Miracle-dz/UniFAR-FTUs huggingface dataset:
Interaction-induced atomic displacements revealed by drift-corrected dynamic force spectroscopy

The three-dimensional force field above an NaCl(001) surface was measured on a fine grid by small amplitude dynamic force spectroscopy at room temperature. After careful drift corrections, maps in nominally equivalent symmetry planes as well as in sections parallel to the surface reveal distance-dependent shifts of characteristic atomic-sized features. These shifts reflect asymmetries of the probing tip apex but are mainly due to atomic displacements induced by short-range forces. In addition, weak decaying force oscillations with a period close to the interlayer spacing are detected at distances where no atomic-scale variations are expected. Stronger site-dependent changes appear in the interaction-induced energy dissipation.
Effect of “Uchakiri”(Vitex doniana),“Uturukpa” (Pterocarpus santalinoides) and “Ewa” (Solanum americanum) Methanoic Extract on Iron Status of Rats

Background: Iron deficiency anaemia is a hidden hunger which can affect at every stage of human development especially pregnant women and children. Aim: The study was carried out to ascertain the effect of “ewa”, “uturukpa” and “uchakiri” on iron status of rat. Methods: The vegetables were purchased from Oriemba market Akpugo in Nkanu West Local Government Area of Enugu State. The vegetables were trimmed, washed with deionized water and drained. The vegetables were ground using electric blender. Methanolic extraction was done using a modified method. All the analysis were carried out using a standard method. Results: The results obtained were 2.67-3.52 mg iron, 0.52-0.89 mg copper, 1.56-7.43 mg zinc, 2.42-120.70 mg calcium 10.16-39.10 mg magnesium, and 68.80-90.40 mg potassium. The mean serum ferritin, haemoglobin, packed cell volume and RBC all increased gradually after consumption of leaves extract. Conclusion: The result showed that ethanol leaf extract of Vitex doniana, “ewa” and “uturukpa” posseses anti-anemic potentials that are capable of reducing the risk of iron deficiency anemia in the society.
Characterization of karonda (Carissa carandus) genotypes under Punjab conditions

Karonda is rich source of iron, ascorbic acid, anthocyanins and other antioxidants. As karonda fruit is astringent and sour in taste and not used for desert purpose. Both ripe and unripe karonda fruits are used to prepare various value added products. On the basis of chemical composition, ripe fruits were better with desirable characters, hence G-3 appears to be the best among all the tested karonda genotypes i.e. more total soluble solids, total soluble sugars, ascorbic acid, total soluble proteins and iron content with low acidity and phenols. While, the physical parameters, viz. fruit colour, fruit diameter, fruit length, seed number, seed weight and pulp weight were observed maximum in G-2 followed by G-3 genotypes which can be useful for processing industries for preparation of value added products.
Asteroseismic masses of retired planet-hosting A-stars using SONG

To better understand how planets form, it is important to study planet occurrence rates as a function of stellar mass. However, estimating masses of field stars is often difficult. Over the past decade, a controversy has arisen about the inferred occurrence rate of gas-giant planets around evolved intermediate-mass stars -- the so-called `retired A-stars'. The high masses of these red-giant planet hosts, derived using spectroscopic information and stellar evolution models, have been called into question. Here we address the controversy by determining the masses of eight evolved planet-hosting stars using asteroseismology. We compare the masses with spectroscopic-based masses from the Exoplanet Orbit Database that were previously adopted to infer properties of the exoplanets and their hosts. We find a significant one-sided offset between the two sets of masses for stars with spectroscopic masses above roughly 1.6Msun, suggestive of an average 15--20% overestimate of the adopted spectroscopic-based masses. The only star in our sample well below this mass limit is also the only one not showing this offset. Finally, we note that the scatter across literature values of spectroscopic-based masses often exceed their formal uncertainties, making it comparable to the offset we report here.
Large data analysis: automatic visual personal identification in a demography of 1.2 billion persons

The largest biometric deployment in history is now underway in India, where the Government is enrolling the iris patterns (among other data) of all 1.2 billion citizens. The purpose of the Unique Identification Authority of India (UIDAI) is to ensure fair access to welfare benefits and entitlements, to reduce fraud, and enhance social inclusion. Only a minority of Indian citizens have bank accounts; only 4 percent possess passports; and less than half of all aid money reaches its intended recipients. A person who lacks any means of establishing their identity is excluded from entitlements and does not officially exist; thus the slogan of UIDAI is: To give the poor an identity. " This ambitious program enrolls a million people every day, across 36,000 stations run by 83 agencies, with a 3-year completion target for the entire national population. The halfway point was recently passed with more than 600 million persons now enrolled. In order to detect and prevent duplicate identities, every iris pattern that is enrolled is first compared against all others enrolled so far; thus the daily workflow now requires 600 trillion (or 600 million-million) iris cross-comparisons. Avoiding identity collisions (False Matches) requires high biometric entropy, and achieving the tremendous match speed requires phase bit coding. Both of these requirements are being delivered operationally by wavelet methods developed by the author for encoding and comparing iris patterns, which will be the focus of this Large Data Award" presentation.
Finite-density transition line for QCD with 695 MeV dynamical fermions

