Miracle-dz/UniFAR-FTUs huggingface dataset:
Recoil-ion momentum distribution for nonsequential double ionization of Xe in intense midinfrared laser fields

We experimentally investigate the recoil-ion momentum distribution along the laser polarization direction for nonsequential double ionization of Xe by 50 fs, 2400 nm laser pulses at intensities of $(22\ensuremath{-}68) \mathrm{TW}/{\mathrm{cm}}^{2}$. The observed doubly charged ion momentum distribution exhibits a distinct transition from a flat-top structure near zero longitudinal momentum at $22\phantom{\rule{0.16em}{0ex}}\mathrm{TW}/{\mathrm{cm}}^{2}$ to the one with two maxima at nonzero longitudinal momentum at $37\phantom{\rule{0.16em}{0ex}}\mathrm{TW}/{\mathrm{cm}}^{2},\phantom{\rule{4pt}{0ex}}52\phantom{\rule{0.16em}{0ex}}\mathrm{TW}/{\mathrm{cm}}^{2}$, and $68\phantom{\rule{0.16em}{0ex}}\mathrm{TW}/{\mathrm{cm}}^{2}$, which is remarkably different from the case of 800 nm. Simulation based on a semiclassical model is used to obtain the ratios of contributions from the recollision-impact ionization (RII) and the recollision-induced excitation with subsequent field ionization (RESI) in nonsequential double ionization. Our calculation reveals that the increasing contribution of the RII channel is responsible for the more prominent double-hump structure at longer wavelength or higher laser intensity. Moreover, a simple fitting based on the calculated ratios allows one to reproduce the experimental ion momentum distributions well and obtain contributions from these two channels.
THE NUMBER OF GENERATORS OF THE ALGEBRA OF KAHLER DIFFERENTIALS

where I i s the kernel of the multiplication A A —»-A. The purpose of this paper i s to find lower bounds for the number of generators of (A) . In particular we show that for most a lgebras of r ea l continuous functions the cardinal of any set of generators of i ? ^(A) i s at least that of the rea l numbers. This i s in contrast to the A-module of derivations of A in A, Der_ (A ,A) , which i s the dual of K i? ^(A) and i s zero for A Cp(X) (a lgebra of rea l continuous functions on any topological space X ) .
Joint Power Allocation and 3D Deployment for UAV-BSs: A Game Theory Based Deep Reinforcement Learning Approach

Ultra-dense unmanned aerial vehicle (UAV) plays an important role in the field of communications due to its flexibility and low-cost feature. Ultra-dense unnamed aerial vehicle base station (UAV-BS) can improve communication quality by providing temporary and cost-effective wireless communication services for hotspots. In this paper, a multiple UAV-BSs assisted downlink network is investigated to maximize the system throughput. It is still a challenging problem to jointly optimize the power allocation and the 3D deployment of multiple UAV-BSs. Therefore, in this paper, for effective interference management, the power allocation problem is first formulated as a non-cooperative game with a pricing mechanism to imitate the interactions among users served by UAV-BSs. Then, based on the combination of deep reinforcement learning (DRL) and the game theory, the power allocation and the 3D deployment of UAV-BSs are transformed into a Markov decision problem. Finally, a novel price-based proximal policy optimization (3PO) algorithm is proposed to explore the optimal policy to maximize the system throughput. Simulation results reveal that the proposed 3PO algorithm can significantly improve system throughput and energy efficiency compared to other baselines by jointly optimizing power allocation and 3D deployment for UAV-BSs.
Use of Binary Sigmoid Function And Linear Identity In Artificial Neural Networks For Forecasting Population Density

