Time Schedule Research Articles

Heterogeneous system list scheduling algorithm based on improved optimistic cost matrix

In heterogeneous computing systems, efficient task-scheduling methods are paramount for enhancing computational performance. However, the existing algorithm exhibits certain deficiencies, notably its oversight of load balancing concerns and inadequate emphasis on the out-degree property of tasks. To address these issues, a novel list scheduling algorithm is proposed, Average Earliest Finish Time (AEFT), which proficiently allocates task flows onto heterogeneous processors. The AEFT algorithm primarily consists of two key stages: (1) prioritizing tasks to determine the distribution of task priorities and (2) assigning optimal processors for tasks with given priorities. By leveraging its specific topology, the AEFT algorithm minimizes the scheduling length of task flows. Simultaneously, a prediction mechanism in determining task prioritization and selecting processors stages is proposed to reduce the scheduling time of task flows. In addition, in the processor selection stage, AEFT algorithm considers the out-degree characteristics of tasks, ameliorating situations of processor load imbalance. The AEFT algorithm demonstrates superior performance compared to prior list scheduling algorithms concerning makespan, speedup, and the percentage of occurrences of better solutions, as evidenced by experiments conducted on randomly generated and real-application graphs. Specifically, for t tasks and p processors, the AEFT algorithm achieves a time complexity of O(t2p).

Project Acceleration Analysis Using the Crashing Method with The Alternative of Additional Labor and Additional Working Hours in Drainage Work

Project work delays often occur due to differences in site conditions, design changes, weather influences, and planning errors. The problem faced is the project duration, where if the project duration is accelerated or crashes, there will be several options to cut the project duration. This is the problem that becomes the topic of the thesis/journal, namely "Analysis of Project Acceleration with the Crashing Method with Alternatives for Adding Manpower and Additional Working Hours in Drainage Works". The author uses the primary method, with sources of RAB, Time Schedule, working drawings and analysis of city unit prices. As well as secondary research methods with sources, from relevant books, and project data such as price lists and wages. From the results of the study it can be concluded that the total wages of workers under normal conditions is IDR. 16,864,000.00 with the duration of project work for 30 working days. From the results of the analysis in this study, the total wages of workers with alternative labor additions of IDR. 19,672,000.00 with the duration of project construction work for 25 working days or 15.15% faster than the normal duration. Meanwhile, the total wage for workers with the alternative of additional working hours (overtime) is IDR. 25,052,300.00 with the duration of the project construction work for 25 working days or 15.15% faster than the normal duration. A more economical alternative to completing the project is the addition of manpower because it saves IDR. 2,228,000.00 from additional working hours (overtime), from normal wages.

Sistem Informasi Penyewaan Arena Futsal dan Alarm Permainan dengan Menggunakan Laravel Berbasis Web di Kota Kraksaan Kabupaten Probolinggo

The advancement of information technology has transformed the management of futsal businesses, simplifying processes such as court reservations, schedule management, payments, and providing automated notifications to users through a game alarm feature. This system also includes an automatic reporting feature that generates accurate and real-time rental summaries. This study aims to design and implement a web-based futsal rental information system using the Laravel framework, featuring a game alarm to enhance management efficiency. The system is designed to address limitations in futsal rental management and time scheduling, as well as simplify the reporting process, which is currently done manually. The system development follows the waterfall model, which includes requirements analysis, system design, implementation, testing, and maintenance stages. The results show that the implementation of this web-based system significantly improves the efficiency of futsal court management in Kraksaan City, particularly in managing game time, rental reporting, and real-time financial management. The game alarm feature effectively reduces time conflicts between users, while the automatic reporting feature helps business owners track revenue and rental trends easily. The implementation of this system is expected to improve service quality and provide a better user experience, while assisting business owners in managing their operations more efficiently.

