bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advanced distribution transformer asset management embracing its relocation: A cost saving approach
Authors: Azimi Hosseini Kamyar , Hajiaghapour‐Moghimi Mehran , Hajipour Ehsan , Vakilian Mehdi 
Published: March 2022

AbstractChange in customers' consumption patterns due to the introduction of new electricity consuming technologies into human consumption practices has impacted the existing optimal loading profile of the grid facilities. Although some MV/LV distribution transformers (DTs) are operating under a light load profile, this does not guarantee that they are in a healthy condition, since necessary maintenance procedures are required. On the other hand, many unplanned overloading conditions occur on the other DTs and causes accelerated failures which contributes to very high operational costs. This paper presents the outcome of a study on how the planned DTs relocation can save asset managers against their huge DTs replacement costs developed due to the highly overloaded DTs failures in a utility, and how it will improve the overall reliability of the DTs. A mixed‐integer linear programming (MILP) solution is proposed to formulate the introduced economic relocation‐based asset management (AM) framework while minimizing total cost (TC) of the network. The results show that incorporating relocation techniques into the AM formulation ends in reduction of the distribution network TC and a decrease in asset failure rates if compared with application of traditional techniques.
Week‐ahead daily peak load forecasting using genetic algorithm‐based hybrid convolutional neural network
Authors: Hong Ying‐Yi , Chan Yu‐Hsuan , Cheng Yung‐Han , Lee Yih‐Der , Jiang Jheng‐Lun , Wang Shen‐Szu 
Published: March 2022

AbstractDaily peak load forecasting is crucial for the operation of bulk power systems, including economic dispatch and unit commitment. It is also essential for peak load shaving and load management in distribution systems. In power markets, peak load forecasting helps participants develop bidding strategies. This paper proposes a new method, using a hybrid convolutional neural network (CNN) that is cascaded with a fully‐connected network, for making week‐ahead daily peak load forecasts. The proposed method uses three loops to obtain the optimal CNN: The outer loop performs crossover/mutation operations and tournament selection to produce chromosomes to optimize the network topology and hyperparameters (such as kernel size) of the hybrid CNN by genetic algorithms; the middle loop deals with the order of chromosomes; the inner loop optimizes the synaptic weights and parameters (e.g. values of a kernel) using Adam optimizer. Daily peak load data and corresponding meteorological data for Taiwan are explored. Simulation results show that the proposed method outperforms the traditional CNN, multi‐layer neural network, recurrent neural network, support vector regression and vector autoregressive moving average model.
The jump and stagnation of mass with speed
Authors: Dong Jun , Dong Na 
Published: March 2022

AbstractIn the general theory of relativity, the four‐dimensional space‐time of describing a mass body accelerated motion or in a gravitational field, although it is a curved Riemannian geometric space from the perspective of “integral geometry”, but for any instantaneous position of the moving mass body, there is a local Flat Space of Riemannian geometric space. The local Flat Space is a Mincowski space in which the inertial coordinate system can be used in the local small area. Between the proper coordinate systems of two interacting moving masses, or between a series of following proper coordinate systems experienced by a mass body moving in any way, there should be a coordinate transformation relationship similar to the traditional special theory of relativity. However, they have an important difference: in these instantaneous local inertial systems, the speed of light is no longer the constant c of vacuum, the effect of gravitational field or acceleration on the speed of light is the same as that of a medium with a dielectric constant of ε and a magnetic permeability of μ. Using the special theory of relativity with variable speed of light that the author has established can discuss relevant relativity physics issues in these instantaneous local inertial systems. This article uses the special theory of relativity with variable speed of light to derive the functional relationship between a moving mass and the change of speed. In addition to obtain the traditional continuous increasing function relationship, a step function relationship with stepped discontinuous changes is also obtained. At the same speed, the mass can have two values, such as a ladder upgrade one level; the same mass can be matched with two different speeds, such as one step extension forward on the same step stair. From the perspective of the increase in speed, the mass is stagnant on the step platform (the speed increases, the mass does not change), and it jumps in the step up ladder (the speed does not change, the mass has a jump change). This obviously incorporates the main image of quantum theory into the theory of relativity, which is the result that all physics researchers care about and expect.
Accurate, affordable, and generalizable machine learning simulations of transition metal x-ray absorption spectra using the XANESNET deep neural network
Authors: Rankine C. D. , Penfold T. J. 
Published: March 2022

