Miracle-dz/UniFAR-FTUs huggingface dataset:
Perception-reality bias: the differences in government trust across income groups

This paper first measures and compares the size of middle-income groups in China based on the subjective income evaluation method and the objective criteria. Second, it empirically investigates the differences in government trust of different income groups defined by the subjective evaluation method and the objective criteria. It is found that there is a significant difference between the results of the subjective evaluation of income and objective criteria. Compared with individuals in the middle-income group, individuals in the low-income group have a significantly worse overall evaluation of local government and a considerably lower trust in local government officials. On the other hand, individuals in the high-income group have a substantially better assessment of local government and a significantly higher trust in local government officials. However, the differences in trust in government across income groups defined by objective criteria are insignificant overall. In terms of policy insights, the effect of targeting low-income groups determined by subjective evaluation may be more effective in improving people’s trust in the government.
Optimum Solutions for Weighted Sum-Rate of NOMA and TDMA in Wireless-Powered IoT Networks

Wireless-powered Internet of Things (IoT) systems allow small IoT devices to operate without accompanying dedicated power sources. A well-known protocol for such networks utilizes the harvest and then transmit concept which involves wireless energy transfer (WET) followed by wireless information transfer (WIT). We formulate two optimization problems for wireless-powered IoT systems to maximize the weighted sum-rate for time-division multiple access (TDMA) and nonorthogonal multiple access (NOMA) by optimizing the harvesting time and transmission time variables. First, we derive semi-closed form solutions, which achieve the global optimum, for these two problems. The proposed approach is highly computationally efficient for large IoT networks. We prove that the scalar equations in both TDMA and NOMA maintain a unique solution which can be found via bisection. It is revealed that when the device’s circuit power consumption is negligible, NOMA outperforms TDMA. However, when devices consume large circuit power, TDMA is more efficient than NOMA. Numerical results determine a critical point where NOMA surpasses TDMA in weighted sum-rate if plotted versus WET transmit power. The critical point depends on the WET power, device’s circuit power consumption, conversion efficiency and saturation level of the (non)linear energy harvester, and finally the number of devices and their associated weights.
Statistical estimation in the presence of group actions

Imagine we want to recover an unknown vector given many noisy copies of it, except each copy is cyclically shifted by an unknown offset (this is “multi-reference alignment”). Or imagine we want to reconstruct an unknown 3D structure (e.g. a molecule) given many noisy pictures of it taken from different unknown angles (this is “cryo-EM”). These problems (and many others) involve the action of unknown group elements drawn randomly from a compact group such as Z/p or SO(3). In this thesis we study two statistical models for estimation in the presence of group actions. The first is the synchronization model in which we attempt to learn an unknown collection of group elements based on noisy pairwise comparisons. The second is the orbit recovery model in which we observe noisy copies of a hidden signal, each of which is acted upon by a random group element. For both of these models, we explore the fundamental statistical limits as well as the fundamental computational limits (i.e. how well can a polynomial-time algorithm perform? ). We use methods from a wide variety of areas, including statistical physics, approximate message passing, representation theory, contiguity and the associated second moment method, invariant theory, algebraic geometry, and the sum-of-squares hierarchy. Thesis Supervisor: Ankur Moitra Title: Associate Professor of Mathematics
Finite element analysis of the underslung carrier rocket effect on stress and strain distribution in a structure of the MiG-29 aircraft

