bluuebunny/crossref_metadata_2025 huggingface dataset:
High-sensitivity biosensor based on SERS integrated with dendrimer-assisted boronic acid-functionalized magnetic nanoparticles for IL-6 detection in human serum
Authors: Wang Ying , Guan Ming , Hu Cunming , Mi Fang , Geng Pengfei , Li Yingjun
Published: April 2023

High-sensitivity quantitative analysis of sepsis disease markers in circulating blood is essential for sepsis early diagnosis, rapid stratification, and interventional treatment. Herein, a high-sensitivity biosensor combining surface-enhanced Raman spectroscopy (SERS) and functionalized magnetic materials was developed to quantitatively detect interleukin-6 (IL-6), a glycoprotein disease marker closely related to sepsis. First, boronic acid-functionalized magnetic nanomaterials with high adsorption performance were synthesized by utilizing the branched polyethyleneimine to provide many binding sites for boronic acid. Under antibody-free conditions, dendrimer-assisted boronic acid-functionalized magnetic nanomaterials selectively capture glycoproteins in complex biological samples as bio-capture element. Then, a core–shell bimetallic material with plenty of ‘hot spots’ was designed and synthesized as the enhancement substrate. The 4-Mercaptobenzonitrile (4-MP) with a characteristic peak at 2224 cm−1 (Raman-silent region) was embedded as the Raman reporter to form a SERS immune probe with highly efficient electromagnetic enhancement effect, achieving specific recognition and high-sensitivity detection of IL-6 on bio-capture elements. Using this strategy for quantitative analysis of IL-6, a wide detection range (0.5–5000 pg ml−1) and a low detection limit (0.453 pg ml−1) were obtained. Moreover, this method exhibited excellent detection performance for IL-6 in human serum samples, demonstrating its potential promise in screening clinically relevant diseases. The biosensor presented here not only provides a novel and universally applicable sensing strategy for the enrichment and detection of trace glycoprotein disease markers, but also the application of a portable Raman spectrometer provides a more reliable experimental basis for the diagnosis and treatment of major diseases in the clinic or remote and deprived areas.
Data-driven adaptive needle insertion assist for transperineal prostate interventions
Authors: Bernardes Mariana C , Moreira Pedro , Mareschal Lisa , Tempany Clare , Tuncali Kemal , Hata Nobuhiko , Tokuda Junichi
Published: April 2023

Objective. Clinical outcomes of transperineal prostate interventions, such as biopsy, thermal ablations, and brachytherapy, depend on accurate needle placement for effectiveness. However, the accurate placement of a long needle, typically 150–200 mm in length, is challenging due to needle deviation induced by needle-tissue interaction. While several approaches for needle trajectory correction have been studied, many of them do not translate well to practical applications due to the use of specialized needles not yet approved for clinical use, or to relying on needle-tissue models that need to be tailored to individual patients. Approach. In this paper, we present a robot-assisted collaborative needle insertion method that only requires an actuated passive needle guide and a conventional needle. The method is designed to assist a physician inserting a needle manually through a needle guide. If the needle is deviated from the intended path, actuators shifts the needle radially in order to steer the needle trajectory and compensate for needle deviation adaptively. The needle guide is controlled by a new data-driven algorithm which does not require a priori information about needle or tissue properties. The method was evaluated in experiments with both in vitro and ex vivo phantoms. Main results. The experiments in ex vivo tissue reported a mean final placement error of 0.36 mm with a reduction of 96.25% of placement error when compared to insertions without the use of assistive correction. Significance. Presented results show that the proposed closed-loop formulation can be successfully used to correct needle deflection during collaborative manual insertion with potential to be easily translated into clinical application.
Positional sleep apnea phenotyping using machine learning and digital oximetry biomarkers
*
Authors: Ben Sason Yuval , Levy Jeremy , Oksenberg Arie , Sobel Jonathan , Behar Joachim A
Published: April 2023

Study Objectives. To examine the feasibility of using digital oximetry biomarkers (OBMs) and body position to identify positional obstructive sleep apnea (POSA) phenotypes. Methods. A multiclass extreme gradient boost (XGBoost) was implemented to classify between three POSA phenotypes, i.e., positional patients (PP), including supine-predominant OSA (spOSA), and supine-isolated OSA (siOSA), and non-positional patients (NPP). A total of 861 individuals with OSA from the multi ethnic study of atherosclerosis (MESA) dataset were included in the study. Overall, 43 OBMs were computed for supine and non-supine positions and used as input features together with demographic and clinical information (META). Feature selection, using mRMR, was implemented, and nested cross validation was used for the model’s performance evaluation. Results. The best performance for the multiclass classification yielded a median weighted F1 of 0.79 with interquartile range (IQR) of 0.06. Binary classification between PP to NPP achieved weighted F1 of 0.87 (0.04). Conclusion. Using OBMs computed in PP and NPP with OSA, it is possible to distinguish between the different phenotypes of POSA. This data-driven algorithm may be embedded in portable home sleep tests.
Application of de-shape synchrosqueezing to estimate gait cadence from a single-sensor accelerometer placed in different body locations
Authors: Wu Hau-Tieng , Harezlak Jaroslaw
Published: April 2023

