Time Metrics Research Articles

Security analysis and provision of authentication protocol, based on peer-to-peer structure in IOT platform

The Internet of Things technology allows you to transfer data to any asset through communication networks such as the Internet or intranet. One of the most important problems is security, which includes confidentiality, authenticity validation, and completeness. Among security problems, the most important ones are ensuring authenticity and protecting privacy. The elliptic curve encryption algorithm is famous protocols for maintaining privacy and verifying authenticity. Despite the capabilities they have and provide good security against network attacks, they face challenges such as response time, delay in the authentication and authentication process, as well as the amount of memory consumed. Two-factor authentication (2FA) is a security process where users provide two different authentication factors to authenticate themselves. It also provides a higher level of security than authentication methods that rely on single-factor authentication (SFA). This article presents two novel methods for 2FA that use encryption techniques, scramble architecture, and chord architecture. These methods allow for the authentication process to be initiated by both parties involved in the communication. Three scenarios and three metrics of reaction time, memory usage, and connection latency were used to assess the efficacy of the suggested approach. The average reaction time is improved and is 0.012 s when the lengths of the finger table in the chord structure are increased to 10, 15, and 20. The findings show that the suggested approach reduces computing complexity, reaction time, and communication latency. It has an average reaction time of 0.016 s, an average memory use of 30,360 kb, and an average connection latency of 0.042 s.

Evaluating the Safety and Efficacy of Telemedicine Physician Assessments on a Mobile Stroke Unit: Protocol for a Prospective Open-Label Blinded End-Point Randomized Controlled Trial.

Mobile stroke units have been shown to deliver faster patient care and improve clinical outcomes. However, costs associated with staffing limit their use to densely populated cities. Using the Melbourne mobile stroke unit, we aim to evaluate the safety, timeliness, and resource efficiency of a telemedicine model, where the neurologist assesses a patient remotely, via telemedicine, compared with an onboard neurologist model. We hypothesize that, without compromising patient safety, the telemedicine model will provide timely care and superior resource efficiency. Using a prospective, randomized, blinded end-point controlled design, 270 participants consecutively assessed on the Melbourne mobile stroke unit over ≈12 months will be assigned into 2 arms: (1) telemedicine neurologist assessment (intervention) versus (2) onboard assessment (comparator). Enrollment is based on prospectively designated randomized days of neurologist review onboard versus telemedicine. The primary outcome will be the odds that a randomly selected participant in the telemedicine arm will have a better outcome than a randomly selected participant in the onboard arm, measured using a desirability-of-outcome ranking, an outcome measure that includes, in order of importance: (1) safety, (2) scene-to-treatment-decision time metrics, and (3) resource usage. All participants within each arm will be compared with those in the other, resulting in a "win/tie/loss" distribution for telemedicine compared with the onboard model. The study will establish whether use of a telemedicine neurologist delivers superior resource efficiency without compromising patient care. This would enable the broader use of mobile stroke units, particularly relevant to regions with limited access to neurologists, thus improving equity in access to time-critical, lifesaving stroke care. URL: clinicaltrials.gov; Unique Identifier: NCT05991310.

Red Blood Cell (RBC) Antigen Confirmation Workflow – A Positive Impact at an Academic Medical Center

Abstract Introduction/Objective Introduction: Blood group antigens, present on the surface of red blood cells (RBCs), play a crucial role in transfusion medicine. These antigens are recognized serologically and form the basis of RBC phenotyping. Understanding the significance of antigen-negative RBCs is essential for mitigating the risk of hemolytic transfusion reactions and hemolytic disease of the fetus and newborn (HDFN). This study aims to assess the impact of implementing a new RBC antigen confirmation workflow on transfusion service efficiency and patient outcomes. Methods/Case Report Method: The study involved collaboration between our Transfusion Services Department (TS), the Blood Center supplier, and the Apheresis department. A comprehensive review of historical practices and FDA recommendations regarding RBC antigen labeling was conducted. Changes were implemented to streamline antigen confirmation testing and labeling processes. The impact on TS workload, turnaround time, and patient care metrics was evaluated. Results (if a Case Study enter NA) Results: Implementation of the new RBC antigen confirmation workflow led to a significant reduction in antigen confirmation tests performed by TS, with a 607% decrease observed from 2020 to 2023. Concurrently, the workload for reference lab workups increased by 337% over the same period. This shift in workload distribution allowed TS staff to focus more on patient reference workup cases and case review. The improved workflow efficiency resulted in enhanced turnaround times for providing patients with antigen-negative RBCs, ultimately improving the patient experience. Conclusion Conclusion: The adoption of the new RBC antigen confirmation workflow has resulted in compliance with FDA labeling requirements, efficient utilization of TS staff resources, and decreased turnaround times for blood delivery. These improvements have positively impacted patient care by ensuring timely access to compatible blood products. Future steps include developing reports to track turnaround time for patients with special blood product needs and continuing collaboration with the blood supplier and the Apheresis department to optimize inventory management and transfusion processes.

