Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential response to climate change and human activities in three lineages of Sichuan snub‐nosed monkeys (Rhinopithecus roxellana)

Determining the mechanisms by which climate change and human activities affect patterns of ecological specialization in different genetic units of the same species is crucial for developing local or regionally‐based conservation solutions. This study uses species distribution models and genetic analysis to (1) identify the evidence of intraspecific differences in the population size and distribution of the three extant lineages (Sichuan/Gansu (SG), Qinling (QL) and Shennongjia (SNJ)) of Sichuan snub‐nosed monkeys and (2) determine why some lineages have lower population numbers, a smaller geographical distribution, and are more threatened with extinction.
Prevalence and Early Prediction of Diabetes Using Machine Learning in North Kashmir: A Case Study of District Bandipora

Diabetes is one of the biggest health problems that affect millions of people across the world. Uncontrolled diabetes can increase the risk of heart attack, cancer, kidney damage, blindness, and other illnesses. Researchers are motivated to create a Machine Learning methodology that can predict diabetes in the future. Exploiting Machine Learning Algorithms (MLA) is essential if healthcare professionals are able to identify diseases more effectively. In order to improve the medical diagnosis of diabetes this research explored and contrasts various MLA that can identify diabetes risk early. The research includes the analysis on real datasets such as a clinical dataset gathered from a doctor in the Indian district of Bandipora in the years April 2021–Feb2022. MLA are currently important in the healthcare sector due to their prediction abilities. Researchers are using MLA to improve disease prediction and reduce cost. In this Paper author developed a methodology using Machine Learning Algorithms for Diabetes Disease Risk Prediction in North Kashmir. Six MLA have been successfully used in the experimental study such as Random Forest (RF), Multi-Layer Perceptron (MLP), Support Vector Machine (SVM), Gradient Boost (GB), Decision Tree (DT), and Logistic Regression (LR). RF is the most accurate classifier with the uppermost accuracy rate of 98 percent followed by MLP (90.99%), SVM (92%), GBC (97%), DT (96%), and LR (69%), respectively, with the balanced data set. Lastly, this study enables us to effectively identify the prevalence and prediction of diabetes.
Exploiting Machine Learning Models for Identification of Heart Diseases

Cardiovascular illnesses have surpassed disease as the leading cause of death in industrialized, emerging, and underprivileged countries in recent decades. The mortality rate can be lowered through early detection and effective care of cardiac diseases. However, reliable detection of heart disorders in all conditions and serving doctors with 24-hour medical consultations are not possible since they require more intelligence, time, and talent to train the computer for a specific duty. Artificial intelligence and machine learning algorithms may have a substantial impact on the lives of those who are afflicted with chronic diseases. In this work, we used artificial intelligence to create a hybrid model for the prediction of cardiac disease and flags for prevention. The goal of this research was to develop a prediction model that can identify and characterize a patient's illness. We used data of 68975 patients from the University of California, Irvine's repository and trained several algorithms for CVD illness prediction. In our simulation maximum classifiers have achieved the greatest accuracy, which is a huge accomplishment for our research team. Our proposed hybrid ML algorithm framework improved CVD prediction performance when compared to previously offered prediction models. The proposed methods are decision tree and random forest models, which have a 99.98% accuracy for training, followed by support vector machine, which has a 99.30% accuracy followed by other classifiers which yield higher results in comparison. Pre-existing CVD history was considered the most important factor determining the prediction model's accuracy. Our findings reveal that our CVD prediction model based on machine learning techniques developed for health screening datasets is simple to apply and more accurate. Our proposed classifiers have the best accuracy rate.
Development of a framework for person-centred physiotherapy