Objective. Commercial and research-grade wearable devices have become increasingly popular over the past decade. Information extracted from devices using accelerometers is frequently summarized as ‘number of steps’ (commercial devices) or ‘activity counts’ (research-grade devices). Raw accelerometry data that can be easily extracted from accelerometers used in research, for instance ActiGraph GT3X+, are frequently discarded. Approach. Our primary goal is proposing an innovative use of the de-shape synchrosqueezing transform to analyze the raw accelerometry data recorded from a single sensor installed in different body locations, particularly the wrist, to extract gait cadence when a subject is walking. The proposed methodology is tested on data collected in a semi-controlled experiment with 32 participants walking on a one-kilometer predefined course. Walking was executed on a flat surface as well as on the stairs (up and down). Main results. The cadences of walking on a flat surface, ascending stairs, and descending stairs, determined from the wrist sensor, are 1.98 ± 0.15 Hz, 1.99 ± 0.26 Hz, and 2.03 ± 0.26 Hz respectively. The cadences are 1.98 ± 0.14 Hz, 1.97 ± 0.25 Hz, and 2.02 ± 0.23 Hz, respectively if determined from the hip sensor, 1.98 ± 0.14 Hz, 1.93 ± 0.22 Hz and 2.06 ± 0.24 Hz, respectively if determined from the left ankle sensor, and 1.98 ± 0.14 Hz, 1.97 ± 0.22 Hz, and 2.04 ± 0.24 Hz, respectively if determined from the right ankle sensor. The difference is statistically significant indicating that the cadence is fastest while descending stairs and slowest when ascending stairs. Also, the standard deviation when the sensor is on the wrist is larger. These findings are in line with our expectations. Conclusion. We show that our proposed algorithm can extract the cadence with high accuracy, even when the sensor is placed on the wrist.
Charged-particle transport models for global models
Authors: Alves L L , Tejero-del-Caz A
Published: April 2023

This work analyses the influence of different charged-particle transport models on the global modeling of low-temperature plasmas. The simulations use the LisbOn KInetics simulation tool, calculating the charged-particle loss frequency due to transport with various formulations, categorized into two large groups: ambipolar-based and h-factor transport models. The models are applied to the description of (i) a DC discharge in oxygen (as example of an electronegative multi-ion plasma), at low to intermediate pressures, adopting a validated kinetic scheme as reference model; (ii) a microwave discharge in helium (as example of an electropositive multi-ion plasma), from low to atmospheric pressures, proposing and validating an updated kinetic scheme that bridges two previous models, adjusted separately for low to intermediate pressures and for atmospheric pressure. The analysis shows that using different charged-particle transport models can result in uncertainties of 20%–60% and 8%–115% in the discharge characteristics of oxygen and helium, respectively, with larger dispersion at low pressure and low electron density. The spreading in the results is observed also in the densities of the main plasma species, corresponding to uncertainties up to

60
%

and within 50%–150% in oxygen and helium, respectively. Since transport accounts for more than

50
%

of total charge losses, this mechanism should always be part of the quantitative sensitivity analysis of a kinetic scheme, considering several models with different validity domains, according to the electro-positive/-negative single-/multi-ion plasma under study and the low/high pressure conditions considered.
Spacetime foam: a review
Authors: Carlip S
Published: April 2023

More than 65 years ago, John Wheeler suggested that quantum uncertainties of the metric would be of order one at the Planck scale, leading to large fluctuations in spacetime geometry and topology, which he termed ‘spacetime foam.’ In this review I discuss various attempts to implement this idea and to test it, both theoretically and, to a lesser extent, observationally.
A novel MXene-based high-performance flexible pressure sensor for detection of human motion
Authors: Zhang Zhidong , Zhang Qingchao , Zhang Huinan , Li Bo , Zang Junbin , Zhao Xuefeng , Zhao Xiaolong , Xue Chenyang
Published: April 2023

Flexible pressure sensors possess superior conformal ability, great flexibility, and strong biocompatibility than conventional silicon-based sensors, thereby widely used in electronic skin, wearable devices, and robotic tactile sensing, among other fields. However, flexible pressure sensors are still limited by many challenges related to extended linearity and high sensitivity. In this paper, MXene with a loose layered structure was employed to fabricate high-performance flexible piezoresistive sensors comprising polydimethylsiloxane (PDMS) film with cylindrical microstructure, multilayer Ti3C2T
x
-MXene film, and interdigital electrodes. A cylindrical microstructured silicon wafer was designed and processed by deep silicon etching process, and PDMS flexible substrate was obtained by two inversions as the pressure sensing layer. The resulting flexible pressure sensor exhibited excellent performance in terms of excellent sensitivity up to 519 kPa−1 in the large detection range of 0–8 kPa coupled with great linearity, a response time of 62.7 ms, and a recovery time of 62.8 ms. The high sensitivity was associated with the compression of the interlayer spacing of multilayer MXene nanosheets. In addition, a single flexible pressure sensor and integrated array were utilized to detect the human physical signals and quantitative measurements of pressure distributions. Overall, these findings provided experimental verification for the design and manufacturing of highly sensitive and linear flexible pressure sensors.
Design of a programmable particle filtering medium using a novel auxetic metamaterial
Authors: Ali Hafiz M A , Abdi Meisam , Zahedi S Abolfazl , Sun Yong
Published: April 2023