The affordable, accurate, and generalizable prediction of spectroscopic observables plays a key role in the analysis of increasingly complex experiments. In this article, we develop and deploy a deep neural network—XANESNET—for predicting the lineshape of first-row transition metal K-edge x-ray absorption near-edge structure (XANES) spectra. XANESNET predicts the spectral intensities using only information about the local coordination geometry of the transition metal complexes encoded in a feature vector of weighted atom-centered symmetry functions. We address in detail the calibration of the feature vector for the particularities of the problem at hand, and we explore the individual feature importance to reveal the physical insight that XANESNET obtains at the Fe K-edge. XANESNET relies on only a few judiciously selected features—radial information on the first and second coordination shells suffices along with angular information sufficient to separate satisfactorily key coordination geometries. The feature importance is found to reflect the XANES spectral window under consideration and is consistent with the expected underlying physics. We subsequently apply XANESNET at nine first-row transition metal (Ti–Zn) K-edges. It can be optimized in as little as a minute, predicts instantaneously, and provides K-edge XANES spectra with an average accuracy of ∼±2%–4% in which the positions of prominent peaks are matched with a &gt;90% hit rate to sub-eV (∼0.8 eV) error.
Spectroscopic characterization of singlet–triplet doorway states of aluminum monofluoride
Authors: Walter N. , Seifert J. , Truppe S. , Schewe H. C. , Sartakov B. G. , Meijer G. 
Published: March 2022

Aluminum monofluoride (AlF) possesses highly favorable properties for laser cooling, both via the A1Π and a3Π states. Determining efficient pathways between the singlet and the triplet manifold of electronic states will be advantageous for future experiments at ultralow temperatures. The lowest rotational levels of the A1Π, v = 6 and b3Σ+, v = 5 states of AlF are nearly iso-energetic and interact via spin–orbit coupling. These levels thus have a strongly mixed spin-character and provide a singlet–triplet doorway. We here present a hyperfine resolved spectroscopic study of the A1Π, v = 6//b3Σ+, v = 5 perturbed system in a jet-cooled, pulsed molecular beam. From a fit to the observed energies of the hyperfine levels, the fine and hyperfine structure parameters of the coupled states and their relative energies as well as the spin–orbit interaction parameter are determined. The standard deviation of the fit is about 15 MHz. We experimentally determine the radiative lifetimes of selected hyperfine levels by time-delayed ionization, Lamb dip spectroscopy, and accurate measurements of the transition lineshapes. The measured lifetimes range between 2 and 200 ns, determined by the degree of singlet–triplet mixing for each level.
State-selective exciton–plasmon interplay in a hybrid WSe2/CuFeS2 nanosystem
Authors: Cheng Zhiqiang , Niu Xiaoyou , Jiang Shenlong , Zhang Qun 
Published: March 2022

The integration of confined exciton and localized surface plasmon in a hybrid nanostructure has recently stimulated extensive interests. The mechanistic insights into the elusive exciton–plasmon interplay at the nanoscale are of both fundamental and applicable values. Herein, by taking a hybrid WSe2/CuFeS2 system as a prototype, in which the excitonic semiconductor WSe2 nanosheets are interfaced with the plasmonic semiconductor CuFeS2 nanocrystals to form a heterostructure, we design and perform an ultrafast dynamics study to glean information in this regard. Specifically, the band-alignment relationship between the two components enables the contrasting case studies in which the excitonic excited states of WSe2 are pre-selected to be on-/off-resonant with the plasmon band of CuFeS2. As revealed by the joint observations from steady-state absorption and photoexcitation-dependent/temperature-dependent femtosecond time-resolved transient absorption (fs-TA) spectroscopy, an effective energy transfer process occurs in this exciton–plasmon system where the energy donor (acceptor) is the excitonic WSe2 (plasmonic CuFeS2) and its efficiency is modulated by the exciton–plasmon coupling strength. Furthermore, as inferred from the temperature-dependent fs-TA analysis, the opening of such an energy-transfer channel turns out to take place during the early phase of plasmon decay (∼1 ps). In addition, the activation energy of energy transfer for a specific exciton-state-selected case is estimated (∼200 meV). This work provides a dynamics perspective to the plasmon semiconductor-involved exciton–plasmon interplay that features excited-state selectivity of exciton band and, hence, would be of guiding value for rational design and optimization of relevant applications based on exciton–plasmon manipulation.
Magnetostriction in microwave synthesized La0.5Ba0.5CoO3
Authors: Manikandan M. , Ghosh A. , Mahendiran R. 
Published: March 2022