Abstract Background There is a growing call for healthcare to focus on person-centred practice. This can lead to improved outcomes for patients in terms of physical and psychological health. Challenges exist around how person-centredness is understood in physiotherapy. Having a physiotherapy framework would help support a shared understanding of the meaning of person-centred physiotherapy. Aim The aim of this study was to locate and synthesise studies which have a conceptualisation of person-centred physiotherapy practice. These were used to develop an overarching conceptual framework for person-centred physiotherapy practice. Methods The framework was developed through a systematic process involving a systematic literature search, screening studies against eligibility criteria, data extraction, data synthesis, naming and defining core constructs of person-centred physiotherapy practice, and generation of a pictorial representation of an overarching conceptual framework. Results The person-centred physiotherapy framework is comprised of four constructs: physiotherapist characteristics, which focuses on the knowledge and skills for clinical proficiency, attributes of the physiotherapist, reflection and self-awareness; person-physiotherapist interaction(s), which focuses on partnership, empowerment and self-management; the environment, which focuses on coordinated healthcare delivery, culture of the organisation and practice environment, and the physical environment; and the ongoing unique journey of the person and self-management. The relationships between the constructs reflect the complex nature of person-centred practice. Conclusions The framework presented can be used to better understand person-centred physiotherapy with a view to enhancing practice. The framework needs to be tested further through empirical research to establish its utility.
Latina girls of Puerto Rican origin who are successful in science and mathematics high school courses.

LATINA GIRLS OF PUERTO RICAN ORIGIN WHO ARE SUCCESSFUL IN SCIENCE AND MATHEMATICS HIGH SCHOOL COURSES FEBRUARY 1999 AIDA L. OQUENDO RODRIGUEZ B A. , UNIVERSITY OF PUERTO RICO, RIO PIEDRAS M. A. , UNIVERSITY OF PUERTO RICO, RIO PIEDRAS Ed. D. , UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Gretchen Rossman Professions and careers related to science and mathematics lack representation of minorities. Within these underrepresented minority populations there is no other group more affected than Latina women and girls. Women in general, are still underrepresented in many areas of our society. While women’s roles are changing in today’s society, most changes encourage the participation of more White / Anglo women in traditionally male roles. Latina women are still more disadvantaged than White women. There is no doubt that education is significant in increasing the participation of minorities in the fields of science and mathematics, especially for minority girls (Oakes, 1990; Rodriguez, 1993). This study explored the interests, life experiences, characteristics and motivations of Latina girls of Puerto Rican origin who are successful in science and mathematics high school courses. The study identifies factors that can influence the interest of Latina girls of Puerto Rican origin in science and mathematics career choices. This research is significant and relevant to educators and policy makers, especially to science and mathematics educators. The research is primarily descriptive and exploratory. It
CC Sculptoris: Eclipsing SU UMa-Type Intermediate Polar

We observed the 2014 superoutburst of the SU UMa-type intermediate polar CC Scl. We detected superhumps with a mean period of 0.05998(2) d during the superoutburst plateau and during three nights after the fading. During the post-superoutburst stage after three nights, a stable superhump period of 0.059523(6) d was detected. We found that this object is an eclipsing system with an orbital period of 0.058567233(8) d. By assuming that the disk radius in the post-superoutburst phase is similar to those in other SU UMa-type dwarf novae, we obtained a mass ratio of q=0.072(3) from the dynamical precession rate of the accretion disk. The eclipse profile during outbursts can be modeled by an inclination of 80.6+/-0.5 deg. The 2014 superoutburst was preceded by a precursor outburst and the overall appearance of the outburst was similar to superoutbursts in ordinary SU UMa-type dwarf novae. We showed that the standard thermal-tidal instability model can explain the outburst behavior in this system and suggest that inner truncation of the disk by magnetism of the white dwarf does not strongly affect the behavior in the outer part of the disk.
Extension of Vortex Bessel Beams Generated by Finite-Width Durnin Ring With Helical Phase Modulation

