Design and Implement Scalable Robust Modern Web Application

Modern web application has grown in popularity because of its ease of access on multiple platforms and devices. In regards to this growth, the expectations for modern web application have arisen over the years. As a result, modern web application nowadays can have large scale and high complexity just as any native desktop or mobile application. To build a modern web application, there are differences in choice of tools, frameworks and theoretical approaches. Each of the choices has its own advantages and disadvantages, thus, in order to create a robust and scalable modern web application, developers should be able to grasp the technologies provided by the choice, and the relation between the project requirements and the features of which technologies have to offer. Recognizing the vital aspects of using tools and frameworks for modern web application development, this study aims to conclude and provide an approach to utilize a certain tool and framework, which are AngularJS and TypeScript in particular, in order to produce a highly scalable and maintainable development approach. In order to achieve this, the study analyses the current states of modern web, assesses the tools and frameworks in question, and through a case project, demonstrates their features with a detailed architectural implementation. Throughout the study, AngularJS has proved its expressiveness, reusability and testability in its components. TypeScript has also proved its essential role in the development process of the large web application for its type system. The combination induced a high level of abstraction to the development process and slowed the pace at first, but in the long run, from the perspective of scaling and maintaining, the combination itself has made the development process much more effortless and at the same time, more reliable

Angular rate sensing by circulatory vortex flow: design, simulation and experiment

A fully packaged convective vortex gyrometer actuated by a PZT diaphragm is reported. The flow circulates at higher velocity after each actuating circle to form a vortex in the desired chamber. The vortex is characterized by hotwire anemometry. The device is initially designed based on a numerical analysis whose results are used to set up the experiment. The angular rate sensing of the device is successfully tested using a turntable. The technique is a potential solution to various applications related to inertial sensing and fluidic amplifier

When Intervention Becomes Imperative: A Case Report of Spontaneous Vulvar Edema During Pregnancy

Spontaneous idiopathic vulvar edema during the second trimester is a rare condition. The approach to managing this condition involves relieving symptoms, identifying underlying causes, and implementing appropriate treatment. Managing such cases during pregnancy is challenging because of concerns for potential adverse fetal outcomes. Conservative management expects the condition to be relieved spontaneously postpartum, whereas invasive treatment offers a more rapid resolution. Treatment choices are controversial because each method has its pros and cons and influences the delivery process to a certain extent. Surgical drainage becomes a viable option when patients are not responsive to medications. We report a case of spontaneous massive vulvar edema in a 22-year-old primigravida in her 23rd week of pregnancy. After ruling out other notable causes of vulvar edema, we decided to intervene using an invasive procedure because she complained of progressive symptoms and discomfort. Subsequently, the edema subsided postprocedure, and the patient experienced successful labor with no complications. This report aims to alert clinicians that drainage attempts should be considered in pregnant patients with worsening symptoms

Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling

IntroductionNeoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow.MethodsIn this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP).ResultsWe detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data.DiscussionThis integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Application of Multi-Fusion Network for Human-Object Interaction Detection

Diese Abschlussarbeit stellt Multi-Fusion Network Architektur für Erkennung von Mensch-Objekt-Interaktion mit mehreren Kameras vor und implementiert eine Anwendung für einen spezifischen Anwendungsfall eines Getränkekühlschranks. Die Abschlussarbeit präsentiert einfache jedoch effektive Vorgehensweisen zur Reduzierung der erforderten Trainingsdatenmenge und des Risikos von Overfitting, insbesondere im Umgang mit kleinem Datensatz, der üblich von individueller Person oder kleiner Organisation aufgenommen wurde. Das Modell erreichte eine Testgenauigkeit von 91.235% und ein vergleichbares Ergebnis im praktischen Test an der Veranstaltung Solutions Hamburg 2019. Multi-Fusion Network ist leicht zu skalieren durch gemeinsame lernbare Parameter und auch so leichtgewichtig, dass es auf kleine Geräte mit durchschnittlicher Rechenleistung laufen kann. Multi-Fusion Network könnte für Indoor-Aktivitäten Erkennung für Smarthome Anwendungen oder Gaming-Erlebnis angewendet werden.This thesis proposes Multi-Fusion Network architecture for human-object interaction detection with multiple cameras and implements an application for a specific use case of a drink refrigerator. The thesis also introduces simple but effective approaches for minimizing the required amount of training data and the risk of overfitting, especially when dealing with a small dataset that is commonly recorded by a person or small organization. The model achieved 91.235% test accuracy and comparable result in the real-world test at the event Solutions Hamburg 2019. Multi-Fusion Network is easy to scale thanks to shared learnable parameters. It is also lightweight to run on small devices with average computation capability and, therefore, can be used for smart home applications, gaming experiences, or augmented reality

Determination of Cobalt in Seawater Using Neutron Activation Analysis after Preconcentration by Adsorption onto γ-MnO2 Nanomaterial

The γ-MnO2 nanomaterial has been used to adsorb cobalt in the seawater at Phan Thiet City, Binh Thuan Province, Vietnam. Its concentration is determined by using the neutron activation analysis (NAA) method at the Dalat nuclear research reactor. Factors affecting the uptake of cobalt on the γ-MnO2 material such as the pH, adsorption time, and initial cobalt(II) concentration are investigated. The irradiated experiment data are calculated using the K0-Dalat program. The results obtained show that the trace dissolved cobalt in Phan Thiet seawater is found equal to 0.25 ± 0.04 μg/L (n=5, P=95%) with the adsorption efficiency being higher than 95% (n=4, P=95%)