A Robust Human–Machine Framework for Project Portfolio Selection

Based on the project portfolio selection and scheduling problem (PPSS), the development of a systematic and scientific project scheduling plan necessitates comprehensive consideration of individual preferences and multiple realistic constraints, rendering it an NP-hard problem. Simultaneously, accurately and swiftly evaluating the value of projects as a complex entity poses a challenging issue that requires urgent attention. This paper introduces a novel qualitative evaluation-based project value assessment process that significantly reduces the cost and complexity of project value assessment, upon which a preference-based deep reinforcement learning method is presented for computing and solving project subsets and time scheduling plans. This paper first determines the key parameter values of the algorithm through specific examples. Then, using the method of controlling variables, it explores the sensitivity of the algorithm to changes in problem size and dimensionality. Finally, the proposed algorithm is compared with two classical algorithms and two heuristic algorithms across different instances. The experimental results demonstrate that the proposed algorithm exhibits higher effectiveness and accuracy.

Improving prediction accuracy of open shop scheduling problems using hybrid artificial neural network and genetic algorithm

Scheduling issues are typically classified as constrained optimization problems that examine the allocation of machines and the sequence in which tasks are processed. Regarding the existence of one machine, identification of works processing sequence forms a complete time schedule. Therefore, following a review of previous works, the goal of the present study is designing a mathematical model for open shop scheduling (OSS) problems using different machines aiming at minimizing the maximum time required to complete the works using an artificial neural network (ANN) and genetic algorithm (GA). The research data were driven from a Shoe company carried out between the years 2019 and 2020. The GA and ANN methodologies were employed to analyze and forecast the scheduling of activities within the shoe manufacturing sector. The findings indicated that the probability associated with the third population of the GA was 0.15. Furthermore, an examination of the average values of standard error revealed that the neural network model outperformed in terms of predictive accuracy. The estimated minimum time necessary for task completion, as determined by the neural network, was calculated to be 0.96699, facilitating an optimal condition for meeting the established objectives.

Applying Ant Colony Optimization to Reduce Tram Journey Times

Nature-inspired algorithms allow us to solve many problems related to the search for optimal solutions. One such issue is the problem of searching for optimal routes. In this paper, ant colony optimization is used to search for optimal tram routes. Ant colony optimization is a method inspired by the behavior of ants in nature, which as a group are able to successfully find optimal routes from the nest to food. The aim of this paper is to present a practical application of the algorithm as a tool for public transport network planning. In urban public transport, travel time is crucial. It is a major factor in passengers’ choice of transport mode. Therefore, in this paper, the objective function determining the operation of the algorithm is driving time. Scheduled time, real time and theoretical time are analyzed and compared. The routes are then compared with each other in order to select the optimal solution. A case study involving one of the largest tramway networks in Poland demonstrates the effectiveness of the nature-inspired algorithm. The obtained results allow route optimization by selecting the route with the shortest travel time. Thus, the development of the entire network is also possible. In addition, due to its versatility, the method can be applied to various modes of transport.

Defining the Treatment Window: Early Versus Late Pulsed Dye Laser Therapy for Posttraumatic and Surgical Scars in Asian Patients

ABSTRACTObjectivesThis retrospective study evaluates the effectiveness of pulsed dye laser (PDL) treatment in early versus late treatment groups for traumatic or postoperative scars. The study aims to determine the threshold between early and late treatment. Additionally, it investigates factors that may influence wound healing outcomes.MethodsThe medical records of 147 patients who underwent PDL treatment at our institution between January 2018 and December 2022 were retrospectively reviewed. Inclusion criteria were patients receiving PDL treatment for traumatic or postoperative scars. Out of these patients, we selected those who were willing to receive telephone interviews or re‐visit at a scheduled time. Eventually, 52 participants were included in our study. A standardized questionnaire was administered to all participants during telephone interviews, encompassing inquiries regarding their medical history, treatment experiences, and the patient component of the Patient and Observer Scar Assessment Scale. Among the enrolled patients, 38 were contacted and interviewed via telephone, while the remaining 14 patients attended follow‐up visits where photographs of their current skin condition were captured. The pretreatment and latest follow‐up photographs obtained from the clinical database were independently scored in a blinded manner by two dermatologist reviewers using both the Vancouver Scar Scale and the Manchester Scar Scale.ResultsAmong the 52 patients, 43 (82.7%) were successfully treated with good response. The correlation coefficients between week‐to‐treatment initiation and posttreatment MSS and VSS among patients with good response were 0.50 (p < 0.001) and 0.46 (p = 0.002), respectively. Given these findings, we established a treatment initiation threshold of 10 weeks, distinguishing patients into early and late treatment groups. The early treatment group showed borderline significantly lower posttreatment MSS and VSS scores than the late treatment group (MSS: 7.5 ± 2.1 vs. 9.3 ± 2.5, p = 0.011; VSS: 2.8 ± 2.0 vs. 4.5 ± 2.3, p = 0.011). Furthermore, both MSS and VSS of posttreatment showed significantly greater improvement in the early treatment group (4.4 ± 1.6 vs. 3.2 ± 1.9; p = 0.03 and 3.8 ± 1.8 vs. 2.8 ± 1.4; p = 0.04).ConclusionsEarly intervention using a PDL within 10 weeks post‐injury achieved better outcomes in treating traumatic and postoperative scars based on both clinical and patient opinions.

