Tool For Evaluation Research Articles

Elevated Blood Pressure and Culprit Aneurysm Rebleeding During the Unsecured Period of Aneurysmal Subarachnoid Hemorrhage: A Systematic Review.

In aneurysmal subarachnoid hemorrhage, rebleeding prior to securing the culprit aneurysm leads to significant morbidity and mortality. Elevated blood pressure has been identified as a possible risk factor. In this systematic review, we evaluated the association between elevated blood pressure and aneurysm rebleeding during the unsecured period. We searched MEDLINE, Embase + Embase Classic, and CENTRAL, from inception to March 8th, 2024. We included studies of adults with aneurysmal subarachnoid hemorrhage reporting at least one blood pressure measurement during the unsecured period and a measure of association with rebleeding. Results were stratified by blood pressure thresholds, effect measure, and adjustment for confounding. Separate meta-analyses were performed for each of these groups. Our search identified 5,209 citations. After screening, 15 studies were included in our review. All studies were observational in design and at moderate or high risk of bias. Meta-analysis of the unadjusted results produced mixed findings across the systolic blood pressure (SBP) thresholds: SBP > 140mmHg, unadjusted odds ratio (uOR) 1.03 (95% confidence interval [CI] 0.55-1.93; I2 = 66%); SBP > 160mmHg, uOR 3.35 (95% CI 1.44-7.81; I2 = 83%); SBP > 180mmHg, uOR 1.52 (95% CI 0.40-5.81; I2 = 89%); and SBP > 200mm Hg, uOR 7.99 (95% CI 3.60-17.72; I2 = 0%). Meta-analysis of adjusted results was only possible at an SBP > 160mmHg; adjusted hazard ratio 1.13 (95% CI 0.98-1.31; I2 = 0%). The overall quality of evidence as assessed by the Grading of Recommendations, Assessment, Development, and Evaluations tool was rated as very low. Based on very low quality evidence, our systematic review failed to determine whether there is an association between elevated blood pressure during the unsecured period and increased risk of culprit aneurysm rebleeding.

Evaluating community projects through participatory rural appraisal: case study of a CSR initiative in India

ABSTRACT The success of any project depends on the stakeholder participation. There are many methods by which stakeholder participation is ensured in a project. Participatory Rural Appraisal (PRA) is an approach that is used by many development projects to incorporate knowledge and opinions of the stakeholders, especially the beneficiaries, in various stages like planning, implementation, and evaluation. This paper documents a PRA exercise done by trained social work students to evaluate a company’s Corporate Social Responsibility (CSR) projects implemented in India. Apart from highlighting the process of conducting PRA, this paper sheds light on the possibility of using participatory methods like PRA to assess CSR projects in India, which ensures the inclusion of the perception of beneficiaries. The research adopted a case study approach, and the participants were the beneficiaries of CSR projects in the community. Qualitative feedback was also taken from 20 participants to understand the advantages of using participatory tools in the performance evaluation of CSR. The group discussions, in-depth interviews and PRA techniques were adopted to gather data. The findings underline the relevance of social work professionals in CSR initiatives and also the role of PRA in empowering the beneficiaries.

Limitations of Self-Report Tools in Pain Evaluation of Patients With Vertebral Fractures.

Few studies have evaluated the usefulness and limitations of pain assessment using verbal communication tools for acute orthopedic diseases in older patients. The purpose of this study was to assess the rate of usage of the numerical rating scale (NRS), a verbal communication tool, and to identify the characteristics of patients in whom continuous assessment was impossible. We retrospectively examined electronic medical records of patients with acute vertebral fractures who had been admitted to our hospital between April 2018 and March 2020. Continuous pain assessment using the NRS was possible in 43.2% of hospitalized patients with the fractures. The factors preventing continuous pain assessment using the NRS were an advanced age and low Mini-Mental State Examination (MMSE) scores. Based on the receiver-operating characteristic curves, the cutoff age and MMSE score were >85.3 years and <22, respectively. Continuous NRS-based pain assessment is difficult in older adult patients or those with cognitive decline with acute vertebral fractures. In future, a simple observational assessment tool for patients with dementia should be introduced in acute medical care settings.

