bluuebunny/crossref_metadata_2025 huggingface dataset:
A numerical algorithm for inverse problem from partial boundary measurement arising from mean field game problem
Authors: Chow Yat Tin , Wu Fung Samy , Liu Siting , Nurbekyan Levon , Osher Stanley
Published: November 2022

In this work, we consider a novel inverse problem in mean-field games (MFGs). We aim to recover the MFG model parameters that govern the underlying interactions among the population based on a limited set of noisy partial observations of the population dynamics under the limited aperture. Due to its severe ill-posedness, obtaining a good quality reconstruction is very difficult. Nonetheless, it is vital to recover the model parameters stably and efficiently in order to uncover the underlying causes for population dynamics for practical needs. Our work focuses on the simultaneous recovery of running cost and interaction energy in the MFG equations from a finite number of boundary measurements of population profile and boundary movement. To achieve this goal, we formalize the inverse problem as a constrained optimization problem of a least squares residual functional under suitable norms. We then develop a fast and robust operator splitting algorithm to solve the optimization using techniques including harmonic extensions, three-operator splitting scheme, and primal-dual hybrid gradient method. Numerical experiments illustrate the effectiveness and robustness of the algorithm.
Direct current triboelectric nanogenerators: a review
Authors: Naval Sourav , Jain Ankesh , Mallick Dhiman
Published: November 2022

Rapid advancements in the Internet of things (IoT) have revolutionized the world by creating a proliferation of low-power wireless devices and sensor nodes. The issue of powering these devices remains a critical challenge as they require a regulated direct current (DC) supply for their operation. Mechanical energy scavenging mechanisms are viewed and promoted as renewable powering solutions for low-power electronics. However, a majority of these energy harvesting mechanisms generate alternating current (AC). Converting AC to DC is a critical issue as it involves using a rectifier, which is not a preferred option considering additional circuitry, power requirements, and the significant threshold voltage of even the most state-of-the-art diodes. DC triboelectric nanogenerators (DC-TENG) have emerged as a direct powering solution, incorporating strategies like electrostatic breakdown, mechanical switching, and dynamic Schottky junction to generate a unidirectional current. Based on these strategies, different topologies for DC-TENG devices have been developed by researchers over time. Since its inception in 2014, the study on DC-TENG has rapidly emerged and expanded. This article reviews the progress associated with DC-TENG mechanisms and topologies, presents a theoretical and comparative study of these mechanisms, and highlights their applications. This article also examines the challenges, recent advancements, and future research prospects in this domain.
Synthesis of infinite-layer nickelates and influence of the capping-layer on magnetotransport
Authors: Krieger Guillaume , Raji Aravind , Schlur Laurent , Versini Gilles , Bouillet Corinne , Lenertz Marc , Robert Jérôme , Gloter Alexandre , Viart Nathalie , Preziosi Daniele
Published: November 2022

The recent discovery of a zero-resistance state in nickel-based compounds has generated a re-excitement about the long-standing problem in condensed matter of high-critical temperature superconductivity, in light of the similarities between infinite-layer nickelates and cuprates. However, despite some formal valence and crystal symmetry analogies, the electronic properties of infinite-layer nickelates are remarkably original accounting, among other properties, of a unique Nd 5d-Ni 3d hybridization. This designates infinite-layer nickelates as a new class of oxide superconductors which should be considered on their own. Here we report about Nd1-x
Sr
x
NiO2 (x = 0, 0.05 and 0.2) thin films synthesized with and without a SrTiO3 (STO) capping-layer, showing very smooth and step-terraced surface morphologies. Angle-dependent anisotropic magnetoresistance (AMR) measurements performed with a magnetic field rotating in-plane or out-of-plane with respect to the sample surface, rendered important information about the magnetic properties of undoped STO-capped and uncapped samples. The results point at a key role of the capping-layer in controlling the magnitude and anisotropy of the AMR. We discuss this control in terms of a combined effect between the Nd 5d-Ni 3d hybridization and an intra-atomic Nd 4f-Nd 5d exchange coupling. Further studies foresee the influence of the capping layer on infinite-layer nickelates with no magnetic rare-earth.
The influence of building material structure on radon emanation
Authors: Kuzmanović Predrag , Miljević Bojan , Todorović Nataša , Forkapić Sofija , Čeliković Igor , Petrović Leposava Filipović , Radić Jovana Knežević
Published: November 2022

In this work, the radon emanation coefficients for selected building materials that are most often used in Serbia for covering floor surfaces (concrete, concrete screed, granite, glazed ceramic tiles, marble, roofing tile, and terrazzo tile) were determined, and the influence of the material structure on their values. The concentration of 226Ra activity in the samples was determined using the gamma spectrometry method. Radon emanation was measured with the RAD7 device. The porosity of the samples was tested using mercury intrusion porosimetry and water absorption methods, and the structural analysis was performed using x-ray diffraction analysis and x-ray fluorescence analysis. The measured values of 226Ra activity concentrations were in the range (4.93–298) Bq kg−1, and the estimated values of the radon emanation coefficients were in the range (0.55–6.05) %. The obtained results indicate that the chemical and mineralogical composition, method of production, and the 226Ra activity concentration have an influence on the emanation of radon from the material. No significant correlation was found between the radon emanation coefficient and the open porosity of the material, most likely due to the inhomogeneous presence of pores of different dimensions in the materials. It was established that the total value of the emanation coefficient depends on the emanation coefficient for pores ⩽100 μm in size.
A lightweight model for train bearing fault diagnosis based on multiscale attentional feature fusion
Authors: He Changfu , He Deqiang , Lao Zhenpeng , Wei Zexian , Xiang Zaiyu , Xiang Weibin
Published: November 2022

