Miracle-dz/UniFAR-FTUs huggingface dataset:
The kinematics and surface mass density in the solar neighbourhood using TGASxRAVE

Abstract We investigate the kinematics of stars in the Solar neighbourhood by combining radial velocities from the latest data release of the RAVE survey with the Tycho-Gaia Astrometric Solution presented in Gaia Data Release 1. We use moments of the velocity distribution to characterise the kinematics over a radial distance range of 6-10 kpc and up to 1 kpc away from the plane. Our ultimate goal is to use these to put new constraints on the (local) distribution of mass using the Jeans Equations.
Electrons in Molecules: From Basic Principles to Molecular Electronics.

This article reviews Electrons in Molecules: From Basic Principles to Molecular Electronics. by Jean-Pierre Launay, Michel Verdaguer 509 pp. , Oxford, UK, 2014. Price: $89.95 (hardcover). ISBN 978-0-19-929778-8.
Gold Nanoparticle-Based Microfluidic Chips for Capture and Detection of Circulating Tumor Cells

Liquid biopsy has progressed to its current use to diagnose and monitor cancer. Despite the recent advances in investigating cancer detection and diagnosis strategies, there is still a room for improvements in capturing CTCs. We developed an efficient CTC detection system by integrating gold nanoparticles with a microfluidic platform, which can achieve CTC capture within 120 min. Here, we report our development of a simple and effective way to isolate CTCs using antibodies attached on gold nanoparticles to the surface of a lateral filter array (LFA) microdevice. Our method was optimized using three pancreatic tumor cell lines, enabling the capture with high efficiency (90% ± 3.2%). The platform was further demonstrated for isolating CTCs from patients with metastatic pancreatic cancer. Our method and platform enables the production of functionalized, patterned surfaces that interact with tumor cells, enhancing the selective capture of CTCs for biological assays.
A class of predefined-time stable dynamical systems

This article introduces predefined-time stable dynamical systems which are a class of fixed-time stable dynamical systems with settling time as an explicit parameter that can be defined in advance. This concept allows for the design of observers and controllers for problems that require to fulfil hard time constraints. An example is encountered in the fault detection and isolation problem, where mode detection in a timely manner needs to be guaranteed in order to apply a recovery action. Furthermore, through the notion of strong predefined-time stability, the approach hereinafter presented permits to overcome the problem of overestimation of the convergence time bound encountered in previous methods for the analysis of finite-time stable systems, where the stabilization time is often an unbounded function of the initial conditions of the system. A Lyapunov analysis is provided together with a detailed discussion of the applications to consensus and first order sliding mode controller design.
Performance of BARI-released gladiolus varieties under the climatic conditions of young Brahmaputra and Jamuna floodplain

The experiment was conducted in the farmers’ field at the Farming System Research and Development site (FSRD), Atia, Delduar, Tangail during the Rabi season of 2018-19 and 2019-20 to evaluate the performance of BARI released gladiolus varieties and popularize these varieties among the farmers of Tangail region. BARI developed three varieties of gladiolus, namely BARI Gladiolus-3, BARI Gladiolus-4, and BARI Gladiolus-5. Among the three varieties, BARI Gladiolus-4 performed the best in terms of the spike (191009 piece ha-1) and corm (254322 piece ha-1) production from the average of 2018-19 and 2019-20. Though BARI Gladiolus-4 performed the best in terms of yield, the maximum economic return was obtained from BARI Galdiolus-5 due to a higher spike in demand and market price compared to the other two varieties. The highest gross return (Tk.2406215 ha-1), gross margin (Tk. 1402546 ha-1), as well as BCR (2.40), were also recorded in BARI Gladiolus-5 followed by BARI Gladiolus-4. The lowest gross return (Tk. 1837608 ha-1), gross margin (Tk. 833939 ha-1) as well as BCR (1.83), were obtained from BARI Gladiolus-3. The farmers under the AEZ-8 areas can become economically benefitted by the production of BARI Gladiolus-5 and BARI Gladiolus-4. Bangladesh J. Agri. 2023, 48(1): 10-18
Stability Behaviour of Shells and Imperfection Sensitivity by the Asymptotic Numerical Method

This paper is concerned with stability behaviour and imperfection sensitivity of thin elastic shells. The aim is to determine the reduction of the critical buckling load as a function of the imperfection amplitude. For this purpose, the direct calculation of the so-called fold line connecting all the limit points of the equilibrium branches when the imperfection varies is performed. This fold line is the solution of an extended system demanding the criticality of the equilibrium. The Asymptotic Numerical Method is used as an alternative to Newton-like incremental-iterative procedures for solving this extended system. It results in a very robust and efﬁcient path-following algorithm that takes the singularity of the tangent stiffness matrix into account. A modern and efﬁcient ﬁnite shell element is considered for the discretization. The underlying shell theory uses the EAS concept. It allows ﬁnite rotations as well as thickness stretch. A numerical example involving a shape imperfection is presented.
Privacy‐preserving distributed projected one‐point bandit online optimization over directed graphs

