bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hypersensitivity to ferroptosis in chromophobe RCC is mediated by a glutathione metabolic dependency and cystine import via solute carrier family 7 member 11
Authors: Zhang Long , Hobeika Charbel S. , Khabibullin Damir , Yu Deyang , Filippakis Harilaos , Alchoueiry Michel , Tang Yan , Lam Hilaire C. , Tsvetkov Peter , Georgiou George , Lamb Candice , Stone Everett , Puigserver Pere , Priolo Carmen , Henske Elizabeth P. 
Published: July 2022

Chromophobe (Ch) renal cell carcinoma (RCC) arises from the intercalated cell in the distal nephron. There are no proven treatments for metastatic ChRCC. A distinguishing characteristic of ChRCC is strikingly high levels of reduced (GSH) and oxidized (GSSG) glutathione. Here, we demonstrate that ChRCC-derived cells exhibit higher sensitivity to ferroptotic inducers compared with clear-cell RCC. ChRCC-derived cells are critically dependent on cystine via the cystine/glutamate antiporter xCT to maintain high levels of glutathione, making them sensitive to inhibitors of cystine uptake and cyst(e)inase. Gamma-glutamyl transferase 1 (GGT1), a key enzyme in glutathione homeostasis, is markedly suppressed in ChRCC relative to normal kidney. Importantly, GGT1 overexpression inhibits the proliferation of ChRCC cells in vitro and in vivo, suppresses cystine uptake, and decreases levels of GSH and GSSG. Collectively, these data identify ferroptosis as a metabolic vulnerability in ChRCC, providing a potential avenue for targeted therapy for these distinctive tumors.
Laser welding of FeCoCrNiMnAlx (x = 0, 0.75) high-entropy alloys fabricated by additive manufacturing
Authors: Shan Mengdie , Wang Songyu , Cai Yangchuan , Gao Feifeng , Manladan Sunusi Marwana , Zhu Lisong , Sun Da , Han Jian 
Published: July 2022

In the present study, the laser melting deposition (LMD) technology was adopted to fabricate FeCoCrNiMn and FeCoCrNiMnAl0.75 high entropy alloys (HEAs). Then, laser welding method was used to join the HEAs in forms of similar (FeCoCrNiMnAl/FeCoCrNiMnAl and FeCoCrNiMnAl0.75/FeCoCrNiMnAl0.75) and dissimilar (FeCoCrNiMnAl0/FeCoCrNiMnAl0.75) combinations, respectively. Ultra-depth field microscope and electron backscatter diffraction detection were used to observe the macro-morphology and microstructure, respectively. It was found that the width of the weld bead and heat-affected zone with higher aluminium content was larger. In both base metals and welded joints, aluminium promoted the face-centered cubic (FCC) phase transfer into body-centered cubic (BCC), significantly refined the grain and the dislocation density of HEA is also increased, which increased strength and hardness, and decreased ductility. Highlights The FeCoCrNiMn/FeCoCrNiMn, FeCoCrNiMn/FeCoCrNiMnAl0.75, FeCoCrNiMnAl0.75/FeCoCrNiMnAl0.75 joints were produced by laser welding. The widths of the weld bead and heat-affected zone increased with higher Al content. The weld bead with higher content of Al exhibited higher strength and hardness, but lower ductility.
Development of a microkinetic model for non-oxidative coupling of methane over a Cu catalyst in a non-thermal plasma reactor
Authors: Pourali Nima , Vasilev Maksim , Abiev Rufat , Rebrov Evgeny V 
Published: July 2022