Automotive workers: the role of coordinative and conditional abilities as effectiveness wellness indicator.

Noncommunicable diseases are on the rise due to sedentary and unhealthy lifestyles. The World Health Organization (WHO) and the American College of Sports Medicine (ACSM) recommend maintaining a healthy diet and engaging in regular physical activity, particularly in the workplace. Prolonged and repetitive work tasks can result in extended sick leave and decreased productivity while at work. Therefore, it is important to identify predictive factors that can act as indicators of the health status of employees. Utilizing motor abilities assessment tests can help to identify health issues at an early stage. Promoting preventive health measures is crucial for addressing chronic diseases and enhancing overall occupational well-being. The purpose of the study was to characterize workers' motor abilities and fitness levels and identify potential indicators. A total of 605 workers participated in this study, including 529 male participants with a height of 176 ± 0.09 cm and a body mass of 75.9 ± 14.1 kg and 77 female participants with a height of 162 ± 0.11 cm and an average body mass of 58.9 ± 11.1 kg. These individuals were enrolled during an Italian automotive corporation's mandatory annual medical check-up. The participants were categorized into three groups based on their occupational roles: blue-collar, manager, and white-collar groups. The participants underwent motor abilities assessment tests for upper-limb strength, trunk flexibility, and reaction time. The blue-collar group reported the best results in upper-limb strength (93.3 kgf ± 18.60), but had the worst results in flexibility (21.7 cm ± 7.90), total reaction time (58.8 s ± 4.74); and average intermedium (0.68 ms ± 0.11). The white-collar group reported the best result in flexibility (23.7 cm ± 8.94) and reaction time (48.5 s ± 4.38; 0.64 ms ± 0.09). Despite being frequently used to assess health status, handgrip measurements may not provide accurate differentiations because of the common use of blue-collar workers for tasks that require upper-limb strength. In contrast, reaction time metrics appear more reliable and discriminative in evaluating a worker's physical fitness.

An Algorithm for Clustering with Confidence-Based Must-Link and Cannot-Link Constraints

We study here the semisupervised k-clustering problem where information is available on whether pairs of objects are in the same or different clusters. This information is available either with certainty or with a limited level of confidence. We introduce the pair-wise confidence constraints clustering (PCCC) algorithm, which iteratively assigns objects to clusters while accounting for the information provided on the pairs of objects. Our algorithm uses integer programming for the assignment of objects, which allows us to include relationships as hard constraints that are guaranteed to be satisfied or as soft constraints that can be violated subject to a penalty. This flexibility distinguishes our algorithm from the state of the art, in which all pair-wise constraints are considered hard or all are considered soft. We developed an enhanced multistart approach and a model-size reduction technique for the integer program that contribute to the effectiveness and efficiency of the algorithm. Unlike existing algorithms, our algorithm scales to large-scale instances with up to 60,000 objects, 100 clusters, and millions of cannot-link constraints (which are the most challenging constraints to incorporate). We compare the PCCC algorithm with state-of-the-art approaches in an extensive computational study. Even though the PCCC algorithm is more general than the state-of-the-art approaches in its applicability, it outperforms the state-of-the-art approaches on instances with all hard or all soft constraints in terms of both run time and various metrics of solution quality. The code of the PCCC algorithm is publicly available on GitHub. History: Accepted by Ram Ramesh, Area Editor for Data Science and Machine Learning. Funding: The research of D. S. Hochbaum was supported by the AI Institute NSF Award [Grant 2112533]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0419 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0419 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Influence of Stroke-Onset Location on the Efficacy of Endovascular Thrombectomy: Comparison of Outcomes between In-Hospital versus Community-Onset Strokes.