This study presents the design and development of a 2D auxetic filtering medium with programmable geometric features specifically designed to vary under in-plane tensile strain. This feature empowers the filtering medium to control the particles separation. A novel design and optimisation algorithm developed in Matlab® determines the final optimized geometry of the filtering medium based on the desired particle size input. Upon thorough numerical investigation, an empirical relationship between the linear elastic in-plane tensile strain and aperture size of the proposed metamaterial is revealed. This empirical relation can be used in mechatronic and control systems to steer the proposed filtering medium. A prototype of such filtering medium capable of classification of particles of size 4 mm to 4.5 mm, when subjected to linear strain, is fabricated through fused deposition modelling process. The developed geometry configurations in this research are scalable, providing a potential cost-effective and efficient solution for industrial applications including reconfigurable filtration and segregation systems.
Cyclotron radiation from shaped electron wavefunctions
Authors: Khalaf Majed , Rivera Nicholas , Kaminer Ido
Published: April 2023

Recent years have shown increasing interest in understanding the role of the wavefunction of a quantum source on the characteristics of its emitted radiation. In this work, we demonstrate that shaping the wavefunction of the source can drastically change the instantaneous emission. We exemplify this concept by examining an electron in cyclotron motion, calculating the angular power distribution of emission by an electron in a Schrodinger cat state. The emitted cyclotron radiation reveals a breakdown of classical–quantum correspondence. The short-time dynamics of the radiation process shows deviations in the power and electron trajectory that disappear at long times, where the predictions of classical electrodynamics are recovered.
Dynamical N-photon bundle emission
Authors: Zou F , Li Y , Liao J-Q
Published: April 2023

Engineering multiphoton resources is of importance in quantum metrology, quantum lithography, and biological sensing. Here we propose a concept of dynamical emission of N strongly-correlated photons. This is realized in a circuit quantum electrodynamical system driven by two Gaussian-pulse sequences. The underlying physical mechanism relies on the stimulated Raman adiabatic passage that allows efficient and selective preparation of target multiphoton states. Assisted by the photon decay, a highly pure N-photon bundle emission takes place in this system. In particular, the dynamical N-photon bundle emission can be tuned by controlling the time interval between consecutive pulses so that the device behaves as an N-photon gun, which can be triggered on demand. Our work opens up a route to achieve multiphoton source devices, which have wide potential applications in quantum information processing and quantum metrology.
An efficient numerical method for the time-fractional distributed order nonlinear Klein–Gordon equation with shifted fractional Gegenbauer multi-wavelets method
Authors: Ghuraibawi Amer A , Marasi H R , Derakhshan M H , Kumar Pushpendra
Published: April 2023

In this paper, we propose an effective numerical method using two-dimensional Shifted fractional-order Gegenbauer Multi-wavelets to find the approximate solutions of the time-fractional distributed order non-linear partial differential equations. The method is applied to numerically solve the fractional distributed order non-linear Klein–Gordon equation. We derive an exact formula for the Riemann-Liouville fractional integral operator for the Shifted fractional Gegenbauer Multi-wavelets. Applying function approximations obtained by this method turns the considered equation into a system of algebraic equations. Error estimation and convergence analysis of the method are also studied. Some numerical examples are included to show and check the effectiveness of the proposed method.
Measurement-based quantum computation using two-component BECs
Authors: Fujii Genji
Published: April 2023

Measurement-based quantum computation (MBQC) using two-component Bose–Einstein condensates (BECs) is proposed in this paper. An arbitrary state for one logical qubit is obtained by three-body measurement. Furthermore, a method is proposed for implementing controlled-Z gates for logical qubits in a graph state using BEC qubits and controlled-Z gates for BEC-type encoding. Results showed that the state after a measurement depends on the number of particles. These results pave the way for a novel quantum computing process based on particle control.
Right-handed sneutrino and gravitino multicomponent dark matter in light of neutrino detectors
Authors: Kim Jong Soo , López-Fogliani Daniel E. , Perez Andres D. , Ruiz de Austri Roberto
Published: April 2023

We investigate the possibility that right-handed (RH) sneutrinos and gravitinos can coexist and explain the dark matter (DM) problem. We compare extensions of the minimal supersymmetric standard model (MSSM) and the next-to-MSSM (NMSSM) adding RH neutrinos superfields, with special emphasis on the latter. If the gravitino is the lightest supersymmetric particle (LSP) and the RH sneutrino the next-to-LSP (NLSP), the heavier particle decays to the former plus left-handed (LH) neutrinos through the mixing between the scalar partners of the LH and RH neutrinos.
However, the interaction is suppressed by the Planck mass, and if the LH-RH sneutrino mixing parameter is small, ≪ O(10-2), a long-lived RH sneutrino NLSP is possible even surpassing the age of the Universe.
As a byproduct, the NLSP to LSP decay produces monochromatic neutrinos in the ballpark of current and planned neutrino telescopes like Super-Kamiokande, IceCube and Antares that we use to set constraints and show prospects of detection.
In the NMSSM+RHN, assuming a gluino mass parameter M
3 = 3 TeV we found the following lower limits for the gravitino mass m
3/2 ≳ 1-600 GeV and the reheating temperature T
R ≳ 105 - 3 × 107 GeV, for mν̃
R
10-800 GeV. If we take M
3 = 10 TeV, then the limits on TR
are relaxed by one order of magnitude.
New carbon–nitrogen–oxygen compounds as high energy density materials
Authors: Shen Junyu , Duan Qingzhuo , Miao Junyi , He Shi , He Kaihua , Dai Wei , Lu Cheng
Published: April 2023

