. The effects of these control elements on engine reaction variables such as brake thermal efficiency (BTE), peak pressure (Pmax), nitrogen oxides (NOx), carbon monoxide (CO), and unburned hydrocarbons (UHC) were simulated. The created models were tested using a variety of statistical approaches, including the coefficient of determination (0.9628–0.9892), Pearson’s coefficient (0.9812–0.9945), mean absolute error (0.4412–5.89), and mean squared error (0.2845–101.7), all of which indicated a robust prognostic model. The use of the increased compression ratio helped in the improvement of BTE with a peak BTE of 26.12%, which could be achieved at an 18.5 compression ratio 220 bar fuel injection pressure peak engine load. Furthermore, our findings give light regarding how to improve the performance of dual-fuel engines that run on waste-derived biogas, with potential implications for cutting emissions in the transportation sector.
Rapid and Automated Method for Detecting and Quantifying Adulterations in High-Quality Honey Using Vis-NIRs in Combination with Machine Learning
Authors: Calle José Luis P. , Punta-Sánchez Irene , González-de-Peredo Ana Velasco , Ruiz-Rodríguez Ana , Ferreiro-González Marta , Palma Miguel
Published: June 2023

Honey is one of the most adulterated foods, usually through the addition of sweeteners or low-cost honeys. This study presents a method based on visible near infrared spectroscopy (Vis-NIRs), in combination with machine learning (ML) algorithms, for the correct identification and quantification of adulterants in honey. Honey samples from two botanical origins (orange blossom and sunflower) were evaluated and adulterated with low-cost honey in different percentages (5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50%). The results of the exploratory analysis showed a tendency to group the samples according to botanical origin, as well as the presence of adulteration. A supervised analysis was performed to detect the presence of adulterations. The best performance with 100% accuracy was achieved by support vector machines (SVM) and random forests (RF). A regression study was also carried out to quantify the percentage of adulteration. The best result was obtained by support vector regression (SVR) with a coefficient of determination (R2) of 0.991 and a root mean squared error (RMSE) of 1.894. These results demonstrate the potential of combining ML with spectroscopic data as a method for the automated quality control of honey.
Essential Guide to Hydrogel Rheology in Extrusion 3D Printing: How to Measure It and Why It Matters?
Authors: Herrada-Manchón Helena , Fernández Manuel Alejandro , Aguilar Enrique
Published: June 2023

Rheology plays a crucial role in the field of extrusion-based three-dimensional (3D) printing, particularly in the context of hydrogels. Hydrogels have gained popularity in 3D printing due to their potential applications in tissue engineering, regenerative medicine, and drug delivery. The rheological properties of the printing material have a significant impact on its behaviour throughout the 3D printing process, including its extrudability, shape retention, and response to stress and strain. Thus, understanding the rheological characteristics of hydrogels, such as shear thinning behaviour, thixotropy, viscoelasticity, and gelling mechanisms, is essential for optimising the printing process and achieving desired product quality and accuracy. This review discusses the theoretical foundations of rheology, explores different types of fluid and their properties, and discusses the essential rheological tests necessary for characterising hydrogels. The paper emphasises the importance of terminology, concepts, and the correct interpretation of results in evaluating hydrogel formulations. By presenting a detailed understanding of rheology in the context of 3D printing, this review paper aims to assist researchers, engineers, and practitioners in the field of hydrogel-based 3D printing in optimizing their printing processes and achieving desired product outcomes.
Application of Hydrogels in the Device of Ophthalmic Iontophoresis: Theory, Developments and Perspectives
Authors: Wei Dong , Pu Ning , Li Si-Yu , Zhao Na , Song Zong-Ming , Tao Ye
Published: June 2023