Abstract
A surface microkinetic plasma model for non-oxidative coupling of methane into H2 and higher hydrocarbons was developed over a Cu catalytic film. Twenty key plasma species including electron, ions, radicals, and neutrals were considered in respective chemical reactions leading to the formation of C2 hydrocarbons onto the catalyst surface. The kinetic model was coupled with a global plasma model to describe the performance of a non-thermal plasma reactor. In the reactor model, the reactant gas flows between the two coaxial cylindrical metal electrodes with a length of 50 mm and a diameter of 2 mm (inner) and 6 mm (outer electrode) coated with a Cu film. The effect of discharge power, initial CH4 concentration, and inlet flow rate on methane conversion was investigated. The surface model shows that the CH4 conversion of 47% is obtained at a discharge power of 70 W with a selectivity of C2H2 (49%). Increase in power increased the conversion of methane while increase in pressure and/or inlet gas flow rate decreased it. Also, the results of the plasma-catalyst model were compared with those of plasma alone (without catalyst). It showed that presence of the catalyst inside the plasma increases the selectivity and yield of acetylene, while it deceases the selectivity and yield of hydrogen. Also, the density of radical CH3 in the plasma phase increased in the presence of catalyst, while CH2 and CH densities decreased with that.
Coal-based ultrathin N-doped carbon nanosheets synthesized by molten-salt method for high-performance lithium-ion batteries
Authors: Gao Shasha , Liu Lang , Mao Feifei , Zhang Zhang , Pan Kecheng , Zhou Zhen 
Published: July 2022

Abstract
Coal is a typical fossil fuel and it is also a natural carbon material, therefore, converting it to functional carbon materials is an effective way to enhance the economic advantages of coal. Here, ultrathin N-doped carbon nanosheets were prepared from low-cost coal via a handy and green molten-salt method, which shown excellent performance for lithium-ion batteries (LIBs). The formation mechanism of ultrathin nanosheets was studied in detail. The eutectic molten salts possess low melting points and become a strong polar solvent at the calcined temperature, making the acidified coal miscible with them in very homogeneously state. Therefore, they can play a gigantic role in in situ pore-forming during the carbonization and induce the formation of ultrathin nanosheets due to the salt ions. Simultaneously, the ultrathin N-doped carbon nanosheets with rich defects and controllable surface area was smoothly prepared without any more complex process while revealing brilliant electrochemical performance due to rich ion diffusion pathways. It delivers reversible capacity of 727.0 mAh g−1 at 0.2 A g−1 after 150 cycles. Thus, the molten-salt method broadens the avenue to construct porous carbon materials with tailor-made morphologies. Equally important, this approach provides a step toward the sustainable materials design and chemical science in the future.
Mitigating the uncertainty in small field dosimetry by leveraging machine learning strategies
Authors: Zhao Wei , Yang Yong , Xing Lei , Chuang Cynthia F , Schüler Emil 
Published: July 2022

Abstract
Small field dosimetry is significantly different from the dosimetry of broad beams due to loss of electron side scatter equilibrium, source occlusion, and effects related to the choice of detector. However, use of small fields is increasing with the increase in indications for intensity-modulated radiation therapy and stereotactic body radiation therapy, and thus the need for accurate dosimetry is ever more important. Here we propose to leverage machine learning (ML) strategies to reduce the uncertainties and increase the accuracy in determining small field output factors (OFs). Linac OFs from a Varian TrueBeam STx were calculated either by the treatment planning system (TPS) or measured with a W1 scintillator detector at various multi-leaf collimator (MLC) positions, jaw positions, and with and without contribution from leaf-end transmission. The fields were defined by the MLCs with the jaws at various positions. Field sizes between 5 and 100 mm were evaluated. Separate ML regression models were generated based on the TPS calculated or the measured datasets. Accurate predictions of small field OFs at different field sizes (FSs) were achieved independent of jaw and MLC position. A mean and maximum % relative error of 0.38 ± 0.39% and 3.62%, respectively, for the best-performing models based on the measured datasets were found. The prediction accuracy was independent of contribution from leaf-end transmission. Several ML models for predicting small field OFs were generated, validated, and tested. Incorporating these models into the dose calculation workflow could greatly increase the accuracy and robustness of dose calculations for any radiotherapy delivery technique that relies heavily on small fields.
Active-PET: a multifunctional PET scanner with dynamic gantry size featuring high-resolution and high-sensitivity imaging: a Monte Carlo simulation study
Authors: Sanaat Amirhossein , Jamalizadeh Mahdi , Khanmohammadi Hadi , Arabi Hossein , Zaidi Habib 
Published: July 2022