As one of the key components of a train, the running gear bearing has the highest fault rate, and its health condition is very important for the safe operation of the train. Therefore, how to quickly and accurately diagnose the health condition of the train running gear bearings under strong noise and variable working conditions has become one of the core contents of the intelligent operation and maintenance strategy. To meet these requirements, a lightweight convolutional neural network based on multiscale attentional feature fusion (MA-LCNN) is proposed in this paper, which takes the inverted residual network as the main structure. Firstly, a multiscale attention module (MA) was designed to extract fault feature information. Secondly, by embedding MAs in different locations, the ability of the MA-LCNN to extract fault feature information is greatly improved. Finally, an ablation experiment and noise resistance experiment are performed. The recognition accuracy scores of the MA-LCNN for cases 2 and 3 are 99.70% and 99.83%, respectively. The results show that the proposed attention module has better learning ability and stability compared to the contrast modules. The MA-LCNN demonstrates better fault diagnosis performance than contrast models under different noise environments and variable working conditions.
White light-emitting, biocompatible, water-soluble metallic magnesium nanoclusters for bioimaging applications
Authors: Srivastava Prachi , Verma Vivek Kumar , Sabbarwal Shivesh , Singh Mamata , Sahoo Kedar , Koch Biplob , Kumar Manoj
Published: November 2022

Ultra-small (1.6 nm), water-soluble, white light-emitting (WLE), highly stable (∼8 months) BSA templated metallic (Mg0) nanoclusters (fluorescent magnesium nanoclusters = FMNCs) is developed using the green and facile route. Synthesis was facilitated by the reduction of magnesium salt, where template bovine serum albumin is utilized as a reducing agent and ascorbic acid act as a capping agent to impart stability in water, thereby obtaining stabilized Mg0 nanoclusters In solution, stabilized Mg0 nanoclusters produce white light (450–620 nm with FWHM ∼120 nm) upon 366 nm light excitation. This white light emission was found to have a CIE coordinate of 0.30, 0.33 [pure white light CIE (0.33, 0.33)]. Taking advantage of WLE and ultrasmall size, FMNCs were used for in vitro fluorescence imaging of HaCaT cell lines, yielding blue (τ = 2.94 ns, with a relative of QY = 1.2 % w.r.t QS), green (τ = 3.07 ns; relative quantum yield of 4.6% w.r.t R6G) and red (τ = 0.3 ns) images. Further, incubation of FMNCs with HEK293 (Human embryonic kidney cell) and cancerous MDA-MB-231 (Breast cancer cell line) human cell lines yielded 100 % cell viability. Current work is envisioned to contribute significantly in the area of science, engineering, and nanomedicine.
An ultra-fast deep-learning-based dose engine for prostate VMAT via knowledge distillation framework with limited patient data
Authors: Tseng Wenchih , Liu Hongcheng , Yang Yu , Liu Chihray , Lu Bo
Published: November 2022

Objective. Deep-learning (DL)-based dose engines have been developed to alleviate the intrinsic compromise between the calculation accuracy and efficiency of the traditional dose calculation algorithms. However, current DL-based engines typically possess high computational complexity and require powerful computing devices. Therefore, to mitigate their computational burdens and broaden their applicability to a clinical setting where resource-limited devices are available, we proposed a compact dose engine via knowledge distillation (KD) framework that offers an ultra-fast calculation speed with high accuracy for prostate Volumetric Modulated Arc Therapy (VMAT). Approach. The KD framework contains two sub-models: a large pre-trained teacher and a small to-be-trained student. The student receives knowledge transferred from the teacher for better generalization. The trained student serves as the final engine for dose calculation. The model input is patient computed tomography and VMAT dose in water, and the output is DL-calculated patient dose. The ground-truth \dose was computed by the Monte Carlo module of the Monaco treatment planning system. Twenty and ten prostate cases were included for model training and assessment, respectively. The model’s performance (teacher/student/student-only) was evaluated by Gamma analysis and inference efficiency. Main results. The dosimetric comparisons (input/DL-calculated/ground-truth doses) suggest that the proposed engine can effectively convert low-accuracy doses in water to high-accuracy patient doses. The Gamma passing rate (2%/2 mm, 10% threshold) between the DL-calculated and ground-truth doses was 98.64 ± 0.62% (teacher), 98.13 ± 0.76% (student), and 96.95 ± 1.02% (student-only). The inference time was 16 milliseconds (teacher) and 11 milliseconds (student/student-only) using a graphics processing unit device, while it was 936 milliseconds (teacher) and 374 milliseconds (student/student-only) using a central processing unit device. Significance. With the KD framework, a compact dose engine can achieve comparable accuracy to that of a larger one. Its compact size reduces the computational burdens and computing device requirements, and thus such an engine can be more clinically applicable.
Thermo/hydration responsive shape memory polymers with enhanced hydrophilicity for biomedical applications
Authors: Suzuki Yuta , Hu Qichan , Batchelor Benjamin , Voit Walter , Ecker Melanie
Published: November 2022

