Transport Time Research Articles

Adjusting on-scene CPR duration based on transport time interval in out-of-hospital cardiac arrest: a nationwide multicenter study

The optimal duration of on-scene cardiopulmonary resuscitation (CPR) for out-of-hospital cardiac arrest (OHCA) patients remains uncertain. Determining this critical time period requires outweighing the potential risks associated with intra-arrest transport while minimizing delays in accessing definitive hospital-based treatments. This study evaluated the association between on-scene CPR duration and 30-day neurologically favorable survival based on the transport time interval (TTI) in patients with OHCA. We retrospectively analyzed data from the Korean Cardiac Arrest Research Consortium registry of OHCA, comprising 65 participating hospitals in South Korea, between October 2015 and December 2021. We categorized the patients into Short-TTI (TTI < 10 min) and Long-TTI (TTI ≥ 10 min) groups. Differences in clinical features were adjusted for using propensity score matching (PSM) for TTI. The primary outcome was a 30-day neurologically favorable outcome, defined as cerebral performance category 1 or 2. Multivariable logistic regression was used to determine the variables associated with clinical outcomes. A generalized additive model based on a restricted cubic spline smooth function was utilized to infer the optimal cutoff point for on-scene CPR duration. Of the 6,345 patients, 5,844 PSM pairings were created (Short-TTI: 2,922; Long-TTI: 2,922). The primary outcome was achieved in 7.4% and 9.8% of the patients in Short-TTI and Long-TTI groups, respectively (p = 0.001). Increased on-scene CPR duration was associated with decreased neurologically favorable survival (adjusted odds ratio, 0.94; 95% confidence interval, 0.92–0.96). The optimal on-scene CPR durations in the overall PSM, Short-TTI, and Long-TTI groups were 5.1, 0, and 5.0 min, respectively. An adjusted on-scene CPR duration based on expected transport duration may be beneficial for favorable clinical outcomes in patients with OHCA.

The differences in injury patterns and outcomes of thoracic trauma between rural and urban level two trauma centers in a single country.

Equal level trauma centers in the same country might have significant differences regarding their demographics and types of trauma. Understanding geographic variations in injury patterns are essential for optimal care. Here we describe the differences in injury patterns and associated outcomes of thoracic trauma patients between rural and urban level-II trauma centers in a single country. A retrospective analysis of patients with thoracic trauma over a three-year period in a rural level-II and an urban level-II in Israel were compared. Demographics, mechanism of injury, prehospital care, transport, hospitalization course, discharge disposition, and outcomes were all analyzed. There were significant differences between the demography, mechanisms of injury, and sustained injuries. The urban population was older, with more pedestrians hit by motor vehicles, falls from standing or sitting, and penetrating injuries. The rural population suffered from more motor vehicle crashes and falls from heights, with injuries related to higher velocity mechanisms such as lung contusions, sternal fractures, and liver injuries. There was no significant difference in transportation time or injury severity scores. More advanced life support ambulances were utilized in the rural setting together with more transfers to a higher level of care, while more patients in the urban center were lost to follow-up. Understanding the differences between geographic locations is crucial towards optimizing trauma care. The complexities of thoracic trauma patients are an important example of the variations between rural and urban trauma centers. Respecting these differences will help to improve preparedness and treatment for trauma patients.

Hospital selection for suspected stroke: risk-averse approach considering the minimal risk of exceeding the therapeutic time window

BackgroundTimely treatment within the therapeutic window is critical for patients with stroke. This study adopts a risk-averse optimization approach to maximize the likelihood of receiving treatment within this window.MethodsWe developed...

A Novel Artificial Intelligence-Enhanced Digital Network for Prehospital Emergency Support: Community Intervention Study.