A single phase polycrystalline La0.5Ba0.5CoO3-d sample possessing cubic structure (space group Pm3̄m) was synthesized by microwave irradiation within 20 minutes of processing time and its structural, magnetic, electrical, and magnetostrictive properties were investigated. While the temperature dependence of field-cooled magnetization (M) in a field of H = 0.5 kOe indicates the onset of ferromagnetic transition at TC = 177 K, irreversibility between the zero field-cooled and field cooled M(T) persists even at H = 3 kOe. M(H) at 10 K does not saturate at the maximum available field and has a much smaller value (0.83 μB/Co in a field of 50 kOe) than 1.9 μB/Co expected for spin only contribution from intermediate Co3+ and Co4+ spins. Resistivity shows insulating behavior down to 10 K and only a small magnetoresistance (∼ -2% for H = 70 kOe) occurs around TC. All these results suggest a magnetically heterogeneous ground state with weakly interacting ferromagnetic clusters coexisting with a non-ferromagnetic phase. The length of the sample expands in the direction of the applied magnetic field (positive magnetostriction) and does not show saturation even at 50 kOe. The magnetostriction has a maximum value (λpar = 265 x 10-6) at 10 K and it decreases with increasing temperature. The smaller value of λpar compared to the available data on La0.5Sr0.5CoO3 (λpar = 900 x 10-6) suggests that the non-ferromagnetic matrix is most likely antiferromagnetic and it restrains the field-induced expansion of ferromagnetic clusters in the microwave synthesized La0.5Ba0.5CoO3-d sample.
Dualisms in Jihad
Authors: Patterson Katie J. 
Published: March 2022

Abstract
This paper explores how metaphors are employed in jihadist magazines to promote a dichotomist worldview of ‘us’
versus ‘them’, ‘good’ versus ‘bad’, ‘east’ versus ‘west’ and ‘right’ versus ‘wrong’. It argues that juxtapositions in both
language and thought help writers to reaffirm and/or challenge certain paradigms. The approach uses critical metaphor analysis
(Charteris-Black 2004) to investigate qualitative evidence of conceptual metaphors,
focusing on the domains life is a seed, conflict is a relationship between predator and prey, and faith is light/lack
of faith is darkness. Dichotomous language in these domains (e.g., ‘seed’ versus ‘weed’; ‘sheep’ versus ‘wolves’; the
‘spark of Jihad’ versus the ‘shadow’ of Western governments) helps to position extremist groups on the right side of a number of
paradigms. The use of binary metaphors also permits simultaneously conflicting conceptualisations; for instance, jihadists are
both innocent victims and merciless defenders of their faith, depending on with whom or what they are juxtaposed. The research
concludes that the use of binary metaphors serves to underscore entrenched paradigms of ‘good’ versus ‘bad’, thus allowing the
writers to frame their discourse in a way that justifies and promotes their extremist agenda.
Electron drag force in EUV induced pulsed hydrogen plasmas
Authors: Chaudhuri M , Yakunin A , van de Kerkhof M , Snijdewind R 
Published: March 2022

Abstract
Extreme ultraviolet (EUV) induced pulsed plasma is unique due to its transient characteristics: the plasma switches between non-thermal state (when EUV power is ON at the beginning of the pulse) and thermal state (end of the pulse at ∼20 μs). It is shown that although electron drag force acting on nm size particles in hydrogen plasma is negligible compared to the ion drag force at the beginning of the pulse, however it can be dominant at the end of the pulse and can play important role in particle transport leading to defectivity issues for semiconductor chip production technologies.
Improved training in paraffin-wax impregnated Nb3Sn Rutherford cables demonstrated in BOX samples
Authors: Daly Michael , Auchmann Bernhard , Brem André , Hug Christoph , Sidorov Serguei , Otten Simon , Dhallé Marc , Guo Zichuan , Kario Anna , Ten Kate Herman 
Published: March 2022

