Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Viral Infections on Iron Homeostasis and the Potential for Lactoferrin as a Therapeutic in the Age of the SARS-CoV-2 Pandemic

The association of hyperinflammation and hyperferritinemia with adverse outcomes in SARS-CoV-2-infected patients suggests an integral role for iron homeostasis in pathogenesis, a commonly described symptom of respiratory viral infections. This dysregulated iron homeostasis results in viral-induced lung injury, often lasting long after the acute viral infection; however, much remains to be understood mechanistically. Lactoferrin is a multipurpose glycoprotein with key immunomodulatory, antimicrobial, and antiviral functions, which can be found in various secreted fluids, but is most abundantly characterized in milk from all mammalian species. Lactoferrin is found at its highest concentrations in primate colostrum; however, the abundant availability of bovine-dairy-derived lactoferrin (bLf) has led to the use of bLf as a functional food. The recent research has demonstrated the potential value of bovine lactoferrin as a therapeutic adjuvant against SARS-CoV-2, and herein this research is reviewed and the potential mechanisms of therapeutic targeting are considered.
Toward a multifrequency quasi‐static Ritz vector method for frequency‐dependent acoustic system application

Computational issues concerning the calculation of acoustic responses of a complex finite element (FE) model for various noise and vibration inputs have become prevalent. Such a model requires a significant amount of computation time because of repeated inversions of dynamic stiffness matrices. Thus, even state‐of‐the‐art computer hardware and software often face limitations where a model order reduction (MOR) scheme can help. The established MOR schemes such as Ritz vector or quasi‐static Ritz vector methods are efficient for general engineering systems, but these MOR methods become inaccurate for frequency response analyses in some acoustic systems with frequency‐dependent mass and stiffness matrices and force vectors (hereinafter frequency‐dependent acoustic systems). To cope with the inaccurate prediction by these methods for frequency‐dependent acoustic systems, this research presents and applies the multifrequency quasi‐static Ritz vector method. Unlike the Ritz vector or quasi‐static Ritz vector methods, the present multifrequency quasi‐static Ritz vector method employs direct Krylov subspace bases without an orthonormal procedure at multiple center frequencies. In comparison with the existing MOR scheme, a significant gain in computational efficiency is achieved, as well as enhanced accuracy. A comparison of these methods based on criteria such as efficiency, accuracy, and reliability was also conducted. Copyright © 2011 John Wiley & Sons, Ltd.
Theoretical analysis of practical heuristics for satisfiability

The SATISFIABILITY problem (SAT) is one of the central subjects of research in modern computing science. This problem provides a rich language to model practical problems. Moreover modern SAT solvers are capable of solving large instances of SAT and can be successfully applied to industrial scale problems. Since SAT is NP-complete the success of the practical SAT algorithms apparently contradicts the belief that NP-complete problems are hard to solve. One of the most promising approaches to explaining this phenomenon is the typical case analysis. Local search principles are actively used for practical SAT solving, as well as for many other important problems. In this work we perform a typical case analysis of the basic Local Search algorithm on Random Planted 3-SAT. We show that a phase transition of the effectiveness of the Local Search on Random Planted 3-SAT occurs at density ρ = 76 lnn. That is, for any constant e the algorithm with high probability solves instances of density (76 + e) ln n and with high probability fails for instances of density (76 − e) ln n. The first successful practical algorithm based on local search principles, GSAT, was proposed in 1991 by Selman, Levesque and Mitchell. In fact this algorithm is nothing more than basic Local Search enhanced with plateau moves. At the time the algorithm was proposed, it was outperforming state of the art systematic search solvers and it continues serving a basis for development of efficient local search algorithms. We analyze GSAT theoretically on Random Planted 3-SAT and show that it can solve Random Planted 3-SAT of any density ρ such that ρ > κ ln n for some constant κ. This theoretical result agrees with, and partially explains, the empirical observation that adding plateau moves dramatically improves Local Search. Finally we propose a Weighted Random Walk algorithm. The algorithm is obtained by adding a simple weighting scheme to the well known Random Walk algorithm. We prove that Weighted Random Walk with high probability gives a good approximation. Moreover, in experiments this simple algorithm solves Random Planted 3-SAT for any constant density.
Hypoglossal nerve stimulator patient usage: Patterns and trends over time

Hypoglossal nerve stimulation (HNS) is an effective treatment for obstructive sleep apnea (OSA) patients intolerant of continuous positive airway pressure but is only effective if used regularly. Usage patterns have not been studied in detail. In this study, we aimed to characterize granular HNS usage patterns.
Photon-Efficient Non-Line-of-Sight Imaging