Thiol-ene/acrylate shape memory polymers (SMPs) have sufficient stiffness for facile insertion and precision placement and soften after exposure to physiological conditions to reduce the mechanical mismatch with body tissue. As a result, they have demonstrated excellent potential as substrates for various flexible bioelectronic devices, such as cochlear implants, nerve cuffs, cortical probes, plexus blankets, and spinal cord stimulators. To enhance the shape recovery properties and softening effect of SMPs under physiological conditions, we designed and implemented a new class of SMPs as bioelectronics substrates. In detail, we introduced dopamine acrylamide (DAc) as a hydrophilic monomer into a current thiol-ene polymer network. Dry and soaked dynamic mechanical analyses were performed to evaluate the thermomechanical properties, softening kinetics under wet conditions, and shape recovery properties. Modification of SMPs by DAc provided an improved softening effect and shape recovery speed under physiological conditions. Here, we report a new strategy for designing SMPs with enhanced shape recovery properties and lower moduli than previously reported SMPs under physiological conditions without sacrificing stiffness at room temperature by introducing a hydrophilic monomer.
Dynamical change under slowly changing conditions: the quantum Kruskal–Neishtadt–Henrard theorem
Authors: Stabel Peter , Anglin James R
Published: November 2022

Adiabatic approximations break down classically when a constant-energy contour splits into separate contours, forcing the system to choose which daughter contour to follow; the choices often represent qualitatively different behavior, so that slowly changing conditions induce a sudden and drastic change in dynamics. The Kruskal–Neishtadt–Henrard (KNH) theorem relates the probability of each choice to the rates at which the phase space areas enclosed by the different contours are changing. This represents a connection within closed-system mechanics, and without dynamical chaos, between spontaneous change and increase in phase space measure, as required by the Second Law of Thermodynamics. Quantum mechanically, in contrast, dynamical tunneling allows adiabaticity to persist, for very slow parameter change, through a classical splitting of energy contours; the classical and adiabatic limits fail to commute. Here we show that a quantum form of the KNH theorem holds nonetheless, due to unitarity.
Information preservation of two qubits in a structured environment
Authors: Xiong Heng-Na , Li Lingfeng , Sun Zhe , Yang ZeJin , Le Zichun , Huang Yixiao , Wang Xiaoguang
Published: November 2022

The environment-induced decoherence of a quantum open system makes it fundamentally import to preserve the initial quantum information of the system in its steady state. Here we study information preservation of two maximally entangled qubits lying inside a photonic-crystal waveguide with semi-infinite cavity-array structure. We generalize our study to arbitrary position and arbitrary frequency detuning of the qubits. We find that for weak qubits-waveguide couplings, the information preservation greatly depends on the position and the frequency detuning of the qubits, while for strong couplings, both of these dependence is significantly weakened. Interestingly, by suitably choosing the position and the frequency of the qubits, high information preservation could be achieved for both weak and strong couplings, irrespective to Markovian or non-Markovian dynamics. Physically, we analytically verify that the ability of information preservation is indeed determined by the existence of the bound states of the entire system, but the probability of information preservation is closely related to the probability of the initial state of the qubits in the bound states. Our results provide an alternative route getting high information preservation without any external controls of the system.
Scattering dominated spatial coherence and phase correlation properties in plasmonic lattice lasers
Authors: Heikkinen Janne I , Asamoah Benjamin , Calpe Roman , Nečada Marek , Koivurova Matias , Hakala Tommi K
Published: November 2022

We present a comprehensive study of the polarization and spatial coherence properties of the lasing modes supported by a four-fold symmetric plasmonic lattice. We can distinguish the scattering induced effects from the lattice geometry induced effects by modifying only the diameter of the particles while keeping the lattice geometry constant. Customized interferometric measurements reveal that the lasing emission undergoes a drastic change from 1D to 2D spatial coherence with increasing particle size, accompanied with dramatic changes in the far field polarization and beaming properties. By utilizing T-matrix scattering simulations, we reveal the physical mechanism governing this transition. In particular, we find that there exists increased radiative coupling in the diagonal directions at the plane of the lattice when the particle diameter is increased. Finally, we demonstrate that the x- and y-polarized (degenerate) lasing modes become phase locked with sufficiently large particles.
The thermoelectric properties of XTe (X = Ge, Sn and Pb) monolayers from first-principles calculations
Authors: Liu Xin , Zhang Dingbo , Chen Yuanzheng , Wang Hui , Ou Kai , Xia Yudong , Wang Hongyan , Ni Yuxiang
Published: November 2022

