Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Optimal Whole-Body Vibration Protocol for Muscle Strength

The application of Whole Body Vibration (WBV) has been demonstrated to be effective in improving muscle strength/power by a number of studies, but an optimal training protocol has never been established. This paper presents a review of studies on the effects of WBV on muscles and an analysis of data to identify the optimal protocols for the most beneficial neuromuscular responses in terms of vibration frequency, amplitude, knee flexion angle, body posture (standing, sitting, supine, prone), muscle type (quadriceps, hamstrings), and vibration mode (superoinferior, anteroposterior, rotational). Ninety articles were selected for final review from initially selected 2093 articles using PRISMA guidelines. The findings suggest that the beneficial effects of WBV increase with frequency and amplitude but the optimal frequency and amplitude have not been established. The effect of the knee flexion angle is not clear. The optimal WBV protocol should be determined by considering the adverse effects of WBV on all parts of the human body including that related to head acceleration. WBV in sitting or lying positions may provide a better muscle response than standing. Directions for future research are discussed with regard to establishing the optimal WBV protocol as a safe and effective therapeutic/exercise modality for improving muscle strength and health.
Mechanisms for production of hypernuclei beyond the neutron and proton drip lines

We analyze hypernuclei coming from fragmentation and multifragmentation of spectator residues obtained in relativistic ion collisions. These hypernuclei have a broad distribution in masses and isospin. They reach beyond the neutron and proton drip lines, and they are expected to be stable with respect to neutron and proton emission. This gives us the opportunity to investigate the properties of exotic hypernuclei, as well as the properties of normal nuclei beyond the drip lines, which can be produced after weak decay of such hypernuclei.
Comparative Review of Environmental Audit Tools for Public Open Spaces from the Perspective of Children’s Activity

Public open spaces are important venues for children’s participation in outdoor activities and social life. This study performs a comparative and qualitative review of the tools that can be used to audit the environments of children-focused public open spaces. The analysis reviews 25 studies involving 11 tools for comparison. The results reveal that (1) the tools were developed in different fields; (2) the tools use two data resources, field investigation and geographic databases; (3) the tool dimensions are diverse, as are the number of items covered, and are generally related to four categories: surrounding environment and accessibility, activity and perceived safety, children’s sports and play opportunities, and aesthetic and comfort of the environment; (4) the reliability of most tools has been verified, with some validity still to be confirmed; (5) there are differences in tool users, settings, and aims. Among the tools, the CPAT and the EAPRS are the most comprehensive. Comparative analysis of the tools provides a reference for studies on children-focused public open spaces and for the development and improvement of corresponding tools in the future.
A wideband circularly polarized monopole antenna with elliptic ring slot patch using characteristic mode analysis

This article presented a wideband circularly polarization (CP) monopole antenna with elliptic ring slot patch using characteristic mode analysis (CMA). By analyzing the characteristic modes of elliptical patch and elliptical ring patch in turn, it is found that the elliptical ring slot patch can meet the phase requirement of CP. Then, the parasitic elliptical ring slot patch is used to broaden the impedance bandwidth and polarization bandwidth of the antenna. The broadband is obtained by the modal significance (MS) analysis, and the CP is realized by analyzing the characteristic current of two modes are orthogonal and the characteristic angle (CA) close to 90°. The proposed antenna was fabricated and measured with the size of 0. 59λ0 × 0. 59λ0 × 0. 02λ0. The measured 3‐dB axial ratio (AR) band is from 5.3 to 9.4 GHz (55.8%), and the −10 dB impedance band is from 4.5 to 9.7 GHz (73.2%).
Analytic model of the energy spectrum of a graphene quantum dot in a perpendicular magnetic field

We analytically calculate the energy spectrum of a circular graphene quantum dot with radius $R$ subjected to a perpendicular magnetic field $B$ by applying the infinite-mass boundary condition. We can retrieve well-known limits for the cases $R,B\ensuremath{\rightarrow}\ensuremath{\infty}$ and $B\ensuremath{\rightarrow}0$. Our model is capable of capturing the essential details of recent experiments. Quantitative agreement between theory and experiment is limited due to the fact that a circular dot deviates from the actual experimental geometry, that disorder plays a significant role, and that interaction effects may be relevant.
Into the central 10 pc of the most distant known radio quasar - VLBI imaging observations of J1429+5447 at z = 6.21

