Miracle-dz/UniFAR-FTUs huggingface dataset:
Vibrations of an Incompressible Linearly Elastic Plate Using Discontinuous Finite Element Basis Functions for Pressure

We numerically analyze, with the finite element method, free vibrations of incompressible rectangular plates under different boundary conditions with a third-order shear and normal deformable theory (TSNDT) derived by Batra. The displacements are taken as unknowns at the nodes of a 9-node quadrilateral element and the hydrostatic pressure at four interior nodes. The plate theory satisfies the incompressibility condition, and the basis functions satisfy the Babuska-Brezzi condition. Because of the singular mass matrix, Moler's QZ algorithm (also known as the generalized Schur decomposition) is used to solve the resulting eigenvalue problem. Computed results for simply supported, clamped, and clamped-free rectangular isotropic plates agree well with the corresponding analytical frequencies of simply supported plates and with those found using the commercial software, abaqus, for other edge conditions. In-plane modes of vibrations are clearly discerned from mode shapes of square plates of aspect ratio 1/8 for all three boundary conditions. The magnitude of the transverse normal strain at a point is found to equal the sum of the two axial strains implying that higher-order plate theories that assume null transverse normal strain will very likely not provide good solutions for plates made of rubberlike materials that are generally taken to be incompressible. We have also compared the presently computed through-the-thickness distributions of stresses and the hydrostatic pressure with those found using abaqus.
Practical considerations for improved reliability and precision during compound specific analysis of δ15N in amino acids using a single combined oxidation-reduction reactor

RATIONALE There has been increased interest in the analysis for δ15N in amino acids to gain simultaneous insight into both trophic relationships and source producers within ecosystems. New developments in gas chromatography combustion isotope ratio mass spectrometry equipment has led to variable outcomes in performance due to limited information about best practices for new systems. METHODS Precision for δ15N in amino acids using the single combined oxidation-reduction reactor is improved across a sequence of analyses if the reactor is oxidized for a substantial period (2 h), immediately followed with a conditioning run of alkanes prior to analysis for N, and the liquid N2 CO2 trap is left immersed throughout. A five point calibration curve using amino acids with a range of δ15N values from −2.4‰ to +61.5‰ was used in combination with a 13 amino acid mixture to correct for offsets during derivatization. RESULTS Combining the improved setup with normalization techniques using both internal and external standards allows for a reliable throughput of ~25 samples per week. It allowed for a reproducible level of error of <±0.5‰ within standards repeated 10 times across each sequence and a sample error of (±0.18‰), which is lower than analytical error typically associated with δ15N-amino acid analysis (±1‰). CONCLUSIONS A few practical considerations regarding oxidation and conditioning of the combustion reactor allow for increased sequence capacity with the single combined oxidation-reduction reactor. These considerations combined with normalization techniques result in a higher throughput and reduced analytical error during analysis of δ15N in amino acids.
Detection of retinal abnormalities using smartphone-captured fundus images: a survey

Several retinal pathologies lead to severe damages that may achieve vision lost. Moreover, some damages require expensive treatment, other ones are irreversible due to the lack of therapies. Therefore, early diagnoses are highly recommended to control ocular diseases. However, early stages of several ocular pathologies lead to the symptoms that cannot be distinguish by the patients. Moreover, ageing population is an important prevalence factor of ocular diseases which is the cases of most industrial counties. Further, this feature involves a lake of mobility which presents a limiting factor to perform periodical eye screening. Those constraints lead to a late of ocular diagnosis and hence important ocular pathology patients are registered. The forecast statistics indicates that affected population will be increased in coming years. Several devices allowing the capture of the retina have recently been proposed. They are composed by optical lenses which can be snapped on Smartphone, providing fundus images with acceptable quality. Thence, the challenge is to perform automatic ocular pathology detection on Smartphone captured fundus images that achieves higher performance detection while respecting timing constraint with respect to the clinical employment. This paper presents a survey of the Smartphone-captured fundus image quality and the existing methods that use them for retinal structures and abnormalities detection. For this purpose, we first summarize the works that evaluate the Smartphone-captures fundus image quality and their FOV (field-of-view). Then, we report the capability to detect abnormalities and ocular pathologies from those fundus images. Thereafter, we propose a flowchart of processing pipeline of detecting methods from Smartphone captured fundus images and we investigate about the implementation environment required to perform the detection of retinal abnormalities.
Detection of Botnet Using Flow Analysis and Clustering Algorithm