Abstract
Resin-impregnated high-field Nb3Sn type of accelerator magnets are known to require extensive training campaigns and even may exhibit performance-limiting defects after thermal or electromagnetic cycling. In order to efficiently explore technological solutions for this behaviour and assess a wide variety of impregnation material combinations and surface treatments, the BOnding eXperiment (BOX) sample was developed. BOX provides a short-sample test platform featuring magnet-relevant Lorentz forces and exhibits associated training. Here we report on the comparative behaviour of BOX samples comprising the same Nb3Sn Rutherford cable but impregnated either with common resins used in high-field magnets, or with less conventional paraffin wax. Remarkably, the two paraffin wax-impregnated BOX samples reached their critical current without training and are also resilient to thermal and mechanical cycling. These rather encouraging results strongly contrast to those obtained with resin impregnated samples, which show the characteristic extensive training and at best barely reach their critical current value.
Low-cost Access to the Deep, High-cadence Sky: the Argus Optical Array
Authors: Law Nicholas M. , Corbett Hank , Galliher Nathan W. , Gonzalez Ramses , Vasquez Alan , Walters Glenn , Machia Lawrence , Ratzloff Jeff , Ackley Kendall , Bizon Chris , Clemens Christopher , Cox Steven , Eikenberry Steven , Howard Ward S. , Glazier Amy , Mann Andrew W. , Quimby Robert , Reichart Daniel , Trilling David 
Published: March 2022

Abstract
New mass-produced, wide-field, small-aperture telescopes have the potential to revolutionize ground-based astronomy by greatly reducing the cost of collecting area. In this paper, we introduce a new class of large telescope based on these advances: an all-sky, arcsecond-resolution, 1000 telescope array which builds a simultaneously high-cadence and deep survey by observing the entire sky all night. As a concrete example, we describe the Argus Array, a 5 m-class telescope with an all-sky field of view and the ability to reach extremely high cadences using low-noise CMOS detectors. Each 55 GPix Argus exposure covers 20% of the entire sky to m

g
= 19.6 each minute and m

g
= 21.9 each hour; a high-speed mode will allow sub-second survey cadences for short times. Deep coadds will reach m

g
= 23.6 every five nights over 47% of the sky; a larger-aperture array telescope, with an étendue close to the Rubin Observatory, could reach m

g
= 24.3 in five nights. These arrays can build two-color, million-epoch movies of the sky, enabling sensitive and rapid searches for high-speed transients, fast-radio-burst counterparts, gravitational-wave counterparts, exoplanet microlensing events, occultations by distant solar system bodies, and myriad other phenomena. An array of O(1000) telescopes, however, would be one of the most complex astronomical instruments yet built. Standard arrays with hundreds of tracking mounts entail thousands of moving parts and exposed optics, and maintenance costs would rapidly outpace the mass-produced-hardware cost savings compared to a monolithic large telescope. We discuss how to greatly reduce operations costs by placing all optics in thermally controlled, sealed domes with only a few moving parts. Coupled with careful software scope control and use of existing pipelines, we show that the Argus Array could become the deepest and fastest Northern sky survey, with total costs in the $20M range.
Astrometric Calibration for All-sky Camera with Machine Learning
Authors: Tian J. F. , Ge L. , Wu Y. , Zhou Z. Z. 
Published: March 2022

Abstract
The night images obtained with an all-sky camera can provide spatial and time sampling, which can be used for measurement cloud coverage measurement and meteor monitoring. The astrometric calibration of an all-sky camera is necessary because of strong field distortions. We use machine learning to complete the calibration of an all-sky camera. In order to prepare the data sets needed for machine learning, a particle swarm optimization algorithm is used to determine the parameters of the method proposed by Borovicka in 1995. Machine learning can transform plate coordinates to celestial coordinates and transform celestial coordinates to plate coordinates. The actual test shows that the standard deviation of residuals is of the order of 1′ for the transformation from plate coordinates to celestial coordinates and the standard deviation of residuals is of the order of 0.3 px for the transformation from celestial coordinates to the plate coordinates.
Fluctuation assisted collapses of Bose–Einstein condensates
Authors: Pan Junqiao , Wang Yuqi , Shi Tao , Yi Su 
Published: March 2022