Context. There are about 60 quasars known at redshifts z > 5.7 to date. Only three of them are detected in the radio above 1 mJy flux density at 1.4 GHz frequency. Among them, J1429+5447 (z = 6.21) is the highest-redshift radio quasar known at present. These rare, distant, and powerful objects provide important insight into the activity of the supermassive black holes in the Universe at early cosmological epochs and into the physical conditions of their environment. Aims. We studied the compact radio structure of J1429+5447 on the milli-arcsecond (mas) angular scale to compare the structural and spectral properties with those of another two z ∼ 6 radio-loud quasars, J0836+0054 (z = 5.77) and J1427+3312 (z = 6.12). Methods. We performed Very Long Baseline Interferometry (VLBI) imaging observations of J1429+5447 with the European VLBI Network (EVN) at 1.6 GHz on 2010 June 8, and at 5 GHz on 2010 May 27. Results. Based on its observed radio properties, the compact but somewhat resolved structure on linear scales of 6.
Universal algorithms for quantum data learning

Operating quantum sensors and quantum computers would make data in the form of quantum states available for purely quantum processing, opening new avenues for studying physical processes and certifying quantum technologies. In this Perspective, we review a line of works dealing with measurements that reveal structural properties of quantum datasets given in the form of product states. These algorithms are universal, meaning that their performances do not depend on the reference frame in which the dataset is provided. Requiring the universality property implies a characterization of optimal measurements via group representation theory.
The COVID-19 “First Lockdown” Experience in Italy: The Role of Hope and Optimism and Their Impact on Psychological Well-Being and Risk Perception

Introduction: The present study investigates the lockdown experience in Italy during the COVID-19 pandemic within a positive psychology framework, focusing on the protective role of the positive anticipatory states: optimism and hope. Aims: The aims were to verify if and how optimism and hope influenced people’s psychological wellbeing and their risk perception of the situation, addressing how individuals portrayed the present and how they imagined the future after the lockdown. Methods: Based on the differences between the two constructs, as from the literature, the hypothesis is that individuals with higher levels of optimism would report positive but hazy future scenarios and lower levels of risk perception about the future. Therefore 1,471 participants received an online survey, which was administered as a set of questionnaires investigating three areas: demographic information, psychological wellbeing, and risk of contagion perception. Results: The results showed that positive anticipatory states are positively associated with psychological wellbeing. Moreover, the results highlighted the relationship between optimism and risk perception regarding future scenarios. Conclusions: The presented predictive model demonstrated that positive anticipatory states, sex, and age had a central role in determining the psychological wellbeing during the first wave of the pandemic events in Italy. Practical implications are discussed.
THE SPREADING LAYER OF GX 9+9

The spreading layer (SL) of GX 9+9 during the upper banana state was studied using INTEGRAL and RXTE observations. The SL-area becomes larger with increasing accretion rate while the SL-temperature remains close to the critical Eddington value, confirming predictions of (3) and (7). However, at low accretion rate the observed temperature is higher and SL-belt shallower than those predicted, requiring confirmation and theoretical explanation.
Effect of Green Plants on Individuals’ Mental Stress during the COVID-19 Pandemic: A Preliminary Study

The COVID-19 pandemic has not only jeopardized people’s physical health, but also put additional strain on their mental health. This study explored the role of indoor natural elements (i.e., green plants) in relieving individuals’ mental stress during a prolonged stressful period. A pilot and three formal studies examined the effect of indoor green plants placed in living and working environments on people’s perceived stress during the pandemic and further uncovered its underlying mechanism emphasizing a mediating role of emotion. The pilot study confirmed that the severity of the pandemic positively correlated with individuals’ level of stress. Study 1 then demonstrated that indoor green plants in people’s living environments might reduce their perceived stress during the pandemic, which is referred to as the “plant effect”. Study 2 repeated the plant effect in a field experiment conducted in a working environment and Study 3 revealed a mediating role of positive emotion. This study provides preliminary evidence for the mitigating effect of indoor green plants on individuals’ mental stress during the COVID-19 pandemic period. The indoor green plants placed in living and working environments may elicit positive emotion, which in turn reduce people’s mental stress. In addition, our results reveal that growth status of the indoor green plants affected the plant effect as well.
An Introduction to Wavelets

wavelets, wavelet transform, multiresolution analysis, nonstationary signal analysis The past ten years have seen an explosion of research in the theory of wavelets and their applications. Theoretical accomplishments include development of new bases for many different function spaces and the characterization of orthonormal wavelets with compact support. Applications span the fields of signal processing, image processing and compression, data compression, and quantum mechanics. At the present time however, much of the literature remains highly mathematical, and consequently, a large investment of time is often necessary to develop a general understanding of wavelets and their potential uses. This paper thus seeks to provide an overview of the wavelet transform from an intuitive standpoint. Throughout the paper a signal processing frame of reference is adopted.
Advanced Genetic Studies on Powdery Mildew Resistance in TGR-1551