With the increase of digital data on the internet, computers are at higher risk of getting corrupted through cyber-attacks. Criminals are adopting more and more sophisticated techniques to steal sensitive information from the web. The botnet is one of the most aggressive threats as it combines lots of advanced malicious techniques. Detection of the botnet is one of the most serious concerns and prominent research area among the researchers. This paper proposes a detection model using the clustering algorithm to group bot traffic and normal traffic into two different clusters. Our contribution focused on applying K-means clustering algorithm to detect botnets based on their detection rate (true and false positives). Experimental results clearly demonstrate the fact that with the help of clustering we were able to separate the complete dataset into two entirely distinguishable clusters, where one cluster is representing the botnet traffic and other one representing the normal traffic.
Substitute Seed Nodes Mining Algorithms for Influence Maximization in Multi-Social Networks

Due to the growing interconnections of social networks, the problem of influence maximization has been extended from a single social network to multiple social networks. However, a critical challenge of influence maximization in multi-social networks is that some initial seed nodes may be unable to be active, which obviously leads to a low performance of influence spreading. Therefore, finding substitute nodes for mitigating the influence loss of uncooperative nodes is extremely helpful in influence maximization. In this paper, we propose three substitute mining algorithms for influence maximization in multi-social networks, namely for the Greedy-based substitute mining algorithm, pre-selected-based substitute mining algorithm, and similar-users-based substitute mining algorithm. The simulation results demonstrate that the existence of the uncooperative seed nodes leads to the range reduction of information influence. Furthermore, the viability and performance of the proposed algorithms are presented, which show that three substitute node mining algorithms can find suitable substitute nodes for multi-social networks influence maximization, thus achieves better influence.
Submodularity in Conic Quadratic Mixed 0-1 Optimization

We describe strong convex valid inequalities for conic quadratic mixed 0-1 optimization. These inequalities can be utilized for solving numerous practical nonlinear discrete optimization problems from value-at-risk minimization to queueing system design, from robust interdiction to assortment optimization through appropriate conic quadratic mixed 0-1 relaxations. The inequalities exploit the submodularity of the binary restrictions and are based on the polymatroid inequalities over binaries for the diagonal case. We prove that the convex inequalities completely describe the convex hull of a single conic quadratic constraint as well as the rotated cone constraint over binary variables and unbounded continuous variables. We then generalize and strengthen the inequalities by incorporating additional constraints of the optimization problem. Computational experiments on mean-risk optimization with correlations, assortment optimization, and robust conic quadratic optimization indicate that the new inequalities strengthen the convex relaxations substantially and lead to significant performance improvements.
Magnetospheric Dynamo Driving Large‐scale Birkeland Currents

Based upon recent global magnetohydrodynamic (MHD) simulations, we provide a theoretical foundation for magnetospheric dynamos driving large‐scale field‐aligned current (FAC) systems. In the framework of MHD, the dynamo is a process in which plasma thermal energy is converted to electromagnetic energy. Theoretical analysis using ideal MHD equations indicates the existence of two types of dynamos that allow this energy conversion. One is the expanding slow dynamo associated with flux tube expansion, and the other is the contracting slow dynamo associated with flux tube contraction. The expanding slow is a stationary dynamo without significant magnetic field curvature, with the field intensity gradient playing a central role. In contrast, the contracting slow is a dynamo with finite time variation and finite magnetic field curvature. A supplementary MHD simulation in this study, together with those in the past studies, indicates the existence of a general relation between the main voltage generator (i.e., dynamo) and the main FAC generator (i.e., divergence of FACs) that appears commonly for large‐scale FAC systems. That is, the dynamo overlaps the FAC generator in a specific spatial configuration and that at the transition between compressible high beta plasma and incompressible low beta plasma. This overlap represents a coupling of slow mode and Alfvén mode disturbances. We performed linear analysis of that special configuration using ideal MHD equations and derived the general expression relating the voltage generator and the FAC generator.
Grain-size distribution unmixing using the R package EMMAgeo