Enhancing Tuberculosis Treatment Adherence: Evaluating the Efficacy of the Support for Treatment Adherence and Medication Protocols (STAMP) Device for Automatic Dispensing and Real-Time Medication Monitoring.

Tuberculosis (TB) remains a significant global health challenge, necessitating strict adherence to medication for successful treatment and prevention of drug resistance. Adherence to a regular medication regimen is crucial in TB management, yet achieving high adherence rates among patients proves challenging due to various factors including forgetfulness, complexity of treatment schedules, and socioeconomic barriers. This study explores the potential of an automatic medicine dispenser (AMD) anchored system to improve medication adherence among TB patients and evaluates its impact through monitoring and feedback mechanisms. The AMD integrates advanced technology to dispense medications at scheduled times, thereby reducing reliance on patient memory and manual adherence tracking. This device is complemented by a monitoring system where healthcare mentors oversee adherence data in real-time via a web-linked dashboard. Such real-time monitoring enables mentors to promptly intervene in cases of non-adherence, offering personalized support and guidance tailored to individual patient needs. The study employs a mixed-methods approach, combining quantitative analysis of adherence rates derived from the AMD anchored system with qualitative data from patient surveys. These surveys gather insights into patient experiences and perceptions regarding the use of the AMD anchored system, including feedback on the accuracy of medication intake recorded by the device. Data obtained from the surveys are analyzed alongside adherence metrics from the dashboard to elucidate factors influencing adherence behavior and the device's effectiveness in fostering sustained treatment adherence. Preliminary findings indicate promising outcomes associated with the AMD anchored system intervention. High rates of adherence are observed among patients utilizing the device, attributed to the device's automated dispensing mechanism and the supportive role of healthcare mentors. Challenges such as technical malfunctions and patient acceptance are also identified, prompting continuous refinement of the AMD and mentorship strategies. In conclusion, the integration of an AMD coupled with real-time monitoring through a web-linked dashboard represents a significant advancement in TB treatment adherence management. Future research should focus on the scalability and sustainability of this technology-augmented, holistic approach across diverse healthcare settings to maximize its impact on global TB management strategies.

Next generation yellow fever vaccine induces an equivalent immune and transcriptomic profile to the current vaccine: observations from a phase I randomised clinical trial

Yellow fever (YF), a mosquito-borne acute viral haemorrhagic illness, is endemic to many tropical and subtropical areas of Africa and Central and South America. Vaccination remains the most effective prevention strategy; however, as repeated outbreaks have exhausted vaccine stockpiles, there is a need for improved YF vaccines to meet global demand. A live-attenuated YF vaccine candidate (referred to as vYF) cloned from a YF-17D vaccine (YF-VAX®) sub-strain, adapted for growth in Vero cells cultured in serum-free media, is in clinical development. We report the innate and adaptive immune responses and the transcriptome profile of selected genes induced by vYF. Healthy adults aged 18-60 years were randomised at a 1:1:1:1 ratio to receive one dose of vYF at 4, 5 or 6 Log CCID50 or YF-VAX (reference vaccine), administered subcutaneously in the upper arm (ClinicalTrials.gov identifier: NCT04142086). Blood/serum samples were obtained at scheduled time points through 180 days (D180) post-vaccination. The surrogate endpoints assessed were: serum cytokine/chemokine concentrations, measured by bead-based Multiplex assay; peripheral blood vYF-specific IgG and IgM memory B cell frequencies, measured by FluoroSpot assay; and expression of genes involved in the immune response to YF-17D vaccination by RT-qPCR. There was no increase in any of the cytokine/chemokine concentrations assessed through D14 following vaccination with vYF or YF-VAX, except for a slight increase in IP-10 (CXCL10) levels. The gene expression profiles and kinetics following vaccination with vYF and YF-VAX were similar, inclusive of innate (antiviral responses [type-1 interferon, IFN signal transduction; interferon-stimulated genes], activated dendritic cells, viral sensing pattern recognition receptors) and adaptive (cell division in stimulated CD4+ T cells, B cell and antibody) immune signatures, which peaked at D7 and D14, respectively. Increases in vYF-specific IgG and IgM memory B cell frequencies at D28 and D180 were similar across the study groups. vYF-induced strong innate and adaptive immune responses comparable to those induced by YF-VAX, with similar transcriptomic and kinetic profiles observed. Sanofi.

