Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduced basis methods for parabolic PDEs with parameter functions in high dimensions and applications in finance

The present thesis deals with variants of the space-time reduced basis method for parametrised parabolic partial differential equations. The reduced basis method is a well-known projection based model reduction technique for parameter dependent problems. We consider parabolic partial differential equations in space-time variational formulation. The formulation includes integration over space and time and a model reduction is achieved in both, space and time dimension. One objective of this thesis is the development of a reduced basis method to handle functions as parameters. A parameter in the reduced basis method is usually a vector of real numbers that describes the underlying model properties. The more general concept of a parameter space that is a subspace of a Hilbert space requires new reduced basis generation processes. In particular, the initial value of a parabolic partial differential equation is considered as a function parameter. A Two-Step Greedy Method is presented where two reduced bases are constructed, one for the approximation of the initial value and one for the evolution of the solution. The decomposition into two steps allows for a better approximation error control. A-priori as well as a-posteriori error bounds are provided. As the space-time reduced basis method deals with time as additional dimension, the reduced basis generation process is computationally expensive. We apply the H-Tucker low rank tensor format in the reduced basis offline phase to reduce the computational costs. The high dimensional linear system is decomposed in its tensor product components and can efficiently be solved applying the low rank tensor method. The resulting solution of the high dimensional problem implies an additional approximation error that has to be considered in the basis generation process. Error analysis is provided to combine both model reduction methods. For derivative pricing in finance, one needs to calculate the conditional expectation of the discounted payoff under a risk neutral measure. To this end one can equivalently solve the associated parabolic partial differential equation in diffusion based models. If we want to apply the reduced basis method as model reduction scheme, we usually have to construct a new reduced basis for each payoff function. To avoid this effort, the reduced basis method for parameter functions can be applied. Two standard option pricing models are considered, the Black-Scholes model and the Heston model. Both models provide a closed form solution such that the numerical results can easily be verified.
THE ECONOMICS OF STARTUP BUSINESS FINANCE: AN INVESTIGATION THROUGH THE LENS OF FINANCIAL GROWTH CYCLE THEORY

The provision of finance is the key to the survival and success of new firms. The current paper examines the startup firms’ finance acquisition through the viewpoint of financial growth cycle theory. We used chi-square and Mann-Whitney U tests to examine our hypotheses. Our study uses data from 386 Indian startup entrepreneurs over the period 2019 – 2021. Our results show that the startups access angel finance significantly in the initial years and the venture capital, banks and NBFCs in their later stage of life. Our findings argue that Indian startups partially follow the financing patterns proposed by the financial growth cycle theory.
On minimal absorbent sets for some types of tolerance relations

Tolerance relations provide the most general tool for studying indiscernibility phenomena. The importance of those phenomena had been noticed by Poincare and studies by, among others, Menger, Zadeh, and Pawlak, has led to the emergence of such approaches to indiscernibility as probabilistic theory of relations, fuzzy sets and rough sets. We contribute to the general theory of tolerance relations by proving that, in case of a non-Archimedean tolerance r, any subset of the tolerance space has a minimal absorbent extension. We indicate a possible application of minimal absorbent sets as a tool in defining the informational content of an information system and in studying formally the structure of reducts, and by applying an idea of a discernibility function due to Skowron we offer a positive result on the related Minimal Absorbent Extension Problem.
Role of Deep Learning in Computed Tomography

Computed tomography has played an instrumental role in the understanding of the pathophysiology of atherosclerosis in coronary artery disease. It enables visualization of the plaque obstruction and vessel stenosis in a comprehensive manner. As technology for computed tomography is constantly evolving, coronary applications and possibilities are constantly expanding. This influx of information can overwhelm a physician's ability to interpret information in this era of big data. Machine learning is a revolutionary approach that can help provide limitless pathways in patient management. Within these machine algorithms, deep learning has tremendous potential and can revolutionize computed tomography and cardiovascular imaging. In this review article, we highlight the role of deep learning in various aspects of computed tomography.
Online Adaptive Integral Reinforcement Learning for Nonlinear Multi-Input System