Non-line-of-sight (NLOS) imaging techniques have the ability to look around corners, which attracts growing interest for diverse applications in autonomous navigation, medicine, transportation, manufacturing and many other domains. At present, to recover the hidden scenes, most existing transient NLOS methods need full histogram at each scanning point, which requires hundreds of detected photons to obtain both the time-of-flight (TOF) information and the intensity information. In this paper, we introduce a photon-efficient method to recover the hidden scene using only one detected photon, which contains only the TOF information of the detected photon, at each scanning point. Our method first uses the single detected photon to estimate the intensity information, and then introduces a convex optimization method with a tailored joint regularization term to recover the 3D information of the hidden scene. The regularization term contains a non-local self-similarity (NLSS) norm, which is used to capture the local structure of the hidden scene, and a total variation (TV) semi norm, which is used to enhance the edge features. To evaluate the performance of our method, both simulations and experiments are demonstrated in this paper. The results show that this photon-efficient method outperforms previous approaches under low-flux conditions.
Verifiable threshold cryptosystems based on elliptic curve

Verifiable (t, n) threshold ECSA (elliptic curve signature verification) signature algorithm and verifiable (t, n) threshold ECES (elliptic curve encrypt scheme) encryption algorithm are presented according to a secret sharing scheme for elliptic curve using Lagrange polynomial interpolation as access structure. A group of n players share an ECC (elliptic curve cryptosystem) secret key. Every qualified subset of the group, including t out of n players, could recover the secret key, so that they can sign and decrypt as well as the whole group, while no subset of t-1 players can accomplish it. The algorithms are perfect and secure verifiable secret shared schemes and their complexity is less than the same schemes based on DLP.
Optimal classification of music genres based on acoustic and visual features

Generally, music includes numerous genres like jazz, pop and so forth. Every genre encompasses diverse musical instruments. For classifying music manually, the individual should pay attention to the song and choose the genre. It consumes more time and the individual should know diverse genres. This article aims to introduce an innovative music genre classification model by considering 2 phases. Initially, short‐time Fourier transform, pitch, Timbre, MNMF, and proposed LBP and bag of words‐based features are extracted. Subsequently, the extracted features are subjected to ensemble classifiers, where support vector machine, neural network, random forest are deployed. The output attained from ensemble classifiers is then classified using deep belief network (DBN) which classifies the music genres in a precise way. For precise detection, the training of DBN is made optimal via tuning the weights. This optimization is carried out by a Whale Integrated Sea Lion Algorithm. At last, the supremacy of the developed model is examined via the evaluation of extant techniques.
Formative Research to Inform Market-Based Interventions to Increase Egg Purchase and Consumption in Tigray, Ethiopia

We aimed to understand and address barriers and enablers related to market access, purchase, and consumption of animal source foods by children aged 6–23 months and to inform subsequent market-based interventions. Key Findings Eggs are the most likely animal source foods to be purchased for children’s consumption in Tigray, Ethiopia, and should be considered as a potential food source to achieve healthy, balanced diets for children. While food sellers within rural marketplaces proved willing to test innovative marketing practices to promote the sale of eggs, households do not regularly procure eggs in local markets. Both egg retailers and consumers indicated that households prefer to receive information about healthy food products, including eggs, from trusted community members such as religious leaders and health extension workers. ABSTRACT Animal source foods (ASFs) have a demonstrated ability to improve child health yet are underutilized by many communities faced with malnutrition. Recognizing that improving knowledge about the benefits of consuming ASFs alone is not adequate to change behavior, the Studying Animal Food Markets in Rural Areas (SAFIRA) pilot project planned to test a market-based intervention to increasing the intake of ASFs by children 6–23 months in rural Tigray, Ethiopia. Our process of designing in-market behavior change strategies involved identifying the project’s target ASF, cocreating and testing marketing interventions, and understanding barriers and enablers driving key retailer behaviors. Qualitative research methods including focus group discussions, key informant interviews, trials of improved practices, and transect walks were used throughout 2 rounds of formative research. The first round of formative research led the project to focus on eggs, and the second round resulted in an improved understanding of the Tigrayan local food markets and egg consumption. Consumers were receptive to nutrition messaging from trusted community members and consider eggs to be healthy and affordable relative to other ASFs. Despite a willingness on the part of egg retailers in Tigrayan markets to try new practices to market eggs to consumers, formative research revealed that retailers function primarily as aggregators, moving eggs toward urban markets, correcting a foundational assumption that households routinely purchase eggs at local markets. These findings demonstrate the importance of formative research to inform design—especially in the development of context-specific behavior change interventions situated within local marketplaces.
Role of Increased Syncytin-1 Expression in Pathogenesis of Anti-N-Methyl-d-Aspartate Receptor Encephalitis

