Miracle-dz/UniFAR-FTUs huggingface dataset:
An Oil-Based Adjuvant Improves Immune Responses Induced by Canine Adenovirus-Vectored Vaccine in Mice

There is a significant need for highly effective vaccines against emerging and common veterinary infectious diseases. Canine adenovirus type 2 (CAV2) vectors allow rapid development of multiple vaccines and have demonstrated their potential in animal models. In this study, we compared the immunogenicity of a non-replicating CAV2 vector encoding the rabies virus glycoprotein with and without MontanideTM ISA 201 VG, an oil-based adjuvant. All vaccinated mice rapidly achieved rabies seroconversion, which was associated with complete vaccine protection. The adjuvant increased rabies antibody titers without any significant effect on the anti-CAV2 serological responses. An RT2 Profiler™ PCR array was conducted to identify host antiviral genes modulated in the blood samples 24 h after vaccination. Functional analysis of differentially expressed genes revealed the up-regulation of the RIG-I, TLRs, NLRs, and IFNs signaling pathways. These results demonstrate that a water-in-oil-in-water adjuvant can shape the immune responses to an antigen encoded by an adenovirus, thereby enhancing the protection conferred by live recombinant vaccines. The characterization of early vaccine responses provides a better understanding of the mechanisms underlying the efficacy of CAV2-vectored vaccines.
Sensitization of the SST Turbulence Model to Rotation and Curvature by Applying the Spalart-Shur Correction Term

A rotation-curvature correction suggested earlier by Spalart and Shur for the one-equation Spalart-Allmaras turbulence model is adapted to the Shear Stress Transport model. This new version of the model (SST-CC) has been extensively tested on a wide range of both wall-bounded and free shear turbulent flows with system rotation and/or streamline curvature. Predictions of the SST-CC model are compared with available experimental and DNS data, on one hand, and with the corresponding results of the original SST model and advanced Reynolds stresses transport model (RSM), on the other hand. It is found, that in terms of accuracy the proposed model significantly improves the original SST model and is quite competitive with the RSM, whereas its computational cost is significantly less than that of the RSM. © 2008 ASME
A study of evoluntionary perturbative hyper-heuristics for the nurse rostering problem.

Hyper-heuristics are an emerging field of study for combinatorial optimization. The aim of a hyper-heuristic is to produce good results across a set of problems rather than producing the best results. There has been little investigation of hyper-heuristics for the nurse rostering problem. The majority of hyper-heuristics for the nurse rostering problem fit into a single type of hyperheuristic, the selection perturbative hyper-heuristic. There is no work in using evolutionary algorithms employed as selection perturbative hyper-heuristics for the nurse rostering problem. There is also no work in using the generative perturbative type of hyper-heuristic for the nurse rostering problem. The first objective of this dissertation is to investigate the selection perturbative hyper-heuristic for the nurse rostering problem and the effectiveness of employing an evolutionary algorithm (SPHH). The second objective is to investigate a generative perturbative hyper-heuristic to evolve perturbation heuristics for the nurse rostering problem using genetic programming (GPHH). The third objective is to compare the performance of SPHH and GPHH. SPHH and GPHH were evaluated using the INRC2010 benchmark data set and the results obtained were compared to available results from literature. The INRC2010 benchmark set is comprised of sprint, medium and long instance types. SPHH and GPHH produced good results for the INRC2010 benchmark data set. GPHH and SPHH were found to have different strengths and weaknesses. SPHH found better results than GPHH for the medium instances. GPHH found better results than SPHH for the long instances. SPHH produced better average results. GPHH produced results that were closer to the best known results. These results suggest future research should investigate combining SPHH and GPHH to benefit from the strengths of both perturbative hyper-heuristics.
The impact of the COVID-19 pandemic on life expectancy by the level of area deprivation in South Korea

