bluuebunny/crossref_metadata_2025 huggingface dataset:
ℏ2 expansion of the transmission probability through a barrier
Authors: Pollak Eli , Cao Jianshu
Published: July 2022

Ninety years ago, Wigner derived the leading order expansion term in ℏ2 for the tunneling rate through a symmetric barrier. His derivation included two contributions: one came from the parabolic barrier, but a second term involved the fourth-order derivative of the potential at the barrier top. He left us with a challenge, which is answered in this paper, to derive the same but for an asymmetric barrier. A crucial element of the derivation is obtaining the ℏ2 expansion term for the projection operator, which appears in the flux-side expression for the rate. It is also reassuring that an analytical calculation of semiclassical transition state theory (TST) reproduces the anharmonic corrections to the leading order of ℏ2. The efficacy of the resulting expression is demonstrated for an Eckart barrier, leading to the conclusion that especially when considering heavy atom tunneling, one should use the expansion derived in this paper, rather than the parabolic barrier approximation. The rate expression derived here reveals how the classical TST limit is approached as a function of ℏ and, thus, provides critical insights to understand the validity of popular approximate theories, such as the classical Wigner, centroid molecular dynamics, and ring polymer molecular dynamics methods.
More extensive land loss expected on coastal deltas due to rivers jumping course during sea-level rise
Authors: Chadwick Austin J. , Steele Sarah , Silvestre Jose , Lamb Michael P.
Published: July 2022

River deltas are home to hundreds of millions of people worldwide and are in danger of sinking due to anthropogenic sea-level rise, land subsidence, and reduced sediment supply. Land loss is commonly forecast by averaging river sediment supply across the entire delta plain to assess whether deposition can keep pace with sea-level rise. However, land loss and deposition vary across the landscape because rivers periodically jump course, rerouting sediment to distinct subregions called delta lobes. Here, we developed a model to forecast land loss that resolves delta lobes and tested the model against a scaled laboratory experiment. Both the model and the experiment show that rivers build land on the active lobe, but the delta incurs gradual land loss on inactive lobes that are cut off from sediment after the river abandons course. The result is a band of terrain along the coast that is usually drowned but is nonetheless a sink for sediment when the lobe is active, leaving less of the total sediment supply available to maintain persistent dry land. Land loss is expected to be more extensive than predicted by classical delta-plain–averaged models. Estimates for eight large deltas worldwide suggest that roughly half of the riverine sediment supply is delivered to terrain that undergoes long periods of submergence. These results draw the sustainability of deltas further into question and provide a framework to plan engineered diversions at a pace that will mitigate land loss in the face of rising sea levels.
A mechanism of self-lipid endocytosis mediated by the receptor Mincle
Authors: Kostarnoy Alexey V. , Gancheva Petya G. , Kireev Igor I. , Soloviev Andrey I. , Lepenies Bernd , Kulibin Andrey Y. , Malolina Ekaterina A. , Scheglovitova Olga N. , Kondratev Alexey V. , Sokolova Maria V. , Vorobyeva Daria , Filippova Nadezhda , Kapkaeva Marina R. , Lagarkova Maria A. , Metalnikov Pavel S. , Riabenko Evgeniy , Grumov Daniil A. , Bobrov Maxim A. , Vasilieva Elena , Naroditsky Boris S. , Gintsburg Alexander L.
Published: July 2022

Cellular lipid uptake (through endocytosis) is a basic physiological process. Dysregulation of this process underlies the pathogenesis of diseases such as atherosclerosis, obesity, diabetes, and cancer. However, to date, only some mechanisms of lipid endocytosis have been discovered. Here, we show a previously unknown mechanism of lipid cargo uptake into cells mediated by the receptor Mincle. We found that the receptor Mincle, previously shown to be a pattern recognition receptor of the innate immune system, tightly binds a range of self-lipids. Moreover, we revealed the minimal molecular motif in lipids that is sufficient for Mincle recognition. Superresolution microscopy showed that Mincle forms vesicles in cytoplasm and colocalizes with added fluorescent lipids in endothelial cells but does not colocalize with either clathrin or caveolin-1, and the added lipids were predominantly incorporated in vesicles that expressed Mincle. Using a model of ganglioside GM3 uptake in brain vessel endothelial cells, we show that the knockout of Mincle led to a dramatic decrease in lipid endocytosis. Taken together, our results have revealed a fundamental lipid endocytosis pathway, which we call Mincle-mediated endocytosis (MiME), and indicate a prospective target for the treatment of disorders of lipid metabolism, which are rapidly increasing in prevalence.
Molecular framework integrating nitrate sensing in root and auxin-guided shoot adaptive responses
Authors: Abualia Rashed , Ötvös Krisztina , Novák Ondřej , Bouguyon Eleonore , Domanegg Kevin , Krapp Anne , Nacry Philip , Gojon Alain , Lacombe Benoit , Benková Eva
Published: July 2022