Abstract
Organ-specific PET scanners have been developed to provide both high spatial resolution and sensitivity, although the deployment of several dedicated PET scanners at the same center is costly and space-consuming. Active-PET is a multifunctional PET scanner design exploiting the advantages of two different types of detector modules and mechanical arms mechanisms enabling repositioning of the detectors to allow the implementation of different geometries/configurations. Active-PET can be used for different applications, including brain, axilla, breast, prostate, whole-body, preclinical and pediatrics imaging, cell tracking, and image guidance for therapy. Monte Carlo techniques were used to simulate a PET scanner with two sets of high resolution and high sensitivity pixelated Lutetium Oxyorthoscilicate (LSO(Ce)) detector blocks (24 for each group, overall 48 detector modules for each ring), one with large pixel size (4 × 4 mm2) and crystal thickness (20 mm), and another one with small pixel size (2 × 2 mm2) and thickness (10 mm). Each row of detector modules is connected to a linear motor that can displace the detectors forward and backward along the radial axis to achieve variable gantry diameter in order to image the target subject at the optimal/desired resolution and/or sensitivity. At the center of the field-of-view, the highest sensitivity (15.98 kcps MBq−1) was achieved by the scanner with a small gantry and high-sensitivity detectors while the best spatial resolution was obtained by the scanner with a small gantry and high-resolution detectors (2.2 mm, 2.3 mm, 2.5 mm FWHM for tangential, radial, and axial, respectively). The configuration with large-bore (combination of high-resolution and high-sensitivity detectors) achieved better performance and provided higher image quality compared to the Biograph mCT as reflected by the 3D Hoffman brain phantom simulation study. We introduced the concept of a non-static PET scanner capable of switching between large and small field-of-view as well as high-resolution and high-sensitivity imaging.
Learning entanglement breakdown as a phase transition by confusion
Authors: Gavreev M A , Mastiukova A S , Kiktenko E O , Fedorov A K 
Published: July 2022

Abstract
Quantum technologies require methods for preparing and manipulating entangled multiparticle states. However, the problem of determining whether a given quantum state is entangled or separable is known to be an NP-hard problem in general, and even the task of detecting entanglement breakdown for a given class of quantum states is difficult. In this work, we develop an approach for revealing entanglement breakdown using a machine learning technique, which is known as ‘learning by confusion’. We consider a family of quantum states, which is parameterized such that there is a single critical value dividing states within this family into separate and entangled. We demonstrate the ‘learning by confusion’ scheme allows us to determine the critical value. Specifically, we study the performance of the method for the two-qubit, two-qutrit, and two-ququart entangled state. In addition, we investigate the properties of the local depolarization and the generalized amplitude damping channel in the framework of the confusion scheme. Within our approach and setting the parameterization of special trajectories, we obtain an entanglement-breakdown ‘phase diagram’ of a quantum channel, which indicates regions of entangled (separable) states and the entanglement-breakdown region. Then we extend the way of using the ‘learning by confusion’ scheme for recognizing whether an arbitrary given state is entangled or separable. We show that the developed method provides correct answers for a variety of states, including entangled states with positive partial transpose. We also present a more practical version of the method, which is suitable for studying entanglement breakdown in noisy intermediate-scale quantum devices. We demonstrate its performance using an available cloud-based IBM quantum processor.
Hybrid no-signaling-quantum correlations
Authors: Banacki Michał , Mironowicz Piotr , Ramanathan Ravishankar , Horodecki Paweł 
Published: July 2022

Abstract
Fundamental investigations in non-locality have shown that while the no-signaling principle alone is not sufficient to single out the set of quantum non-local correlations, local quantum mechanics and no-signaling together exactly reproduce the set of quantum correlations in the two-party Bell scenario. Here, we introduce and study an intermediate hybrid no-signaling quantum set of non-local correlations that we term HNSQ in the multi-party Bell scenario where some subsystems are locally quantum while the remaining subsystems are only constrained by the no-signaling principle. Specifically, the set HNSQ is a super-quantum set of correlations derived from no-signaling assemblages by performing quantum measurements on the trusted subsystems. We show that in contrast to the set NS of no-signaling behaviors, there exist extreme points of HNSQ in the tripartite Bell scenario that admit quantum realization. As a tool for optimization over the set HNSQ, we introduce an outer hierarchy of semi-definite programming approximations to the set following an approach put forward by Doherty–Parrilo–Spedalieri. We perform an extensive numerical analysis of the maximal violation of the facet Bell inequalities in the three-party binary input–output scenario and study the corresponding self-testing properties. In contrast to the usual no-signaling correlations, the new set allows for simple security proofs of (one-sided)-device-independent applications against super-quantum adversaries.
Melting of spin ice state and development of fifth order susceptibility with magnetic field in pyrochlore Tb2Sn2O7
Authors: Singh Karan , Ranaut Dheeraj , Sharma G , Mukherjee K 
Published: July 2022