Molecular crystals are complex systems exhibiting various crystal structures, and accurately modeling the crystal structures is essential for understanding their physical behaviors under high pressure. Here, we perform an extensive structure search of ternary carbon-nitrogen-oxygen (CNO) compound under high pressure with the CALYPSO method and first principles calculations, and successfully identify three polymeric CNO compounds with Pbam, C2/m and

I

4
¯

m
2

symmetries under 100 GPa. More interestingly, these structures are also dynamically stable at ambient pressure, and are potential high energy density materials (HEDMs). The energy densities of Pbam, C2/m and

I

4
¯

m
2

phases of CNO are about 2.30 kJ/g, 1.37 kJ/g and 2.70 kJ/g, respectively, with the decompositions of graphitic carbon and molecular carbon dioxide and α-N (molecular N2) at ambient pressure. The present results provide in-depth insights into the structural evolution and physical properties of CNO compounds under high pressures, which offer crucial insights for designs and syntheses of novel HEDMs.
Structural origin for composition-dependent nearest atomic distance in Cu–Zr metallic glass
Authors: Zhang 张 Chi 驰 , Liu 刘 Hua-Shan 华山 , Peng 彭 Hai-Long 海龙
Published: April 2023

We systematically investigate the structures of Cu–Zr metallic glass (MG) by varying the Cu concentration in classic molecular-dynamics simulation. From the pair distribution functions (PDFs), it is found that the nearest atomic distance between Zr atom and Zr atom increases significantly after adding Cu, which is related to the composition-dependent coordination behavior between Cu atom and Zr atom in the nearest neighbors. The portion of PDF related to the nearest connection is decomposed into the contributions from quadrilateral structure, pentagonal structure, hexagonal structure, and heptagonal bipyramid structure. Although the population of denser structures, i.e. 5-, 6-, and 7-number sharing ones, increases with Cu addition increasing, the connection distances between the central atoms in all these bipyramids increase for Zr–Zr pairs, leading to the expansion of Zr–Zr nearest atomic distance. These results unveil the effect of the interplay between chemical interaction and geometric packing on the atomic-level structure in Cu–Zr metallic glasses.
Quantification and economic analysis of virtual energy storage caused by thermal inertia in buildings
Authors: Shi Weijie , Liu Qingrong , Ruan Yingjun , Qian Fanyue , Meng Hua
Published: April 2023

The virtual energy storage caused by the thermal inertia of the building is the property and can participate in the demand response. However, the quantification of this virtual energy storage part is not clear. To determine the energy flexibility potential of building virtual energy storage, quantitative indicators such as charging and discharging time, and charging and discharging energy are proposed. The building model was created using the building energy simulation software EnergyPlus, and the quantification of each performance indicator of the building’s virtual energy storage was developed. Among them, the optimal charging time for this building model is 30 minutes, and the optimal discharging time is 60 minutes. Under the optimal virtual energy storage operation strategy, the charging energy is 57 kWh and the discharging energy is 84 kWh. Compared with the reference strategy, the building virtual energy storage operation strategy saves 48.76 yuan in single-day cooling electricity cost, with a 3% savings rate. The results show that building virtual energy storage has certain energy flexibility without additional investment and can generate certain economic benefits at the same time.
Thermal Management of Lithium-ion Battery based on Flow and Heat Transfer Entropy Generation Analysis
Authors: Yu Shuai , Xu Yanzhe , Yang Shuai , Leng Feng , Liu Fei , Wang Yunfan , Hu Qiwei , Zhao Yutian , Li Zhoupin , Wang Zhen
Published: April 2023

In order to realize the problem of efficient heat dissipation management of lithium battery modules, the thermal management model of liquid cooled lithium-ion battery modules is studied in this paper. The entropy increase characteristics caused by the flow process and heat transfer process of the lithium-ion battery module under three liquid cooling inlet and outlet modes are analyzed by numerical simulation, and the internal mechanism of the local entropy generation characteristics of the lithium-ion battery module is clarified. The numerical results show that the 3×3 MIMO is the best model considering the heat dissipation and fluidity of the protective fluid. In addition, the results of this study can provide effective design guidance for thermal management of lithium-ion batteries.
Analysis of New Energy Consumption Capacity Considering Photovoltaic Uncertainty
Authors: Sun Jingliao , Hu Changhong , Mei Fuxian , Xiang Yejun , Liu Jinyuan
Published: April 2023