Mineral nutrition is one of the key environmental factors determining plant development and growth. Nitrate is the major form of macronutrient nitrogen that plants take up from the soil. Fluctuating availability or deficiency of this element severely limits plant growth and negatively affects crop production in the agricultural system. To cope with the heterogeneity of nitrate distribution in soil, plants evolved a complex regulatory mechanism that allows rapid adjustment of physiological and developmental processes to the status of this nutrient. The root, as a major exploitation organ that controls the uptake of nitrate to the plant body, acts as a regulatory hub that, according to nitrate availability, coordinates the growth and development of other plant organs. Here, we identified a regulatory framework, where cytokinin response factors (CRFs) play a central role as a molecular readout of the nitrate status in roots to guide shoot adaptive developmental response. We show that nitrate-driven activation of NLP7, a master regulator of nitrate response in plants, fine tunes biosynthesis of cytokinin in roots and its translocation to shoots where it enhances expression of
CRFs
. CRFs, through direct transcriptional regulation of
PIN
auxin transporters, promote the flow of auxin and thereby stimulate the development of shoot organs.
LOCOM: A logistic regression model for testing differential abundance in compositional microbiome data with false discovery rate control
Authors: Hu Yingtian , Satten Glen A. , Hu Yi-Juan
Published: July 2022

Compositional analysis is based on the premise that a relatively small proportion of taxa are differentially abundant, while the ratios of the relative abundances of the remaining taxa remain unchanged. Most existing methods use log-transformed data, but log-transformation of data with pervasive zero counts is problematic, and these methods cannot always control the false discovery rate (FDR). Further, high-throughput microbiome data such as 16S amplicon or metagenomic sequencing are subject to experimental biases that are introduced in every step of the experimental workflow. McLaren et al. [
eLife
8, e46923 (2019)] have recently proposed a model for how these biases affect relative abundance data. Motivated by this model, we show that the odds ratios in a logistic regression comparing counts in two taxa are invariant to experimental biases. With this motivation, we propose logistic compositional analysis (LOCOM), a robust logistic regression approach to compositional analysis, that does not require pseudocounts. Inference is based on permutation to account for overdispersion and small sample sizes. Traits can be either binary or continuous, and adjustment for confounders is supported. Our simulations indicate that LOCOM always preserved FDR and had much improved sensitivity over existing methods. In contrast, analysis of composition of microbiomes (ANCOM) and ANCOM with bias correction (ANCOM-BC)/ANOVA-Like Differential Expression tool (ALDEx2) had inflated FDR when the effect sizes were small and large, respectively. Only LOCOM was robust to experimental biases in every situation. The flexibility of our method for a variety of microbiome studies is illustrated by the analysis of data from two microbiome studies. Our R package LOCOM is publicly available.
Molecular determinants of pH sensing in the proton-activated chloride channel
Authors: Osei-Owusu James , Kots Ekaterina , Ruan Zheng , Mihaljević Ljubica , Chen Kevin Hong , Tamhaney Ami , Ye Xinyu , Lü Wei , Weinstein Harel , Qiu Zhaozhu
Published: July 2022

In response to acidic pH, the widely expressed proton-activated chloride (PAC) channel opens and conducts anions across cellular membranes. By doing so, PAC plays an important role in both cellular physiology (endosome acidification) and diseases associated with tissue acidosis (acid-induced cell death). Despite the available structural information, how proton binding in the extracellular domain (ECD) leads to PAC channel opening remains largely unknown. Here, through comprehensive mutagenesis and electrophysiological studies, we identified several critical titratable residues, including two histidine residues (H130 and H131) and an aspartic acid residue (D269) at the distal end of the ECD, together with the previously characterized H98 at the transmembrane domain–ECD interface, as potential pH sensors for human PAC. Mutations of these residues resulted in significant changes in pH sensitivity. Some combined mutants also exhibited large basal PAC channel activities at neutral pH. By combining molecular dynamics simulations with structural and functional analysis, we further found that the β12 strand at the intersubunit interface and the associated “joint region” connecting the upper and lower ECDs allosterically regulate the proton-dependent PAC activation. Our studies suggest a distinct pH-sensing and gating mechanism of this new family of ion channels sensitive to acidic environment.
Interferon resistance of emerging SARS-CoV-2 variants
Authors: Guo Kejun , Barrett Bradley S. , Morrison James H. , Mickens Kaylee L. , Vladar Eszter K. , Hasenkrug Kim J. , Poeschla Eric M. , Santiago Mario L.
Published: July 2022

The emergence of SARS-CoV-2 variants with enhanced transmissibility, pathogenesis, and resistance to vaccines presents urgent challenges for curbing the COVID-19 pandemic. While Spike mutations that enhance virus infectivity or neutralizing antibody evasion may drive the emergence of these novel variants, studies documenting a critical role for interferon responses in the early control of SARS-CoV-2 infection, combined with the presence of viral genes that limit these responses, suggest that interferons may also influence SARS-CoV-2 evolution. Here, we compared the potency of 17 different human interferons against multiple viral lineages sampled during the course of the global outbreak, including ancestral and five major variants of concern that include the B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma), B.1.617.2 (delta), and B.1.1.529 (omicron) lineages. Our data reveal that relative to ancestral isolates, SARS-CoV-2 variants of concern exhibited increased interferon resistance, suggesting that evasion of innate immunity may be a significant, ongoing driving force for SARS-CoV-2 evolution. These findings have implications for the increased transmissibility and/or lethality of emerging variants and highlight the interferon subtypes that may be most successful in the treatment of early infections.
SARS-CoV-2 impairs interferon production via NSP2-induced repression of mRNA translation
Authors: Xu Zhang , Choi Jung-Hyun , Dai David L. , Luo Jun , Ladak Reese Jalal , Li Qian , Wang Yimeng , Zhang Christine , Wiebe Shane , Liu Alex C. H. , Ran Xiaozhuo , Yang Jiaqi , Naeli Parisa , Garzia Aitor , Zhou Lele , Mahmood Niaz , Deng Qiyun , Elaish Mohamed , Lin Rongtuan , Mahal Lara K. , Hobman Tom C. , Pelletier Jerry , Alain Tommy , Vidal Silvia M. , Duchaine Thomas , Mazhab-Jafari Mohammad T. , Mao Xiaojuan , Jafarnejad Seyed Mehdi , Sonenberg Nahum
Published: July 2022

