Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review.

Vertigo is a sensation of movement that results from disorders of the inner ear balance organs and their central connections, with aetiologies that are often benign and sometimes serious. An individual who develops vertigo can be effectively treated only after a correct diagnosis of the underlying vestibular disorder is reached. Recent advances in artificial intelligence promise novel strategies for the diagnosis and treatment of patients with this common symptom. Human analysts may experience difficulties manually extracting patterns from large clinical datasets. Machine learning techniques can be used to visualize, understand, and classify clinical data to create a computerized, faster, and more accurate evaluation of vertiginous disorders. Practitioners can also use them as a teaching tool to gain knowledge and valuable insights from medical data. This paper provides a review of the literatures from 1999 to 2021 using various feature extraction and machine learning techniques to diagnose vertigo disorders. This paper aims to provide a better understanding of the work done thus far and to provide future directions for research into the use of machine learning in vertigo diagnosis

Pre-clinical development of chimeric virus-like particles based HPV: HIV vaccines by using mammalian cell expression system: limitations and challenges

[eng] HPV and HIV-1 are important public health issues in some developing and industrialized countries, but an effective chimeric HPV:HIV preventive vaccine is still unachievable. We aimed to establish an alternative mammalian (293F) cell expression system combining with chromatographic purification methods to reach an appreciable expression level, purity and recovery rate of chimeric HPV:HIV VLPs. In this study, the chimeric HPV:HIV (L1:P18I10 and L1:T20) immunogens were designed and produced by using 293F expression system. The HPV:HIV VLPs were subsequently purified by a 3-step chromatographic method, including cation (CEC), size exclusion (SEC) and heparin affinity (H-AC) chromatography. Then, the in vitro stability, in vitro self assembly and morphology of purified HPV:HIV VLPs were confirmed by non-reducing SDS-PAGE, molecular mass assay, transmission electron microscopy (TEM) respectively. The sequential and conformational P18I10 and T20 peptides presented on chimeric HPV:HIV VLPs were further characterized by HIV-1 anti-V3 and anti-2F5 monoclonal antibodies in vitro by using Western blot and indirect ELISA. Finally, the immunogenicity of HPV:HIV VLPs were assessed in BALB/c mice model. Because the development and manufacturing of an immunogenic HPV:HIV vaccine is still unachievable, this study provided a baseline strategy that may be worthy to support the global efforts to develop novel chimeric VLP-based vaccines for controlling HPV and HIV-1 infection

Cyber-physical business systems modelling : advancing Industry 4.0

Abstract: The dynamic digital age drives contemporary multinationals to focus on delivering world-class business solutions with the use of advanced technology. Contemporary multinationals relate to a present-day business primarily engaged to generate profits. These complex multinationals offer value through the manufacture, sale, and management of products and services. Disruptive strategies in operations driven by emerging technological innovations demand continuous business improvements. These insightful opportunities are inclusive of operations, enterprise systems, engineering management, and research. Business sustainability is a strategic priority to deliver exceptional digital solutions. The Fourth Industrial Revolutions (4IR) offer significant technological advancements for total business sustainability. The underlying 4IR technologies include Cyber-Physical Systems (CPS). The collective challenges of a large global business are not easy to predict. CPS protocols deliver sustainable prospects required to integrate and model physical systems in real-time driven by the 4IR implementations. The goal of this thesis is to develop a model (CPS) suitable for self-predicting and to determine ideal operational practice driven by technologies of the 4IR. The model (CPS) seeks a novel tool effective for comprehensive business evaluation and optimisation. The competence of the anticipated tool includes suitability to collaborate current operations and predict the impact of change on a complex business. ..D.Phil. (Engineering Management

Comparative analysis reveals the long-term co-evolutionary history of parvoviruses and vertebrates [preprint]

