Automated Identification of Digital Evidence across Heterogeneous Data Resources

Digital forensics has become an increasingly important tool in the fight against cyber and computer-assisted crime. However, with an increasing range of technologies at people’s disposal, investigators find themselves having to process and analyse many systems with large volumes of data (e.g., PCs, laptops, tablets, and smartphones) within a single case. Unfortunately, current digital forensic tools operate in an isolated manner, investigating systems and applications individually. The heterogeneity and volume of evidence place time constraints and a significant burden on investigators. Examples of heterogeneity include applications such as messaging (e.g., iMessenger, Viber, Snapchat, and WhatsApp), web browsers (e.g., Firefox and Google Chrome), and file systems (e.g., NTFS, FAT, and HFS). Being able to analyse and investigate evidence from across devices and applications in a universal and harmonized fashion would enable investigators to query all data at once. In addition, successfully prioritizing evidence and reducing the volume of data to be analysed reduces the time taken and cognitive load on the investigator. This thesis focuses on the examination and analysis phases of the digital investigation process. It explores the feasibility of dealing with big and heterogeneous data sources in order to correlate the evidence from across these evidential sources in an automated way. Therefore, a novel approach was developed to solve the heterogeneity issues of big data using three developed algorithms. The three algorithms include the harmonising, clustering, and automated identification of evidence (AIE) algorithms. The harmonisation algorithm seeks to provide an automated framework to merge similar datasets by characterising similar metadata categories and then harmonising them in a single dataset. This algorithm overcomes heterogeneity issues and makes the examination and analysis easier by analysing and investigating the evidential artefacts across devices and applications based on the categories to query data at once. Based on the merged datasets, the clustering algorithm is used to identify the evidential files and isolate the non-related files based on their metadata. Afterwards, the AIE algorithm tries to identify the cluster holding the largest number of evidential artefacts through searching based on two methods: criminal profiling activities and some information from the criminals themselves. Then, the related clusters are identified through timeline analysis and a search of associated artefacts of the files within the first cluster. A series of experiments using real-life forensic datasets were conducted to evaluate the algorithms across five different categories of datasets (i.e., messaging, graphical files, file system, internet history, and emails), each containing data from different applications across different devices. The results of the characterisation and harmonisation process show that the algorithm can merge all fields successfully, with the exception of some binary-based data found within the messaging datasets (contained within Viber and SMS). The error occurred because of a lack of information for the characterisation process to make a useful determination. However, on further analysis, it was found that the error had a minimal impact on subsequent merged data. The results of the clustering process and AIE algorithm showed the two algorithms can collaborate and identify more than 92% of evidential files.HCED Ira

Automating the harmonisation of heterogeneous data in digital forensics

Digital forensics has become an increasingly important tool in the fight against cyber and computer-assisted crime. However, with an increasing range of technologies at people’s disposal, investigators find themselves having to process and analyse many systems (e.g. PC, laptop, tablet, Smartphone) in a single case. Unfortunately, current tools operate within an isolated manner, investigating systems and applications on an individual basis. The heterogeneity of the evidence places time constraints and additional cognitive loads upon the investigator. Examples of heterogeneity include applications such as messaging (e.g. iMessenger, Viber, Snapchat and Whatsapp), web browsers (e.g. Firefox and Chrome) and file systems (e.g. NTFS, FAT, and HFS). Being able to analyse and investigate evidence from across devices and applications based upon categories would enable investigators to query all data at once. This paper proposes a novel algorithm to the merging of datasets through a ‘characterisation and harmonisation’ process. The characterisation process analyses the nature of the metadata and the harmonisation process merges the data. A series of experiments using real-life forensic datasets are conducted to evaluate the algorithm across five different categories of datasets (i.e. messaging, graphical files, file system, Internet history, and emails), each containing data from different applications across difference devices (a total of 22 disparate datasets). The results showed that the algorithm is able to merge all fields successfully, with the exception of some binary-based data found within the messaging datasets (contained within Viber and SMS). The error occurred due to a lack of information for the characterisation process to make a useful determination. However, upon the further analysis it was found the error had a minimal impact on subsequent merged data

The Optimizing of Prefabricated Solar Cells by Dual Plasmonic Nanoparticles

Background: The quest for improving the efficiency of solar cells has garnered considerable attention in numerous scientific investigations. One promising approach involves utilizing plasmons generated by metal nanoparticles to enhance the performance of photovoltaic solar cells. Materials and Methods: High-purity gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and a combination of both were synthesized using pulsed laser ablation in distilled water. Subsequently, these nanoparticles were deposited onto silicon (Si) substrates and pre-existing Si homo-junction photovoltaic cells. Results: The optical analysis of the prepared nanoparticle suspension revealed distinct plasmonic bands located at approximately 400 nm and 523 nm wavelengths for AgNPs and AuNPs, respectively. In the case of the AuNPs:AgNPs mixture, two plasmonic bands were observed, corresponding to the presence of both types of metal nanoparticles. The X-ray diffraction (XRD) analysis of the deposited nanoparticle samples on Si wafers demonstrated a polycrystalline structure for all samples. Scanning electron microscopy (SEM) imaging displayed uniformly distributed spherical Au nanoparticles on the substrate, while AgNPs exhibited some aggregations. Conclusion: The photovoltaic (PV) solar cells demonstrated an enhanced performance, attributed to the ability of the plasmonic nanoparticles to facilitate increased light absorption or enhance surface conductivity. The combination of silver and gold particles holds promise for solar surface coating, further optimizing the cells to capture a greater amount of solar radiation within their plasmon peaks. This study highlights the potential of plasmonic nanoparticles to enhance the efficiency of previously prepared PV cells