Viruses evade the innate immune response by suppressing the production or activity of cytokines such as type I interferons (IFNs). Here we report the discovery of a mechanism by which the SARS-CoV-2 virus coopts an intrinsic cellular machinery to suppress the production of the key immunostimulatory cytokine IFN-β. We reveal that the SARS-CoV-2 encoded nonstructural protein 2 (NSP2) directly interacts with the cellular GIGYF2 protein. This interaction enhances the binding of GIGYF2 to the mRNA cap-binding protein 4EHP, thereby repressing the translation of the
Ifnb1
mRNA. Depletion of GIGYF2 or 4EHP significantly enhances IFN-β production, which inhibits SARS-CoV-2 replication. Our findings reveal a target for rescuing the antiviral innate immune response to SARS-CoV-2 and other RNA viruses.
Actin–microtubule dynamic composite forms responsive active matter with memory
Authors: Kučera Ondřej , Gaillard Jérémie , Guérin Christophe , Théry Manuel , Blanchoin Laurent
Published: July 2022

Active cytoskeletal materials in vitro demonstrate self-organizing properties similar to those observed in their counterparts in cells. However, the search to emulate phenomena observed in living matter has fallen short of producing a cytoskeletal network that would be structurally stable yet possess adaptive plasticity. Here, we address this challenge by combining cytoskeletal polymers in a composite where self-assembling microtubules and actin filaments collectively self-organize due to the activity of microtubule-percolating molecular motors. We demonstrate that microtubules spatially organize actin filaments that in turn guide microtubules. The two networks align in an ordered fashion using this feedback loop. In this composite, actin filaments can act as structural memory and, depending on the concentration of the components, microtubules either write this memory or get guided by it. The system is sensitive to external stimuli, suggesting possible autoregulatory behavior in changing mechanochemical environments. We thus establish an artificial active actin–microtubule composite as a system demonstrating architectural stability and plasticity.
Sinterability and microstructure evolution of powder metallurgy processed titanium aluminides
Authors: Alves Nogueira da Silva Jefferson , Quaglio Lorenzo , Alves Monfardini Warlen , Soyama Juliano
Published: July 2022

The objective of this study was to assess the effect of different aluminium additions in microstructure evolution and hardness of powder metallurgy processed titanium aluminides. Alloys with aluminium contents of 10, 20, 30, 40 and 45 at.-% were prepared using mixtures of elemental powders that were cold uniaxially pressed. Sintering was conducted at 1300 and 1400°C for 2 h under argon atmosphere. The results indicated a sharp decrease in sinterability for larger elemental aluminium additions. Furthermore, the hardness values decreased with the aluminium content due to the higher porosity. However, in alloys with higher aluminium content, despite the higher porosity, microstructural homogeneity was improved and equilibrium phases α2-Ti3Al and γ-TiAl could be achieved in fully lamellar Ti-40Al and Ti-45Al.
Final report "Key comparison CCM.FF-K1.2015 - water flow: 30 m3/h ... 200 m3/h"
Authors: Furuichi N , Arias R , Yang C-T , Chun S , Meng T , Shinder I , Frahm E , Büker O , Mills Chr , Akselli B , Smits F M
Published: July 2022

Main text

The objective of the Key Comparison CCM.FF-K1.2015 for water flow measurement was to support and prove the Calibration and Measurement Capabilities (CMC) of the participating NMIs of Japan (AIST), Mexico (CENAM), Chinese Taipei (ITRI), Korea (KRISS), P.R. China (NIM), Germany (PTB), USA (NIST), Sweden (RISE), UK (NEL), Turkey (TUBITAK UME) and Netherlands (VSL). The comparison was organized as a round robin, started in December 2015 at PTB and finished in April 2018, also at PTB. As pilot laboratory, the national metrology institute of Germany (PTB) organised the comparison. A combined setup of a turbine meter and Coriolis meter was used as a transfer standard (TS), which was provided by the pilot laboratory. The nominal calibration conditions of the KC were defined within the flow range between 30 m3/h and 200 m3/h, 20 °C fluid temperature and 3 bar line pressure.

A special focus of the comparison was to estimate the uncertainties of the transfer standard (u
TS). Both transfer meters were subjected to extensive characterization measurements at pilot laboratory, with the following investigated parameters: fluid temperature, line pressure, repeatability, flow stability, meter sensitivity to varying inflow conditions and hysteresis effects.

For turbine meter, all labs passed the E
N criteria of ≤ 1.20. The calibrations of the turbine meter were strongly affected by the presence of the large values for u
TS with > 0.12 % k =1) which were mainly caused by the meter sensitivity to disturbed inflow conditions. This effect led to inconclusive calibration results for all laboratories. The evaluation criteria u
comp/u
base exceeded the critical value of 2.00. Finally, the turbine meter was not suitable for a confirmation of all submitted CMC values.

