Miracle-dz/UniFAR-FTUs huggingface dataset:
Meshfree Approximation Methods For Free-form Optical Surfaces With Applications To Head-worn Displays

Compact and lightweight optical designs achieving acceptable image quality, field of view, eye clearance, eyebox size, operating across the visible spectrum, are the key to the success of next generation head-worn displays. The first part of this thesis reports on the design, fabrication, and analysis of off-axis magnifier designs. The first design is catadioptric and consists of two elements. The lens utilizes a diffractive optical element and the mirror has a free-form surface described with an x-y polynomial. A comparison of color correction between doublets and single layer diffractive optical elements in an eyepiece as a function of eye clearance is provided to justify the use of a diffractive optical element. The dual-element design has an 8 mm diameter eyebox, 15 mm eye clearance, 20 degree diagonal full field, and is designed to operate across the visible spectrum between 450-650 nm. 20% MTF at the Nyquist frequency with less than 3% distortion has been achieved in the dual-element head-worn display. An ideal solution for a head-worn display would be a single free-form surface mirror design. A single surface mirror does not have dispersion; therefore, color correction is not required. A single surface mirror can be made see-through by machining the appropriate surface shape on the opposite side to form a zero power shell. The second design consists of a single off-axis freeform mirror described with an x-y polynomial, which achieves a 3 mm diameter exit pupil, 15 mm eye relief, and a 24 degree diagonal full field of view. The second design achieves 10% MTF at the Nyquist frequency set by the pixel spacing of the VGA microdisplay with less than 3% distortion. Both designs have been fabricated using diamond turning techniques. Finally, this thesis addresses the question of “what is the optimal surface shape for a single mirror constrained in an off-axis magnifier configuration with multiple fields? ” Typical optical
Lessons Learned from the Development and Roll-Out of the rVSVΔG-ZEBOV-GP Zaire ebolavirus Vaccine to Inform Marburg Virus and Sudan ebolavirus Vaccines

This review describes key aspects of the development of the rVSVΔG-ZEBOV-GP Ebola vaccine and key activities which are continuing to further expand our knowledge of the product. Extensive partnerships and innovative approaches were used to address the various challenges encountered during this process. The rVSVΔG-ZEBOV-GP Ebola vaccine was initially approved by the European Medicines Agency and prequalified by the World Health Organization in November 2019. It was approved by the United States Food and Drug Administration in December 2019 and approved in five African countries within 90 days of prequalification. The development resulted in the first stockpile of a registered Ebola vaccine that is available to support outbreak response. This also provides insights into how the example of rVSVΔG-ZEBOV-GP can inform the development of vaccines for Sudan ebolavirus, Marburg virus, and other emerging epidemic diseases in terms of the types of approaches and data needed to support product registration, availability, and the use of a filovirus vaccine.
Low Profile Microstrip Resonator Dielectric Sensor for Development of Artificial Phantom

In this article, a microstrip line T stub resonator is proposed as a sensor for dielectric characterization of liquid material for the development of artificial tissue-mimicking phantom. T stub is miniaturized using Hilbert curve geometry. The proposed sensor is modeled to sense permittivity from 1 to 80 values between 300 and 900 MHz. Two configuration planar and conformal model has been analyzed. The proposed sensor utilizes two parameters: transmission coefficient and reflection coefficient independently. However, the reflection coefficient response is more sensitive than the transmission coefficient response. The sensor is quite sensitive to sense the broad range of permittivity. The proposed sensor is fabricated and tested with different concentrations of sugar water mixture solution. The measured result shows a very much satisfactory response to the proposed sensor design.
The Trend of Metaverse and Augmented & Virtual Reality Extending to the Healthcare System

There is no escaping Internet's favorite buzzword for 2022: The Metaverse. Everyone is talking about it, but only a few know what it is or how it works. One can look at the Metaverse as a 3D model of the Internet where it is possible to spend your reality parallel to the virtual world. In broad terms, Metaverse can be explained as a virtual space, graphically rich, leaning towards verisimilitude where people can do all sorts of things they do in real-life such as shop, play, socialize, and party. The pandemic has accelerated innovations in the digital age. Looking beyond revolutions in telehealth, payments, remote monitoring, and secure data-sharing are other essential innovations in the fields of artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and blockchain technology. The Metaverse is still in its nascent stage and evolving continuously, having a huge potential in health care to combine the technologies of AI, AR/VR, web 3.0, Internet of medical devices, and quantum computing, along with robotics to give a new direction to healthcare systems. From improving surgical precision to therapeutic usage and more, the Metaverse can bring significant changes to the industry
Tensile Strength of Porcine Aorta Decellularized with Liquefied Dimethyl Ether and DNase