Quasi-two-dimensional MHD duct flow around a 180-degree sharp bend in a strong magnetic field

This study considers the quasi-two-dimensional flow of an electrically conducting fluid subjected to a strong out-of-plane magnetic field in a rectangular duct. The effect of Hartmann number on flow features such as the length of the downstream recirculation bubbles and the threshold Reynolds numbers between steady-state and unsteady flow regimes for values of the ratio between the throat of the bend and the duct height, β = 1 are identified. The simulations reveal that the primary recirculation bubble length decreases with increasing Hartmann number, and simultaneously the secondary recirculation bubble is significantly damped compared to the corresponding non-MHD case. The critical Reynolds number where the transitions from steady to unsteady flow occurs was found to increase with increasing of Hartman number. This study provides information that will be useful for refining the design of heat exchanger ducting in MHD systems to maximise the useful mass transport adjacent to the duct walls where heating is applied

Extracting dualband antenna response from UWB based on current distribution analysis

An entirely new design approach has been employed to create the printed dualband monopole antenna that was the subject of this investigation. The printed monopole antenna construction is the primary component of the suggested design. CPW transmission lines with 50 Ohm impedance and a relative dielectric constant of 4.6 were used to power the antennas, which were housed in thin substrates with thicknesses of 1.6 millimeters (mm). In this study, the antennas discussed were modeled and analyzed by Computer Simulation Technique (CST) simulator. Using fractal structures on the radiating element of a dualband antenna can improve the resonance of the antenna as well as the coupling of the resonating bands that emerge from the resonance

European Society of Cardiology: Cardiovascular Disease Statistics 2019

Aims The 2019 report from the European Society of Cardiology (ESC) Atlas provides a contemporary analysis of cardiovascular disease (CVD) statistics across 56 member countries, with particular emphasis on international inequalities in disease burden and healthcare delivery together with estimates of progress towards meeting 2025 World Health Organization (WHO) non-communicable disease targets. Methods and results In this report, contemporary CVD statistics are presented for member countries of the ESC. The statistics are drawn from the ESC Atlas which is a repository of CVD data from a variety of sources including the WHO, the Institute for Health Metrics and Evaluation, and the World Bank. The Atlas also includes novel ESC sponsored data on human and capital infrastructure and cardiovascular healthcare delivery obtained by annual survey of the national societies of ESC member countries. Across ESC member countries, the prevalence of obesity (body mass index ≥30 kg/m2) and diabetes has increased two- to three-fold during the last 30 years making the WHO 2025 target to halt rises in these risk factors unlikely to be achieved. More encouraging have been variable declines in hypertension, smoking, and alcohol consumption but on current trends only the reduction in smoking from 28% to 21% during the last 20 years appears sufficient for the WHO target to be achieved. The median age-standardized prevalence of major risk factors was higher in middle-income compared with high-income ESC member countries for hypertension {23.8% [interquartile range (IQR) 22.5–23.1%] vs. 15.7% (IQR 14.5–21.1%)}, diabetes [7.7% (IQR 7.1–10.1%) vs. 5.6% (IQR 4.8–7.0%)], and among males smoking [43.8% (IQR 37.4–48.0%) vs. 26.0% (IQR 20.9–31.7%)] although among females smoking was less common in middle-income countries [8.7% (IQR 3.0–10.8) vs. 16.7% (IQR 13.9–19.7%)]. There were associated inequalities in disease burden with disability-adjusted life years per 100 000 people due to CVD over three times as high in middle-income [7160 (IQR 5655–8115)] compared with high-income [2235 (IQR 1896–3602)] countries. Cardiovascular disease mortality was also higher in middle-income countries where it accounted for a greater proportion of potential years of life lost compared with high-income countries in both females (43% vs. 28%) and males (39% vs. 28%). Despite the inequalities in disease burden across ESC member countries, survey data from the National Cardiac Societies of the ESC showed that middle-income member countries remain severely under-resourced compared with high-income countries in terms of cardiological person-power and technological infrastructure. Under-resourcing in middle-income countries is associated with a severe procedural deficit compared with high-income countries in terms of coronary intervention, device implantation and cardiac surgical procedures. Conclusion A seemingly inexorable rise in the prevalence of obesity and diabetes currently provides the greatest challenge to achieving further reductions in CVD burden across ESC member countries. Additional challenges are provided by inequalities in disease burden that now require intensification of policy initiatives in order to reduce population risk and prioritize cardiovascular healthcare delivery, particularly in the middle-income countries of the ESC where need is greatest

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Three-dimensional linear stability analysis of the flow around a sharp 180-degree bend

This study seeks to characterise the stability of a two-dimensional channel flow involving a 180-degree sharp bend, to infinitesimal three-dimensional disturbances by way of linear stability analysis. A highly accurate global linear stability analysis of the flow is presented via the Reynolds number Re varies in the range 100 ≤ Re ≤ 700, this Re range produces steady state two-dimensional flow solutions for bend opening ratio (ratio of bend width on inlet height) β = 1. The two-dimensional base flow solutions demonstrate that as β decreases, the transition from steady to unsteady occurs at lower Reynolds number. The stability analysis shows that the flow first becomes unstable to a synchronous three-dimensional instability mode with spanwise wavenumber k = 2 at approximately Re = 400, whereas the two-dimensional solution branch undergoes transition to unsteady flow somewhere near Re ≈ 800. Instability mode structures associated with the leading eigenvalues are localized at the re-attachment point of the first separation bubble and the separation point of the second separation bubble. The stability analysis is used to produce neutral stability curves and visualisations of the global modes of the system for typical Reynolds number are also presented