Objective Comparative evidence suggests that the impact of COVID-19 on life expectancy has been relatively milder in South Korea. This study aims to examine whether the pandemic has universal or unequal impacts on life expectancy across 250 districts with varying levels of deprivation. Methods Using mortality data from 2012 to 2021 obtained from the Microdata Integrated Service of Statistics Korea, we calculated life expectancy at birth and age 65 for both sexes, by deprivation quintiles, before and during the pandemic. We summarized life expectancy gaps using the slope of the inequality index (SII) and further decomposed the gaps by the contribution of age and cause of death using Arriaga’s method. Results Both men and women experienced consistent improvements in life expectancy from 2012 to 2019, but the trend was disrupted during 2020 and 2021, primarily driven by older people. While men in more deprived areas were initially hit harder by the pandemic, the life expectancy gap across deprivation quintiles remained relatively constant and persistent across the study period [SII: -2.48 (CI: −2.70 from −2.27) for 2019 and − 2.84 (CI: −3.06 from −2.63) for 2020]. Middle-aged men from the most deprived areas were the most significant contributors to the life expectancy gap, with liver disease, liver cancer, transport accidents, and intentional injuries being the leading causes, both in the pre and during the pandemic. While these contributors remained largely similar before and during the pandemic, the contribution of transport accidents and liver cancer to the male life expectancy gap slightly decreased during the pandemic, while that of ischemic heart disease and pneumonia slightly increased. A similar increase was also observed for the female life expectancy gap. Conclusion This study found no clear evidence of an increased life expectancy gap during the pandemic in South Korea, unlike in other countries, although access to emergency healthcare services may have been slightly more disturbed in deprived areas. This achievement can provide lessons for other countries. However, the persistent regional gaps in life expectancy observed over the past decade indicate the need for more targeted public health policies to address this issue.
A switchable absolute bandwidth tunable filter with etched slot

Abstract In this paper, a reconfigurable filter with tunable center-frequency and switchable bandwidths is proposed. Frequency flexibility is achieved by varactors in the inner resonant parts. The switchable bandwidth states are implemented by pin diode connected with the etched slot on the ground. The coupling coefficient could be adjusted by the physical size of grounded slot, which would determine filter’s bandwidth. To demonstrate the scheme, a proof-of-concept prototype filter is designed at 800 MHz. The measurement results show the center frequency of the designed filter could be tuned from 720 to 820 MHz; meanwhile, the two states switches the passband bandwidth from 45 to 36 MHz via turning on/off the grounded pin diode. The proposed filter has been fabricated, and measured, and exhibits excellent performance.
CLONING, MOLECULAR CHARACTERIZATION AND FUNCTIONAL ANALYSIS OF THE CIS-MUUROLADIENE SYNTHASE (SgCMS) GENE FROM LEAVES OF SALVIA GUARANITICA PLANT

n terms of its nutritional and medical value, Salvia guaranitica is ranked among the most important medicinal and aromatic plants because of the abundance of essential active components it contains. The most important and abundant active ingredients are terpenoid molecules, particularly monoterpenes (C10) and sesquiterpenes (C15). Terpenes play a variety of tasks and possess beneficial biological traits in plants. Considering these characteristics, the current research was done to clone S. guaranitica gene for Cis-muuroladiene synthase ( SgCMS , EC: 4.2.3.67). The 600 amino acid protein coded by SgCMS has an open reading frame of 1.802 base pairs. Moreover, SgCMS protein has four terpene synthase family domains which belong to terpenes and terpenoid synthase domains. We altered and overexpressed SgCMS gene in Arabidopsis thaliana to investigate the gene's function. Compared to the wild-type plants, the transgenic A. thaliana plants showed a decrease in leaf diameter, while the flowering stems started growth earlier when compared to the GUS control. Ultimately, the results of the transgenic plants' gas chromatography-mass spectrometry examination revealed that SgCMS was in charge of producing several terpene types, particularly sesquiterpene.
Phase-correcting denoising for diffusion magnetic resonance imaging

