A Wireless Sensor Network (WSN) is usually made up of a large number of discrete sensor nodes, each of which requires restricted resources, including memory, computing power, and energy. To extend the network lifetime, these limited resources must be used effectively. In WSN, clustering constitutes one of the best methods for optimizing network longevity and energy conservation. In this work, we proposed a novel Energy and Throughput Aware Adaptive Routing (ETAAR) algorithm based on Cooperative Game Theory (CGT). To achieve the energy efficient and improved data rate routing in WSN, we are applied two game theories of CGT and coalition game. The main part of this routing mechanism is cluster head selection and clustering the nodes to perform energy efficient and throughput effective communication between the nodes. In first stage, CGT based utility function which adopts both energy and throughput is utilized to handpick the CH nodes. In the second stage, along with the energy and throughput, average end-to-end delay is considered for the adaptive time slot transmission to avoid collision in the coalition game approach. MATLAB tool is used for simulation. The simulation results shows that the proposed ETAAR protocol is outperforms than earlier works of routing in terms of residual energy, PDR, energy due ratio, average end-to-end delay, dead nodes. The network lifetime of 48% extension, energy saving of 60% and 52.5% of delay shortage attained in ETAAR.

Automation in clinical flow cytometry has the potential to revolutionize the field by improving processes and enhancing efficiency and accuracy. Integrating advanced robotics and artificial intelligence, these technologies can streamline sample preparation, data acquisition, and analysis. Automated sample handling reduces human error and increases throughput, allowing laboratories to handle larger volumes with consistent precision. Intelligent algorithms contribute to rapid data interpretation, aiding in the identification of cellular markers for disease diagnosis and monitoring. This automation not only accelerates turnaround times but also ensures reproducibility, making clinical flow cytometry a reliable tool in the realm of personalized medicine and diagnostics.

Wireless sensor networks (WSN) are among the most prominent current technologies. Its popularity has skyrocketed because of its capacity to operate in difficult situations. The WSN market encompasses various industries, including building automation, security networks, healthcare systems, logistics, and military operations. Therefore, increasing the energy efficiency of these networks is of utmost importance. Hierarchical topology, which typically uses a clustering methodology, is one of the most well-known methods for WSN energy optimization. To achieve energy efficiency in WSN, hierarchical topology low-energy adaptive clustering hierarchy (LEACH) was first introduced, and this served as the foundation. However, conventional LEACH has several limitations, which have led to extensive research into improving LEACH\'s efficacy in its current form. The use of particular algorithms and strategies to enhance the functionality of the conventional LEACH protocol forms the basis of ongoing efforts. Utilizing this enhanced LEACH, performance in terms of throughput and network life may be enhanced by concentrating on elements such as cluster head formation and transmission energy consumption. The enhanced LEACH algorithm demonstrates significant improvements in both throughput and network lifetime compared with conventional LEACH. Through rigorous experimentation, it was found that the enhanced algorithm increases the throughput by 25% on average, which is attributed to its dynamic clustering and optimized routing strategies. Furthermore, the network lifetime is extended by approximately 30%, primarily because of enhanced energy efficiency through adaptive clustering and transmission power control.

UNASSIGNED: Research suggests that quantitative metric reports can improve the clinical performance of emergency physicians; however, few studies have examined their effects on physicians in training. The primary study objective was to assess the effects of providing emergency medicine (EM) residents with individualized throughput metrics with regard to emergency department (ED) disposition times.
UNASSIGNED: We performed a single-center, retrospective, observational study from January 2021 to December 2022 examining ED disposition times before and after providing upper-level EM residents individualized throughput metrics. Residents received monthly reports of three specific metrics averaged over the preceding 6 months: (1) median time from room to discharge order (Rm2Dc), (2) median time from return of all results to discharge order (Rlts2Dc), and (3) median time from room and to consult order for hospitalization (Rm2Hosp). Overall mean values of the three metrics before and during metric sharing were compared via independent t-test and stratified by level of training and time of year. Adjusted analysis was performed to control for temporal differences between study periods. Testing was conducted at α = 0.05 level of significance.
UNASSIGNED: A total of 35 unique residents were included in the analysis. Overall, mean disposition times were not significantly different before and during reporting of metrics: Rm2Dc (154.8 min vs. 148.9 min, p = 0.109), Rslt2Dc (46.5 min vs. 45.1 min, p = 0.522), and Rm2Hosp (141.7 min vs. 135.7 min, p = 0.257). Subgroup analysis yielded similar results, aside from a significant decrease in mean Rm2Hosp in the postgraduate year-3 (PGY-3) group (145.8 min vs. 124.1 min, p = 0.004). Analysis with adjusted means yielded results similar to those observed with unadjusted data.
UNASSIGNED: Overall, individualized throughput metrics were not correlated with decreased average times to ED disposition for upper-level EM residents; however, in the subset of hospitalized patients seen by PGY-3 residents, we observed a mean decrease of 21.7 min to consultation.

In this study, we analyze the CSMA Non-Persistent protocol with a finite number of nodes, providing more accurate results for applications like wireless sensor networks. The finite model addresses scenarios where the node count is moderate, capturing realistic system dynamics. Our analysis reveals a dependency on the node count, impacting system throughput. As the node count increases, throughput behavior aligns with Kleinrock\'s infinite model. We derive a complex closed-form throughput expression for a finite quantity of nodes in the system, solved numerically, and offer an approximate expression for specific conditions. These insights advance understanding of low-contention network performance, especially in scenarios where the infinite model becomes inadequate.

