Relativistic k-fields with Massless Soliton Solutions in 3+1 Dimensions

In this work, the relativistic non-standard Lagrangian densities (k-fields) with massless solutions are generally introduced. Such solutions are not necessarily energetically stable. However, in 3+1 dimensions, we introduce a new k-field model that results in a single non-topological massless solitary wave solution. This special solution is energetically stable; that is, any arbitrary deformation above its background leads to an increase in the total energy. In other words, its energy is zero which is the least energy in all solutions. Hence, it can be called a massless soliton solution

Computer-Aided Diagnosis Systems in the Classification of Neuroblastoma Histological Images

University of Technology Sydney. Faculty of Engineering and Information Technology.Neuroblastoma is the most common extracranial solid malignancy in early childhood. Optimal management of neuroblastoma depends on many factors, including histopathological classification. Although histopathological classification by a human histopathologist is considered the gold standard, computers can help to extract many more features, some of which may not be recognisable by the human eye. Neuroblastoma histological images have a complex texture with complicated features which are different from appearance-based features. Computer-aided diagnosis (CAD) systems facilitate the analysis and classification of neuroblastoma histological images which are non-trivial tasks due to the differences in staining, intensity, and instrumentation. This motivates the thesis to work on the classification of neuroblastoma histological images. In the past, a small number of methods were proposed by previous studies for the classification of neuroblastoma histological images. These methods are based on the geometry and appearance of the different cells. However, there is a high intra-class variation of intensity and size of the neuroblast cells within the same classification group. Therefore, these methods are not applicable to neuroblastoma histological images. This research proposes a solution based on traditional machine learning approaches and deep learning approaches to extract non-appearance-based features in small regions. This thesis will investigate two research areas of feature extraction: low-level feature extraction and high-level feature extraction. Low-level features are minor details of the image such as lines, curves and edges. However, high-level features are on top of the low-level features to detect object and larger shape in the image. Feature extraction is aggregated with the classifier in this research to classify neuroblastoma histological images into five categories. This thesis makes four contributions. Contribution 1 is the construction of a dataset comprising neuroblastoma histological images which are labeled by an expert histopathologist. Contribution 2 is the proposal of a local feature extraction method which can extract local features which are robust to high intra-class variations of intensity. Contribution 3 is the extraction of discriminative features which are robust to high intra-class variation of scale of the neuroblast cells within the same class. Contribution 4 is the proposal of deep networks to extract high-level features which are difficult for the human eye to recognise. The performance of all the proposed methods in this research is evaluated on a dataset collected from The Children's Hospital at Westmead, Sydney, Australia. As there was no publicly available dataset in this field, the proposed algorithms were evaluated on the second dataset of neuroblastoma provided by the University of Bristol and the public breast cancer dataset. All the results are compared with state-of-the-art methods. The results indicate the effectiveness of the proposed algorithms. This is the first time that neuroblastoma histological images have been classified into five subtypes using low-level and high-level features. However, there are limitations in this research. The specificity is not 100% compared with the gold standard. Moreover, the proposed algorithms are confused in the distinction between poorly-differentiated and differentiating neuroblastoma, a distinction that human pathologists also find difficult in limited fields of view

Explain the relationship between customer orientations; knowledge management and customer relationship with CRM technology with organizational variables mediate Pasargad Bank

Abstract: The present study is considered as an applied science from the nature of studied objectives. Managers and experts of Pasargad Bank branches in cities have formed the stoical population. In this study, simple random sampling method was used and a sample size of 200 was calculated using Cochran's sample size formula. The required data was gathered in the field study, using a standard questionnaire consisted of 39 questions that all questions have to be a five-item Likert form. These data are analyzed by LISREL software. Chronbach alpha coefficient was used to determine the validity of questionnaire, that the percent of reliability was calculated, equal to 0.859 for a questionnaire with 39 questions. In this pape r, the mea suring model has been provided by applying Perlis program from Liserel software after plotting the research analytical model based on the data by Pat

Super-Resolution through StyleGAN Regularized Latent Search: A Realism-Fidelity Trade-off