The distributed online optimization (DOO) problem with privacy‐preserving properties over multiple agents is considered in this paper, where the network model is built by a strongly connected directed graph. To solve this problem, a stochastic bandit DOO algorithm based on differential privacy is proposed. This algorithm uses row‐ and column‐stochastic matrix as the weighting matrices, the requirement of the double random weighting matrix is released. To handle the unknown objective function, the one‐point bandit is used to estimate the true gradient information, and the estimated gradient information is used to update of decision variables. Different from the existing DOO algorithms that ignore privacy issues, this algorithm successfully protects the privacy of nodes through a differential privacy policy. Theoretical results show that the algorithm can not only achieve sublinear regret bounds but also protect the privacy of nodes. Finally, simulation results verify the effectiveness of the algorithm.
A Combined 2D–3D Object Detection Framework

ABSTRACT As a key step of video surveillance, motion detection attracts the attention of the scientific community. Detection and labelling dynamic objects are addressed in this paper. We cope with sudden illumination changes, the presence of shadow and partial occlusions. The main contribution of this work is the use of data: RGB image coming from an HD camera and depth coming from a Kinect, contour, movement resulting from the temporal inter frame difference and optical flow. The proposed 2D–3D combination achieves complete detection of moving objects. We carried out an experimental evaluation of the proposed approach on challenging dynamic scenes; we notice an increase in detection rate.
Prediction of anti‐HIV activity on the basis of stacked auto‐encoder

The prediction of biologically active compounds plays a very important role for high‐throughput screening approaches in drug discovery. Most computational models, in this area, concentrate on measuring structural similarities between chemical elements. There are various methods to predict anti‐HIV activity, such as artificial neural network and support vector machine, but generally using shallow machine learning with low accuracies and less samples. In this work, one of deep learning methods, stacked auto‐encoder (SAE), is proposed to predict anti‐HIV activity of a broad group of compounds for the first time. Through contrasting experiments of artificial neural network, support vector machine, and SAE under the same condition, the accuracy after descriptors screening is higher than using raw descriptors, and SAE performs better than the other two methods to achieve the perfect forecast of anti‐HIV activity. It has a great significance on promoting anti‐HIV drug design, which therefore can reduce research and development costs and improve the efficiency of anti‐HIV drug discovery.
Effects of a Simple Convective Organization Scheme in a Two‐Plume GCM

A set of experiments is described with the Community Atmosphere Model (CAM5) using a two‐plume convection scheme. To represent the differences of organized convection from General Circulation Model (GCM) assumptions of isolated plumes in uniform environments, a dimensionless prognostic “organization” tracer Ω is invoked to lend the second plume a buoyancy advantage relative to the first, as described in Mapes and Neale (2016). When low‐entrainment plumes are unconditionally available (Ω = 1 everywhere), deep convection occurs too easily, with consequences including premature (upstream) rainfall in inflows to the deep tropics, excessive convective versus large‐scale rainfall, poor relationships to the vapor field, stable bias in the mean state, weak and poor tropical variability, and midday peak in diurnal rainfall over land. Some of these are shown to also be characteristic of CAM4 with its separated deep and shallow convection schemes. When low‐entrainment plumes are forbidden by setting Ω = 0 everywhere, some opposite problems can be discerned. In between those extreme cases, an interactive Ω driven by the evaporation of precipitation acts as a local positive feedback loop, concentrating deep convection: In areas of little recent rain, only highly entraining plumes can occur, unfavorable for rain production. This tunable mechanism steadily increases precipitation variance in both space and time, as illustrated here with maps, time‐longitude series, and spectra, while avoiding some mean state biases as illustrated with process‐oriented diagnostics such as conserved variable profiles and vapor‐binned precipitation curves.
Nonlocal suppression of Biermann battery magnetic-field generation for arbitrary atomic numbers and magnetization

The Biermann battery term of magnetohydrodynamics (MHD) generates a magnetic field where electron density gradients and electron temperature gradients are perpendicular to one another. Kinetic simulations and experiments have shown that the rate of magnetic-field generation is lower than Biermann when the electron mean free path becomes comparable to or greater than the temperature gradient scale length, known as the nonlocal regime. We investigate the nonlocal suppression of the Biermann term using simplified Fokker–Planck simulations covering a wide range of parameters. We provide the first fit for nonlocal Biermann suppression that has physically accurate behavior for small and large values of a suitable nonlocality parameter, valid for an arbitrary atomic number, and that includes the effect of magnetization on nonlocality. The fit is intended to provide an approximate method to account for reduced magnetic-field generation in MHD codes and theory.
Contour sensitive saliency and depth application in image retargeting