Abstract. The analysis of grain-size distributions has a long tradition in Quaternary Science and disciplines studying Earth surface and subsurface deposits. The decomposition of multi-modal grain-size distributions into inherent subpopulations, commonly termed end-member modelling analysis (EMMA), is increasingly recognised as a tool to infer the underlying sediment sources, transport and (post-)depositional processes. Most of the existing deterministic EMMA approaches are only able to deliver one out of many possible solutions, thereby shortcutting uncertainty in model parameters. Here, we provide user-friendly computational protocols that support deterministic as well as robust (i.e. explicitly accounting for incomplete knowledge about input parameters in a probabilistic approach) EMMA, in the free and open software framework of R. In addition, and going beyond previous validation tests, we compare the performance of available grain-size EMMA algorithms using four real-world sediment types, covering a wide range of grain-size distribution shapes (alluvial fan, dune, loess and floodplain deposits). These were randomly mixed in the lab to produce a synthetic data set. Across all algorithms, the original data set was modelled with mean R2 values of 0.868 to 0.995 and mean absolute deviation (MAD) values of 0.06 % vol to 0.34 % vol. The original grain-size distribution shapes were modelled as end-member loadings with mean R2 values of 0.89 to 0.99 and MAD of 0.04 % vol to 0.17 % vol. End-member scores reproduced the original mixing ratios in the synthetic data set with mean R2 values of 0.68 to 0.93 and MAD of 0.1 % vol to 1.6 % vol. Depending on the validation criteria, all models provided reliable estimates of the input data, and each of the models exhibits individual strengths and weaknesses. Only robust EMMA allowed uncertainties of the end-members to be objectively estimated and expert knowledge to be included in the end-member definition. Yet, end-member interpretation should carefully consider the geological and sedimentological meaningfulness in terms of sediment sources, transport and deposition as well as post-depositional alteration of grain sizes. EMMA might also be powerful in other geoscientific contexts where the goal is to unmix sources and processes from compositional data sets.
Error Correction in Coded Caching With Symmetric Batch Prefetching

In coded caching, a single server is connected to a set of users through a shared bottleneck link, which is assumed to be error free. During non-peak hours, all the users fill their local cache with portions of the files available. During the delivery phase, each user requests a file and the server delivers coded transmissions to meet the demands. In this paper, the links between the server and the users are assumed to be error prone. Prefetching errors are also considered. A new delivery scheme is required to meet the demands of each user even after receiving a finite number of transmissions in error in the presence of erroneous portions of files in the cache. The minimum average rate and minimum peak rate for this problem are characterized. Closed form expressions for average and peak rates for a particular caching scheme, namely, symmetric batch prefetching are established when there are no prefetching errors. An optimal linear error correcting delivery scheme is proposed for coded caching problems with symmetric batch prefetching in the absence of prefetching errors. In addition to this, lower bounds are established for the optimal rate required when there are prefetching errors in symmetric batch prefetching.
Äâóõñòóïåí÷àòûå Ìîäåëè È Ïðîáëåìà Ïåðåîáó÷åíèÿ Â Ëàòåíòíîì Ñåìàíòè÷åñêîì Àíàëèçå *

Ïðåäëàãàåòñÿ àëãîðèòì âûÿâëåíèÿ ñêðûòûõ èíòåðåñîâ êëèåíòîâ ïî íàáëþäàåìîìó ïðîòîêîëó èõ äåéñòâèé, íàïðèìåð, ïîñåùåíèé ñàéòîâ. Àëãîðèòì ñî÷åòàåò â ñåáå èäåè àíàëèçà êëèåíòñêèõ ñðåä è âåðîÿòíîñòíîãî ëàòåíòíîãî ñåìàíòè÷åñêîãî àíàëèçà. Äëÿ îïòèìèçàöèè ïàðàìåòðîâ àëãîðèòìà è îáúåêòèâíîãî ñðàâíåíèÿ åãî ñ äðóãèìè àëãîðèòìàìè ââîäèòñÿ êðèòåðèé êà÷åñòâà, îñíîâàííûé íà êëàññèôèêàöèè çàðàíåå ðàçìå÷åííîãî ìíîæåñòâà ñàéòîâ. Ýêñïåðèìåíòû ïîêàçûâàþò, ÷òî êà÷åñòâî èìååò îïòèìóì ïî îñíîâíûì ïàðàìåòðàì àëãîðèòìà, è ÷òî ïîïûòêà ÷ðåçìåðíî òî÷íîé îïòèìèçàöèè ìîæåò ïðèâîäèòü ê ïåðåîáó÷åíèþ.
SIAG/OPT Views-and-News pdfsubject