Efficient emergency patient transport systems, which are crucial for delivering timely medical care to individuals in critical situations, face certain challenges. To address this, CONNECT-AI (CONnected Network for EMS Comprehensive Technical-Support using Artificial Intelligence), a novel digital platform, was introduced. This artificial intelligence (AI)-based network provides comprehensive technical support for the real-time sharing of medical information at the prehospital stage. This study aimed to evaluate the effectiveness of this system in reducing patient transport delays. The CONNECT-AI system provided 3 key AI services to prehospital care providers by collecting real-time patient data from the scene and hospital resource information, such as bed occupancy and the availability of emergency surgeries or procedures, using 5G communication technology and internet of things devices. These services included guidance on first aid, prediction of critically ill patients, and recommendation of the optimal transfer hospital. In addition, the platform offered emergency department medical staff real-time clinical information, including live video of patients during transport to the hospital. This community-based, nonrandomized controlled intervention study was designed to evaluate the effectiveness of the CONNECT-AI system in 2 regions of South Korea, each of which operated an intervention and a control period, each lasting 16 weeks. The impact of the system was assessed based on the proportion of patients experiencing transfer delays. A total of 14,853 patients transported by public ambulance were finally selected for analysis. Overall, the median transport time was 10 (IQR 7-14) minutes in the intervention group and 9 (IQR 6-13) minutes in the control group. When comparing the incidence of transport time outliers (>75%), which was the primary outcome of this study, the rate was higher in the intervention group in region 1, but significantly reduced in region 2, with the overall outlier rate being higher in the intervention group (27.5%-29.7%, P=.04). However, for patients with fever or respiratory symptoms, the group using the system showed a statistically significant reduction in outlier cases (36.5%-30.1%, P=.01). For patients who received real-time acceptance signals from the hospital, the reduction in the percentage of 75% outliers was statistically significant compared with those without the system (27.5%-19.6%, P=.02). As a result of emergency department treatment, 1.5% of patients in the control group and 1.1% in the intervention group died (P=.14). In the system-guided optimal hospital transfer group, the mortality rate was significantly lower than in the control group (1.54%-0.64%, P=.01). The present digital emergency medical system platform offers a novel approach to enhancing emergency patient transport by leveraging AI, real-time information sharing, and decision support. While the system demonstrated improvements for certain patient groups facing transfer challenges, further research and modifications are necessary to fully realize its benefits in diverse health care contexts. ClinicalTrials.gov NCT04829279; https://clinicaltrials.gov/study/NCT04829279.

Greedy Algorithm Based Travel Route Planning under Multi-objective Decision Making

In this paper, greedy algorithm is used to optimize the planning of tourism routes based on multi-objective decision theory. The main goal of the research is to design the best travel route for foreign tourists by considering various factors such as time, cost and number of attractions. Firstly, this paper establishes a dataset including information of cities, attraction ratings, transportation time and cost through data integration and processing. Secondly, this paper used hierarchical analysis to evaluate 352 cities in multiple dimensions and identified the 50 cities that are most desirable to foreign tourists. Finally, combined with the greedy algorithm, this paper designed multiple optimization strategies under different constraints. The greedy algorithm used in the study can quickly provide tourist routes that meet the needs of tourists under multi-objective decision-making, and at the same time provides a new way of thinking for the planning of tourist routes.

EP109 Assesment of factors contributing to delay of emergency laparotomies and potential solutions to optimize patient flow at a high volume centre. A Quality Improvement Project

Abstract Aim To identify factors resulting in delay of emergency laparotomies and offer potential solutions. Methods This was a retrospective study spanning 7 months including all laparotomies and major laparoscopic procedures excluding appendicectomies and cholecystectomeis. Data from the trust IT system was used to populate the various times of each procedure. Results 265 patients were studied in total including 76 category 1 laparotomies. Transport time defined as the duration between completion of the briefing to patient arrival at the operating theatre was found to be inaccurately documented in 66 cases. Median time was 20 min with 15 patients needing more than 45 min for transport. Median anaesthetic time defined as time from patient arrival to initiation of surgery was 50 min. Median procedure duration was 113 min. Median post operative time defined as the duration between surgery completion and exiting the operating theatre was 17 min. Median post op recovery time was 137 min with 15 patients requiring more than 12 hours in recovery. Post changes of informal education the median transport time reduced to 17 min. Conclusions Factors that can be optimized to reduce delays are ensuring ward prepardeness before transferring to theatres, appropriate documentation of transport times so staff are aware they maybe audited and satisfactory communication between teams (including site/bed managers) to ensure adequate prepardeness and a smooth flow of patients to the ward and prevent a hold up in recovery.