Image retargeting technique requires important information preservation and less edge distortion during increasing/decreasing image size. The major existed content-aware methods perform well. However, there are two problems should be improved: the slight distortion appeared at the object edges and the structure distortion in the nonsalient area. According to psychological theories, people evaluate image quality based on multi-level judgments and comparison between different areas, both image content and image structure. The paper proposes a new standard: the structure preserving in non-salient area. After observation and image analysis, blur (slight blur) is generally existed at the edge of objects. The blur feature is used to estimate the depth cue, named blur depth descriptor. It can be used in the process of saliency computation for balanced image retargeting result. In order to keep the structure information in nonsalient area, the salient edge map is presented in Seam Carving process, instead of field-based saliency computation. The derivative saliency from x- and y-direction can avoid the redundant energy seam around salient objects causing structure distortion. After the comparison experiments between classical approaches and ours, the feasibility of our algorithm is proved.
COEXISTENCE OF REGIONS OF EQUILIBRIUM AND NON-EQUILIBRIUM TWO-POINT TURBULENCE DYNAMICS IN GRID-GENERATED TURBULENCE BOTH WITH -5/3 SPECTRA BUT DIFFERENT UNDERLYING PHYSICS

In this paper we present results concerning the spatial development of energy spectra E11( f ) and their associated integral and Taylor scales in conjunction with the spatial developments of vorticity, strain and production rates of vorticity and strain obtained from Direct Numerical Simulations of spatially developing grid-generated turbulence. We use a fractal square grid and a single mesh grid where the mesh is similar to the largest square on the fractal square grid. We find two adjacent but physically different regions in these flows relatively close to the grid: one where the Q-R diagram has not yet formed its well-known, presumed universal, tear-drop shape (Tsinober (2009)) but E11( f ) ∼ f−5/3 over more than a decade of a frequency range which is set by inlet conditions rather than Kolmogorov scalings: and one where theQ-R diagram immediately adopts the well-known tear-drop shape and E11( f ) ∼ f−5/3 over a Kolmogorov range of frequencies which increases as the local Reynolds number increases. In the one case with the higher local Reynolds numbers, the first region gives rise, as one moves downstream, to the non-equilibrium behaviour Cε ∼ 1/Reλ whilst the second region leads to Cε =Const.
Intermediate states and structure evolution in the free-falling process of the dislocation in graphene

Abstract This paper investigated the intermediate states and the structure evolution of the dislocation in graphene when it falls freely from the saddle point of the energy landscape. The O-type dislocation, an unstable equilibrium structure located at the saddle point, is obtained from the lattice theory of the dislocation structure and improved by the ab initio calculation to take the buckling into account. Intermediate states along the kinetics path in the falling process are obtained from the ab initio simulation. Once the dislocation falls from the saddle point to the energy valley, this O-type dislocation transforms into the stable structure that is referred to as the B-type dislocation, and in the meantime, it moves a distance that equals half a Burgers vector. The structure evolution and the energy variation in the free-falling process are revealed explicitly. It is observed that rather than smooth change, a platform manifests itself in the energy curve. The unusual behaviour in the energy curve is mainly originated from symmetry breaking and bond formation in the dislocation core. The results can provide deep insight in the mechanism of the brittle feature of covalent materials.
Folded single-layer 8 × 8 Butler matrix

Abstract A concept of an 8 × 8 Butler matrix realized in a single-layer structure folded to create a cylindrical surface has been proposed. With the use of such a structure it is possible to eliminate crossovers and to reduce losses within a circuit by maintaining connecting lines as short as possible. The proposed concept has been experimentally verified by simulations and measurements of an 8 × 8 Butler matrix operating at 2.5 GHz.
ADAPTION OF INDUSTRIAL NDT PROTOCOLS BASED ON ACTIVE INFRARED THERMOGRAPHY TO THE ART CONSERVATION WORLD: THE CASE OF THE WALL PAINTING AT HERODIUM

Abstract. Salt weathering is one of the most detrimental agents in the deterioration of historic wall paintings. Unfortunately, it is most noticeable once it reaches the surface, and the damage has already been done. Its elusive nature and its integration into the historic structures make it difficult to accurately detect soluble salts at the sub surfaces of wall painting non-destructively. Detailed detection in a delicate artifact such as wall paintings requires custom methodology. The study's case study is the wall painting in Herodium. The wall paintings were severely damaged by salt weathering. Although great efforts were invested in restoring and protecting the paintings their state is still unstable. This study offers a new perspective on the matter utilizing the adaption of industrial protocols based on active Infrared thermography (IRT) with data processing via thermographic signal reconstruction (TSR). The study's primary goal was to optimize the inspection methodology and assist the conservation process with knowledge of soluble salt hazards hidden at the subsurface.
Formules de Jensen en plusieurs variables et applications arithmétiques

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Spectral Ergodicity in Deep Learning Architectures via Surrogate Random Matrices.