Abstract
We study the collapse dynamics of a Bose–Einstein condensate subjected to a sudden change of the scattering length to a negative value by adopting the self-consistent Gaussian state theory for mixed states. Compared to the Gross–Pitaevskii and the Hartree–Fock–Bogoliubov approaches, both fluctuations and three-body loss are properly treated in our theory. We find a new type of collapse assisted by fluctuations that amplify the attractive interaction between atoms. Moreover, the calculation of the fluctuated atoms, the entropy, and the second-order correlation function showed that the collapsed gas significantly deviated from a pure state.
Graphene quantum dot based ultrasensitive probe for biosensing of prostate cancer biomarkers: current updates and future challenges
Authors: Pantwalawalkar Jidnyasa , Chandankar Sachin , Tade Rahul , Khan Zamir , Shaikh Matin , Powar Trupti , Patil Prashant , Sugandhi Vrushabh , Nangare Sopan 
Published: March 2022

Abstract
Prostate cancer (PC) is significantly increasing as a principal cause of mortality among the men’s population. Accordingly, research scholars have made tremendous development for the effective treatment of PC. Despite this, the early diagnosis of PC is a challenging task for scientific fraternities due to the plenty of demerits of currently engaged methods in terms of sensitivity, selectivity, and many more. For that reason, PC management needs exceptional alternative strategies for proficient management of PC that can endow with early diagnosis of PC and eventually it will result in promising cure of PC. Strategies involved in advanced nanomaterials especially carbon nanomaterials have gained tremendous consideration due to their numerous benefits. Notably, graphene quantum dots (GQDs) are a promising next-generation carbon nanomaterial with manifold biomedical applications such as biosensing and drug delivery in cancer and different life-threatening health issues that may be due to the versatile and tunable properties of GQDs. In a nutshell, it provides high sensitivity and selectivity towards the target biomarker of PC. In this review, the prevalence and distribution of PC, major highlights and limitations of current diagnostics and treatments, as well as recent trends for PC management have been discussed in brief. Afterward, the synthesis methods, properties, biocompatibility, and bioconjugation of GQDs along with their impact on the performance of biosensors have been summarised in brief. Finally, the application of GQD based biosensors exhibited the lowest detection limit up to femtogram in simulated and real-time samples. As a result, the applications of GQDs as novel biosensors presents plentiful advantages including high sensitivity, high selectivity, high stability, rapid response, etc of the PC biomarkers. Therefore, this review will provide the details of recent updates to prepare and extend advanced biosensing prospects using GQDs as excellent nanomaterial probes in PC and other cancer types.
Royal jelly fatty acids downregulate ANGPTL8 expression through the decrease in HNF4α protein in human hepatoma HepG2 cells
Authors: Inoue Yuki , Ienaga Marina , Kamiya Tetsuro , Adachi Tetsuo , Ohta Mitsuhiro , Hara Hirokazu 
Published: March 2022

ABSTRACT
Royal jelly (RJ) intake has been reported to be effective for reducing serum lipids; however, the mechanism is not fully understood. Angiopoietin-like protein 8 (ANGPTL8), a secreted protein, plays a key role in lipid metabolism. In this study, we investigated the effects of specific fatty acids included in RJ (RJ fatty acids), such as 10-hydroxy-2-decenoic acid, 10-hydroxydecanoic acid, and sebacic acid (SA), on expression of ANGPTL8 in human hepatoma HepG2 cells. SA markedly reduced the expression of ANGPTL8. Reporter assay revealed that SA suppressed ANGPTL8 promoter activity. In addition, we identified a functional binding site of hepatocyte nuclear factor-4α (HNF4α), a liver-enriched transcription factor, in the ANGPTL8 promoter. SA reduced the levels of HNF4α protein and the binding of HNF4α to the ANGPTL8 promoter. Moreover, siRNA knockdown of HNF4α suppressed the expression of ANGTPL8 mRNA. Taken together, we conclude that SA downregulates ANGPTL8 expression via the decrease in HNF4α protein.