Bessel beams are widely used for different applications due to their attractive non-diffractive behavior. However, the real-world Bessel beams have finite propagation distance, where such behavior can be assumed. In this work we consider the degradation of vortex Bessel beams generated by a finite-width Durnin ring with helical phase modulation. For this purpose, we derive the expression that describes the propagation of rotationally symmetric vortex beams. By using this expression, we show that the axial degradation of the main lobe of Bessel beams is almost independent on their topological charge and decreases by increasing the radius of the Durnin ring and its width. The increase of ring width also yields to the radial degradation (deformation of the secondary lobes) of the Bessel beams. These findings are particularly important for the construction of more sophisticated structured beams described as a linear superposition of vortex Bessel beams.
Design and Low Complexity Implementation of FRM-Based OMFB With STB

Due to limited hardware resources, multi-channel digital channelizers often use a 50% overlapping wide transition bandwidth in array signal processing. In this brief, we proposed an oversampled modulated filter bank (OMFB) with sharp transition bandwidth (STB) based on frequency response masking (FRM). The FRM approach is used to design and optimize the prototype filter with STB. The design process and fast implementation based on Xilinx System Generator of the proposed FRM-based OMFB with STB is presented. The proposed FRM-based OMFB with STB has the advantages of low complexity, which is suitable for high sampling rate system. Compared with conventional polyphase filter bank for digital channelizer, the proposed FRM-based OMFB with STB can offer 81.14% reduction in multipliers complexity.
A NEW RESULT ON THE ORIGIN OF THE EXTRAGALACTIC GAMMA-RAY BACKGROUND

In this paper, we repeatedly use the method of image stacking to study the origin of the extragalactic gamma-ray background (EGB) at GeV bands, and find that the Faint Images of the Radio Sky at Twenty centimeters (FIRST) sources undetected by the Large Area Telescope on the Fermi Gamma-ray Space Telescope can contribute about (56 ± 6)% of the EGB. Because FIRST is a flux-limited sample of radio sources with incompleteness at the faint limit, we consider that point sources, including blazars, non-blazar active galactic nuclei, and starburst galaxies, could produce a much larger fraction of the EGB.
Ultrafast optical control of magnetization in EuO thin films

All-optical pump-probe detection of magnetization precession has been performed for ferromagnetic EuO thin films at 10 K. We demonstrate that the circularly-polarized light can be used to control the magnetization precession on an ultrafast time scale. This takes place within the 100 fs duration of a single laser pulse, through combined contribution from two nonthermal photomagnetic effects, i.e., enhancement of the magnetization and an inverse Faraday effect. From the magnetic field dependences of the frequency and the Gilbert damping parameter, the intrinsic Gilbert damping coefficient is evaluated to be {\alpha} \approx 3\times10^-3.
Interferometry and the Fundamental Properties of Stars

For many decades the determination of accurate fundamental parameters for stars (masses, radii, temperatures, luminosities, etc.) has mostly been the domain of eclipsing binary systems. That has begun to change as long-baseline interferometric techniques have improved significantly, and powerful new instruments have come online. This paper will review the status of the field, and in particular how the knowledge of precise stellar properties helps us understand stars. Main-sequence stars similar to the Sun are by far the best studied, but much remains to be done for other kinds of objects such as early-type as well as late-type stars including brown dwarfs, evolved stars, metal-poor stars, and pre-main sequence stars. Progress is illustrated with several examples of how interferometry has contributed significantly in some of these areas.
SeamFlow: Seamless Flow Forwarding in Energy Harvesting-Enabled Access Points of SDWLAN

The deployment of software-defined wireless local area networks (SDWLANs) in hostile regions requires solar energy harvesting-enabled battery-powered access points (APs). The aforementioned APs replenish batteries and forward data flows by avoiding the problem of frequent energy outages. In this work, we propose a scheme called SeamFlow to place APs in energy harvesting mode without disrupting the forwarding of flows. In contrast to previous works, we focus not only on the energy replenishment of battery, but also, seamless forwarding of flows without violating flow constraints. Specifically, we formulate SeamFlow as a two-phase optimization problem – a) optimal selection of APs and b) finding forwarding paths. As solving both optimization problems are NP-hard, we propose two greedy-heuristic schemes to solve them in polynomial time. Extensive simulation results show that proposed scheme reduces flow forwarding cost by 24% and 16%, per-flow energy consumption by 27% and 21%, and flow violations by 92% and 86% compared to the benchmarks using random and grid topologies, respectively.
QUALITATIVE ASPECTS OF THE PHASE DIAGRAM OF J1–J2 MODEL ON THE CUBIC LATTICE

