BUCKLING ANALYSIS OF THE INDUSTRIAL FACTORY MODEL BY FINITE ELEMENT METHOD

Buckling is a subject that has been discussed for a long time, however, it still be studied and developed due to its practicality. The following article introduces two methods that are used to solve the problems involving buckling of the beam, shell and solid with an I shape cross-section having different cases of boundary load. The theory which is used in this article is Euler's formula and Eurocode 3 standard. The analytical results by ANSYS commercial software are compared with the theoretical results and results from Eurocode 3 standard. The authors based on the reliability of the calculating results to simulate buckling of the industrial factory model with different cases of load conditions. The simulating results show a general view of buckling cases

Bayesian Deep Learning and Uncertainty in Computer Vision

Visual data contains rich information about the operating environment of an intelligent robotic system. Extracting this information allows intelligent systems to reason and decide their future actions. Erroneous visual information, therefore, can lead to poor decisions, causing accidents and casualties, especially in a safety-critical application such as automated driving. One way to prevent this is by measuring the level of uncertainty in the visual information interpretation, so that the system knows the reliability degree of the extracted information. Deep neural networks are now being used in many vision tasks due to their superior accuracy compared to traditional machine learning methods. However, their estimated uncertainties have been shown to be unreliable. To mitigate this issue, researchers have developed methods and tools to apply Bayesian modeling to deep neural networks. This results in a class of models known as Bayesian neural networks, whose uncertainty estimates are more reliable and informative. In this thesis, we make the following contributions in the context of Bayesian Neural Network applied to vision tasks. In particular: - We improve the understanding of visual uncertainty estimates from Bayesian deep models. Specifically, we study the behavior of Bayesian deep models applied to road-scene image segmentation under different factors, such as varying weather, depth, and occlusion levels. - We show the importance of model calibration technique in the context of autonomous driving, which strengthens the reliability of the estimated uncertainty. We demonstrate its effectiveness in a simple object localization task. - We address the high run-time cost of the current Bayesian deep learning techniques. We develop a distillation technique based on the Dirichlet distribution, which allows us to estimate the uncertainties in real-time