Stability of a Queue Fed by Scheduled Traffic at Critical Loading

Performance of a queueing system with scheduled arrivals A scheduled arrival sequence is one in which customers are scheduled to arrive at constant interarrival times, but each customer’s actual arrival time is perturbed from her scheduled arrival time by a random perturbation. In “Stability of a Queue Fed by Scheduled Traffic at Critical Loading”, V.F. Araman and P.W. Glynn consider a single server queue with deterministic service times in which customers arrive following a scheduled arrival process. Unlike a queue fed by renewal traffic, this queue is shown to be stable even when the utilization is equal to one. It is also shown that for finite mean perturbations, a necessary and sufficient condition for stability is when the positive part of the perturbation has bounded support, with no requirement on the negative part of the perturbation. Perhaps surprisingly, this criterion is not reversible, in the sense that such a queue can be stable for a scheduled traffic process in forward time, but unstable for the time-reversal of the same traffic process.

Feasibility Testing of the Health4LIFE Weight Loss Intervention for Primary School Educators Living with Overweight/Obesity Employed at Public Schools in Low-Income Settings in Cape Town and South Africa: A Mixed Methods Study.

Given the high prevalence of overweight and obesity amongst educators, this study investigated the feasibility of the 16-week Health4LIFE weight loss intervention for primary school educators living with overweight/obesity in low-income settings in Cape Town, South Africa. The research comprised two sub-studies, a pilot randomised controlled trial testing the intervention (10 intervention, n = 79 and 10 control schools, n = 58), and an investigation of the perceptions of participating educators and principals. Feasibility outcomes included reach, applicability, acceptability, implementation integrity, and a hypothesis-generating signal of effect on lifestyle factors and weight. The intervention consisted of a wellness day, weight loss manual, and text messages. Results indicated acceptable reach, with positive feedback on intervention components from principals and educators. Implementation was largely successful, though three schools dropped out due to scheduling issues. Barriers included interruption of teaching time and busy school schedules. The intervention group (n = 42) showed favourable shifts in belief patterns, stages of change, and lifestyle behaviours, with a trend towards weight loss. Control group (n = 43) changes were limited to dietary intake. The triangulation of results supported the intervention's feasibility in terms of primary and secondary outcomes. Recommendations for enhancement include adding in-person follow-up sessions and an app-based element to potentially increase impact on lifestyle indicators and weight loss.

An Approach to Near-Optimal Continuous-Thrust Solution for Plane Constellation Deployment

Paving the way in satellite constellation deployment, this article presents the Comprehensive Program (GCP) for planning constellation deployment missions by introducing a near-optimal solution for continuous-thrust maneuvers. The GCP establishes time constraints, enabling appropriate time scheduling and eliminating reconfiguration phases. It considers various cases of satellite departure and arrival sequences, collision avoidance constraints, and time limitations. A near-optimal solution for the continuous-thrust trajectory of each satellite is introduced, relying on the Fourier series approximation of the thrust pointing angle. The Fourier series with constant coefficients replaces the thrust angle in the satellite’s orbital motion equations in polar coordinates. The primary advantage of this near-optimal approach lies in its simplicity in accommodating space perturbations, posing no challenges in problem-solving. Additionally, the approach is beneficial due to its straightforward implementation and simple mathematical computations. This approach does not require pre-determining the revolution number of the transfer trajectory, unlike shape-based methods. The proposed method’s flexibility allows it to adapt and optimize the trajectory without prior assumptions about the number of revolutions required for the mission. Analyses demonstrate the proposed algorithm’s versatility and precision across various scenarios involving different orbital eccentricities, thrust forces, and thrust pointing angles. The constant coefficients of the Fourier series are determined by defining a set of objective functions and minimizing them using the Multi-Objective Particle Swarm Optimization algorithm (MOPSO). The first and second objective functions ensure that the transfer orbit reaches the desired deployment point, while the third and fourth ones guarantee the tangential conditions between the transfer orbit and the final orbit. An additional objective function minimizes the trajectory time. As a perturbation of interest, the effect of Earth’s oblateness is considered.

