bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on path tracking control of unmanned vehicle
Authors: Wang Yunjing , Wang Jian , Yang Jun , Du Ruofei , Hai Zhenyang , Deng Huan 
Published: April 2023

Abstract
With the continuous progress of science and technology, driverless vehicles have become one of the development trends of automobiles in the future. Path tracking control is a key problem in the research of driverless vehicles. Based on one control theory or by combining several different theories, different control algorithms are proposed, and some achievements have been made. This paper mainly studies the tracking control research method, which is a key problem in driverless vehicles. By analyzing and comparing the LQR control method and MPC control method, we compare their advantages and disadvantages, understand the concepts and related algorithms of various path-tracking control methods, and analyze the advantages and disadvantages of various control methods.
Adaptive Dynamic Surface Control of Buck Converter Based on Energy Storage System
Authors: He Huan , Jia Yilin , Guan Qi , Wang Duo , Zhang Tianyi , Ni Yulin , Zhang Xiuyu , Zhu Guoqiang 
Published: April 2023

Abstract
To enhance the stability of the Buck converter and the capacity of resisting disturbance of the controller and converter, come up with an adaptive dynamic surface control strategy based on voltage mode control, which improves the ability of the energy storage system to stabilize the output voltage when the input voltage or load changes. The Radial Basis Function (RBF) neural network is combined with the finite covering lemma to approximate the unknown nonlinear functions with time-delay in the system. The error conversion and performance functions are adopted to ensure the tracking performance index. The adaptive dynamic surface controller is applied to ensure the stability of the output voltage of the system when the external conditions change. The proposed control method is tested on the hardware-in-the-loop (HIL) experimental platform. The consequence illustrate that the designed controller is feasible and has good voltage stability performance.
Design of Novel Ultra-wideband Slow-wave Microstrip Transmission Line
Authors: Yang Cheng , Wu Ruinan , Xiao Zhiliang. , Xu Wenfang 
Published: April 2023

Abstract
Microwave passive devices with high efficiency, small size, and light weight are one of the fundamental requirements for mobile communication coverage in the 5G frequency band. In this paper, the design of a novel ultra-wideband slow-wave microstrip transmission line is proposed and studied. The electromagnetic field simulation software HFSS is used to simulate the slow-wave microstrip transmission line, and the simulation results show that the ultra-wideband slow-wave structure has the advantage of wider bandwidth, smaller size, and lower cost, which meets the needs of 5G communication systems. Finally, the proposed slow-wave microstrip line is used in the U-shaped phase shifter, and the experimental results show that the novel slow-wave microstrip transmission line has a large application potential in the base station antenna system.
Theoretical Analysis of External Insulation of Typical Electric Equipment under Impulse Voltage and Research on Design and Verification Method of Margin
Authors: Zhang Shiling , Xiping Jiang 
Published: April 2023

Abstract
Lightning impulse voltage, one of the typical characteristic working conditions for assessing high-voltage power equipment, can be divided into two forms, namely full wave, and chopped wave. The external structure size of the power equipment directly depends on the lightning impulse voltage, but how lightning impulse voltage relates to the external structure size of the power equipment needs to be carefully studied. Firstly, the theoretical analytical expressions of full wave and chopped wave lightning waveforms are given from the perspective of theoretical formulas. And the lightning waveform is considered to be a polynomial superposition of exponential functions. Based on this, the discussion is divided into two typical insulation structure scenarios: 1) the verification and analysis of the space net distance of a 10 m class super long composite insulator; 2) the analysis of the relationship between the breakdown electric field strength of 5 mm tiny oil gap and oil gap spacing. Further, the lightning impulse voltage test was conducted for large hardware structures, and the corona layer mathematical model was obtained through the precise observation of the structure with the ultraviolet imager. The research shows that the lightning impulse voltage mainly checks the external insulation performance of large insulation structures such as bushings and post-insulators. For the internal oil gap duct structure of the large converter transformer, the lightning impulse voltage mainly checks the micro gap insulation strength. Lightning impulse voltage also has a breakdown effect on SF6 insulation gas, but its internal gas decomposition mechanism needs theoretical and experimental analysis urgently. The research content of this paper has certain theoretical and practical guiding value for the optimization design of large insulation structures under lightning impulse voltage.
Implementation of Channel Equalization for Large-scale Wideband Digital Array
Authors: Liu Hui , Shang Linfeng , Zhang Yuehua 
Published: April 2023