The paper presents selected aspect of the analytical-conceptual research project entitled: Airborne-Rocket Launch System for Delivering Satellite Payloads into Low Earth Orbit – Feasibility Study. The aim of the project is to conduct series of aerodynamic, strength, and aeroelastic simulations of Polish aging combat aircraft (Mig-29 and Su-22) to explore applicability of both fighters as an airborne platform for carrying out carrier rockets with a detachable satellite payload. This work presents exemplary analyses in the area of airframe loads and structural strength and deformability of MiG-29 for predicted operational variants with carrier rockets put to the hardpoints under fuselage. The numerical simulations were conducted for a structural discrete model of the aircraft prepared for finite element analysis in MSC Software. Model development involved such aspects as precise discretization of geometric model, declaration of material constants, identification of structural properties, introduction of suitable merging connections for included airframe assemblies, and final validation of model mass and stiffness. The model was analyzed in MSC Nastran software with application of linear “Statics” solution. External flight loads introduced into the model were calculated for specific points of the flight envelope—the highest values of load factor were taken into consideration (n=9). The counterpart aerodynamic force distribution in a form of a set of equivalent lumped forces was calculated. Then, the aerodynamic and weight loads were added to the model as a set of forces applied to specific structural nodes. Additionally, weights of applicable carrier rockets were taken into account as concentrated forces applied to under-fuselage suspension hardpoints. Calculations were performed for several rockets of mass values between 250 and 1200 kg. Parametric dependencies were investigated as an effect of missile mass and size on stress and strain distribution over the whole structure. The areas of stress cumulations were identified. On the basis of static structural deformation, maximum wing tip displacements were assessed.
A multigrid method with local adaptive refinement, application to a ternary Cahn-Hilliard model.

The aim of this communication is to describe some numerical aspects linked to incompressible three-phase flow simulations, thanks to Cahn-Hilliard type model. The numerical capture of transfer phenomenon in the neighborhood of the interface require a mesh thickness which become crippling in the case where it is applied to the whole computational domain. This suggests the use of a local refinement method which allows to dynamically focus on problematic areas. The notion of refinement pattern, introduced for Lagrange finite elements, allows to build a conceptual hierarchy of nested conformal approximation spaces which is then used to implement the so-called CHARMS local refinement methods. Properties of these methods are proved ensuring in particular the conformity of approximation spaces at every time of simulations. Furthermore, the multilevel structure obtained by this method, is used to construct multigrid preconditioners. Finally, after a validation on a model problem, the performance of the whole method is illustrated on an example of a liquid lens spreading between two stratified fluids.
Study of the influence of the Reynolds number on the organization of wall-bounded turbulence

This work is an experimental study of the influence of the Reynolds number on the characteristics of the streamwise and spanwise vortices in near-wall turbulence. Stereo-PIV measurements in streamwise/wall-normal and spanwise/wall-normal planes of turbulent boundary layer flow are conducted in the LTRAC water-tunnel and LML wind-tunnel at six Reynolds numbers comprised between $Re_\theta=1300$ and $Re_\theta=18950$. The measurements feature good spatial resolution and low measurement uncertainty. The database is validated through an analysis of some single-points statistics (mean and RMS velocity, PDF of the fluctuations), and of the power spectra, compared with reference profiles from theory, hot-wire measurements and DNS data. A coherent structure detection is then undertaken on the SPIV database, as well as on a DNS dataset at $Re_\tau=950$. The detection is based on a fit of an Oseen vortex to the velocity field surrounding extrema of 2D swirling strength. The wall-normal evolution of some statistical quantities (mean, RMS, PDF) of the vortex characteristics (radius, vorticity, circulation, convection velocity.) is analyzed, using two different scalings: the wall-unit scaling and the Kolmogorov scaling. In wall-unit scaling, a good universality in Reynolds numbers is observed in the near-wall and logarithmic region, but some Reynolds number effects are visible in the outer region of the flow. In contrast, the Kolmogorov scaling was found to be universal both in Reynolds number and wall-normal distance across the three regions investigated. Finally, the results obtained are interpreted in terms of vortices generation mechanisms
Theoretical Investigation on Monomer and Dimers of Inhibitor of Cytochrome P450 Enzymes: 1-Aminobenzotriazole