We apply the relative weights method to SU(3) gauge theory with staggered fermions of mass 695 MeV at a set of temperatures in the range $151 \le T \le 267$ MeV, to obtain an effective Polyakov line action at each temperature. We then apply a mean-field method to search for phase transitions in the effective theory at finite densities. The result is a transition line in the plane of temperature and chemical potential, with an endpoint at high temperature, as expected, but also a second endpoint at a lower temperature. We cannot rule out the possibilities that a transition line reappears at temperatures lower than the range investigated, or that the second endpoint is absent for light quarks.
Static and dynamic bifurcations associated with a double-zero eigenvalue

This paper is concerned with the static and dynamic bifurcation phenomena exhibited by a nonlinear autonomous system in the vicinity of a double-zero eigenvalue. It is demonstrated analytically that such a coincident critical point is often located on the intersection of the divergence and flutter boundaries of the system. The analysis is performed via a new ‘unification technique’ which is based on an intrinsic perturbation procedure. The new approach is capable of yielding information about stability of solutions as well as incipient and secondary bifurcations. Indeed, the stability properties of the system and secondary Hopf bifurcations are discussed conveniently, and explicit results concerning post-critical solutions are presented. An illustrative example is analysed.
‘Not my dream’: Mother’s challenge of raising intellectual disability child in Vhembe district

Background The birth of a child with an intellectual disability in a family brings confusion, depression and frustrations, especially to the mother. Activities required by these children place a heavy burden on mothers in terms of support and care, as most mothers are the ones who take full care in the well-being of a child, regardless of whether a child has an intellectual disability or not. Challenges include feeding, bathing, dressing, finance and assisting with elimination, especially when the child is a teenager, where one expects the child to be able to do everything for himself or herself. Aim To explore and describe the challenges experienced by mothers of children with intellectual disabilities. Setting The study was conducted in the selected hospitals of the Vhembe district in Limpopo province. Methods A qualitative, exploratory, descriptive and contextual research design was adopted. A nonprobability purposive sample comprised 13 mothers of children with intellectual disabilities such as down syndrome and cerebral palsy. Data were collected through unstructured interviews until saturation was reached. Data were analysed by the open-coding method. Results Study findings revealed that mothers of children with intellectual disabilities experienced feelings of fear, embarrassment and financial burdens because of children’s special needs and initial awareness of the diagnosis. Conclusion It is imperative that mothers of children with intellectual disabilities be supported by family, relatives, health care professionals and the community. Contribution The study’s contribution was to strengthen psychological intervention and support to mothers and awareness to accept children with intellectual disability.
Einstein Yang–Mills Higgs dark energy revisited

Inspired in the standard model of elementary particles, the Einstein Yang–Mills Higgs action with the Higgs field in the SU(2) representation was proposed in Rinaldi (2015 Class. Quantum Grav. 32 045002) as the element responsible for the dark energy phenomenon. We revisit this action emphasizing in a very important aspect not sufficiently explored in the original work and that substantially changes its conclusions. This aspect is the role that the Yang–Mills Higgs interaction plays at fixing the gauge for the Higgs field, in order to sustain a homogeneous and isotropic background, and at driving the late accelerated expansion of the Universe by moving the Higgs field away of the minimum of its potential and holding it towards an asymptotic finite value. We analyse the dynamical behaviour of this system and supplement this analysis with a numerical solution whose initial conditions are in agreement with the current observed values for the density parameters. This scenario represents a step towards a successful merging of cosmology and well-tested particle physics phenomenology.
Compact representation of the facial images for identification in a parallel-hierarchical network

The work offers the methods for invariant representation of images against a variety of distorting factors including 2D and 3D rotation, changes in brightness, contrast and scale. The problems of preliminary image processing based on the method of generalized Q-transformation are being solved. The calculating algorithms based on the methodology of dichotomous balance of the images being prepared have been used for the classification of human facial images. It also deals with the procedure of recursive contour preparation consisting of step-by-step preparation of differences among the pixels of grey-scale image and formation of positive, negative and zero preparations. Thus at the first step the contour preparation is effected for the first differences, at the second step, for the second differences, and so on, with a step-by-step definition of the criterial function of distribution of binarized preparations. So it is possible to identify objects in different lighting conditions which simplifies the implementation of similar approaches. This relative simplicity of this method extends the range of its possible application for recognition purposes and for its implementation in the parallel-hierarchical network in particular.
Control of conditional output probability density functions for general nonlinear and non-Gaussian dynamic stochastic systems