Purpose Syncytin-1 may play a role in several neuropsychiatric disorders, but its function in anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is unknown. The purpose of this study was to examine the possible mechanism of action of syncytin-1 in patients with anti-NMDAR encephalitis. Patients and Methods Twenty patients with anti-NMDAR encephalitis and eight controls were recruited. The protein levels of syncytin-1 in serum were determined using an enzyme-linked immunosorbent assay, and the transcript levels of syncytin-1 were determined using real-time quantitative PCR. Flow cytometry was used for peripheral blood lymphocyte subset detection. Further, the relationship between syncytin-1 levels and clinical features of anti-NMDAR encephalitis and peripheral blood lymphocyte subsets was analyzed. Results Compared with those in controls, higher syncytin-1 levels and percentage of B cells (CD3-CD19+) were observed in patients with anti-NMDAR encephalitis. Among anti-NMDAR encephalitis patients, the level of syncytin-1 positively correlated with the proportion of B cells and modified Rankin scale score at onset and after immunotherapy and negatively correlated with the proportion of CD3+ T cells. Conclusion An increased expression of Syncytin-1 is associated with the pathogenesis of anti-NMDAR encephalitis, providing evidence for elucidating the pathogenesis of the disease and suggesting novel therapeutic targets. Further, this study clarifies the role of syncytin-1 in neuroimmune disorders.
Application of computational geometry to pattern recognition problems

In this thesis it is shown that several pattern recognition problems can be solved efficiently by exploiting the geometrical structure of the problems. The problems considered are in the area of clustering and classification. These problems are: (i) computing the diameter of a finite planar set, (ii) computing the maximum and minimum distance between two finite planar sets of points, (iii) testing for point inclusion in a convex polyhedron in d-dimensional space, and (iv) exact and inexact reference set thinning for the nearest neighbor decision rule. Algorithms to solve the above problems are presented and analyzed for worst-case and average-case situations. These algorithms are implemented and experimentally compared with the existing algorithms. In solving the above problems, a geometrical construct, known as the Voronoi diagram is used extensively. However, there exists no practical algorithm to construct the Voronoi diagram in d dimensional spaces when d > 2. In this thesis an efficient algorithm to construct the Voronoi diagram in d-space is presented.
Semiparametric models and two-phase samples: Applications to Cox regression

: A standard estimation method when ﬁtting parametric models to data from two-phase stratiﬁed samples is inverse probability weighting of the estimating equations. In previous work we applied this approach to like- lihood equations for both Euclidean and non-Euclidean parameters in semiparametric models. We proved weak convergence of the inverse probability weighted empirical process and derived an asymptotic expansion for the estimator of the Euclidean parameter. We also showed how adjustment of the sampling weights by their calibration to known totals of auxiliary variables, or their estimation using these same variables, could markedly improve eﬃciency. Here we consider joint estimation of Euclidean and non-Euclidean parame- ters. Our asymptotic expansion for the non-Euclidean parameter is apparently new even in the special case of simple random sampling. The results are applied to estimation of survival probabilities for individual subjects using the regression coeﬃcients (log hazard ratios) and baseline cumulative hazard function of the Cox proportional hazards model. Expressions derived for the variances of regression coeﬃcients and cumulative hazards estimated after calibration of the weights aid construction of the auxiliary variables used for adjustment. We demonstrate empirically the improvement oﬀered by calibration or estimation of the weights via simulation of two-phase stratiﬁed samples using publicly available data from the National Wilms Tumor Study and data analysis with the R survey package.
The predictive value of 18F-FDG PET/CT in an EGFR-mutated lung adenocarcinoma population

Background A non-invasive, simple, and convenient method to evaluate the presence of epidermal growth factor receptor (EGFR) mutations is important for initial treatment decisions in lung adenocarcinoma. Methods We retrospectively reviewed 297 untreated primary lung adenocarcinoma patients with exact EGFR status. Based on their EGFR status, the patients were divided into a mutant-type group (138 patients) and wild-type group (159 patients). General patient characteristics and possible factors reflecting the status of EGFR were also evaluated. Results Of the 297 lung adenocarcinoma patients analyzed for EGFR status who underwent positron emission tomography (PET)/computed tomography (CT) between January 2013 and December 2017, mutations in the EGFR gene were detected in 138 patients (46.5%). EGFR mutations were more frequently associated with women, never smokers, and low 18F-fluoro-2-deoxy-glucose (18F-FDG) PET/CT maximal standard uptake value of the primary tumor (pSUVmax). Multivariate analysis indicated that women [odds ratio (OR) =2.853; 95% confidence interval (CI): 1.451–5.611; P=0.002], never smokers (OR =2.414; 95% CI: 1.217–4.789; P=0.012), tumor size <3.5 cm (OR, 2.170; 95% CI: 1.205–3.908; P=0.010), and pSUVmax <8.2 (OR =1.904; 95% CI: 1.098–3.302; P=0.022) were effective predictors of EGFR mutation. In addition, the area under the curve (AUC) of pSUVmax and tumor size was 0.623 and 0.600, respectively. Combined with clinical characteristics, including sex and smoking status, the AUC of the 4 predictors was 0.770. Conclusions These indicators could be helpful for enhancing predictive accuracy of EGFR mutations in lung adenocarcinoma patients, especially in those for whom EGFR detection is unavailable.
Literary Historicism: Romanticism, Philologists, and the Presence of the Past