Abstract
Pyrochlores offer an ideal playground to investigate the magnetic ground state of frustrated magnetic systems. In this class of materials, competition between various magnetic interactions remains frustrated and prevents an ordered magnetic state at low temperatures. Tb2Sn2O7 has recently attracted significant attention due to its ordered spin-ice state. Additionally, in such systems, application of external magnetic field might result in exotic magnetic states. Our current investigation on Tb2Sn2O7 reveal the presence of a new phase associated with fifth order susceptibility at low temperatures and high magnetic fields. In this compound, at zero fields, for a stabilized spin-ice state, the singlet–singlet state separated by δ play an imperative role. Under magnetic fields, δ increases and the Zeeman energy associated with the magnetic anisotropy is believed to get enhanced; which can be the key ingredient for evolution of higher-order moments, above 10 kOe, in this compound.
Thermoelectric properties of 2D semiconducting Pt2CO2
Authors: Wei Xiao-Ping , Shen Jing , Du Lan-Lan , Chang Wen-Li , Tao Xiao-Ma 
Published: July 2022

Abstract
Quantum confinement effect in 2D materials leads to the reduction of the degree of freedom of space and the weakening of the correlation between the thermoelectric factors. Only by adjusting a certain physical quantity can optimized the thermoelectric performance. MXenes as a new class of 2D material have attracted widely attention due to their good mechanical and chemical stability, controllable layer thickness, easily functionalized surface and excellent electrical conductivity. In the present paper, using first-principles calculations, we design and study the stability, electronic and thermoelectric properties of 2D monolayer Pt2CO2. Results show that the Pt2CO2 is a new non-magnetic semiconductor, and can bear its own weight, and maintain its free-standing planar structure without substrate support. Futher, the stable calculations indicate that the Pt2CO2 meets thermodynamic, mechanical and dynamic stabilities. Finally, using the Boltzmann transport theory combined with Slack model, we calculate the Seebeck coefficient S, electrical conductivity σ/τ, and the thermal conductivity κ, and then obtain the ZT value from 300 K to 1000 K. It is found that the largest ZT value closes to 1.05 at 1000 K, implying the Pt2CO2 potential application as thermoelectric material.
Optimal design for vibration energy harvesters based on quasi-periodic structures
Authors: Dowlati Shakiba , Kacem Najib , Bouhaddi Noureddine 
Published: July 2022

Abstract
In this paper, the design of large-scale quasi-periodic Vibration Energy Harvesters (VEH) is optimized to enhance the harvested power of an electromagnetic mode localized structure. This work aims to optimize the output power by employing the energy localization phenomenon in a large-scale periodic configuration by introducing the minimum number of perturbations. The harvested power, number and location of perturbations are among the objectives that need to be optimized. A genetic-based mixed-integer optimization algorithm is used to meet the objective functions within a constraint on the system kinetic energy. Numerical simulations for quasi-periodic systems with 20 and 100 Degrees of Freedom (DOF) are performed. It is shown that the ratio of harvested power increases as the number of perturbations rises and it exceeds 80% of the total output power by perturbing almost one-third of the total DOFs. The proposed methodology is a decision-making aid to provide an optimal design in a generalized quasi-periodic VEH in order to reduce the number of harvesting transducers while providing a significantly high amount of harvested power.
PV-reduction of sunset topology with auxiliary vector
Authors: Feng Bo , Li Tingfei 
Published: July 2022

Abstract
The Passarino–Veltman (PV) reduction method has proven to be very useful for the computation of general one-loop integrals. However, not much progress has been made when it is applied to higher loops. Recently, we have improved the PV-reduction method by introducing an auxiliary vector. In this paper, we apply our new method to the simplest two-loop integrals, i.e., the sunset topology. We show how to use differential operators to establish algebraic recursion relations for reduction coefficients. Our algorithm can be easily applied to the reduction of integrals with arbitrary high-rank tensor structures. We demonstrate the efficiency of our algorithm by computing the reduction with the total tensor rank up to four.
Effect of FeNb on microstructure and mechanical properties of Al-Cu-Ni alloy
Authors: Pulisheru Kumara Swamy , Birru Anil Kumar , Dixit Uday Shanker 
Published: July 2022