Thermoelectric (TE) materials are increasingly attracting the attention of researchers as new energy materials that are capable of converting thermal energy into electrical energy. In this work, combining first-principles calculations and the Boltzmann transport equation, the TE related properties of XTe (X = Ge, Sn and Pb) monolayers have been thoroughly studied. The calculated results show that XTe monolayers are indirect band gap semiconductors, and they possess small effective masses which lead to large carrier mobilities and high electrical conductivities. Except for p-type PbTe, the other XTe monolayers share extremely high PF, thanks to the high Seebeck coefficients and large electrical conductivity. Furthermore, owing to the low phonon group velocity and strong anharmonicity, the lattice thermal conductivities of SnTe and PbTe are quite low. At 500 K, the optimum figure of merit (ZT) values are calculated to be 1.26, 2.61 and 5.91 for GeTe, SnTe and PbTe respectively. The obtained ZT values of the XTe monolayers are larger than these of their bulk counterparts. These results qualify XTe monolayers as promising candidates for building outstanding TE devices.
A new 5D fractional-order conservative hyperchaos system
Authors: Tian Bowen , Peng Qiqi , Leng Xiangxin , Du Baoxiang
Published: November 2022

At present, most of the encryption algorithms based on chaotic systems use dissipative chaotic systems. However, the dissipative chaotic systems have attractors and are easy to reconstruct, which leads to potential security risks in the process of data transmission. Therefore, a novel five-dimensional conservative hyperchaotic system is proposed in this paper, and the integer order system is transformed into a fractional-order system based on the Adomian decomposition method(ADM). The dynamic characteristics of the system are discussed by using classical analysis methods such as Lyapunov exponent spectrum(LEs), bifurcation diagram, phase diagram, and timing diagram. By changing the system parameters and the differential order q, we found a wealth of dynamic phenomena, such as quasi-periodic flow, chaotic flow, and hyperchaotic flow. When the initial value is used as a variable, it is found that the system has initial offset boosting behavior, multiple stability, and special transient behavior. In addition, we use the spectral entropy algorithm to analyze the complexity of the system. Finally, hardware experiments are also carried out using digital signal processor (DSP) to verify the correctness of the numerical simulation, and also to prove the physical realizability of the system, to create conditions for its subsequent engineering applications.
Structural, optical, and antibacterial properties of Li-doped ZnO nanoparticles synthesized in water: evidence of incorporation of interstitial Li
Authors: Mukherjee Sumit , Pramanik Subhamay , Das Sandip , Mandal Rajesh , Chakraborty Subhabrata , Chattopadhyay Amarnath , Ghosh Tatan , Pal Sukanta , Nath Rajib , Kuiri Probodh K
Published: November 2022

The mode of incorporation of lithium (Li) (as substitution or interstitial position) in zinc oxide (ZnO) has its own importance as far as the potential applications of Li-doped ZnO nanoparticles (NPs) are concerned. Fabrication of p-type ZnO-based semiconductors as well as defect engineering-based applications demand substitution of Zn2+ by Li+. However, doping of ZnO by Li with interstitial positions can play an important role in controlling different properties of it. In the present study, we report the successful doping of Li in ZnO NPs up to a Li concentration of 10 mol% employing a simple wet chemical precipitation method in water. Up to a Li concentration of 8 mol%, doping by substitution of Li to the Zn sites has been observed. However, for 10 mol% of Li concentration, doping by incorporation of interstitial sites in addition to the substitution has been confirmed through complementary characterization techniques. The effects of interstitial Li in ZnO on structural, optical, and antimicrobial properties have been studied in detail systematically. For all the cases (structural, optical, and antimicrobial), the properties of Li-doped ZnO NPs have been changed reversibly in the ZnO NPs after the incorporation of interstitial sites by Li as compared to the substitution of Li. For example, the microstrain, band gap, and antimicrobial activity have been found to increase with the increase in Li concentration up to 8 mol%. However, the microstrain, band gap, and antimicrobial activity are found the decrease for 10 mol% of Li as compared to 8 mol% of Li. This study indicated that the different properties of Li-doped ZnO NPs can be controlled suitably as per the requirements for the practical applications of ZnO-based materials.
Structure, half-metallic and magnetic properties of bulk and (001) surface of Rb2XMoO6 (X = Cr, Sc) double perovskites: a DFT + U study
Authors: Mebed Abdelazim M , Mushtaq Muhammad , Muhammad Iltaf , Lone Ikram Un Nabi , AL-Qaisi Samah , Algethami Norah , EL-Shamy E F , Laref Amel , AL-Hosiny N M
Published: November 2022