Artificial Neural Network (ANN) is often used to solve forecasting cases. As in this study. The artificial neural network used is with backpropagation algorithm. The study focused on cases concerning overcrowding forecasting based District in Simalungun in Indonesia in 2010-2015. The data source comes from the Central Bureau of Statistics of Simalungun Regency. The population density forecasting its future will be processed using backpropagation algorithm focused on binary sigmoid function (logsig) and a linear function of identity (purelin) with 5 network architecture model used the 3-5-1, 3-10-1, 3-5 -10-1, 3-5-15-1 and 3-10-15-1. Results from 5 to architectural models using Neural Networks Backpropagation with binary sigmoid function and identity functions vary greatly, but the best is 3-5-1 models with an accuracy of 94%, MSE, and the epoch 0.0025448 6843 iterations. Thus, the use of binary sigmoid activation function (logsig) and the identity function (purelin) on Backpropagation Neural Networks for forecasting the population density is very good, as evidenced by the high accuracy results achieved.
Multiple model adaptive control for a class of nonlinear systems with unknown control directions

ABSTRACT This study introduces an improved multiple model adaptive control (MMAC) algorithm for a class of nonlinear discrete-time systems. The controller consists of a linear direct adaptive controller, a neural network-based nonlinear direct adaptive controller and a switching mechanism. The assumption of the nonlinear term is relaxed by incorporating a parameter estimator with an augmented error. The control direction of the system is not required to be known by employing a linear direct adaptive controller with the discrete Nussbaum gain and future output predictions. The stability of the closed-loop systems applying the proposed MMAC method is proved and the improved transient performance of the system is illustrated by the simulation results.
Field Theory with Fourth-order Differential Equations

We introduce a new class of higgs type fields $\{U,U^{\mu},U^{\mu\nu}\}$ with Feynman propagator $\thicksim 1/p^4$, and consider the matching to the traditional gauge fields with propagator $\thicksim 1/p^2$ in the viewpoint of effective potentials at tree level. With some particular restrictions on the convergence, there are a wealth of potential forms generated by the fields $\{U,U^{\mu},U^{\mu\nu}\}$, such as: (1) in the case of $U$ coupled to the intrinsic charges of matter fields, electromagnetic Coulomb potential with an extra linear potential and Newton's gravitation could be generated with the operators of different orders from the dynamics of $U$, respectively; (2) for the matter fields, with the multi-vacuum structure of a sine-Gordon type vector field $A^{\mu}$ induced from $U$, a seesaw mechanism for gauge symmetry and flavor symmetry of fermions could be generated, in which the heavy fermions could be produced; besides, by treating the fermion current as a field, a possible way for renormalizable gravity could be proposed; (3) the Coulomb potential in electromagnetism and gravitation could be generated by an anti-symmetric field strength of $U^{\mu}$, when it's coupled to the intrinsic charge and momentum of matter fields, respectively; and, except for the Coulomb part in each case, there is a linear and a logarithmic part in the former case which might correspond to the confinement in strong QED, while there is a linear and a logarithmic part in the latter case which might correspond to the dark energy effects in the impulsive case and dark matter effects in the attractive case, respectively; besides, a symmetric field strength of $U^{\mu}$ could also generate the same gravitation form as the anti-symmetric case; (4) a nonlinear version Klein-Gordon equation, QED and the Einstein's general relativity, could be generated as a low energy approximation of the dynamics of $U$, $U^{\mu}$ and $U^{\mu\nu}$, respectively; moreover, in the weak field case, the gauge symmetry could superficially arise, and, a linear QED, linear gravitation and a 3rd-order tensor version QED could be generated by relating the field strength of $U$, $U^{\mu}$ and $U^{\mu\nu}$ to the corresponding gauge fields, respectively; (5) for the massive $\{U, U^{\mu}\}$, attractive potentials for particles with the same kind of charges could be generated, which might serve as candidate for interactions maintaining the s-wave pairing and d-wave pairing Cooper pairs in superconductors, with electric charge in the $U$ case and magnetic moment in the $U^{\mu}$ case as interaction charge, respectively; etc.
A robust momentum closure approach for multiphase computational fluid dynamics applications