With the active promotion of the double carbon policy, vigorously developing the new energy industry is our important job. Considering the volatility and randomness of distributed photovoltaic forces, abandonment often occurs. This article proposes a new energy consumption capability analysis model that considers distributed photovoltaic uncertainty. First of all, a typical contribution curve of massive scenarios is reduced to generate a typical power curve of distributed photovoltaic; then the model simplifies; finally, based on the random optimization method, the operating cost, photovoltaic construction cost, and abandoned cost of the unit are based on the random optimization method. The above theory is verified by the IEEE 33 standard node, which proves the theory’s effectiveness. The energy storage equipment can improve the configuration capacity of distributed photovoltaic, reduce system operating costs, and improve the ability of new energy.
Comprehensive Reliability Assessment Method for Lithium Battery Energy Storage Systems
Authors: Si Jiandong , Tang Yiqin , Li Xinang , Zhang Linyu
Published: April 2023

Electrochemical energy storage systems have the advantages of fast power response, intensive energy storage, flexible and convenient deployment, but the output characteristics of the battery system directly affect the service effect of the energy storage power plant. Therefore, it is quite necessary to analyze the reliability of battery energy storage and scientifically assess the system’s performance. This paper considers the aging state of the battery storage system as well as sudden failures and establishes a comprehensive reliability assessment method for battery energy storage systems that take into account the battery health index and the impact of thermal runaway failures, which makes up for the shortcomings of existing reliability assessment methods.
Low Carbon Operation Optimization Study of Integrated Energy Systems Considering Interruptible Loads
Authors: Di HuiQiang , Zhang Min , Chang Xiao , Fan Rui , Li Rui
Published: April 2023

Aiming at the consumption of renewable energy, researched controllable load mechanisms and energy storage regulation strategies in an electric-thermal coupled network, and a comprehensive flexible resource model was constructed to optimize the low-carbon operation of the system. Firstly, analyzed the industrial load regulation mechanism of differentiated layout in the regional power grid. Based on the electric-thermal coupled system in the urban energy grid, the regulation model of controllable load and electric/thermal energy storage was established. Then a comprehensive benefit model was constructed with an economic cost, wind and solar usage, and carbon emissions as indicators. Proposed a carbon emission flow topology to describe the carbon emission flow information attached to the energy flow. Finally, combined with the IEEE 33-node distribution network and 45-node heat network coupling system, the improvement effect of the multiple flexible resource response on the comprehensive benefits of the system was analyzed. And the carbon emission flow process of the electricity-thermal network in the typical scenario was visually displayed through topology. The results show that exploring flexible resources can improve the consumption margin of wind and solar energy in the integrated energy system, which verifies the rationality and effectiveness of the proposed method.
Research on input-output evaluation index of high energy consumption main transformer transformation
Authors: Zhang Hongyang , Lu Shaohua , Zhang Ming , Wang Shuo , Gao Jingren
Published: April 2023

In order to quantify the input-output evaluation index of high-energy consumption main transformer transformation projects of power grid enterprises, to provide a real, effective, and quantitative basis for investment decisions, the project input and output indexes are measured from the whole life cycle perspective. The whole life cycle cost, including the initial investment and annual operational maintenance cost, is selected as the input evaluation index, and the four dimensions of safety, economics, efficiency, and greenness are considered. The output evaluation index is proposed, combined with the investment effectiveness of typical projects of production technology reform, the potential output analysis indexes under each dimension are sorted out, the full set of output evaluation indexes of production technology reform projects is constructed, the corresponding characteristic indexes of high energy consumption main transformation projects are selected from the full set of indexes, and mathematical evaluation model of input-output analysis of high energy consumption main transformation projects is built. Verify the model through practical engineering examples.
A prediction model based on an adaptive genetic algorithm and optimized Elman neural network for PV power
Authors: Wang Guanfu , Gao Difei , Jiang Yu , Wang Zhe , Cui Jia , Xu Jiachen
Published: April 2023

Due to the high volatility and randomness of PV power generation, fast change frequency, limited data samples and poor data conditions, the reliability, stability and economy of grid operation are affected seriously. Therefore, the accurate prediction of PV power generation can mitigate the impact of its volatility on the stability of national grid power operations. And it improves PV consumption capacity and enhances the security of microgrid and distribution grid interconnection. This paper first proposed a PV power prediction method. Secondly, through the introduction and analysis of three types of prediction methods, the first type of prediction is selected using statistical analysis and modeling methods. Thirdly, an optimized Elman neural network-based PV power prediction model is proposed to allow accurate prediction of PV power prediction. Finally, an example is given to verify the advantages of the algorithm.
Analysis and treatment of oil chromatography of a 1000kV high voltage parallel reactor
Authors: Wei Kai , Qin Wenping
Published: April 2023

In this paper, the author combined with gas chromatography to a 1000kV high voltage shunt reactor oil chromatography anomaly analysis, preliminary theoretical analysis conclusion, then in the maintenance process through the equipment breakdown and the fault cause, verify the correctness of the theoretical analysis, for the next step of equipment manufacturers equipment manufacturing and process control provides advice.
Research on High-Frequency Data Acquisition Technology in Distributed Photovoltaic Station Areas
Authors: Kang Liyan , Shang Ying , Liu Xinran , Qin Yuewei
Published: April 2023