In counter-current chromatography (CCC), linear scale-up is an ideal amplification strategy. However, when transferring from analytical to predictable preparative processes with high throughput, linear scale-up would be challenging due to limitations imposed by differences in instrument parameters, such as gravitational forces, tubing cross-section area, tubing length, column volume and flow rate. Some effective scale-up strategies have been studied for different instrument parameters, but so far, these scale-up works have only been tested on standard circular (SC) tubing. The previous research of our group found that rectangular horizontal (RH) tubing can double the separation efficiency compared with conventional SC tubing, and has industrial production potential. This paper used the separation of tilianin from Dracocephalum moldavica L. as an example to demonstrate how to scale up the optimized process from analytical SC tubing to preparative RH tubing. After systematic optimization of solvent systems, sample concentration and flow rate on the analytical CCC, the optimized parameters obtained were successfully transferred to the preparative CCC. The results showed that a crude sample of 2.07 g was successfully separated using a solvent system of n-hexane - ethyl acetate - ethanol - water (1:4:1:5, v/v/v/v) in reversed phase mode, and the three consecutive separations produced a total of 380 mg tilianin in 75 min with high purities of 98.3%, as analyzed by HPLC. The total throughput achieved from the analytical to semi-preparative scale was improved by 138 times (from 12 mg/h to 1.66 g/h), while the column volume was increased by only 46.5 times (from 15.5 mL to 720 mL). This is the successful application of CCC for the separation and purification of tilianin. Given that SC tubing is the traditional configuration for CCC columns, this study is a necessary step to prove the applicability of RH tubing columns for routine use and potential large-scale industrial applications.

Background Hospital overcrowding compromises patient safety. The contribution of variability in admissions and discharges to overall hospital capacity needs to be quantified. This study describes the statewide day-to-day fluctuation in the volume of hospitalized patients, the variability and pattern of hospital admissions and discharges throughout the week, and the contribution of Emergency Department (ED) vs. elective (non-ED) admissions and discharges to the overall variability in the system across the week. Methodology This is a retrospective analysis of the New York State Statewide Planning and Research Cooperative System database, in which all New York healthcare facilities submit patient-level data monthly. The study period was from January 01 to December 31, 2015. Outcomes included total volumes of admissions and discharges and length of stay sorted by patient origin (ED vs. non-ED admits (elective)) and service type (medicine vs. surgery) by day of the week. Results We studied 1,692,090 hospital admissions. Admissions were highest on Mondays and Tuesdays and steadily decreased throughout the week. There was little variability in the ED admissions throughout the week. Surgical elective admissions had significant variability throughout the week, with higher admissions at the beginning of the week. There was a significant difference (p < 0.01) between admissions on weekdays vs. weekends. Discharges increased from Monday to Friday, with a dramatic drop on the weekends, for both ED and elective pathways. Systemwide, on Monday, hospitals were 21% above the mean volume, and on Fridays, hospitals were 32% below the mean volume. Conclusions Overall hospital capacity shows dramatic variability throughout the week, driven primarily by elective admissions and discharges from any source throughout the week. Because elective admissions are schedulable, hospitals can reduce variability by smoothing scheduling. Increased weekend discharges will also improve capacity.

In today\'s health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors.

BACKGROUND: Research shows that one-time doses of intravenous (IV) antibiotics do not improve resolution of infection. However, providers continue to use them-especially in the emergency department (ED). Very few studies have aimed to quantify the cost of this practice.
OBJECTIVE: The primary objective was to evaluate the difference in average total cost of ED stay between patients who received a one-time dose of IV antibiotics in the ED before discharging on oral antibiotics and patients who were just discharged on oral antibiotics. Secondary objectives were to evaluate the differences in durations of stay between the 2 groups, as well as the differences in adverse drug effects and need for health care contact after discharge.
METHODS: Chart review was conducted to identify patients who received and did not receive a one-time dose of IV antibiotics in the ED between April 30, 2020, and April 30, 2022. A microcosting approach was used to determine ED-associated costs per patient. Comparisons in primary and secondary outcomes were performed using statistical inferential tests.
RESULTS: A total of 102 patients were analyzed in each group. Patients who received a one-time dose of IV antibiotics in the ED before being discharged on oral antibiotics had an average length of stay of 4.55 hours, as opposed to patients who did not receive a one-time dose of IV antibiotics before being discharged on oral antibiotics who had an average length of stay of 2.82 hours (absolute difference 1.73 hours, P < 0.001). One-time dosing of IV antibiotics in the ED incurred an additional cost of approximately $556 per patient, totaling to more than $56,000 in our study cohort.
CONCLUSIONS: The use of one-time IV antibiotics in the ED did not confer any additional benefits to patients. The use of one-time doses resulted in statistically significant reduced throughput in the ED and statistically significant increased health care costs.

OBJECTIVE: Delays within the postanesthesia care unit (PACU) are a major cause of complications and inefficiency. In this project, we investigated the factors associated with delays in the PACU and implemented policies to mitigate these factors.
METHODS: A quality improvement project.
METHODS: Data were collected for 10 months and included 1,134 surgical patients in a tertiary Obstetrics and Gynecology hospital in Kuwait. Several meetings were held with stakeholders to identify and overcome the reasons contributing to delays within the PACU.
RESULTS: Among the top reasons for PACU delay were manpower shortage and lack of bed availability in the surgical wards due to improper admission and discharge policies. Policies were implemented to improve admission policy, hasten patient discharge, and improve patient flow through the operating theater (OT). These policies lead to a significant reduction (25 minutes) in the average time patients spend in the OT, mainly by reducing the stay in the PACU by 19 minutes.
CONCLUSIONS: PACU delays were mostly due to reasons outside the OT. Further, follow-up is needed to assess the sustainability of these improvements and identify any new challenges that may arise.