Abstract
Channel equalization is essential in wideband digital array radar to compensate the channel distortion and mismatch. Inverse Fourier transform (IFT) method and weighted least squares (WLS) algorithm are used to calculate the coefficients of the equalizer filter. However, the accuracy of equalizer coefficient calculation is affected by many non-ideal factors in the actual correction of large-scale digital TR channels. This paper aims to analyze the influence of various non-ideal factors in equalizer coefficient calculation and propose a test method to reduce or eliminate their influence. Finally, based on 90 channel scale FPGA-based system, the method proposed in this paper is tested and verified, and good performance is achieved.
Analysis of Communication Simulation Model of Urban Comprehensive Energy Network Based on the Internet of Things
Authors: Fang Xin , Yuan Xiaodong , Pan Yi , Shi Mingming , Yang Jinggang , Sun Tiankui 
Published: April 2023

Abstract
In urban construction, all energy infrastructures have been realized by the information structure. However, due to the non-uniform structure of each energy network, the data cannot be more compatible, and the communication guarantee based on the Internet of Things is one of the most urgent problems to be solved. In this paper, a reasonable network computing offloading model is designed in the edge computing layer, and the computing offloading algorithm is introduced. Considering the dependency between subtasks, an optimization problem is established, and a central scheduling algorithm is proposed to solve it. An optimized distributed unloading algorithm is proposed according to the solution idea of the classical distributed unloading algorithm. Simulation results show that the optimized distributed unloading algorithm proposed in this paper has good solving efficiency and performance, and reduces the task processing delay. At the same time, the experimental simulation proves that the efficiency of multiple edge servers in processing subtasks is higher than that of a single server. It is established that changing the convergence speed and communication delay stability margin of the system by changing the system eigenvalue is beneficial to design a better communication network structure to keep the system stable.
Node Importance Evaluation Method of Satellite Information Network Based on Heterogeneous Virtual Subnet
Authors: Li Jingling , Li Jun , Cui Tao , Liang Wei , Zhang Yi 
Published: April 2023

Abstract
The node importance evaluation method is of great significance for studying the robustness and routing strategies of satellite information network. According to the heterogeneous characteristics of nodes in satellite information network, they can be abstracted into two types of virtual connected nodes, and then the satellite information network model based on multi-virtual subnet is constructed. Furthermore, the node importance evaluation method based on heterogeneous virtual subnet (named HVS_based NIE) is proposed through the defined parameters such as normalization degree of virtual nodes, virtual node betweenness and correlation factor, which can accurately evaluate the node importance of satellite information network. Results of case analysis show that compared with classical graph theory algorithm, the proposed HVS_based NIE algorithm not only considers the network connectivity, but also considers the impact of data throughput on the nodes importance of satellite network, so as to evaluate the nodes importance of satellite network more accurately.
Telemetry Data Processing and Analysis Platform for Flight Test Based on Flink
Authors: Hao Mingzhe , Wang Xi 
Published: April 2023

Abstract
Telemetry data processing has extremely high real-time requirements in flight tests. In response to the problems faced by the traditional telemetry data processing system, such as insufficient computing capacity and low scalability, the Flink-based telemetry data processing and analysis technology is proposed to give full play to the cluster computing capacity of Flink, improve the throughput of real-time processing and reduce the processing delay. After flight test verification, the platform meets the real-time processing of multiple telemetry data and has significantly improved the stability, processing efficiency, and scalability compared with the traditional system.
Demonstration of Gd-GEM detector design for neutron macromolecular crystallography applications
Authors: Pfeiffer D. , Brunbauer F. , Cristiglio V. , Hall-Wilton R. , Lupberger M. , Markó M. , Muller H. , Oksanen E. , Oliveri E. , Ropelewski L. , Rusu A. , Samarati J. , Scharenberg L. , van Stenis M. , Thuiner P. , Veenhof R. 
Published: April 2023