Tracking acute flaccid paralysis in Niger: a half-decade epidemiological portrait (2016–2021)

BackgroundRecently, a total of 74 circulating vaccine-derived poliovirus (cVDPV) outbreaks were detected in 39 countries, with 672 confirmed Acute Flaccid Paralysis (AFP) cases identified in 27 countries. Despite progress, Niger experienced cVDPV outbreaks in 2018, highlighting the importance of maintaining AFP surveillance as a tool for polio eradication. This analysis aims to comprehensively assess AFP surveillance trends, patterns, and challenges in Niger, offering insights for public health initiatives in conflict-affected contexts.MethodsWe analyzed nationwide AFP surveillance data from 2016 to 2021. The data included information about the person's background, vaccinations, medical history, cVDPV, AFP cases, stool samples, how quickly AFP cases were reported, how complete weekly zero reporting (WZR) was, and non-polio enteroviruses (NPEV). Tables, graphs, and maps presented the study findings.ResultsA total of 4,134 AFP cases under 15 years old were included, with a sex ratio of 1.3. Most cases (79.85%) were aged 1 to 4 years, and 79.44% received three or more doses of oral polio vaccine (OPV). Fever onset (90.13%), asymmetric paralysis (80.33%), and a 3-day AFP progression (80.48%) were common. cVDPV2 was found in 33 cases, predominantly in Zinder province. The annualized non-polio AFP rate per 100,000 population < 15 years fluctuated, with the lowest at 2.5 in 2016 and highest at 8.7 in 2018 (mean 5.93). Surveillance indicators, including faecal specimen collection, follow-up exams, NPEV detection, timeliness of AFP case notification, WZR, and timely laboratory results performed above the set target. However, stool specimen quality was suboptimal (69% in 2016), timeliness of AFP case investigation and contact sampling, and stool transportation times were below the set target. Five districts reported less than 80% stool adequacy.ConclusionThis study underscores the importance of continued AFP surveillance in Niger, with room for improvement in stool specimen quality and transportation times. Enhancing these aspects can improve public health efforts in conflict-affected areas and contribute to polio eradication in the region.

Research on Cold-Energy Loss of Long-Distance Sleeve-Type Insulated Pipe for High-Temperature Deep Mines

As mining operations extend to greater depths, they encounter critical challenges, including increased distances and substantial energy losses. To address the challenges of cold-energy loss in deep mine cooling systems and improve the working environment for miners, a long-distance sleeve-type insulated pipe system was developed. This system aims to mitigate thermal energy loss caused by heat transfer between the pipe and surrounding soil throughout the water transport path from the source to the deep mine in boreholes. A heat transfer analysis model was developed to assess the impact of variables such as transport time, water flow rate, inlet temperature, and insulation materials on the temperature of cold water. The study reveals that the temperature of cold water increases rapidly during transportation before reaching a stable state. Implementing modifications such as increasing the inlet temperature, enhancing the water flow rate, or utilizing materials with lower thermal conductivity can effectively mitigate temperature rises. Additionally, the novel sleeve-type design enhanced the pipe’s pressure-bearing capacity, reduced the required pipe length by 4752 m and minimized energy loss compared to traditional systems. In practical applications, after 45 h, the supply and return water temperatures increased by 0.45 °C and 0.38 °C, respectively, while maintaining cooling energy loss below 12%. This innovative solution improves mine cooling efficiency and provides guidance to reduce cold-energy loss.