Multiphase computational fluid dynamics (M-CFD) modeling approaches allow for the prediction of critical three-dimensional thermal-hydraulics phenomena in nuclear reactor applications. The advancement and consistent adoption of such tools could transform the industry's approach to the design of reliable systems, and the efficient operation of systems existing, which in the past have been dependent upon correlation-based sub-channel analysis codes. The success of these M-CFD methods in simulating two-phase flow and boiling heat transfer depends on their demonstrated accuracy and robustness, which signals a dual need for the comprehensive analysis of existing data and a reevaluation of the underlying physics. By virtue of the Eulerian-Eulerian two-fluid approach, additional terms manifest in the M-CFD phase momentum equations, which represent information that has been lost, and require closure through prescription of interfacial force models. These momentum "closures" are vital to M-CFD prediction of mean flow profiles, including void fraction and phase velocity distributions, and require high-resolution, robust models to perform accurately throughout a diverse array of flow conditions. While an overwhelming number of models have been developed with a wide range of varying performance, no consensus exists about how to assemble these models successfully in a CFD framework, suggesting that their predictive power is still limited. The lift force, responsible for lateral void fraction redistribution, is particularly refractory to the development of a consistent modeling strategy for these closures. Historically, CFD approaches have been forced to inconsistently leverage existing models derived for single bubbles in laminar flow, which disregard the complex dynamics and interactions of bubbles with turbulence and bubble wakes. Current understanding of the lift force in turbulent flow has been limited to qualitative evidences that small spherical bubbles experience a positive lift, resulting in a wall-peaked void fraction distribution, while larger deformed bubbles experience a negative lift and corresponding center-peaked profile. The present work brings forward a new physical interpretation of the lift force in turbulent bubbly flow through a synthesis of information from DNS studies, fine and coarse scale experiments, and analytical investigations. To overcome the limitations of previous models, a simple dimensionless quantity, the Wobble number, a number which systematically describes the unsteady behavior of bubbles in turbulent flow conditions, is proposed. Introducing this dependency into the lift formulation allows for precise identification of lift inversion, which alone exceeds capabilities of existing models. Additionally, the model is extended to account for group behavior with the introduction of a swarm-like function based on void fraction. Its formulation is built on the conceptual understandings of drift phenomena, bubble interaction probability, and the maximum packing factor for dispersed bubbly flow. These…
Full Eulerian deformable solid‐fluid interaction scheme based on building‐cube method for large‐scale parallel computing

We propose a full Eulerian incompressible solid‐fluid interaction scheme capable of achieving high parallel efficiency and easily generating meshes for complex solid geometries. While good scalability of a full Eulerian solid‐fluid interaction formulation has been reported by Sugiyama et al, their analysis was carried out using uniform Cartesian mesh and an artificial compressibility method. Typically, it is more challenging to achieve good scalability for hierarchical Cartesian meshes and a fully incompressible formulation. In addition, the conventional full Eulerian methods require a large computational cost to resolve complex solid geometries due to the usage of uniform Cartesian meshes. In an attempt to overcome the aforementioned issues, we employ the building‐cube method, where the computational domain is divided into cubic regions called cubes. Each cube is divided at equal intervals, the same number of cubes is assigned to each core, and the spatial loop processing is executed for each cube. The numerical method is verified by computing five numerical examples. In the weak scaling test, the parallel efficiency at 32768 cores with 32 cores as a reference is 93.6%. In the strong scaling test, the parallel efficiency at 32768 cores with 128 cores as a reference is 70.2%.
Low RCS and broadband metamaterial-based low-profile antenna using PCM

In this study, a novel cross layout of polarisation conversion metamaterial (PCM) is investigated for the first time. Based on the principle of phase cancellation, the cross structure can reduce radar cross section (RCS) significantly over a wider band compared with the chessboard configuration. The low-profile metamaterial-based antenna is composed of the cross PCM structure and a driven patch sandwiched between the PCM patches and the ground plane. Simulated and measured results show that compared with the microstrip patch antenna, the proposed antenna can achieve a wider impedance bandwidth of 6.05-7.52 GHz (21.7%) and milder gain variation in the working band, while the monostatic RCS can be reduced over 5.8-18.0 GHz (102.5%).
THE EVALUATION OF VIRTUAL TUTORING IN AN ENGLISH DEGREE BEFORE AND DURING COVID-19