Previous studies have suggested that patients experiencing an in-hospital stroke may face delays in treatment and worse outcomes compared with patients with community-onset strokes. However, most studies occurred when IV thrombolysis was the primary treatment. This study aimed to examine the outcomes of patients experiencing an in-hospital stroke in the endovascular thrombectomy era. This was a single-center retrospective cohort study of patients older than 18 years of age with acute ischemic stroke treated with endovascular thrombectomy within 12 hours of stroke onset from January 1, 2015, to April 30, 2021. Patients were classified into 2 groups: in-hospital strokes and community-onset strokes. We compared the time metrics of stroke care delivery, the rate of successful reperfusion, and functional outcome as scored using the mRS score at 90 days (favorable outcome was defined as mRS 0-2). Differences in proportions were assessed using the Fisher exact and χ2 tests as appropriate. For continuous variables, differences in medians between groups were evaluated using Mann-Whitney U tests. A total of 676 consecutive patients were included, with 69 (10%) comprising the in-hospital stroke group. Patients experiencing in-hospital stroke were more likely to have diabetes (36% versus 18%, P = .02) and less likely to receive thrombolysis (25% versus 68%, P < .001) than those in the community-onset stroke group, but they were otherwise similar. Patients with in-hospital stroke had significantly faster overall time metrics, most notably from stroke recognition to imaging (median, 70 [interquartile range, 38-141] minutes versus 121 [74-228] minutes, P < .001). Successful recanalization was achieved in >75% in both groups (P = .39), with a median NIHSS score at discharge of <4 (P = .18). The 90-day mRS was similar in both groups, with a trend toward higher in-hospital mortality in the in-hospital stroke group (P = .06). Patients with in-hospital stroke had shorter workflow delays to initiation of endovascular thrombectomy compared with their community counterparts but with a similar rate of successful recanalization and clinical outcomes. Most important, 90-day mortality and mRS scores were equivalent between in-hospital stroke and community-onset stroke groups.

The Impact of the Pandemic of COVID-19 on the Head Injury Fast-Track System and Surgical Outcome

Abstract Objective This study aims to evaluate the impact of the coronavirus disease 2019 (COVID-19) pandemic on the head injury fast-track system and surgical treatment outcomes. Materials and Methods A retrospective review was conducted on patients who underwent emergency neurological procedures according to the head injury fast-track system. Data from April 2018 to April 2020 (pre-COVID) were compared with data from May 2020 to May 2022 (during COVID). Results The analysis comprised 128 patients in the prepandemic group and 119 patients in the pandemic group, with 5 patients diagnosed with COVID infection during the pandemic. Acute subdural hematoma resulting from motorcycle accidents was the most common diagnosis in both groups (56.3 and 47.5%, respectively). The initial Glasgow coma scale (GCS) score was significantly lower during the pandemic compared to the prepandemic period (p = 0.025). Time metrics in the emergency department, including door to computed tomography (CT), emergency room (ER) exit, and incision times, were significantly longer in the pandemic group (p &lt; 0.05). However, there were no statistically significant differences in in-hospital mortality rates (25.8 and 17.7%, respectively; p = 0.12) or the percentage of patients with a favorable functional outcome (Glasgow outcome scale ≥4). At 1 month, a favorable functional outcome was observed in 51.6% of prepandemic patients and 57.1% of pandemic patients (p = 0.69), while at 6 months, the percentages were 56.8 and 64.5%, respectively (p = 0.23). Conclusions Our study revealed significant delays in hospital processes for head injuries during the COVID-19 pandemic. However, we found no significant impact on mortality rates or functional outcomes of patients.