Abstract
The European Spallation Source (ESS) in Lund, Sweden will
become the world's most powerful thermal neutron source. The
Macromolecular Diffractometer (NMX) at the ESS requires three
51.2 × 51.2 cm2 detectors with reasonable detection
efficiency, sub-mm spatial resolution, a narrow point-spread
function (PSF), and good time resolution. This work presents
measurements with the improved version of the NMX detector prototype
consisting of a Triple-GEM (Gas Electron Multiplier) detector with a
natural Gd converter and a low material budget readout. The detector
was successfully tested at the neutron reactor of the Budapest
Neutron Centre (BNC) and the D16 instrument at the Institut
Laue-Langevin (ILL) in Grenoble. The measurements with Cadmium and
Gadolinium masks in Budapest demonstrate that the point-spread
function of the detector lacks long tails that could impede the
measurement of diffraction spot intensities. On the D16 instrument
at ILL, diffraction spots from Triose phosphate isomerase w/
2-phosphoglycolate (PGA) inhibitor were measured both in the MILAND
Helium-3 detector and the Gd-GEM. The comparison between the two
detectors shows a similar point-spread function in both detectors,
and the expected efficiency ratio compared to the Helium-3
detector. Both measurements together thus give good indications that
the Gd-GEM detector fits the requirements for the NMX instrument at
ESS.
Rectifying low-frequency variability in future climate sea surface temperature simulations: are corrections for extreme change scenarios realistic?
Authors: Kusumastuti Cilcia , Mehrotra Rajeshwar , Sharma Ashish 
Published: April 2023

Abstract
Most procedures for redressing systematic bias in climate modeling are calibrated using current climate observations, and perform well. However, their performance in the future climate remains uncertain as no observations exist to compare against. In this context, we use the current and future climate outputs of an ultra-high resolution of Community Earth System Model (UHR-CESM) as the representative truth and bias correct monthly sea surface temperature (SST) simulations of eight Coupled Model Intercomparison Project 6 models over the Niño 3.4 region. A time-frequency bias correction approach is used to correct for bias in distributional, trend, and spectral attributes present in the models. This results in a near perfect power spectrum of the bias corrected current climate model simulations. Considering all correction procedures remain unchanged into the future, the overall representation of the corrected SST simulations shows improvement with consistency across models for the doubled CO2 scenario, but higher variability and lower consistency in the quadrupled CO2 concentration scenario.
Dynamic recrystallization behavior and processing maps of 5CrNiMoV steel during hot deformation
Authors: Li Qin , Bu Hengyong , Han Jiuyan , Li Mengnie 
Published: April 2023

Abstract
Hot deformation tests of 5CrNiMoV steel were performed at deformation temperatures of 700 to 870 °C and strain rates of 0.001 to 0.1 s−1 using the DIL 805D thermomechanical simulator. The critical strain and volume fraction models of Dynamic Recrystallization (DRX) were constructed based on the work hardening theory. The results showed that the critical strain of DRX decreases with increasing deformation temperature and decreasing strain rate, which implies that DRX occurs easily at higher temperatures and lower strain rates. The average DRX grain size model was established to predict grain size changes during hot deformation. Based on the hot processing maps that were constructed using the Dynamic Material Model (DMM) and microstructure observation, the optimum hot working parameters for 5CrNiMoV steel are a deformation temperature of 800 °C–870 °C, a strain rate of 0.001–0.05 s−1.
A practical exploration of land cover impacts on surface and air temperature when they are most consequential
Authors: Novick Kimberly A , Barnes Mallory L 
Published: April 2023