Stabilized oily-wastewater separation based on superhydrophilic and underwater superoleophobic ceramic membranes: Integrated experimental design and standalone machine learning algorithms

BackgroundReliable computational approaches to evaluate ceramic membrane performance in wastewater treatment mark a transformative step towards optimizing separation processes, ensuring environmental sustainability, and advancing water purification technologies. The current study explores the influential factors using artificial intelligence (AI) tools in the performance evaluation of superhydrophilic and underwater super-oleophobic ceramic membranes for the selective treatment of oily wastewater. MethodsThe chemometrics scenario of the research based on established experimental work employs advanced AI models viz: Random Forest (RF), Support Vector Regression (SVR), and Gaussian Process Regression (GPR) to predict the efficacy of these membranes in terms of rejection and flux. The model predictions were evaluated using the Pearson Correlation Coefficient (PCC), Willmott Index (WI), mean absolute percentage error (MAPE), and mean absolute error (MAE). Significant findingsFrom the results, GPR had shown good agreement with correlations (WI=99.9) during the training and testing phases for flux prediction, indicating an exceptional model fit with negligible error (MAPE=0.001, MAE=0.000 in the testing phase). For rejection modelling, GPR and SVR exhibit similar levels of accuracy, with moderate PCC and WI values, while RF reveals significant limitations with the lowest scores across all statistical metrics. The findings highlight the potential of AI in optimizing wastewater treatment processes, with GPR identified as the most promising model for flux prediction. This study would provide insight into the modelling of the membrane separation process for oily wastewater and integrate AI in the performance evaluation of wastewater reclamation.

Ecosystem risk from human use of ocean space and resources: A case study from the Norwegian coast

Coastal and adjacent shelf waters are generally highly productive ecosystems harboring important ecological processes and exposed to a range of anthropogenic pressures from land-based and marine sectors. Ensuring that the cumulative pressures from human activities do not cause unacceptable, permanent harm to the ecosystem is challenging but crucial for sustainable management of these regions. Linkage frameworks and ecological risk assessments have proven to be useful tools for holistic evaluations of cumulative human pressures as a guide to managers and policy makers for prioritization of risk factors. Here, we present the first holistic assessment of ecosystem risk from human activities along the Norwegian coast. Pressures from coastal sectors are identified and weighted by the exposure to and potential impact on ecosystem components following the ODEMM (Options for Delivering Ecosystem-based Marine Management) framework. We focus on four coastal regions with contrasting scales of human activities. Two southern regions with multiple anthropogenic activities are associated with higher cumulative risk of negative impacts compared to northern areas where less extensive activities have a lower potential of harming the coastal ecosystems. Despite latitudinal differences in human use of the coastline, the pressures and ecosystem components associated with the greatest risk of cumulative impacts are relatively similar between the regions. Contaminants and underwater noise stand out as high-risk pressures, associated with multiple sectors with a high spatiotemporal footprint and with the potential to negatively impact a range of ecosystem components. Nevertheless, a confidence assessment also highlights the need for more in-depth analysis on the input, spread and effect of these pressures on coastal ecosystems. We discuss strengths and weaknesses of the risk assessment framework and suggest new directions which may enhance the utility and uptake of such assessments for sustainable management of coastal ecosystems.