Half-metallic (HM) ferromagnets (HM-FMs) with large HM gap and high Curie temperature (TC) have a great importance in the field of spintronics. In this study, the geometric features, electronic structure and magnetism of two new double perovskites (DPs) represented by Rb2XMoO6 (X = Cr, Sc) were explored in bulk phase and (001) surface using quantum mechanical total energy calculations based on density functional theory (DFT). The results showed that optimized lattice constant a is 7.96 Å and 8.26 Å for Rb2CrMoO6 (RCMO) and Rb2ScMoO6 (RSMO), respectively, in the cubic phase (space group Fm-3m, #225). The cohesive energy Ecoh, formation energy Efor and elastic constants (mechanical) calculations proved that present materials are stable. The magnetic properties were explored in terms of ground state magnetic coupling, total magnetic moment (M) and atomic magnetic moment (m), exchange energy (J), and Curie temperature. It was found that both materials have ferromagnetic coupling in the ground state, with M of integer value of 8.0 μ
B (4.0 μ
B), J value of 47 meV(72 meV) and TC of 365 K (557 K) in Rb2CrMoO6 (Rb2ScMoO6). The electronic properties computed with electronic band structure and density of states demonstrated both DPs to be half-metal with HM gap of 1.61 eV (2.1 eV) in Rb2Cr-based (Rb2Sc-based) system. Finally the electronic and magnetic properties of (001) surfaces were investigated and compared with that of bulk phase. Interestingly, bulk HM property was retained in RSMO, but disappeared in RCMO due the emergence of defect states at Fermi level (EF). The reported results suggest that Rb-based DPs carry some fascinating properties for spin-based devices.
Experimental SDR implementation of cooperative spectrum sensing in cognitive radio networks
Authors: Bouzegag Younes , Teguig Djamal , Maali Abdelmadjid
Published: November 2022

In this paper, a Software Defined Radio (SDR) implementation of Cooperative Spectrum Sensing (CSS) is investigated. More precisely, various local spectrum sensing algorithms have been implemented and validated on USRP B210 using the Qt framework. The realized test bed is based on a client-server architecture. In the client interface, different spectrum sensing techniques have been implemented and analyzed. The fusion center interface implements all hard decision combination schemes, namely OR, AND, and the MAJORITY rule. Finally, several realistic scenarios have been considered to validate our SDR implementation. Moreover, these implementations allowed us to assess the efficiency of different hard-decision combination schemes for cooperative detection in the context of cognitive radio. Besides, the performance improvement is analytically evaluated and corroborated by the experimental results. These results regarding real scenarios confirm that Goodness of Fit-based (GoF) sensing methods outperform conventional methods. Furthermore, theoretical and simulation results from CSS have been validated experimentally that OR-rule gives clearly better results than other hard decisions combinations schemes.
Extending the applicability of popular force fields for describing water/metal interfaces: application to water/Pd(111)
Authors: Gomes-Filho Márcio S. , Pereira Aline O. , Feliciano Gustavo T , Pedroza Luana S. , Coutinho-Neto Mauricio D.
Published: November 2022

We propose a new method for constructing a polarizable classical force field using data obtained from QM and QM/MM calculations to account for the charge redistribution at the water/metal interface. The induced charge effects are described by adding dipoles to the system topology following the Rod Model (Iori, F, et al J. Comput. Chem.2009, 30, 1465). Furthermore, the force field uses the TIP3P water model, and its functional form is compatible with popular force fields such as AMBER, CHARMM, GROMOS, OPLS-AA, CVFF and IFF. The proposed model was evaluated and validated for water/Pd(111) systems. We tuned the model parameters to reproduce a few critical water/Pd(111) geometries and energies obtained from DFT calculations using both PBE and a non-local van der Waals xc-functional. Our model can reproduce the hexagonal ice layer for the Pd(111)/water systems typically present in low-temperature experiments, in agreement with information available from the literature. Additionally, the model can also reproduce the experimental metal-water interfacial tension at room temperature.
The free field representation for the GL(1∣1) WZW model revisited
Authors: Lashkevich Michael
Published: November 2022

The GL(1∣1) WZW model in the free field realization that uses the bc system is revisited. By bosonizing the bc system we describe the Neveu-Schwarz and Ramond sector modules



en

NS

=

⨁

l
∈
Z



en

l

and



en

R

=

⨁

l
∈
Z
+

1

2



en

l

in terms of the subspaces of a given fermion number l. We show that there are two sectors of mutually local operators, each consists of all Neveu-Schwarz operators and of Ramond operators with either integer or half-integer spins. Conformal blocks and structure constants are found for operators that correspond the highest weight vectors of the spaces



en

l

. The crossing and braiding matrices are considered and the hexagon and pentagon equations are shown to be satisfied for typical modules. The degenerate case of conformal blocks with atypical (logarithmic) modules as intermediate states is considered. The known conformal block decomposition of correlation functions in the degenerate case is shown to be related to the degeneration splitting in the crossing and braiding relations. The scalar product in atypical modules is discussed. The decomposition of unity in the full correlation functions in the degenerate case in terms of this scalar product is explained.
A transparent water-based metamaterial broadband absorber with a tunable absorption band
Authors: Yao Boyi , Zeng Qu , Duan Junping , Wei Li , Kang Jinfeng , Zhang Binzhen
Published: November 2022

In this study, a tunable and optically transparent water-based wideband metamaterial absorber (MMA) is proposed and verified. By adjusting the thickness of the water layer, the conversion of the absorber absorption band from 7.4–22.4 GHz to 23.1–35.5 GHz can be achieved, which demonstrates the flexibility of MMA. Indium tin oxide (ITO) as the resonant and reflective layers of the material structure. Optically transparent polymethyl methacrylate (PMMA) is used as a medium container to encapsulate the water. Furthermore, the suggested MMA is polarization insensitive and has broad incident angle stability. Experiments verify the excellent properties of the proposed MMA. As a result, the suggested MMA has various applications in military and medical equipment optical windows.
Optimization for ultrahigh specific capacity and superior temperature control in a Li-ion battery cell
Authors: Farsi Salman , Islam Md Rasidul , Rahman Md Arafat
Published: November 2022

