Delay Operator Research Articles

The Positive Value of Rotation-Specific Guides for Resident Education and Patient Care: A Process Improvement Study.

IntroductionProviding high-quality cost-effective patient care requires knowledge of treatment protocols as well as an understanding of the institution's procedures, e.g., what orders to place and how to effectively place them. Disseminating rotation-specific evidence-based practice and institutional policies in a timely manner to medical residents rotating onto a service can be challenging. We determined, by root cause analysis, that a solution was to use a structured guide containing rotation-specific information. The purpose of this study was to evaluate the effectiveness of a rotation-specific pocket reference guide to distribute evidence-based and rotation-specific practice information to medical residents rotating through an Academic Vascular Surgery service and to evaluate this tool’s ability to increase participants’ perception of comfort and efficacy, all of which can be linked to high-quality and cost-effective patient care.Materials and methodsWe conducted a prospective study at the Detroit Medical Center, a Michigan-based level one trauma hospital, from November 2020 through February 2021. The inclusion criteria included medical residents that were on the Vascular Surgery rotation in the given time frame and that agreed to take a pre-/post-evaluation. The evaluation consisted of a quantitative test and a qualitative questionnaire. A t-test was used to analyze pre- and post-question score averages.ResultsThere was a significant improvement in quantifiable knowledge as participants’ scores increased on post-rotation testing scoring with an average of 88% post-rotation compared to 58% pre-rotation (p<0.01). Ancillary staff reported a decrease in incorrect orders, substantiating increased efficacy and inferring cost-effectiveness. Individuals evaluated post-rotation indicated the usefulness of the guide as an educational tool for the dissemination of evidence-based practice (p<0.01) and increased confidence in placing preoperative orders (p<0.01). This, coupled with a post-rotation increase in preference toward a written learning style, led to the additional conclusion that this guide would be a beneficial preparatory tool for future board examinations. ConclusionsThis study supports the implementation of rotation guides as a preparatory source used to improve the dissemination of rotation-specific information, which should increase resident efficacy, improve cost-effectiveness, and potentially improve future board examination scores. We recommend a chart review of specified metrics, e.g., incorrect order frequency and related operative delays, to show to what extent the cost-effectiveness and increase in high-quality patient care manifested.

Stability Analysis of Pseudo-Almost Periodic Solution for a Class of Cellular Neural Network with D Operator and Time-Varying Delays

Cellular neural networks with D operator and time-varying delays are found to be effective in demonstrating complex dynamic behaviors. The stability analysis of the pseudo-almost periodic solution for a novel neural network of this kind is considered in this work. A generalized class neural networks model, combining cellular neural networks and the shunting inhibitory neural networks with D operator and time-varying delays is constructed. Based on the fixed-point theory and the exponential dichotomy of linear equations, the existence and uniqueness of pseudo-almost periodic solutions are investigated. Through a suitable variable transformation, the globally exponentially stable sufficient condition of the cellular neural network is examined. Compared with previous studies on the stability of periodic solutions, the global exponential stability analysis for this work avoids constructing the complex Lyapunov functional. Therefore, the stability criteria of the pseudo-almost periodic solution for cellular neural networks in this paper are more precise and less conservative. Finally, an example is presented to illustrate the feasibility and effectiveness of our obtained theoretical results.

Traffic Performance Evaluation for Selected Streets within the Southern Part of Al-Najaf City Network

Urban streets are essential parts in cities and their development can enhance various aspects of economic life and social activities. Al-Najaf city is one of the Iraqi developing cities that has been suffering from traffic congestion at various sections of its street network. The reasons, locations and intensities of these congestions are important to be regularly diagnosed for two key reasons: first, in order to choose the right traffic engineering solutions and second to adequately prioritize the funding required for planning and implementing the traffic management programs for these congested sections. This paper attempts to evaluate the performance of the main urban streets located within the southern part of Al-Najaf city street network during evening peak hours. The methodology includes collecting field data and conducting traffic surveys such as traffic volume, travel time and free flow speed surveys. The evaluating approaches illustrated in the U.S Highway Capacity Manual are adopted as a tool for assessing the operational performance for the selected urban streets. The results reveal that there are several segments that operate at their capacity (LOS E) or even under congested flow condition (LOS F). The analysis also shows that whereas some segments are with good LOS using volume-capacity ratio (v/c) criterion, they are actually with low LOS based on field observations or when using travel time as a performance measure. This indicates the inadequacy of using v/c ratio alone in evaluating urban streets because part of the congestion at such streets is due to side friction operational delays rather than over traffic demand.

