bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variable mechanism of electrical impedance for MCT high voltage switch under synergetic action of the mechanical and electric loads
Authors: Chen Chuang , Guo Zihan , Guo Yuyang , Wang Ruizhi , Tang Enling 
Published: September 2023

Abstract
To study the electromechanical coupling effect of Metal Oxide Semiconductor Controlled Thyristor (MCT) high voltage switch under the synergistic action of mechanical load and strong voltage in the actual use of penetrating hard targets and launching, the universal testing machine was used to simulate the overload environment. The rising edge time, falling time and impedance changes in the conduction path of MCT under different stress–strain were tested, respectively. Experimental results showed that the rise time of MCT decreased from 0.08 ms to 0.03 ms when the uniaxial compressive stress increased from 1.20 MPa to 7.3 MPa, and the rising edge time after unloading was 0.04 ms. The falling time had no obvious change with the increase of stress. The total resistance in the path decreased from 833.30 Ω to 564.22 Ω with the increase of strain. The stress–strain of each part of MCT under different uniaxial compressive stress was collected by COMSOL Multiphysics finite element software. Based on the Schrödinger equation, the potential energy operator was established. By introducing the strain Hamiltonian H

ε,ν
, the E(k)-k model near the minimum value of the conduction band of Si was established by using the k·p perturbation method. Combined with the physical field interface of Schrödinger equation in COMSOL Multiphysics, the valence band structure of Si material under uniaxial strain was studied on the basis of strain Hamiltonian perturbation. The results showed that the 6-degree degenerate valley (Δ6) in the conduction band was split into a 2-degree degenerate valley (Δ2) and a 4-degree degenerate valley (Δ4) due to the stress effect. The strain caused more electrons to occupy the lower Δ4 energy valley, resulting in a decrease in the effective mass of the total conductivity. Therefore, the electron mobility of Si was increased under uniaxial strain. The uniaxial compressive stress could more effectively reduce the curvature radius of valence band top, the effective mass of carriers and the interband scattering between light and heavy hole bands, which was beneficial to improve the hole mobility.
Evaluation of Renewable Energy Accommodation Capacity Considering Multiple Flexibility Resources of Source-Load-Storage
Authors: Liu Juan , Wang Zhimin , Zhao Shuang , Chen Yu , Wang Lingyi , Zhang Xiuzhao , Chen Wen 
Published: September 2023

Abstract
The utilization of multiple flexibility resources (MFR), such as source-load-storage (SLS-sides), plays a vital role in promoting the integration of large-scale grid-connected renewable energy (RE). Analyzing the renewable energy accommodation capacity (REAC) and assessing the impact of flexibility resources on enhancing REAC is vital for the coordinated development of SLS sides. This study focuses on the technical mechanisms of thermal power (TP) deep peak regulation, load demand response (DR), and energy storage (ES). Considering the operational constraints of these MFR, an evaluation model for REAC is established. The model is a multi-objective optimization framework that encompasses the maximized installed capacity of RE while minimizing the comprehensive expenses of the power system. A hierarchical decoupling solution method is used to solve the evaluation model, obtaining the Pareto optimal solution set for RE installed capacity and power system operating cost. Subsequently, a fuzzy membership function is applied to select a compromise solution, quantitatively characterizing the REAC. The case study results demonstrate that by effectively coordinating the “SLS-sides” MFR, the REAC of the IEEE-RTS96 system can be improved from 1, 758 MW to 2, 731 MW, indicating a remarkable enhancement of 55.35%.
Wind Power-Photovoltaic-Hydropower Optimization in Watershed Based on Wind Power-Photovoltaic Cluster Convergence
Authors: Liu Juan , Zhao Yuanyuan , Zhao Shuang , Wang Zhimin , Chen Yu , Wang Lingyi 
Published: September 2023