With the revolution in power generation and the development of electrification, portable electronic gadgets have recently posed escalating needs for suitable energy storage applications. The lithium-ion battery (LIB) is an electrochemical energy storage device that can achieve high energy density while retaining high power density. Here, we build a high energy density LIB module with a ∼12.10% increase in energy density over the previous cell. For environmental and safety reasons, several design elements such as electrode thickness, porosity, current density, and particle size were iterated to improve specific capacity and energy density without changing the ambient temperature increment. We have used a simple heat generation system; the temperature raised by ∼18.96% from the room environment was close to 29.74 °C. The specific capacity was also improved by ∼14.56% as compared to commercial LIB. Besides, we used the gassing and plating methods to reduce the integrated Li-ion loss for both the cathode and anode. All of the remarkable findings in this work will aid in the optimization and design of next-generation LIB cells.
The Significance of Thermally Pulsing Asymptotic Giant Branch Stars in Post-starburst Galaxies
Authors: Liu Siqi , Luo A-Li
Published: November 2022

We measure the significance of thermally pulsing asymptotic giant branch (TP-AGB) stars via the spectral energy distributions (SEDs) of a sample of post-starburst (PSB) galaxies at z = 0.2–0.7. Using ground- and space-based photometry from the 3D-HST catalog, as well as associated near-infrared (NIR) Hubble Space Telescope (HST) slitless grism spectroscopy, we evaluate the importance of TP-AGB stars in the SEDs of 177 PSB galaxies by fitting simple stellar populations with different levels of TP-AGB contributions. The grism spectra, despite their low resolution of R ∼ 100, enable the detection of molecular features specific to TP-AGB stars and thus improve constraints on their contribution. A majority (∼70%) of galaxies in the PSB sample show features indicative of TP-AGB stars, while the remainder does not and they are well fit by Bruzual & Charlot TP-AGB light models. Stacked spectra of sources classified to be the best fit by TP-AGB heavy/mild models reveal strong detections of NIR molecular features associated with TP-AGB stars. Additionally, we observe a tentative trend with redshift where more TP-AGB heavy galaxies are observed in the higher redshift PSB galaxy population. Finally, neglecting the contribution of TP-AGB stars can yield an over-prediction of stellar masses measured in the K-band ranging from 0.13–0.23 dex.
Effect of negative triangularity on the bulk ions co-current rotation caused by the ion orbit loss at the edge of the tokamak plasmas
Authors: Wang Ruoying , Pan Chengkang
Published: November 2022

The ion orbit loss (IOL) can drive the bulk ions co-current rotation at the edge of the tokamak plasmas. The effect of triangularity on the IOL is investigated by using an analytical tokamak equilibrium model for the shaped plasmas. The peaking speed of the bulk ions co-current rotation at the tokamak edge will be increased greatly with the negative triangularity.
ConViT: improving vision transformers with soft convolutional inductive biases*
Authors: d’Ascoli Stéphane , Touvron Hugo , Leavitt Matthew L , Morcos Ari S , Biroli Giulio , Sagun Levent
Published: November 2022

Convolutional architectures have proven to be extremely successful for vision tasks. Their hard inductive biases enable sample-efficient learning, but come at the cost of a potentially lower performance ceiling. Vision transformers rely on more flexible self-attention layers, and have recently outperformed CNNs for image classification. However, they require costly pre-training on large external datasets or distillation from pre-trained convolutional networks. In this paper, we ask the following question: is it possible to combine the strengths of these two architectures while avoiding their respective limitations? To this end, we introduce gated positional self-attention (GPSA), a form of positional self-attention which can be equipped with a ‘soft’ convolutional inductive bias. We initialize the GPSA layers to mimic the locality of convolutional layers, then give each attention head the freedom to escape locality by adjusting a gating parameter regulating the attention paid to position versus content information. The resulting convolutional-like ViT architecture, ConViT, outperforms the DeiT (Touvron et al 2020 arXiv:2012.12877) on ImageNet, while offering a much improved sample efficiency. We further investigate the role of locality in learning by first quantifying how it is encouraged in vanilla self-attention layers, then analyzing how it has escaped in GPSA layers. We conclude by presenting various ablations to better understand the success of the ConViT. Our code and models are released publicly at https://github.com/facebookresearch/convit.
Ising model selection using ℓ
1-regularized linear regression: a statistical mechanics analysis*
Authors: Meng Xiangming , Obuchi Tomoyuki , Kabashima Yoshiyuki
Published: November 2022

We theoretically analyze the typical learning performance of ℓ
1-regularized linear regression (ℓ
1-LinR) for Ising model selection using the replica method from statistical mechanics. For typical random regular graphs in the paramagnetic phase, an accurate estimate of the typical sample complexity of ℓ
1-LinR is obtained. Remarkably, despite the model misspecification, ℓ
1-LinR is model selection consistent with the same order of sample complexity as ℓ
1-regularized logistic regression (ℓ
1-LogR), i.e.