In this brief article, a novel adaptive integral reinforcement learning (AIRL) scheme is proposed for the continuous-time (CT) system. Moreover, it is used to learn the optimal controls of the partially unknown multi-input nonlinear system. Firstly, the Nash equilibrium of multi-input is defined. Two neural networks (NN) are used to approximate the cost functions with the integral reinforcement signal, which can avoid directly solving the Hamilton–Jacobi–Bellman (HJB) equation such that dynamic information and derivatives of NN activations are not needed. Then, a novel learning algorithm is used to update the unknown NN weights. The studied weights are used to obtain the optimum multi-policies. The learned weight convergence is proved. Finally, two examples are presented to verify the system performance with the proposed AIRL scheme.
Using McMC method to estimate double exponential jump diffusion model

In this paper we propose a Bayesian method to estimate the double exponential jump diffusion model(DEJD). The approach is based on the Markov chain Monte Carlo(McMC) method with the likelihood of the discredited process as the approximate posterior likelihood.We demonstrate that the McMC method provides a useful tool in analyzing DEJD diffusion.In particular,quantities of posterior distributions obtained from the McMC outputs can be used for statistical inference.The McMC method is based on Euler scheme.Our simulation shows that the DEJD diffusion exhibits many stylized characters about asset returns such as thick tails,and smiles effect.
Plant-Derived Quorum Sensing Inhibitors (Quercetin, Vanillin and Umbelliferon) Modulate Cecal Microbiome, Reduces Inflammation and Affect Production Efficiency in Broiler Chickens

Quorum sensing inhibitors (QSIs) are an attractive alternative to antibiotic growth promoters in farmed animal nutrition. The goal of the study was the diet supplementation of Arbor Acres chickens with quercetin (QC), vanillin (VN), and umbelliferon (UF), which are plant-derived QSIs preliminarily showing cumulative bioactivity. Chick cecal microbiomes were analyzed by 16s rRNA sequencing, inflammation status was assessed by blood sample analyses, and zootechnical data were summarized in the European Production Efficiency Factor (EPEF). When compared to the basal diet control group, a significant increase in the Bacillota:Bacteroidota ratio in the cecal microbiome was found in all experimental subgroups, with the highest expression > 10 at VN + UV supplementation. Bacterial community structure in all experimental subgroups was enriched with Lactobacillaceae genera and also changed in the abundance of some clostridial genera. Indices of richness, alpha diversity, and evenness of the chick microbiomes tended to increase after dietary supplementation. The peripheral blood leukocyte content decreased by 27.9–45.1% in all experimental subgroups, likely due to inflammatory response reduction following beneficial changes in the cecal microbiome. The EPEF calculation showed increased values in VN, QC + UF, and, especially, VN + UF subgroups because of effective feed conversion, low mortality, and broiler weight daily gain.
Vasospasm in the First Septal Perforator Branch and Late High-Grade Atrioventricular Block Following Successful Primary Percutaneous Coronary Intervention for the Proximal Left Anterior Descending Coronary Artery: A Case Report

We present a case of a high-degree advanced atrioventricular block (AVB), which occurred 24 hours after successful primary percutaneous coronary intervention (PCI) in the proximal left anterior descending coronary artery (LAD), the culprit of ST-segment elevation myocardial infarction (STEMI). The methylergometrine provocation test for coronary vasospasms, which was performed on the eighth hospital day, revealed transient total occlusion of the first septal perforator branch. After prescribing a calcium channel blocker to the patient, AVB did not recur for three years, as confirmed using an implantable loop recorder (ILR). In this patient, delayed high-grade AVB following primary PCI in the proximal LAD might be caused by the spasm of the first septal perforator branch. Documented cases of spasms in this branch are rare.
Rotational Velocities of “Field” Be Stars