Feasibility of 10-Minute Arrival Time to Departure Time Metric for STEMI Patients

Objectives Delays in reperfusion treatment in ST-elevation myocardial infarction (STEMI) patients leads to higher morbidity and mortality. Previous reports for Helicopter Emergency Medical Services (HEMS) suggests a 10-minute skid-to-skid (arrival to departure) time to achieve appropriate reperfusion times. However, there is no published data on whether this goal is achievable for a HEMS service. This study aims to see if a midwestern critical care service can consistently achieve a 10-minute helicopter skid-to-skid time or ground critical care service arrival to departure time. Further, comparing this metric between ground and helicopter transportations will help evaluate the ideal transportation method to optimize time to percutaneous intervention (PCI). Methods This was a retrospective chart review utilizing 10 years of data from our ground and HEMS program to assess whether a 10-minute arrival to departure time for STEMI patients could be achieved. Patients included were at least 18 years of age and were transported from the referring facility for further STEMI management. Wilcoxon rank sum test and Chi-square tests were used to evaluate data between helicopter and ground services. Results Included in the study were 686 patients, 608 by helicopter transport and 78 by ground transport. The median arrival to departure time was 14 min (IQR = 5) for helicopter patients and 13 min (IQR = 6) for ground patients. There was not a statistically significant difference in this metric for STEMI patients transported by helicopter versus ground. A statistically significant difference, though, existed between helicopter and ground transports among percent with times less than or equal to 10 min versus percent times greater than 10 min, X2 = 5.46, df = 1, p = 0.02. Two referring facilities had statistically significant differences in median arrival to departure times. Conclusions Our study found that a median EMS arrival to departure time of 10 min to transport STEMI patients was not consistently achieved via either helicopter or ground transportation.

The Integration of AI and Machine Learning in Supply Chain Optimization: Enhancing Efficiency and Reducing Costs

One of the biggest issues today is the increasing intricacy of supply chain networks and supply chain networks becoming more global. Following is the research paper on supply chain management accompanying the integration of AI &amp; ML for effectiveness &amp; efficiency &amp; reduction of cost impacts. The purpose of the research is to assess the effectiveness of adoption of Artificial Intelligence and Machine Learning tools based on predictive analytics, automation, and real-time decision models with supply chain management tendencies in demand forecasting, inventory control, and logistics. In line with the research design that is mixed method, the data were obtained from high-impact case studies and industry reports with further support from the literature review. The usefulness analysis of AI and ML was conducted in line with the supply chain performance measures that include lead time, cost and system metrics for the actual implementation. The results suggest that the application of AI and ML leads to the key performance improvement in companies, such as an average of 20% decrease in operational costs and 15% shorter delivery times. The study will also provide a new understanding of the real world incorporation of AI and ML in supply chain and a path forward in the literature and practice. These technologies reveal the development prospect of how these supply chains can be rebuilt to be more robust as well as flexible.

Beyond Simple Tapping: Is Timed Body Movement Influenced When Balance Is Threatened?

The tapping paradigm offers valuable insights into movement timing; however, it simplifies mechanics by minimizing force, restricting motion, and relying on a clear contact endpoint. Thus, it may not fully capture the complexity of larger-scale multi-segmental (or single-segment) timed body movements. The aim of this study was to extend beyond the tapping paradigm by examining the timing of two large-scale movements commonly performed in physical fitness or rehabilitation modalities, with varying inherent balance threats: two-legged squatting (low balance threat) and standing hip abduction (higher balance threat) paced by a metronome set at the participants’ preferred tempo (N = 39, all physically active). In synchronization with the metronome audio signal, the trunk and shank angular velocities were also recorded to extract the entrainment, synchronization, and pace stability metrics. Paired t-tests indicated similar entrainment in both movements (p &gt; 0.05 for IRI match) but significant differences in timing metrics’ manifestations (p ≤ 0.05, standing hip abduction: 50% greater IRI error, 30% lower synchronization error, 2.6% units lower pace stability). The similar entrainment but different synchronization error and pace stability highlight a complex timing interplay between balance threat/challenges and movement complexity concerning the two large-scale movements employed in physical fitness and rehabilitation modalities.

Cell cycle expression heterogeneity predicts degree of differentiation.

