Degree Of Urgency Research Articles

Scheduled Surgery and Antibiotic Therapy in Catarrhal Acute Appendicitis

<i>Introduction: </i>Appendicitis is an acute inflammation of the appendix. Appendectomy remains one of the most frequently performed digestive surgeries in the world. The degree of urgency of this surgery and the increasingly proven efficacy of antibiotics still remains a debate. The main objectiveof our study is to compare the therapeutic results of a programmed appendectomy initially treated by antibiotic versus emergency appendectomies performed from the outset in casesof simple acute appendicitis. <i>Patients and method: </i>Our comparative study was carried out at the Joseph Ravoahangy Andrianavalona University Hospital from 01th August 2021 to 31th July 2022. Group A included simple acute appendicitis patients who underwent emergency surgery, while group B included patients who had been treated with antibiotics for ten days before undergoing surgery. <i>Results: </i>Our cohort of 95 patients comprised 70 patients (group A) versus 25 patients (group B). Twenty-three patients (92%) in group B had a Clavien-Dindo I score compared with 74.3% in group A. Parietal infections were 21% (group A) vs 4% (group B). There was no significant difference inpatient outcome between the two groups. <i>Conclusion: </i>Antibiotic therapy has already proved effective in the treatment of simple acute appendicitisin recent years, and means that emergency surgery can be avoided. However, the timingof surgery remains debatable in fragile patients.

Frequent callers contacting the Norwegian national emergency medical number 113: a retrospective study

BackgroundCalling for help is the first link in the chain of survival; however, few studies have investigated the challenges faced by frequent callers (FCs) to emergency medical communication centres (EMCCs). This study aimed to explore the characteristics of FCs and the nature of their calls to the Bergen EMCC, Norway.MethodsThis was a retrospective analysis of all emergency calls to the Bergen EMCC over three consecutive years (2019–2021). Bergen is the second-largest city in Norway, and the Bergen EMCC and ambulance services are part of the specialist medical service, covering a population of 460,000. The Bergen EMCC receives approximately 60,000 emergency calls per year. The study population comprised all adults identified during emergency medical calls. FCs were defined as individuals who registered five or more calls over 12 consecutive months during the three-year period.ResultsThe analysis included approximately 50,000 individuals, who made > 90,000 calls during the study period. Of those, 1,594 (3.2%) were FCs, accounting for approximately one in four (21,339 of 90,085, 23.7%) calls. The FCs included more men (882 of 1,594 (55.3%) vs. 24,204 of 47,564 (50.9%)) and registered a lower proportion of calls with an acute degree of urgency (6,051 of 21,339 calls (28.4%) vs. 30,276 of 68,746 calls (44.0%)). Calls from FCs showed an even occurrence throughout the week, peaking between 19:00 h and 20:00 h. Compared with calls from non-FCs, calls from FCs had a higher proportion of ‘no response/verbal referral to local emergency medical department’ and involved a lower proportion of hospital transfers. The EMCC most frequently used the medical criterion ‘Mental health problems/suicide’ for calls from FCs.ConclusionsFCs were common, and more often men. The EMCC dispatched ambulances or admitted patients to hospitals less frequently following these calls. Many of these situations could be handled in other parts of the healthcare system, reducing the burden on EMCCs, and providing more suitable services for FCs. Thus, EMCCs should identify and adjust patient management to match their actual needs.

Intelligent Fuzzy Traffic Signal Control System for Complex Intersections Using Fuzzy Rule Base Reduction