Distributions of true rotational velocities as a function of spectral type for different luminosity class groups of B and Be stars are compared. While the distributions for B stars differ clearly from one luminosity class to another, those of Be stars differ less, which indicates that due to rotational effects many Be stars are considered more evolved than they actually are. Be stars 'select' a narrow range of true rotational velocities to display the Be phenomenon and those of latter spectral types rotate only marginally faster than the early ones.
Three-Dimensional Multi-UAV Trajectory Design for Cooperative Video Inspection and Uploading

This paper studies the multiple unmanned aerial vehicles (UAVs) trajectory design for post-disaster information collection via cooperative video inspection and information uploading, via the sustained ground base stations (BSs). The locations to be inspected are modeled as points of interest (PoIs) with heterogeneous resolution requirements. The three-dimensional (3D) trajectories for multiple cooperative UAVs are designed to minimize the time for successfully inspecting all the PoIs and maximize the communication time for the video uploading. An UAV inspection model is built to clarify the criteria for successful inspection, which is related to the UAV's 3D positions and velocity. The proposed UAV trajectory design involves two steps. First, the PoIs in proximity are grouped by convex optimization. Then, the multiple UAV trajectories are jointly designed by solving a multiple traveling salesman problem (MTSP). Numerical results show that the proposed design can significantly reduce the multi-UAV cooperative video inspection time, which enables swift response and efficient planning for post-disaster rescue.
Schur Polynomials, Restricted Schur Polynomials and the AdS/CFT Correspondence

In this thesis we introduce novel technology pertaining to the calculation of certain classes of correlation functions in the half BPS, near BPS and multimatrix sectors (particularly the SU(2) sector) of N = 4 Super Yang-Mills (SYM) theory using the Schur polynomial and restricted Schur polynomial bases. This technology allows the detailed exploration of a host of physical questions within the AdS/CFT correspondence. We first treat multi-point correlators of restricted Schur polynomials which constitute a particularly convenient basis for the SU(2) and general multi-matrix sectors of N = 4 SYM. We introduce a product rule for the restricted Schur polynomials, which, together with the two point correlator result of arXiv:0801.2061 allows us to compute exact multi-point correlators, in the free field theory limit. This facilitates the exploration of physical questions such as elucidating the appropriate degrees of freedom for a perturbative description of quantum gravity in the sectors under consideration. We then treat the calculation of correlators of operators in the presence of large background operators with aR-charge ofO(N) that are dual to asymptotically AdS5×S backgrounds. Evaluating these correlators is a hard problem in general since the planar approximation fails. In this thesis we develop general techniques, known as the “cutting rules”, that allow the computation of such correlators. Specializing to the LLM annulus geometry allows a number of concrete results to be derived. We then study the perturbation theory of these correlators and identify new perturbative expansion parameters replacing 1/N . Motivated by these results we explore new BMN-type sectors. Finally, we treat the problem of computing the anomalous dimensions of a class of (nearly) half BPS operators with a large R-charge. This problem is reduced to the problem of diagonalizing a Cuntz oscillator chain. Non-planar corrections must be summed to correctly construct the Cuntz oscillator dynamics. We explore whether these non-planar corrections that account for backreaction from the heavy operator rather than quantum corrections in the dual gravitational theory also spoil integrability as is generally the case with quantum corrections. We find a limit in which our Cuntz chain continues to admit extra conserved charges suggesting that integrability might survive.
Handling discardable measurements in power system state estimation

Observability analysis based exclusively on topological information may lead to systems whose state cannot be estimated by regular state estimation methods. Some practical situations in which the presence of the so-called discardable measurements may pass undetected by topological observability analysis are discussed. As a consequence, wrong results, or even convergence problems, may occur. A numerically based observability analysis procedure is suggested for handling such cases; the new technique is an extension of previously published work on numerical observability analysis. The technique is fully illustrated by small scale examples taken from a real-life system where difficulties with discardable measurements have been observed. <<ETX>>
Phytomediated-Assisted Preparation of Cerium Oxide Nanoparticles Using Plant Extracts and Assessment of Their Structural and Optical Properties

