Miracle-dz/UniFAR-FTUs huggingface dataset:
RSSI Fingerprint Height Based Empirical Model Prediction for Smart Indoor Localization

Smart indoor living advances in the recent decade, such as home indoor localization and positioning, has seen a significant need for low-cost localization systems based on freely available resources such as Received Signal Strength Indicator by the dense deployment of Wireless Local Area Networks (WLAN). The off-the-shelf user equipment (UE’s) available at an affordable price across the globe are well equipped with the functionality to scan the radio access network for hearable single strength; in complex indoor environments, multiple signals can be received at a particular reference point with no consideration of the height of the transmitter and possible broadcasting coverage. Most effective fingerprinting algorithm solutions require specialized labor, are time-consuming to carry out site surveys, training of the data, big data analysis, and in most cases, additional hardware requirements relatively increase energy consumption and cost, not forgetting that in case of changes in the indoor environment will highly affect the fingerprint due to interferences. This paper experimentally evaluates and proposes a novel technique for Received Signal Indicator (RSSI) distance prediction, leveraging transceiver height, and Fresnel ranging in a complex indoor environment to better suit the path loss of RSSI at a particular Reference Point (RP) and time, which further contributes greatly to indoor localization. The experimentation in different complex indoor environments of the corridor and office lab during work hours to ascertain real-life and time feasibility shows that the technique’s accuracy is greatly improved in the office room and the corridor, achieving lower average prediction errors at low-cost than the comparison prediction algorithms. Compared with the conventional prediction techniques, for example, with Access Point 1 (AP1), the proposed Height Dependence Path–Loss (HEM) model at 0 dBm error attains a confidence probability of 10.98%, higher than the 2.65% for the distance dependence of Path–Loss New Empirical Model (NEM), 4.2% for the Multi-Wall dependence on Path-Loss (MWM) model, and 0% for the Conventional one-slope Path-Loss (OSM) model, respectively. Online localization, amongst the hearable APs, it is seen the proposed HEM fingerprint localization based on the proposed HEM prediction model attains a confidence probability of 31% at 3 m, 55% at 6 m, 78% at 9 m, outperforming the NEM with 26%, 43%, 62%, 62%, the MWM with 23%, 43%, 66%, respectively. The robustness of the HEM fingerprint using diverse predicted test samples by the NEM and MWM models indicates better localization of 13% than comparison fingerprints.
Preharvest Application of Salicylic Acid, Calcium Acetate and Proline for Improving Fruit Quality and Shelf Life of “Early Swelling” Peaches

T HE effects of preharvest foliar application of salicylic acid, calcium acetate and proline alone or in combinations on fruit quality and storability of “Early Sweet” peaches cultivar were investigated during 2020 and 2021 seasons. The results showed that preharvest application of all treatments increased fruit flesh firmness as compared with control treatment. Salicylic acid treatment increased fruit weight, size and diameter. Moreover, decreased total sugars and fruit weight loss after storage. The results also showed that, calcium acetate treatment enhanced physical and chemical properties of fruits especially fruit firmness before and after harvest. Proline treatment increased fruit weight, fruit diameter, flesh firmness , TSS, peel anthocyanin content and total sugars. Furthermore, decreased fruit acidity and weight loss after storage on room temperature. In conclusion, the results of the present study recommended using the combination of salicylic acid plus calcium acetate and proline to enhance fruit quality and shelf life of peaches.
A Comprehensive Investigation into the Application of Convolutional Neural Networks (ConvNet/CNN) in Smart Grids

The Convolutional Neural Network (CNN) methodologies have been a fundamental deep learning solution to smart grid applications. It is essential to investigate and evaluate the progress of this method in the smart grid. Consequently, a comprehensive investigation with the aid of PRISMA had been conducted. The PRISMA standard queries including the CNNs and its abbreviation forms of ConvNet or CNN reveal a significant increase in the popularity of this deep learning method in smart grid applications. This research identifies 2200 pieces of literature in the field. After considering the PRISMA guideline the most relevant and fundamental application had been reduced to 46 documents where the single and hybrid methods had been identified. The investigation showed that hybrid methods delivered a better performance with higher accuracy. It is expected that more hybrid methods will have emerged in the smart grid application.
Representing convex geometries by almost-circles