Parvoviruses (family Parvoviridae) are small, non-enveloped DNA viruses that infect a broad range of animal species. Comparative studies, supported by experimental evidence, show that many vertebrate species contain sequences derived from ancient parvoviruses embedded in their genomes. These ‘endogenous parvoviral elements’ (EPVs), which arose via recombination-based mechanisms in infected germline cells of ancestral organisms, constitute a form of ‘molecular fossil record’ that can be used to investigate the origin and evolution of the parvovirus family. Here, we use comparative approaches to investigate 198 EPV loci, represented by 470 EPV sequences identified in a comprehensive in silico screen of 752 published vertebrate genomes. We investigated EPV loci by constructing an open resource that contains all of the data items required for comparative sequence analysis of parvoviruses and uses a relational database to represent the complex semantic relationships between them. We used this standardised framework to implement reproducible comparative phylogenetic analysis of combined EPV and virus data. Our analysis reveals that viruses closely related to contemporary parvoviruses have circulated among vertebrates since the Late Cretaceous epoch (100-66 million years ago). We present evidence that the subfamily Parvovirinae, which includes ten vertebrate-specific genera, has evolved in broad congruence with the emergence and diversification of major vertebrate groups. Furthermore, we infer defining aspects of evolution within individual parvovirus genera - mammalian vicariance for protoparvoviruses (genus Protoparvovirus), and inter-class transmission for dependoparvoviruses (genus Dependoparvovirus) - thereby establishing an ecological and evolutionary perspective through which to approach analysis of these virus groups. We also identify evidence of EPV expression at RNA level and show that EPV coding sequences have frequently been maintained during evolution, adding to a growing body of evidence that EPV loci have been co-opted or exapted by vertebrate species, and especially by mammals. Our findings offer fundamental insights into parvovirus evolution. In addition, we establish novel genomic resources that can advance the development of parvovirus-related research - including both therapeutics and disease prevention efforts - by enabling more efficient dissemination and utilisation of relevant, evolution-related domain knowledge

Long term integrity for space station power systems

A study was made of the High Temperature Design Codes ASME N47, British R5, and the French RCC-MR Rules. It is concluded that all these codes provide a good basis of design for space application. The new British R5 is the most complete since it deals with the problem of defects. The ASME N47 was subjected longer to practical application and scrutiny. A draft code is introduced, and a proposed draft for high temperature design in which attempts were made to identify gaps and improvements is suggested. The design is limited by creep characteristics. In these circumstances, life is strongly affected by the selected value of the factor of safety. The factor of safety of primary loads adopted in the codes is 1.5. Maybe a lower value of 1.25 is permissible for use in space. Long term creep rupture data for HAYNES 188 is deficient and it is suggested that extrapolation methods be investigated

Quantitative and systems pathology for therapeutic response prediction

The measurement of tissue biomarkers for therapeutic response prediction in cancer patients has become standard pathological practice, but only for a very limited number of targets. This is in spite of massive intellectual and financial investment in molecular pathology for translational cancer research. A re-evaluation of current approaches, and the testing of new ones, is required in order to meet the challenges of predicting responses to existing and novel therapeutics, and individualising therapy.Herein I critique the current state of tissue biomarker analysis and quantification in cancer pathology and the reasons why so few novel biomarkers have entered the clinic. In particular, we examine the central role of signalling pathway biology in sensitivity and resistance to targeted therapy. I discuss how accurate quantification, and the ability to simulate biological responses over time and space, may lead to more accurate prediction of therapeutic response. I propose that different mathematical techniques used in the nascent field of systems biology (ordinary differential equation-based, S-systems, and Bayesian approaches) may provide promising new avenues to improve prediction in clinical and pathological practice. I also discuss the challenges and opportunities for quantification in pathological research and practice.I have examined the role of cellular signalling pathways in therapeutic sensitivity and resistance in three different ways. Firstly, I have taken a hypothesis-driven and reductionist approach and shown that decreased Sprouty 2, a feedback inhibitor of MAPK and PI3K signalling, is associated with trastuzumab-resistance in vitro and in a cohort of breast cancer patients treated with trastuzumab. Secondly, I have characterised the activation state of ten growth and survival pathways across different histological subtypes of ovarian cancer using quantitative fluorescence microscopy. I have shown that unsupervised clustering of phosphoprotein expression profiles results in new subgroups with distinct biological properties (in terms of proliferation and apoptosis), and which predict therapeutic response to chemotherapy. Thirdly, I have developed a new mathematical model of PI3K signalling, parameterised using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays, and shown that quantitative PTEN protein expression is the key determinant of resistance to anti-HER2 therapy in silico. Furthermore, the quantitative measurement of PTEN is more predictive of response than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalised therapy in cancer, and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision-making in patients treated with anti-HER2 therapies