Methods that predict fate potential or degree of differentiation from transcriptomic data have identified rare progenitor populations and uncovered developmental regulatory mechanisms. However, some state-of-the-art methods are too computationally burdensome for emerging large-scale data and all methods make inaccurate predictions in certain biological systems. We developed a method in R (stemFinder) that predicts single cell differentiation time based on heterogeneity in cell cycle gene expression. Our method is computationally tractable and is as good as or superior to competitors. As part of our benchmarking, we implemented four different performance metrics to assist potential users in selecting the tool that is most apt for their application. Finally, we explore the relationship between differentiation time and cell fate potential by analyzing a lineage tracing dataset with clonally labelled hematopoietic cells, revealing that metrics of differentiation time are correlated with the number of downstream lineages.

Abstract A086: Racial and ethnic disparities in prostate cancer survival in the Multiethnic Cohort Study (MEC)

Abstract Background: Prostate cancer (PCa) survival has improved over the past 20 years due to advancements in treatment and screening. However, racial and ethnic disparities in PCa survival remain. Studying population differences in PCa survival may help identify underlying contributing factors. Methods: We conducted survival analyses among 10,651 African American, Latino, Native Hawaiian, Japanese American, and non-Hispanic White (NHW) men with an incident PCa diagnosis since 1993 who were part of the Multiethnic Cohort Study. Sub- hazard ratios (SHRs) and 95% confidence intervals (CI) were estimated using the Fine and Grey Subdistribution Hazards Model to account for competing risks in PCa-specific mortality, with age since diagnosis as the time metric. Multivariable models included age at PCa diagnosis, Gleason score, stage at diagnosis, and baseline values of education, initial treatment (radiation, surgery, hormone therapy, chemotherapy, or no active treatment), diabetes history, physical activity, BMI, smoking status, and dietary intakes linked to PCa progression (tomatoes, whole milk, fatty fish, processed meat, saturated fat, and alcohol). We also performed stratified analyses by tumor stage (localized or regional/distant) and Gleason score (≤7 or &amp;gt;7). Associations were considered statistically significant at P &amp;lt; 0.05. Results: Of 10,651 men diagnosed with PCa over 27 years of follow-up (mean duration, 8.4 years), 1,324 (12.4%) died of PCa. Those with lower Gleason scores were less likely to die than those with higher scores (6.8% of men with Gleason score ≤7 vs 21.3% of men with Gleason score &amp;gt;7, p&amp;lt;0.001). Likewise, men with localized disease were less likely to die than men with regional/distant disease (7.5% of men with localized disease vs. 29.2% of men with regional/distant disease, p&amp;lt;0.001). Japanese Americans had significantly lower mortality compared with NHWs (SHR=0.63, 95% CI:0.51, 0.79, p&amp;lt;0.001), consistently observed across stage and Gleason score: localized (SHR=0.64, 95% CI: 0.48, 0.87, p&amp;lt;0.001); regional/distant (SHR=0.63, 95% CI: 0.45, 0.88, p=0.01); Gleason ≤7 (SHR=0.61, 95% CI: 0.44, 0.86, p&amp;lt;0.001); and Gleason score &amp;gt;7 (SHR=0.59, 95% CI: 0.43, 0.79, p&amp;lt;0.001). PCa-specific mortality was significantly higher among African Americans compared to NHWs (SHR=1.31, 95% CI: 1.08-1.60, p=0.01). This difference was more pronounced for less aggressive tumors: localized (SHR=1.50, 95% CI: 1.15, 1.96, p&amp;lt;0.001); Gleason ≤7 (SHR=1.28, 95% CI: 0.95, 1.71, p=0.11). Lastly, we did not observe significant differences in PCa mortality for Latinos and Native Hawaiians compared to NHWs overall or by disease severity. Conclusions: Japanese American have ∼40% lower and African Americans have ∼30% higher PCa-specific mortality relative to NHWs, even after accounting for lifestyle/behavioral factors, stage, Gleason score, and treatment. Further investigations are needed to explore social and cultural factors that impact care as well as tumor-based characteristics that may vary between populations to understand these disparities in PCa mortality. Citation Format: Wei Xiong, Fei Chen, Ann S. Hamilton, David Conti, Raymond Hughley, David Bogumil, Anqi Wang, Song-Yi Park, Peggy Wan, Lynne R. Wilkens, Loïc Le Marchand, Brenda Y. Hernandez, Christopher A. Haiman. Racial and ethnic disparities in prostate cancer survival in the Multiethnic Cohort Study (MEC) [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A086.