PHASE-CORRECTING DENOISING FOR DIFFUSION MAGNETIC RESONANCE IMAGING Sevgi Gökçe Kafal M.S. in Electrical and Electronics Engineering Advisor: Emine Ülkü Sar ta3 Çukur April 2018 Di usion magnetic resonance imaging (MRI) is a low signal-to-noise ratio (SNR) acquisition technique when compared to anatomical MRI. Multiple acquisitions have to be averaged to overcome this SNR problem. However, subject motion and/or local pulsations during di usion sensitizing gradients create varying phase o sets and k-space shifts between repeated acquisitions, prohibiting direct complex averaging due to local signal cancellations in the resultant images. When multiple acquisitions are magnitude averaged, these phase issues are avoided at the expense of noise accumulation. This thesis proposes a reconstruction routine to overcome the local signal cancellations, while increasing the SNR. First, a global phase correction algorithm is employed, followed by a partial Fourier reconstruction algorithm. Then, a novel phase-correcting non-local means (PC-NLM) ltering is proposed to denoise the images without losing structural details. The proposed PC-NLM takes advantage of the shared structure of the multiple acquisitions as they should only di er in terms of phase issues and noise. The proposed PC-NLM technique is rst employed on di usion-weighted imaging (DWI) of the spinal cord, and is then modi ed to capture the joint information from di erent di usion sensitizing directions in di usion-tensor imaging (DTI). The results are demonstrated with extensive simulations and in vivo DWI and DTI of the spinal cord. These results show that the proposed PC-NLM provides high image quality without any local signal cancellations, while preserving the integrity of quantitative measures such as apparent di usion coe cients (ADC) and fractional anisotropy (FA) maps. This reconstruction routine can be especially bene cial for the imaging of small body parts that require high resolution.
Airborne Circular Flight Array SAR 3-D Imaging Algorithm of Buildings Based on Layered Phase Compensation in the Wavenumber Domain

Circular synthetic aperture radar (CSAR) offers multiangle scattering for strong directional targets, benefiting urban surveying. However, the CSAR 3-D imaging of buildings is difficult. The reference height mismatch problem during imaging can lead to a defocused target, and a significant layover phenomenon exists in urban environments. To solve these problems and realize the CSAR 3-D imaging of buildings, this study adopts the airborne circular flight array synthetic aperture radar (CFASAR) system for data acquisition and proposes a 3-D processing method for airborne CFASAR based on layered phase compensation in the wavenumber domain. CFASAR has advantages over single-baseline and multibaseline CSAR, as 3-D imaging is independent of target azimuth scattering consistency and reduces flight experiment complexity. 3-D imaging of buildings consists of two key steps: layered focusing based on phase compensation in the wavenumber domain and super-resolution imaging, which solves the defocusing problem and contributes to high-dimensional resolution. Compared with the traditional layered backprojection (BP) imaging, the layered focusing method based on phase compensation in the wavenumber domain has a lower computational complexity. Layered focusing combined with super-resolution processing effectively suppresses conical sidelobes, addresses layover issues, and establishes an accurate 3-D scattering model. The proposed method was validated using X-band airborne CFASAR data obtained in Rizhao, Shandong Province, China, in 2021. The experimental results indicate that the proposed method has low time complexity, and it can effectively suppress the conical sidelobe of CSAR and realize high-quality 3-D reconstruction of buildings.
Exact Stochastic Sşmulation Algorithms and Impulses in Biological Systems

The stochastic model is the only sort of expressions which can capture the randomness of biological systems under different reactions. There are mainly three methods; Gillespie, first reaction and next reaction algorithms; for implementing exact stochastic simulations in these systems. Although these algorithms are successful in explaining the natural behaviors of the systems’ activation, they cannot describe the absurd changes, i.e., impulses. Moreover, the source codes in R are not available and open for all users. In this study, we produce these R codes and insert two major scenarios inside. In the application, we use distinct dimensional systems and compare their computational demands.
Modified block preconditioner for generalized saddle point matrices with highly singular(1,1) blocks

