Evaluation of Transfer Efficiency between Subway and Bus Based on the Interval Number Ranking Method by Employing Probability Reliability: Taking Ningbo for Example

In recent years, the construction and operation of urban subways have been gradually increasing in developing countries. In the next step, more attention should be paid to the transfer efficiency between subway and bus so as to improve the travel efficiency of more urban residents. This paper uses the probability credibility interval number ranking method to evaluate the bus transfer efficiency. Firstly, this study obtains the dynamic transfer time data by matching individual smart card and subway/bus global positioning system (GPS) records, which is used to evaluate the transfer efficiency of corresponding subway stations. Then, we establish a probability density function to represent the characteristic information of transfer time. Accordingly, the probability reliability model of the order relation of interval numbers can be constructed. In the end, the method is applied to evaluate the transfer efficiency between subway and bus stations in Ningbo. Compared to the traditional interval number ranking method, the evaluation result shows that this method can get a more objective transfer efficiency order relation. The reason is that this method can not only consider the random feature of transfer time but also make use of the data distribution characteristics. This method could be applied to obtain the stations with relatively low transfer efficiency and the feedback can be used for bus line operation and station layout improvement.

Characteristics associated with delays in decision to transfer injured patients

Introduction The regionalized nature of trauma care necessitates interfacility transfer which is vulnerable to delays given its complexity. Little is known about the interval of time a patient spends at the sending hospital prior to when the transfer is initiated—the “decision to transfer” time. This primary objective of the study was to explore the impact of patient, environmental, and institutional characteristics on decision to transfer time. Methods This was a retrospective cohort study of injured adult patients who underwent emergent interfacility transfer by a provincial critical care transport organization over a 31-month period. Quantile regression was used to evaluate the impact of patient, environmental, and institutional characteristics on the time to decision to transfer. Results A total of 1128 patients were included. The median decision to transfer time was 2.42 h and the median total transport time was 3.12 h. The following variables were associated with an increase in time to decision to transfer at the 90th percentile of time: age >75 (+2.47 h), age 66–75 (+3.70 h), age 56–65 (+1.20 h), transfer between 00:00 and 07:59 (+2.08 h), and transfer in the summer (+2.25 h). The following variables were associated with a decrease in time to decision to transfer at the 90th percentile of time: Glasgow Coma Scale 3–8 (−2.21 h), respiratory rate >30 (−2.01 h), sending site being a community hospital with <100 beds (−4.11 h), or the sending site being a nursing station (−5.66 h). Conclusion Time to decision to transfer was a sizable proportion of the patients interfacility transfer. Older patients were associated with a delay in decision to transfer as were patients transferred overnight and in the summer. These findings may be used to support the implementation of geriatric trauma triage guidelines and promote ongoing education and quality improvement initiatives to decrease delay.

Abstract 1122‐000159: Area Deprivation Index and Transfer Likelihood Offer Insight into Improving Stroke Care Access Equity

Introduction : Time is brain for stroke care. Socioeconomic disparities may have an impact on timely access to stroke care. A well known factor that affects access to thrombectomy is the necessity for transfer from a non‐thrombectomy capable center to a thrombectomy capable center (TSC). The Area Deprivation Index (ADI) is a validated, neighborhood‐level composite measure (scored 1–100) which uses income, education, employment, housing quality, and other factors to identify geographic areas with increased need. We analyzed the association between ADI and requirement of transfer prior to thrombectomy to further understand how establishment of TSCs in areas with higher ADI and severity score bypass protocols can increase access to stroke care across all ranges of socioeconomic need. Methods : We obtained transfer status and the duration of the transfer time for all thrombectomy patients treated between 2016 and 2021 in a large, urban multi‐hospital health system and matched them with their respective census‐tract level ADI scores from Neighborhood Atlas, with a higher ADI score signifying lower socioeconomic status. Preliminary analysis utilized logistic regression to compare the ADI between transfer and non‐transfer cases. Further exploration observed temporal changes to the percentage of patients requiring transfer across 4 ADI ranges. Results : Among 513 cases for which we had a pick up address for between 2016–2021, the average ADI of pick‐up locations was 10.3 (range: 1 ‐ 70.5). ADI was significantly predictive of transfer status (p = 0.0004), with a 1 unit increase in ADI increasing the odds of being transferred by 1.035. Patients requiring transfer took an average of 2.7 hours longer to thrombectomy compared to non‐transfer patients. However, within the transfer population, a higher ADI did not correlate with increased transfer time. Across all ADI ranges, the likelihood of transfer began to decrease in 2018. This is likely due to the establishment of a new TSC in 2018 as well as the implementation of an EMS triage protocol transporting patients with a higher severity of stroke directly to TSCs. Notably, patients in the highest ADI range did not experience decreased likelihood of transfer until 2020, correlating with establishment of another TSC. Conclusions : Across urban census tracts, patients with a higher ADI had an increased likelihood of transfer, and hence delay in access to thrombectomy. Equity to access to thrombectomy improved over time. Expanding thrombectomy access as well as establishing EMS triage protocols appear to correlate with improvement in access to stroke thrombectomy care for patients with higher ADI.

Signatures of Quantum Interference in the Time Dependence of Charge Transfer in Donor–Bridge–Acceptor Molecules

Numerical solution of the time-dependent Schrödinger equation is combined with a statistical procedure for analyzing the time-dependent probability density to look for signatures of quantum phase interference in charge transfer across two donor–bridge–acceptor molecules. The results show a strong dependence of transfer time on relative phase in an initially localized state. Additionally, the transfer time shows a stronger dependence on molecular symmetry for asymmetric initial localizations than symmetric initial localizations.