The human eye is a consolidated organ with delicate structures and unique immune privileges. Ocular diseases are intractable due to the intrinsic biological barriers within the eyeball. Hydrogels are excellent drug-carrying substances with soft material and excellent properties. They have been extensively used to deliver drugs into ocular tissue via iontophoresis devices. Ophthalmic iontophoresis is an electrochemical technique using tiny electrical currents to deliver drugs into the eye non-invasively. The early infantile iontophoresis technique often required long applying time to achieve therapeutic dose in the posterior ocular segment. The potential limitations in the initial drug concentration and the maximum safe currents would also impede the efficiency and safety of iontophoresis. Moreover, the poor patient compliance always leads to mechanical damage to the cornea and sclera during application. Advantageously, the flexible drug-carrying hydrogel can be in direct contact with the eye during iontophoresis, thereby reducing mechanical damage to the ocular surface. Moreover, the water absorption and adjustable permeability of hydrogels can reduce the electrochemical (EC) reactions and enhance the efficiency of iontophoresis. In this review, we focus on recent developments of hydrogels iontophoresis in ophthalmologic practice. Refinements of the knowledge would provide an outlook for future application of hydrogels in treating ocular disease.
Clinical Instructors’ Perspectives on the Assessment of Clinical Knowledge of Undergraduate Nursing Students: A Descriptive Phenomenological Approach
Authors: Chen Li-Chin , Lin Chun-Chih , Han Chin-Yen , Huang Ya-Ling
Published: June 2023

This study aimed to determine clinical instructors’ perceptions of the assessments used to evaluate the clinical knowledge of undergraduate nursing students. This study uses a descriptive phenomenological approach. Purposive sampling was used to recruit sixteen clinical instructors for semi-structured interviews between August and December 2019. All interviews were audio recorded and transcribed verbatim. Data were analyzed using a modified Colaizzi’s seven-step method. Four criteria were used to ensure the study’s validity: credibility, transferability, dependability, and confirmability. Three themes were identified in the clinical instructors’ views on evaluating the clinical performance of student nurses: familiarity with students, patchwork clinical learning, and differing perceptions of the same scoring system. The study results suggest a need for a reliable, valid, and consistent approach to evaluating students’ clinical knowledge. If the use of patchwork clinical internships for student nurses is unavoidable, a method for assessing student nurses’ clinical performance that requires instructor consensus is necessary.
Attitudes That Might Impact upon Donation after Brain Death in Intensive Care Unit Settings: A Systematic Review
Authors: Alshammari Areej , Brown Michael
Published: June 2023

Background: Organ donation and transplantation can save or improve the quality of life of people worldwide. However, there are many challenges associated with organ donation, as the demand for organs greatly outstrips supply. Additionally, there are brain-dead patients who could be potential organ donors. It is thus important to determine the attitudes affecting organ donation and transplantation in intensive care unit settings. Aim: this study aimed to identify attitudes that might affect organ donation and transplantation in intensive care unit settings. Methodology: Five electronic databases (CINAHL, Medline, PsycINFO, Scopus, and EMBASE) were searched systematically. A systematic search strategy was formulated. The quality of each study was assessed using the MMAT quality appraisal tool. Results: A total of seven studies were included. The findings of this systematic review demonstrate that education, policy, and continuing professional development could help to address barriers to donation. Conclusions: therefore, to influence organ donation and transplantation positively, the main themes evaluated in this systematic review provide an opportunity to influence organ donation and transplantation attitudes in intensive care unit settings.
The Effectiveness of Compression Garments for Reducing Pain in Non-Vascular Ehlers-Danlos Syndromes: A Prospective Observational Cohort Study
Authors: Benistan Karelle , Pontier Bénédicte , Leblond Catherine , Flageul Ophélie , Le Guicher Gwenvael , Enjalbert Michel , Gillas Fabrice
Published: June 2023