With the large-scale development of low-voltage distributed photovoltaic in power systems, the safe and effective operation of the power grid has been put forward. The analysis of the operation of distributed photovoltaics depends on the development of high-frequency data acquisition technology. This paper mainly aims at the problem of high-frequency data acquisition for distributed photovoltaic users and proposes a solution to achieve high-frequency data acquisition using high-speed power line carriers and dual-mode communication technology. The high-speed power line carrier is used to achieve minute-level data acquisition. The dual-mode communication technology further improves communication reliability. This paper provides theoretical support and construction experience for data acquisition and analysis of distributed photovoltaic users.
Evaluation of factors influencing subsynchronous oscillation of wind turbine
Authors: Wang Liqiang , Yuan Shuai , Zhang Xiuqi , Wang Qi , Cong Yu
Published: April 2023

Because of the subsynchronous oscillation caused by wind turbines connected to the AC power grid, the causes of subsynchronous oscillation are analyzed, and the frequency impedance test method of a wind turbine is proposed, which can effectively evaluate the impedance characteristics of a wind turbine. On this basis, the research on the influence of the parameters of several network side control links of the wind turbine generator, such as phase lock loop, current loop, and voltage loop, on the impedance characteristics is carried out. Combined with the influencing factors, a targeted improvement scheme for subsynchronous oscillation is proposed to improve the safety and stability of the wind turbine generator grid connection.
Distribution network planning with distributed photovoltaic and electric vehicle charging stations based on multi-population traction differential evolution algorithm
Authors: Wang Daye , Liu Yang , Wang Jing
Published: April 2023

Currently, in the background of a large number of distributed photovoltaic and electric vehicle charging stations with access to the distribution network, this paper presents a distribution network planning method with distributed photovoltaic and electric vehicle charging stations based on multi-population traction differential evolution algorithm. Firstly, this paper considers the curve characteristics of photovoltaic and load, and uses cluster analysis to determine the planning scenery, so that the planning results are more accurate. Then, the distribution network planning model is constructed from the aspects of the minimum investment cost, operation cost and performance index. Then, to improve the speed and the accuracy of planning results, the multi-population traction differential evolution algorithm is used to solve the planning model. Finally, a 10kV line is used as an example to verify the reliability of the proposed method. Then, the traditional differential evolution algorithm and the other two algorithms are compared and analyzed to verify the effectiveness of the proposed planning method.
Identification of Insulator Contamination Status Based on Multi-spectral Image Fusion and Radial Basis Function Neural Network
Authors: Li Lu , Wang Yi , Zhang Yang , Zhang Jian , Wang Wenjing , Wang Jiapeng
Published: April 2023

Insulator contamination monitoring is an important way to avoid insulator contamination and maintain insulation performance. In order to ensure power supply and achieve contactless detection of insulator contamination status, a method is proposed in this paper to identify insulator contamination status by adopting infrared, ultraviolet, and visible multi-spectral image information fusion. An insulator with different contamination states in a number of substations is taken as the research object in this paper. The image segmentation is performed by using the seed region growth method to extract the infrared, ultraviolet and visible features of the insulator surface, and the radial basis function neural network learning algorithm is used to classify and decompose and fuse the images according to their different local area energies. The comparison of the recognition rates using infrared and ultraviolet features with those fused shows that the method has significant advantages and provides a new method for the detection of insulator contamination status.
Fast assessment method of power outage risks caused by extreme cold disasters based on probabilistic graph model
Authors: Wang Zhiqiang , Yan Yunqi , Cui Zhengda , Chen Ying , Wang Dongsheng , Li Xin
Published: April 2023

The extremely cold weather may cause cascading failures of power grid components, resulting in large-scale outages and economic losses. Thus, to make better anti-disaster preparations, it is necessary to assess the system-level risk of the power grid efficiently with extreme weather predictions. This paper proposes a risk assessment method for power grids based on the probabilistic graphical model (PGM). First, the time-varying failure probabilities of power lines are estimated with consideration of the cascading effects of the direct impact of disasters and power flow transfer. Then, load supply reliabilities are fast inferred by solving the probability graph model of power component failure propagations. Finally, the overall outage risk is evaluated by considering the capacity and importance of different loads, which helps to improve anti-disaster decisions. Through theoretical analysis and case studies, the efficacy of the proposed method is verified.
Research on photovoltaic MPPT algorithm based on improved perturbation observation method
Authors: Hu Yuan , Wu Peng , Zheng Junguan , Wang Ning , Zhang Shuai , Li Yan , Zhao Penghui , Gao Ming , Li Tianhao
Published: April 2023

The connection of new energy, mainly solar energy, is closely related to the output of photovoltaic power supply. When the PV curve of photovoltaic output is optimally solved, it is easy to take the local optimal solution as the global optimal solution. Aiming at the shortcoming that the traditional perturbation observation method is only suitable for single peak tracking in maximum power tracking, the characteristics of photovoltaic output power are studied and analyzed, and the perturbation method is used to track the maximum power according to the distribution characteristics of each extreme point. Through the simulation analysis in MATLAB/Simulink environment, the results show that the improved algorithm has high accuracy and is easy to realize, and it has a good effect on solving the global optimal solution of photovoltaic output power.
Calculation of Emission Factors of the Northwest Regional Grid Based on Linear Support Vector Machines
Authors: Peng Yu , Chong Ting , Zhang Xiaoye , Chen Shaolin , Xie Gang
Published: April 2023