Finite convex geometries are combinatorial structures. It follows from a recent result of M. Richter and L. G. Rogers that there is an infinite set TRR of planar convex polygons such that T^RR with respect to geometric convex hulls is a locally convex geometry and every finite convex geometry can be represented by restricting the structure of T^RR to a finite subset in a natural way. For a (small) nonnegative ɛ < 1, a differentiable convex simple closed planar curve S will be called an almost-circle of accuracy 1 − ɛ if it lies in an annulus of radii 0 < r ^1 ≤ r ^2 such that r _1/ r ^2 ≥ 1 − ɛ . Motivated by Richter and Rogers’ result, we construct a set T ^new such that (1) T ^new contains all points of the plane as degenerate singleton circles and all of its non-singleton members are differentiable convex simple closed planar curves; (2) T ^new with respect to the geometric convex hull operator is a locally convex geometry; (3) T ^new is closed with respect to non-degenerate affine transformations; and (4) for every (small) positive ɛ ∈ R and for every finite convex geometry, there are continuum many pairwise affine-disjoint finite subsets E of T ^new such that each E consists of almost-circles of accuracy 1 − ɛ and the convex geometry in question is represented by restricting the convex hull operator to E. The affine-disjointness of E^1 and E^2 means that, in addition to E^1 ∩ E^2 = ∅, even ψ(E1) is disjoint from E^2 for every non-degenerate affine transformation ψ.
Study of the Drivers of Inappropriate Use of Antibiotics in Community Pharmacy: Request for Antibiotics Without a Prescription, Degree of Adherence to Treatment and Correct Recycling of Leftover Treatment

Introduction The WHO considered antibiotic resistance as 1 of the 10 greatest threats to global health in 2019. The inappropriate and indiscriminate use of antibiotics, together with the lack of new therapeutic alternatives, may eradicate their effectiveness in the closest future. Objective The general objective is to analyze the different causes attributable to patients, providers and pharmacists that could be drivers of irrational use of antibiotics, and responsible for the appearance of bacterial resistance, in community pharmacies. To this end, the different processes or indicators were studied: patients’ requests of antibiotics at the pharmacy, their degree of adherence, satisfaction with the prescribed treatment and antibiotics’ surplus recycling. Methods This study was observational, descriptive, and cross-sectional, carried out in 2 pharmacy offices, including 333 participants. At the time of dispensing, first phase, surveys to collect patients’, providers’ and pharmacists’ data were carried out over the counter. The second phase, with the aim of checking adherence, degree of satisfaction and recycling. Results There were 333 requests for antibiotic regardless prescription availability, 17% of the patients requested an antibiotic without having one. 38% of patients did not have full adherence to antibiotics. Exploring non-adherence reasons, 24% forgot to take the treatment, 2% experienced adverse effects; 8% improved infection symptoms and 21% had problems to follow schedule. Regarding the recycling habits, 57% of patients had leftover treatments at home, but only 11% recycled it. 10% of medical prescriptions were forced by the patient, and significant gender differences were observed in adherence and knowledge of treatment. Conclusion The results of this study suggested that there may be a significant level of antibiotic inappropriate use locally, potentially related to patients’ sex, finding significant deficiencies in prescription by doctors, in the dispensing act carried out in community pharmacies, and finally in patient compliance with treatment.
Exact solution to the Dirichlet problem for degenerating on the boundary elliptic equation of Tricomi-Keldysh type in the half-space

In the paper by means of Fourier transform method and similarity method we solve the Dirichlet problem for a multidimensional equation wich is a generalization of the Tricomi, Gellerstedt and Keldysh equations in the half-space, in which equation have elliptic type, with the boundary condition on the boundary hyperplane where equation degenerates.The solution is presented in the form of an integral with a simple kernel which is an approximation to the identity and self-similar solution of Tricomi-Keldysh type equation . In particular, this formula contains a Poisson's formula, which gives the solution of the Dirichlet problem for the Laplace equation for the half-space. If the given boundary value is a generalized function of slow growth, the solution of the Dirichlet problem can be written as a convolution of this function with the kernel (if a convolution exists).
Reply to Ackermann