In this study, the concept of symmetry is employed to implement an intelligent fuzzy traffic signal control system for complex intersections. This approach suggests that the implementation of reduced fuzzy rules through the reduction method, without compromising the performance of the original fuzzy rule base, constitutes a symmetrical approach. In recent decades, urban and city traffic congestion has become a significant issue because of the time lost as a result of heavy traffic, which negatively affects economic productivity and efficiency and leads to energy loss, and also because of the heavy environmental pollution effect. In addition, traffic congestion prevents an immediate response by the ambulance, police, and fire brigades to urgent events. To mitigate these problems, a three-stage intelligent and flexible fuzzy traffic control system for complex intersections, using a novel hybrid reduction approach was proposed. The three-stage fuzzy traffic control system performs four primary functions. The first stage prioritizes emergency car(s) and identifies the degree of urgency of the traffic conditions in the red-light phase. The second stage guarantees a fair distribution of green-light durations even for periods of extremely unbalanced traffic with long vehicle queues in certain directions and, especially, when heavy traffic is loaded for an extended period in one direction and the short vehicle queues in the conflicting directions require passing in a reasonable time. The third stage adjusts the green-light time to the traffic conditions, to the appearance of one or more emergency car(s), and to the overall waiting times of the other vehicles by using a fuzzy inference engine. The original complete fuzzy rule base set up by listing all possible input combinations was reduced using a novel hybrid reduction algorithm for fuzzy rule bases, which resulted in a significant reduction of the original base, namely, by 72.1%. The proposed novel approach, including the model and the hybrid reduction algorithm, were implemented and simulated using Python 3.9 and SUMO (version 1.14.1). Subsequently, the obtained fuzzy rule system was compared in terms of running time and efficiency with a traffic control system using the original fuzzy rules. The results showed that the reduced fuzzy rule base had better results in terms of the average waiting time, calculated fuel consumption, and CO2 emission. Furthermore, the fuzzy traffic control system with reduced fuzzy rules performed better as it required less execution time and thus lower computational costs. Summarizing the above results, it may be stated that this new approach to intersection traffic light control is a practical solution for managing complex traffic conditions at lower computational costs.

Indications du scanner post-mortem à l’Institut médico-légal de Paris en 2021–2022

Objective: Evaluate recent developments of large-scale post-mortem CT (PMCT) in the forensic practice at the Paris Forensic Institute.Methods: All decedents who underwent a PMCT between 2021 and 2022 were included. Variables, extracted from the PMCT information form and report metadata, included: demographic characteristics, context, degree of urgency, identity knowledge, use of CT for comparative identification, time from PMCT to radiology report.Results: 1775 PMCT were performed on request of 5 different courts. Decedents were mostly male (n=1256, 71%) and median age was 58 years (IQR 43-72). The 3 most frequent contexts were: traumatic death (n=618, 35%), unknown cause of death in preserved (n=593, 33%) or putrefied decedents (n=434, 25%). Identity was unknown in 164 (9%) decedents and supposed in 504 (29%) cases, among which a comparative identification was successfully performed using CT in 41/504 (8%) patients. The median delay from PMCT to radiologic report was 6h (IQR 1.8-18.6hrs) and was significantly shorter for urgent as compared to non-urgent reports (2.3 hours [IQR 1.2-6.1] vs. 8.4 hours [IQR 2.4-21.4], p<0.001).Conclusion: Large-scale PMCT usage is possible in forensic setting, in varied indications and contexts. Fast edition of radiologic reports allows its integration into time constraints of the judiciary system.

Research on the Optimal Trajectory Planning Method for the Dual-Attitude Adjustment Mechanism Based on an Improved Multi-Objective Salp Swarm Algorithm

In this study, an optimization method for the motion trajectory of attitude actuators was investigated in order to improve assembly efficiency in the automatic docking process of large components. The self-developed dual-attitude adjustment mechanism (2-PPPR) is used as the research object, and the structure is symmetrical. Based on the modified Denavit–Hartenberg (MDH) parameter description method, a kinematic model of the attitude mechanism is established, and its end trajectory is parametrically expressed using a five-order B-spline curve. Based on the constraints of the dynamics and kinematics of the dual-posture mechanism, the total posturing time, the degree of urgency of each joint, and the degree of difficulty of the mechanism’s posturing are selected as the optimization objectives. The Lévy flight and Cauchy variation algorithms are introduced into the salp swarm algorithm (SSA) to solve the parameters of the multi-objective trajectory optimization model. By combining the evaluation method of the multi-objective average optimal solution, the optimal trajectory of the dual-tuning mechanism and the motion trajectory of each joint are obtained. The simulation and experiment results show that the trajectory planning method proposed in this paper is effective and feasible and can ensure that the large-part dual-posture mechanism can complete the automatic docking task smoothly and efficiently.

Book Review – Intelligence Overview: The Watchers and the Watchdog

Book Review by Dr Peter Grace Didier Bigo, Emma Mc Cluskey, Felix Tréguer (eds), (2024), Intelligence Oversight in Times of Transnational Impunity. Who will Watch the Watchers? Oxon: Routledge. ISBN 9781032406541. 310 pages. This book focuses on two important issues in intelligence oversight: the long-standing acceptance of raison d’état, and the increasing relations between intelligence agencies transnationally and how much those should come under scrutiny and legal restraint. It is not a book that is designed to be read comfortably by intelligence practitioners, and indeed there are priors that suggest practitioners would much prefer it if there was no oversight of their activities at all. Whether framing the enquiry in this way provokes some degree of urgency or simply divides opinion, the questions of raison d’état and transnational oversight are important.