Abstract
With the construction of wind power-photovoltaic-hydropower (WVH-system) clean energy base in the river basin, the complex geographical distribution characteristics of WVH-system along the river basin and the randomness and fluctuation of their output bring challenges to the basin on a large scale. How to consider the complementary characteristics of wind-photovoltaic (WV-power) output and cluster effect to smooth the WV-power output curve is an important way to solve this challenge. For this reason, a WVH-system bundling optimization method based on WV-power cluster convergence is proposed in this paper. Considering the complementary coupling characteristic of wind power and photovoltaic output, the output characteristic index of the WV-power cluster is constructed to evaluate the output complementarity, output stationarity and load tracking characteristics of the WV-power cluster. Based on the characteristic index, the clustering method of the WV-power cluster is constructed to divide the WV-power power cluster along the river basin. A basin WVH-system bundling optimization model is developed based on the division of clusters and efficient utilization of pumped storage units’ regulation capacity. Finally, the WVH-system data of a river basin in southwest China are taken as an example to verify the effectiveness of the proposed method.
Multi-objective Capacity Planning for Expressway Microgrid Considering Photovoltaic Panel Dust Removal Maintenance
Authors: Liao Guangrong , Yang Xiaojuan , Lou Suhua , Qin Weijie , Liu Jin , Hong Xuanjiao 
Published: September 2023

Abstract
The increasing passenger volume and the rapid development of the electric vehicle industry make the electricity consumption of the expressway service area grow day by day. It is of great significance to study the planning and design method of the microgrid in the expressway service area. This paper established a wind-photovoltaic-storage capacity planning model for the microgrid in expressway service areas, which considered the dust removal maintenance of photovoltaic panels. The multi-objective optimization problem was solved by the improved fast non-dominated sorted genetic algorithm (NSGA II) with the aim of minimizing the total system investment, and operating cost and maximizing the self-consistent rate of electricity consumption of the microgrid. The Pareto optimal solution frontier with uniform distribution and wide range is obtained, and the capacities of PV, wind power, energy storage, and contact line are obtained under different self-consistent rates of electricity consumption. This method can not only make full use of distributed PV resources that can be developed on the expressway to improve the self-consistent level of energy but also comprehensively evaluate the economy of the microgrid system and meet the requirements of power supply reliability.
Study on forecasting model of transmission line failure rate and outage time
Authors: Liu Jie , Zhang Zhimeng , Zheng Xiongwei 
Published: September 2023

Abstract
Given the complex problem of transmission line failure and outage and the difficulty of predicting the failure rate and outage time of the transmission line with certainty, the accident prediction information is provided for power grid managers. This paper proposes a three-order fundamental Fourier function fault rate prediction model based on a monthly time scale. This method does not rely on any strict assumptions and is driven by the real transmission line fault data in a province. The fitting results reflect the monthly bimodal fault characteristic distribution law of the transmission line fault rate. On this basis, the historical outage time is analyzed and counted, the probability density distribution characteristics of forced outage time are proposed, and the ExpGro function is used to fit it. The results show that the prediction results of the model proposed in this paper have good sharpness and reliability, which has a guiding significance for actual maintenance work.
Systematic effects in the search for a muon electric dipole moment using the frozen-spin technique
Authors: Dutsov Chavdar , Giovanozzi Massimo , Hume Timothy , Schmidt-Wellenburg Philipp ,   the muonEDM collaboration
Published: September 2023

Abstract
At the Paul Scherrer Institute we are developing a high precision instrument to measure
the electric dipole moment (EDM) of the muon. The salient feature of the experiment is the use of
the frozen-spin technique to suppress the anomalous precession of the muon spin, allowing for a
sensitivity that cannot be achieved with conventional g-2 muon storage rings. With this technique,
the expected statistical sensitivity for the EDM after one year of data taking is
6 × 10-23 e · cm with a p = 125 MeV/c muon beam available at PSI.
Reaching this goal necessitates a comprehensive analysis on spurious effects that mimic the EDM signal. This work discusses a quantitative approach to study systematic effects for the frozen-spin technique when searching for the muon EDM with a focus on the kinematics of decay positrons in the context of this experiment, which operates at muon momenta well below the ultrarelativistic limit.
Comparative evaluation of radiation detection capabilities of CsPbI2Br and CsPbIBr2 materials for the development of QA relative dosimeter for brachytherapy
Authors: Yang S.W. , Kim J.Y. , Cho S.J. , Kim K.H. , Park S.K. 
Published: September 2023