In a previous report, we proposed a method for decellularizing porcine aortas by removing lipids from the aortas using liquefied dimethyl ether (DME) instead of the conventional sodium dodecyl sulfate (SDS). This is followed by DNA fragmentation with DNase. In the current work, the physical properties of porcine aortas decellularized using the DME method are evaluated by tensile strength tests. Conventional SDS decellularized aortas are typically swollen, rupture very easily, and have poor elasticity. By contrast, DME-treated samples are found to be less elastic. However, the maximum stress required for rupture is greater than that for the original aorta. These results indicate that decellularization with DME and DNase increases the maximum stress that can be withstood. Reduction of elasticity may derive from the appearance of temporary C=N bonds due to Schiff-base reactions that occur during the lipid removal process by liquefied DME, and methods to avoid this are desirable.
High-Redshift Galaxies with Large Ionization Parameters

Motivated by recent observations of galaxies dominated by emission lines, which show evidence of being metal poor with young stellar populations, we present calculations of multiple model grids with a range of abundances, ionization parameters, and stellar ages, finding that the predicted spectral line diagnostics are heavily dependent on all three parameters. These new model grids extend the ionization parameter to larger values than typically explored. We compare these model predictions with previous observations of such objects, including two new Lyman-$\alpha$ emitting galaxies (LAE) that we have observed. Our models give improved constraints on the metallicity and ionization parameter of these previously studied objects, as we are now able to consider high ionization parameter models. However, similar to previous work, these models have difficulty predicting large line diagnostics for high ionization potential species, requiring future work refining the modelling of FUV photons. Our model grids are also able to constrain the metallicity and ionization parameter of our LAEs, and give constraints on their Ly$\alpha$ escape fractions, all of which are consistent with recent lower redshift studies of LAEs.
A GBS-Based GWAS Analysis of Leaf and Stripe Rust Resistance in Diverse Pre-Breeding Germplasm of Bread Wheat (Triticum aestivum L.)

Yellow (YR) and leaf (LR) rusts caused by Puccinia striiformis f. sp. tritici (Pst) and Puccinia triticina, respectively, are of utmost importance to wheat producers because of their qualitative and quantitative effect on yield. The search for new loci resistant to both rusts is an ongoing challenge faced by plant breeders and pathologists. Our investigation was conducted on a subset of 168 pre-breeding lines (PBLs) to identify the resistant germplasm against the prevalent local races of LR and YR under field conditions followed by its genetic mapping. Our analysis revealed a range of phenotypic responses towards both rusts. We identified 28 wheat lines with immune response and 85 resistant wheat genotypes against LR, whereas there were only eight immune and 52 resistant genotypes against YR. A GWAS (genome-wide association study) identified 190 marker-trait associations (MTAs), where 120 were specific to LR and 70 were specific to YR. These MTAs were confined to 86 quantitative trait loci (QTLs), where 50 QTLs carried MTAs associated with only LR, 29 QTLs carried MTAs associated with YR, and seven QTLs carried MTAs associated with both LR and YR. Possible candidate genes at the site of these QTLs are discussed. Overall, 70 PBLs carried all seven LR/YR QTLs. Furthermore, there were five PBLs with less than five scores for both LR and YR carrying positive alleles of all seven YR/LR QTLs, which are fit to be included in a breeding program for rust resistance induction.
Recurrence of the frozen shoulder after hydrodilatation, what is the true incidence?

Purpose of the study To assess the outcome and recurrence rates of frozen shoulder treated by hydrodilatation in an independent hospital setting. Method Patients presenting to a shoulder clinic from August 2019 to July 2021 with a diagnosis of frozen shoulder were offered hydrodilatation. Data included primary or secondary frozen shoulder, length of symptoms, and diabetic status. An Oxford Shoulder Score was completed prior to hydrodilatation. Using ultrasound guidance, 40 mg Triamcinolone and local anaesthetic (10–25 mL depending on patient tolerance) were injected into the rotator interval. At a mean of 9 months, patients recorded their tolerance of the procedure, subsequent progress, the need for further treatment, and their current Oxford Shoulder Score. Results From 55 shoulders, six patients had a failure to improve and 10 patients had a transient improvement followed by recurrence (29%). 2/21 (9.5%) patients had 25 mL injected compared to 14/34 (41%) who had < = 20 mL (p = 0.012). 14/43 (33%) of primary frozen shoulder patients had a recurrence, compared with 2/12 (16%) secondary frozen shoulder patients, p = 0.019. Conclusion Further treatment was indicated in 14/34 (41%) of patients who underwent hydrodilatation in the frozen stage of frozen shoulder and could not tolerate more than 20 mL of injection, and was more commonly required in primary (33%) versus secondary (16%) frozen shoulder.
A Novel Knowledge Distillation Method for Self-Supervised Hyperspectral Image Classification