Abstract
The present research work deals with the investigation of mechanical properties and microstructure evaluation by particulate reinforcement of ferroniobium (FeNb) into Al-5Cu-2Ni alloy. The two-step stir casting method was employed for the fabrication of the material. The metallography study was carried out with optical microscopy (OM), scanning electron microscopy (SEM) with energy-dispersive x-ray spectroscopy (EDS), and x-ray diffraction (XRD). The XRD peaks revealed the presence of the Fe2Nb phase and intermetallic compound phases of Al2Cu and Al3Ni2. However, the Fe2Nb phase is in the form of short sticks uniformly distributed around the intermetallic compound phases. Tensile strength, microhardness and impact strength were evaluated according to ASTM standards. The average tensile strength and Vickers microhardness of the Al-5Cu-2Ni matrix alloy were 179 MPa and 115 HV respectively. By adding 1%, 3% and 5% of FeNb particulate reinforcement into Al-5Cu-2Ni alloy, the tensile strength could be enhanced to 185, 193 and 207 MPa respectively. The corresponding microhardness values were 130, 132 and 151 HV, respectively. Thus, the addition of 5% ferroniobium particulate reinforcement material could significantly enhance the tensile strength and microhardness of the composites. Fractography revealed that fracture mode changes from ductile to brittle with the reinforcement of FeNb particles. The FeNb particles resist the dislocation movement of the intermetallic compound phases in the composites leading to micro-cracks and subsequent brittle fracture.
Effects of Nb microalloying on properties of Zr-Al-Fe-Cu glassy alloy
Authors: Yu De-chuan , Zheng Chong-wei , Qin Qiong , Li Chun-xin , Li Xue-hong , Di Wu  , Qi Yang , Zhang Hai-feng , Wang Yong , Yu Yue 
Published: July 2022

Abstract
The effects of Nb-microalloying on glass forming ability, thermal properties and mechanical properties of (Zr0.6032Cu0.2256Fe0.0995Al0.0717)100-xNbx (x = 0, 1, 2, 3, 4) alloys were investigated. The best glass former was obtained for (Zr0.6032Cu0.2256Fe0.0995Al0.0717)97Nb3, which could be fabricated into full glass with diameter up to 6 mm at least. In addition, the origin of enhancing GFA of ZrAlFeCu amorphous alloy by means of the minor addition of Nb, Gd and Hf, was also discussed from the aspects of clusters and mixing entropy, which might provide a method of understanding the mechanism of enhancing glass-forming ability via microalloying, and choosing minor alloying element with an aim of enhancing glass-forming ability. It was found that the thermal stability reduced as the content of Nb increased along with the supercooled liquid region decreased. Nb-microalloying decease the fracture strength. However, moderate Nb microalloying could enhance the room temperature plastic strain.
Strip detector array (SDA) for beam monitoring in radiotherapy: reconstruction of MLC parameters from multiple projections of flux
Authors: Hoegele W , Zygmanski P 
Published: July 2022

Abstract

Objective. In this paper we propose and investigate a new detector with multiple strip detector arrays (SDA) for monitoring MLC shaped x-ray beams for radiotherapy treatment. Approach. Each SDA measures 1D dose profiles equivalent to dose projections. The goal of such a detector is to determine individual MLC leaf positions as well as the Monitor Units (MU) per MLC segment during radiotherapy. In the present work we investigate an optimal SDA detector configuration and reconstruction algorithm. We determine the accuracy of SDA for different treatment sites (spine, pelvis, retroperitoneum, prostate, brain SRT, SRS, lung and head and neck). We perform a simulation study accounting for different type of MLC leaf positional errors: random MLC leaf, systematic for the whole leaf bank and systematic for an individual leaf. In a similar fashion, we also account for errors in Monitor Units per segment. Main results. We demonstrate that for a broad range of IMRT treatment plans a robust reconstruction of errors is achievable with only 3 projections (3 sets of SDA oriented at at 0°, 45° and 135°). The SDA is capable of capturing both systematic errors in leaf banks and individual leaves as well as random errors sufficient for practical clinical purposes. Significance. These features of the SDA detector makes it suitable for real-time Quality Control of MLC collimated linac output.