Trauma nursing competency in the emergency department: a concept analysis

ObjectivesDespite numerous published concept analyses of nursing competency, the specific understanding of trauma nursing competency in emergency departments remains limited, with no clear definition. This study aimed to clarify the...

Effect of microchannel cross-section geometry on the flow resistance with stainless steel flat-plate solar collectors

The stainless steel flat plate solar collector is a new type of collector that has a longer lifespan in high-temperature and high-humidity environments. When using stainless steel as the base material of the collector, the microchannel structure is typically employed to increase the heat transfer area and compensate for the lack of heat transfer coefficient of stainless steel. However, the shape of the channel section in microchannel structures affects the flow resistance of the heat transfer medium. This article presented the equation for the optimal feature size of the channel, obtained through fluid theory analysis of the stainless steel flat plate collector. The study analyzed the impact of different section parameters on the flow distribution and pressure drop characteristics of the medium in the channel through numerical simulation. The results showed that for a certain inlet flow rate, the cross-sectional geometry of the microchannel heat-absorbing plate determined the parameters such as the type of core cross-section, the degree of wall urgency, and the geometrical length of the microchannel, which in turn affected the distribution of the fluid in the flow channel and the energy loss. The optimal thermal performance of the stainless steel collector was observed when the width of the micro-channel was 8.7 mm and the corrugation height of the tube group was 3.00 mm.

The Impact of Transparency on Driver Trust and Reliance in Highly Automated Driving: Presenting Appropriate Transparency in Automotive HMI

Automation transparency offers a promising way for users to understand the uncertainty of automated driving systems (ADS) and to calibrate their trust in them. However, not all levels of information may be necessary to achieve transparency. In this study, we conceptualized the transparency of the automotive human–machine interfaces (HMIs) in three levels, using driving scenarios comprised of two degrees of urgency to evaluate drivers’ trust and reliance on a highly automated driving system. The dependent measures included non-driving related task (NDRT) performance and visual attention, before and after viewing the interface, along with the drivers’ takeover performance, subjective trust, and workload. The results of the simulated experiment indicated that participants interacting with an SAT level 1 + 3 (system’s action and projection) and level 1 + 2 + 3 (system’s action, reasoning, and projection) HMI trusted and relied on the ADS more than did those using the baseline SAT level 1 (system’s action) HMI. The low-urgency scenario was associated with higher trust and reliance, and the drivers’ visual attention and NDRT performance improved after viewing the HMI, but not statistically significantly. The findings verified the positive role of the SAT model regarding human trust in the ADS, especially in regards to projection information in time-sensitive situations, and these results have implications for the design of automotive HMIs based on the SAT model to facilitate the human–ADS relationship.

Predicting the effect of climate change on the geographic range of the Mediterranean relict tree Liquidambar orientalis Mill

Climate change is anticipated to pose a significant danger to the habitats and spatial distribution of species in the Mediterranean region throughout the present century. The primary objective of this study was to predict the future geographic range of Liquidambar orientalis, commonly known as the oriental sweetgum under different climate change scenarios. This species is a relict riparian Mediterranean plant originating from the southwestern Anatolia region and Rhodos Island in Greece. To gain insights into the potential effects of climate change on the range of L. orientalis in the future, I used an ensemble modeling approach of species distribution models based on the shared socioeconomic pathways (SSP1‐2.6 and SSP5‐8.5 for the years 2035, 2055 and 2070). The models suggested that the level of precipitation during the wettest month has a crucial role in determining the occurrence of the oriental sweetgum tree. Future projections indicate that the oriental sweetgum will significantly contract its native distribution range due to warming and declining precipitation levels. The population of L. orientalis has previously undergone a decrease as a result of anthropogenic activity. Therefore, it is imperative to augment the degree of urgency in conservation endeavors for the oriental sweetgum species against the ramifications of human‐induced actions and the persistent effects of climate change.