Cucurbits powdery mildew (CPM) is one of the main limiting factors of melon cultivation worldwide. Resistance to races 1, 2, and 5 has been reported in the African accession TGR-1551, whose resistance is controlled by a dominant–recessive epistasis. The dominant and recessive quantitative trail loci (QTL) have previously been located in chromosomes 5 and 12, respectively. We used several densely genotyped BC3 families derived from the cross between TGR-1551 and the susceptible cultivar ‘Bola de Oro’ to finely map these resistance regions. The further phenotyping and genotyping of the selected BC5, BC5S1, BC5S2, BC4S1, BC4xPS, and (BC4xPS) S1 offspring allowed for the narrowing of the candidate intervals to a 250 and 381 kb region in chromosomes 5 and 12, respectively. Moreover, the temperature effect over the resistance provided by the dominant gene has been confirmed. High resolution melting markers (HRM) were tightly linked to both resistance regions and will be useful in marker-assisted selection programs. Candidate R genes with variants between parents that caused a potential modifier impact on the protein function were identified within both intervals. These candidate genes provide targets for future functional analyses to better understand the resistance to powdery mildew in melons.
MATHEMATICAL MODELLING OF BLOCH NMR TO SOLVE THE SCHRODINGER TIME DEPENDENT EQUATION

Many solutions have been propounded for Schrodinger’s equation. The application of these solutions is restricted to a few aspects of physics. One of the methods used for solving the Schrodinger equation is the Finite Difference Time Domain (FDTD) method [1]. It was used to solve numerically the Schrodinger equation for ground state and excited state eigenvalues, and eigenfunctions for a single particle in one-, two-, and three-dimensional potential wells. In the past, analytical methods which have been used to solve the Schrodinger equation are: supersymmetry [1], Nikiforov Uvarov method (NU) [3], asymptotic iteration method (AIM) [4,5], hyperviria perturbation [6], exact quantization rule (EQR) [7], perturbative formalism [8], wave function ansatz method [9], and path integral [10]. In all these methods highlighted above, none has been incorporated with the Bloch NMR to solve nuclear spin among other problems in physics and chemistry. The solution of the Schrodinger equation using the mathematical modeling of Bloch NMR has wide range of applications in many fields of physics and chemistry. It can be used for checking and improving models developed to study quantum mechanical systems, improve on the effective analysis of biological systems, analyzing spin transport, nuclear spin dynamics, improvement of the numerical methods and so on. In Sec. 2, the solution of the Schrodinger is given. In Sec. 3, the solution was validated by applying it to the harmonic solution. The energy
Gastrulation and hatch as critical thermal windows for salmonid embryo development

Climate change and impoundment increase river temperatures, shifting the bioclimatic envelope in which freshwater biota have evolved and increasing salmonid egg mortality. To mitigate this, conservation flows from reservoirs are often implemented to maintain favourable water temperatures downstream from impoundments throughout salmonid embryo development. However, as water to maintain conservation flows becomes scarcer, there is a need to understand the requirements of salmonid embryos and balance these with anthropogenic demands. This study combines a laboratory‐based and a modelling approach to test the effect of different temperatures on the survival from fertilisation to hatch of a model salmonid species. Further, the effect of dropping temperatures from high to optimal conditions at hatch—a perceived period of greater sensitivity to high temperatures—is tested. The study shows embryo mortality increases with temperature and is greatest during gastrulation and hatch. Also, embryos that experienced high temperatures during gastrulation had high mortality rates at hatch, even when hatch conditions were optimal. This indicates sublethal developmental abnormalities caused by high temperatures during gastrulation increase mortality at hatch. Therefore, to maintain high rates of salmonid embryo survival, cold water resources from reservoirs ideally will target both gastrulation and hatch developmental stages.
Examining the influence of amicus briefs and patents on information policymaking

This study traces a network of strategic power relations between a Google amicus curiae brief and patent to reveal how elite organizations influence information policymaking. The lens of actor-network theory is applied to the selected cases to trace the complex sociotechnical network of heterogeneous relations (Latour, 1993). A microanalysis reveals how information policymaking is influenced by persuasive information presented in amicus briefs and the technical disclosures described in patent claims of black box technologies (Collins, 2018; Frohmann, 1995). This study is part of a larger, mixed methods research project that analyzes over 4,000 geospatial technology patents to reveal the growing trend of inferred geospatial data production where artificial intelligence is leveraged, to demonstrate that constitutional protections for digital privacy rights must incorporate a privacy model that recognizes anonymous data production and not merely user agency to grant consent. Presently, information policy and data privacy laws are interpreted through a lens of inescapability (Tokson, 2020). This lens situates digital privacy rights within a fallible dichotomic premise that assumes clear, perpetual agency to grant or deny consent to access data. Moreover, the implications of Fourth Amendment rights are exemplified in geofence warrants—an investigative technique that searches location history to identify suspects in a geofenced region and time series in the absence of evidence. Geofence warrants have been utilized to conduct sweeping searches that collect user data of innocent people such as protesters, cyclists, and other passersby. This study offers the potential to improve policymaking to protect the rights of datafied citizens.
Analysis of Mouse Blood Serum in the Dynamics of U87 Glioblastoma by Terahertz Spectroscopy and Machine Learning