An outlier identification method based on parallel clustering and the Adaboost algorithm for power multi-source heterogeneous data

Abstract Influenced by the diversity of data scheduling and the multi-level differentiation of data distribution, the multi-source heterogeneous data of electric power have serious deviations in space and time scheduling, which makes it difficult to identify outliers. Therefore, a method for identifying outliers of multi-source heterogeneous data of electric power based on parallel clustering and the Adaboost algorithm is proposed. A sampling node model of heterogeneous data is constructed, and random numbers that obey Gaussian distribution are generated according to the mean value of data, and their mean square loss values are optimized to form an objective function of abnormal values of multi-source heterogeneous data of electric power. According to parallel clustering and the Adaboost algorithm, a unified format is created to obtain the load control results of abnormal values of multi-source heterogeneous data of electric power, so as to realize the identification of abnormal values of multi-source heterogeneous data of electric power. The experimental results show that at the time point of 18 s, the data identification quality of this method has reached 80, and with the increase of time, its data identification quality remains stable. It is demonstrated that the method has good recognition results.

Sports event quality and athlete’s behavioural intentions at the World Wrestling Championship

Abstract The COVID-19 pandemic caused unpredictable times and led to changes in tourism, sporting society, and events organisations. Sports events were postponed or cancelled. Indeed, there was a need to reconstruct the event circumstances for safety reasons. Therefore, this study aimed to provide insights into relationships between sports event quality, satisfaction, and behavioural intentions (repeated destination visits, positive word-of-mouth communication) during the implementation of COVID-19 security risk measures. The sample included 150 athletes from the U23 World Wrestling Championship organised in Belgrade, Serbia, in 2021. The sport event quality, satisfaction, and behavioral intentions were measured with a questionnaire. The proposed model was assessed using a confirmatory factor analysis with structural equation modeling using Smart PLS, SPSS, and AMOS. Results revealed a significant direct effect of the sport event quality (core dimension) and an indirect effect across satisfaction (tangibles and COVID-19 risk measures) on the athletes’ behavioural intentions. As wrestlers lived in a „bubble” and competed without spectators during the competition, it is not a surprise that the core dimension of service quality, including the competition itself, the opening ceremony, organisation, time schedule, medal ceremonies, and the total quality of the event, has a significant impact for wrestlers’ likelihood of coming back to the city or the country and to recommend the destination to others. Thisstudy contributes to advancing the general scientific knowledge concerning understanding sports events from the aspect of sports tourism and event organisation, especially in the post-COVID-19 era.

Knowledge Of Timing And Compliance With Routine Immunization Schedule Among Mothers Of Under Five Attending Immunization Clinic In A Tertiary Hospital, Sokoto State, Nigeria