ABSTRACT In this paper, based on the preconditioners presented by Zhang [A new preconditioner for generalized saddle matrices with highly singular(1,1) blocks. Int J Comput Maths. 2014;91(9):2091-2101], we consider a modified block preconditioner for generalized saddle point matrices whose coefficient matrices have singular (1,1) blocks. Moreover, theoretical analysis gives the eigenvalue distribution, forms of the eigenvectors and the minimal polynomial. Finally, numerical examples show the eigenvalue distribution with the presented preconditioner and confirm our analysis.
A Super Wideband Dual-Polarized Vivaldi Antenna for 5G mmWave Applications

Millimeter wave (mmWave) is a key band for fifth-generation (5G) mobile communication that features large available bandwidth and high data rates. Antenna elements are recommended to be dual-polarized, compact, wideband, and high gain to be utilized for 5G array antenna systems. In this paper, a miniaturized gain-enhanced Vivaldi antenna element in an evolutional-oriented process is designed, simulated, and successfully measured for 5G mmWave applications. The size of the antenna is as compact as 5.5mm $\times12$ mm. The measured operational bandwidth of the antenna element is between 22.5 – 45 GHz covering 5G n257, n258, n259, n260, and n261 frequency bands even though the simulation results reveal the extension of the bandwidth to 70 GHz. The results show a nearly constant end-fire radiation pattern with a measured gain of more than 5dBi across the whole bandwidth. The comparison of the proposed antenna with the most recent related works justifies the novelties and advantages of the antenna in terms of 5G requirements, bandwidth, and compactness properties. The proposed antenna element is a suitable candidate for large antenna arrays and 5G MIMO applications.
EM-Patroller: Entropy Maximized Multi-Robot Patrolling With Steady State Distribution Approximation

This letter investigates the multi-robot patrolling (MuRP) problem in a discrete environment with the objective of achieving uniform node coverage probability distribution by the robot team. Existing MuRP solutions for uniform node coverage either involve high computational complexity for the global optimal solution or rely on heuristics for approximate solutions without performance guarantees. To bridge the gap, we propose an efficient iterative algorithm, namely Entropy Maximized Patroller (EM-Patroller), with the per-iteration performance improvement guarantee and polynomial computational complexity. We reformulate the MuRP problem as an “unnormalized” joint steady state distribution entropy maximization problem and use multi-layer perceptron (MLP) to model the relationship between each robot's patrolling strategy and the individual steady state distribution. We derive a multi-agent model-based policy gradient method to update the robots' patrolling strategies towards the optimum. Complexity analysis indicates the polynomial computational complexity of EM-Patroller, and we show that EM-Patroller has additional benefits of accommodating user-defined joint steady state distributions and incorporating other objectives such as entropy maximization of individual steady state distribution. We compare EM-Patroller with state-of-the-art MuRP algorithms in various canonical MuRP environments and deploy it to a real multi-robot system for patrolling in a self-constructed indoor environment.
Dispersion-corrected PBEsol exchange-correlation functional

We study the compatibility between the PBEsol exchange-correlation energy functional of Phys. Rev. Lett. 100 , 136406 (2008) and the rVV10 van der Waals nonlocal correlation functional of Phys. Rev. B 87 , 041108 (2013). By applying a density-gradient dependence in the expression of rVV10, we develop a new functional: The PBEsol + rVV10s functional, which is remarkably accurate for layered solids, rare-gas crystals, densely packed bulk solids, and the adsorption of noble-gas atoms on metal surfaces, and is also competitive for noncovalent interactions between molecular complexes as well as for potential-energy curves of noble-gas dimers. The capacity of this dispersion-corrected functional to describe various interactions in solids makes it useful for electronic-structure calculations in solid-state physics and materials science.
Plasma Modification Techniques for Natural Polymer-Based Drug Delivery Systems