Your Blood is Out for Delivery: Considerations of Shipping Time and Temperature on Degradation of RNA from Stabilized Whole Blood.

Remote research studies are an invaluable tool for reaching populations with limited access to large medical centers or universities. To expand the remote study toolkit, we previously developed homeRNA, which allows for at-home self-collection and stabilization of blood and demonstrated the feasibility of using homeRNA in high temperature climates. Here, we expand upon this work through a systematic study exploring the effects of high temperature on RNA integrity (represented as RNA Integrity Number, RIN) through in-lab and field experiments. Compared to the frozen controls (overall mean RIN of 8.2, n = 8), samples kept at 37 °C for 2, 4, and 8 days had mean RINs of 7.6, 5.9, and 5.2 (n = 3), respectively, indicating that typical shipping conditions (∼2 days) yield samples suitable for downstream RNA sequencing. Shorter time intervals (6 h) resulted in minimal RNA degradation (median RIN of 6.4, n = 3) even at higher temperatures (50 °C) compared to the frozen control (mean RIN of 7.8, n = 3). Additionally, we shipped homeRNA-stabilized blood from a single donor to 14 states and back during the summer with continuous temperature probes (7.1 median RIN, n = 42). Samples from all locations were analyzed with 3' mRNA-seq to assess differences in gene counts, with the data suggesting that there was no preferential degradation of transcripts as a result of different shipping times, temperatures, and regions. Overall, our data support that homeRNA can be used in elevated temperature conditions, enabling decentralized sample collection for telemedicine, global health, and clinical research.

Retrospective analysis of trauma patients transported by dispatch monitored type B ambulances to Dhulikhel Hospital, Kavre, Nepal, 2019–2023

BackgroundTimely emergency medical services (EMS) are particularly important among trauma patients, as inefficient EMS systems can result in potentially avoidable death before reaching a hospital. The Dhulikhel Hospital Dispatch Center coordinates and monitors a growing network of ambulances, including seven Type B ambulances staffed with a trained prehospital care provider and medical equipment. This study evaluates the prehospital care and outcomes of trauma patients transported by Type B ambulances to Dhulikhel Hospital’s Emergency Department, as monitored by the Dispatch Center.MethodsData were collected via a retrospective chart review of Dispatch Center records, including patient demographics, injury mechanisms, prehospital care, and outcomes. Patients were included if they experienced physical trauma and were transported by a Type B ambulance to Dhulikhel Hospital’s Emergency Department between 2019 and 2023.ResultsBetween 2019 and 2023, 224 trauma patients were transported to the hospital and received prehospital care services from Type B ambulances monitored by the Dispatch Center. Most patients were male (59%), and nearly half were aged 18–44 (49%). The median total transport time for Dhulikhel Hospital-owned Type B ambulances was 40 min. Type B ambulances reached patients across 24 municipalities (88% in Kavrepalanchowk and Sindupalchowk districts). Falls (55%) and road traffic accidents (30%) were the most common injury mechanisms, followed by physical assault (7%). Falls were significantly associated with female, pediatric, and geriatric patients (p < 0.05), while road traffic accidents predominated among males, particularly in adults aged 25–34 years (p < 0.05). Approximately one-third of patients admitted to the hospital after evaluation in the emergency department experienced multiple injuries, and the most prevalent diagnosis of admitted cases were extremity fractures (52%).ConclusionTrauma cases accounted for 15% (227/1541) of all patients who received transport and prehospital care services from a Type B ambulance monitored by the Dispatch Center between 2019 and 2023. This study demonstrates the critical role of Type B ambulances and an integrated dispatch center in advancing timely and efficient prehospital care for trauma patients in Nepal.