M
=
O

log

N

, where N is the number of variables of the Ising model. Moreover, we provide an efficient method to accurately predict the non-asymptotic behavior of ℓ
1-LinR for moderate M, N, such as precision and recall. Simulations show a fairly good agreement between theoretical predictions and experimental results, even for graphs with many loops, which supports our findings. Although this paper mainly focuses on ℓ
1-LinR, our method is readily applicable for precisely characterizing the typical learning performances of a wide class of ℓ
1-regularized M-estimators including ℓ
1-LogR and interaction screening.
On the proliferation of support vectors in high dimensions*
Authors: Hsu Daniel , Muthukumar Vidya , Xu Ji
Published: November 2022

The support vector machine (SVM) is a well-established classification method whose name refers to the particular training examples, called support vectors, that determine the maximum margin separating hyperplane. The SVM classifier is known to enjoy good generalization properties when the number of support vectors is small compared to the number of training examples. However, recent research has shown that in sufficiently high-dimensional linear classification problems, the SVM can generalize well despite a proliferation of support vectors where all training examples are support vectors. In this paper, we identify new deterministic equivalences for this phenomenon of support vector proliferation, and use them to (1) substantially broaden the conditions under which the phenomenon occurs in high-dimensional settings, and (2) prove a nearly matching converse result.
An analytical theory of curriculum learning in teacher–student networks*
Authors: Saglietti Luca , Mannelli Stefano Sarao , Saxe Andrew
Published: November 2022

In animals and humans, curriculum learning—presenting data in a curated order—is critical to rapid learning and effective pedagogy. A long history of experiments has demonstrated the impact of curricula in a variety of animals but, despite its ubiquitous presence, a theoretical understanding of the phenomenon is still lacking. Surprisingly, in contrast to animal learning, curricula strategies are not widely used in machine learning and recent simulation studies reach the conclusion that curricula are moderately effective or even ineffective in most cases. This stark difference in the importance of curriculum raises a fundamental theoretical question: when and why does curriculum learning help? In this work, we analyse a prototypical neural network model of curriculum learning in the high-dimensional limit, employing statistical physics methods. We study a task in which a sparse set of informative features are embedded amidst a large set of noisy features. We analytically derive average learning trajectories for simple neural networks on this task, which establish a clear speed benefit for curriculum learning in the online setting. However, when training experiences can be stored and replayed (for instance, during sleep), the advantage of curriculum in standard neural networks disappears, in line with observations from the deep learning literature. Inspired by synaptic consolidation techniques developed to combat catastrophic forgetting, we propose curriculum-aware algorithms that consolidate synapses at curriculum change points and investigate whether this can boost the benefits of curricula. We derive generalisation performance as a function of consolidation strength (implemented as an L
2 regularisation/elastic coupling connecting learning phases), and show that curriculum-aware algorithms can yield a large improvement in test performance. Our reduced analytical descriptions help reconcile apparently conflicting empirical results, trace regimes where curriculum learning yields the largest gains, and provide experimentally-accessible predictions for the impact of task parameters on curriculum benefits. More broadly, our results suggest that fully exploiting a curriculum may require explicit adjustments in the loss.
Disordered systems insights on computational hardness
Authors: Gamarnik David , Moore Cristopher , Zdeborová Lenka
Published: November 2022

In this review article we discuss connections between the physics of disordered systems, phase transitions in inference problems, and computational hardness. We introduce two models representing the behavior of glassy systems, the spiked tensor model and the generalized linear model. We discuss the random (non-planted) versions of these problems as prototypical optimization problems, as well as the planted versions (with a hidden solution) as prototypical problems in statistical inference and learning. Based on ideas from physics, many of these problems have transitions where they are believed to jump from easy (solvable in polynomial time) to hard (requiring exponential time). We discuss several emerging ideas in theoretical computer science and statistics that provide rigorous evidence for hardness by proving that large classes of algorithms fail in the conjectured hard regime. This includes the overlap gap property, a particular mathematization of clustering or dynamical symmetry-breaking, which can be used to show that many algorithms that are local or robust to changes in their input fail. We also discuss the sum-of-squares hierarchy, which places bounds on proofs or algorithms that use low-degree polynomials such as standard spectral methods and semidefinite relaxations, including the Sherrington–Kirkpatrick model. Throughout the manuscript we present connections to the physics of disordered systems and associated replica symmetry breaking properties.
Transport properties of diffusive particles conditioned to survive in trapping environments
Authors: Pozzoli Gaia , De Bruyne Benjamin
Published: November 2022

We consider a one-dimensional Brownian motion with diffusion coefficient D in the presence of n partially absorbing traps with intensity β, separated by a distance L and evenly spaced around the initial position of the particle. We study the transport properties of the process conditioned to survive up to time t. We find that the surviving particle first diffuses normally, before it encounters the traps, then undergoes a period of transient anomalous diffusion, after which it reaches a final diffusive regime. The asymptotic regime is governed by an effective diffusion coefficient D
eff, which is induced by the trapping environment and is typically different from the original one. We show that when the number of traps is finite, the environment enhances diffusion and induces an effective diffusion coefficient that is systematically equal to D
eff = 2D, independently of the number of the traps, the trapping intensity β and the distance L. On the contrary, when the number of traps is infinite, we find that the environment inhibits diffusion with an effective diffusion coefficient that depends on the traps intensity β and the distance L through a non-trivial scaling function