In this research, structures and properties of monomer and two dimers (1 and 2) of inhibitor of cytochrome P450 enzymes, 1-Aminobenzotriazole (ABT) have been studied by using functional hybrid B3LYP/6-311++G** calculations. The very good correlations observed between theoretical and experimental 1H-, 13C-NMR, FT-IR and FT-Raman spectra suggest that C-H···N interactions of dimeric species should be expected in the solid phase, as was observed in the experimental crystalline structure of a quinolin benzotriazole derivative. NBO and AIM calculations suggest that dimer 2 with inverted positions of its monomers could be present in the solid phase because it evidence higher stabilities in both media. On the other hand, frontier orbitals studies support a higher reactivity of dimer 2 of ABT higher than the monomer and dimer 1, for which, the presence of dimer 2 containing N-NH2 groups in ABT could justify the biological activities observed for this species with gap values between 4.5933 and 4.8164 eV different from antiviral agents containing the C-NH2 moiety, as amantadine and chloroquine whose gap values are around 4.3012-4.1116 eV. Finally, the presence of bands of monomer and of both dimers are predicted in the vibrational spectra and, hence, its completes assignments have been performed. The scaled force constants for the three studied species are also reported.
Radar Self-Following Shopping Cart Based on Multi-Sensor Fusion

Long queues of people waiting for a settlement in global shopping supermarkets are bustling with traffic. In order to further improve operating efficiency and reduce the cost of manual operation of the supermarket, this article proposes a multi-sensor integration shopping cart system, which mainly includes image recognition, radar self-following technology and road patrol. The improved SIFT algorithm effectively identifies a variety of commodities. At the same time, relying on the public cloud platform, discount information is recommended through WeChat programs, and the development of member users login interface. After comprehensive calculation, the total price is displayed by the EAIDK-610 user interface edited by Tkinter to complete the checkout. The LD-14 radar used can realize the functions of autonomous follow-up and pedestrian obstacles. When a sensor in the system fails or the detection deviation is too large, the multi-sensor fusion technology can ensure the normal operation of the system due to a certain degree of redundant. Improve the credibility and effectiveness of the data as a whole. This not only solves the problem of queuing and checkout in the supermarket, but also helps brand merchants to achieve precise marketing and scenario access. Finally, the use of computer vision technology and various embedded hardware devices to build a radar self-following the hardware prototype of the shopping cart for experimental verification. The average accuracy of APs in the system is as high as 98.31%and 97.28%, respectively.
ImgFi: A High Accuracy and Lightweight Human Activity Recognition Framework Using CSI Image

Although human activity recognition (HAR) based on WiFi channel state information (CSI) has been widely studied, as the CSI signal is susceptible to the external environment, a recognition framework with high accuracy and low complexity remains a key and difficult problem. To improve WiFi sensing performance and reduce model complexity, ImgFi, a gesture recognition system, is proposed, which includes a conversion module and a recognition module. The conversion module is used to convert the CSI to images, and the key difference of the proposed ImgFi is using signal variations in arbitrarily different timestamps as feature extraction units rather than single signal points. This conversion can also take advantage of the powerful ability of the convolutional neural network (CNN) in the field of image recognition. Five CSI imaging approaches are introduced in ImgFi to realize the CSI conversion while a CNN is designed to recognize the activity from the converted images. To verify the proposed framework, we make some tests in our laboratory and get a dataset. The tests on four datasets under different contexts indicate that ImgFi with only three convolutional layers achieves 99.5% recognition accuracy. That is, our method has higher accuracy and lower complexity, which is important to related applications, such as smart homes and virtual reality. We will publish our code at https://github.com/shengjunzi/ImgFi.
The comparable tumour microenvironment in sporadic and NF2-related schwannomatosis vestibular schwannoma