Optimization of Urban Fire Emergency Resource Allocation Based on Pre-Allocated Swarm Algorithm

As a high-frequency disaster with potentially devastating consequences, urban fires not only threaten the lives of city residents but can also lead to severe property losses, especially for hazardous chemical leaking scenarios. Quick and scientific decision-making regarding resource allocation during urban fire emergency responses is crucial for reducing disaster damages. Based on several key factors such as the number of trapped individuals and hazardous chemical leaks during the early stages of an incident, an emergency weight system for resource allocation is proposed to effectively address complex situations. In addition, a multi-objective optimization model is built to achieve the shortest response time for emergency rescue teams and the lowest cost for material transportation. Additionally, a pre-allocated bee swarm algorithm is introduced to mitigate the issue of local incident points being unable to participate in rescue due to low weights, and a comparison of traditional genetic algorithms and particle swarm optimization algorithms is conducted. Experiments conducted in a virtual urban fire scenario validate the effectiveness of the proposed model. The results demonstrate that the proposed model can effectively achieve the dual goals of minimizing transportation time and costs. Furthermore, the bee swarm algorithm exhibits advantages in convergence speed, allowing for the faster identification of ideal solutions, thereby providing a scientific basis for the rapid allocation of resources in urban fire emergency rescues.

Fluid Resuscitation in the Prehospital Setting

Urban Emergency Medical Services benefit from an increased number of higher-level personnel (Advanced Emergency Medical Technicians and Paramedics) responding to all calls that are trained to obtain intravenous access. Current Advanced Trauma Life Support guidelines require all trauma patients to receive intravenous access, and as such it is essential for EMS clinicians to be conversant with situations which may require fluid resuscitation. These situations are especially common in rural or austere environments as long transport times require EMS clinicians to maintain adequate hemodynamics until arrival at a trauma center for definitive care. Historically, crystalloid solutions have been the mainstay of fluid resuscitation with Normal Saline or Lactated Ringer’s solution being preferred. Despite the recent shift in best practices from aggressive fluid resuscitation to delayed or significantly scaled back fluid resuscitation in most settings of trauma, it is essential for EMS clinicians to understand when fluid resuscitation is indicated, or, more importantly, contraindicated. EMS clinicians must be comfortable with the various fluids available to them in the field. This review provides an overview of the most common crystalloid fluids and blood component therapies which may be used for resuscitation in the prehospital setting.

Production scheduling with multi-robot task allocation in a real industry 4.0 setting

The demand for efficient Industry 4.0 systems has driven the need to optimize production systems, where effective scheduling is crucial. In smart manufacturing, robots handle material transfers, making precise scheduling essential for seamless operations. However, research often oversimplifies the Robotic Flexible Job Shop problem by focusing only on transportation time, ignoring resource allocation and robot diversity. This study addresses these gaps, tackling a Multi-Robot Flexible Job Shop (MRFJS) scheduling problem with limited buffers. It involves non-identical parallel machines and robots with varying capabilities overseeing material handling under blocking conditions. The case study is based on a real Industry 4.0 scenario, where the layout restricts each robotic arm’s access, requiring strategic buffer placement for part transfers. A Mixed-Integer Programming (MILP) model aims to minimize makespan, followed by a new Genetic Algorithm (GA) using Roy and Sussman’s Alternative Graph. Computational tests on various scales and real data from a manufacturing plant demonstrate the GA’s efficacy in solving complex scheduling problems in real-world production settings. Based on the data, the Proposed Genetic Algorithm (PGA), with an average Relative Deviation (ARD) of 0.25%, performed approximately 34% better compared to the Basic Genetic Algorithm (BGA), with an average ARD of 0.38%. This percentage indicates that the PGA significantly outperforms in solving complex scheduling problems.

Unraveling the Meaning of Effective Uptake Coefficients in Multiphase and Aerosol Chemistry.