: This research presents results of the evaluation of virtual tutoring before and during COVID-19 at the higher level. The objective of this research is to document the points of view of the tutors and tutees of the Bachelor’s program in English virtual mode through a SWOT study to evaluate the tutoring program in the Bachelor’s Degree in English (LI) virtual modality. The research questions are: How are virtual tutoring being delivered? , What are the strengths of virtual tutoring? , and What are the weaknesses of virtual tutoring? , Has virtual tutoring improved during the COVID-19 pandemic? A mixed methodology was contemplated. In the qualitative part, the current situation of virtual tutoring is described and interpreted, and the points of view of tutors, tutees and the coordination of Tutoring are reflected. In addition, the quantitative information was obtained through the application of questionnaires applied with Google forms and data analyzed with the SSPSS program. The opinion of ten virtual tutors before the pandemic and 7 virtual tutors during the pandemic, and 27 students with an initial, intermediate, and final school trajectory, and two tutors within the tutoring coordination (PAT) at the School of Languages were considered. The research considers two moments, the first before the Covid-19 pandemic in 2019 and the second during the pandemic considers the entire year of 2020 and the first half of 2021. Finally, reflections and suggestions are presented for the improvement of virtual tutoring.
Regional Forecasting of Wind Speeds during Typhoon Landfall in Taiwan: A Case Study of Westward-Moving Typhoons

Taiwan is located on a route where typhoons often strike. Each year, the strong winds accompanying typhoons are a substantial threat and cause significant damage. However, because the terrains of high mountains in Taiwan vary greatly, when a typhoon passes the Central Mountain Range (CMR), the wind speed of typhoons becomes difficult to predict. This research had two primary objectives: (1) to develop data-driven techniques and a powerful artificial neural network (ANN) model to predict the highly complex nonlinear wind systems in western Taiwan; and, (2) to investigate the accuracy of wind speed predictions at various locations and for various durations in western Taiwan when the track of westward typhoons is affected by the complex geographical shelters and disturbances of the CMR. This study developed a typhoon wind speed prediction model that evaluated various typhoon tracks (covering Type 2, Type 3, and Type 4 tracks, as defined by the Central Weather Bureau), and evaluated the prediction accuracy at Hsinchu, Wuqi, and Kaohsiung Stations in western Taiwan. Back propagation neural networks (BPNNs) were employed to establish wind speed prediction models, and a linear regression model was adopted as the benchmark to evaluate the strengths and weaknesses of the BPNNs. The results were as follows: (1) The BPNNs generally had favorable performance in predicting wind speeds and their performances were superior to linear regressions; (2) when absolute errors were adopted to evaluate the prediction performances, the predictions at Hsinchu Station were the most accurate, whereas those at Wuqi Station were the least accurate; however, when relative errors were adopted, the predictions at Hsinchu Station were again the most accurate, whereas those at Kaohsiung were the least accurate; and, (3) regarding the relative error rates for the maximum wind speed of Types 2, 3, and 4 typhoons, Wuqi, Kaohsiung, and Wuqi had the most accurate performance, respectively; as for maximum wind time error (ETM) for Types 2, 3, and 4 typhoons, Kaohsiung, Wuqi, and Wuqi correspondingly performed the most favorably.
Climate Potential for Apple Growing in Norway—Part 1: Zoning of Areas with Heat Conditions Favorable for Apple Growing under Observed Climate Change

