Tracing System Research Articles

Implementation of the Disclosure Principle in Submitting Evidence in Civil Lawsuits Through e-Court in the Class 1 A District Court Medan and Class 1 A District Court Lubuk Pakam

This article aims to determine the implementation of the principle of disclosure in submitting evidence in civil lawsuits through e-Court in the district court, by taking the location of research in the Class 1 A District Court Medan and Class 1 A District Court Lubuk Pakam. Technological advances have provided convenience in public services, including electronic case resolution services in district courts with the introduction of e-Court. The research methods used are the type of normative juridical research supported by field research, the approach methods used are statutory approaches and conceptual approaches, secondary data sources and primary data, technical data collection literature research and field research, qualitative data analysis and deductive conclusions. This study concludes that the electronic justice system (e-Court) in the Medan Class 1 A District Court and Lubuk Pakam Class 1 A Court provides convenience to the parties concerned and their legal representatives to submit evidence in civil lawsuits, but regarding the implementation of the principle of disclosure, the information obtained regarding evidence is only limited to information on letter evidence that enters the Court Information Tracing System which is still of doubtful authenticity without direct mail check.

Adoption of precision livestock farming technologies has the potential to mitigate greenhouse gas emissions from beef production

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometer-based sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kg CO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3 months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems.

Spatio-temporal evolution mechanism and dynamic simulation of nitrogen and phosphorus pollution of the Yangtze River economic Belt in China

Excess nitrogen and phosphorus inputs are the main causes of aquatic environmental deterioration. Accurately quantifying and dynamically assessing the regional nitrogen and phosphorus pollution emission (NPPE) loads and influencing factors is crucial for local authorities to implement and formulate refined pollution reduction management strategies. In this study, we constructed a methodological framework for evaluating the spatio-temporal evolution mechanism and dynamic simulation of NPPE. We investigated the spatio-temporal evolution mechanism and influencing factors of NPPE in the Yangtze River Economic Belt (YREB) of China through the pollution load accounting model, spatial correlation analysis model, geographical detector model, back propagation neural network model, and trend analysis model. The results show that the NPPE inputs in the YREB exhibit a general trend of first rising and then falling, with uneven development among various cities in each province. Nonpoint sources are the largest source of land-based NPPE. Overall, positive spatial clustering of NPPE is observed in the cities of the YREB, and there is a certain enhancement in clustering. The GDP of the primary industry and cultivated area are important human activity factors affecting the spatial distribution of NPPE, with economic factors exerting the greatest influence on the NPPE. In the future, the change in NPPE in the YREB at the provincial level is slight, while the nitrogen pollution emissions at the municipal level will develop towards a polarization trend. Most cities in the middle and lower reaches of the YREB in 2035 will exhibit medium to high emissions. This study provides a scientific basis for the control of regional NPPE, and it is necessary to strengthen cooperation and coordination among cities in the future, jointly improve the nitrogen and phosphorus pollution tracing and control management system, and achieve regional sustainable development.

Determination of Electrode Balancing in Multilayer Pouch Cells Through Tracking and Tracing in Lithium‐Ion Battery Production

AbstractManufacturing lithium‐ion batteries is a complex procedure with interconnected process steps. Unknown interdependencies lead to production deviations, which, in combination with expensive materials, result in costly rejects. To gain better insight into the processes, tracking and tracing systems are increasingly being established in battery cell production. This improves the database and enhances transparency, as quality‐critical production data is already recorded during electrode production and specifically assigned to individual intermediate products. The data assignment aids in characterizing intermediate products properties to identify correlations and defects. An important parameter is the balancing from cathode to anode, which has a crucial influence on cell performance. Therefore, this paper demonstrates the determination of the balancing between all electrode layers in a lithium‐ion pouch cell using a traceability system. The traceable areal mass loading was determined for each electrode sheet. After the stacking process, the opposing electrode areal mass loadings of the cathodes and anodes were used to calculate the electrode balancing. Subsequently, their influence on the cycling performance of the cells was investigated. Battery cells with areal mass loadings within the permissible tolerances showed no abnormalities, whereas cells with production fluctuations exhibited rapid ageing.

PM-Vis: A Visual Analytics System for Tracing and Analyzing the Evolution of Pottery Motifs.