In this research, an experimental U87 glioblastoma small animal model was studied. The association between glioblastoma stages and the spectral patterns of mouse blood serum measured in the terahertz range was analyzed by terahertz time-domain spectroscopy (THz-TDS) and machine learning. The THz spectra preprocessing included (i) smoothing using the Savitsky–Golay filter, (ii) outlier removing using isolation forest (IF), and (iii) Z-score normalization. The sequential informative feature-selection approach was developed using a combination of principal component analysis (PCA) and a support vector machine (SVM) model. The predictive data model was created using SVM with a linear kernel. This model was tested using k-fold cross-validation. Achieved prediction accuracy, sensitivity, specificity were over 90%. Also, a relation was established between tumor size and the THz spectral profile of blood serum samples. Thereby, the possibility of detecting glioma stages using blood serum spectral patterns in the terahertz range was demonstrated.
Explosive desorption of icy grain mantles in dense clouds

Due to the short timescale for the accretion of free molecules on grains in dense clouds, an efficient desorption mechanism is required to replenish the gas phase material. As a possibility, the explosive desorption which may take place when the ice mantle which condenses on the grain is heated sufficiently to release its potential chemical energy is investigated. At the low temperatures of interstellar grains (∼10 K), such energy can be stored in the form of frozen free radicals when the ice is photolysed by UV radiation. To study the efficiency of this desorption process, a laboratory investigation of the photochemical storage of free radicals in astrophysical ice analogues and of the sublimation upon the explosive energy release which occurred when the irradiated ice was rapidly heated were made.
MAGNETIC ANALYSIS OF ATOMIC AND MOLECULAR BEAMS. I. CONSTRUCTION AND CALIBRATION OF INHOMOGENEOUS DEFLECTING MAGNETS

Three small iron-core electromagnets have been constructed for experinients in magnetic analysis of atomic and molecular beams. The magnets and their characteristics are described, and measurements of their efficiency by examination of the flux through the air gap and various cross sections of the magnet yoke as a function of the energizing current are made. One magnet displays a peak induction at the gap midpoint of 15 Kgauss with a transverse gradient of 90 Kgauss/cm. Corresponding values for the other two are 10 Kgauss and 30 Kgauss/cm. (D.C.W.)
Power to Detect Moderated Effects in Studies with Three-Level Partially Nested Data

Abstract Comprehensive evaluation of treatment effects is aided by considerations for moderated effects. In educational research, the combination of natural hierarchical structures and prevalence of group-administered or shared facilitator treatments often produces three-level partially nested data structures. Literature details planning strategies for a variety of experimental designs when moderation effects are of interest but has yet to establish power formulas for detecting moderation effects in three-level partially nested designs. To address this gap, we derive and assess the accuracy of power formulas for detecting the different types of moderation effects possible in these designs. Using Monte Carlo simulation studies, we probe power rates and adequate sample sizes for detecting the different moderation effects while varying common influential factors including variance in the outcome explained by covariates, magnitude of the moderation effect, and sample sizes. The power formulas developed improve the planning of experimental studies with partial nesting and encourage the inclusion of moderator variables to capture for whom and under what conditions a treatment is effective. Educational researchers also have some initial guidance regarding adequate sample sizes and the factors that influence detecting moderation effects in three-level partially nested designs.
Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review

Sensorless control of permanent magnet synchronous motors is nowadays used in many industrial, home and traction applications, as it allows the presence of a position sensor to be avoided with benefits for the cost and reliability of the drive. An estimation of the rotor position is required to perform the field-oriented control (FOC), which is the most common control scheme used for this type of motor. Many algorithms have been developed for this purpose, which use different techniques to derive the rotor angle from the stator voltages and currents. Among them, the so-called passive methods have gained increasing interest as they do not introduce additional losses and current distortion associated instead with algorithms based on the injection of high-frequency signals. The aim of this paper is to present a review of the main passive sensorless methods proposed in the technical literature over the last few years, analyzing their main features and principles of operation. An experimental comparison among the most promising passive sensorless algorithms is then reported, focusing on their performance in the low-speed operating region.
Water Consumption during COVID-19 Pandemic: Trend Analyses in Puglia (Southern Italy)

The COVID-19 pandemic has affected water consumption due to the Italian government's stay-at-home orders to reduce virus spread. Thanks to a complete dataset (hourly water demand for 2019, 2020, and 2021) related to five Apulian towns, there were observed different trends in water consumption during the pandemic period compared with the pre-pandemic one, having previously excluded other possible influencing factors. There is a marked reduction in areas characterised by a high number of collective activities, less evident where the economy is mainly based on agriculture or summer tourism, highlighting that the water consumption by collective activities is significant.