Abstract
High-dose-rate brachytherapy is a cancer treatment that intensively irradiates tumors by inserting radioactive isotopes with high dose rates into the body. For this treatment, it is necessary to deliver an appropriate dose to the tumor tissue through an accurate treatment plan but only deliver the minimum dose to the normal tissue. Therefore, it is imperative to verify the positional accuracy of the source through accurate quality assurance (QA) in clinical practice. However, in clinical practice, the position of the source is visually determined using rulers, automatic radiographers, video monitors, and other devices, yielding inaccurate results. In this study, a semiconductor dosimeter using either CsPbI2Br or CsPbIBr2 was manufactured. The radiation detectability of both materials was tested and compared to evaluate which of the two materials would be more suitable as the QA relative dosimeter for brachytherapy. The reproducibility, linearity, and percentage interval distance (PID) of the two materials were analyzed to evaluate the radiation detectability and applicability of the relative dosimeter. In the reproducibility evaluation, the relative standard deviation (RSD) of CsPbI2Br was 0.98%, and the RSD of CsPbIBr2 was 3.45%. In the linearity evaluation, the coefficient of determination (R2) of CsPbI2Br was 0.9998, and the R2 of CsPbIBr2 was 0.9994. In the PID evaluation, both materials showed an exponential and constant decrease in measured signal sizes as the distance from the source increased. As a result of the evaluations, the CsPbI2Br dosimeter showed greater stability in detecting radiation and satisfied the evaluation criteria. In conclusion, CsPbI2Br shows promise as a digital relative dosimeter for brachytherapy QA.
Quantification of systematic errors in the electron density and temperature measured with Thomson scattering at W7-X
Authors: Nelde P. , Fuchert G. , Pasch E. , Beurskens M.N.A. , Bozhenkov S.A. , Brunner K.J. , Höfel U. , Kwak S. , Meineke J. , Scott E.R. , Wolf R.C. ,   and W7-X team
Published: September 2023

Abstract
The electron density and temperature profiles measured with Thomson scattering at the stellarator Wendelstein 7-X show features which seem to be unphysical, but so far could not be associated with any source of error considered in the data processing.
A detailed Bayesian analysis reveals that errors in the spectral calibration cannot explain the features observed in the profiles.
Rather, it seems that small fluctuations in the laser position are sufficient to affect the profile substantially.
The impact of these fluctuations depends on the laser position itself, which, in turn, provides a method to find the optimum laser alignment in the future.
Entropy change reversibility in MnNi1−x
Co
x
Ge0.97Al0.03 near the triple point
Authors: Samanta Tapas , Taake Chris , Bondzio Laila , Caron Luana 
Published: September 2023

Abstract
The nature of the phase transition has been studied in MnNi1−x
Co
x
Ge0.97Al0.03 (x= 0.20–0.50) through magnetization, differential scanning calorimetry and x-ray diffraction measurements; and the associated reversibility in the magnetocaloric effect has been examined. A small amount of Al substitution for Ge can lower the structural phase transition temperature, resulting in a coupled first-order magnetostructural transition (MST) from a ferromagnetic orthorhombic to a paramagnetic hexagonal phase in MnNi1−x
Co
x
Ge0.97Al0.03. Interestingly, a composition-dependent triple point (TP) has been detected in the studied system, where the first-order MST is split into an additional phase boundary at higher temperature with a second-order transition character. The critical-field-value of the field-induced MST decreases with increasing Co concentration and disappears at the TP (x= 0.37) resembling most field-sensitive MST among the studied compositions. An increase of the hexagonal lattice parameter a
hex near the TP indicates a lattice softening associated with an enhancement of the vibrational amplitude in the Ni/Co site. The lattice softening leads to a larger field-induced structural entropy change (structural entropy change≫ magnetic entropy change, for this class of materials) with the application of a lower field, which results in a larger reversibility of the low-field entropy change (|ΔS
rev| = 6.9 J kg−1 K for Δμ
0
H = 2 T) at the TP.
Computational fluid dynamics-based PDMS-graphene triboelectric nanogenerator ‘PG-TENG’ blue energy harvester
Authors: Memon Muzamil Hussain , Abro Zeeshan Ali 
Published: September 2023

Abstract
Developing cost-effective and efficient energy harvesting technologies is critical with the rising demand for clean and sustainable energy. In this research paper we presents a CFD-based study on a PDMS-Graphene Triboelectric Nanogenerator (PG-TENG) for blue energy harvesting. Our study focuses on the vertical (contact-separation) mode of the PG-TENG and investigates the effect of TENG’s varying size on its electrical output performance. To optimize the properties and performance of the PG-TENG system, we used COMSOL Multiphysics for mathematical-modeling and simulations. The outcomes show that the varying size of the PG-TENG significantly impacts its electrical output capabilities, with larger PG-TENGs exhibiting higher current and voltage outputs. Moreover, we compared our outcomes to other studies on graphene-based TENGs and highlighted the advantages of our PG-TENG in terms of durability, performance, and mechanical stability. Our research contributes to the field of blue energy generation by providing insights into the design and optimization of PG-TENGs for low-cost, effective, and efficient energy harvester devices.
Polynomial differentiation decreases the training time complexity of physics-informed neural networks and strengthens their approximation power
Authors: Suarez Cardona Juan-Esteban , Hecht Michael 
Published: September 2023