Asset Pricing, Investment, and Trading Strategies

Asset pricing, investment, and trading strategies are very important in finance. They are useful in various situations, for example, supporting the decision-making process of choosing investments; determining the asset-specific required rate of return on the investment; pricing derivatives for trading or hedging; getting portfolios from fixed incomes or bonds, stocks, and other assets; evaluating diverse portfolios; determining macroeconomic variables affecting market prices; calculating option prices; and incorporating features such as mean reversion and volatility, etc. They can also be applied in financial forecast for assets, portfolios, business projects.Understanding, modeling, and using various asset pricing models, investment models, and models for different trading strategies is paramount in many different areas of finance and investment, including banking, stocks, bonds, currencies, and related financial derivatives. Different asset pricing models, investment models, and models for different trading strategies also allow us to compare the performances of different variables through the analysis of empirical real-world data.This Special Issue on "Asset Pricing, Investment, and Trading Strategies” will be devoted to advancements in the theoretical development of various asset pricing models, investment models, and models for different trading strategies as well as to their applications.The Special Issue will encompass innovative theoretical developments, challenging and exciting practical applications, and interesting case studies in the development and analysis of various asset pricing models, investment models, and models for different trading strategies in finance and cognate disciplines

An extended model order reduction technique for linear delay systems

\u3cp\u3eThis paper presents a model reduction technique for linear delay differential equations that, first, preserves the infinite-dimensional nature of the system, and, second, enables the preservation of additional properties such as physical interconnection structures or uncertainties. This structured/robust reduction of delay systems is achieved by allowing additional degrees of freedom in the characterization of (bounds on) controllability and observability energy functionals, leading to a so-called extended balancing procedure. In addition, the proposed technique preserves stability properties and provides an a priori error bound. The relevance of the method in controller reduction is discussed and illustrative numerical examples are presented.\u3c/p\u3

Blood pressure variability following ischaemic stroke

Variability in blood pressure (BP) may influence ischaemic stroke outcomes in addition to mean BP. However, how best to measure BP variability (BPV) and whether different measurements are equivalent is unknown, as is whether treatment can reduce BPV. This thesis aimed to investigate relationships between BP and BPV measurements from different devices in patients with ischaemic cerebrovascular disease, relationships between BPV and stroke severity, and whether antihypertensive medications can reduce BPV. Three trials that recruited patients following an ischaemic cerebrovascular event provided data. Correlations and limits of agreement between mean BP and BPV from different measurement devices were assessed. Relationships between baseline BPV and stroke severity were investigated, along with differences in baseline BPV in those treated with calcium channel blockers (CCB) or renin-angiotensin system inhibitors. A feasibility trial was developed to compare the effects of these medication classes on reduction of BPV post stroke. BP from daytime ambulatory monitoring was significantly lower than home BP monitoring and BPV values from different devices were unrelated. There was an inverse relationship between baseline BPV and stroke severity, with BPV increased in lacunar infarction. There was no difference in baseline BPV with the medication regimens specified above. Recruitment to the feasibility trial was insufficient due to patient ineligibility, but a reduction in BPV over three month follow-up was demonstrated. In patients with ischaemic cerebrovascular disease, BP and BPV recorded using different devices are not equivalent. Work to standardise BPV measurement and establish if any method is clinically superior is required. Treatment to reduce BPV may particularly benefit certain stroke patients, yet establishing that it is possible to target BPV, and doing so improves outcomes, is prerequisite. The feasibility trial in this thesis requires modification to be scaled up, but a definitive trial could be successful if recruitment were improved