A Decision Support Tool for Long-Term Planning of Marine Operations in Ocean Energy Projects

Ocean energy is a relevant source of clean renewable energy, and as it is still facing challenges related to its above grid-parity costs, tariffs intended to support in a structured and coherent way are of great relevance and potential impact. The logistics and marine operations required for installing and maintaining these systems are major cost drivers of marine renewable energy projects. Planning the logistics of marine energy projects is a highly complex and intertwined process, and to date, limited advances have been made in the development of decision support tools suitable for ocean energy farm design. The present paper describes the methodology of a novel, opensource, logistic and marine operation planning tool, integrated within DTOceanPlus suite of design tools, and responsible for producing logistic solutions comprised of optimal selections of vessels, port terminals, equipment, as well as operation plans, for ocean energy projects. Infrastructure selection logistic functions were developed to select vessels, ports, and equipment for specific projects. A statistical weather window model was developed to estimate operation delays due to weather. A vessel charter rate modeling approach, based on an in-house vessel database and industry experience, is described in detail. The overall operation assumptions and underlying operating principles of the statistical weather window model, maritime infrastructure selection algorithms, and cost modeling strategies are presented. Tests performed for a case study based a theoretical floating wave energy converter produced results in good agreement with reality.

Impact of weather conditions on airport arrival delay and throughput

PurposeWeather events have a significant impact on airport arrival performance and may cause delays in operations and/or constraints in airport capacity. In Europe, almost half of all regulated airport traffic delay is due to adverse weather conditions. Moreover, the closer airports operate to their maximum capacity, the more severe is the impact of a capacity loss due to external events such as weather. Various weather uncertainties occurring during airport operations can significantly delay some arrival processes and cause network-wide effects on the overall air traffic management (ATM) system. Quantifying the impact of weather is, therefore, a key feature to improve the decision-making process that enhances airport performance. It would allow airport operators to identify the relevant weather information needed, and help them decide on the appropriate actions to mitigate the consequences of adverse weather events. Therefore, this research aims to understand and quantify the impact of weather conditions on airport arrival processes, so it can be properly predicted and managed.Design/methodology/approachThis study presents a methodology to evaluate the impact of adverse weather events on airport arrival performance (delay and throughput) and to define operational thresholds for significant weather conditions. This study uses a Bayesian Network approach to relate weather data from meteorological reports and airport arrival performance data with scheduled and actual movements, as well as arrival delays. This allows us to understand the relationships between weather phenomena and their impacts on arrival delay and throughput. The proposed model also provides us with the values of the explanatory variables (weather events) that lead to certain operational thresholds in the target variables (arrival delay and throughput). This study then presents a quantification of the airport performance with regard to an aggregated weather-performance metric. Specific weather phenomena are categorized through a synthetic index, which aims to quantify weather conditions at a given airport, based on aviation routine meteorological reports. This helps us to manage uncertainty at airport arrival operations by relating index levels with airport performance results.FindingsThe results are computed from a data set of over 750,000 flights on a major European hub and from local weather data during the period 2015–2018. This study combines delay and capacity metrics at different airport operational stages for the arrival process (final approach, taxi-in and in-block). Therefore, the spatial boundary of this study is not only the airport but also its surrounding airspace, to take both the arrival sequencing and metering area and potential holding patterns into consideration.Originality/valueThis study introduces a new approach for modeling causal relationships between airport arrival performance indicators and meteorological events, which can be used to quantify the impact of weather in airport arrival conditions, predict the evolution of airport operational scenarios and support airport decision-making processes.

The Influence of Electric-Arc-Furnace Input Feeds on its Electrical Energy Consumption

Operation of the electric arc furnaces (EAFs) is a subject to consider fluctuations in terms of its key performance indicators, such as the electrical energy consumption (EEC), tap-to-tap time, steel yield, and others. In this paper, a more detailed analysis of the electric arc furnace data is performed, investigating its EEC. It is well known that the EEC is affected by the weight and the type of charged scrap, the operational delays, and the tapping temperature. On the other hand, one can also deduce that the feeds, such as the carbon and the oxygen, could also affect the EEC, due to their role in redox equations and impact to the bath energy balance. Therefore, special attention is devoted to the analysis of the carbon-to-oxygen ratio during the electric arc furnace operation and the consequent influence of the oxygen availability on the EEC. Statistical analysis of more than 2500 heats of data, which were clustered according to the produced steel grade and the charged scrap mixture, has revealed that besides the beforementioned factors, fluctuations in EEC could appear also due to different amounts of added carbon and oxygen. Since the furnace operators usually rely on predefined guidelines and their own experience when actuating the furnace, a simplistic statistical approach can be used to reveal some of the weaknesses in the control routines, which can be used as a starting point to improve their actuation, leading to decreased energy consumption.Graphical