Natural polymers have attracted significant attention in drug delivery applications due to their biocompatibility, biodegradability, and versatility. However, their surface properties often limit their use as drug delivery vehicles, as they may exhibit poor wettability, weak adhesion, and inadequate drug loading and release. Plasma treatment is a promising surface modification technique that can overcome these limitations by introducing various functional groups onto the natural polymer surface, thus enhancing its physicochemical and biological properties. This review provides a critical overview of recent advances in the plasma modification of natural polymer-based drug delivery systems, with a focus on controllable plasma treatment techniques. The review covers the fundamental principles of plasma generation, process control, and characterization of plasma-treated natural polymer surfaces. It discusses the various applications of plasma-modified natural polymer-based drug delivery systems, including improved biocompatibility, controlled drug release, and targeted drug delivery. The challenges and emerging trends in the field of plasma modification of natural polymer-based drug delivery systems are also highlighted. The review concludes with a discussion of the potential of controllable plasma treatment as a versatile and effective tool for the surface functionalization of natural polymer-based drug delivery systems.
UXBIV: An Evaluation Framework for Business Intelligence Visualization

Nowadays, visualization is becoming an essential part of data analysis. Business Intelligence Visualization (BIV) is a powerful tool that helps modern business flows faster and smoother than ever before. However, research on BIV evaluation is severely lacking; most evaluation studies for BIV focus on usability, which have limited aspects covered for customers’ needs. The purpose of this research is to develop a UX framework that evaluates BIV (UXBIV), including decision-making experience and interactivity. First, we did a literature survey for good understanding of research progress in related fields, and established a conceptual framework. Second, we performed a case study that implemented this framework to demonstrate how our framework can be used in real business. Our analysis shows that this UXBIV framework is quite reasonable, and it can capture the differences among various BIV designs from the users’ standpoints. This UXBIV framework can help design BIV and promote better decision-making on business affairs.
Design of cointegrating vectors and its empirical implications

This work examines the design of cointegrating vectors by evaluating the performance of standard tests for unit roots/ stationary. It shows the behaviour of the estimated coefficients of the models with little variation in the number of replications. The maximum likelihood estimates were obtained by using Johansen? s algorithm. The system design indicates from the Monte Carlo experiments that for the cointegrating system to be efficient and consistent, the method must incorporate all prior knowledge about the presence of unit roots. This eliminates the median bias, the nonsymmentry; part of the nuisance parameter dependencies and increase efficiency. Empirically, the vector error correction estimates shows that the higher the lag interval the better the error correction model and the cointegrating equation provided the sample size of the series is not too short.
Dream to posture: visual posturing of a tendon-driven hand using world model and muscle synergies

Although tendon-driven anthropomorphic robot hands have the potential to achieve human-level dexterity, controlling them is a great challenge owing to their mechanical complexities. Therefore, investigating human-hand control strategies is of the utmost importance. An important skill that enables the versatile manipulation ability of humans is visual posturing, i.e. the skill to make arbitrary hand postures based solely on visual observation. Visual posturing facilitates manipulation learning by enabling visual imitation learning and reusing visually similar past experiences. Therefore, this study investigates a method to replicate visual posturing in anthropomorphic robotic hands. Visual posturing in tendon-driven hands is challenging because of the hysteresis in tendon systems, the partial observability of the problem, and the presence of many actuators owing to the antagonistic tendon arrangement. To address these challenges, we propose a method that combines a model predictive path integral, a world model, and bio-inspired muscle synergies. The evaluation in a physical tendon-driven anthropomorphic robot hand showed that the proposed method achieved better visual posturing performance than a naive regression model. We anticipate that our visual posturing method will lay the foundation for versatile manipulation controllers that can adaptively learn manipulation tasks, similar to humans. GRAPHICAL ABSTRACT