(R-2): If two thinkable (i.e., supported, unviolated, and unexhausted hypotheses, K and L, are such that, (1) Their consequent predicates denote the same class of individuals; (2) The antecedent predicate of K is not as well-entrenched as the antecedent predicate of L; (3) The evidence class for K is contained in (or identical with) the evidence class for L; and (4) The projective class of K contains some individuals not in the projective class of L; then K is to be rejected on the grounds that it is not presumptively projectible.
A method of plane geometry primitive presentation

Point feature and line feature are basic elements in object feature sets, and they play an important role in object matching and recognition. On one hand, point feature is sensitive to noise; on the other hand, there are usually a huge number of point features in an image, which makes it complex for matching. Line feature includes straight line segment and curve. One difficulty in straight line segment matching is the uncertainty of endpoint location, the other is straight line segment fracture problem or short straight line segments joined to form long straight line segment. While for the curve, in addition to the above problems, there is another difficulty in how to quantitatively describe the shape difference between curves. Due to the problems of point feature and line feature, the robustness and accuracy of target description will be affected; in this case, a method of plane geometry primitive presentation is proposed to describe the significant structure of an object. Firstly, two types of primitives are constructed, they are intersecting line primitive and blob primitive. Secondly, a line segment detector (LSD) is applied to detect line segment, and then intersecting line primitive is extracted. Finally, robustness and accuracy of the plane geometry primitive presentation method is studied. This method has a good ability to obtain structural information of the object, even if there is rotation or scale change of the object in the image. Experimental results verify the robustness and accuracy of this method.
Research on line spectrum extraction based on improved discrete particle swarm

The extraction path of the weak line spectrum in the LOFAR spectrogram under low signal-to-noise ratio conditions is typically about NP-hard combinatorial optimization, which is crucial to determine the motion characteristics of the target. Classical particle swarm optimization (PSO) algorithms have continuous optimization problems, and in this paper, a set-based algorithm for line spectrum extraction of improved discrete particle swarm (S-PSO-LSE) is proposed. The algorithm treats the discrete search space as a point set defined by each path node, while updating the definition of the operator on the set, and a new fitness function is proposed as a line spectrum quality standard. This increases the convergence accuracy for searching the line spectrum, improves the convergence rate, and provides good global search capability. The effectiveness and accuracy of the algorithm for weak line spectra are verified by simulation and sea trial data.
Implementation of a Nurse-Delivered Cognitive Behavioral Therapy for Adherence and Depression of People Living with HIV in Korea

Background Cognitive behavioral therapy for adherence and depression (CBT-AD) performed by clinical psychologists is an effective treatment for improving the depression in people living with HIV (PLWH). However, because access to clinical psychologists is limited in most clinics, CBT-AD is rarely performed for PLWH in Korea. This pilot study evaluates whether CBT-AD can be effectively performed by a nurse trained and supervised by a clinical psychologist, with a view to the wider provision of CBT-AD. Materials and Methods One clinical psychologist developed manuals, educated and supervised one nurse. PLWH with depression or adherence to self-reported antiretroviral therapy <90% were enrolled, and CBT-AD was conducted once weekly for 12 sessions. PLWH were assessed for adherence by visual analog scale, Beck depression inventory (BDI) for depression, PozQoL for quality of life, and Berger’s 40-item stigma scale for stigma at baseline, after the 6th, 12th session, at 4-, and 8-months after CBT-AD. Acceptability for PLWH and feasibility for providers were evaluated through surveys. Results Five male PLWH have completed the study protocols (mean age 29.2 years). All study participants showed improving depression (mean BDI at baseline 33.0 ± 7.0, and after the 12th session 13.4 ± 3.5), and the effect was maintained at the 8-month follow-up (BDI 15.4 ± 6.4). Quality of life showed a tendency to improve (mean PozQoL at baseline 28.0 ± 7.7, after 12th session 36.8 ± 4.4, and at the 8-month follow-up 38.2 ± 7.9), but stigma did not show clear improvement (Berger’s 40-item stigma scale at baseline 121.0 ± 3.9, after 12th session 107.6 ± 8.8. and at the 8-month follow-up 107.6 ± 5.0). All study participants received great help from CBT-AD and expressed their desire to continue. All providers agreed that nurse-delivered CBT-AD could be implemented in routine clinical practice. Conclusion Our findings suggest that a nurse-delivered CBT-AD could be feasible and acceptable for PLWH through structured interventions. It has been shown to have the potential to help PLWH, especially for their depression and quality of life. Trial Registration ClinicalTrials.gov Identifier: NCT03823261
H\"{o}lder continuous weak solution of 2d Boussinesq equation with diffusive temperature