Ports and climate uncertainty: An economic imperative for India

ABSTRACT Seaports are an indispensable asset in interconnected and interdependent global supply chains. Their complex infrastructural and operational systems and critical foreland and hinterland networks make ports a vital nodal point in the economic progress of nations at large, and the coastal urban agglomerations in particular. These critical maritime assets are currently under threat from the disruptive impacts of anthropogenic climate change, such as sea-level rise and intensifying extreme weather events. The economic losses from these impacts will span a wide range, from hard infrastructural damages to operational delays in supply chain management. Incorporating climate resilience in existing and new port infrastructure remains a complex challenge that will require port authorities to confront the problem of climate uncertainty and its socio-economic implications. This article focuses on seaports in the Indian context to highlight the complex threats of climate change. It examines the main debates on climate uncertainty and policymaking, path dependencies in port planning, global best practices, knowledge gaps and strategies that will be critical for Indian ports to better confront climate change induced disruptions in the near future.

Legal Regulation of The Civil Liability of The Air Carrier for Damages to The Goods Authors Amera Jaafar Shareef

The main focus of this research will revolve around the topic of damage to goods during air transport operations (aviation accidents, delay and cancellation of flights, poor level of services) as it deals with the legal basis for the liability of the air carrier for damage to goods and compensation for the damages caused under the international laws and agreements, especially in light of the increase in the percentage of aviation accidents and the aggravation of damages that has resulted in a low level of confidence and protection of consumers rights. The research will further emphasis on the nature of air carrier, the scope of air transport contract, the elements of the responsibility of the air carrier, the liability claim, the position of Iraqi laws and regulation in comparison with the international agreements on the responsibility of the air carrier for damage to goods. The research reached several results, the most important finding is on the basis of the responsibility of the carrier found in the Warsaw Convention which highlights the fault of the air carrier, but the fault can be proven otherwise under the international agreements, especially the Warsaw Agreement adopted by comparative laws, have been self-regulating when dealing with provisions for passenger transport by air, despite this and as a result of the bifurcation of air transport operations. This agreement failed to take into account the regulation of all the rights granted to passengers as a result of the air transport process and the damages that they suffer as a result of that process. &nbsp;The research recommendations are primarily initiated on the responsibility of the air carrier where the foundation lays on bearing dependency and that the responsibility of the air carrier should be based on the liability and the obligation to provide compensation. Furthermore, the legislator has to distinguish between the responsibility of the carrier for the personal injuries caused to the passengers and the goods more precisely, and to encourage air transport companies with a decent financial position to invest in this field, and operate on the basis to provide full compensation for moral damages in addition to the material damage and to offer full clarification in this regard.

Impact of Anticipatory Batching of Pharmacy Compounded Sterile Products on Time to Nurse Administration

Background: Timely medication administration is integral to patient care, and operational delays can challenge timely administration. Within an inpatient pharmacy of an academic medical center, intravenous medications were historically compounded on a patient-specific basis. In 2020, the pharmacy began batching frequently-utilized medications. This analysis explored the impact of compounded sterile batching on pharmacy and nursing services. Methods: This pre- and post-interventional study compared data from February through March 2020 with a seasonally matched period from 2019. The primary endpoint was difference in time to administration of urgent (STAT) medications. Secondary endpoints included timeframes for a pharmacy technician to prepare, a pharmacist to check, and a nurse to administer the medications, as well as reprinted labels and estimated waste. Results: On average, it took one hour and 43 minutes to administer a STAT medication in 2019 and one hour and 57 minutes in 2020 (p = 0.122). It took about four hours to administer routine medications in 2019 and 2020 (p = 0.488). The number of labels reprinted decreased from 616 in 2019 to 549 in 2020 (p = 0.195), relating to decreased missing doses. The mean time to check and send a medication decreased from 2019 to 2020 for STAT orders (p < 0.001), and there was no difference in wasted medications looking at all orders in this time. Conclusion: Anticipatory batching decreased time to prepare, check, and send medications, though there was no effect on waste or on time to administration. Future studies can examine the correlation between pharmacy operations and medication administration.

Rapid administration of undiluted intravenous levetiracetam.

