A survey on online monitoring approaches of computer-based systems

This report surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use

Exploring disparities in acute myocardial infarction events between Aboriginal and non-Aboriginal Australians: roles of age, gender, geography and area-level disadvantage

We investigated disparities in rates of acute myocardial infarction (AMI) between Aboriginal and non-Aboriginal people in the 199 Statistical Local Areas (SLAs) in New South Wales, Australia. Using routinely collected and linked hospital and mortality data from 2002 to 2007, we developed multilevel Poisson regression models to estimate the relative rates of first AMI events in the study period accounting for area of residence. Rates of AMI in Aboriginal people were more than two times that in non-Aboriginal people, with the disparity greatest in more disadvantaged and remote areas. AMI rates in Aboriginal people varied significantly by SLA, as did the Aboriginal to non-Aboriginal rate ratio. We identified almost 30 priority areas for universal and targeted preventive interventions that had both high rates of AMI for Aboriginal people and large disparities in rates

Diagnostic, demographic, memory quality, and cognitive variables associated with acute stress disorder in children and adolescents

To date, no studies have investigated factors associated with acute stress disorder (ASD) in children and adolescents. Relationships between ASD and a number of demographic, trauma, cognitive, and trauma memory variables were therefore investigated in a sample (N=93) of children and adolescents involved in assaults and motor vehicle accidents. Several cognitive variables and the quality of trauma memories, but not demographic or trauma variables, were correlated with ASD and also mediated the relationship between peritraumatic threat and ASD. Finally, nosological analyses comparing ASD with indexes of posttraumatic stress disorder in the month posttrauma revealed little support for the dissociation mandate that uniquely characterizes ASD. The results are discussed with respect to assessment and treatment for the acute traumatic stress responses of children and young people

Prediction of far-field acoustic emissions from cavitation clouds during shock wave lithotripsy for development of a clinical device

This study presents the key simulation and decision stage of a multi-disciplinary project to develop a hospital device for monitoring the effectiveness of kidney stone fragmentation by shock wave lithotripsy (SWL). The device analyses, in real time, the pressure fields detected by sensors placed on the patient's torso, fields generated by the interaction of the incident shock wave, cavitation, kidney stone and soft tissue. Earlier free-Lagrange simulations of those interactions were restricted (by limited computational resources) to computational domains within a few centimetres of the stone. Later studies estimated the far-field pressures generated when those interactions involved only single bubbles. This study extends the free-Lagrange method to quantify the bubble–bubble interaction as a function of their separation. This, in turn, allowed identification of the validity of using a model of non-interacting bubbles to obtain estimations of the far-field pressures from 1000 bubbles distributed within the focus of the SWL field. Up to this point in the multi-disciplinary project, the design of the clinical device had been led by the simulations. This study records the decision point when the project's direction had to be led by far more costly clinical trials instead of the relatively inexpensive simulations. <br/

AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges

Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big data generated by IT Operations processes, particularly in cloud infrastructures, to provide actionable insights with the primary goal of maximizing availability. There are a wide variety of problems to address, and multiple use-cases, where AI capabilities can be leveraged to enhance operational efficiency. Here we provide a review of the AIOps vision, trends challenges and opportunities, specifically focusing on the underlying AI techniques. We discuss in depth the key types of data emitted by IT Operations activities, the scale and challenges in analyzing them, and where they can be helpful. We categorize the key AIOps tasks as - incident detection, failure prediction, root cause analysis and automated actions. We discuss the problem formulation for each task, and then present a taxonomy of techniques to solve these problems. We also identify relatively under explored topics, especially those that could significantly benefit from advances in AI literature. We also provide insights into the trends in this field, and what are the key investment opportunities

The Role of Suggestions and Personality Characteristics in Producing Illness Reports and Desires for Suing the Responsible Party

For this project, 92 students entered an abandoned theater room in an old basement of the university where sand was scattered throughout. The purpose of the study was to experimentally demonstrate that psychological suggestions could produce illness reports and to explore who is most likely to say that they would sue for personal damages. The students filled out the Trait-State Anger Scale and two subscales, Anger Temperament and Anger Reaction as well as the Costello-Corey Anxiety Scale, the Hardiness Inventory, the Pennebaker Inventory of Limbic Languidness, and, embedded in the Hardiness Inventory, measures of current illness as a result of exposure to the basement room. Half the participants were met by a confederate student who claimed to be cleaning up the remains of a production of Lawrence of Arabia, and the other half were met by a confederate construction worker who claimed that The stuff will tear up your skin and your lungs. Those in the experimental groups who perceived danger and scored low in the hardiness dimension of challenge were more likely to report symptoms of illness. Willingness to file a law suit was predicted by a model including perceived danger and the personality characteristic of anger reactivity