In this work a novel method to quantify spectral ergodicity for random matrices is presented. The new methodology combines approaches rooted in the metrics of Thirumalai-Mountain (TM) and Kullbach-Leibler (KL) divergence. The method is applied to a general study of deep and recurrent neural networks via the analysis of random matrix ensembles mimicking typical weight matrices of those systems. In particular, we examine circular random matrix ensembles: circular unitary ensemble (CUE), circular orthogonal ensemble (COE), and circular symplectic ensemble (CSE). Eigenvalue spectra and spectral ergodicity are computed for those ensembles as a function of network size. It is observed that as the matrix size increases the level of spectral ergodicity of the ensemble rises, i.e., the eigenvalue spectra obtained for a single realisation at random from the ensemble is closer to the spectra obtained averaging over the whole ensemble. Based on previous results we conjecture that success of deep learning architectures is strongly bound to the concept of spectral ergodicity. The method to compute spectral ergodicity proposed in this work could be used to optimise the size and architecture of deep as well as recurrent neural networks.
Design and optimisation of direct-driven PM variable-flux synchronous generators for directly grid-connected slip-synchronous wind-turbines

This dissertation presents design, optimisation and prototype tests of radial-flux, low-speed, permanent magnet (PM) and copper excited, synchronous generators with a new topology. The designed generators are for use in direct-drive directly grid-connected slip-synchronous wind-turbine systems. For direct-drive systems, (PM) generators deployment is more attractive due to the convenience of high-energy permanent magnet types for example NdFeB.Thus, replacing conventional PM synchronous generators with PM variable flux synchronous generators (PM VFSGs) has recently gained great interest. PM VFSG ( have some rotor windings, which result in a flux variation capability and therefore they give better performance in grid compliance than purely PM excited SGs. In addition, they offer better efficiency and reduced mass when compared to purely electrically excited synchronous generators (EESGs). Using analytical and FEM analysis, the PM VFSG design with non-overlap concentrated windings was carried out applying three optimisation algorithms, i.e. modified method of feasible direction (MMFD), non-sorted genetic algorithm (NSGA II) and particle swarm optimisation (PSO). Using simplified equivalent magnetic circuit and PM properties, an initial iterative preliminary design for the proposed generator was carried out. The rotor field coil analysis was performed using FE analysis in MagNet solver to numerically evaluate four generator designs from a benchmarked surface-PM VFSG calculated analytically. The aim of the electromagnetic analysis is to satisfy a grid compliance design, where flux variation is necessary. The rotor design values changes depending on the amount of magneto-motive force (MMF) required, supplied by magnets and rotor field coils. From the analysed rotor designs, it was found that the rotor slot area is a key constraining factor. Another key outcome of the study is that the location of the PMs on/in the rotor tooth influences the flux linked to the stator . The rotor design corresponding to the lowest rotor copper losses was adopted. The optimisation procedure uses d−q analysis at steady state and no-load, to investigate the size, efficiency and active mass of 13 kW, 100 kW and 1 MW generators with a base winding of 34/36. The buried-PM topology is found to achieve the least mass and highest efficiency. The outer diameters of the optimised generators have marginal difference with other conventional systems. Compared with other direct drive generator systems, the proposed generator has a larger air-gap diameter and heavier rotor but with comparable total active mass. The prototype generators were constructed using rare-earth permanent magnets NdFeB48H with a remanent flux density of 1.41 T. The rotor and stator lamination cores were laser cut but can be punched in mass production. Open-slots with straight teeth were adopted for the stator with double-layer non-overlap concentrated windings. The short Stellenbosch University https://scholar.sun.ac.za
The Physics of Glaciers

The transformation of snow to ice mass balance heat budget and climatology structure and deformation of ice hydraulics and glaciers glacier sliding deformation of subglacial till structures and fabrics in glaciers and ice sheets distribution of temperature in glaciers and ice sheets steady flow of glaciers and ice sheets flow of ice shelves and ice streams non-steady flow of glaciers and ice sheets surging and tidewater glaciers ice core studies.
A new approach for periodic disturbance rejection in input-time-delay systems

An innovative approach combining equivalent-input-disturbance (EID) theory with the internal model principle is applied to achieve periodic disturbance rejection in input-time-delay systems. The EID estimator, which exhibits the synthetic effect of the time-delay and the periodic disturbance as an input-dependent disturbance, is constructed by inserting appropriate time-delay elements to compensate for the total influence of the input-time-delay and the periodic disturbance. A sufficient stability criterion is derived based on the separation theorem and the small-gain theorem. A design algorithm is developed for the system based on the stability criterion. Design and simulation results for the example are also employed to compare our method with the disturbance observer approach, and to demonstrate the validity of our method.