Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review of Recent Advancements in Face Recognition Systems

— Face recognition technology has made significant advancements in recent years. It is quite convenient and simple to capture facial features even from a long distance since it offers a non-contact process. Also, it is now widely accepted that facial features are a highly effective way of identifying individuals, surpassing other biometric measures like fingerprints, which require contact sensors. However, false match and false non-match errors in face recognition systems are challenging since they significantly drop the performance accuracy. Researchers currently concentrate on enhancing accuracy by refining feature extraction and pre-processing algorithms. Deep learning using neural networks with multiple layers to learn complex and high-level features from data has made remarkable contributions to Computer Vision. Since face recognition technology is widely used in areas like law enforcement and surveillance, precision and performance need to be the top priorities. This paper examines and analyzes various face recognition systems, including RPRV, LWKPCA, SVM Model, LTrP-based SPM, SynFace, AdaFace, and a deep learning framework for recognizing images from CCTV. The methods involved, design feasibility, implementation details, and performance evaluation of each model are compared to determine the best approach for future development.
Optical trapping of Au-Fe alloyed nanoparticles: a theoretical calculation

Magnetoplasmonic nanoparticles, such as Au-Fe alloys, are very interesting for their properties. In this article, the optical trapping of Au-Fe nanoparticles are investigated as a function of Fe atomic percent doped in gold nanoparticles, theoretically. Using a generalized Lorenz–Mie theory, it is shown that the maximum force exerted on the alloyed nanoparticles enhances about 75% with increasing Fe atomic percent. It is shown that the trapping strength is depth-dependent and shows a 20% increment in shallow positions and a 17% decrement in the axial direction in the optimal depth, which is 7 μ m deep inside the sample. Wavelength dependence of alloyed nanoparticles is studied too.
Harnessing Skyrmion Hall Effect by Thickness Gradients in Wedge-Shaped Samples of Cubic Helimagnets

The skyrmion Hall effect, which is regarded as a significant hurdle for skyrmion implementation in thin-film racetrack devices, is theoretically shown to be suppressed in wedge-shaped nanostructures of cubic helimagnets. Under an applied electric current, ordinary isolated skyrmions with the topological charge 1 were found to move along the straight trajectories parallel to the wedge boundaries. Depending on the current density, such skyrmion tracks are located at different thicknesses uphill along the wedge. Numerical simulations show that such an equilibrium is achieved due to the balance between the Magnus force, which instigates skyrmion shift towards the wedge elevation, and the force, which restores the skyrmion position near the sharp wedge boundary due to the minimum of the edge–skyrmion interaction potential. Current-driven dynamics is found to be highly non-linear and to rest on the internal properties of isolated skyrmions in wedge geometries; both the skyrmion size and the helicity are modified in a non-trivial way with an increasing sample thickness. In addition, we supplement the well-known theoretical phase diagram of states in thin layers of chiral magnets with new characteristic lines; in particular, we demonstrate the second-order phase transition between the helical and conical phases with mutually perpendicular wave vectors. Our results are useful from both the fundamental point of view, since they systematize the internal properties of isolated skyrmions, and from the point of view of applications, since they point to the parameter region, where the skyrmion dynamics could be utilized.
Two “Edges” in Our Knowledge on the Functions of Ribosomal Proteins: The Revealed Contributions of Their Regions to Translation Mechanisms and the Issues of Their Extracellular Transport by Exosomes