Abstract Bilateral vestibular schwannoma is the hallmark of NF2-related schwannomatosis, a rare tumour predisposition syndrome associated with a lifetime of surgical interventions, radiotherapy and off-label use of the anti-angiogenic drug bevacizumab. Unilateral vestibular schwannoma develops sporadically in non-NF2-related schwannomatosis patients for which there are no drug treatment options available. Tumour-infiltrating immune cells such as macrophages and T-cells correlate with increased vestibular schwannoma growth, which is suggested to be similar in sporadic and NF2-related schwannomatosis tumours. However, differences between NF2-related schwannomatosis and the more common sporadic disease include NF2-related schwannomatosis patients presenting an increased number of tumours, multiple tumour types and younger age at diagnosis. A comparison of the tumour microenvironment in sporadic and NF2-related schwannomatosis tumours is therefore required to underpin the development of immunotherapeutic targets, identify the possibility of extrapolating ex vivo data from sporadic vestibular schwannoma to NF2-related schwannomatosis and help inform clinical trial design with the feasibility of co-recruiting sporadic and NF2-related schwannomatosis patients. This study drew together bulk transcriptomic data from three published Affymetrix microarray datasets to compare the gene expression profiles of sporadic and NF2-related schwannomatosis vestibular schwannoma and subsequently deconvolved to predict the abundances of distinct tumour immune microenvironment populations. Data were validated using quantitative PCR and Hyperion imaging mass cytometry. Comparative bioinformatic analyses revealed close similarities in NF2-related schwannomatosis and sporadic vestibular schwannoma tumours across the three datasets. Significant inflammatory markers and signalling pathways were closely matched in NF2-related schwannomatosis and sporadic vestibular schwannoma, relating to the proliferation of macrophages, angiogenesis and inflammation. Bulk transcriptomic and imaging mass cytometry data identified macrophages as the most abundant immune population in vestibular schwannoma, comprising one-third of the cell mass in both NF2-related schwannomatosis and sporadic tumours. Importantly, there were no robust significant differences in signalling pathways, gene expression, cell type abundance or imaging mass cytometry staining between NF2-related schwannomatosis and sporadic vestibular schwannoma. These data indicate strong similarities in the tumour immune microenvironment of NF2-related schwannomatosis and sporadic vestibular schwannoma.
A PRECISE METHOD FOR DETERMINING CONTOURED SURFACES

Although the petroleum geologist is concerned with analysing three-dimensional data, he relies entirely on two-dimensional portrayals - cross-sections and particularly contour maps of all types. With the advent of digital computers, machine contouring has become increasingly common, but little attention has been directed to the limitations of the various algorithms that can be employed to generate contour maps from a set of control points. For example, it is not widely appreciated that contouring procedures which faithfully honour the value of original control points produce poor predictions at locations where no control is available. Contouring a published set of topographic data shows how this and other limitations lead to approximations and errors in machine-generated contours. A new method based on triangulation interpolation using Delaunay tessellations (deltri analysis) is superior to existing methods. Not only does the method give the most accurate and objective measurement and display of the contoured surface, but it is also computationally efficient. Rapid calculation of volume of closure over contoured structures is possible. The method also allows estimation of the adequacy of the data on which the contouring is based by introducing a measure of 'roughness' of the surface. This is achieved by analysing the directions of normals to triangles surrounding each control point.
The Occurrence of Gluten-Related Antibodies, Sensitization to Selected Food Allergens, and Antibodies against Intrinsic Factor in Adult Patients with Diarrhea-Predominant Irritable Bowel Syndrome

Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder. Due to the possible overlap of IBS clinical symptoms with gluten-related diseases, food allergies, and autoimmune gastritis (AIG), the aim of this study was to present the frequency of anti-tissue transglutaminase 2 (TTG2) autoantibodies, anti-deamidated gluten peptide (DGP) antibodies, specific immunoglobulin E antibodies (sIgE) to selected food allergens, and anti-intrinsic factor (IF) autoantibodies in adult patients with diarrhea-predominant IBS (IBS-D). The study involved 244 patients (170 women) aged 18–75 years. The antibodies were measured with the use of multiparametric immunoassays. Elevated antibody concentrations, irrespective of the class of tested antibody, occurred in 44 patients (17.6%), including 11 patients (4.5%) with positive DGP antibodies, four patients (1.6%) with TTG2 autoantibodies, six patients (2.5%) with IF autoantibodies, and 31 patients (12.7%) with sIgE to food allergens. Sensitization to gluten, proteins from cow’s milk, and bovine serum albumin was found in 2.1%, 5.3%, and 9.0% of patients, respectively. Our study showed a high percentage of positive results for the tested antibodies in the IBD-D patients, which indicates the need to perform serological tests for CD, food allergies, and AIG in this group of patients.
Recommender Systems Based on Reinforced Learning