Present and Future of Network Security Monitoring

This work was funded by the Ministry of Science and Innovation through CDTI through the Ayudas Cervera para Centros Tecnologicos grant of the Spanish Centre for the Development of Industrial Technology (CDTI) through the Project EGIDA under Grant CER-20191012, and in part by the Spanish Ministry of Economy and Competitiveness and European Regional Development Fund (ERDF) funds under Project TIN2017-83494-R.Network Security Monitoring (NSM) is a popular term to refer to the detection of security incidents by monitoring the network events. An NSM system is central for the security of current networks, given the escalation in sophistication of cyberwarfare. In this paper, we review the state-of-the-art in NSM, and derive a new taxonomy of the functionalities and modules in an NSM system. This taxonomy is useful to assess current NSM deployments and tools for both researchers and practitioners. We organize a list of popular tools according to this new taxonomy, and identify challenges in the application of NSM in modern network deployments, like Software Defined Network (SDN) and Internet of Things (IoT).Ministry of Science and Innovation through CDTI through the Ayudas Cervera para Centros Tecnologicos grant of the Spanish Centre for the Development of Industrial Technology (CDTI) through the Project EGIDA CER-20191012Spanish Ministry of Economy and CompetitivenessEuropean Regional Development Fund (ERDF) funds TIN2017-83494-

Spectroscopic detection of pathological severity in Alzheimer's disease

Alzheimer’s disease (AD) has emerged as one of the most widespread and devastating forms of dementia. Over the past few decades, AD has consistently increased in prevalence worldwide due to the rising proportion of elderly individuals and lack of effective screening and treatment modalities. To date, few economically viable and widely applicable tools exist to make definitive, early diagnoses of the disease. Therefore, there is a clear need for interventions that facilitate accurate diagnoses, monitoring, and therapeutic treatment of AD. In the course of AD, cognitive impairment is preceded by physiological changes to the central nervous system (CNS). This includes neuronal atrophy, synaptic dysfunction, and the abnormal post-translational modification of the proteins tau and beta-amyloid (A), which contributes to the deposition of intracellular neurofibrillary tangles (NFTs) and extracellular neuritic plaques (NPs). The pathological cellular changes in AD occur long before the clinical course of the disease, and biomarkers for these changes can be detected prior to measurable cognitive decline. Because the biochemical changes associated with AD are irreversible, effective tools for diagnosis must detect the presence and severity of molecular pathology during the preliminary stages of the disease’s insidious onset. Biomarkers of AD can be detected by neuroimaging technologies, including magnetic resonance imaging (MRI), positron emission tomography (PET), and blood or cerebrospinal fluid (CSF) analyses. However, these methods are not currently suited to diagnose and monitor the unique pathogenesis of AD prior to cognitive decline. An ideal instrument for widespread AD screening, diagnosis, and monitoring must be noninvasive, inexpensive, portable, and accommodating to the cognitive sensitivities of patients on a spectrum from mild cognitive impairment (MCI) to full-blown dementia. Recently, several spectroscopic methods of assessing AD pathology have met these criteria and may be better suited for widespread clinical application. The objective of this thesis is to evaluate the use of near-infrared optical spectroscopy (NIRS) to detect pathological severity in human AD. Near-infrared (NIR) light is poorly absorbed by biological tissue, and can safely penetrate bone, skin, vasculature, and neuronal tissue. NIRS has traditionally been used in biomedical contexts to evaluate cerebral oxygenation changes, however the dense protein aggregates NFTs and NPs in AD tissue have recently been shown to characteristically affect several optical parameters of a NIR signal, including fluorescence and particle path (scattering). To date, applications of NIRS have been used to differentiate AD brains from non-AD controls in vitro, and further identify MCI patients in vivo, suggesting the NIR signal can identify molecular changes in AD. Severe AD cases are characterized by increased involvement of NFTs and NPs in the cerebral cortex, which would be expected to further affect the extent of NIR scatter. The current study aims to quantify AD-related pathology for investigation into whether the extent of optical scattering is correlated with the severity of amyloid plaque load and NFT density in the temporal cortex. Quantification of these lesions was accomplished using immunohistochemistry (IHC) and stereological analyses. Preliminary results show that the severity of AD pathology detected via IHC can be correlated with measured parameters of an in vitro near-infrared signal. Future studies aim to further characterize the relationship between scattering intensity and pathological severity, as well as evaluate the in vivo potential of this technology in predicting the clinical outcome and cognitive status of individuals in different stages of AD

Contrast enhanced spectroscopic optical coherence tomography

A method of forming an image of a sample includes performing SOCT on a sample. The sample may include a contrast agent, which may include an absorbing agent and/or a scattering agent. A method of forming an image of tissue may include selecting a contrast agent, delivering the contrast agent to the tissue, acquiring SOCT data from the tissue, and converting the SOCT data into an image. The contributions to the SOCT data of an absorbing agent and a scattering agent in a sample may be quantified separately