Methodology Underlying Indonesian Corporates Decarbonization Evaluator (INCODE)

The urgency to significantly decarbonize is increasing with the rising frequency of natural disasters caused by climate change. In 2019, the industrial sector produced more than 3 billion tons of carbon dioxide equivalent (CO2eq) (Ritchie et al. 2023) and played a crucial role in the reduction of global greenhouse gas (GHG) emissions, due also to substantial cross-sector emission contributions. The reduction of GHG emissions in the industrial sector can be achieved with proper and ambitious decarbonization planning, but formulating decarbonization strategies for the industrial sector is complex due to supply chain activities related to various sectors. Furthermore, the tools currently available are generally not easily accessible and have not integrated emission reduction with the impacts and costs generated. Recognizing this complexity, the Indonesian Corporates Decarbonization Evaluator (INCODE) was developed as an Excel-based tool that is easy to use, accessible, and comprehensive for the development and evaluation of net-zero emission strategies employed by companies involved in the industrial sector. In performing its functions, INCODE consists of two tools, namely the Corporate Greenhouse Gas Inventory Tool for Scopes 1, 2, and 3 (AIGRK) and the Decarbonization Evaluator Tool (AED). These two tools will offer four different features: emissions inventory, emission reduction evaluation, cost evaluation, and impact evaluation.

Accuracy Analysis of DeepL: Breakthroughs in Machine Translation Technology

This study examines the accuracy and technological innovations of DeepL, a prominent machine translation tool. Through a comprehensive literature review, we analyze DeepL's performance compared to other translation systems, exploring its advanced neural network architecture and training methods. Key findings indicate that DeepL consistently outperforms other tools in BLEU scores and human evaluations, particularly excelling in handling context, idiomatic expressions, and specialized terminology. The research highlights DeepL's use of the Transformer model, diverse training data, and techniques like transfer learning and data augmentation. Practical applications across academic, professional, and educational sectors are discussed, with special emphasis on how DeepL benefits students and teachers by facilitating multilingual learning, enhancing comprehension of foreign texts, and assisting in accurate translation of academic materials. User feedback underscores DeepL's accuracy and user-friendly features. While demonstrating significant advancements in machine translation technology, this study also acknowledges areas for potential improvement, contributing to the ongoing development of AI-driven language solutions.

International consensus on the management of large (≥20 mm) colorectal laterally spreading tumors: World Endoscopy Organization Delphi study.

There have been significant advances in the management of large (≥20 mm) laterally spreading tumors (LSTs) or nonpedunculated colorectal polyps; however, there is a lack of clear consensus on the management of these lesions with significant geographic variability especially between Eastern and Western paradigms. We aimed to provide an international consensus to better guide management and attempt to homogenize practices. Two experts in interventional endoscopy spearheaded an evidence-based Delphi study on behalf of the World Endoscopy Organization Colorectal Cancer Screening Committee. A steering committee comprising six members devised 51 statements, and 43 experts from 18 countries on six continents participated in a three-round voting process. The Grading of Recommendations, Assessment, Development and Evaluations tool was used to assess evidence quality and recommendation strength. Consensus was defined as ≥80% agreement (strongly agree or agree) on a 5-point Likert scale. Forty-two statements reached consensus after three rounds of voting. Recommendations included: three statements on training and competency; 10 statements on preresection evaluation, including optical diagnosis, classification, and staging of LSTs; 14 statements on endoscopic resection indications and technique, including statements on en bloc and piecemeal resection decision-making; seven statements onpostresection evaluation; and eight statements on postresection care. An international expert consensus based on the current available evidence has been developed to guide the evaluation, resection, and follow-up of LSTs. This may provide guiding principles for the global management of these lesions and standardize current practices.

Enhanced staging of extrahepatic hepatocellular carcinoma metastasis through dual-tracer PET/computed tomography: a systematic review and meta-analysis.