Machine learning can perform correlation analysis on a large amount of data and explore their relationship. Thus, the status quo can be analyzed, and the values of specific power industry indicators can be predicted in the future. This paper deduced the industry indicators that affect the grid emission factor by analyzing the grid emission factor algorithm. The study used the support vector machine regression algorithm to model and analyze collected power grid data and discussed the regression effect from five main aspects, including RMSE, MSE, MAE, coefficient and running time. Finally the most fitted regression model parameters were obtained. And the optimal model predicted the emission factors of the Northwest power grid.
Design of a multichannel polychromator for KTX Thomson scattering diagnostic
Authors: Peng Yuan , Jian Zheng , Weiqiang Tan , Peng Wang , Jinlin Xie , Tao Lan , Hong Li , Weixing Ding , Wandong Liu
Published: April 2023

A polychromator is designed based on the transmission volume phase holographic grating spectrometer coupled with avalanched photon diodes through fiber bundle and has been successfully implemented on the Keda Torus eXperiment [Plasma Phys. Control. Fusion
 56 (2014) 094009] Thomson scattering system. The polychromator is operated with a 1064 nm laser, and the designed spectral range is from about 1000 nm to 1100 nm. The spectral channels have been optimized with a five-channel design to lower the estimated error of the electron temperature and density within 5% and 3% respectively when the temperature is around 100 eV. With a calibration method about the ratio of the channel average responses using bremsstrahlung radiation, we obtain an electron temperature of 7 eV in a typical experiment with low plasma currents.
A new method for the timber tracing toolbox: applying multi-element analysis to determine wood origin
Authors: Boeschoten Laura E , Vlam Mart , Sass-Klaassen Ute , Rocha Venâncio Meyer-Sand Barbara , Adzkia Ulfa , Bouka Gaël D U , Ciliane-Madikou Jannici C U , Engone Obiang Nestor L , Guieshon-Engongoro Mesly , Loumeto Joël J , Mbika Dieu-merci M F , Moundounga Cynel G , Ndangani Rita M D , Bourobou Dyana Ndiade , Rahman Mohamad M , Siregar Iskandar Z , Tassiamba Steve N , Tchamba Martin T , Toumba-Paka Bijoux B L , Zanguim Herman T , Zemtsa Pascaline T , Zuidema Pieter A
Published: April 2023

To effectively reduce illegal timber trade, law enforcers need forensic methods to independently verify claims of wood origin. Multi-element analysis of traded plant material has the potential to be used to trace the origin of commodities, but for timber it has not been tested at relevant large scales. Here we put this method to the test, by evaluating its tracing accuracy for three economically important tropical timbers: Azobé and Tali in Central Africa (22 sites) and Red Meranti on Borneo (9 sites). Wood samples from 991 trees were measured using Inductively Coupled Plasma Mass Spectrometry and element concentrations were analysed to chemically group similar sites (clustering) and assess accuracy of tracing samples to their origin (Random Forest models). For all three timbers, we found distinct spatial differences in chemical composition. In Central Africa, tracing accuracy was 86%–98% for regional clusters of chemically similar sites, with accuracy depending on the tracing question. These clusters were 50–800 km apart and tracing accuracy was highest when combining the two timbers. Tracing accuracy of Red Meranti on Borneo was 88% at the site level. This high accuracy at a small scale may be related to the short distances at which differences in soil type occur on Borneo. A blind sample analysis of 46 African timber samples correctly identified the origin of 70%–72% of the samples, but failed to exclude 70% of the samples obtained from different species or outside the study area. Overall, these results illustrate a high potential for multi-element analysis to be developed into a timber tracing tool which can identify origin for multiple species and can do so at a within-country scale. To reach this potential, reference databases need to cover wider geographic areas and represent more timbers.
The impact of policy and model uncertainties on emissions projections of the Paris Agreement pledges
Authors: den Elzen Michel G J , Dafnomilis Ioannis , Hof Andries F , Olsson Marika , Beusen Arthur , Botzen W J Wouter , Kuramochi Takeshi , Nascimento Leonardo , Rogelj Joeri
Published: April 2023

Tracking progress towards the Paris Agreement climate goal requires understanding the 2030 emission levels implied by countries’ National Determined Contributions (NDCs). However, key uncertainties and assumptions impact greenhouse gas (GHG) emission projections implied by the NDCs. This study analyses this impact, both globally and for major emitting countries. We find that the assessed uncertainties markedly affect global GHG emission projections. Full achievement of NDC targets is estimated to result in a range of 46–60 GtCO2eq by 2030 (median estimate: 53 GtCO2eq). The uncertainty in measuring historical emissions, including land-use, as reflected by different datasets is the most important contributing factor. This is followed by two equally important factors globally: socio-economic baseline uncertainty and uncertainty about the emissions implied by current policies in case NDCs are less ambitious than these. Overall, the impact of policy uncertainty (i.e. uncertainty resulting from conditionality of or ranges in NDC targets and uncertainty in emissions resulting from current policies) is about equally important as model/technical uncertainty (i.e. uncertainty in historical emissions and socio-economic baseline variations). This new insight is important for decision makers and researchers because a larger share of the total uncertainty is now attributable to aspects that can be influenced by policy decisions compared to previous analyses of NDC uncertainty.
Studying the Inhibitory Effect of Cinnamon and Ginger Aqueous Extracts Against Rice-Associated Fungi that Produce Aflatoxin
Authors: Al-Alwani Khalid Abbood Kurdi , Al-Nazzal Ahmed Ismail
Published: April 2023