Background: Immunization is the most efficacious and low-cost strategy to save the lives of children and prevent dangerous communicable diseases. In order to develop the highest level of protection against diseases, children should be fully vaccinated as per the schedule and at the right age. Complete vaccination to children is a successful way of reducing the infant mortality rate, and to make zero dropouts and achieve 100% vaccination, vaccines should be administered as per scheduled time. Aim: The aim of this study is assess the knowledge of timing and compliance with routine immunization schedule among mothers of under five children attending immunization clinic in a tertiary hospital in Sokoto state, Nigeria Materials and Methods: This is a descriptive study conducted among 280 mothers of under five children attending immunization clinic in a tertiary hospital in Sokoto state in May and June, 2022. The respondents were selected by multistage sampling technique. A set of pretested, semi-structured interviewer- administered questionnaire was usedtocollect data on the research variables. Data were analyzed using IBM® SPSS version 25 statistical package. Results: The ages of the respondents ranged from 18 to 45 years with a mean age of 29.18 ± 8.16 years. Majority of the respondents 167 (59.5%) were aged 21-30 years. Most of the respondents were married 277 (99.0%) and larger proportion (58.1%) had tertiary education. The proportions of respondents with good knowledge of routineimmunization timing as the per schedule was (90.7%) and majority 235(83.9%) complied with timing according totheschedule. About two-third 175 (62.5%) of the respondents were fully vaccinated, some of the reasons mentioned by therespondents for not complying with timing were; waiting time, attitude of the health workers, husband disapproval andsickness of the child among others. Conclusion and Recommendations: Most of the respondents demonstrated good knowledge of routine immunization timing and majority compliedwith the timing according to the scheduled. About two-third of them were fully immunized, some of the reasons fornot complying with timing as per the schedule among the respondents were waiting time, attitude of the healthworkers, husband disapproval and sickness of the child among others. Improving the knowledge of parents about immunization was recommended by providing health education session consistently at every clinic day before the immunization session

Assessing Healthcare Equity in Orthopaedic Surgery: An Analysis of Over 24,000 Surgical Cases.

Health disparities have been widely studied in the primary care and surgical settings. The purpose of this study was to examine surgical access disparities for orthopaedic surgical cases performed at a large academic health center by comparing the relationship between patient demographic factors and surgical wait time. A total of 24,778 orthopaedic surgical cases from 2018 to 2022 at a public, tertiary care, Level I trauma center were retrospectively analyzed to assess for surgical timing disparities based on patient-specific factors, including race, sex, language, and socioeconomic status. Elective surgical cases were completed with an average surgical wait time of 28.11 ± 26.34 days. Urgent surgical cases were completed with an average surgical wait time of 1.23 ± 1.50 days. Patient race, sex, language, and socioeconomic status had no effect on surgical wait time for urgent case scheduling. Female patients had longer average wait times in elective cases, whereas race had a weak association with increased wait time. Two-factor interaction analysis showed no multifactorial effects of patient demographic factors on surgical wait time. Patient race and socioeconomic status were associated with increased distance from surgical sites, although increased distance did not correlate with increased surgical wait time. Patient demographic factors did not demonstrate clinically notable associations with surgical timing in this patient cohort, in contrast to previous studies demonstrating the effects of race and socioeconomic status on healthcare outcomes and access. Race and socioeconomic status did correlate with increased distance from surgical centers although distance from surgical sites did not correlate with surgical wait time. This contributes to previous literature on healthcare equity and indicates that surgical wait time may not contribute to the known healthcare inequalities seen in minority and marginalized patients.

Comparison of Analgesic Effect of Local Anesthetic Injection for Pain Relief During Peripheral Venous Insertion in Adult Surgical Patients: A Prospective Observational Study

PurposeIntradermal injection of local anesthetic has been reported to have greater analgesic effect for peripheral venous catheter (PVC) insertion than topical application in adult surgical patients. However, the injection of local anesthetic itself is a painful procedure compared to topical application. We compared the analgesic effect of a lidocaine-prilocaine patch with intradermal injection of 2 % lidocaine on pain intensity at the time of analgesia and PVC insertion as assessed by a visual analog scale (VAS) in adult patients. DesignA prospective observational study. MethodsAfter institutional review board (IRB) approval, we studied 70 patients scheduled for surgery and expected to have peripheral venous cannulation in the operating room. Patients who presented in the operating room with a topical anesthetic patch were assigned to the patch group, and patients who presented without a topical anesthetic patch were assigned to the injection group. The injection group received a 2 % lidocaine injection with a 26-gauge (G) needle just before PVC insertion by anesthetists. The patch group received a lidocaine-prilocaine patch on the dorsal hand 1 to 2 hours before the scheduled surgery time by ward nurses. The primary endpoints were pain using the VAS score at the time of PVC insertion and pain associated with the local anesthetic procedure. FindingsThe patch group included 34 patients (21 male, 13 female, age 61 [median], interquartile range [IQR] 45 to 69), and the intradermal injection group included 31 patients (22 male, 9 female, age 60 [median], IQR 52 to 73). All patients analyzed had a 20-G catheter in the dorsal hand. The median VAS score for PVC insertion was 4 in the intradermal injection group (IQR 0 to 14) and 2 in the patch group (IQR 0 to 16) (P = .707). Median VAS scores for the local anesthetic procedure were 16 in the intradermal injection group (IQR 10 to 32) and 0 in the patch group (IQR 0 to 0) (P < .001). ConclusionsWe found no difference in the pain intensity for PVC insertion between topical application of local anesthetic by lidocaine-prilocaine patch and intradermal injection of 2 % lidocaine. VAS scores for anesthetic application were significantly lower in the patch group. The lidocaine-prilocaine patch provided analgesia equivalent to intradermal injection with 2 % lidocaine for PVC but without the pain associated with injection of local anesthetic.