Agricultural production is already, and obviously, affected by climate change. Adapting to climate change includes reducing future risks to ensure yield quality and quantity and considers seizing any potential opportunities induced by climate change. In higher latitude areas, such as Norway, cold climate limits the cultivation of fruits. An increase in temperature offers more favorable conditions for fruit production. In this study, using available phenological observations (full blooming) and harvest dates, and meteorological data from the experimental orchard of NIBIO Ullensvang, the minimum heat requirements for growing different apple varieties are determined. Those criteria are used for zoning of the areas with heat favorable conditions for apple growing. Data on six varieties were used, with lower and higher requirements for heat for fruit development (Discovery, Gravenstein, Summerred, Aroma, Rubinstep, and Elstar). High resolution daily temperature data were generated and used for zoning of the areas with heat favorable conditions for apple growing within the selected domain, which includes Western Norway, Southern Norway, Eastern Norway, and the western part of Trøndelag, Mid-Norway. Dynamics of the change in such surfaces was assessed for the period of 1961–2020. The total surface with favorable heat conditions for growing the varieties with lesser requirement for heat increased three times during this period. The growing of more heat-demanding varieties increased from near zero to about 2.5% of the studied land surface. In the period of 2011–2020, surface area with favorable heat conditions for apple growing was almost 27,000 km2, and a surface area of about 4600 km2 can sustain growing of more heat-demanding varieties. The presented results show the increasing potential of the climate of Norway for apple cultivation and highlight the importance of implementation of fruit production planned according to climate change trends, including the assessment of potential risks from climate hazards. However, the methodology for determining heat requirements can be improved by using phenological ripening dates if available, rather than harvest dates which are impacted by human decision. Zoning of areas with the potential of sustainable apple growing requires the use of future climate change assessments and information on land-related features.
Quadrotor Control Via Robust Generalized Dynamic Inversion and Adaptive Non‐Singular Terminal Sliding Mode

A robust two‐loops structured control system design for quadrotor's position/attitude trajectory tracking is proposed. The aim of the outer loop is to provide the roll/pitch tilting commands to the inner loop, which in turns generates the tilting angles that control the quadrotor's center of gravity in the horizontal plane. The outer loop utilizes Robust Generalized Dynamic Inversion (RGDI) of a prescribed asymptotically stable differential equation in the deviation function of the horizontal position coordinates from their reference trajectories. The inner loop employs an Adaptive Non‐singular Terminal Sliding Mode (ANTSM) to control the tilting angles, in addition to controlling the yaw attitude angle and the vertical position coordinate. The proposed scheme solves the singularity avoidance problems of generalized inversion and terminal sliding mode control. The stability of outer and inner loop is ensured by utilizing positive definite Lyapunov energy function for stable tracking performance against parametric variations and bounded unknown external disturbances. Numerous simulations are conducted on a six Degrees of Freedom (DoF) quadrotor model in the presence of parametric variations, un modeled dynamics, and external disturbances.
Impact of Television Advertisement on Children

Advertising is second only to films as far as its influence on the society is concerned. Advertising is the most influential and powerful medium in the present commercial society. The main objective of this study is to find out, how children are influenced by the television advertisements. There are both good and bad impact of advertisement. An attempt has been made to know the children's awareness about advertised products and its impact on children behaviour towards them. Descriptive research design was used as the study followed structured design with predetermined objectives & hypotheses. Primary data have been collected though questionnaire. Chi-square test and Correlation was carried out to test the hypotheses. The study comes out with useful insights and recommendations.
SWIPT-Aided Device-to-Device Communications for Massive IoT Networks: A Novel Resource Allocation With Sparse Code Multiple Access

Spectral efficiency (SE) and energy efficiency (EE) are crucial for next-generation wireless Internet of Things networks. Device-to-device (D2D) communications and sparse code multiple access (SCMA) are promising solutions to meet the high Quality of Service. This requires a proper interference management for an ultradense user system. Considering both resource and power allocation, we herein aim to optimize the SE and improve the EE. First, rate fairness is considered to assign SCMA codewords to both cellular and D2D users. Subsequently, we propose a beamforming design and power allocation algorithm for D2D communications underlaying downlink and uplink operation of cellular networks, wherein energy harvesting is involved as a simultaneous wireless information and power transfer to assist an SCMA network.
Analysing parking search ('cruising') time using generalised multilevel structural equation modelling

The aim of this paper is to identify factors influencing parking search (cruising) time. A revealed-preference on-street parking survey was undertaken with individual drivers in four UK cities to investigate the influence of personal, trip, socio-economic, physical, time-related, and price-related variables on parking search. In order to address the potential endogeneity problems between the factors (e.g. parking fee and parking search time) and hierarchical issues in the survey data, a generalised multilevel structural equation model was applied. It was revealed that cruising time could be reduced by seeking drivers to pay for parking as a way of improving social welfare.