The aim of this study was to quantify the diagnostic value of dual-tracer PET/computed tomography (CT) with 11 C-acetate and fluorodeoxyglucose (FDG) in per-lesion and per-patient and its effect on clinical decision-making for choosing the most appropriate management. The study protocol is registered a priori at https://osf.io/rvm75/ . PubMed, Web of Science, Embase , and Cochrane Library were searched for relevant studies until 1 June 2023. Studies regarding the review question were included. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess bias risk. Per-lesion and per-patient diagnostic performance were calculated for: (1) 11 C-acetate alone; (2) FDG alone; and (3) dual tracer of 11 C-acetate and FDG. A direct comparison of these three combinations was made. The possible sources of statistical heterogeneity were also examined. We also calculated the percentage change in clinical decision-making when dual-tracer PET/CT was added to conventional imaging routinely used for metastatic evaluation (CT/MRI). Grading of Recommendations, Assessment, Development, and Evaluations tool was used to evaluate the certainty of evidence. Eight studies including 521 patients and 672 metastatic lesions were included. Dual-tracer PET/CT had a per-lesion sensitivity of 96.3% [95% confidence interval (CI), 91.8-98.4%] and per-patient sensitivity of 95.5% (95% CI, 89.1-98.2%) which were highly superior to either of tracers alone. Per-patient specificity was 98.5% (84.1-99.9%) which was similar to either of tracers alone. Overall, 9.3% (95% CI, 4.7-13.9%) of the patients had their management beneficially altered by adding dual-tracer PET/CT to their conventional CT/MRI results. Dual-tracer PET/CT substantially outperforms single-tracer methods in detecting extrahepatic hepatocellular carcinoma metastases, evidencing its reliability and significant role in refining clinical management strategies based on robust diagnostic performance.

Impact of spiritual interventions in individuals with cancer: A systematic review and meta-analysis

PurposeThis meta-analysis aimed to determine how spiritual interventions affect cancer patients’ physical, emotional, and spiritual outcomes and quality of life. MethodsBetween 2012 and May 2024, the Cochrane Library, Scopus, PubMed, and Web of Science were searched considering the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Twenty-six randomized controlled trials were included, and 16 were synthesized in the meta-analysis. Bias risk was evaluated using the Cochrane risk-of-bias methodology for randomized studies. The Grading of Recommendations, Assessment, Development, and Evaluations tool was employed for evidence certainty. Heterogeneity was expressed through I2 and Q statistics. Hedge's g was calculated for effect sizes. Egger's and Kendall's Tau were used for publication bias. ResultsSpiritual interventions yielded beneficial effects on fatigue (Hedges's g = 0.900, p < 0.001) and pain (Hedges's g = 0.670, p < 0.001) but not for overall symptom burden (Hedges's g = 0.208, p = 0.176). Significant effects were found for anxiety (Hedges's g = 0.301, p < 0.001), depression (Hedges's g = 0.175, p = 0.016), and psychological distress (Hedges's g = 0.178, p = 0.024), except for hopelessness (Hedges's g = 0.144, p = 0.091). Spiritual interventions enhanced faith (Hedges's g = 0.232, p = 0.035), the meaning of life (Hedges's g = 0.259, p = 0.002), spiritual well-being (Hedges's g = 0.268, p < 0.001), and quality of life (Hedges's g = 245, p < 0.001). Moderator analysis pointed out that cancer stage, total duration, delivery format, providers' qualification, content, and conceptual base of spiritual interventions significantly affect physical, emotional, and spiritual outcomes and quality of life. ConclusionThis meta-analysis highlighted the benefits of spiritual interventions with varying effect sizes on patients’ outcomes, as well as quality of life in cancer, and shed on how to incorporate these approaches into clinical practice.

Simplified and Detailed Evaluations of the Uncertainty of the Measurement of Microbiological Contamination of Pharmaceutical Products.