In Chinese archaeological research, analyzing the evolution of motifs in ancient pottery is crucial for studying the spread and growth of cultures across various eras and regions. However, such analyses are often challenging due to the complexities of identifying motifs with evolutionary connections that may manifest concurrent changes in appearance, space, and time, compounded by ineffective documentation. We propose PM-Vis, a visual analytics system for tracing and analyzing the evolution of pottery motifs. PM-Vis is anchored in a "selection-organization-documentation" workflow. In the selection stage, we design a three-fold projection paired with a motif-based search mechanism, displaying the appearance similarity and temporal and spatial proximities of all motifs or a specific motif, aiding users in selecting motifs with evolutionary connections. The organization stage helps users establish the evolutionary sequence and segment the selected motifs into distinct evolutionary phases. Finally, the documentation stage enables users to record their observations and insights through various forms of annotation. We demonstrate the usefulness and effectiveness of PM-Vis through two case studies, expert feedback, and a user study.

Peripheral defocus of monofocal intraocular lenses.

To quantify the angular dependence of monofocal intraocular lens (IOL) power. Ophthalmic Biophysics Laboratory, Kallam Anji Reddy campus, L V Prasad Eye Institute, Hyderabad, India. Laboratory study. Experiments were performed on IOLs from 2 different manufacturers (APPALENS 207, Appasamy Associates and SN60WF, Alcon Laboratories, Inc.). IOL powers ranged from 17 to 25 diopters (D). The IOLs were mounted in a fluid-filled chamber, and the on-axis and off-axis powers were measured using a laser ray tracing system over the central 3 mm zone with delivery angles ranging from -30 to +30 degrees in 5-degree increments. The position of the best focus was calculated for each IOL at each angle. The angular dependence of IOL power was compared with theoretical predictions. Peripheral defocus increased significantly with increasing incidence angle and power. The peripheral defocus at ±30 degrees increased from 5.8 to 8.5 D when the power increased from 17.5 to 24.5 D for APPALENS 207 and from 4.9 to 7.4 D when the power increased from 17 to 25 D for SN60WF. The mean difference between the measured and theoretical tangential power at ±30 degrees was 0.50 ± 0.16 D for the APPALENS 207 and -0.40 ± 0.10 D for the SN60WF, independent of IOL power. IOLs introduce a significant amount of peripheral defocus which varies significantly with IOL power and design. Given that peripheral defocus is related to lens power, replacement of the crystalline lens (approximately 24 D) with an IOL will produce a significant difference in peripheral defocus profile after surgery.

Machine learning experiment management tools: a mixed-methods empirical study

Machine Learning (ML) experiment management tools support ML practitioners and software engineers when building intelligent software systems. By managing large numbers of ML experiments comprising many different ML assets, they not only facilitate engineering ML models and ML-enabled systems, but also managing their evolution—for instance, tracing system behavior to concrete experiments when the model performance drifts. However, while ML experiment management tools have become increasingly popular, little is known about their effectiveness in practice, as well as their actual benefits and challenges. We present a mixed-methods empirical study of experiment management tools and the support they provide to users. First, our survey of 81 ML practitioners sought to determine the benefits and challenges of ML experiment management and of the existing tool landscape. Second, a controlled experiment with 15 student developers investigated the effectiveness of ML experiment management tools. We learned that 70% of our survey respondents perform ML experiments using specialized tools, while out of those who do not use such tools, 52% are unaware of experiment management tools or of their benefits. The controlled experiment showed that experiment management tools offer valuable support to users to systematically track and retrieve ML assets. Using ML experiment management tools reduced error rates and increased completion rates. By presenting a user’s perspective on experiment management tools, and the first controlled experiment in this area, we hope that our results foster the adoption of these tools in practice, as well as they direct tool builders and researchers to improve the tool landscape overall.