A method to control the shape of the conditional output probability density function for general nonlinear-dynamic stochastic systems represented by a nonlinear ARMAX model is presented. The system is subjected to an arbitrary and bounded random input. Under the assumption that all the variables are uniformly bounded, a mathematical relationship is formulated among the conditional output probability density function, the system nonlinear structure and the characteristics of the random input. This leads to the establishment of a recursive formula for the evolution of the conditional output probability density functions for the system. An optimal control has thus been developed by embedding the system dynamics into the recursive formula and by minimising the difference between the conditional output probability density function and a target probability density function. It has been shown that the obtained control input is of an output feedback type, where the on-line measurements of the conditional output probability density functions are not required. An illustrative example is utilised to demonstrate the use of the control algorithm, some satisfactory results have been obtained.
Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)

Abstract. The Community Atmosphere Model (CAM6.1), the atmospheric component of the Community Earth System Model (CESM; version 2.1), simulates the life cycle (emission, transport, and deposition) of mineral dust and its interactions with physio-chemical components to quantify the impacts of dust on climate and the Earth system. The accuracy of such quantifications relies on how well dust-related processes are represented in the model. Here we update the parameterizations for the dust module, including those on the dust emission scheme, the aerosol dry deposition scheme, the size distribution of transported dust, and the treatment of dust particle shape. Multiple simulations were undertaken to evaluate the model performance against diverse observations, and to understand how each update alters the modeled dust cycle and the simulated dust direct radiative effect. The model–observation comparisons suggest that substantially improved model representations of the dust cycle are achieved primarily through the new more physically-based dust emission scheme. In comparison, the other modifications induced small changes to the modeled dust cycle and model–observation comparisons, except the size distribution of dust in the coarse mode, which can be even more influential than that of replacing the dust emission scheme. We highlight which changes introduced here are important for which regions, shedding light on further dust model developments required for more accurately estimating interactions between dust and climate.
Learning from Demonstrations in Human-Robot Collaborative Scenarios: A Survey

Human–Robot Collaboration (HRC) is an interdisciplinary research area that has gained attention within the smart manufacturing context. To address changes within manufacturing processes, HRC seeks to combine the impressive physical capabilities of robots with the cognitive abilities of humans to design tasks with high efficiency, repeatability, and adaptability. During the implementation of an HRC cell, a key activity is the robot programming that takes into account not only the robot restrictions and the working space, but also human interactions. One of the most promising techniques is the so-called Learning from Demonstration (LfD), this approach is based on a collection of learning algorithms, inspired by how humans imitate behaviors to learn and acquire new skills. In this way, the programming task could be simplified and provided by the shop floor operator. The aim of this work is to present a survey of this programming technique, with emphasis on collaborative scenarios rather than just an isolated task. The literature was classified and analyzed based on: the main algorithms employed for Skill/Task learning, and the human level of participation during the whole LfD process. Our analysis shows that human intervention has been poorly explored, and its implications have not been carefully considered. Among the different methods of data acquisition, the prevalent method is physical guidance. Regarding data modeling, techniques such as Dynamic Movement Primitives and Semantic Learning were the preferred methods for low-level and high-level task solving, respectively. This paper aims to provide guidance and insights for researchers looking for an introduction to LfD programming methods in collaborative robotics context and identify research opportunities.
Non-collinear Korringa-Kohn-Rostoker Green function method: Application to 3d nanostructures on Ni(001)

Magnetic nanostructures on non-magnetic or magnetic substrates have attracted strong attention due to the development of new experimental methods with atomic resolution. Motivated by this progress we have extended the full-potential Korringa-Kohn-Rostoker (KKR) Green function method to treat non-collinear magnetic nanostructures on surfaces. We focus on magnetic 3d impurity nanoclusters, sitting as adatoms on or in the first surface layer on Ni(001), and investigate the size and orientation of the local moments and moreover the stabilization of non-collinear magnetic solutions. While clusters of Fe, Co, Ni atoms are magnetically collinear, non-collinear magnetic coupling is expected for Cr and Mn clusters on surfaces of elemental ferromagnets. The origin of frustration is the competition of the antiferromagnetic exchange coupling among the Cr or Mn atoms with the antiferromagnetic (for Cr) or ferromagnetic (for Mn) exchange coupling between the impurities and the substrate. We find that Cr and Mn first-neighbouring dimers and a Mn trimer on Ni(001) show non-collinear behavior nearly degenerate with the most stable collinear configuration. Increasing the distance between the dimer atoms leads to a collinear behavior, similar to the one of the single impurities. Finally, we compare some of the non-collinear {\it ab-initio} results to those obtained within a classical Heisenberg model, where the exchange constants are fitted to total energies of the collinear states; the agreement is surprisingly good.
Prenatal Metal Exposures and Associations with Kidney Injury Biomarkers in Children