The control of the microbial contamination of pharmaceutical products (PP) is crucial to ensure their safety and efficacy. The validity of the monitoring of such contamination depends on the uncertainty of this quantification. Highly uncertain quantifications due to the variability of determinations or the magnitude of systematic effects affecting microbial growth or other analytical operations make analysis unfit for the intended use. The quantification of the measurement uncertainty expressing the combined effects of all random and systematic effects affecting the analysis allows for a sound decision about quantification adequacy for their intended use. The complexity of the quantification of microbial analysis uncertainty led to the development of simplified ways of performing this evaluation. This work assesses the adequacy of the simplified quantification of the uncertainty of the determination of the microbial contamination of PP by log transforming microbial count and dilution factor of the test sample whose uncertainty is combined in a log scale using the uncertainty propagation law. This assessment is performed by a parallel novel bottom-up and accurate evaluation of microbial analysis uncertainty involving the Monte Carlo method simulation of the Poisson log-normal distribution of counts and of the normally distributed measured volumes involved in the analysis. Systematic effects are assessed and corrected on results to compensate for their impact on the determinations. Poisson regression is used to predict precision affecting determinations on unknown test samples. Simplified and detailed models of the uncertainty of the measurement of the microbial contamination of PP are provided, allowing objective comparisons of several determinations and those with a maximum contamination level. This work concludes that triplicate determinations are required to produce results with adequately low uncertainty and that simplified uncertainty quantification underevaluates or overevaluates the uncertainty from determinations based on low or high colony numbers, respectively. Therefore, detailed uncertainty evaluations are advised for determinations between 50 and 200% of PP's maximum admissible contamination value. User-friendly tools for detailed and simplified evaluations of the uncertainty of the measurement of microbial contamination of PP are provided together with the understanding of when simplifications are adequate.

Benefits of Digital Tools in Learning Evaluation

Benefits of Digital Tools in Learning Evaluation

Localizing hidden Interictal Epileptiform Discharges with simultaneous intracerebral and scalp high-density EEG recordings

BackgroundScalp EEG is one of the main tools in the clinical evaluation of epilepsy. In some cases intracranial Interictal Epileptiform Discharges (IEDs) are not visible from the scalp. Recent studies have shown the feasibility of revealing them in the EEG if their timings are extracted from simultaneous intracranial recordings, but their potential for the localization of the epileptogenic zone is not yet well defined. New methodWe recorded simultaneous high-density EEG (HD-EEG) and stereo-electroencephalography (SEEG) during interictal periods in 8 patients affected by drug-resistant focal epilepsy. We identified IEDs in the SEEG and systematically analyzed the time-locked signals on the EEG by means of evoked potentials, topographical analysis and Electrical Source Imaging (ESI). The dataset has been standardized and is being publicly shared. ResultsOur results showed that IEDs that were not clearly visible at single-trials could be uncovered by averaging, in line with previous reports. They also showed that their topographical voltage distributions matched the position of the SEEG electrode where IEDs had been identified, and that ESI techniques can reconstruct it with an accuracy of ∼2 cm. Finally, the present dataset provides a reference to test the accuracy of different methods and parameters. Comparison with existing methodsOur study is the first to systematically compare ESI methods on simultaneously recorded IEDs, and to share a public resource with in-vivo data for their evaluation. ConclusionsSimultaneous HD-EEG and SEEG recordings can unveil hidden IEDs whose origins can be reconstructed using topographical and ESI analyses, but results depend on the selected methods and parameters.

COMPARING EXERCISE AGAINST A PLACEBO FOR PAIN AND DISABILITY OUTCOMES IN MUSCULOSKELETAL CONDITIONS: A SYSTEMATIC REVIEW &amp; META-ANALYSIS

BACKGROUND Musculoskeletal conditions are the leading cause of years lived with disability globally, with pain and disability being two of the most important patient-reported outcomes. Exercise is a commonly recommended treatment for musculoskeletal conditions, though it is unclear whether exercise outperforms sham for improving pain and disability. AIM: To determine if exercise improves pain and disability more than sham for people with musculoskeletal conditions. METHODS We searched 5 databases and 3 clinical trial registers for randomised controlled trials comparing exercise against sham in people with a musculoskeletal condition. The co-primary outcomes were pain and disability. Data were analysed using random effects meta-analysis or narrative synthesis if &amp;lt; 5 studies were available to be pooled. The certainty of findings was assessed using the Grading of Recommendations, Assessment, Development and Evaluations tool. Data are presented as mean difference [95% CI], with a difference of &amp;gt;10/100 for pain and &amp;gt;14.5/68 for disability (WOMAC physical function sub-scale) considered clinically meaningful. RESULTS Within the 15 included studies, all reported pain intensity and 13 reported disability. There was low certainty evidence that exercise was more efficacious than sham for lowering low back pain (-5.94 [-7.74, -4.15], n=1091), osteoarthritis pain (-6.19 [-14.36, 1.97], n=447) and osteoarthritis disability (-7.95 [-11.45, -4.46], n=211). Narrative synthesis showed varied effects of exercise versus sham on pain and disability in neck pain, as well as on disability in low back pain and other measures of disability in osteoarthritis. No studies were located for rheumatoid arthritis. CONCLUSION Based on low certainty evidence from a limited number of studies, exercise may not cause clinically significant differences for pain and disability compared to sham in adults with osteoarthritis and back pain. Further research is needed to confirm this for low back pain and osteoarthritis and to extend the findings other musculoskeletal conditions.