Pre- and post-skeletal muscle biopsy quantitative magnetic resonance imaging reveals correlations with histopathological findings.

Quantitative muscle magnetic resonance imaging (MRI) is a promising non-invasive method in the diagnostic workup as well as follow-up of neuromuscular disorders. The aim of this study was to correlate quantitative MRI (qMRI) parameters to histopathological changes in skeletal muscle tissue and thus to verify the data from our pilot study. Twenty-six patients (eight females, 46.4 ± 15.1 years) were examined within 72 h before and within 24 h after a skeletal muscle biopsy using quantitative muscle MRI. Post-biopsy MRI was employed to pinpoint the exact localization of the biopsy. qMRI parameters including fat fraction, water T2 relaxation time and diffusion metrics including fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were extracted from the localization of the biopsy and correlated with histopathological findings. Additionally, three different segmentation masks were applied to the qMRI dataset, to evaluate whether the whole muscle represents the exact biopsy location. Fat fraction and water T2 relaxation time in qMRI correlated significantly with the fat fraction in the muscle biopsy and histopathological inflammatory markers. Fractional anisotropy correlated with the quantity of type 2 fibres, whilst mean diffusivity correlated with p62. No differences were found using different segmentation masks in qMRI. In this follow-up study, the results from our previous study were verified regarding the correlation of qMRI parameters with histopathological features in muscle biopsies, indicating that qMRI serves as a suitable non-invasive method in the follow-up of patients with neuromuscular disorders. If post-biopsy MRI is not available, whole muscle volume can be used for histopathological correlations.

Comparison between "Mothership" and "Drip and Ship" models in the management of acute ischemic strokes eligible for mechanical thrombectomy in the Charleroi area, Belgium

BackgroundIn the management of acute ischemic stroke with large vessel occlusion (LVO-AIS), current data are conflicting as to whether a mothership model of management (MS) is associated with better functional recovery than a drip-and-ship model (DS). MethodFiles from LVO-AIS patients treated with MT at CHU Charleroi were analyzed between 01/01/2017 and 12/31/2022. Consecutive patients with a LVO-AIS of the anterior circulation and a prestroke modified Rankin Scale (mRS) ≤2 were included. The study's primary endpoint was the functional independence, defined as a mRS of 0-2 at 3 months post-stroke. Times metrics of MT and thrombolysis application, safety outcome including symptomatic intracranial hemorrhage and death were recorded. We conducted similar analyses by dividing DS patients, depending of their transfer time (less or >20 min). Logistic regression was used to assess if differences in baseline characteristics affected the primary outcome. Results366 patients were included: 229 in the DS group and 137 in the MS group. Demographic data showed a higher rate of tobacco use and lower functional status prestroke in the MS population. The MS group demonstrated better performance in time metrics related to thrombolysis and MT administration. The proportion of patients achieving an mRS of 0-2 at 3 months was similar in the DS and MS groups (50.22 % vs. 48.17 %, p = 0.706). The same conclusions were drawn from the subgroup analysis. Logistic regression analysis showed no impact of baseline characteristic differences on the primary outcome. ConclusionDespite faster access to MT in the MS model, our study did not find any significant differences in functional recovery at three months post-stroke between the MS and DS management models. Our data suggest further that the prestroke health status was an important factor influencing functional outcomes after LVO-AIS.

Workflow Trace Profiling and Execution Time Analysis in Quantitative Verification

Workflows orchestrate a collection of computing tasks to form a complex workflow logic. Different from the traditional monolithic workflow management systems, modern workflow systems often manifest high throughput, concurrency and scalability. As service-based systems, execution time monitoring is an important part of maintaining the performance for those systems. We developed a trace profiling approach that leverages quantitative verification (also known as probabilistic model checking) to analyse complex time metrics for workflow traces. The strength of probabilistic model checking lies in the ability of expressing various temporal properties for a stochastic system model and performing automated quantitative verification. We employ semi-Makrov chains (SMCs) as the formal model and consider the first passage times (FPT) measures in the SMCs. Our approach maintains simple mergeable data summaries of the workflow executions and computes the moment parameters for FPT efficiently. We describe an application of our approach to AWS Step Functions, a notable workflow web service. An empirical evaluation shows that our approach is efficient for computer high-order FPT moments for sizeable workflows in practice. It can compute up to the fourth moment for a large workflow model with 10,000 states within 70 s.