For Coriolis meter, all labs passed the E
N criteria of ≤ 1.20. In contrast to turbine meter, the evaluation criteria u
comp/u
base exceeded the critical value of 2.00 for one laboratory, only. The maximum uncertainty u
TS of Coriolis meter was estimated with 0.022 % (k =1).

In summary, the comparison was successfully finished for a confirmation of the submitted CMC values, related to mass calibrations. For volume related CMCs this comparison was not suitable.

To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.

The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Inverse medium scattering problems with Kalman filter techniques
Authors: Furuya Takashi , Potthast Roland
Published: July 2022

We study the inverse medium scattering problem to reconstruct the unknown inhomogeneous medium from the far field patterns of scattered waves. The inverse scattering problem is generally ill-posed and nonlinear, and the iterative optimization method is often adapted. A natural iterative approach to this problem is to place all available measurements and mappings into one long vector and mapping, respectively, and to iteratively solve the linearized large system equation using the Tikhonov regularization method, which is called Levenberg–Marquardt scheme. However, this is computationally expensive because we must construct the larger system equations when the number of available measurements is increasing. In this paper, we propose two reconstruction algorithms based on the Kalman filter. One is the algorithm equivalent to the Levenberg–Marquardt scheme, and the other is inspired by the extended Kalman filter. For the algorithm derivation, we iteratively apply the Kalman filter to the linearized equation for our nonlinear equation. By applying the Kalman filter, our proposed algorithms sequentially update the state and the weight of the norm for the state space, which avoids the construction of large system equation, and retains the information of past updates. Finally, we provide numerical examples to demonstrate the proposed algorithm.
Periodic evolution of the Pearcey Gaussian beam under fractional effect
Authors: Ren Shumin , Gao Ru , Guo Teng , Wang Pengxiang , Xiao Yan
Published: July 2022

In this paper, the propagation dynamics of the Pearcey Gaussian beam modeled by the fractional Schrödinger equation in linear potential have been investigated. Different from the propagation properties of the Pearcey Gaussian beam described by the standard Schrödinger equation, the diffraction-free phenomenon which is presented under the fractional Schrödinger equation with or without linear potential, is influenced by the Lévy index. When the linear potential is considered, the periodic evolution of the Pearcey Gaussian beams is given, and results show that the transmission period is inversely proportional to the linear potential coefficient. The direction of beam propagation can also be controlled by the symbol of linear potential parameters. The propagation of incident beam with transverse wave velocity has been studied. Moreover, the chirp does not influence the evolution period of the Pearcey Gaussian beam but does influence the intensity distribution. These properties can be well implemented for promising applications of Pearcey Gaussian beams in optical manipulation and optical switches.
Coherent x-ray radiation induced by high-current breakdown on a ferrite surface
Authors: Tilikin I N , Savinov S Yu , Pestovskii N V , Pikuz S A , Tskhai S N , Shelkovenko T A , Dushkin G A
Published: July 2022

For the first time observed that at the initial stage of a high-current discharge, a low-divergence short (<2 ns) electromagnetic pulse is formed over a ferrite surface. The 50% part of the energy spectrum of this pulse lies in the region of sufficiently hard x-ray radiation (hν > 1 keV) with an energy of 0.6 mJ and an average power of 0.3 MW. The radiation propagates parallel to the surface in the anode direction with the angle divergence <2°. The high directionality of the radiation in absence of the aperture-limiting devices for the radiation beam and the quadratic dependence of the spatial radiation energy flux density on the length of working part of the ferrite prism points to the coherent nature of the observed radiation. A possible generation mechanism of the radiation is proposed. It is based on the short-lived magnetization of the ferrite plots by a high-power electromagnetic pulse and the subsequent coherent interference of unit waves irradiated by these plots.
Unravelling the magnetodielectric characteristics of strain-coupled PMN-PT/FSMA multiferroic heterojunction toward flexible MEMS applications
Authors: Arora Diksha , Kumar Pradeep , Kaushlendra Kumar , Kaur Davinder
Published: July 2022

Flexible microelectromechanical (MEMS) devices are poised to scaffold technological innovations in the fields of wearable sensors, implantable health monitoring systems and touchless human-machine interaction. Here, we report the magnetoelectric properties of cost-effective and room-temperature sensitive 0.67Pb(Mg1/3Nb2/3)O3-0.33PbTiO3/Ni50Mn35In15 (PMN-PT/ferromagnetic shape memory alloy (FSMA)) multiferroic heterostructure integrated on flexible stainless steel substrate via RF/DC magnetron sputtering technique. The growth of the pure perovskite phase of PMN-PT without any pyrochlore impurity is confirmed by the dominant (002) orientation of the tetragonal PMN-PT. The double logarithmic plot of current density with electric field validates the Ohmic conduction mechanism with low leakage current density of ∼10−6 A cm−2. The anomaly observed in temperature-dependent dielectric and ferroelectric characteristics of the heterostructure overlap with the martensite transformation regime of the bottom Ni–Mn–In (FSMA) layer. The PMN-PT/Ni–Mn–In multiferroic heterostructure exhibits a significant magnetodielectric effect of ∼3% at 500 Oe and can be used as an ultra-sensitive room-temperature magnetic field sensor. These results have been explained by an analytical model based on strain-mediated magnetoelectric coupling between interfacially coupled PMN-PT and Ni–Mn–In layers of the multiferroic heterostructure. Furthermore, the excellent retention of magnetodielectric response up to 200 bending cycles enhances its applicability towards flexible MEMS devices. Such PMN-PT based multiferroic heterostructures grown over the flexible substrate can be a potential candidate for piezo MEMS applications.
Theoretical analysis and modelling of degradation for III–V lasers on Si
Authors: Liu Jianzhuo , Tang Mingchu , Deng Huiwen , Shutts Samuel , Wang Lingfang , Smowton Peter M , Jin Chaoyuan , Chen Siming , Seeds Alywn , Liu Huiyun
Published: July 2022