Hospital reform in Germany: Population-based calculation and simulation model for planning and impact assessment

Background: Due to the increasing shortage of specialists, disproportionately rising costs and inadequate quality of care, Germany is planning a fundamental hospital reform. The government commission has developed the central principles for this reform. The aim is to achieve a centralization of hospital services in oversupplied metropolitan areas by planning according to groups of services based on defined requirements for structural quality. The economic pressure to increase the number of cases shall be reduced through the introduction of a reserve payment and by dividing hospitals into levels - at least by transparent information for the general public. So far, however, there has been no generic model to determine the significance of specific care providers considering population needs (reachability), capacity of a hospital location, and the number and severity of treated patients. Methods: We developed a generic model to determine the significance of hospital location-related care and the need for the various groups of services. The model may also be used to assess reserve financing. For the model, the groups of services were divided into four categories according to degree of specialization and urgency with limits of reachability of 30, 45, 90 and 180 minutes. Gravity models were used to simulate the population-based significance of care providers for each group of services. In the basic model, the allocation of the significance was based exclusively on the reachability for the population living within the respective reachability corridor. In extended models, the historical number of cases and their case severity were also taken into account in order to account for current care capacities and existing choices of the population regarding, among other things, the quality of care. The model was implemented on the basis of nationwide data provided in accordance with § 21 data (of the German law for hospital remuneration). We then determined the effects of weighting the three influencing variables (i) population, (ii) number of cases and (iii) case severity on the significance of the hospital sites. Using the example of "endoprosthetics of the knee" (service group 14.2 in North Rhine-Westphalia) in the federal state of Saxony, the effect of concentration on the distribution of the reserve budgets and on the accessibility of the population was illustrated. The importance of care determined in this way is contrasted with a key value that reflects the need for hospitals in terms of securing care in rural areas. Results: From the approximately 16.5 million somatic treatment cases in 2021, 98.5% could be assigned to one of the 60 somatic groups of services according to North Rhine-Westphalia model. The simulation models show a differentiated picture for the various service groups. For the majority of service groups, a moderate concentration of services does not lead to relevant restrictions in terms of reachability. Exclusively considering the population to be cared for (basic model) would lead to significant shifts in the financing of running costs, which are, however, very well mitigated by considering the historic number and severity of cases (extended models). As an example, we show the effects for the service group "endoprosthetics of the knee" in the federal state of Saxony compared to the extrapolation at location level. Discussion: The empirically based simulation model proposed here takes into account reachability, patient preference and hospital capacity and offers a scientific way of comparing the regional significance of care providers as well as the necessity of hospital locations for each service group against the background of the state's obligation to provide care and to make economical use of resources. The simulation model is meant to support hospital planning (here: the allocation of groups of services) in the federal states and to guide rational planning. It is also suitable for the management of financial resources in the context of hospital reform. It also enables an impact analysis. The model is not intended to automate planning or otherwise make rigid specifications. The calculations should be regarded as exemplary. The weights of all parameters can be varied. However, the reachability thresholds and the parameterization of the simulation model should be defined jointly by federal and state governments in terms of a common set of objectives.

A Descriptive Study to Assess the Knowledge Regarding Triage Among Staff Nurses of Batra Hospital and Medical Research Centre [BHMRC], New Delhi

Nurse triage' refers to the formal process of early assessment by a trained nurse, in an attempt to ensure that patients receive appropriate attention, in a suitable location and with the requisite degree of urgency. The study was conducted in BHMRC, New Delhi in the month of November, 2023. The structured questionnaire was administered to 60 nurses. The result showed that (36.66%) staff nurses were of less than 25 years of age, most of them (86.66%) were females, mostly (70%) belonged to Hindu religion, more than half of the staff nurses (66.66%) had diploma in nursing, mostly nurses (41.66%) had working experience of 3-5yrs, (26.66%) nurses worked in the emergency department and (50%) had taken training on triage. Out of 60 staff nurses of BHMRC in which 16.66% were having very good knowledge, 56.66% were having good knowledge, 18.33% were having average knowledge and 8.33% were having poor knowledge regarding triage with the mean knowledge score and standard deviation of staff nurses was 20.41 3.88. The study concluded that out of 60 staff nurses, 10 staff nurses have very good knowledge 34 staff nurses have good knowledge, 11 staff nurses have average knowledge and 5 staff nurses have poor knowledge. Keywords: Triage, Staff Nurses, Hospital, Knowledge.