Ribosomal proteins (RPs), the constituents of the ribosome, belong to the most abundant proteins in the cell. A highly coordinated network of interactions implicating RPs and ribosomal RNAs (rRNAs) forms the functionally competent structure of the ribosome, enabling it to perform translation, the synthesis of polypeptide chain on the messenger RNA (mRNA) template. Several RPs contact ribosomal ligands, namely, those with transfer RNAs (tRNAs), mRNA or translation factors in the course of translation, and the contribution of a number of these particular contacts to the translation process has recently been established. Many ribosomal proteins also have various extra-ribosomal functions unrelated to translation. The least-understood and -discussed functions of RPs are those related to their participation in the intercellular communication via extracellular vesicles including exosomes, etc., which often carry RPs as passengers. Recently reported data show that such a kind of communication can reprogram a receptor cell and change its phenotype, which is associated with cancer progression and metastasis. Here, we review the state-of-art ideas on the implications of specific amino acid residues of RPs in the particular stages of the translation process in higher eukaryotes and currently available data on the transport of RPs by extracellular vesicles and its biological effects.
Reduced Tie2 in Microvascular Endothelial Cells Is Associated with Organ-Specific Adhesion Molecule Expression in Murine Health and Endotoxemia

Endothelial cells (ECs) in the microvasculature in organs are active participants in the pathophysiology of sepsis. Tyrosine protein kinase receptor Tie2 (Tek; Tunica interna Endothelial cell Kinase) is thought to play a role in their inflammatory response, yet data are inconclusive. We investigated acute endotoxemia-induced changes in the expression of Tie2 and inflammation-associated endothelial adhesion molecules E-selectin and VCAM-1 (vascular cell adhesion molecule-1) in kidneys and lungs in inducible, EC-specific Tie2 knockout mice. The extent of Tie2 knockout in healthy mice differed between microvascular beds, with low to absent expression in arterioles in kidneys and in capillaries in lungs. In kidneys, Tie2 mRNA dropped more than 70% upon challenge with lipopolysaccharide (LPS) in both genotypes, with no change in protein. In renal arterioles, tamoxifen-induced Tie2 knockout was associated with higher VCAM-1 protein expression in healthy conditions. This did not increase further upon challenge of mice with LPS, in contrast to the increased expression occurring in control mice. Also, in lungs, Tie2 mRNA levels dropped within 4 h after LPS challenge in both genotypes, while Tie2 protein levels did not change. In alveolar capillaries, where tamoxifen-induced Tie2 knockout did not affect the basal expression of either adhesion molecule, a 4-fold higher E-selectin protein expression was observed after exposure to LPS compared to controls. The here-revealed heterogeneous effects of absence of Tie2 in ECs in kidney and lung microvasculature in health and in response to acute inflammatory activation calls for further in vivo investigations into the role of Tie2 in EC behavior.
Liver-Support Therapies in Critical Illness—A Comparative Analysis of Procedural Characteristics and Safety

Extracorporeal liver-support therapies remain controversial in critically ill patients, as most studies have failed to show an improvement in outcomes. However, heterogeneous timing and inclusion criteria, an insufficient number of treatments, and the lack of a situation-dependent selection of available liver-support modalities may have contributed to negative study results. We retrospectively investigated the procedural characteristics and safety of the three liver-support therapies CytoSorb, Molecular Adsorbent Recirculating System (MARS) and therapeutic plasma exchange (TPE). Whereas TPE had its strengths in a shorter treatment duration, in clearing larger molecules, affecting platelet numbers less, and improving systemic coagulation and hemodynamics, CytoSorb and MARS were associated with a superior reduction in particularly small protein-bound and water-soluble substances. The clearance magnitude was concentration-dependent for all three therapies, but additionally related to the molecular weight for CytoSorb and MARS therapy. Severe complications did not appear. In conclusion, a better characterization of disease-driving as well as beneficial molecules in critically ill patients with acute liver dysfunction is crucial to improve the use of liver-support therapy in critically ill patients. TPE may be beneficial in patients at high risk for bleeding complications and impaired liver synthesis and hemodynamics, while CytoSorb and MARS may be considered for patients in whom the elimination of smaller toxic compounds is a primary objective.
Intrinsic negative variance components: case of non-normal functions of random variables