Operational delays have the potential to lead to suboptimal time to seizure control during status epilepticus. Levetiracetam (LEV) is an urgent control antiepileptic medication that offers relative lack of adverse effects and ease of monitoring. There are limited data published demonstrating safety and tolerability of undiluted rapid intravenous (IV) push of LEV in doses of 1000mg or less. The purpose of this study was to evaluate the safety of IV push administration of LEV doses up to 4500mg. This is a retrospective, observational, cohort analysis of adult patients who received at least one dose of undiluted IV push LEV from October 15, 2019 to August 31, 2020 at a large academic medical center in Phoenix, Arizona. Outcomes of interest include safety and tolerability of rapid administration of undiluted LEV. There were 953 unique patients included during the study period. LEV was a new medication for witnessed or suspected seizure in 51.9% of patients, and 40.7% of patients had a documented history of epilepsy or seizure disorder. There were 8561 undiluted IV push LEV doses administered, 3674 (42.9%) of which were greater than 1000mg. LEV was administered most often through a peripheral IV (79.1%). There were 12 patients with documented adverse drug events during the study period, with four potentially directly related to IV push LEV administration. These events were limited to local injection site reactions and included redness, burning, and loss of a peripheral IV line. Rapid IV administration of undiluted LEV is both safe and tolerable in doses of up to 4500mg, allowing for rapid drug administration, which is paramount during neurologic emergencies.

Parameter identification of fractional-order time delay system based on Legendre wavelet

This paper proposes a parameter identification method of fractional-order time delay system based on Legendre wavelet. An integration operational matrix and delay operational matrix of a Legendre wavelet are constructed. The process is derived to convert a fractional-order time delay system based on a Legendre wavelet operational matrix to algebraic equation. The least squares method is used to simultaneously estimate the order, model parameters and time delay coefficient of a system. In addition, wavelet decomposition and reconstruction algorithm are used to pre-process the output signal, which separate the noise from signal. The proposed method overcomes the initial-state dependence and randomness of the identification result in the algebraic solution of the traditional operational matrix, and reduces the effect of noise on the accuracy of parameter identification. It is especially suitable for engineering application. The effectiveness is verified by numerical simulation and a temperature process control system.

Remotely operated vehicle-based methodology for the reduction of costs and operational delays associated with rock dredging for channel deepening

Rock dredging for river channel deepening presents problems concerning the identification of whether the blasted rock is properly fragmented for the following operations and whether the excavation and disposal reach the determined project level. These issues lead to decision making that involves expensive equipment and vessel movement procedures that can result in an increase in costs and time. After characterizing and analyzing all underwater blasting and rock excavation procedures, a new methodology was developed to improve this process by applying a low-cost observation remotely operated vehicle. The tasks of the vehicle focus on monitoring and controlling some key procedures, improving the operating time and identifying operation fail points, in addition to helping to control the environmental impact. The proposed methodology was tested in São Paulo, Brazil, where the deepening of a river channel has been used to expand the waterway. The results of the tests show a 37% saving in time and a 32% saving in cost

The Comparative Influence of 2 and 4Weeks Preoperative Antituberculosis Treatment on Spinal Tuberculosis Surgery: A Multicenter, Prospective, Randomized Clinical Trial.

IntroductionA trade-off between successful surgery and minimizing the operation delay for patients with spinal tuberculosis (TB) is a major consideration to determine the duration of preoperational anti-TB treatment (AAT). In this study, 2 and 4 weeks preoperative AAT durations were compared for their influence on the operation outcomes.MethodA multicenter, prospective, randomized trial was conducted in four hospitals in China. New patients with spinal TB were recruited and randomly allocated to two groups (2 or 4 weeks’ preoperative treatment) and administered the standardized first-line anti-TB drugs. The symptom changing and indicators reflecting recovery and side effects of the treatment were monitored. Patient was followed up for another 18 months after completion of treatment.ResultsIn total, 150 eligible patients were enrolled between June 2014 and December 2016, and 13 patients were excluded after the enrollment. The remaining 137 participants were randomly allocated to the 2-week group (n = 68) or the 4-week group (n = 69). These two groups acquired similar surgical outcomes, considering wound healing rate within 3 months after the operation (94.20%, 65/69 vs 89.71%, 61/68; P = 0.333) and bony fusion rate within 6 months (98.46%, 64/65 vs 95.45%, 63/66; P = 0.317). However, the culture positive rate of pus collected during operation in the 4-week group (41.94%) was significantly lower than that of the 2-week group (60.94%, P = 0.033). No reoccurrence of disease was observed in either group during the 18-month follow-up period.ConclusionPatients with spinal TB administered 2 or 4 weeks of preoperative anti-TB treatment acquired similar surgical outcomes. However, patients who underwent the operation sooner suffered 2 weeks less agony from the disease.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40121-021-00462-2.