We show the existence of H\"{o}lder continuous periodic weak solutions of the 2d Boussinesq equation with diffusive temperature which satisfy the prescribed kinetic energy. More precisely, for any smooth $e(t):[0,1]\rightarrow R_+$ and $\varepsilon\in (0, \frac{1}{10})$, there exist $v\in C^{\frac{1}{10}-\varepsilon}([0,1]\times {\rm T}^2), \theta\in C_t^{1,\frac{1}{20}-\frac{\varepsilon}{2}}C_x^{2,\frac{1}{10}-\varepsilon}([0,1]\times {\rm T}^2)$ which solve boussinesq equation in the sense of distribution and satisfy e(t)=\int_{{\rm T}^2}|v(t,x)|^2dx, \quad \forall t\in [0,1].
Explicit calculation of Frobenius isomorphisms and Poincar\'{e} duality in the theory of arithmetic $\mathscr{D}$-modules

The aim of this paper is to compute the Frobenius structures of some cohomological operators of arithmetic $\ms{D}$-modules. To do this, we calculate explicitly an isomorphism between canonical sheaves defined abstractly. Using this calculation, we establish the relative Poincar\'{e} duality in the style of SGA4. As another application, we compare the push-forward as arithmetic $\ms{D}$-modules and the rigid cohomologies taking Frobenius into account. These theorems will lead us to an analog of "Weil II" and a product formula for $p$-adic epsilon factors.
Projector augmented-wave method: an analysis in a one-dimensional setting

In this article, a numerical analysis of the projector augmented-wave (PAW) method is presented, restricted to the case of dimension one with Dirac potentials modeling the nuclei in a periodic setting. The PAW method is widely used in electronic ab initio calculations, in conjunction with pseudopotentials. It consists in replacing the original electronic Hamiltonian H by a pseudo-Hamiltonian HPAW via the PAW transformation acting in balls around each nuclei. Formally, the new eigenvalue problem has the same eigenvalues as H and smoother eigenfunctions. In practice, the pseudo-Hamiltonian HPAW has to be truncated, introducing an error that is rarely analyzed. In this paper, error estimates on the lowest PAW eigenvalue are proved for the one-dimensional periodic Schrödinger operator with double Dirac potentials.
Newtonian limit and trend to equilibrium for the relativistic Fokker-Planck equation

The relativistic Fokker-Planck equation, in which the speed of light c appears as a parameter, is considered. It is shown that in the limit c → ∞ its solutions converge in L1 to solutions of the non-relativistic Fokker-Planck equation, uniformly in compact intervals of time. Moreover in the case of spatially homogeneous solutions, and provided the temperature of the thermal bath is sufficiently small, exponential trend to equilibrium in L1 is established. The dependence of the rate of convergence on the speed of light is estimated. Finally, it is proved that exponential convergence to equilibrium for all temperatures holds in a weighted L2 norm.
Towards a multigrid method for the minimum-cost flow problem