Filter Methods and Optimization Software Introduction by the Editors Lúıs N. Vicente and Andreas Wächter . 1 A Brief History of Filter Methods Roger Fletcher, Sven Leyffer, and Philippe Toint . 2 NEOS Version 5 Jason Sarich . 12 DTOS — A Service for the Optimization Community Hans D. Mittelmann . 17
Risk appetite estimation on financial markets

The thesis studies role of risk appetite on financial markets. In theoretical part, author describes a notion of this concept, refers to known methods and describes the role of behavioral economics in treatment of this concept. In practical part, models are constructed to explain influence of selected indices on CDS which proxy for sovereign risk of individual developed and emerging markets. Across the globe, there is found strong common component which can be explained by selected indices. It is also observed that GRAI indicator can play role in case of emerging markets. In case of developed markets, however, this property is missing. Granger causality does not prove relationship of GRAI explanation power in direction to sovereign risk. JEL Classification C51, D80, F40 G12, G15
The development of a South African medical practitioner outcome questionnaire

There is much room for improvement within the South African healthcare system. As recognised by many middle-income countries, a key point of leverage is the utilisation of primary care staff. However, key stakeholders have recognised a gap between the skills of healthcare professionals and the needs of the general population. Therefore, efforts such as increasing frontline staff or spending more on hospital resources alone will not lead to improved primary care outcomes. The argument is made in this study that training institutions and primary care units would benefit from an accurate and comprehensive medical practitioner competency model as it would allow training and management efforts to be better suited for the South African context and be clearly aligned with the needs of the general population. The study aimed to develop a theoretical model of medical practitioner performance with emphasis on non-clinical performance. The objectives of this study were twofold. Firstly, the outcomes and competencies of optimal performance of medical practitioners who act as the first point of contact in primary healthcare facilities were defined. Secondly, a South African Medical practitioner outcome questionnaire to measure these outcomes was developed. This study applied a Delphi technique (n=4) as well as content validity rating (n=24) to adequately conceptualise the outcomes, obtain consensus among experts, and develop items for the questionnaire. Various interprofessional subject matter experts participated in the study. The study resulted in a South African medical practitioner outcome questionnaire (SAMPOQ) which consists of a self-rating, patient-rating and other-rating form. It concluded with a proposed medical practitioner competency model. It is recommended that future researchers test the SAMPOQ on a representative sample to statistically evaluate its psychometric properties and evaluate the questionnaire. Stellenbosch University https://scholar.sun.ac.za
An Efficient Footprint-Guided Compact Finite Element Algorithm for 3-D Airborne Electromagnetic Modeling

The airborne electromagnetic (AEM) method is an efficient tool for assessing conductivity structures near the earth’s surface. The huge amounts of collected data over a survey area of tens to thousands of square kilometers result in an extremely high computational cost for rigorous modeling. Fortunately, for each transmitter and receiver (Tx–Rx) station, a volume of limited scale beneath the transmitter, called the footprint, contains the majority of the induced current and contributes most of the EM response at the receiver. In this letter, we develop a footprint-guided compact finite element method (CFEM), in which the inhomogeneous conductivity structure in the entire survey area is divided into small subareas based on the footprint so that the forward modeling for each subarea can be performed efficiently. The computational domain for every single Tx–Rx station consists of a small subarea and a surrounding layer. The accuracy of the algorithm is verified by comparing its solutions with semianalytical solutions on a layered earth model, and its applicability and efficiency are demonstrated with a more complex 3-D model consisting of a large inhomogeneous structure.
ECONOMIC EXPOSURE AND INTEGRATED RISK MANAGEMENT