Hacking Habits for High-Performance Leadership

This article discusses how leaders can continuously improve their skills and effectiveness through habit hacking. It explores how reframing mindsets, building supportive systems, and committing to small daily optimizations can strengthen areas of weakness over time. Specifically, the article recommends practicing self-compassion and adopting a growth mindset. It also suggests implementing daily rituals like morning reflection and scheduled time for skill-building. Leaders are encouraged to do micro-optimizations like extending exercise routines slightly each day. Recognizing even small milestones is important for maintaining motivation. Real-world examples demonstrate how specific leaders hacked habits like prioritizing tasks, scheduling device-free breaks, and sharing mistakes to boost various outcomes like productivity, creativity, morale and innovation. The conclusion emphasizes that viewing routines through a growth lens and hacking habits through small tweaks can significantly enhance leadership abilities and fulfillment as part of an ongoing development process.

Empowering London Primary School Communities to Know and Tackle Air Pollution Exposure

This study tested the effectiveness of participatory methods to engage primary school communities in London with air pollution issues to help them identify, understand, and reduce their air pollution exposure. Three primary schools with high pollution levels participated in environmental educational activities, including air quality workshops and field campaigns involving different methods, time schedules, and project scopes. Participants completed surveys before and after these activities to measure their understanding, perceptions, and behavior. After the workshops, students admitted feeling more skillful in monitoring air quality and confident in incorporating this education into daily life and teaching others. They shared their results with peers, school leadership, and the community and led campaigns to help design experiments, choose measurement locations, and reduce air pollution exposure in schools. The results showed increased concern about air pollution, a better understanding of its causes and impacts, and more reported reduction behaviors. An Air Pollution Exposure Index (APEI) was combined with participatory monitoring data to raise awareness and understanding among students on typical school-day exposure. Feedback indicates that the tool was useful in defining air pollution exposure status and identifying exposure risks. Overall, this study contributes to the evidence of the feasibility and impact of student-led environmental education interventions These interventions involve collecting personalized exposure data, co-planning mitigations with school community groups, and employing methods to raise awareness of air pollution and empower pupils to identify potential solutions and change behaviors.

Physical model-assisted deep reinforcement learning for energy management optimization of industrial electric-hydrogen coupling system with hybrid energy storage

Utilizing renewable energy sources (RESs), such as wind and solar, to convert electrical energy into hydrogen energy for industrial users with different types of energy storage can enhance the integration of green electricity, thereby replacing fossil fuels like natural gas. In the energy management optimization of industrial electric‑hydrogen coupling system (EHCS) with high RESs integration, the traditional optimization methods cannot effectively address the nonlinear characteristics of equipment and stochastic RES generation, while the model-free reinforcement learning methods struggle to improve the training efficiency and may lead to constraint violation. To address this challenge, this paper proposes a short time scale energy management approach for EHCS based on physical models assisted deep reinforcement learning (DRL). Firstly, the energy management optimization model of the EHCS is developed based on the operation characteristics of the equipment within the system. Secondly, the energy management model of EHCS is formulated as a DRL framework. The DRL agent is efficiently trained with the assistance of the action transformation which takes into account the physical characteristics of the equipment during operation. Finally, a case study is conducted to verify the effectiveness of the proposed model for achieving high-efficiency agent training, reducing decision-making time for equipment scheduling, addressing the stochastic RES generation, and realizing the economic operation of EHCS with good performance based on the equipment characteristics.