Key Advantages of Agrivoltaic Systems in Germany – A Comparison of the Electricity Yield of Different Systems

In addition to food production, energy can also be produced on agricultural land. This can lead to land use conflicts and often results in political discussions. As the energy transition progresses, the area required for renewable energies is increasing, leading to more land use conflicts. Agrivoltaics (APV) allows for continued farming alongside solar power production, providing a solution to this conflict. In this analysis, the land energy yields of different APV concepts were compared with those of other renewable energies. The results show that wind and PV can produce the most energy on land, regardless of whether the sectors are electricity, heat or transport. When considering different APV concepts on cropland, it is important to consider which area is being evaluated. A distinction can be made between the PV-system area (the visually influenced area in the landscape) and the loss of farmland. Depending on the perspective, the concepts have different advantages. The APV vertical concept enables 3 times more electricity production per loss of farmland compared to a conventional ground-mounted PV system. However, in relation to the PV-system area, the electricity yield is only 1/3 of this. The APV horizontal concept has the highest electricity yields per area of loss of farmland. The APV 3D tracing system has the highest electricity yield of all APV concepts per PV-system area. Initial economic analyses show that higher energy yields per loss of farmland are accompanied by higher costs for APV systems. These results can be used for political advice.

Классификация и информационные ячейки следовых ядер

The article reviews the problems of the establishment of new understanding of the system of traces in Russian criminalistics. The authors suggest a classifi cation of "trace cores", which is a term introduced in the scholarly dispute, and analyze the content of "trace cores" (information cells). A classifi cation of "trace cores" will give practitioners a better understanding of what traces are to be searched for in the investigation of certain crime types. This will improve the crime investigation effi ciency.

Efficient practical Byzantine Consensus-based reputation method for IoT based electronic waste tracking and tracing system using blockchain

Efficient practical Byzantine Consensus-based reputation method for IoT based electronic waste tracking and tracing system using blockchain

COVID-19 cluster surveillance using exposure data collected from routine contact tracing: The genomic validation of a novel informatics-based approach to outbreak detection in England.

Contact tracing was used globally to prevent onwards transmission of COVID-19. Tracing contacts alone is unlikely to be sufficient in controlling community transmission, due to the pre-symptomatic, overdispersed and airborne nature of COVID-19 transmission. We describe and demonstrate the validity of a national enhanced contact tracing programme for COVID-19 cluster surveillance in England. Data on cases occurring between October 2020 and September 2021 were extracted from the national contact tracing system. Exposure clusters were identified algorithmically by matching ≥2 cases attending the same event, identified by matching postcode and event category within a 7-day rolling window. Genetic validity was defined as exposure clusters with ≥2 cases from different households with identical viral sequences. Exposure clusters were fuzzy matched to the national incident management system (HPZone) by postcode and setting description. Multivariable logistic regression modelling was used to determine cluster characteristics associated with genetic validity. Over a quarter of a million (269,470) exposure clusters were identified. Of the eligible clusters, 25% (3,306/13,008) were genetically valid. 81% (2684/3306) of these were not recorded on HPZone and were identified on average of one day earlier than incidents recorded on HPZone. Multivariable analysis demonstrated that exposure clusters occurring in workplaces (aOR = 5·10, 95% CI 4·23-6·17) and education (aOR = 3·72, 95% CI 3·08-4·49) settings were those most strongly associated with genetic validity. Cluster surveillance using enhanced contact tracing in England was a timely, comprehensive and systematic approach to the detection of transmission events occurring in community settings. Cluster surveillance can provide intelligence to stakeholders to support the assessment and management of clusters of COVID-19 at a local, regional, and national level. Future systems should include predictive modelling and network analysis to support risk assessment of exposure clusters to improve the effectiveness of enhanced contract tracing for outbreak detection.

An evaluation of the COVID-19 self-service digital contact tracing system in New Zealand

BackgroundDigital contact tracing (DCT) aims to improve time-to-isolation (timeliness) and find more potentially exposed individuals (sensitivity) to enhance the utility of contact tracing. The aim of this study was to evaluate the public uptake of a DCT self-service survey and its integration with the Bluetooth exposure notification system within the New Zealand Covid Tracer App (NZCTA). MethodsWe adopted a retrospective cohort study design using community COVID-19 cases from February 2022 to August 2022 in New Zealand (1.2 million cases). We examined the proportion of cases completing a self-service survey and the time to complete the survey by age, sex and ethnicity. ResultsOverall, 66 % of cases completed their self-service survey. Completion was influenced by age, sex and ethnicity. The median completion time was 1.8 h (IQR 0.2, 17.2), with 95 % of those completing this survey doing so within 48 h of case identification. Around 13 % of all survey completers also uploaded their Bluetooth data, which resulted in an average of 663 cases per day notifying 4.5 contacts per case. ConclusionThe combination of high public uptake and rapid response times suggest self-service DCT could be a useful tool for future outbreaks, particularly if implemented in conjunction with manual processes and other DCT tools (e.g. Bluetooth) to address issues related to performance (sensitivity, timeliness), effectiveness, and health equity.