Using deep learning to classify hyperspectral image(HSI) with only a few labeled samples available is a challenge. Recently, the knowledge distillation method based on soft label generation has been used to solve classification problems with a limited number of samples. Unlike normal labels, soft labels are considered the probability of a sample belonging to a certain category, and are therefore more informative for the sake of classification. The existing soft label generation methods for HSI classification cannot fully exploit the information of existing unlabeled samples. To solve this problem, we propose a novel self-supervised learning method with knowledge distillation for HSI classification, termed SSKD. The main motivation is to exploit more valuable information for classification by adaptively generating soft labels for unlabeled samples. First, similarity discrimination is performed using all unlabeled and labeled samples by considering both spatial distance and spectral distance. Then, an adaptive nearest neighbor matching strategy is performed for the generated data. Finally, probabilistic judgment for the category is performed to generate soft labels. Compared to the state-of-the-art method, our method improves the classification accuracy by 4.88%, 7.09% and 4.96% on three publicly available datasets, respectively.
Impacts of Physical Exercise and Media Use on the Physical and Mental Health of People with Obesity: Based on the CGSS 2017 Survey

Obesity has become a common chronic disease in many countries around the world. People with obesity, as a minority, deserve more social attention. Currently, there are few studies on the health level of people with obesity from the perspective of social influencing factors. This study examines the effects of the frequency of physical exercise and frequency of use of different media types on the level of physical and mental health in people with obesity. In addition, we explore the mediating effect of physical exercise frequency on the relationship between online media use frequency and the mental health of people with obesity. The participants are 882 patients with obesity from the 2017 China General Social Survey (CGSS). The results show that: (1) Online media use was a possible positive predictor of physical health improvement among people with obesity. (2) Physical exercise was a possible positive predictor of mental health improvement among people with obesity. (3) Physical exercise played an entirely mediating role between online media use and mental health. The study is conducive to understanding the relationship and mediating mechanism between physical exercise, media use, and physical and mental health in people with obesity. The results of this study can provide suggestions for improving the health and well-being of people with obesity. Future research could explore more aspects of physical activity (e.g., the methods for physical exercise) and media use (e.g., media preference or compulsive use). More variables can be included in the study of influencing factors of the physical and mental health of people with obesity.
Encroachment strategy and revenue-sharing contract for product customization

This paper investigates the optimal encroachment strategy of product customization and the revenue-sharing contract in a two-stage supply chain consisting of a contract manufacturer (CM) and an original equipment manufacturer (OEM). In addition to producing and wholesaling standard products for OEM, CM has the motive to manufacture customized products under store brand and encroach the end consumer market. Stackelberg game models with different strategies (encroachment or noencroachment) under both decentralized and centralized supply chains are explored. Models analyzing CM’s encroachment with product customization are rare. Besides, this paper characterizes both vertical partnership and horizontal competitive relationships between supply chain members. The findings show that it is unprofitable to encroach on the retailing market for CM when the acceptance degree of store brand is low. There is a threshold value of customization level that can gain positive demand. Interestingly, as the Stackelberg leader, OEM always suffers from the encroachment. Then a revenue-sharing contract is designed that can fully integrate the decentralized supply chain and obtain a contract-implementing Pareto zone. Furthermore, a numerical example is developed, demonstrating the validity of the obtained analytical results. On this basis, some suggestions for industry managers are discussed in the form of managerial insights.
Random matrix theory for the robustness, quantization, and end-to-end correlation of zero-bias conductance peaks in a class D ensemble