Studies from https://doi.org/10.6084/m9.figshare. 3840753 and http://doi.org/10.6084/m9.figshare. 3978087 are here extended to include the possibility that stochastic physical parameters (i.e., parameters that are functions of random variables) may not be normally distributed in general. It is shown that such parameters would possess at least two intrinsic negative variance components that are always negative for regression models that apply a second-degree Taylor series. Plausible implications of their impact on the random effects ANOVA model are discussed.
2 kW pump-light-stripper-free distributed side-coupled cladding-pumped fiber oscillator

A 2 kW pump-light-stripper-free all-fiber distributed-pumping oscillator fabricated with the distributed side-coupled cladding-pumped Yb-doped fiber is demonstrated for the first time, to the best of our knowledge. An output power of 1969 W with a slope efficiency of 72.2% is obtained. By utilizing the final-section counter-pumping scheme, pure output spectra free from residual pump light are obtained without using any pump light stripper, which demonstrates that the pump light stripper is not indispensable for this configuration. Besides, no stimulated Raman scattering component is observed in the output spectra. The laser has the M2 factor ranging from 2.0 to 2.6. We believe that the pertinent results are helpful and valuable for designing high-power fiber laser systems.
Fourth Order Moment Statistical Characteristic of the Laser Pulse Scattering on One-dimensional Random Rough Surface

Abstract| The fourth order moment statistical characteristic of the pulse wave scatteringon one-dimensional random rough surfaces is investigated numerically and presented based onKirchhoﬁ’s approximation in detail. As a special application, the fourth order moment (FOM)is simpliﬂed to get the two positions and two frequencies mutual correlation function of the pulsewave scattering on random rough surfaces. Which the distributions of FOM change with thecoherence bandwidth frequency diﬁerence and scattering angles in diﬁerent incidence angles, themean of °uctuating heights and coherent length on the random rough surface is computed. Thenumerical results show that the mean of °uctuating heights and coherent length of random roughsurfaces have an important eﬁect on the value of the FOM. Generally, the largest scattering valueand smallest coherence bandwidth of the FOM occur at the specular directions. That is to say,the FOM will have a lower coherent component and its distributions of scattering angles will bebroadened in relation to the rugged surface. At same time, the FOM decreased rapidly as therewas a bigger coherence bandwidth frequency diﬁerence. 1. INTRODUCTION
Exploring the Test Driven Development of an Information Retrieval System

: Today’s society is heavily driven by data intensive systems, whose application promises immense benefits. However, this only applies when they are utilized correctly. Yet these types of applications are highly susceptible to errors. Consequently, it is necessary to test them comprehensively and rigorously. One method that has an especially high focus on test coverage is the test driven development (TDD) approach. While it generally has a rather long history, its application in the context of data intensive systems is still somewhat novel. Though, rather recently, a microservice-based test driven development concept has been proposed for the big data domain. The publication at hand explores its feasibility regarding the application in an actual project. For this purpose, a prototypical, microservice based information retrieval system is implemented in a test driven way with particular consideration for scalability.
Detecting Misleading Headlines Through the Automatic Recognition of Contradiction in Spanish

Misleading headlines are part of the disinformation problem. Headlines should give a concise summary of the news story helping the reader to decide whether to read the body text of the article, which is why headline accuracy is a crucial element of a news story. This work focuses on detecting misleading headlines through the automatic identification of contradiction between the headline and body text of a news item. When the contradiction is detected, the reader is alerted to the lack of precision or trustworthiness of the headline in relation to the body text. To facilitate the automatic detection of misleading headlines, a new Spanish dataset is created (ES_Headline_Contradiction) for the purpose of identifying contradictory information between a headline and its body text. This dataset annotates the semantic relationship between headlines and body text by categorising the relation between texts as compatible, contradictory and unrelated. Furthermore, another novel aspect of this dataset is that it distinguishes between different types of contradictions, thereby enabling a more fine-grain identification of them. The dataset was built via a novel semi-automatic methodology, which resulted in a more cost-efficient development process. The results of the experiments show that pre-trained language models can be fine-tuned with this dataset, producing very encouraging results for detecting incongruency or non-relation between headline and body text.
Allosteric Mechanism of Calmodulin Revealed by Targeted Molecular Dynamics Simulation