Smoking out Australia's growing illicit tobacco market: Current trends and future challenges

Data from the Australian Taxation Office and Australian Border Force show notable recent increases in illicit tobacco seizures across Australia. The illicit tobacco market results in substantial losses in tax revenue, funds organised crime, and perpetuates tobacco use, threatening to undermine Australia's ability to achieve its national commercial tobacco endgame goal of 5 % or less smoking prevalence by 2030. This commentary discusses recent trends in Australia's illicit tobacco trade, reasons why this is of concern, potential drivers of Australians’ illicit tobacco use, and policy measures that could be implemented to mitigate increasing illicit tobacco trade such as implementing a track and trace system, increased investment in the Australian Border Force to enhance detection of illicit tobacco shipments at Australia's borders, and encouraging public tip-offs of illicit tobacco sales.

Exploring individual's public trust in the NHS Test and Trace System – A pragmatic reflexive thematic analysis

ContextDigital contact tracing uses automated systems and location technology embedded on smartphone software for efficient identification of individuals exposed to COVID-19. Such systems are only effective with high compliance, yet compliance is mediated by public trust in the system. This work explored the perception of individual's trust and expectation of the broader Test and Trace system in the United Kingdom (UK) with the upcoming release of the National Health Service's (NHS) COVID-19 app as a case example. MethodsTwelve adults underwent online semi-structured interviews in August 2020, prior to public availability of the COVID-19 app. Pragmatic reflexive thematic analysis was applied inductively to explore common themes between participants, using an organic and recursive process (Braun & Clarke, 2019). ResultsThemes highlighted features of the technology that would be perceived to be trustworthy (Theme 1), and concerns relating to i) whether users would comply with a T&T system (Theme 2) and ii) how a T&T system would handle user's personal data (Theme 3). Two further themes built on aspects of automation within a T&T system and its impact on trust (Theme 4) and how the media altered perceptions of the T&T system (Theme 5). ConclusionsParticipants outlined the need for different user requirements that could be built into the NHS COVID-19 app that would support increased adherence. Concurrently, participants raised questions surrounding personal data and privacy of their data, plus the level of automated versus manual tasks, which impacted perception of trust in the app and wider system. Additionally, themes highlighted that T&T systems do not happen within a vacuum, but within a pre-existing environment influenced by variables such as the media and perception of other's compliance to T&T. ImplicationsSince it's roll-out, controversies surrounding the UK T&T system include concerns about privacy, stigma and uptake. Considering the current piece of work, which anticipated similar concerns prior to public access to COVID-19 app, engaging with the public may have been an important step in improving the perception and compliance with the app. Principles fundamental to patient and public involvement (PPI) and Responsible Research and Innovation (RRI) such as the inclusion of the public in the early development of research and aligning the outcomes of research and innovation with broader societal values and expectations would have been well-applied to this system and should be applied to future autonomous systems requiring high public uptake.

Digital Contact Tracing Solutions: Promises, Pitfalls and Challenges

The COVID-19 pandemic has caused many countries to deploy novel digital contact tracing (DCT) systems to boost the efficiency of manual tracing of infection chains. In this paper, we systematically analyze DCT solutions and categorize them based on their design approaches and architectures. We analyze them with regard to effectiveness, security, privacy and ethical aspects and compare prominent solutions based on these requirements. In particular, we discuss shortcomings of the Google and Apple Exposure Notification API (GAEN) that is currently widely adopted all over the world. We find that the security and privacy of GAEN has considerable deficiencies as it can be compromised by severe large-scale attacks. We also discuss other proposed approaches for contact tracing, including our proposal <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TraceCORONA</small> , that are based on Diffie-Hellman (DH) key exchange and aim at tackling shortcomings of existing solutions. Our extensive analysis shows that <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TraceCORONA</small> fulfills the above security requirements better than deployed state-of-the-art approaches. We have implemented <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TraceCORONA</small> and its beta test version has been used by more than 2000 users without any major functional problems <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://tracecorona.net/download-tracecorona/</uri> , demonstrating that there are no technical reasons requiring to make compromises with regard to the requirements of DCT approaches.