ConspectusReactions of gas phase molecules with surfaces play key roles in atmospheric and environmental chemistry. Reactive uptake coefficients (γ), the fraction of gas-surface collisions that yield a reaction, are used to quantify the kinetics in these heterogeneous and multiphase systems. Unlike rate coefficients for homogeneous gas- or liquid-phase reactions, uptake coefficients are system- and observation-dependent quantities that depend upon a multitude of underlying elementary steps. As such, uptake coefficients adopt complex scaling behavior with reactant concentrations and other physicochemical properties of the interface, making predictions of γ particularly challenging.Typically, γgas is obtained by measuring the loss rate of a gas-phase molecule above a liquid or solid surface, relative to its collision frequency. By definition, γgas ≤ 1. Highly efficient reactions proceed at or near the gas-surface collision frequency and exhibit values of γgas near unity. Alternatively, heterogeneous kinetics are often measured using the consumption rate of a condensed phase reactant normalized to the gas-surface collision frequency, yielding instead an effective uptake coefficient (γeff). In many cases, γeff and γgas are not equal, yielding additional insights into the nature of the reaction. For example, substantial diffusive limitations in the condensed phase may inhibit reactivity, yielding γeff ≪ γgas. In contrast, γeff > γgas in the presence of condensed phase secondary reactions, with values of γeff often exceeding 1 for the case of radical chain reactions.In this Account, we will discuss how measurements of γeff in aerosol can uniquely reveal the origins of complex physical and chemical behavior in multiphase reactions under laboratory conditions. For example, measurements of the scaling of γeff with shell thickness during the ozonolysis of core-shell aerosol yields insight into the relative transport and reaction time scales of gaseous oxidants, while measurements of γeff, as a function of relative humidity (RH) during OH radical oxidation of hygroscopic citric acid aerosol, highlight the role that mixing times of particle-phase reactants play in determining aerosol reaction kinetics. Additionally, the scaling of γeff with oxidant and trace gas concentrations during the oxidation of long-chain hydrocarbons in aerosols by OH radicals and chlorine atoms provides distinctive signatures of the underlying competition between free radical propagation and termination mechanisms. Finally, it is shown how changes in γeff that are induced by careful selection of the molecular structure of the particle-phase reactant help to identify new reaction pathways, such as alternative mechanisms for lipid peroxidation, and to report on the reaction kinetics of short-lived reactive species, including Criegee Intermediates. Together, these examples will demonstrate how proper experimental design and accurate measurements of an effective uptake coefficient can be used to interrogate the fundamental steps governing complex multiphase reaction mechanisms.

A Method for Imaging the Ischemic Penumbra with MRI using IVIM.

In acute ischemic stroke, the amount of "local" CBF distal to the occlusion, i.e. all blood flow within a region whether supplied antegrade or delayed and dispersed through the collateral network, may contain valuable information regarding infarct growth rate and treatment response. DSC CBF using a local arterial input function (AIF) is one method of quantifying local CBF (local-qCBF) and correlates with collaterals. Similarly, intravoxel incoherent motion MRI (IVIM) is "local", with excitation and readout in the same plane, and a potential alternative way to measure local-qCBF. The purpose of this work was to compare IVIM local-qCBF against DSC local-qCBF in the ischemic penumbra, compare measurement of perfusion-diffusion mismatch (PWI/DWI), and examine if local-qCBF may improve prediction of final infarct. Eight experiments in a pre-clinical canine model of middle cerebral artery occlusion were performed; native collateral circulation was quantified via x-ray DSA 30 minutes post-occlusion, and collateralization was subsequently enhanced in a subset of experiments with simultaneous pressor and vasodilator. IVIM and DSC MRI were acquired 2.5hr post-occlusion. IVIM was post-processed to return local-qCBF from fD*, water transport time (WTT) from D*, diffusion from D, and the PWI/DWI mismatch. These were compared with DSC parameters processed first with a standard global-AIF and then with a local-AIF. These DSC parameters included time-to-maximum, local MTT, standard-qCBF, local-qCBF and PWI/DWI mismatch. Infarct volume was measured with DWI at 2.5hrs and 4hrs post-occlusion. 2.5hr post-occlusion, IVIM local-qCBF in the non-infarcted ipsilateral territory strongly correlated with DSC local-qCBF (slope=1.00, R2=0.69, Lin's CCC=0.71). Correlation was weaker between IVIM local-qCBF and DSC standard-qCBF (R2=0.13). DSC localqCBF and IVIM local-qCBF in the non-infarcted ipsilateral territory both returned strong prediction of final infarct volume (R2=0.78, R2=0.61 respectively). DSC standard-qCBF was a weaker predictor (R2=0.12). The hypoperfused lesion from DSC local-qCBF and from IVIM local-qCBF both predicted final infarct volume with good sensitivity and correlation (slope=2.08, R2=0.67, slope=2.50, R2=0.68 respectively). The IVIM PWI/DWI ratio was correlated with infarct growth (R2=0.70) and WTT correlated with DSC MTT (R2=0.60). Non-contrast IVIM measurement of local-qCBF and PWI/DWI mismatch may include collateral circulation and improve prediction of infarct growth. AIF: arterial input function, IVIM: intravoxel incoherent motion, qCBF: quantitative cerebral blood flow, WTT: water transport time, MCAO: middle cerebral artery occlusion, MD: mean diffusivity.