The qualitative aspects of the phase diagram of the Ising model on the cubic lattice, with ferromagnetic (F) nearest-neighbor interactions (J1) and antiferromagnetic (AF) next-nearest-neighbor couplings (J2) are analyzed in the plane temperature versus α, where α = J2/|J1| is the frustration parameter. We used the original Wang–Landau sampling (WLS) and the standard Metropolis algorithm to confront past results of this model obtained by the effective-field theory (EFT) for the cubic lattice. Our numerical results suggest that the predictions of the EFT are in general qualitatively correct, but the low-temperature re-entrant behavior, observed in the frontier separating the F and the collinear order, is an artifact of the EFT approach and should disappear when we consider Monte Carlo (MC) simulations of the model. In addition, our results indicate that the continuous phase transition between the F and the paramagnetic (P) phases, that occurs for 0.0 ≤α< 0.25, belongs to the universality class of the three-dimensional pure Ising Model.
A Family of Interleaved Boost Converters for Battery Discharging in Space Applications

A family of interleaved boost converters and an original systematic derivation method based on the two-phase interleaved inverse-coupled inductor concept are proposed in this article for battery discharging in spacecraft applications. The family, including 14 converters, is generated by interconnecting multiple pulsating voltage cells through the energy storage cells. The basic pulsating voltage cells are derived from an inverse-coupled boost converter, and the energy storage cells include an inductor cell, tapped inductor cell, flyback cell, buck-current-fed cell, and partially current-fed cell. The proposed family of converters achieves high efficiency, step-up power conversion without the right-half-plane zero effect, continuous output current and low side switch driver. The operational principle and small-signal analysis of a representative topology in the proposed family of converters are discussed in detail. Moreover, experimental and simulation results are presented to verify the feasibility and effectiveness of the developed converter. Finally, the characteristics of the proposed family of converters are compared with other state-of-the-art converters.
Coupling of the As A1g phonon to magnetism in iron pnictides

of this entanglement is the behavior of the A1g As-phonon resonance in the different polarization symmetries of Raman spectroscopy when undergoing the magnetostructural transition. In this work, we show that the observed behavior could be a direct consequence of the coupling of the phonons with the electronic excitations in the anisotropic magnetic state. We discuss this scenario within a five-orbital tight-binding model coupled to phonons via the dependence of the Slater-Koster parameters on the As position. We identify two qualitatively different channels of the electron-phonon interaction: a geometrical one related to the Fe-As-Fe angle α and another one associated with the modification upon As displacement of the Fe-As energy integrals pdσ and pdπ. While both mechanisms result in a finite B1g response, the behavior of the phonon intensity in the A1g and B1g Raman polarization geometries is qualitatively different when the coupling is driven by the angle or by the energy integral dependence. We discuss our results in view of the experimental reports.
Centrality dependence of charged jets in p-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$ TeV measured with the ALICE detector

Highly energetic jets are sensitive probes for the kinematics and the topology of nuclear collisions. Jets are collimated sprays of charged and neutral particles, which are produced in the fragmentation of hard scattered partons in the early stage of the collision. The measurement of nuclear modification of charged jet spectra in p-Pb collisions provides an important way of quantifying the effects of cold nuclear matter in the initial state on jet production, fragmentation, and hadronization. Unlike in Pb-Pb collisions, modifications of jet production due to hot nuclear matter effects are not expected to occur in p-Pb collisions. Therefore, measurements of nuclear modifications in charged jet spectra in p-Pb collisions (commonly known as $R_\mathrm{pPb}$) can be used to isolate and quantify cold nuclear matter effects. Potential nuclear effects are expected to be more pronounced in more central p-Pb collisions due to a higher probability of an interaction between the proton and the lead-nucleus. To measure the centrality dependence of charged jet spectra, it is crucial to use a reliable definition of event centrality, which ALICE developed utilizing the Zero-Degree Calorimeter (ZDC).
Cosmic Acceleration and a New Concordance from Causal Backreaction