Patients with Ehlers-Danlos Syndrome (EDS) frequently suffer from severe chronic pain. We carried out an observational cohort study to assess the effectiveness of compression garments (CGs) for reducing this pain. Patients with non-vascular EDS were given custom-made Cerecare® CGs during a visit to a specialist clinic (visit V0). They were followed up over 2 years with visits every 6 months (V1–V4). At each visit, pain was assessed for the joints treated with CGs using a visual analogue scale (VAS; 0–100 mm). Additional measures were obtained to assess neuropathic pain (painDETECT questionnaire), proprioception/balance (Berg Balance Scale), and functional independence, amongst others. Data were analyzed for 67 patients with EDS (hypermobile: 91%; classical: 6%; kyphoscoliotic: 3%). For the most painful joint, the mean VAS rating was 71.5 ± 22.8 mm at V0; this decreased to 53.5 ± 25.5 mm at V1 and 45.7 ± 29 mm at V4 (t-tests: p < 0.0001). From V0 to V4, improvements were also seen for pain at the other joints, neuropathic pain, functional independence, proprioception/balance, and the incidence of sprains and dislocations/subluxations, although not all comparisons were statistically significant (p < 0.05 level). These results indicate that CGs may effectively reduce the pain and joint instability in non-vascular EDS patients.
Does the Intersectionality of Race/Ethnicity and Type 2 Diabetes Increase the Odds of a Cervical Cancer Diagnosis? A Nested Case–Control Study of a Florida Statewide Multisite EHR Database
Authors: Mkuu Rahma S. , Hall Jaclyn M. , Galochkina Zhanna , Cho Hee Deok , Staras Stephanie A. S. , Lee Ji-Hyun , Guo Yi , Chakrabarti Choeeta , Barrow Sable Bowman , Ortega Selena , Avery Daniel M. , Higginbotham John , Lockhart Jala , Shenkman Elizabeth A.
Published: June 2023

Cervical cancer and Type 2 Diabetes (T2D) share common demographic risk factors. Despite this, scarce research has examined the relationship between race/ethnicity, having T2D, and cervical cancer incidence. We analyzed statewide electronic health records data between 2012 and 2019 from the OneFlorida+ Data Trust. We created a 1:4 nested case–control dataset. Each case (patient with cervical cancer) was matched with four controls (patients without cervical cancer) without replacement by year of encounter, diagnosis, and age. We used conditional logistic regression to estimate the unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to examine the association between race/ethnicity, T2D, and cervical cancer incidence. A total of 100,739 cases and 402,956 matched controls were identified. After adjusting for sociodemographic characteristics, non-Hispanic Black women with T2D had higher odds of cervical cancer compared with non-Hispanic White women with T2D (OR: 1.58, 95% CI 1.41–1.77). Living in a rural area, having Medicaid/Medicare insurance, and having high social vulnerability were associated with higher odds of having a cervical cancer diagnosis. Our findings imply the need to address the higher burden of cervical cancer diagnosis among non-Hispanic Black women with T2D and in underserved populations.
Comparison of the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Logic for Flood Exposure Risk Assessment in Arid Regions
Authors: Baalousha Husam Musa , Younes Anis , Yassin Mohamed A. , Fahs Marwan
Published: June 2023

Flood risk assessment is an important tool for urban planning, land development, and hydrological analysis. The flood risks are very high in arid countries due to the nature of the rainfall resulting from thunderstorms and the land cover, which comprises mostly very dry arid soil. Several methods have been used to assess the flood risk, depending on various factors that affect the likelihood of occurrence. However, the selection of these factors and the weight assigned to them remain rather arbitrary. This study assesses the risk of flood occurrence in arid regions based on land cover, soil type, precipitation, elevation, and flow accumulation. Thematic maps of the aforementioned factors for the study area were prepared using GIS. The Fuzzy Analytic Hierarchy Process (F-AHP) was used to calculate the likelihood of the flood occurrence, and land use was used to assess the exposure impact. Using the likelihood map (i.e., probability) from the Fuzzy-AHP and an exposure map, the flood risk was assessed. This method was applied to Qatar as a case study. Results were compared with those produced by fuzzy logic. To explore the pairwise importance of the F-AHP, equal weight analysis was performed. The resulting risk map shows that the majority of urbanized areas in Qatar are within the high-risk zone, with some smaller parts within the very high flood-risk area. The majority of the country is within the low-risk zone. Some areas, especially land depressions, are located within the intermediate-risk category. Comparison of Fuzzy logic and the F-AHP showed that both have similarities in the low-risk and differences in the high-risk zones. This reveals that the F-AHP is probably more accurate than other methods as it accounts for higher variability.