InAs/GaAs quantum-dot (QD) lasers offer a promising method to realise Si-based on-chip light sources. However, the monolithic integration of III–V materials on Si introduces a high density of threading dislocations (TDs), which limits the performance of such a laser device in terms of device lifetime. Here, we proposed a kinetic model including a degradation term and a saturation term to simulate the degradation process caused by the TDs in the early stage of laser operation. By using a rate equation model, the current density in the wetting layer, where the TDs concentrate, is calculated. We compared the rate of degradation of QD lasers with different cavity lengths and of quantum-well lasers, where both are directly grown on Si substrates, by varying the fitting parameters in the calculation of current densities in the kinetic model.
Fault monitoring and diagnosis of high-pressure heater system based on improved particle swarm optimization and probabilistic neural network
Authors: Wu Zheng , Zhang Yue , Dong Ze , Li Dingshuai
Published: July 2022

The high-pressure heater system is an important part of the return heat system of thermal power units, which can significantly reduce the boiler fuel consumption and is of great significance to the safe and economic operation of the units. Taking into consideration the issues that the high-pressure heater system data has strong non-linear characteristics and the fault diagnosis accuracy is low, this paper proposes a hybrid model-based fault monitoring and diagnosis method for a high-pressure heater system. Firstly, an improved particle swarm optimization algorithm (IEDPSO) is proposed. A differential evolution operation is introduced to enhance particle diversity, and the inertia weight coefficients and learning factor parameters are improved to optimize the particle position and velocity update process. The problem that PSO tends to fall into local optimum at the late stage of iterative optimization search is solved. Numerical simulation experiments demonstrate that IDEPSO has high convergence speed and accuracy in the optimization process of the test function. Secondly, a fault monitoring and diagnosis method based on a hybrid kernel principal component analysis (KPCA)-IDEPSO-probabilistic neural network (PNN) model is proposed. Non-linear features are extracted using KPCA for fault monitoring. The IDEPSO algorithm is used to iteratively find the best PNN to improve the fault diagnosis accuracy. Simulation experiments prove that compared with the traditional PNN model, the fault diagnosis accuracy of the KPCA-IDEPSO-PNN model is improved by 4.9% and the number of fault misclassifications is reduced by 34, effectively improving the fault diagnosis accuracy of the high-pressure heater system and ensuring the safe and stable operation of thermal power units.
Micro-force sensing techniques and traceable reference forces: a review
Authors: Yang Yong , Zhao Meirong , Yinguo Huang , Zhang Hong , Guo Ning , Zheng Yelong
Published: July 2022

Micro-force measurement with high resolution, accuracy, and reliability is of interest in a broad range of applications including gravitational-wave detection, intelligent healthcare, bionic robotics, and micromanipulation. Herein, the researchand development in recent years of micro-force sensors based on various principles is reviewed thoroughly, presenting their characteristics and applications, as well as summarizing their advantages and limitations. The most indispensable component of force sensors, elastic sensitive elements, is underlined. Next, four kinds of not widely used but promising sensors are also introduced briefly. Finally, the traceable reference forces are analyzed, concluding with a future perspective into the corresponding challenges and opportunities of micro-force sensors for future research. This review aims at providing references for developing micro-force sensors and improving their performance.
Prediction of static strength properties of carbon fiber-reinforced composite using artificial neural network
Authors: Sharan Agam , Mitra Mira
Published: July 2022

In this paper, an artificial neural network (ANN) based model is developed considering the significant parameters affecting the strength properties of the fiber-reinforced composite. The model utilizes the experimental data obtained from Composite Materials Handbook, Volume 2—Polymer Matrix composites material properties (Military Handbook 17-1F). The data is extracted for unidirectional carbon fiber reinforced composite (CFRP) which represents the mean data obtained from experimentally tested specimens in batches. The dataset consists of 74 samples with eight input parameters: fiber strength, matrix strength, number of plies, loading axis, temperature, volume fraction, void percentage and thickness of ply. The output of the ANN model is the strength of the composite. The hyper-parameter of the ANN model is tuned and selected optimally. The network architecture arrived at is 8-[4]-1 with training function as Levenberg–Marquardt and activation function as tan-sigmoid in the hidden layer and pure-linear in the output layer. The agreement between the prediction from the developed model and experimental data is satisfactory, indicating the model’s applicability and efficacy. The trend analysis with respect to the input parameters is also carried out to verify that the model captures the mechanics-based behavior of CFRP.
B, P-co-doped PdCu nanothorn assemblies for enhanced oxygen reduction electrolysis
Authors: Wang Hongjing , Chen Hongyong , Yin Shuli , Mao Qiqi , Li Chunjie , Xu You , Li Xiaonian , Wang Ziqiang , Wang Liang
Published: July 2022