D

eff

=
D
F

(

β
L
/
D

)

, for which we obtain a closed-form. Moreover, we provide a rejection-free algorithm to generate surviving trajectories by deriving an effective Langevin equation with an effective repulsive potential induced by the traps. Finally, we extend our results to other trapping environments.
Low intensity gamma-ray monitor for in-situ solids fraction measurements in liquids
Authors: Kaur Sraw Talwinder , Yu Bo , Sedgwick Andrea , Junaid Abu , Tsui Ying , Gupta Manisha , Fedosejevs Robert
Published: November 2022

A novel detection system has been designed to measure the settling of solids in tailing ponds in order to facilitate the reuse of water in oil sands extraction processing, tailings excavation, transportation and management. The system is based on a weak gamma ray source and an inexpensive scintillator-based detector. The system measures gamma ray photons which are transmitted through the material of interest which are detected by a combined scintillator and Multi Pixel Photon Counter (MPPC) detector. This non-destructive measurement allows the determination of the solids contents profile versus depth in a tailing pond. The attenuation of gamma radiation depends on the density of the solids within the fluid tailings and thus varies with the weight fraction of solids content of the tailings. Modelling of the system was carried out by Geant4 simulations. The system was deployed using a weak 133Ba gamma-ray source together with a simple microprocessor controller readout circuit to analyze the pulse height response of a Cerium doped Lutetium Yttrium Orthosilicate (LYSO (Ce)) scintillator crystal. The detection system is calibrated with the known samples and can measure solids content with a relative precision of within ∼2%.
Signal amplification in multistage charge collection process in Si detectors in situ irradiated at superfluid helium temperature
Authors: Eremin V. , Shepelev A. , Verbitskaya E.
Published: November 2022

The effect of charge multiplication in Si p+-n-n+ detectors observed in the unique conditions of the in situ irradiation with 23 GeV proton beam fragmented into 400 ms spills and the temperature of superfluid helium, 1.9 K, was analyzed. The current pulse responses of the detector irradiated to 5 × 1013 p/cm2 demonstrated a two-stage process of charge collection, in which, in the first stage, the current was induced by holes, and in the second, by electrons arising due to avalanche multiplication produced by holes. In the detector irradiated to 2.7 × 1014 p/cm2, the third stage of charge collection was observed that was related to avalanche multiplication produced by electrons reaching the n+ contact and sequential drift of generated holes back to the p+ contact. The developed procedure of data treatment allowed extracting the full set of carrier transport parameters and internal charge gain rising to 3.7 at the bias voltage of 400 V and the fluence of 5 × 1013 p/cm2. An evolution of charge multiplication at the p+ contact initiated by holes originated from a high rate of the hole trap introduction at 1.9 K described by a fivefold rise in the trapping probability at 1.9 K in comparison with its value at T = -10°C. This increases the electric field near the p+ contact and leads to the avalanche multiplication affecting the following stages of charge collection.
Active Region Extent Assessment with X-rays (AREA-X)
Authors: Poley Luise , Blue Andrew , Fadeyev Vitaliy , Sperlich Dennis
Published: November 2022

The development of semiconductor sensors for new particle tracking detectors places increasing limits on sensor characteristics such as uniformity, size and shape of inefficient areas and size of active compared to inactive sensor areas. Accurately assessing these relatively subtle effects requires either measurements in particle beams or the modification of samples to be used in dedicated laser test setups.

Active Region Extent Assessment with X-rays (AREA-X) has been developed as an alternative method for the fast, efficient and precise study of the active area of a semiconductor sensor. It uses a monochromatic, micro-focused X-ray beam with a 10–20 keV energy range as provided by several synchrotron beam lines and uses the photo current induced in the sensor to measure the depth of the responsive sensor volume. It can be used to study local inhomogeneities or inefficiencies, the overall extent of the active sensor volume and its shape and its localised application, which makes the need to gather statistics over a large area unnecessary, allowing for fast readout, which enables studies of the sensor behaviour at a range of external parameters, e.g. temperature or applied bias voltage.

This paper presents the measurement concept and technical setup of the measurement, results from initial measurements as well as capabilities and limitations of the method.
Automatic transmission optimization of the plane-grating monochromator using collimated light
Authors: Shi Y. , Tang L. , He J.
Published: November 2022

It is essential to perform plane-grating monochromator transmission optimization for synchrotron radiation beamlines. Usually, The optimization is time-consuming. In this contribution, an automatic transmission optimization method for the plane-grating monochromator using collimated light based on the Differential Evolution (DE) algorithm is introduced. This method can quickly find the optimal solution. To test this method, a program developed using C++ is verified by optimizing the efficiency of a plane-grating monochromator with a 2000 lines/mm lamellar grating at soft X-ray region. Furthermore, the transmission optimizations of most of the PGM using lamellar gratings in soft x-ray region are performed.