Prenatal exposure to arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb) may be nephrotoxic, yet limited studies have examined subclinical kidney injury biomarkers in children. We assessed whether metal exposure in the second trimester (2T), a crucial time of kidney development, is associated with altered urine kidney injury and function biomarkers in preadolescent children. Analyses included 494 children participating in a birth cohort study in Mexico City. Concentrations of As, Cd, and Pb were measured from pregnant women in 2T blood and urine, and Hg in urine only. Kidney biomarkers were measured from children in urine at age 8–12 years. We assessed the associations between individual metals and (1) kidney biomarkers using linear regression and (2) a multi-protein kidney mixture using weighted quantile sum (WQS) regression. Associations of separate urine and blood metal mixtures with individual kidney biomarkers were assessed via WQS. Within the multi-protein mixture, the association with increased urinary As was predominated by urine alpha-1-microglobulin (A1M), interferon gamma-induced protein 10 (IP10), and fatty acid binding protein 1; the association with increased urinary Cd was predominated by A1M, clusterin, and albumin. The urine metal mixture was associated with increased albumin (0.23 ng/mL; 95% confidence interval (CI): 0.10, 0.37), IP10 (0.15 ng/mL; 95% CI: 0.02, 0.28), and cystatin C (0.17 ng/mL; 95% CI: 0.04, 0.31); these associations were mainly driven by urinary As and Cd. We observed null associations between prenatal blood or urine metal mixtures and estimated glomerular filtration rate. Higher prenatal urinary metals, individually and as a mixture were associated with altered kidney injury biomarkers in children. Further research and longer participant follow-up are required to ascertain the risk of kidney disease later in life.
Electric-field-induced phase transition and electrocaloric effect in PMN-PT

Ferroelectric perovskite oxides possess a large electrocaloric (EC) effect, but usually at high temperatures near the ferroelectric/paraelectric phase transition temperature, which limits their potential application as next generation solid-state cooling devices. We use classical molecular dynamics to study the electric-field-induced phase transitions and EC effect in PMN-PT (PbMg1/3Nb2/3O3-PbTiO3). We find that the maximum EC strength of PMN-PT occurs within the morphotropic phase boundary (MPB) region at 300 K. The large adiabatic temperature change is caused by easy rotation of polarization within the MPB region.
Interlaminar Stresses in Laminated Composite Beam-Type Structures Under Shear/Bending

A boundary integral model for composite laminates under out-of-plane shear/bending is presented. The formulation proposed allows one to determine the elastic response of generally stacked composite laminates having general shape of the cross section. The integral equations governing the ply behavior within the laminate are deduced starting from the reciprocity theorem for beam-type structures. The ply integral equations are obtained by employing the analytical expression of the fundamental solution of generalized plane strain anisotropic problems. The laminate model is completed by imposing the displacement and stress continuity along the interfaces and the external boundary conditions. The formulation is numerically solved by the boundary element method, proposing a solution strategy for standard laminate configurations. The solution of the linear algebraic resolving system provides the displacements and tractions on the boundary of each ply of the laminate. Once this boundary elastic response is known, the displacements and stresses at any internal point of the laminate section are computed using their boundary integral representations. Some applications are presented to demonstrate the accuracy and effectiveness of the method proposed.
Shape-memory effect for self-healing and biodegradable photonic systems

Photonic systems with the capability to respond to different stimuli are more and more desirable for achieving multifunctionality and higher levels of performance. They demand materials with responsivity that may eventually be used for integrating sensing and actuating functions, a feature highly pursued in technological applications. A notable property which is being gradually incorporated in this kind of multifunctional materials is the shape memory effect (SME). In this work, a material system consisting of a two-dimensional photonic crystal (PC) imprinted in the surface of a shape memory polymer (SMP) is reported. It integrates several interesting features such as elasticity, thermoresponsivity and shape memory. The referred PC is composed of a hexagonal lattice of nanobowls, transferred to the SMP surface using replica molding. Good quality and large extensions of PC were achieved. Differential scanning calorimetry studies confirmed a melting transition responsible for the SME in these materials. From the structural point of view, their surfaces were characterized by atomic force and scanning electron microscopies. From the optical point of view, the characterization of the first order Bragg diffraction angle was carried out. A full programmable character of the structures, derived from the SME, was demonstrated. The reported material system presents some interesting additional features. In particular, the SMP selected for replicating the PC belongs to the family of polydiolcitrates, which are known to be biocompat- ible and biodegradable elastomers. The PC described herein is thus attractive for the development of disposable devices or for temporal usage in biomedicine or biophotonics.