Identifying key items to be addressed by non-clinical operators to manage out-of-hours telephone triage services for older adults seeking non-urgent unplanned care in Belgium: an e-Delphi study

BackgroundThis study aimed to achieve expert consensus regarding key items to be addressed by non-clinical operators using computer-software integrated medical dispatch protocols to manage out-of-hours telephone triage (OOH-TT) services for calls involving older adults seeking non-urgent unplanned care across Belgium.MethodsA three-part classic e-Delphi study was conducted. A purposive sample of experts specialized in out-of-hours unplanned care and/or older persons across Belgium were recruited as panelists. Eligibility criteria included experts with at least 2 years of relevant experience. Level of consensus was defined to be reached when at least 70% of the panelists agreed or disagreed regarding the value of each item proposed within a survey for the top 10 most frequently used protocols for triaging older adults. Responses were analyzed over several rounds until expert consensus was found. Descriptive and thematic analyses were used to aggregate responses.ResultsN = 12 panelists agreed that several important missing protocol topics were not covered by the existing OOH-TT service. They also agreed about the nature of use (for the top 10 most frequently used protocols) but justified that some modifications should be made to keywords, interrogation questions, degree of urgency and/or flowcharts used for the algorithms to help operators gain better comprehensive understanding patient profiles, medical habits and history, level of support from informal caregivers, known comorbidities and frailty status. Furthermore, panelists also stressed the importance of considering feasibility in implementing protocols within the real-world setting and prioritizing the right type of training for operators which can facilitate the delivery of high-quality triage. Overall, consensus was found for nine of the top 10 most frequently used protocols for triaging older adults with no consensus found for the protocol on triaging patients unwell for no apparent reason.ConclusionOur findings show that overall, a combination of patient related factors must be addressed to provide high quality triage for adults seeking non-urgent unplanned care over the telephone (in addition to age). However, further elements such as appropriate operator training and feasibility of implementing more population-specific protocols must also be considered. This study presents a useful step towards identifying key items which must be targeted within the larger scope of providing non-urgent out-of-hours telephone triage services for older adults seeking non-urgent unplanned care.

Joint Modelling of Latent Cognitive Mechanisms Shared Across Decision-Making Domains.

Decision-making behavior is often understood using the framework of evidence accumulation models (EAMs). Nowadays, EAMs are applied to various domains of decision-making with the underlying assumption that the latent cognitive constructs proposed by EAMs are consistent across these domains. In this study, we investigate both the extent to which the parameters of EAMs are related between four different decision-making domains and across different time points. To that end, we make use of the novel joint modelling approach, that explicitly includes relationships between parameters, such as covariances or underlying factors, in one combined joint model. Consequently, this joint model also accounts for measurement error and uncertainty within the estimation of these relations. We found that EAM parameters were consistent between time points on three of the four decision-making tasks. For our between-task analysis, we constructed a joint model with a factor analysis on the parameters of the different tasks. Our two-factor joint model indicated that information processing ability was related between the different decision-making domains. However, other cognitive constructs such as the degree of response caution and urgency were only comparable on some domains.

Variations in the intended utilization of emergency care in case of gastrointestinal diseases

Frequent utilization of emergency care and overcrowded emergency departments (EDs) are highly relevant topics due to their harmful consequences for patients and staff. The present study examines variations of intended health care use in urgent and non-urgent cases among the general population. In a cross-sectional telephone survey, a sample of N = 1,204 adults residing in Hamburg, Germany, was randomly drawn. At the beginning of the survey, one of 24 different vignettes (case stories) describing symptoms of inflammatory gastrointestinal diseases were presented to the participants. The vignettes varied in sex (male/female), age (15, 49, 72 years), daytime (Tuesday morning, Tuesday evening), and urgency (low, high). Participants were asked in an open-ended question about their primal intended utilization if they or their children would be affected by such symptoms. Overall, about 14 % chose emergency facilities (ED, ambulance, emergency practice) despite presentation of non-urgent conditions (n = 602). Intended emergency care use varied considerably even if the degree of urgency was comparable. Adolescence, male sex, and symptoms occurring in the evening were associated with increased ED and ambulance use. Inappropriate utilization of ED and ambulance (analyses regarding utilization due to non-urgent problems) was more often observed among male respondents and those with a migration background (1st generation). Information campaigns focused on emergency care use and reorganisation of emergency care wards are possible interventions.