This paper addresses the problem of super-resolution: constructing a highly resolved (HR) image from a low resolved (LR) one. Recent unsupervised approaches search the latent space of a StyleGAN pre-trained on HR images, for the image that best downscales to the input LR image. However, they tend to produce out-of-domain images and fail to accurately reconstruct HR images that are far from the original domain. Our contribution is twofold. Firstly, we introduce a new regularizer to constrain the search in the latent space, ensuring that the inverted code lies in the original image manifold. Secondly, we further enhanced the reconstruction through expanding the image prior around the optimal latent code. Our results show that the proposed approach recovers realistic high-quality images for large magnification factors. Furthermore, for low magnification factors, it can still reconstruct details that the generator could not have produced otherwise. Altogether, our approach achieves a good trade-off between fidelity and realism for the super-resolution task

Magnetization Behaviour of Nanocrystalline Permalloy Thin Films Prepared Using Oblique-angle Magnetron Sputtering Technique

In the current work, nanocrystalline Fe0.5Ni0.5 magnetic thin films were deposited on a Si(100) substrate using the oblique-angle sputtering technique with the oblique deposition angle ranging from 11.5 to 45°. Structure, static magnetic properties, and dynamic magnetic characteristics were evaluated as a function of the deposition angle. The results indicate that the nanocrystalline FCC phase of FeNi with (111) preferred orientation and the average crystallite size of 6.3-9.3 nm was deposited successfully. The measured value of the uniaxial anisotropy field shows an increment from 7.65 to 16.71 Oe as the oblique angle rises from 11.5 to 45°, which in turn leads to an increase in the ferromagnetic resonance frequency from 0.63 to 0.88 GHz

Effects of supplemental microbial phytase enzyme on performance and phytate phosphorus digestibility of a corn-wheat-soybean meal diet in broiler chicks

This experiment was conducted to investigate the effects of supplemental phytase in a corn-wheatsoybean meal basal diet on phosphorus (P) digestibility and performance of broiler chicks. 378 one-day old broiler chicks (Ross 308) were allocated to 3×3 factorial arrangements with three levels of phytase enzyme (0, 500 and 1000 FTU/kg) and three levels of non-phytate P (100, 80 and 60% of NRC requirements). Broiler chicks received experimental diets from 7 to 49 days of age. Phytase significantly (P < 0.05) improved body weight gain and feed intake. Tibial ash and P contents increased significantly by phytase supplementation. Ileal P digestibility increased and P excretion reduced by added phytase. The greatest response due to supplemental phytase regarding P digestibility and utilization was obtained at the lowest dietary non-phytate P (NPP) level (60% of NRC requirements). Difference between various levels of added phytase (500 and 1000 FTU/kg) regarding P excretion and utilization was not significant. The interactions between supplemental phytase and dietary NPP for P utilization, tibial ash and P contents were significant (P < 0.05). The results indicate that, supplemental microbial phytase (500 FTU/kg of diet) added to diet containing NPP lower than NRC requirements (60%) can improve growth performance, tibial ash and phytate P utilization in broiler chickens.Key words: Broiler, phytase, phosphorus digestibility, growth performance, tibia

Genotyping of vacA alleles of Helicobacter pylori strains recovered from some Iranian food items

Purpose: To study the vacA genotype status of H. pylori isolated from some Iranian food items.Methods: Three hundred assorted samples of fish, ham, chicken, vegetable and meat sandwiches, and minced meat were purchased and tested using culture method. Those that were H. pylori-positive were analyzed for presence of vacA genotypes using polymerase chain reaction (PCR).Results: Sixty out of 300 (20 %) food samples were positive for H. pylori. Vegetable sandwich (45 %), minced meat (32 %) and meat sandwich (20 %) were the most commonly contaminated. The most commonly detected genotypes in the meat-based foods, viz, vegetable sandwich and ready to eat fish, were vacA s1a, vacA m1a and vacA m2, respectively. The most commonly detected combined genotypes were s1am2 (45 %), s1am1a (40 %) and m1am2 (35 %).Conclusion: The presence of similar genotypes in H. pylori strains of foods and those of human clinical samples suggest that contaminated foods may be the source of bacteria for humans.Keywords: Helicobacter pylori, VacA genotypes, Genotyping, Food item