Anthropogenic gadolinium sources and remediation in highly urbanized river in the Beijing-Tianjin-Hebei (BTH) region, China: Insights from buffer zone and three-dimensional tracer system

As a newly emerging microcontaminant, rare earth elements (REEs), especially gadolinium (Gd) in surface water, are attracting great environmental concern in large urban cities. The Beijing-Tianjin-Hebei (BTH) region stands as the preeminent urban agglomeration in northern China, whereas the riverine Gd characteristics and environmental impacts on this region remain inadequate. This study analyzed 27 river water samples in BTH, all of which displayed evidently positive Gd anomalies ranging 1.44–290.75. Spearman correlation indicated the positively correlated REEs concentrations in river water with urban land and cultivated land. A three-dimensional tracing system was established involving anthropogenic Gd (Gdanth) and conventional ion ratios (NO3−/Na+, Cl−/Na+). This system effectively discerned the influences originating from sewage treatment plants, wastewater treatment plants, hospitals, and factories within the BTH region. Gd-based contrast agents (GBCAs) manifest notable potential ecological toxicity and adverse health effects when getting exposed. However, traditional wastewater treatment methods demonstrate limited efficacy in removing these pollutants completely from urban water. To deal with this challenge, this study proposed a new method by combining the latest GBCAs remediation technology with mixing membrane wastewater treatment. This technology may shed light on the potential of an economical and operational procedure of handling medical wastewater specifically in urban water.

Estimating the impact of test–trace–isolate–quarantine systems on SARS-CoV-2 transmission in Australia

Background:Australian states and territories used test–trace–isolate–quarantine (TTIQ) systems extensively in their response to the COVID-19 pandemic in 2020-2021. We report on an analysis of Australian case data to estimate the impact of test–trace–isolate–quarantine systems on SARS-CoV-2 transmission. Methods:Our analysis uses a novel mathematical modelling framework and detailed surveillance data on COVID-19 cases including dates of infection and dates of isolation. First, we directly translate an empirical distribution of times from infection to isolation into reductions in potential for onward transmission during periods of relatively low caseloads (tens to hundreds of reported cases per day). We then apply a simulation approach, validated against case data, to assess the impact of case-initiated contact tracing on transmission during a period of relatively higher caseloads and system stress (up to thousands of cases per day). Results:We estimate that under relatively low caseloads in the state of New South Wales (tens of cases per day), TTIQ contributed to a 54% reduction in transmission. Under higher caseloads in the state of Victoria (hundreds of cases per day), TTIQ contributed to a 42% reduction in transmission. Our results also suggest that case-initiated contact tracing can support timely quarantine in times of system stress (thousands of cases per day). Conclusion:Contact tracing systems for COVID-19 in Australia were highly effective and adaptable in supporting the national suppression strategy from 2020–21, prior to the emergence of the Omicron variant in November 2021. TTIQ systems were critical to the maintenance of the strong suppression strategy and were more effective when caseloads were (relatively) low.

Abstract 1085: Exploiting bioenergetic vulnerabilities in chemotherapy resistant osteosarcoma

Abstract BACKGROUND: Osteosarcoma (OS) is the most common bone cancer in children and young adults. Standard treatment involves chemotherapy and surgical resection, yet nearly 4 in 10 patients experience disease relapse, and almost all of these patients are resistant to additional chemotherapy. Therefore, there is an urgent need to understand the biology of chemo-resistant OS and identify new therapeutic strategies to treat this therapy-resistant disease state. METHODS: Using a CRISPR-Cas9 based lineage tracing system, RNA sequencing, and Seahorse XF assays in chemo-naïve, -resistant, and -released human 143b and patient-derived 173x OS cell lines, we modeled the evolution of chemoresistance and release from the selective pressure of chemotherapy in osteosarcoma. The phenotype of each cell state was assessed through in vitro and ex vivo cell proliferation assays, a comparison of cell viability upon re-challenge to standard-of-care chemotherapy, and comparison of cell viability in response to novel therapies targeting alterations in cell respiration. RESULTS: Chemo-resistant OS cells demonstrate a decrease in expression of proliferation-associated gene pathways and shift their resources toward expression and maintenance of multi-drug resistance ABC transporters. Chemo-released cells maintain elevated expression of ABC transporters while re-activating proliferation. Across the spectrum of chemotherapy exposure, OS cells demonstrate changes in respiratory capacity, with unique bioenergetic phenotypes observed in chemo-naïve, -resistant, and -released cells. CONCLUSIONS: Chemo-resistant and chemo-released OS cells demonstrate unique bioenergetic patterns that correlate with gene expression signatures and growth phenotypes. Evolution imposed by the selective pressure of chemotherapy may render OS cells vulnerable to therapies that disrupt cellular energetics and exploit multi-drug resistant ABC transporters. Citation Format: Valerie U. Nguyen, Laurie Graves, Veronica Colmenares, Abol Macabangon, Casey Syal, Kelsey Fisher-Wellman, William C. Eward, So Young Kim, Jason A. Somarelli. Exploiting bioenergetic vulnerabilities in chemotherapy resistant osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1085.