Nonmetal doping is a promising strategy to improve electrocatalytic performance of noble metal based catalysts for oxygen reduction reaction (ORR). Herein, we report a facile method to fabricate PdCuBP nanothorn assemblies (PdCuBP NTAs) by co-doping B and P into pre-synthesized PdCu NTAs using NaBH4and NaH2PO2as B source and P source, respectively. The metal-nonmetal structure and multi-branched morphology can optimize oxygen adsorption energy and avoid catalyst migration, agglomeration and Ostwald ripening. As such, the obtained PdCuBP NTAs exhibit efficient activity and excellent long-term stability for ORR. This research offers an excellent strategy for co-doping nonmetal elements into metal nanocrystals with controllable composition and structure to improve electrocatalytic ORR performance.
Engineering the electronic structure of Ni3FeS with polyaniline for enhanced electrocatalytic performance of overall water splitting
Authors: Zou Yang , Wu Yong-Zheng , Huang Yuan , Liu Jia-Lin , Liu Hong , Wang Jian-Jun
Published: July 2022

Developing highly efficient and stable electrocatalysts for oxygen evolution reaction is of significant importance for applications in energy conversion and storage. Modulation of electronic structure of catalysts is critical for improving the performance of the resulting electrodes. Here, we report a facile way to engineer the electronic structure of Ni3FeS by coating a thin polyaniline (PANI) layer for improving electrocatalytic activity for overall water splitting. Experimental investigations unveil that the strong electronic interactions between the lone electron pairs of nitrogen in PANI and d orbitals of iron, nickel in Ni3FeS result in an electron-rich structure of Ni and Fe, and consequently optimize the adsorption and desorption processes to promote the OER activity. Remarkably, the resulting PANI/Ni3FeS electrode exhibited much enhanced OER performance with a low overpotential of 143 mV at a current density of 10 mA·cm−2 and good stability. Promisingly, coupled with the reported MoNi4/MoO2 electrode, the two-electrode electrolyzer achieved a current density of 10 mA·cm−2 with a relatively low potential of 1.55 V, and can generate oxygen and hydrogen bubbles steadily driven by a commercial dry battery, endowed the composite electrocatalyst with high potential for practical applications.
Manipulating liquid metal flow for creating standalone structures with micro-and nano-scale features in a single step
Authors: Shastri Vijayendra , Talukder Santanu , Roy Kaustav , Kumar Praveen , Pratap Rudra
Published: July 2022

Standalone structures with periodic surface undulations or ripples can be spontaneously created upon flowing a liquid metal, e.g. Ga, over a metallic film, e.g. Pt, Au, etc, through a complex ‘wetting-reaction’-driven process. Due to the ability of 3-dimensional patterning at the small length scale in a single step, the liquid metal ‘ripple’ flow is a promising non-conventional patterning technique. Herein, we examine the effect of a few process parameters, such as distance away from the liquid reservoir, size of the liquid reservoir, and the geometry, thickness, and width of substrate metal film, on the nature of the ripple flow to produce finer patterns with feature sizes of ≤ 2 μm. The height and the pitch of the pattern decrease with distance from the liquid reservoir and decrease in the reservoir volume. Furthermore, a decrease in the thickness and width of the substrate film also leads to a decrease in the height and pitch of the ripples. Finally, the application of an external electric field also controls the ripple patterns. By optimizing various parameters, standalone ripple structures of Ga with the height and pitch of ≤ 500 nm are created. As potential applications, the ripple patterns with micro-and nano-scopic features are demonstrated to produce a diffraction grating and a die for micro-stamping.
Efficiency enhancement of triple absorber layer perovskite solar cells with the best materials for electron and hole transport layers: numerical study
Authors: Belarbi Mousaab , Zeggai Oussama , Khettaf Sami , Louhibi-Fasla Souad
Published: July 2022

In this paper, a novel perovskite solar cell (PSC) with a triple absorber layer is numerically simulated using Solar Cell Capacitance One-Dimensional software. The initial simulation of the structure (FTO/TiO2/CsSnI3/CsSnGeI3/Cs3Sb2Br9/spiro-OMeTAD/Au) reveals that by combining cesium tin triiodide (CsSnI3), cesium tin-germanium triiodide (CsSnGeI3) and cesium antimony bromide (Cs3Sb2Br9) as triple absorber layer, we obtain a higher efficiency (31.81%) than the single (CsSnI3), and double (CsSnI3/CsSnGeI3) layer structures, whose efficiencies are 12.87% and 29.41%, respectively. Then, to optimize the proposed structure, different parameters like; thicknesses of the triple absorber layer, different materials of electron transport layer (ETL) and hole transport layer (HTL), thicknesses of ETL and HTL, as well as the operating temperature have been investigated. The optimized structure (0.4/0.1/0.1 µm of CsSnI3/CsSnGeI3/Cs3Sb2Br9 as triple absorber layer; 0.1 µm of tungsten trioxide WO3 as ETL and 0.35 µm of copper(I) oxide Cu2O as HTL, as well as an optimum temperature of 300 K) shows a remarkable photovoltaic parameters i.e. J
SC = 32.640 774 mA cm−2, V
OC= 1.2442 V, FF = 89.17% and η = 36.21% (which corresponds to an improvement of 4.4% compared to the initial proposed structure (31.81%)). This study’s simulation results open a better route toward fabricating highly efficient PSCs.
Chemical sensing and actuation properties of polypyrrole coated fibers
Authors: Beregoi Mihaela , Beaumont Samuel , Jinga Sorin Ion , Otero Toribio F , Enculescu Ionut
Published: July 2022