Artefakte der Bildgebung und Beeinflussung der Magnetkraft

Einleitung: Primärteile prothetisch oder epithetisch genutzter Magnetattachments werden auf Pfeilerzähnen und Implantaten befestigt. Bei MR-Untersuchungen sind zwei Wechselwirkungen zu erwarten: Beeinträchtigung der Bildgebung durch Artefakte und Veränderung der Flussdichte durch das Hauptfeld (B0) des MRT. Ziele dieser In-vitro-Untersuchung sind: - Die Bestimmung der Maximalausdehnung der bei 1,5 und 3 T und drei typischen MR-Sequenzen auftretenden Suszeptibilitätsartefakte. - Die Messung der Entmagnetisierung der im MRT exponierten Magnete bei unterschiedlichen Positionen zu B0. Methodik: Der maximale Radius der um drei verschiedene Minimagnet-Typen und zwei ferromagnetische Gegenanker auftretenden Signalauslöschungszonen wurde am SNR-Phantom bei den drei MR-Sequenzen SE-T1, SE-T2 und GE-T2* gemessen. In einer ersten Entmagnetisierungsstudie wurden 30 SmCo- und 60 NdFeB-Magnete und in einer Folgestudie 40 SmCo-Magnete mit erhöhter Koerzitivkraft dem Hauptfeld eines 1,5- und eines 3 T-MRT in verschiedenen Positionen im Gerätetunnel und am Geräteportal ausgesetzt. Als Äquivalent für die Haftkraft wurde die Flussdichte mit einem Teslameter gemessen. Ergebnisse: Die Auslöschungszonen zeigten keine klinisch relevanten Unterschiede bei den verschiedenen Prüfkörpern und den beiden MRT-Hauptfeldstärken. Deutliche Unterschiede traten jedoch in Abhängigkeit von den genutzten MR-Sequenzen auf: Bei den Spinecho-Sequenzen fanden sich zwar insgesamt viel kleinere, aber deutlich unsymmetrische Signallöschungszonen, deren maximaler Radius bis zu 7,4 cm betrug. Die Signallöschungen bei Gradientenecho-Sequenzen zeigten eine mehr symmetrische und großflächige Formation mit einem Maximalradius bis zu 9,7 cm. Für das Ausmaß der Demagnetisierung sind die Ausrichtung der Minimagnete im MRT-Hauptfeld (B0) und dessen Stärke entscheidend. Bei 1,5 T wurde die Flussdichte von NdFeB- und SmCo-Magneten bei Antiparallelität zu B0 deutlich reduziert, bei 3T wurden beide Magnettypen in antiparalleler Lage umgepolt. SmCo-Magnete mit erhöhter Koerzitivkraft widerstanden dem 1,5 T-Feld, wurden bei 3 T jedoch fast vollständig entmagnetisiert. Die ursprünglichen Flussdichtewerte konnten durch Remagnetisierung verlustfrei wiederhergestellt werden. Schlussfolgerung: Vor einer MRT-Untersuchung mit den hier untersuchten Sequenzen und intraoral festsitzenden ferromagnetischen Gegenankern muss geprüft werden, ob die zu untersuchenden Strukturen weit genug von der entstehenden Signallöschungszone entfernt sind. Bei intraoral oder epicranial verankerten Magnetattachments besteht bei MRT- Exposition die Gefahr einer leichten bis kompletten Demagnetisierung mit dementsprechend insuffizient werdendem Prothesenhalt. Durch Inklination oder Reklination des Patientenkopfes ist dieses Problem nicht zu umgehen. SmCo-Magnete mit erhöhter Koerzitivkraft können dagegen bei 1,5 T gefahrlos in situ verbleiben. Bei 3 T sollten alle Dentalmagnete, falls instrumentell-technisch möglich, vor MRT entfernt werden. Bei den ggf. nach MRT demagnetisierten Produkten ist eine Remagnetisierung durch den Hersteller/Vertreiber möglich.Introduction: The primary coping of prosthetic or epithetic magnetic attachments is fixed on abutment-teeth and implants. In MR-examinations two interactions are expected: Impairment of imaging due to artifacts and alteration of flux density due to the main MR-field. Objectives of this in-vitro-study are: - Determine the maximum size of susceptibility-artifacts occurring at 1.5 and 3T and three common sequences. - To measure the demagnetization of the magnets in the MRI in different positions with respect to the main field. Methods: The maximum radius of the signal loss regions around three mini magnet types and two ferromagnetic keepers was measured on the SNR phantom in the three MR sequences SE-T1, SE-T2 and GE-T2*. In an initial demagnetization study, 30 SmCo and 60 NdFeB magnets and in a follow-up study 40 SmCo magnets with increased coercivity were exposed to the main field of a 1.5 and a 3T-MRI in different positions. Flux density was measured with a teslameter. Results: The signal loss regions showed no clinically relevant differences for the various specimens and the two MRI main-field-strengths. However, significant differences occurred depending on the MR sequence used: In spin-echo-sequences, signal loss regions were much smaller but very asymmetric, with a maximum radius of up to 7.4 cm. In gradient echo sequences, signal loss regions were more symmetric and extensive, with a maximum radius of up to 9.7 cm. The extent of demagnetization depends on the orientation of the mini magnets in the MRI field and its strength. At 1.5T, flux density of antiparallel NdFeB and SmCo magnets is significantly reduced, at 3T, polarity is reversed in both magnet types. SmCo magnets with increased coercivity resisted the 1.5T field, but were almost completely demagnetized at 3T. Remagnetisation fully restored the original flux density. Conclusion: Prior to an MRI using the studied sequences on patients with fixed ferromagnetic keepers, it must be checked whether enough distance is between the structures to be examined and the resulting signal loss region. During MRI exposure, intraoral or epicranial magnetic attachments risk being demagnetised, resulting in insufficient prosthesis retention. Inclining or reclining the patient’s head does not prevent the problem. However, SmCo magnets with increased coercivity can remain in situ at 1.5T without risk. At 3T, all dental magnets should be removed before MRI, if technically possible. Manufacturers/distributors can remagnetise products demagnetised during MRI

Universal Point Estimation, with Applications in Economics, Business and Decision Sciences

Estimation is used widely in numerous disciplines, including Mathematics, Statistics, Economics, Business, and Decision Sciences, among others. Estimation is a process for determining an approximation, which is a value that can be used for a number of purposes, even if input data are sufficient, incomplete, missing or unsecure. In practice, estimation relates to “using the value of a statistic inferred from a sample to estimate the value of a corresponding population parameterâ€. Estimation is usually separated into two categories, namely point estimation and interval estimation. The main purpose of this paper is to present a universal approach to the theory and practice of three methods in statistical inference to obtain point estimates, namely the moment, maximum likelihood, and Bayesian methods. The paper also discusses the advantages and disadvantages of the three universal approaches in practical applications in Economics, Business and Decision Sciences

An effective hyper-parameter can increase the prediction accuracy in a single-step genetic evaluation