Most corporate risk management research focuses on particular risk exposures to the exclusion of other interrelated exposures. By contrast, this study models corporate risk exposures using a multivariate approach integrating the distinct exposures of interest to finance, international business, and strategy researchers. The paper addresses the implications of multivariate modeling for corporate risk management, some key methodological issues arising in empirical estimation of corporate economic exposures, and directions for research on integrated risk management. (? ) 1998 John Wiley & Sons, Ltd.
Stable Activated Furan and Donor–Acceptor Stenhouse Adduct Polymer Conjugates as Chemical and Thermal Sensors

The development and application of novel activated furan copolymers is reported. The platform provides a colorimetric method for sensing amines in aqueous media through the generation of a highly colored donor acceptor Stenhouse adduct (DASA). Furthermore, the resulting DASA polymer conjugates, which are obtained after amine sensing, are characterized to determine fundamental structure property relationships for this emerging class of negative photochromic species.
Transcriptomic study of the mechanism of anoikis resistance in head and neck squamous carcinoma

Background Normal epithelial cells rapidly undergo apoptosis as soon as they lose contact with the extracellular matrix (ECM), which is termed as anoikis. However, cancer cells tend to develop a resistance mechanism to anoikis. This acquired ability is termed as anoikis resistance. Cancer cells, with anoikis resistance, can spread to distant tissues or organs via the peripheral circulatory system and cause cancer metastasis. Thus, inhibition of anoikis resistance blocks the metastatic ability of cancer cells. Methods Anoikis-resistant CAL27 (CAL27AR) cells were induced from CAL27 cells using the suspension culture approach. Transcriptome analysis was performed using RNA-Seq to study the differentially expressed genes (DEGs) between the CAL27ARcells and the parental CAL27 cells. Gene function annotation and Gene Ontology (GO) enrichment analysis were performed using DAVID database. Signaling pathways involved in DEGs were analyzed using Gene Set Enrichment Analysis (GSEA) software. Analysis results were confirmed by reverse transcription PCR (RT-PCR), western blotting, and gene correlation analysis based on the TCGA database. Results GO enrichment analysis indicated that the biological process (BP) of the DEGs was associated with epidermal development, DNA replication, and G1/S transition of the mitotic cell cycle. The analysis of cellular component (CC) showed that the most significant up-regulated genes were related to extracellular exosome. KEGG Pathway analysis revealed that 23 signaling pathways were activated (p-value ≤ 0.05, FDR q-value ≤ 0.05) and 22 signaling pathways were suppressed (p-value ≤ 0.05, FDR q-value ≤ 0.05). The results from the GSEA indicated that in contrast to the inhibition of EGFR signaling pathway, the VEGF signaling pathway was activated. The VEGF signaling pathway possibly activates STAT3 though induction of STAT3 phosphorylation. Gene correlation analysis revealed that the VEGFA- STAT3-KLF4-CDKN1A signal axis was not only present in head and neck squamous carcinoma (HNSCC) but also two other epithelial-derived carcinomas that highly express VEGFA, including kidney renal clear cell carcinoma (KIRC) and ovarian serous cystadenocarcinoma (OV).
MHD free convective flow past an impulsively started vertical plate through a porous medium with radiative heat transfer and chemical reaction in a rotating system

The effect of Hall current, radiation and chemical reaction on MHD free convective flow past an impulsively started vertical plate through a porous medium in a rotating system is considered. The analytical solutions of dimensionless governing equations are obtained by Laplace transform technique. The effects of various parameters on the fluid velocity, concentration and temperature distribution near the plate are analyzed and shown graphically. The numerical values of shear stress at the plate are shown in a table. It is observed that the fluid velocity near the plate is affected significantly by Hall current, radiation, chemical reaction and porous medium. The conclusion of study have applications in the field related to the solar physics dealing with the solar cycle, the sunspot development, the structure of rotating magnetic stars etc.