Designing complex electrochemical artificial muscles aims towards novel devices which besides excellent actuation capabilities should also present the ability to self-sense the modification of environmental parameters. In order to improve efficiency, mimicking the structure of natural muscles, synthetic actuators should have a similar fibrillary morphology. The importance of using materials based on fiber building blocks in actuators aimed at soft robotics field was demonstrated in the present report by comparing a fibrillary artificial muscle with one based on a classical film structure. Nylon electrospun fiber meshes and films were covered in the same conditions with a thin polypyrrole (PPy) layer. The fibrillary electrospun web morphology mimics that of natural muscles and the structure performs a fast, ample bending movement in liquid electrolyte when switching an applied electric potential between −0.6 and +0.6 V. Using the same actuation conditions, no movement of a film based artificial muscle was observed. In order to check the sensing ability of both fibrillary and film like electroactive architectures, their response i.e. PPy reaction when potential cycles were applied in different concentrations of LiClO4 electrolyte were recorded. The obtained results suggest that the ion exchange of the fibrillary artificial muscle is more efficient due to its higher active surface and such devices could work also as dual device (sensor/artificial muscle).
Multiple lump molecules and interaction solutions of the Kadomtsev–Petviashvili I equation
Authors: Zhao Zhonglong , He Lingchao
Published: July 2022

In this paper, a modified version of the solution in form of a Gramian formula is employed to investigate a new type of multiple lump molecule solution of the Kadomtsev–Petviashvili I equation. The high-order multiple lump molecules consisting of M N-lump molecules are constructed by means of the Mth-order determinant and the non-homogeneous polynomial in the degree of 2N. The interaction solutions describing P line solitons radiating P of the M N-lump molecules are constructed. The dynamic behaviors of some specific solutions are analyzed through numerical simulation. All the results will enrich our understanding of the multiple lump waves of the Kadomtsev–Petviashvili I equation.
Breather and its interaction with rogue wave of the coupled modified nonlinear Schrödinger equation
Authors: Wang Ming , Xu Tao , He Guoliang , Tian Yu
Published: July 2022

We investigate the coupled modified nonlinear Schrödinger equation. Breather solutions are constructed through the traditional Darboux transformation with nonzero plane-wave solutions. To obtain the higher-order localized wave solution, the N-fold generalized Darboux transformation is given. Under the condition that the characteristic equation admits a double-root, we present the expression of the first-order interactional solution. Then we graphically analyze the dynamics of the breather and rogue wave. Due to the simultaneous existence of nonlinear and self-steepening terms in the equation, different profiles in two components for the breathers are presented.
A simple semiempirical model for the static polarizability of electronically excited atoms and molecules
Authors: Sharipov Alexander S , Pelevkin Alexey V , Loukhovitski Boris I
Published: July 2022

We present a semiempirical analytical model for the static polarizability of electronically excited atoms and molecules, which requires very few readily accessible input data, including the ground-state polarizability, elemental composition, ionization potential, and spin multiplicities of excited and ground states. This very simple model formulated in a semiclassical framework is based on a number of observed trends in polarizability of electronically excited compounds. To adjust the model, both accurate theoretical predictions and reliable measurements previously reported elsewhere for a broad range of multielectron species in the gas phase are utilized. For some representative compounds of general concern that have not yet attracted sufficient research interest, the results of our multireference second-order perturbation theory calculations are additionally engaged. We show that the model we developed has reasonable (given the considerable uncertainties in the reference data) accuracy in predicting the static polarizability of electronically excited species of arbitrary size and excitation energy. These findings can be useful for many applications, where there is a need for inexpensive and quick assessments of the static gas-phase polarizability of excited electronic states, in particular, when building the complex nonequilibrium kinetic models to describe the observed optical refractivity (dielectric permittivity) of nonthermal reacting gas flows.
Fault-tolerant finite-time dynamical consensus of double-integrator multi-agent systems with partial agents subject to synchronous self-sensing function failure
Authors: Wu Zhi-Hai , Xie Lin-Bo
Published: July 2022

This paper investigates fault-tolerant finite-time dynamical consensus problems of double-integrator multi-agent systems (MASs) with partial agents subject to synchronous self-sensing function failure (SSFF). A strategy of recovering the connectivity of network topology among normal agents based on multi-hop communication and a fault-tolerant finite-time dynamical consensus protocol with time-varying gains are proposed to resist synchronous SSFF. It is proved that double-integrator MASs with partial agents subject to synchronous SSFF using the proposed strategy of network topology connectivity recovery and fault-tolerant finite-time dynamical consensus protocol with the proper time-varying gains can achieve finite-time dynamical consensus. Numerical simulations are given to illustrate the effectiveness of the theoretical results.
The Quasar Candidate Catalogs of DESI Legacy Imaging Survey Data Release 9
Authors: He Zizhao , Li Nan
Published: July 2022