Modelling of non-scheduled air transportation time series based on ARIMA

Forecasting non-scheduled air transportation demand is essential for effective resource allocation, operational planning, and decision-making. In this paper, the use of the ARIMA (Auto Regressive Integrated Moving Average) model for forecasting non-scheduled air transportation is explored. The ARIMA model is a widely employed time series forecasting technique which combines autoregressive (AR), differencing (I), and moving average (MA) components. It has been successfully applied to various fields and can be adapted to capture the patterns and trends in non-scheduled air transportation data. To forecast non-scheduled air transportation demand, historical data, including relevant variables are firstly collected. The data are processed by identifying and addressing any missing values, outliers, or trends that could affect the model's performance. Next, the ARIMA model is applied to the pre-processed data, utilising techniques such as model identification, parameter estimation, and model diagnostics. The ARIMA model captures the relationships between past observations and uses them to predict future demand for non-scheduled air transportation. The forecasting results from the ARIMA model provide insights into expected demand levels, peak periods, and potential fluctuations in non-scheduled air transportation. These forecasts enable decision-makers to optimise resource allocation, schedule aircraft availability, and enhance operational efficiency. However, it is important to note that the accuracy of ARIMA forecasts depends on various factors, including the quality and representativeness of the data, the appropriate selection of model parameters, and the stability of underlying patterns in the time series data. Regular model evaluation and refinement are crucial in maintaining forecasting accuracy.

Impact of Transportation Time on Inventory Management Costs: Analyzing the Relationship in Food Waste Management

Impact of Transportation Time on Inventory Management Costs: Analyzing the Relationship in Food Waste Management

Room-temperature spin-conserved electron transport to semiconductor quantum dots using a superlattice barrier.

To realize the optical transfer of electron spin information, developing a semiconductor layer for efficient transport of spin-polarized electrons to the active layers is necessary. In this study, electron spin transport from a GaAs/Al0.3Ga0.7As superlattice (SL) barrier to In0.5Ga0.5As quantum dots (QDs) is investigated at room temperature through a combination of time-resolved photoluminescence and rate equation analysis, separating the two transport processes from the GaAs layer around the QDs and SL barrier. The electron transport time in the SL increases for a thicker quantum well (QW) of SL due to the weaker wavefunction overlap between adjacent QWs. Additionally, the degree of conservation of spin polarization during transport varies with QW thickness. Rate equation analysis demonstrates an electron transport from SL to QDs while maintaining a high spin polarization for thick QWs. The achieved spin-conserved electron transport can be attributed to the combination of electron transport being sufficiently faster than the spin relaxation in SL and the suppressed spin relaxation in the p-doped GaAs layer capping the QDs. The findings indicate that SL is a promising candidate as an electron spin transport layer for optical spin devices.