Analysis and construction of evaluation index system for tourism management classroom teaching based on regression model

In order to construct an evaluation index system suitable for tourism management classroom teaching, this article evaluates the teaching effectiveness of teachers and improves the teaching quality of tourism management courses. This article is based on developmental evaluation theory, using Analytic Hierarchy Process, Project Response Theory, and CIPP model to construct an indicator system suitable for tourism management classroom teaching. Then, based on the collected data of 5763 students, the reliability and effectiveness of the tool and indicator system were first verified. Then, the variable of teacher teaching style was introduced to construct an OLS regression model for empirical research. The research will summarize teacher and student data collected through the platform and conduct reliability analysis in SPSS 22.0 software, using Cronbach α The credibility of coefficient testing and evaluation tools. Cronbach in Environmental Fundamentals α The cβoefficient value is 0.8350. Cronbach for resource allocation α The coefficient is 0.735, and the Cronbah of the implementation process α Cronb Bach with a coefficient of 0.7 47 for teaching performance α The coefficient is 0.7240, indicating that rat ings has high reliability. Research has found that among the four specific types, the holistic type has the greatest impact on the specific situation, the holistic type has the greatest impact on the environmental foundation and resource allocation, and the legislative type has the greatest impact on the implementation process and teaching performance.

Clinical investigator perspectives on patient outcomes in children with neuronopathic mucopolysaccharidosis II during intrathecal idursulfase-IT treatment

BackgroundMucopolysaccharidosis II (MPS II) is a rare lysosomal storage disease characterized by iduronate-2-sulfatase gene (IDS) deficiency and downstream glycosaminoglycan accumulation. Two-thirds of patients present with neuronopathic disease and evaluating cognitive function in these patients is challenging owing to limitations of currently available tests. During the clinical development of intrathecal idursulfase (idursulfase-IT), regulatory authorities requested qualitative data to further understand the neurocognitive changes observed by the investigators through the clinical trials.ResultsThis qualitative study consisted of semi-structured interviews with all nine of the principal investigators who participated in the idursulfase-IT phase 2/3 (NCT02055118) and extension (NCT02412787) trials. These investigators enrolled the 56 patients with neuronopathic MPS II who qualified for the extension phase of the trial. The investigators were asked to rate the disease status of their patients. Of the 56 patients, 49 (88%) were rated as having disease that was improved/improving, stabilized or slowing progression compared with the expected outcomes with no treatment. Three patients were rated as worsening, while the remaining four patients were considered to have slowing progression or worsening disease. Similar results were demonstrated for patients aged from 3 to under 6 years at baseline, with 33 of 39 patients (85%) rated as having disease that was improved/improving, stabilized or slowing progression. Of the seven patients rated with slowing progression/worsening or worsening disease, five of them had an IDS variant other than missense, while two had a missense class variant. All the assigned improved/improving ratings were in patients receiving idursulfase-IT from the start of the phase 2/3 trial. Moreover, patients under 3 years of age at baseline were all rated as either improved/improving or stabilized disease. In a blinded review of patient profiles, investigators were requested to assign a disease status rating to 18 patients with large IDS deletions; 67% of these patients were rated as improved/improving or stabilized disease.ConclusionsThis qualitative analysis provides a snapshot of clinicians’ considerations when evaluating treatment in patients with neuronopathic MPS II, compared with the expected decline in cognitive function in the absence of treatment. The results highlight the importance of robust assessment tools in treatment evaluation.