IDENTIFICATION OF FACTORS LEADING TO EXCESSIVE WAITING TIME AT THE PHARMACY UNIT OF HEALTH CLINICS IN TEMERLOH DISTRICT, PAHANG, MALAYSIA

Excessive patient waiting time at dispensing pharmacies is attributed to workflow inefficiencies that are difficult to isolate. The objectives of this study are to quantify current operational process and delay times and also to identify bottlenecks that lead to excessive waiting time at the pharmacy unit of primary health clinics in Temerloh district. A multicentre observational cohort study was conducted at a Pharmacy Unit of Bandar Mentakab Health Clinic (KKBM), Temerloh Health Clinic (KKT) and Tanjung Lalang Health Clinic (KKTL). Stopwatch technique was applied for all four operational procedures (greeting, data entry, filling and dispensing) based on workflow analysis. Data collection forms were used to identify factors and their impact on process time. Major components causing long waiting times were found in delay segments. Significant time delay occurred before greeting at KKT; before data entry at KKBM, KKT and KKTL; and before dispensing at KKTL. Among factors found affecting process segment in data entry include presence of intervention and psychotropic substances in the prescription. Filling process was found to be delayed by the presence of more than three items, cold items, intervention and psychotropic substances in the prescription. In addition, dispensing process was found to be delayed by errors in data entry and filling. This study identified several common bottlenecks and isolated issues specific to each pharmacy unit of three health clinics that lead to excessive operational process and delay times in pharmacy dispensing process. This approach laid a solid base to spearhead future optimisation strategies to improve efficiency and shorten waiting time.

Machine Learning Based Emergency Patient Classification System

Public Health Office and the risk map created from the patient information. Many provincial hospitals currently have to admit a large number of patients to their emergency room. Each year, the number outgrow limited medical resources, causing tremendous operational delay, and thus undermining quality of medical services. In addition, existing ER flows remain lacking means of communicating with patients’ relatives and notifying them with treatment status of patients under their care. To addresses these concerns, registered nurses with experiences are required not only to make initial patient screening and prioritization, but also to serve as liaison between physicians and patients’ relatives. These double tasks impose great burden to already overloaded medical staffs. An emergency patient classification system, based on support vector machine was developed. It was implemented as a web application, written in PHP, and running on MySQL database. GIS technology was employed to analyze spatial data and producing relevant reports. The proposed system could classify emergency patient into different groups based on their severity, according to the government standard. The resultant recommendation, verified by a nurse on duty, as well as treatment status were presented to patients’ relatives on a digital screen. Moreover, the hospital was able to use the summarized reports, in both standard and spatial forms, for its managerial purposes. The develop system could help the hospital to make the most of their limit resources for treating emergency patients. The produced reports were useful for making relevant policies and executive planning.

The Research on Delay Propagation of Urban Rail Transit Operation under Sudden Failure

With the increase and extension of urban rail transit lines, networked operation has become an inevitable trend of rail transit operations. Once an emergency occurs, it will cause operational delays; in serious cases, it may further lead to group safety incidents. Firstly, the sudden failure of rail transit is defined, statistical calculation is made according to the accumulated failure data, and then the sudden failures and average processing time are quantitatively calculated. Secondly, the time delay and propagation under the state of sudden failure are analyzed, on the basis of which the propagation and dissipation of time delay based on the single station failure cellular automata model and SIR model network based on multistation fault delay propagation are constructed. Finally, the reliability and accuracy of the model are verified by a case of rail transit in a city. The scheme in this paper can be used to estimate the scope of time and space delay under the sudden failure of rail transit and can provide the basis for the adjustment of traffic organization scheme and evacuation of passenger flow under the sudden failure.