Between 1780 and 1840 a huge rediscovery of the early medieval vernacular roots and rootedness of the various European languages and literatures took place, in a process that reverberated back and forth between the fields of philology, antiquarianism, and imaginative literature. It revolutionized the European self-image and historical consciousness and led to the national diffraction of the Enlightenment’s idea of culture and literature. Instead of one European culture cradled in classical antiquity, people came to envisage a plurality of European cultures, each rooted in the nation’s vernacular and tribal origins. It was as if, in the words of one worried Oxford professor, those philologists who were “nourishing our language not from the humanity of the Greeks and Romans, but from the savagery of the Goths and the AngloSaxons,” were “about to reverse the renaissance. ”1 I wish to view this “reversal of the renaissance” in a fresh light, as a period and condition that might be called literary historicism.
Shuttle Program. Euler angles, quaternions, and transformation matrices working relationships

A brief mathematical development of the relationship between the Euler angles and the transformation matrix, the quaternion and the transformation matrix, and the Euler angles and the quaternion is presented. The analysis and equations presented apply directly to current space shuttle problems. The twelve three-axis Euler transformation matrices are given as functions of the Euler angles, the equations for the quaternion as a funtion of the Euler angles, and the Euler angles as a function of the transformation matrix elements.
Chew's first Delaunay triangulation refinement scheme‐based positioning of road side units for optimal network coverage in vehicular ad‐hoc networks

The temporal network fragmentation and uncertain vehicle mobility are considered to impact the communication connectivity among the vehicular nodes of the network. In this context, road side units (RSUs) play an anchor role in enhancing the vehicle‐to‐vehicle (V2V) communication connectivity and support vehicle‐to‐infrastructure (V2I) communication. In the current scenario, deploying a huge number of RSUs in the vehicular networks at an initial stage is completely impossible as it incurs high installation cost and authority restriction. Moreover, the optimal placement of RSUs in the vehicular network needs to be enforced for attaining maximized network coverage. In this paper, Chew's first Delaunay triangulation refinement scheme (CFDTRS) is proposed for optimal positioning of RSUs in order to attain optimal network coverage in the vehicular network with minimized cost. This CFDTRS considered the factors of vehicular density, number of obstacles in the map, intersection popularity, and global coverage into account during the placement of RSUs. It is proposed with the objective of deploying required number of RSUs within the range of data transmission in order to achieve maximal coverage in the convex map, such that each area of the convex map is completely covered with at least a single RSU in the existence of multiple number of obstacles. The simulation results of the proposed CFDTRS attained from the real time situations of simplex, moderate, and complex maps confirmed improved packet delivery rate of 9.32%, throughput by 10.74% with minimized packet loss of 9.14%, and reduced end‐to‐end delay of 19.31$, compared to the benchmarked schemes considered for investigation.
Studi performa aerodinamis turbin hidrokinetik Savonius dengan 2 semicircular blade-sharp leading edge

This current investigation was conducted to study the aerodynamic characteristics of Savonius hydrokinetics turbine with semicircular blade-sharp leading edge. The influences of blade thickness and freestream velocity were simulated using ANSYS FLUENT with k-w SST model. The results show that the flow structure changes with increasing turbine rotation in which the flow complexity is formed at a larger rotation angle. The coefficient of torque and power for thin blades is higher than for thicker turbine blades and its values increase with the increase in the freestream velocity.
Generalized spectral categories, topological Hochschild homology and trace maps

We define a topological Hochschild (THH) and cyclic (TC) homology theory for differential graded (dg) categories and construct several non-trivial natural transformations from algebraic K-theory to THH(-). In an intermediate step, we prove that the homotopy theory of dg categories is Quillen equivalent, through a four step zig-zag of Quillen equivalences, to the homotopy theory of Eilenberg-Mac Lane spectral categories. Finally, we show that over the rationals two dg categories are topological equivalent if and only if they are quasi-equivalent.