This article is devoted to the problem of building recommender systems based on the use of artificial intelligence methods. The paper analyzes the algorithms of recommender systems. Analyzes the Markov decision-making process in the context of recommender systems. Approaches to the adaptation of reinforcement learning algorithms to the task of recommendations (transition from the task of supervised learning to the task of reinforcement learning) are considered. Reinforcement learning algorithms Deep Deterministic Policy Gradient and Twin Delayed DDPG were implemented with their own environment simulating the user's reaction, and the results were compared. The structure of a recommender system has been developed, in which the recommender agent generates a list of offers for an individual user, using his previous history of ratings. In the system itself, the user has the ability to interact only with the space of recommended films. This can be compared to the main YouTube page, which is a feed with suggestions, but we have a user interacting only with this feed and his reaction to objects in the recommendation space falls into recommender agent, which regulates the parameters of the model in the learning process.
Effects of Adverse Events and 12-Week Group Step Aerobics on Sleep Quality in Chinese Adolescents

Background: In China, sleep disorders have become a public health concern. This study aimed to model the relationship between adverse events and sleep quality, as well as the effect of group step aerobics on sleep quality. Methods: The modeling was built on surveying 2760 16–19-year-old adolescents. The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality, and the Adolescent Self-rating Life Events Checklist (ASLEC) was used to evaluate adverse events. Adolescents with sleep disorders (PSQI ≥ 8) were randomized into the control (n = 26) and exercise (n = 26) groups. The exercise group participated in 12-week step aerobics, and the 300 min weekly volume is compliant with the WHO physical activity guidelines. Results: The double Poisson distribution was chosen to fit the data. ASLEC had a nonlinear relationship with the PSQI. Participants in the exercise group slept better (p < 0.05) from the eighth week until the end of the study. A random adolescent, therefore, has a 92.5% probability of experiencing improved sleep quality after 12 weeks of step aerobics. Conclusions: Intervention should be implemented before adverse events accumulate. An active lifestyle should be a preparedness strategy for increasing the resilience of adolescent mental health in the face of adversity.
In-Band Full-Duplex Coradiator Antenna With High Isolation Using Differential Feed and Dual Polarization for 2.4 GHz WLAN

This letter proposes a novel dual-polarized in-band full-duplex antenna with good interport isolation for the 2.4 GHz WLAN application. The proposed antenna consists of a coradiating patch, which is excited orthogonally with differential feed using the meander slotline balun and normal feed. The meander slotline balun provides differential feed, equal and opposite driving currents, to the patch and effectively suppresses the leakage of surface currents to the other port. Similarly, the leaked in-phase surface currents from the other port generate countering fields in the balun and the interference of countering fields results in neutral coupling. The meander slotline balun, due to its characteristics, improves the interport isolation of the antenna. The proposed antenna provides a minimum of 64 dB interport isolation in the (2.4–2.5) GHz band with significantly low cross-polarization. The prototype of the proposed antenna is fabricated and tested in the anechoic chamber. The simulation and measured results of the prototype show a reasonable correlation, and the far-field measurement shows that the antenna delivers the broadside radiation in both planes with a low cross-polar of less than −35 dB at the 2.45 GHz resonant frequency. The designed meandered slotline balun offers trivial magnitude and phase imbalances of (0.04–0.06) dB and ${\pm \mathbf{{\text {2}}}^{\circ}}$, respectively.