Abstract
Widespread shifts in land cover and land management (LCLM) are being incentivized as tools to mitigate climate change, creating an urgent need for prognostic assessments of how LCLM impacts surface energy balance and temperature. Historically, observational studies have tended to focus on how LCLM impacts surface temperature (T
surf), usually at annual timescales. However, understanding the potential for LCLM change to confer climate adaptation benefits, or to produce unintended adverse consequences, requires careful consideration of impacts on both T
surf and the near-surface air temperature (T
a,local) when they are most consequential for ecosystem and societal well-being (e.g. on hot summer days). Here, long-term data from 130 AmeriFlux towers distributed between 19–71 °N are used to systematically explore LCLM impacts on both T
surf and T
a,local, with an explicit focus on midday summer periods when adaptive cooling is arguably most needed. We observe profound impacts of LCLM on T
surf at midday, frequently amounting to differences of 10 K or more from one site to the next. LCLM impacts on T
a,local are smaller but still significant, driving variation of 5–10 K across sites. The magnitude of LCLM impacts on both T
surf and T
a,local is not well explained by plant functional type, climate regime, or albedo; however, we show that LCLM shifts that enhance ET or increase canopy height are likely to confer a local mid-day cooling benefit for both T
surf and T
a,local most of the time. At night, LCLM impacts on temperature are much smaller, such that averaging across the diurnal cycle will underestimate the potential for land cover to mediate microclimate when the consequences for plant and human well-being are most stark. Finally, during especially hot periods, land cover impacts on T
a,local and T
surf are less coordinated, and ecosystems that tend to cool the air during normal conditions may have a diminished capacity to do so when it is very hot. We end with a set of practical recommendations for future work evaluating the biophysical impacts and adaptation potential of LCLM shifts.
Extracorporeal cardiopulmonary resuscitation: A primer for pharmacists
Authors: Brown Caitlin S , Wieruszewski Erin D , Nei Scott D , Vollmer Nicholas J , Mattson Alicia E , Wieruszewski Patrick M 
Published: April 2023

Abstract

Purpose
To describe the use of mechanical circulatory support in the setting of cardiac arrest and summarize pharmacists’ role in extracorporeal cardiopulmonary resuscitation (ECPR).

Summary
ECPR is increasingly used to reduce morbidity and improve mortality after cardiac arrest. ECPR employs venoarterial ECMO, which provides full circulatory perfusion and gas exchange in both adult and pediatric patients in cardiac arrest. After the emergency medicine team identifies potential candidates for ECPR, the ECMO team is consulted. If deemed a candidate for ECPR by the ECMO team, the patient is cannulated during ongoing standard cardiopulmonary resuscitation. A multidisciplinary team of physicians, nurses, perfusionists, pharmacists, and support staff is needed for successful ECPR. Pharmacists play a vital role in advanced cardiac life support (ACLS) prior to cannulation. Pharmacists intervene to make pharmacotherapy recommendations during ACLS, prepare medications, and administer medications as allowed by institutional and state regulations. Pharmacists also provide pharmacotherapy support in the selection of anticoagulation agents, ongoing vasopressor administration during ECMO cannulation, and the optimization of medication selection in the peri-ECPR period.

Conclusion
With the growing use of ECPR, pharmacists should be aware of their role in medication optimization during ECPR.
Tirzepatide: Clinical review of the “twincretin” injectable
Authors: Krauss Zach , Hintz Alexandra , Fisk Rebecca 
Published: April 2023

Abstract

Purpose
To provide an overview of the safety and efficacy, pharmacology, dosing, place in therapy, and clinical trials for tirzepatide, a novel glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) agonist for treatment of type 2 diabetes.

Summary
Diabetes is a chronic disease state with a high burden on healthcare spending and patient quality of life. Incretin-influencing agents such as GLP-1 receptor agonists have gained favor as diabetes therapeutic options due to their impact on multiple glycemic factors as well as resulting weight loss and cardiovascular benefits. Tirzepatide was approved in 2022 for the management of type 2 diabetes and utilizes GLP-1 receptor agonism along with GIP agonism to simultaneously address 2 incretin pathways. Thus far, the SURPASS and SURMOUNT trials, for which findings have been published, have shown great efficacy of tirzepatide in glycosylated hemoglobin and weight reduction in multiple subgroup populations with and without diabetes. Tirzepatide has similar gastrointestinal adverse reactions and contraindications as traditional GLP-1 receptor agonists.

