Exploiting Context-Aware Event Data for Fault Analysis

Fault analysis in communication networks and distributed systems is a difficult process that heavily depends on system administrator’s experience and supporting tools. This process usually requires analytic techniques and several types of event data including log events, debug messages, trace obtained from these systems to investigate the root cause of faults. This paper introduces an approach of exploiting context-aware data and classification technique for improving this process. This approach uses both event data and context-aware data including CPU load, memory, processes, temperature, status to train a decision tree, and then applies the tree to assess suspected events. We have implemented and experimented the approach on the OpenStack cloud computing system with the Hadoop computing service and MELA event collection system. The experimental results reveal that the accuracy score of the approach reaches 85% on average. The paper also includes detailed analysis for the results

An Extended Occlusion Detection Approach for Video Processing

Occlusions become conspicuous as failure regions in video processing when unified over time because the contraventions of the restriction of brightness have accumulated and evolved in occluded regions. The accuracy at the boundaries of the moving objects is one of the challenging areas that required further exploration and research. This paper presents the work in process approach that can detect occlusion regions by using pixel-wise coherence, segment-wise confidence and interpolation technique. Our method can get the same result as usual methods by solving only one Partial Differential Equations (PDE) problem; it is superior to existing methods because it is faster and provides better coverage rates for occlusion regions than variation techniques when tested against a varied number of benchmark datasets. With these improved results, we can apply and extend our approach to a wider range of applications in computer vision, such as background subtraction, tracking, 3D reconstruction, video surveillance, video compression

Evaluation of different infant vaccination schedules incorporating pneumococcal vaccination (The Vietnam Pneumococcal Project): protocol of a randomised controlled trial.

INTRODUCTION: WHO recommends the use of pneumococcal conjugate vaccine (PCV) as a priority. However, there are many countries yet to introduce PCV, especially in Asia. This trial aims to evaluate different PCV schedules and to provide a head-to-head comparison of PCV10 and PCV13 in order to generate evidence to assist with decisions regarding PCV introduction. Schedules will be compared in relation to their immunogenicity and impact on nasopharyngeal carriage of Streptococcus pneumoniae and Haemophilus influenzae. METHODS AND ANALYSIS: This randomised, single-blind controlled trial involves 1200 infants recruited at 2 months of age to one of six infant PCV schedules: PCV10 in a 3+1, 3+0, 2+1 or two-dose schedule; PCV13 in a 2+1 schedule; and controls that receive two doses of PCV10 and 18 and 24 months. An additional control group of 200 children is recruited at 18 months that receive one dose of PCV10 at 24 months. All participants are followed up until 24 months of age. The primary outcome is the post-primary series immunogenicity, expressed as the proportions of participants with serotype-specific antibody levels ≥0.35 µg/mL for each serotype in PCV10. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Human Research Ethics Committee of the Northern Territory Department of Health and Menzies School of Health Research (EC00153) and the Vietnam Ministry of Health Ethics Committee. The results, interpretation and conclusions will be presented to parents and guardians, at national and international conferences, and published in peer-reviewed open access journals. TRIAL REGISTRATION NUMBER: NCT01953510; Pre-results

Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Chemical Substances and Its Side Effects on Nurse's Health : A Literature Review

The thesis purpose was to observe the dangers of hazardous chemical substances and how to manage problems in the health care setting. The aim of the thesis was to address the side effects of chemical substances on nurses’ health, and how to prevent those side effects in hospitals. The study was done by using the literature review. Strict inclusion and exclusion criteria were utilized to ensure the quality of data. A content analysis was performed, and data has been collected and analyzed from relevant sources based on their particular issues, area of research, or theory. By using systematic literature review method, the collected data was analyzed. The data was collected by using Centria’s databases, such as CINAHL (EBSCO), Science Direct, PubMed and SAGE journals. 23 arti-cles were used in the literature review by applying inclusive and exclusive criteria. The authors chose articles which were published no more than ten years ago to update latest information. The results of the study are divided into two parts which are the impacts of chemical substances and the management of how to avoid chemical hazards in the working environment. Chemical exposure affects every aspect of nurse’s health. For example, respirational failure, biological change, reproductive health, allergic reaction, and neurological damage are the main side effects of chemical hazards. The core findings of the research include the prevention of chemical exposure in the hospital. For example, personal protective equipment (PPE) should be applied in a working environment. The conclusion of this study highlights the importance of management and the need to understand pro-foundly negative effects of chemical substances

Study of Chemical Compounds and Antioxidant Activity of Pectin Isolated From Tithonia Diversifolia

Pectin is a heterogeneous complex polysaccharide found in the primary cell wall of most cells and its effects on health has received growing interest. Studies show that water extract from tithonia diversifolia has been polysaccharide-rich extract.Particularly, pectin has many interesting effects. In this work, low-methoxyl pectin is isolated from Tithonia diversifolia. The isolated low-DE pectin is characterized by FTIR, 1H and 13C NMR, GPC. The structure of pectin includes units (1 → 2)-rhamnose and (1 → 4)-galacturonic acid which form the main chain and units of units (1 → 5)–arabinose branched chain. Its antioxidant activity is also evaluated through hydroxyl radical scavenging activity

Explaining consumers’ channel-switching behavior in the post-COVID-19 pandemic era

AbstractSignificant changes have been brought about in consumer behaviour as a result of the COVID-19 pandemic. Digital consumption has attracted a large number of new consumers during the pandemic. However, there are few academic studies on the determinants of these crucial changes in consumer behaviour. Addressing this gap, this study investigates consumers’ channel-switching behaviour during the COVID-19 pandemic. Using a sample of about 2,640 respondents collected after the outbreak, this study aims to define the key drivers of the changes in consumers’ shopping channel decisions. The study results show that several factors significantly affected consumers’ decisions to change their shopping habits after the pandemic broke out, including marital status, price, quality, convenience, and overall satisfaction with current and new shopping channels. More importantly, this study is one of the few to investigate the differences in determining factors regarding consumers’ choices of online and traditional channels in the post—COVID-19 pandemic era. The level of convenience, the time spent making purchases, technology competency, the abundance of product information, the ability to check product quality, and income significantly impact purchasing channel decisions between online and traditional channels

High variation removal for background subtraction in traffic surveillance systems

Background subtraction has been a fundamental task in video analytics and smart surveillance applications. In the field of background subtraction, Gaussian mixture model is a canonical model for many other methods. However, the unconscious learning of this model often leads to erroneous motion detection under high variation scenes. This article proposes a new method that incorporates entropy estimation and a removal framework into the Gaussian mixture model to improve the performance of background subtraction. Firstly, entropy information is computed for each pixel of a frame to classify frames into silent or high variation categories. Secondly, the removal framework is used to determine which frames from the background subtraction process are updated. The proposed method produces precise results with fast execution time, which are two critical factors in surveillance systems for more advanced tasks. The authors used two publicly available test sequences from the 2014 Change Detection and Scene background modelling data sets and internally collected data sets of scenes with dense traffic