Assessment of hybrid machine learning models for non-linear system identification of fatigue test rigs

The prediction of system responses for a given fatigue test bench drive signal is a challenging problem, since highly dynamic loads from measurement campaigns must be reproduced accurately. Linear frequency response function models are commonly used for this system identification task, but energy intensive experimental iterations are required to account for system non-linearities. Two novel hybrid modeling strategies are suggested, which augment existing approaches using non-linear Long Short-Term Memory networks. These are trained and deployed on short subsequences of measurement data and recombined using a windowing technique, which enables their application to measurement data with high sampling rates. In addition to fatigue test bench commissioning, these hybrid models can also be employed in the field of virtual sensing. The approach is tested using non-linear experimental data from a servo-hydraulic test rig and this dataset is made publicly available. A variety of metrics in time and frequency domains, as well as fatigue strength under variable amplitudes, are employed in the evaluation. It is shown, that hybrid models can successfully use frequency response function models as a linear baseline estimate, which is further improved by Long Short-Term Memory networks to enable non-linear predictions.

Real-World Implementation of Simulation-Free Radiation Therapy (SFRT-1000): A Propensity Score-Matched Analysis of 1000 Consecutive Palliative Courses Delivered in Routine Care.

The feasibility of simulation-free radiation therapy (SFRT) has been demonstrated but information regarding its routine care impact and scalability is lacking. In this single-institution, retrospective cohort study, all patients receiving palliative radiation therapy at an Australian tertiary cancer center were eligible for consideration of SFRT unless mask immobilization, a stereotactic technique, or a definitive dose was indicated. Coprimary endpoints were SFRT utilization, impact on consultation-to-RT time, and on-couch treatment duration. Timing metrics were compared with a contemporary local cohort that received simulation-based palliative radiation therapy using unadjusted Wilcoxon rank-sum tests and a propensity score-matched regression. Electronic patient-reported outcomes captured 2-week toxicity and pain response. Between April 2018 and February 2024, 2849 palliative radiation courses were delivered, of which 1904 were eligible. Of the 1904 courses, 1000 (52.5% SFRT utilization) received SFRT, including 668 using intensity-modulated radiation therapy/volumetric-modulated arc therapy. A total of 788 individual patients received SFRT and the median age was 71 years (IQR, 61-80) with 59% being male and 42% being Eastern Collaborative Oncology Group 2-4. SFRT utilization increased from 41% to 54% between years 2018-2019 and 2022-2024. SFRT reduced median consultation-to-RT time from 7.0 to 5.1 days (P < .0001) corresponding to an adjusted average treatment effect in the treated of -2.1 days (95% CI, -2.8 to -1.3). SFRT increased median on-couch treatment duration from 17.8 to 20.5 minutes (P < .0001; adjusted average treatment effect in the treated 2.6 minutes, 95% CI, 1.3-3.9). Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events grade 3 acute toxicity was 9% and at 4 weeks after RT, patients with moderate/severe pain at baseline (≥5/10) had a mean pain reduction of 3.5 points (7.1-3.6; P < .0001). Using widely available technologies, the SFRT-1000 cohort demonstrates routine care scalability with patient-centered and workflow benefits. SFRT is an attractive new paradigm implementable in most settings following adaptation to local requirements. Thus, SFRT opens new avenues to potentially improve access to palliative RT, which remains a global area of need.