Iterative Reconstruction of Micro Computed Tomography Scans Using Multiple Heterogeneous GPUs.

Graphics processing units (GPUs) facilitate massive parallelism and high-capacity storage, and thus are suitable for the iterative reconstruction of ultrahigh-resolution micro computed tomography (CT) scans by on-the-fly system matrix (OTFSM) calculation using ordered subsets expectation maximization (OSEM). We propose a finite state automaton (FSA) method that facilitates iterative reconstruction using a heterogeneous multi-GPU platform through parallelizing the matrix calculations derived from a ray tracing system of ordered subsets. The FSAs perform flow control for parallel threading of the heterogeneous GPUs, which minimizes the latency of launching ordered-subsets tasks, reduces the data transfer between the main system memory and local GPU memory, and solves the memory-bound of a single GPU. In the experiments, we compared the operation efficiency of OS-MLTR for three reconstruction environments. The heterogeneous multiple GPUs with job queues for high throughput calculation speed is up to five times faster than the single GPU environment, and that speed up is nine times faster than the heterogeneous multiple GPUs with the FIFO queues of the device scheduling control. Eventually, we proposed an event-triggered FSA method for iterative reconstruction using multiple heterogeneous GPUs that solves the memory-bound issue of a single GPU at ultrahigh resolutions, and the routines of the proposed method were successfully executed on each GPU simultaneously.

A self-controlled case series study to measure the risk of SARS-CoV-2 infection associated with attendance at sporting and cultural events: the UK Events Research Programme events

BackgroundIn 2021, whilst societies were emerging from major social restrictions during the SARS-CoV-2 pandemic, the UK government instigated an Events Research Programme to examine the risk of COVID-19 transmission from attendance at cultural events and explore ways to enable people to attend a range of events whilst minimising risk of transmission. We aimed to measure any impact on risk of COVID-19 transmission from attendance at events held at or close to commercially viable capacity using routinely collected data.MethodsData were obtained on attendees at Phase 3 Events Research Programme events, for which some infection risk mitigation measures were in place (i.e. evidence of vaccination or a negative lateral flow test). Attendance data were linked with COVID-19 test result data from the UK Test and Trace system. Using a self-controlled case series design, we measured the within person incidence rate ratio for testing positive for COVID-19, comparing the rate in days 3 to 9 following event attendance (high risk period) with days 1 and 2 and 10–16 (baseline period). Rate ratios were adjusted for estimates of underlying regional COVID-19 prevalence to account for population level fluctuations in infection risk, and events were grouped into broadly similar types.ResultsFrom attendance data available for 188,851 attendees, 3357 people tested positive for COVID-19 during the observation period. After accounting for total testing trends over the period, incidence rate ratios and 95% confidence intervals for positive tests were 1.16 (0.53–2.57) for indoor seated events, 1.12 (0.95–1.30) for mainly outdoor seated events, 0.65 (0.51–0.83) for mainly outdoor partially seated events, and 1.70 (1.52–1.89) for mainly outdoor unseated multi-day events.ConclusionsFor the majority of event types studied in the third phase of the UK Events Research Programme, we found no evidence of an increased risk of COVID-19 transmission associated with event attendance. However, we found a 70% increased risk of infection associated with attendance at mainly outdoor unseated multi-day events. We have also demonstrated a novel use for self-controlled case series methodology in monitoring infection risk associated with event attendance.