Development and validation of survival nomograms in elder triple-negative invasive ductal breast carcinoma patients

ABSTRACT Background We aimed to develop a nomogram to predict the overall survival of elderly patients with Triple-negative invasive ductal breast carcinoma (TNIDC). Research design and methods 12165 elderly patients with nonmetastatic TNIDC were retrieved from the SEER database from 2010 to 2019 and were randomly assigned to training and validation cohorts. Stepwise Cox regression analysis was used to select variables for the nomogram based on the training cohort. Univariate and multivariate Cox analyses were used to calculate the correlation between variables and prognosis of the patients. Survival analysis was performed for high- and low-risk subgroups based on risk score. Results Eleven predictive factors were identified to construct our nomograms. Compared with the TNM stage, the discrimination of the nomogram revealed good prognostic accuracy and clinical applicability as indicated by C-index values of 0.741 (95% CI 0.728–0.754) against 0.708 (95% CI 0.694–0.721) and 0.765 (95% CI 0.747–0.783) against 0.725 (95% CI 0.705–0.744) for the training and validation cohorts, respectively. Differences in OS were also observed between the high- and low-risk groups (p < 0.001). Conclusion The proposed nomogram provides a convenient and reliable tool for individual evaluations for elderly patients with M0_stage TNIDC. However, the model may only for Americans.

Effectiveness, reach, uptake and feasibility of digital health interventions for adults with venous thromboembolism: protocol of a systematic review and meta-analysis

IntroductionPrevention of recurrence after an episode of venous thromboembolism (VTE), and also the post-thrombotic syndrome (PTS), is still a recognised challenge. In this meta-analysis, we will summarise existing evidence to...

Survey on data replication in cloud systems

In a distributed environment, replication is the most investigated phenomenon. Replication is a way of storing numerous copies of the same data at different locations. Whenever data is needed, it will be fetched from the nearest accessible copy, avoiding delays and improving system performance. To manage the replica placement strategy in the Cloud, three key challenges must be addressed. The challenges in determining the best time to make replicas were generated, the kind of files to replicate, as well as the best location to store the replicas. This survey conducts a review of 65 articles published on data replication in the cloud. The literature review examines a series of research publications and offers a detailed analysis. The analysis begins by presenting several replication strategies in the reviewing articles. Analysis of each contributor’s performance measures is conducted. Moreover, this survey offers a comprehensive examination of data auditing systems. This work also determines the analytical evaluation of replication handling in the cloud. Furthermore, the evaluation tools used in the papers are examined. Furthermore, the survey describes a lot of research issues &amp; limitations that might help researchers support better future work on pattern mining for data replication in the cloud.

Quantifying noise effects in optical measures of excited state transport.

Time-resolved microscopy is a widely used approach for imaging and quantifying charge and energy transport in functional materials. While it is generally recognized that resolving small diffusion lengths is limited by measurement noise, the impacts of noise have not been systematically assessed or quantified. This article reports modeling efforts to elucidate the impact of noise on optical probes of transport. Excited state population distributions, modeled as Gaussians with additive white noise typical of experimental conditions, are subject to decay and diffusive evolution. Using a conventional composite least-squares fitting algorithm, the resulting diffusion constant estimates are compared with the model input parameter. The results show that heteroscedasticity (i.e., time-varying noise levels), insufficient spatial and/or temporal resolution, and small diffusion lengths relative to the magnitude of noise lead to a surprising degree of imprecision under moderate experimental parameters. Moreover, the compounding influence of low initial contrast and small diffusion length leads to systematic overestimation of diffusion coefficients. Each of these issues is quantitatively analyzed herein, and experimental approaches to mitigate them are proposed. General guidelines for experimentalists to rapidly assess measurement precision are provided, as is an open-source tool for customizable evaluation of noise effects on time-resolved microscopy transport measurements.