We develop a general theory to study strong random quenched disorder effects in systems of experimental relevance in the search for Majorana zero modes (MZM) in topological superconductors. Using the random matrix theory in a class D ensemble, we simulate the transport properties of random quantum dots by attaching leads, and calculating the differential conductance in the $S$ matrix formalism. To add the concept of the length to the random system so that disordered Majorana nanowires can be simulated by the random matrix theory, we generalize the model of a single quantum dot to a chain of quantum dots by analogy with the superconductor-semiconductor (SC-SM) nanowire Majorana platform. We first define a new concept, the robustness of zero-bias conductance peaks (ZBCPs), in terms of an effective random Hamiltonian considering the self-energy of leads. We then study the joint distribution for the robustness and ZBCPs, and find a strong correlation that the ZBCP with stronger robustness is also prone to carry a larger conductance peak near $2e^2/h$. This trend is more prominent in shorter chains than in longer chains. This is consistent with experimentally observed ZBCPs associated with disorder-induced trivial Andreev bound states (the so-called ugly ZBCPs). Finally, we study the end-to-end correlation of the disorder-induced ZBCPs from two leads by calculating the normalized mutual information, which estimates the degrees of the correlation arising from the trivial ZBCPs. Our work provides an estimate of several important metrics used in SC-SM experiments to determine the nature of ZBCPs, including the robustness, quantization, and end-to-end correlation of the trivial ZBCPs. Therefore, in order to claim any evidence for MZMs, one must establish the observed ZBCPs to have considerable statistical significance well beyond what we find in this work to exist for the trivial peaks.
The Role of Subjective Perception in Visualization, Controllability Hypothesis and Abstract Visualization

Visual analytics tools are used when interpreting and analyzing weakly formalized or non-formalized data. The paper considers the problem of the influence of subjective factors on efficiency of the visualization tools. Based on the previously proposed and developed se-miotic visualization model, a system of initiating factors is formulated that have a significant impact on the effectiveness of visualization tools. A controllability hypothesis is formulated, on the basis of which an assumption is made about limitations of visualization systems It is proposed to take these limitations into consideration when designing new visual analytics tools. Approbation of the assertions presented in the work was carried out on the example of social data.
Income Inequality Shift Paradigm. From Economic Approach to Sharing Responsibilities

This paper investigates the dynamics associated with inequality in EU member states. The variation of the Gini coefficient is analyzed from different perspectives: economic growth, certain macroeconomic variables, socio-demographic environment and historical, political and cultural environment. The use of the panel data regression model allows country specific effects control, the results showing that in the context of European convergence, the historical, political, cultural and socio-demographic factors have the greatest impact in terms of income distribution. Starting from the complex analysis of the evolution of inequalities in the last half century and from the experts' opinions regarding the relationship between the last two crises (from 2008 and the current pandemic), we notice important changes, there is a paradigm shift. The paper proposes a new approach to the economic growth paradigm, based on reversing the dynamics of income inequality in the 21st century and outlines our own vision on support policies to mitigate rising inequalities, in the context of designing a robust resilience strategy and sustainable post-pandemic development.
Identification of Allergenic Proteins in Velvet Mesquite (Prosopis velutina) Pollen: An Immunoproteomics Approach

Velvet mesquite (Prosopis velutina) is a native legume of the southwestern United States and northwestern Mexico, contributing significantly to the desert ecosystem and playing key ecological roles. It is also an important cause of allergic respiratory disease widely distributed in the Sonoran, Chihuahuan, and Mojave Deserts. However, no allergens from velvet mesquite pollen have been identified to date. Pollen proteins were extracted and analyzed by one- and two-dimensional electrophoresis and immunoblotting using a pool of 11 sera from mesquite-sensitive patients as the primary antibody. IgE-recognized protein spots were identified by mass spectrometry and bioinformatics analysis. Twenty-four unique proteins, including proteins well known as pollen, food, airway, or contact allergens and four proteins not previously reported as pollen allergens, were identified. This is the first report on allergenic proteins in velvet mesquite pollen. These findings will contribute to the development of specific diagnosis and treatment of mesquite pollen allergy.
Structure-Texture Parallel Embedding for Remote Sensing Image Super-Resolution

The structure and texture of images are crucial for remote sensing image super-resolution (SR). Generative adversarial networks (GANs) recover image details through adversarial training. However, the recovered images always have structural distortions, on the one hand, and GANs are difficult to train, on the other hand. In addition, some methods assist reconstruction by introducing prior information of the image, but this brings additional computational cost. To address this issue, we propose a novel structure-texture parallel embedding (SPE) method for SR of remote sensing images. Our method does not require additional image priors to reconstruct high-quality images. Specifically, we use the global structure information and local texture information of the image in the ascending space to guide the reconstruction result of the image. First, we design a structure preserving block (SPB) to extract global structural features in the ascending space of the image, so as to obtain global structure information for a priori representation. Then, we design a local texture attention module (LTAM) to restore richer texture details. We have conducted lots of experiments on Draper public dataset. Experimental results show that our proposed method not only achieves a better tradeoff between computational cost and performance, but also outperforms the existing several SR methods in terms of objective index evaluation and subjective visual effects.