Noninvasive blood-brain barrier integrity mapping in patients with high-grade glioma and metastasis by multi-echo time-encoded arterial spin labeling.

In brain tumors, disruption of the blood-brain barrier (BBB) indicates malignancy. Clinical assessment is qualitative; quantitative evaluation is feasible using the K2 leakage parameter from dynamic susceptibility contrast MRI. However, contrast agent-based techniques are limited in patients with renal dysfunction and insensitive to subtle impairments. Assessing water transport times across the BBB (Tex) by multi-echo arterial spin labeling promises to detect BBB impairments noninvasively and potentially more sensitively. We hypothesized that reduced Tex indicates impaired BBB. Furthermore, we assumed higher sensitivity for Tex than dynamic susceptibility contrast-based K2, because arterial spin labeling uses water as a freely diffusible tracer. We acquired 3T MRI data from 28 patients with intraparenchymal brain tumors (World Health Organization Grade 3 & 4 gliomas [n = 17] or metastases [n = 11]) and 17 age-matched healthy controls. The protocol included multi-echo and single-echo Hadamard-encoded arterial spin labeling, dynamic susceptibility contrast, and conventional clinical imaging. Tex was calculated using a T2-dependent multi-compartment model. Areas of contrast-enhancing tissue, edema, and normal-appearing tissue were automatically segmented, and parameter values were compared across volumes of interest and between patients and healthy controls. Tex was significantly reduced (-20.3%) in contrast-enhancing tissue compared with normal-appearing gray matter and correlated well with |K2| (r = -0.347). Compared with healthy controls, Tex was significantly lower in tumor patients' normal-appearing gray matter (Tex,tumor = 0.141 ± 0.032 s vs. Tex,HC = 0.172 ± 0.036 s) and normal-appearing white matter (Tex,tumor = 0.116 ± 0.015 vs. Tex,HC = 0.127 ± 0.017 s), whereas |K2| did not differ significantly. Receiver operating characteristic analysis showed a larger area under the curve for Tex (0.784) than K2 (0.604). Tex is sensitive to pathophysiologically impaired BBB. It agrees with contrast agent-based K2 in contrast-enhancing tissue and indicates sensitivity to subtle leakage.

Longer Total Interhospital Transfer Times for Rural Sepsis Patients Not Associated with Increased Mortality

ABSTRACT OBJECTIVES Sepsis is a time-sensitive condition, and many rural emergency department (ED) sepsis patients are transferred to tertiary hospitals. The objective of this study was to determine whether longer transport times during interhospital transfer are associated with higher sepsis mortality or increased hospital length-of-stay (LOS). METHODS A cohort of rural adult (age ≥ 18y) sepsis patients transferred between hospitals were identified in the TELEmedicine as a Virtual Intervention for Sepsis Care in Emergency Departments (TELEVISED) parent study. We collected data on the time spent between triage and disposition at the rural ED (ED LOS), time from rural ED disposition to arrival at the destination hospital (transport duration), and overall time from rural ED triage to arrival at the destination hospital (total transfer time). We used a zero inflated negative binomial model with log link for the primary outcome (28-day hospital-free days), and a logit model for secondary outcomes of Surviving Sepsis Campaign (SSC) bundle adherence and in-hospital mortality. We included clinical and demographic covariates in model development. RESULTS We included 359 transferred rural sepsis patients. There was no association between ED LOS (aRR: 1.00; 95% CI: 0.98-1.02), transport duration (aRR: 1.03; 95% CI: 0.99-1.07), or total transfer time (aRR: 1.01; 95% CI: 0.99-1.03) and 28-day hospital free days. Similarly, we found no association between ED LOS, transport duration, and total transfer time with secondary outcomes. CONCLUSIONS Longer total transfer time showed no association with 28-day hospital free days in rural sepsis patients. Future work will seek to better understand how rural ED sepsis care can be optimized to maximize outcomes in transferred patients.