Conclusion
Tirzepatide is a novel agent on the market for type 2 diabetes management that offers targeting of a familiar pathway along with the new GIP pathway to address glycemic control in patients with diabetes. Tirzepatide is approved for use in patients with diabetes and may serve as a strong option for patients requiring improved glycemic and weight control.
3D-MSNet: a point cloud-based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data
Authors: Wang Ruimin , Lu Miaoshan , An Shaowei , Wang Jinyin , Yu Changbin 
Published: April 2023

Abstract

Motivation
Liquid chromatography coupled with high-resolution mass spectrometry is widely used in composition profiling in untargeted metabolomics research. While retaining complete sample information, mass spectrometry (MS) data naturally have the characteristics of high dimensionality, high complexity, and huge data volume. In mainstream quantification methods, none of the existing methods can perform direct 3D analysis on lossless profile MS signals. All software simplify calculations by dimensionality reduction or lossy grid transformation, ignoring the full 3D signal distribution of MS data and resulting in inaccurate feature detection and quantification.

Results
On the basis that the neural network is effective for high-dimensional data analysis and can discover implicit features from large amounts of complex data, in this work, we propose 3D-MSNet, a novel deep learning-based model for untargeted feature extraction. 3D-MSNet performs direct feature detection on 3D MS point clouds as an instance segmentation task. After training on a self-annotated 3D feature dataset, we compared our model with nine popular software (MS-DIAL, MZmine 2, XCMS Online, MarkerView, Compound Discoverer, MaxQuant, Dinosaur, DeepIso, PointIso) on two metabolomics and one proteomics public benchmark datasets. Our 3D-MSNet model outperformed other software with significant improvement in feature detection and quantification accuracy on all evaluation datasets. Furthermore, 3D-MSNet has high feature extraction robustness and can be widely applied to profile MS data acquired with various high-resolution mass spectrometers with various resolutions.

Availability and implementation
3D-MSNet is an open-source model and is freely available at https://github.com/CSi-Studio/3D-MSNet under a permissive license. Benchmark datasets, training dataset, evaluation methods, and results are available at https://doi.org/10.5281/zenodo.6582912.
Standardized perioperative management in acute abdominal surgery: Swedish SMASH controlled study
Authors: Timan Terje J , Karlsson Ove , Sernert Ninni , Prytz Mattias 
Published: April 2023

Abstract

Background
Acute high-risk abdominal surgery is common, as are the attendant risks of organ failure, need for intensive care, mortality, or long hospital stay. This study assessed the implementation of standardized management.

Methods
A prospective study of all adults undergoing emergency laparotomy over an interval of 42 months (2018–2021) was undertaken; outcomes were compared with those of a retrospective control group. A new standardized clinical protocol was activated for all patients including: prompt bedside physical assessment by the surgeon and anaesthetist, interprofessional communication regarding location of resuscitation, elimination of unnecessary factors that might delay surgery, improved operating theatre competence, regular epidural, enhanced recovery care, and frequent early warning scores. The primary endpoint was 30-day mortality. Secondary endpoints were duration of hospital stay, need for intensive care, and surgical complications.

Results
A total of 1344 patients were included, 663 in the control group and 681 in the intervention group. The use of antibiotics increased (81.4 versus 94.7 per cent), and the time from the decision to operate to the start of surgery was reduced (3.80 versus 3.22 h) with use of the new protocol. Fewer anastomoses were performed (22.5 versus 16.8 per cent). The 30-day mortality rate was 14.5 per cent in the historical control group and 10.7 per cent in the intervention group (P = 0.045). The mean duration of hospital (11.9 versus 10.2 days; P = 0.007) and ICU (5.40 versus 3.12 days; P = 0.007) stays was also reduced. The rate of serious surgical complications (grade IIIb–V) was lower (37.6 versus 27.3 per cent; P = &lt;0.001).

Conclusion
Standardized management protocols improved outcomes after emergency laparotomy.