Calmodulin (CaM) is involved in the regulation of a variety of cellular signaling pathways. To accomplish its physiological functions, CaM binds with Ca2+ at its EF-hand Ca2+ binding sites which induce the conformational switching of CaM. However, the molecular mechanism by which Ca2+ binds with CaM and induces conformational switching is still obscure. Here we combine molecular dynamics with targeted molecular dynamics simulation and achieve the state-transition pathway of CaM. Our data show that Ca2+ binding speeds up the conformational transition of CaM by weakening the interactions which stabilize the closed state. It spends about 6.5 ns and 5.25 ns for transition from closed state to open state for apo and holo CaM, respectively. Regarding the contribution of two EF-hands, our data indicate that the first EF-hand triggers the conformational transition and is followed by the second one. We determine that there are two interaction networks which contribute to stabilize the closed and open states, respectively.
Curvature and inference for maximum likelihood estimates

Maximum likelihood estimates are sufficient statistics in exponential families, but not in general. The theory of statistical curvature was introduced to measure the effects of MLE insufficiency in one-parameter families. Here we analyze curvature in the more realistic venue of multiparameter families—more exactly, curved exponential families, a broad class of smoothly defined non-exponential family models. We show that within the set of observations giving the same value for the MLE, there is a " region of stability " outside of which the MLE is no longer even a local maximum. Accuracy of the MLE is affected by the location of the observation vector within the region of stability. Our motivating example involves " g-modeling " , an empirical Bayes estimation procedure. 1. Introduction. In multiparameter exponential families, the maximum likelihood estimate (MLE) for the vector parameter is a sufficient statistic. This is no longer true in non-exponential families. Fisher (1925, 1934) argued persuasively that in this case data sets yielding the same MLE could differ greatly in their estimation accuracy. This effect was examined in Efron (1975, 1978), where " statistical curvature " was introduced as a measure of non-exponentiality. One-parameter families were the only ones considered there. The goal of this paper is to quantitatively examine curvature effects in multiparameter families— more precisely, in multiparameter curved exponential families, as defined in Section 2. Figure 1 illustrates a toy example of our situation of interest. Independent Poisson random variables have been observed,
A non-inverting single-switch buck-boost converter based LED driver

This paper focuses on a single-switch buck-boost (SSBB) converter for light emitting diode (LED) lighting applications. The proposed LED driver with power factor correction (PFC) shows enhanced performance in terms of input power factor, efficiency and reduced voltage stress across the switch. The presented LED driver is operated in discontinuous conduction mode (DCM). The input PFC is carried out using average current mode control (ACMC) and the controller is optimized using artificial bee colony (ABC) algorithm. A hardware prototype of 50W LED driver with ACMC for PFC is implemented using a programmable interface circuit (PIC) microcontroller. The experimental results are presented and the performance is compared with a conventional buck boost LED driver. The proposed SSBB LED driver achieves an input power factor of 0.96 with an efficiency of 98%.
The Principal-Agent Model with a Continuum of Constraints: The Infinite-Dimensional Approach

This paper is a survey about the existence of optimal contract mechanisms in the principal- agent problems with moral hazard and adverse selection under a continuum of individual rationality and incentive compatibility constraints. It presents the main existing results under a unified notation, shows explicitly in what sense they are particular cases of the general model presented in Balder (JET, 68 (1996): 133-148), and provides a simple method (the model machine) to construct new models within the infinite dimensional approach.
Real-Time Fault Diagnosis of Motor Bearing via Improved Cyclostationary Analysis Implemented onto Edge Computing System