The studying included testing the inhibitory activity of the aqueous extracts of cinnamon (Cinnamomum zylanicum) and ginger (Zingibero fficinale) at three concentrations (50, 100 and 200 mgL-1) on the aflatoxin-producing fungi (Aspergillus lavus and Aspergillus parasiticus) isolated from rice used for daily consumption in Iraq as well as the studying of possibility of reducing the aflatoxins after treating the fungal isolates with aqueous extract of medicinal plants. The studying showed the possibility of isolating and diagnosing three genera of fungi using phenotypic and microscopic characteristics based on taxonomic keys. The results showed the presence of three species of Aspergillus (A. flavus, A. parasiticus and A. niger), in addition to the Penicillium spp. and Fusarium spp. at different appearance rates. Also, the results revealed that the aqueous extract of cinnamon and ginger had inhibitory activity against the aflatoxin producing fungi at a concentration of 200 mgL-1 and that the fungal diameter of the inhibition area was 22 mm for both A. flavus and A. parasiticus.
Curdlan Gum, Properties, Benefits and Applications
Authors: Al-Rmedh Y. S. S. , Ali H. I. , Al-Sahlany S. T. G.
Published: April 2023

Curdlan gum is a new polymer produced by the microbial fermentation of sugar raw materials. It has the unique property of forming a gel under heating conditions and is also called a thermal gel. In 1996, the FDA approved the application of curdlan gum as a food raw material in the food industry. Curdlan gum does not dissolve in water, but it will swell and disperse easily in cold water. It is heated to form a colloid, according to its properties can be divided into low colloid and high colloid. It is produced by heating to 55~65°C and cooling to about 40°C, forming low-grade colloid with thermal reflection. When the water dispersion of cordlan gum is heated to more than 80°C, a higher colloid is formed. The Curdlan gel can reduce the water loss rate of chilled meat products and extend their shelf life.
The Effectiveness of the Probiotic Bacillus Spp in Induced Infection with Staphylococcus aureus and the Study of Its Effect on Liver Enzymes, Kidney Function and Microbial Balance of the Gut in Male Rats
Authors: Werdi Chalang M. , Al-Hadidy Yasmeen I.
Published: April 2023

The current study aimed to isolate and characterize bacteria of the genus Bacillus. It alsoinvestigate their ability as bio-enhancers, and study their therapeutic effect in vivo in induced infection with Staphylococcusaureus in terms of their impact on the values of liver enzymes Alanine trasaminase, Aspartate aminotranferase, Alkaline phosphatase and kidney functions represented by creatinine and urea, and the microbial balance of the intestine in male rats which were compared with the control groups after a period of 28 days. The study used 20 male Albino Sprague-Dawley rats, ages 8-9 weeks, average weight 148 g. These rats were randomly divided into five groups and four replicates per group. Two types of probiotics of the genus Bacillus were obtained, Bacillus claussi and Bacillus megaterum. The results showed that infection induced by Staphylococcusaureus caused a significant increase at P<0.05 in the values of all liver enzymes ALP, ALT and AST, which were recorded (194.4, 73.17 and 188.6) IU/L compared to the control group, which recorded (180.6, 59.50 and 178.5) IU/L in the same order. The results also showed an increase in creatinine and urea concentrations (52.00 and 0.3000), compared to the control group, which recorded (40.07 and 0.2667) mg/dI. In terms of microbial balance, the results showed an increase in the total number of the tested pathogenic bacteria and a significant decrease in the total number of lactic acid bacteria compared with the control group rats.
Using Artificial Intelligence Techniques to Predict Changes in Land Cover and Land use in Saddha Al-Hindia District Until 2038 by Adopting the (CA-MARCOV) Model
Authors: Abbas Ahmed A. Hadi , Hussain Entessar K. , Hamza Jabbar S. Abdel
Published: April 2023

The aim of this study is to employ CA-MARCOV model as an advanced tool for predicting the state of land cover and land use in Saddha Al-india district until 2038 as a sophisticated tool representing the integration of GIS and remote sensing to predict the state of land cover and land use in Saddha Al-Hindia district. The study found that the land cover and land use categories in the study area recorded a relatively variable probability of their transmission to other varieties, as it reached the highest percentage in the river, which recorded (54.83) for the possibility of moving it at the expense of agricultural land which recorded (53.58), While the other varieties have a transmission probability of (34.75), (29.15), (16.16) and (12.03) to bare land, urban, natural vegetation and water bodies, respectively. All the mentioned percentages were of little stability in favor of the agricultural land category, as shown in Table (1). Where the area of agricultural land equivalent to (126 km2) for the predicted year, while its area was about (114 km2) in 2018, as well as natural vegetation, whose area in the target year was (79 km2) compared to (84 km2) in 2018, in Saddha Al-Hindia district to the next 20 years until 2038.