Quasars can be used to measure baryon acoustic oscillations at high redshift, which are considered as direct tracers of the most distant large-scale structures in the universe. It is fundamental to select quasars from observations before implementing the above research. This work focuses on creating a catalog of quasar candidates based on photometric data to provide primary priors for further object classification with spectroscopic data in the future, such as the Dark Energy Spectroscopic Instrument (DESI) Survey. We adopt a machine learning algorithm (Random Forest, RF) for quasar identification. The training set includes 651,073 positives and 1,227,172 negatives, in which the photometric information are from DESI Legacy Imaging Surveys (DESI-LIS) and Wide-field Infrared Survey Explore (WISE), and the labels are from a database of spectroscopically confirmed quasars based on Sloan Digital Sky Survey and the Set of Identifications & Measurements and Bibliography for Astronomical Data. The trained RF model is applied to point-like sources in DESI-LIS Data Release 9. To quantify the classifier’s performance, we also inject a testing set into the to-be-applied data. Eventually, we obtained 1,953,932 Grade-A quasar candidates and 22,486,884 Grade-B quasar candidates out of 425,540,269 sources (∼5.7%). The catalog covers ∼99% of quasars in the to-be-applied data by evaluating the completeness of the classification on the testing set. The statistical properties of the candidates agree with that given by the method of color-cut selection. Our catalog can intensely decrease the workload for confirming quasars with the upcoming DESI data by eliminating enormous non-quasars but remaining high completeness. All data in this paper are publicly available online.
A-PASS: an automated pipeline to analyze simultaneously acquired EEG-fMRI data for studying brain activities during sleep
Authors: Zou Guangyuan , Liu Jiayi , Zou Qihong , Gao Jia-Hong
Published: July 2022

Objective. Concurrent electroencephalography and functional magnetic resonance imaging (EEG-fMRI) signals can be used to uncover the nature of brain activities during sleep. However, analyzing simultaneously acquired EEG-fMRI data is extremely time consuming and experience dependent. Thus, we developed a pipeline, which we named A-PASS, to automatically analyze simultaneously acquired EEG-fMRI data for studying brain activities during sleep. Approach. A deep learning model was trained on a sleep EEG-fMRI dataset from 45 subjects and used to perform sleep stage scoring. Various fMRI indices can be calculated with A-PASS to depict the neurophysiological characteristics across different sleep stages. We tested the performance of A-PASS on an independent sleep EEG-fMRI dataset from 28 subjects. Statistical maps regarding the main effect of sleep stages and differences between each pair of stages of fMRI indices were generated and compared using both A-PASS and manual processing methods. Main results. The deep learning model implemented in A-PASS achieved both an accuracy and F1-score higher than 70% for sleep stage classification on EEG data acquired during fMRI scanning. The statistical maps generated from A-PASS largely resembled those produced from manually scored stages plus a combination of multiple software programs. Significance. A-PASS allowed efficient EEG-fMRI data processing without manual operation and could serve as a reliable and powerful tool for simultaneous EEG-fMRI studies on sleep.
Reply to Comment on ‘Egypt’s water budget deficit and suggested mitigation policies for the Grand Ethiopian Renaissance Dam filling scenarios’
Authors: Heggy Essam , Sharkawy Zane , Abotalib Abotalib Z
Published: July 2022

The reply herein shows the factual incorrectness of the comment by Eladawy, Asefa and El Nour, which is primarily supported by miscitations and misinterpretations of published research, as well as by claims from social media and unreliable TV interviews. The comment mistakenly ommit the different components of the calculated total water budget deficit in our paper and accordingly claims that it is primarily aimed to create a ‘water panic’, a term that derives from a non-quantitative and subjective reading of the abstract. We show in detail that the comment misrepresents the aim, approach, results, and interpretations reported in our original paper and does not provide any verification on the reproducibility of our results, nor offers any alternative interpretations or suggested impacts on our conclusions which remain valid and unchallenged by the above comment.
Statistical mechanics analysis of generalized multi-dimensional knapsack problems
Authors: Nakamura Yuta , Takahashi Takashi , Kabashima Yoshiyuki
Published: July 2022

Knapsack problem (KP) is a representative combinatorial optimization problem that aims to maximize the total profit by selecting a subset of items under given constraints on the total weights. In this study, we analyze a generalized version of KP, which is termed the generalized multidimensional knapsack problem (GMDKP). As opposed to the basic KP, GMDKP allows multiple choices per item type under multiple weight constraints. Although several efficient algorithms are known and the properties of their solutions have been examined to a significant extent for basic KPs, there is a paucity of known algorithms and studies on the solution properties of GMDKP. To gain insight into the problem, we assess the typical achievable limit of the total profit for a random ensemble of GMDKP using the replica method. Our findings are summarized as follows: (1) when the profits of item types are normally distributed, the total profit grows in the leading order with respect to the number of item types as the maximum number of choices per item type x
max increases while it depends on x
max only in a sub-leading order if the profits are constant among the item types. (2) A greedy-type heuristic can find a nearly optimal solution whose total profit is lower than the optimal value only by a sub-leading order with a low computational cost. (3) The sub-leading difference from the optimal total profit can be improved by a heuristic algorithm based on the cavity method. Extensive numerical experiments support these findings.