Abstract
We present novel approximates of variational losses, being applicable for the training of physics-informed neural networks (PINNs). The formulations reflect classic Sobolev space theory for partial differential equations (PDEs) and their weak formulations. The loss approximates rest on polynomial differentiation realised by an extension of classic Gauss–Legendre cubatures, we term Sobolev cubatures, and serve as a replacement of automatic differentiation. We prove the training time complexity of the resulting Sobolev -PINNs with polynomial differentiation to be less than required by PINNs relying on automatic differentiation. On top of one-to-two order of magnitude speed-up the Sobolev-PINNs are demonstrated to achieve closer solution approximations for prominent forward and inverse, linear and non-linear PDE problems compared to established PINNs.
Neighborhood-scale air quality, public health, and equity implications of multi-modal vehicle electrification
Authors: Visa Maxime A , Camilleri Sara F , Montgomery Anastasia , Schnell Jordan L , Janssen Mark , Adelman Zachariah E , Anenberg Susan C , Grubert Emily A , Horton Daniel E 
Published: September 2023

Abstract
Electric vehicles (EVs) constitute just a fraction of the current U.S. transportation fleet; however, EV market share is surging. EV adoption reduces on-road transportation greenhouse gas emissions by decoupling transportation services from petroleum, but impacts on air quality and public health depend on the nature and location of vehicle usage and electricity generation. Here, we use a regulatory-grade chemical transport model and a vehicle-to-electricity generation unit electricity assignment algorithm to characterize neighborhood-scale (∼1 km) air quality and public health benefits and tradeoffs associated with a multi-modal EV transition. We focus on a Chicago-centric regional domain wherein 30% of the on-road transportation fleet is instantaneously electrified and changes in on-road, refueling, and power plant emissions are considered. We find decreases in annual population-weighted domain mean NO2 (−11.83%) and PM2.5 (−2.46%) with concentration reductions of up to −5.1 ppb and −0.98 µg m−3 in urban cores. Conversely, annual population-weighted domain mean maximum daily 8 h average ozone (MDA8O3) concentrations increase +0.64%, with notable intra-urban changes of up to +2.3 ppb. Despite mixed pollutant concentration outcomes, we find overall positive public health outcomes, largely driven by NO2 concentration reductions that result in outsized mortality rate reductions for people of color, particularly for the Black populations within our domain.
Hexagonal lattice diagrams for complex curves in ℂℙ²
Authors: Zupan Alexander 
Published: September 2023

We demonstrate that the geometric, topological, and combinatorial complexities of certain surfaces in

C
P

2

\mathbb {CP}^2

are closely related: We prove that a positive genus surface

K

\mathcal {K}

in

C
P

2

\mathbb {CP}^2

that minimizes genus in its homology class is isotopic to a complex curve

C

d

\mathcal {C}_d

if and only if

K

\mathcal {K}

admits a hexagonal lattice diagram, a special type of shadow diagram in which arcs meet only at bridge points and tile the central surface of the standard trisection of

C
P

2

\mathbb {CP}^2

by hexagons. There are eight families of these diagrams, two of which represent surfaces in efficient bridge position. Combined with a result of Lambert-Cole relating symplectic surfaces and bridge trisections, this allows us to provide a purely combinatorial reformulation of the symplectic isotopy problem in

C
P

2

\mathbb {CP}^2

. Finally, we show that that the varieties

V

d

=
{
[

z
1

:

z
2

:

z
3

]
∈

C
P

2

:

z
1

z
2

d
−
1

+

z
2

z
3

d
−
1

+

z
3

z
1

d
−
1

=
0
}

\mathcal {V}_d = \{[z_1:z_2:z_3] \in \mathbb {CP}^2 : z_1z_2^{d-1} + z_2z_3^{d-1} + z_3z_1^{d-1} = 0\}

and

V

d
′

=
{
[

z
1

:

z
2

:

z
3

]
∈

C
P

2

:

z
1

d
−
1

z
2

+

z
2

d
−
1

z
3

+

z
3

d
−
1

z
1

=
0
}

\mathcal {V}’_d = \{[z_1:z_2:z_3] \in \mathbb {CP}^2 : z_1^{d-1}z_2 + z_2^{d-1}z_3 + z_3^{d-1}z_1 = 0\}

are in efficient bridge position with respect to the standard Stein trisection of