Factors contributing to delay intensive care unit admission of critically ill patients from the adult emergency Department in Tikur Anbessa Specialized Hospital

Background The transfer time for critically ill patients from the emergency department (ED) to the Intensive care unit (ICU) must be minimal; however, some factors prolong the transfer time, which may delay intensive care treatment and adversely affect the patient’s outcome. Purpose To identify factors affecting intensive care unit admission of critically ill patients from the emergency department. Patients and methods A cross-sectional study design was conducted from January 13 to April 12, 2020, at the emergency department of Tikur Anbesa Specialized Hospital. All critically ill patients who need intensive care unit admission during the study period were included in the study. A pretested structured questionnaire was adapted from similar studies. The data were collected by chart review and observation. Then checked data were entered into Epi-data version 4.1 and cleaned data was exported to SPSS Version 25 for analysis. Descriptive statistics, bivariate and multivariate logistic regression were used to analyze the data. Result From the total of 102 critically ill patients who need ICU admission 84.3% of them had prolonged lengths of ED stay. The median length of ED stay was 13.5 h with an IQR of 7–25.5 h. The most common reasons for delayed ICU admission were shortage of ICU beds 56 (65.1%) and delays in radiological examination results 13(15.1%). On multivariate logistic regression p < 0.05 male gender (AOR = 0.175, 95% CI: (0.044, 0.693)) and shortage of ICU bed (AOR = 0.022, 95% CI: (0.002, 0.201)) were found to have a significant association with delayed intensive care unit admission. Conclusion there was a delay in ICU admission of critically ill patients from the ED. Shortage of ICU bed and delay in radiological investigation results were the reasons for the prolonged ED stay.

Revising the Classic Computing Paradigm and Its Technological Implementations

Today’s computing is based on the classic paradigm proposed by John von Neumann, three-quarters of a century ago. That paradigm, however, was justified for (the timing relations of) vacuum tubes only. The technological development invalidated the classic paradigm (but not the model!). It led to catastrophic performance losses in computing systems, from the operating gate level to large networks, including the neuromorphic ones. The model is perfect, but the paradigm is applied outside of its range of validity. The classic paradigm is completed here by providing the “procedure” missing from the “First Draft” that enables computing science to work with cases where the transfer time is not negligible apart from the processing time. The paper reviews whether we can describe the implemented computing processes by using the accurate interpretation of the computing model, and whether we can explain the issues experienced in different fields of today’s computing by omitting the wrong omissions. Furthermore, it discusses some of the consequences of improper technological implementations, from shared media to parallelized operation, suggesting ideas on how computing performance could be improved to meet the growing societal demands.

Multi Frequency Isotopes Survey to Improve Transit Time Estimation in a Situation of River-Aquifer Interaction

The Barthelasse alluvial aquifer is used to supply water to 180,000 inhabitants. The pumping field is located less than 200 m from the Rhône and is 100% fed by water from the Rhône, which makes it particularly vulnerable to any pollution from the Rhône. Between the Rhône and the pumping field is a Girardon unit, an arrangement that can be found regularly along the banks of the lower and middle reaches of the Rhône, and whose role is to stabilise the banks (alluvial deposits) and to facilitate river navigation. In order to know the transfer times between the Rhône and the pumping field, fortnightly monitoring was carried out over a hydrological year, as well as hourly monitoring during a flood in the winter of 2019. The Rhône shows a cyclicality in its isotopic signature with enrichment in heavy isotopes during the winter period, particularly during floods, and a depletion during the summer period. This variation is found well within the associated alluvial aquifer. The application of LPMs models showed that the average transfer time between the Rhône and the Girardon unit was 20 days and 50 days between the Rhône and the Barthelasse pumping. This study highlighted the importance of using several sampling frequencies to consider the diversity of hydrological situations. For the Rhône, event-based monitoring (flooding) proved to be relevant to account for isotopic variability throughout the year. This work also highlighted the impact of the disruption of hydraulic exchanges between the river and the water table caused by the presence of the Girardon unit in terms of the propagation of contaminants.

Which scaling rule applies to large artificial neural networks

Experience shows that cooperating and communicating computing systems, comprising segregated single processors, have severe performance limitations, which cannot be explained using von Neumann’s classic computing paradigm. In his classic “First Draft,” he warned that using a “too fast processor” vitiates his simple “procedure” (but not his computing model!); furthermore, that using the classic computing paradigm for imitating neuronal operations is unsound. Amdahl added that large machines, comprising many processors, have an inherent disadvantage. Given that artificial neural network’s (ANN’s) components are heavily communicating with each other, they are built from a large number of components designed/fabricated for use in conventional computing, furthermore they attempt to mimic biological operation using improper technological solutions, and their achievable payload computing performance is conceptually modest. The type of workload that artificial intelligence-based systems generate leads to an exceptionally low payload computational performance, and their design/technology limits their size to just above the “toy” level systems: The scaling of processor-based ANN systems is strongly nonlinear. Given the proliferation and growing size of ANN systems, we suggest ideas to estimate in advance the efficiency of the device or application. The wealth of ANN implementations and the proprietary technical data do not enable more. Through analyzing published measurements, we provide evidence that the role of data transfer time drastically influences both ANNs performance and feasibility. It is discussed how some major theoretical limiting factors, ANN’s layer structure and their methods of technical implementation of communication affect their efficiency. The paper starts from von Neumann’s original model, without neglecting the transfer time apart from processing time, and derives an appropriate interpretation and handling for Amdahl’s law. It shows that, in that interpretation, Amdahl’s law correctly describes ANNs.