Cerium oxide nanoparticles were obtained using aqueous extracts of Chelidonium majus and Viscum album. X-ray diffractometry analysis confirmed the crystalline structure of the synthesized cerium oxide nanoparticles calcined at 600 °C. Scanning electron microscopy, UV-Vis reflectance and Raman spectroscopy, XPS, and fluorescence studies were utilized to interpret the morphological and optical properties of these nanoparticles. The STEM images revealed the spherical shape of the nanoparticles and that they were predominantly uniform in size. The optical band gap of our cerium nanoparticles was determined to be 3.3 and 3.0 eV from reflectance measurements using the Tauc plots. The nanoparticle sizes evaluated from the Raman band at 464 cm−1 due to the F2g mode of the cubic fluorite structure of cerium oxide are close to those determined from the XRD and STEM data. The fluorescence results showed emission bands at 425, 446, 467, and 480 nm. The electronic absorption spectra have exhibited an absorption band around 325 nm. The antioxidant potential of the cerium oxide nanoparticles was estimated by DPPH scavenging assay.
Genomic and Epigenetic Changes Drive Aberrant Skeletal Muscle Differentiation in Rhabdomyosarcoma

Simple Summary Rhabdomyosarcoma is the most common soft tissue cancer in children and adolescents. Its resemblance to skeletal muscle tissue distinguishes rhabdomyosarcomas from other types of soft tissue cancer. The development and integrity of healthy skeletal muscle depend on a strictly regulated, hierarchically organized machinery in cells. In rhabdomyosarcoma, this process goes awry, resulting in aberrant, malignant skeletal muscle states. These aberrant skeletal muscle states define subtypes of rhabdomyosarcomas. In this review, we describe normal muscle development and summarize recent insights into how changes in rhabdomyosarcoma cells disrupt normal skeletal muscle homeostasis, thereby defining the cancerous nature of this disease. We also describe differences in myogenic differentiation characteristics between different groups of cells within the tumors. Such differences appear to be dynamic and influence the behavior of the cells. We believe that interactions between cancer genes/proteins and basic muscle programs are key to understanding the cancerous identity of rhabdomyosarcoma and may provide windows of opportunity with regard to rhabdomyosarcoma treatment. Abstract Rhabdomyosarcoma (RMS), the most common soft-tissue sarcoma in children and adolescents, represents an aberrant form of skeletal muscle differentiation. Both skeletal muscle development, as well as regeneration of adult skeletal muscle are governed by members of the myogenic family of regulatory transcription factors (MRFs), which are deployed in a highly controlled, multi-step, bidirectional process. Many aspects of this complex process are deregulated in RMS and contribute to tumorigenesis. Interconnected loops of super-enhancers, called core regulatory circuitries (CRCs), define aberrant muscle differentiation in RMS cells. The transcriptional regulation of MRF expression/activity takes a central role in the CRCs active in skeletal muscle and RMS. In PAX3::FOXO1 fusion-positive (PF+) RMS, CRCs maintain expression of the disease-driving fusion oncogene. Recent single-cell studies have revealed hierarchically organized subsets of cells within the RMS cell pool, which recapitulate developmental myogenesis and appear to drive malignancy. There is a large interest in exploiting the causes of aberrant muscle development in RMS to allow for terminal differentiation as a therapeutic strategy, for example, by interrupting MEK/ERK signaling or by interfering with the epigenetic machinery controlling CRCs. In this review, we provide an overview of the genetic and epigenetic framework of abnormal muscle differentiation in RMS, as it provides insights into fundamental mechanisms of RMS malignancy, its remarkable phenotypic diversity and, ultimately, opportunities for therapeutic intervention.
Soapy: an adaptive optics simulation written purely in Python for rapid concept development