C
P

2

\mathbb {CP}^2

, and their shadow diagrams agree with the two families of efficient hexagonal lattice diagrams. As a corollary, we prove that two infinite families of complex hypersurfaces in

C
P

3

\mathbb {CP}^3

admit efficient Stein trisections, partially answering a question of Lambert-Cole and Meier.
Prognostic microRNA signature for estimating survival in patients with hepatocellular carcinoma
Authors: Yerukala Sathipati Srinivasulu , Aimalla Nikhila , Tsai Ming-Ju , Carter Tonia , Jeong Sohyun , Wen Zhi , Shukla Sanjay K , Sharma Rohit , Ho Shinn-Ying 
Published: September 2023

Abstract

Objective
Hepatocellular carcinoma (HCC) is one of the leading cancer types with increasing annual incidence and high mortality in the USA. MicroRNAs (miRNAs) have emerged as valuable prognostic indicators in cancer patients. To identify a miRNA signature predictive of survival in patients with HCC, we developed a machine learning-based HCC survival estimation method, HCCse, using the miRNA expression profiles of 122 patients with HCC.

Methods
The HCCse method was designed using an optimal feature selection algorithm incorporated with support vector regression.

Results
HCCse identified a robust miRNA signature consisting of 32 miRNAs and obtained a mean correlation coefficient (R) and mean absolute error (MAE) of 0.87 ± 0.02 and 0.73 years between the actual and estimated survival times of patients with HCC; and the jackknife test achieved an R and MAE of 0.73 and 0.97 years between actual and estimated survival times, respectively. The identified signature has seven prognostic miRNAs (hsa-miR-146a-3p, hsa-miR-200a-3p, hsa-miR-652-3p, hsa-miR-34a-3p, hsa-miR-132-5p, hsa-miR-1301-3p and hsa-miR-374b-3p) and four diagnostic miRNAs (hsa-miR-1301-3p, hsa-miR-17-5p, hsa-miR-34a-3p and hsa-miR-200a-3p). Notably, three of these miRNAs, hsa-miR-200a-3p, hsa-miR-1301-3p and hsa-miR-17-5p, also displayed association with tumor stage, further emphasizing their clinical relevance. Furthermore, we performed pathway enrichment analysis and found that the target genes of the identified miRNA signature were significantly enriched in the hepatitis B pathway, suggesting its potential involvement in HCC pathogenesis.

Conclusions
Our study developed HCCse, a machine learning-based method, to predict survival in HCC patients using miRNA expression profiles. We identified a robust miRNA signature of 32 miRNAs with prognostic and diagnostic value, highlighting their clinical relevance in HCC management and potential involvement in HCC pathogenesis.
The UAE’s energy system and GHG emissions: pathways to achieving national goals by 2050
Authors: Hummieda Ammar , Bouabid Ali , Moawad Karim , Mayyas Ahmad 
Published: September 2023

Abstract
In recent years, the United Arab Emirates (UAE) has developed strategies to increase renewable power generation and reduce emissions to net zero by 2050. Electricity generation and energy-intensive industries (EII) have the largest potentials for emission reduction. Therefore, an up-to-date inventory of greenhouse gas emissions and a study of the pathways to achieving the 2050 targets are essential. This study focuses on power production and EII (aluminium, steel and cement). The structure of these sectors is modelled and simulated up to 2050 using a system dynamics (SD) methodology. The SD model is validated to reflect the real-world state of the system using the emissions inventory projections as reference modes. Nineteen mitigation policies are considered in the selected sectors and four policy scenarios were simulated. The results show that implementing the Energy Strategy 2050 in the power sector can result in a reduction of 63.5% in emissions in that sector, which translates into a reduction of 33.5% overall by 2050. Additionally, implementing all identified mitigation strategies to full utilization in EII yields a 94% reduction in that sector, which translates into a 78% reduction overall. Decarbonizing the aluminium industry yields the highest emissions reductions, followed by power production, then cement and finally steel. In the best-case scenario, 22.1% of the business-as-usual emissions are still released and further decarbonization—mainly in the power sector—will be required. This is achievable given the trajectory of the UAE’s successful nuclear energy programme and the prospect of utilizing carbon capture, utilization and storage even further.