A phenomenological formalism is presented in which the apparent acceleration of the universe is generated by large-scale structure formation, thus eliminating the magnitude and coincidence fine-tuning problems of the Cosmological Constant in the Concordance Model, as well as potential instability issues with dynamical Dark Energy. The observed acceleration results from the combined effect of innumerable local perturbations due to individually virializing systems, overlapping together in a smoothly-inhomogeneous adjustment of the FRW metric, in a process governed by the causal flow of inhomogeneity information outward from each clumped system. After explaining why arguments from the literature claiming to place restrictive limits upon backreaction are not applicable in a physically realistic cosmological analysis, we present a selection of simply-parameterized models which are capable of fitting the luminosity distance data from Type Ia supernovae essentially as well as the best-fit flat $\Lambda$CDM model, without resort to Dark Energy, any modification to gravity, or a local void. Simultaneously, these models can reproduce measured cosmological parameters such as the age of the universe, the matter density required for spatial flatness, the present-day deceleration parameter, and the angular scale of the Cosmic Microwave Background to within a reasonable proximity of their Concordance values. A potential observational signature for distinguishing this cosmological formalism from $\Lambda$CDM may be a cosmic jerk parameter significantly in excess of unity.
Absolute Magnitude Calibration for Dwarfs Based on the Colour–Magnitude Diagrams of Galactic Clusters

Abstract We present two absolute magnitude calibrations for dwarfs based on colour–magnitude diagrams of Galactic clusters. The combination of the Mg absolute magnitudes of the dwarf fiducial sequences of the clusters M92, M13, M5, NGC 2420, M67, and NGC 6791 with the corresponding metallicities provides absolute magnitude calibration for a given (g − r)0 colour. The calibration is defined in the colour interval 0.25 ≤ (g − r)0 ≤ 1.25 mag and it covers the metallicity interval − 2.15 ≤ [Fe/H] ≤ +0.37 dex. The absolute magnitude residuals obtained by the application of the procedure to another set of Galactic clusters lie in the interval − 0.15 ≤ ΔMg ≤ +0.12 mag. The mean and standard deviation of the residuals are < ΔMg > = − 0.002 and σ = 0.065 mag, respectively. The calibration of the MJ absolute magnitude in terms of metallicity is carried out by using the fiducial sequences of the clusters M92, M13, 47 Tuc, NGC 2158, and NGC 6791. It is defined in the colour interval 0.90 ≤ (V − J)0 ≤ 1.75 mag and it covers the same metallicity interval of the Mg calibration. The absolute magnitude residuals obtained by the application of the procedure to the cluster M5 ([Fe/H] = −1.40 dex) and 46 solar metallicity, − 0.45 ≤ [Fe/H] ≤ +0.35 dex, field stars lie in the interval − 0.29 and + 0.35 mag. However, the range of 87% of them is rather shorter, − 0.20 ≤ ΔMJ ≤ +0.20 mag. The mean and standard deviation of all residuals are < ΔMJ > =0.05 and σ = 0.13 mag, respectively. The derived relations are applicable to stars older than 4 Gyr for the Mg calibration, and older than 2 Gyr for the MJ calibration. The cited limits are the ages of the youngest calibration clusters in the two systems.
Non-Poisson character of vessel trafficon the Szczecin-Świnoujście fairway

In this paper the hypothesis about Poissonian character of vessel traffic stream from Świnoujście to Szczecin has been verified. And the hypothesis about Non-Poissonian character of vessel traffic stream from Szczecin to Świnoujście has been verified. To reach this goal, VTS data from second half of 2009 has been used. To description of non- Poissonian vessel traffic stream, for the first time, mixed distributions have been used.