Hierarchical deployment of deep neural networks based on fog computing inferred acceleration model

With the widespread adoption of deep neural network approaches in mobile devices, the drawbacks of traditional cloud-based or local deployment solutions are becoming apparent. The high latency caused by cloud-based inferred neural networks and the high power consumption caused by local inference of mobile devices greatly reduce the actual user experience of neural network applications. To solve this problem, this paper proposes a hierarchical deployment and inference acceleration model for deep neural networks based on fog computing. Firstly, a search reallocation of the solution space of a deep neural network is performed, and a Solution Space Tree Pruning (SSTP) based deployment algorithm is designed to select the appropriate network layer for deployment in order to reduce the overall inferred delay of a deep neural network. Next, an algorithm for Maximizing Accuracy based on Guaranteed Latency (MAL) is designed. On the pruned solution-space tree of the SSTP algorithm, the appropriate fog computation nodes are selected for mobile devices in different geographic locations to achieve early exit from the inference task according to the operational delay and inference accuracy requirements of real device terminals. The experimental results show that the proposed solution reduces the average latency of the fog computing-based inference acceleration model by 44.79% compared to the traditional cloud-deployed deep neural network inference, and by 28.75% compared to the edge computing acceleration framework in existing studies. The model meets the minimum latency and accuracy of neural network inference in multiple fog computing scenarios. At the same time, it greatly reduces the performance occupation and case cost of the cloud under the traditional cloud computing model.

25 Operative Delay in Neck of Femur Fracture Management During the COVID 19 Pandemic Lockdown; Reasons and Impact

All NOF patients beyond 24-hour window over the COVID Lockdown period From April 2020 to July 2020 were identified and causes of delay to theatre were stratified. Manual Data collection over a time period of April 2020 to July 2020, when lockdown was introduced. All patients with NOF who had surgery within 24 hours were excluded. Cases not within 24 hours were included. A total of 70 patients were included in the study. Cause for Delay beyond 24 hours included No list space 30, Medically unfit 20, Anticoagulation 18, COVID related 2 needing ventilatory support. Causes of medical Delay include chest infection (not COVID related), High anaesthetic risk, Cardiac, Anaemia, Electrolyte imbalance. Covid19 accounted for 2 % of operative delays of NOF patients. Other causes include medical optimization, theatre efficiency and use of anticoagulation. However, our study proved there is a vital requirement for robust protocols and pathways in the management of NOF especially during a global pandemic. This is important for the reduction of overall Morbidity and Mortality. Local Strategies should be put in place to address these with the importance of a MDT approach including the Anaesthetic and Orthogeriatic team.

208 Assessment of The Impact Of COVID-19 On the Management of Patients with Neck of Femur Fractures in A Major Trauma Center In Wales

IntroductionNeck of femur (NOF) fractures form a significant proportion of trauma. Especially since they do not benefit from COVID-19 social isolation policies. Surgery and hospital admissions present risks to patients during the COVID-19 pandemic.MethodRetrospective analysis of all NOF fractures from 24/3/20 to 26/6/20 in Morriston Hospital. Directly compared with 2019, allowing assessment of COVID-19’s impact.Results179 NOF fractures were admitted, 158 had an operation. Increased from 127 patients in 2019. Average time to surgery increased from 39 to 67 hours. There were operation delays for 98 patients, and non-operative treatment increased from 2 to 21 patients. Prompt orthogeriatric reviews completed in 80.4% patients in 2020, up from 72.5%. Prompt physiotherapy review increased from 66.9% to 74.6%. Mortality remained similar at 8.6% (2019) and 8.5% (2020). Average length of stay reduced; 17.4 to 11 days in 2020.Conclusions2020 saw increased waits for operations. There was reduction in length of stay and improved promptness of orthogeriatric and physiotherapy reviews. Increased non-operative treatment in 2020, reflecting decisions about risks and benefits of surgery in the pandemic. Mortality remained stable. This department improved some aspects of care, potentially due to pressures of COVID-19 heightening awareness of patient's needs.

A data-driven flight schedule optimization model considering the uncertainty of operational displacement

The slot allocation mechanism aims to match flight demand and airport resources from a strategic perspective. However, current research mainly focused on airlines' interests, ignoring the influencing factors that lead to primary delays, which makes the temporal and spatial distribution of flight schedules unreasonable. This paper proposes a data-driven approach to reduce operational delays at a strategic level by considering operational efficiency and airline interests. The displacement probability distribution between the actual execution time and the scheduled time is first mined from the historical operation data. We then develop a model with the ultimate objective of improving the punctuality rate and reducing the actual operational delays by minimizing the total operational displacement. In addition to considering the basic operational restrictions of airports, the model also introduces the corridor capacity of the terminal airspace surrounding an airport, reducing the delay caused by the corridor flow control to a certain extent. The proposed model is applied to Hangzhou Xiaoshan International Airport in China. The experimental results suggest that the optimized flight schedule can significantly reduce flight delay, conforms to airport operational restrictions, and maintains flight connectivity.