Soapy is a newly developed Adaptive Optics (AO) simulation which aims be a flexible and fast to use tool-kit for many applications in the field of AO. It is written purely in the Python language, adding to and taking advantage of the already rich ecosystem of scientific libraries and programs. The simulation has been designed to be extremely modular, such that each component can be used stand-alone for projects which do not require a full end-to-end simulation. Ease of use, modularity and code clarity have been prioritised at the expense of computational performance. Though this means the code is not yet suitable for large studies of Extremely Large Telescope AO systems, it is well suited to education, exploration of new AO concepts and investigations of current generation telescopes.
Microstructural and Mechanical Characteristics of Alkali-Activated Binders Composed of Milled Fly Ash and Granulated Blast Furnace Slag with µ-Limestone Addition

Concrete is the most used construction material, needing large quantities of Portland cement. Unfortunately, Ordinary Portland Cement production is one of the main generators of CO2, which pollutes the atmosphere. Today, geopolymers are an emerging building material generated by the chemical activity of inorganic molecules without the Portland Cement addition. The most common alternative cementitious agents used in the cement industry are blast-furnace slag and fly ash. In the present work, the effect of 5 wt. % µ-limestone in mixtures of granulated blast-furnace slag and fly ash activated with sodium hydroxide (NaOH) at different concentrations was studied to evaluate the physical properties in the fresh and hardened states. The effect of µ-limestone was explored through XRD, SEM-EDS, atomic absorption, etc. The addition of µ-limestone increased the compressive strength reported values from 20 to 45 MPa at 28 days. It was found by atomic absorption that the CaCO3 of the μ-limestone dissolved in NaOH, precipitating Ca(OH)2 as the reaction product. SEM-EDS analysis showed a chemical interaction between C-A-S-H- and N-A-S-H-type gels with Ca(OH)2, forming (N, C)A-S-H- and C-(N)-A-S-H-type gels, improving mechanical performance and microstructural properties. The addition of μ-limestone appeared like a promising and cheap alternative for enhancing the properties of low-molarity alkaline cement since it helped exceed the 20 MPa strength recommended by current regulations for conventional cement.
Den Elastizitätsmodul sicher bestimmen : Voraussetzungen für die Kraft- und Dehnungsmessung im Zugversuch

Problems of reliable determination of the Young's modulus in mechanical material testing. The Young's modulus is an important property for the description of the behaviour of materials. Comparing test results from round robins, significant differences were found. Within this contribution the requirements of measurement systems with regard to the determination of the Young's modulus in tensile testing are described. Special problems such as resolution, accuracy and specified range of the test equipment by conventional and computer aided load-strain-measuring based on the European Standard EN 10002 are highlighted. Different methods of modulus calculation are compared.
The Effect of Lung Resection for NSCLC on Circulating Immune Cells: A Pilot Study

This pilot study sought to evaluate the circulating levels of immune cells, particularly regulatory T-cell (Treg) subsets, before and after lung resection for non-small cell lung cancer. Twenty-five patients consented and had specimens collected. Initially, peripheral blood of 21 patients was collected for circulating immune cell studies. Two of these patients were excluded due to technical issues, leaving 19 patients for the analyses of circulating immune cells. Standard gating and high-dimensional unsupervised clustering flow cytometry analyses were performed. The blood, tumors and lymph nodes were analyzed via single-cell RNA and TCR sequencing for Treg analyses in a total of five patients (including four additional patients from the initial 21 patients). Standard gating flow cytometry revealed a transient increase in neutrophils immediately following surgery, with a variable neutrophil–lymphocyte ratio and a stable CD4–CD8 ratio. Unexpectedly, the total Treg and Treg subsets did not change with surgery with standard gating in short- or long-term follow-up. Similarly, unsupervised clustering of Tregs revealed a dominant cluster that was stable perioperatively and long-term. Two small FoxP3hi clusters slightly increased following surgery. In the longer-term follow-up, these small FoxP3hi Treg clusters were not identified, indicating that they were likely a response to surgery. Single-cell sequencing demonstrated six CD4+FoxP3+ clusters among the blood, tumors and lymph nodes. These clusters had a variable expression of FoxP3, and several were mainly, or only, present in tumor and lymph node tissue. As such, serial monitoring of circulating Tregs may be informative, but not completely reflective of the Tregs present in the tumor microenvironment.