The effect of hydrological variability on stepped fishways

River systems are highly dynamic, affecting all associated structures and their derived uses. This is particularly relevant for applications such as hydropower production and other water abstractions. This dynamic nature also extends to mitigation measures like fishways, which are vital for reducing the impact of river fragmentation on fish populations. Fishways must be designed to balance biological and hydraulic fish requirements, needing adaptability to varying boundary conditions. This study examines the effect of hydrological variability on fish passage through fishways, particularly for the Iberian barbel (Luciobarbus bocagei). We hypothesized that hydrological scenarios can significantly affect upstream fish passage. To test this, we conducted laboratory and field studies, assessing fish movement under different boundary conditions. We compared passage rates, time metrics, and their correlations with the evolution of fishway hydraulics, and employed survival analysis to determine biometric limits. Our findings show that hydrological changes markedly influenced fish passage rates and timings, producing fish size selection and highlighting the impact of factors such as maximum velocity and power dissipation in the studied metrics. These insights underline the necessity of incorporating hydrological variability into fishway design and management, enhancing their effectiveness for fish conservation in river ecosystems, particularly under growing climatic uncertainties. This research underscores and discusses the need for comprehensive, long-term hydrodynamic studies in fishway assessment and design, advocating for adaptive management strategies to accommodate environmental changes.

Enhancing sustainability in the production of palm oil: creative monitoring methods using YOLOv7 and YOLOv8 for effective plantation management

The You Only Look Once (YOLO) deep learning model iterations—YOLOv7–YOLOv8—were put through a rigorous evaluation process to see how well they could recognize oil palm plants. Precision, recall, F1-score, and detection time metrics are analyzed for a variety of configurations, including YOLOv7x, YOLOv7-W6, YOLOv7-D6, YOLOv8s, YOLOv8n, YOLOv8m, YOLOv8l, and YOLOv8x. YOLO label v1.2.1 was used to label a dataset of 80,486 images for training, and 482 drone-captured images, including 5,233 images of oil palms, were used for testing the models. The YOLOv8 series showed notable advancements; with 99.31 %, YOLOv8m obtained the greatest F1-score, signifying the highest detection accuracy. Furthermore, YOLOv8s showed a notable decrease in detection times, improving its suitability for comprehensive environmental surveys and in-the-moment monitoring. Precise identification of oil palm trees is beneficial for improved resource management and less environmental effect; this supports the use of these models in conjunction with drone and satellite imaging technologies for agricultural economic sustainability and optimal crop management.

Thrombolysis with tenecteplase in acute ischaemic stroke in a tertiary care setting in Sri Lanka: A retrospective study

Introduction: Alteplase (ALT) is the standard thrombolytic treatment in acute ischaemic stroke (AIS). Tenecteplase (TNK) is proven to be effective in acute coronary syndrome, is relatively cheap, widely available and can easily be given as a single intravenous (IV) bolus. Despite evidence for its use, there is equivocal guidance for the use of TNK in AIS. On the background of a global reduction in stroke admissions, treatment interventions and prolonged treatment time metrics due to the COVID-19 pandemic, this study highlights the experience with TNK in a tertiary care setting in Sri Lanka, during the pandemic.Objectives: To describe the outcomes at 48 hours among stroke patients who underwent thrombolysis with TNK at District General Hospital Hambantota, Sri Lanka over a period of one year.Methods: We retrospectively reviewed records of adults with AIS thrombolysed with 0.25 mg/kg TNK. The National Institutes of Health Stroke Scale (NIHSS) was assessed on admission and at 24-hours following treatment. Patients were observed for 48-hours for potential adverse events.Results: We thrombolysed 20 consecutive patients over one-year. The baseline mean NIHSS was 9.7 (standard deviation (SD)=4.4; range 4-22), and the 24h-post thrombolysis mean NIHSS was 6.0 (SD=7.3; range 0-28). Seventy percent (n=14) showed an improved NIHSS of at least 1-point after thrombolysis (mean difference=3.7; SD=6.46), and 55%(n=11) displayed a major clinical improvement (change in NIHSS ≥ 4). Ten percent (n=2) developed major adverse effects (one intra-cranial haemorrhage; one haemorrhagic transformation). There were no deaths.Conclusions: TNK 0.25mg/kg for the treatment of AIS appeared efficacious and safe in our case series. The limitation in this study was the low number of patients who underwent thrombolysis during the study period, as a probable effect of the COVID-19 pandemic. Thrombolysis with TNK could be a cost-effective alternative to alteplase in resource-limited South Asian settings.