We present a first step towards a multigrid method for solving the min-cost flow problem. Specifically, we present a strategy that takes advantage of existing black-box fast iterative linear solvers, i.e. algebraic multigrid methods. We show with standard benchmarks that, while less competitive than combinatorial techniques on small problems that run on a single core, our approach scales well with problem size, complexity, and number of processors, allowing for tackling large-scale problems on modern parallel architectures. Our approach is based on combining interior-point with multigrid methods for solving the nonlinear KKT equations via Newton's method. However, the Jacobian matrix arising in the Newton iteration is indefinite and its condition number cannot be expected to be bounded. In fact, the eigenvalues of the Jacobian can both vanish and blow up near the solution, leading to a significant slow-down of the convergence speed of iterative solvers - or to the loss of convergence at all. In order to allow for the application of multigrid methods, which have been originally designed for elliptic problems, we furthermore show that the occurring Jacobian can be interpreted as the stiffness matrix of a mixed formulation of the weighted graph Laplacian of the network, whose metric depends on the slack variables and the multipliers of the inequality constraints. Together with our regularization, this allows for the application of a black-box algebraic multigrid method on the Schur-complement of the system.
Circulating CD19 CD24hi CD38hi Regulatory B Cells Percentage in Lupus Nephritis Patients: Does It Differ?

Background : There is a debate about the functional role of regulatory B cells in the lupus nephritis (LN) pathogenesis. Objective: The aim of the present study was to analyze total B lymphocytes and their subtype regulatory B lymphocytes (Breg) % in systemic lupus erythematous (SLE) patients, in addition to assess their association with LN activity. Patients and Methods: The present study included 19 lupus nephritis (LN) patients, 11 SLE patients without lupus nephritis (non-LN). They were matched with 20 healthy individuals as a control group. LN activity was evaluated by Renal SLEDAI (rSLEDAI), nephritis patients were divided into active lupus nephritis (renal SLEDAI≥4) and non-active lupus nephritis patients (renal SLEDAI = 0). Full history taking, clinical examination and baseline laboratory investigations were done for all participants. Total B lymphocytes and their subtypes Breg were measured by flow cytometry. Results: SLE diseased patients have significantly higher total B lymphocytes compared to matched controls; also, SLE diseased patients (LN and non-LN) have significantly lower CD19+ CD24 hi CD38 hi compared to matched controls, regardless of LN activity. Conclusion: The present study supports B cell and Breg role in aetio-pathogenesis of SLE and also contributes to the onset of LN which indicates a dysfunctional regulatory mechanism.
Regression Diagnostics

Gauging the robustness of regression estimates is especially important in small-sample analyses. Here, we examine recent developments in the detection and analysis of outliers and influential cases in multivariate studies. Specifically, we review five diagnostic procedures: partial regression plots, the “hat” matrix, studentized residuals, DFITSi, and DFBETASij. The main part of the article presents two empirical applications (drawn from recent cross-national studies) that show (a) how the diagnostic procedures can be incorporated into the research process, and (b) what we can learn from them. These applications serve to underscore the point that the diagnostics cannot be employed mechanically. Instead, once a case is diagnosed as influential, remedial action requires a firm substantive grounding. Although case deletion may be warranted in some circumstances, it is an extreme remedy of last resort that should not be routinely followed. The more fruitful approach is to ask why a given case is influential. As our applications indicate, the diagnostics can be helpful in isolating such problems as sample composition, specification error, and errors in measurement.
Measuring particle-substrate distance with surface plasmon resonance microscopy

Because of its high sensitivity, surface plasmon resonance (SPR) has been used to measure the optical properties of thin films. Surface plasmon resonance microscopy (SPRM) has been developed as a tool to image the two-dimensional architecture of thin films. The method can be used as a non-invasive tool for imaging cells on a surface. In this paper SPRM has been used to image latex spheres immobilized on a gold surface. We show that it is possible to calculate the distance between the sphere and the surface in two dimensions by capturing an image at one fixed angle. This technique obviates the need for the traditional angle-scanning system. We show how a map of the particle-substrate gap can be reconstructed directly from a single SPR intensity image. Such a technique could be applied to measure the contact distance between a living cell and a substrate in real time.
Chaotic behavior in piecewise linear Linz–Sprott equations

This paper presents the first rigorous proof of the chaotic behavior in a piecewise linear Linz-Sprott system, which is the algebraically simplest continuous three-dimensional dynamical system with chaotic behavior. The proof is computer assisted and relies on the estimation of the numerical calculation errors. The mathematical part of the proof uses topological hyperbolicity and information on the whereabouts of the periodic trajectories.