Rolling bearing is a key component inside a motor, and its health status directly affects the operational reliability of the motor. Therefore, it is absolutely necessary to conduct research on bearing fault diagnosis. Most of the recent bearing fault diagnosis algorithms are implemented on a desktop/server, which might not satisfy the real-time diagnosis requirement in industrial fields. In this study, an improved cyclostationary analysis algorithm is proposed and implemented onto an edge-computing system to diagnose a motor fault in real time. Considering the traditional contact test methods based on vibration signals are difficult to carry out under complex working environments, the sound signal is collected as the analysis object. Guided by cyclostationary theory, an improved cyclic feature enhancement algorithm is proposed and applied to the acquired signal to extract the distinct features related to the bearing faults. The simulation signal is constructed and analyzed first to verify the superiority of the improved algorithm. Subsequently, experimental fault data is further analyzed to demonstrate the advantages of the proposed method. Furthermore, the proposed algorithm is deployed onto an edge-computing system based on a microcontroller unit. The online diagnosis result can be directly observed through an external display. The edge computing system with the embedded algorithm shows great potential in motor real-time fault diagnosis and intelligent maintenance.
Phantom study to determine optimal PET reconstruction parameters for PET/MR imaging of 90Y microspheres following radioembolization

Yttrium-90 (90Y) radioembolization involves the intra-arterial delivery of radioactive microspheres for treating liver tumors. Although primarily a β− emitter, 90Y occasionally emits positrons via internal pair production. There is growing interest in positron emission tomography (PET) imaging of these microspheres following radioembolization to localize and quantify their distribution. Due to the low abundance of positron emission (0.0032%), the PET images are highly sensitive to the parameters of iterative reconstruction algorithms used in clinical PET imaging. In this study, we aim to determine the optimal 90Y PET reconstruction parameters for PET/MRI that provide maximal activity recovery while maintaining a moderate noise level. We imaged an ACR phantom filled with 90Y chloride solution on two Siemens Biograph mMR scanners with a total activity of 1.00 GBq–7.43 GBq. Images were reconstructed with varying iteration number, post-reconstruction filter size, and scatter correction method. In addition, we evaluated the effects of incorporating point spread function (PSF) compensation as well as reducing the scan time and imaging off the central axis of the scanner in order to simulate realistic patient acquisition protocols as closely as possible. Recovery coefficients (RCs) for hot cylinders 8–25 mm in diameter reached near convergence with limited noise at 3 iterations, 21 subsets, 5 mm FWHM Gaussian post-reconstruction filter, use of PSF compensation, and absolute scatter correction across all scans. RCs increased by as much as 17% and noise decreased by as much as 29% when scan time duration was 30 min compared to only 15 min. Images acquired with the phantom placed 7–10 cm off the central axis of the scanner exhibited slightly reduced RCs, especially for the lowest activity scan. Although optimal reconstruction parameters with current reconstruction software were determined in this study, these parameters failed to achieve perfect count recovery, suggesting further investigation of 90Y PET imaging is required.
Insertion of triangulated surfaces into a meccano tetrahedral discretization by means of mesh refinement and optimization procedures

In this paper, we present a new method for inserting several triangulated surfaces into an existing tetrahedral mesh generated by the meccano method. The result is a conformal mesh where each inserted surface is approximated by a set of faces of the final tetrahedral mesh. First, the tetrahedral mesh is refined around the inserted surfaces to capture their geometric features. Second, each immersed surface is approximated by a set of faces from the tetrahedral mesh. Third, following a novel approach, the nodes of the approximated surfaces are mapped to the corresponding immersed surface. Fourth, we untangle and smooth the mesh by optimizing a regularized shape distortion measure for tetrahedral elements in which we move all the nodes of the mesh, restricting the movement of the edge and surface nodes along the corresponding entity they belong to. The refining process allows approximating the immersed surface for any initial meccano tetrahedral mesh. Moreover, the proposed projection method avoids computational expensive geometric projections. Finally, the applied simultaneous untangling and smoothing process delivers a high‐quality mesh and ensures that the immersed surfaces are interpolated. Several examples are presented to assess the properties of the proposed method.