The H-matrix best linear unbiased prediction (HBLUP) method has been widely used in livestock breeding programs. It can integrate all information, including pedigree, genotypes, and phenotypes on both genotyped and non-genotyped individuals into one single evaluation that can provide reliable predictions of breeding values. The existing HBLUP method requires hyper-parameters that should be adequately optimised as otherwise the genomic prediction accuracy may decrease. In this study, we assess the performance of HBLUP using various hyper-parameters such as blending, tuning, and scale factor in simulated and real data on Hanwoo cattle. In both simulated and cattle data, we show that blending is not necessary, indicating that the prediction accuracy decreases when using a blending hyper-parameter <1. The tuning process (adjusting genomic relationships accounting for base allele frequencies) improves prediction accuracy in the simulated data, confirming previous studies, although the improvement is not statistically significant in the Hanwoo cattle data. We also demonstrate that a scale factor, α, which determines the relationship between allele frequency and per-allele effect size, can improve the HBLUP accuracy in both simulated and real data. Our findings suggest that an optimal scale factor should be considered to increase prediction accuracy, in addition to blending and tuning processes, when using HBLUP

Chemical composition and antibacterial activities of essential oils from Homalomena pierreana (Araceae)

30-37Homalomena is a genus of the Araceae family which contains several remedies used extensively in traditional Vietnamese medicine. H. pierreana is a rare plant species of Homalomena genus and found only in Phu Quoc National Park, Phu Quoc Island, Kien Giang Province, Vietnam. Therefore, the number of studies about this species is limited and the bioactivity of this species is still unknown. In this study, the chemical composition of essential oils was investigated which was isolated from leaves and rhizomes of H. pierreana at the first time by GC-MS. Eight and twelve compounds were identified from the essential oils of rhizomes and leaves, respectively. The major component from both the rhizomes and the leaves was aromadendrene (44 and 48%, respectively). Furthermore, the antibacterial activity of essential oils collected from leaves and rhizomes of H. pierreana was investigated and it was observed that the essential oil of rhizomes could inhibit the growth of Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa, while the essential oil of leaves exhibited an inhibitory effect against Staphylococcus aureus and Escherichia coli.</em

Chemical profile and antibacterial activity of acetone extract of Homalomena cochinchinensis Engl. (Araceae)

Homalomena cochinchinensis Engl. is a rare species which is found in Southern China, Cambodia, Laos and Vietnam and its chemical constituents and bioactivity have not been determined yet. In this study, we identified 32 and 38 compounds in acetone extracts of H. cochinchinensis aerial part and rhizome, respectively via gas chromatography mass spectrometry (GC/MS). The main constituents of acetone extract of the aerial part were 3-((4Z,7Z)-Heptadeca-4,7-dien-1-yl)phenol (18.73%); cis-9,cis-12-Octadecadienoic acid (12.04%); linolenic acid (11.08%); n-Hexadecanoic acid (10.13%); (Z)-3-(Heptadec-10-en-1-yl)phenol (7.09%); ?-Sitosterol (5.58%) and linalool (5.56%). On the other hand, acetone extract of rhizome contained linalool (28.42%); 1,2,3-Propanetriol, 1-acetate (10.13%); 3-((4Z,7Z)-Heptadeca-4,7-dien-1-yl)phenol (5.28%); 3-Buten-2-one, 3-methyl-4-(1,3,3-trimethyl-7-oxabicyclo[4.1.0]heptan-1-yl)- (5.28%) and 4-(2,6,6-Trimethyl-cyclohex-1-enyl)-butyric acid (4.54%). Furthermore, this study has also proved the antibacterial activity of acetone extracts from the aerial part and the rhizome of this species for the first time using disk diffusion method. The results showed that the extract of the aerial part could inhibit the growth of 5 out of a total 6 bacterial strains, including Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa, Salmonella enteritidis and Staphylococcus aureus; while the susceptible strains to the rhizome extract were 5 strains, such as B. cereus, E. coli, P. aeruginosa, Salmonella typhimurium and S. aureus. The findings suggest the further application of this species in pharmacology and medicine

Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives

Polygenic risk scores are emerging as a potentially powerful tool to predict future phenotypes of target individuals, typically using unrelated individuals, thereby devaluing information from relatives. Here, for 50 traits from the UK Biobank data, we show that a design of 5,000 individuals with first-degree relatives of target individuals can achieve a prediction accuracy similar to that of around 220,000 unrelated individuals (mean prediction accuracy = 0.26 vs. 0.24, mean fold-change = 1.06 (95% CI: 0.99-1.13), P-value = 0.08), despite a 44-fold difference in sample size. For lifestyle traits, the prediction accuracy with 5,000 individuals including first-degree relatives of target individuals is significantly higher than that with 220,000 unrelated individuals (mean prediction accuracy = 0.22 vs. 0.16, mean fold-change = 1.40 (1.17-1.62), P-value = 0.025). Our findings suggest that polygenic prediction integrating family information may help to accelerate precision health and clinical intervention