Initial Treatment of Cerebral Hemorrhage:Determining the Cause without Preconceived Notions

In Japan, cerebral hemorrhage accounts for 19.5% of stroke patients, and its prognosis is poorer than that of cerebral infarction, with a mortality rate of 14.6%. In the initial treatment of cerebral hemorrhage, the airway, respiration, and circulation should be stabilized, and the intracranial pressure and body temperature should be controlled. Hypertensive cerebral hemorrhage is the most common cause; however, the cause should be carefully examined, and the treatment method should be selected according to the degree of urgency. Cerebral hemorrhage patients undergoing antithrombotic therapy show poor outcomes owing to increased hematoma. Therefore, antithrombotic drugs should be discontinued immediately. Blood products and neutralizing drugs should be administered in response to the administration of antithrombotic drugs. In young individuals, cerebrovascular disorders may be caused by the abuse of sympathomimetic drugs, such as stimulants and cocaine. Whether individuals or their family members are using illegal drugs should be confirmed.

SoC-VRP: A Deep-Reinforcement-Learning-Based Vehicle Route Planning Mechanism for Service-Oriented Cooperative ITS

With the rapid development of emerging information technology and its increasing integration with transportation systems, the Intelligent Transportation System (ITS) is entering a new phase, called Cooperative ITS (C-ITS). It offers promising solutions to numerous challenges in traditional transportation systems, among which the Vehicle Routing Problem (VRP) is a significant concern addressed in this work. Considering the varying urgency levels of different vehicles and their different traveling constraints in the Service-oriented Cooperative ITS (SoC-ITS) framework studied in our previous research, the Service-oriented Cooperative Vehicle Routing Problem (SoC-VRP) is firstly analyzed, in which cooperative planning and vehicle urgency degrees are two vital factors. After examining the characteristics of both VRP and SoC-VRP, a Deep Reinforcement Learning (DRL)-based prioritized route planning mechanism is proposed. Specifically, we establish a deep reinforcement learning model with Rainbow DQN and devise a prioritized successive decision-making route planning method for SoC-ITS, where vehicle urgency degrees are mapped to three priorities: High for emergency vehicles, Medium for shuttle buses, and Low for the rest. All proposed models and methods are implemented, trained using various scenarios on typical road networks, and verified with SUMO-based scenes. Experimental results demonstrate the effectiveness of this hybrid prioritized route planning mechanism.

Non-inferior outcomes in lower urgency patients transplanted with extended criteria donor hearts

Recent work has suggested that outcomes among heart transplant patients listed at the lower-urgency (United Network for Organ Sharing Status 4 or 6) status may not be significantly impacted by donor comorbidities. The purpose of this study was to investigate outcomes of extended criteria donors (ECD) in lower vs. higher urgency patients undergoing heart transplantation. The United Network for Organ Sharing (UNOS) database was queried for all adult patients undergoing heart transplantation from 10/18/2018 through 12/31/2021. Patients were stratified by degree of urgency (higher urgency: UNOS 1 or 2 vs. lower urgency: UNOS 4 or 6) and receipt of ECD hearts, as defined by donor hearts failing to meet established acceptable use criteria. Outcomes were compared using propensity score matched cohorts. Among 9,160 patients included, 2,320 (25.4%) were low urgency. ECD hearts were used in 35.5% of HU patients and 39.2% of LU patients. While ECD hearts had an impact on survival among high-urgency patients (p<0.01), there was no difference in 1- and 2-year survival (p>0.05) found among low urgency patients receiving ECD vs. standard hearts. Neither ECDs nor individual ECD criteria were independently associated with mortality in low urgency patients (p>0.05). Post-transplant outcomes among low urgency patients are not adversely affected by receipt of ECD vs. standard hearts. Expanding the available donor pool by optimizing use of ECDs in this population may increase transplant frequency, decrease waitlist morbidity, and improve postoperative outcomes for the transplant community at large.

A machine learning model with linear and quadratic regression for designing pharmaceutical supply chains with soft time windows and perishable products

Product perishability is an important problem in Pharmaceutical Supply Chains (PSC). Demand perishability and unpredictability add enormous complexity to successfully implementing efficient Pharmaceutical Supply Chain Network Design (PSCND). This study develops a mathematical model for the PSCND. The two objective functions used in the model minimize the total cost and the delivery penalty due to schedule violations involving Soft Time Windows (STWs). Using a STW strategy in the Distribution Center (DC) allocation model empowers decision-makers to include a time-based performance metric for DC evaluation based on the degree of urgency or need for a part. Moreover, Linear Regression (LR) and Quadratic Regression (QR) Machine Learning (ML) algorithms are proposed to forecast the demand and decrease the possibility of a shortage in the PSCND. We show that QR has better performance than LR in PSCND. In the proposed approach, the demand for medicine is forecasted by the QR technique. The Goal Attainment (GA) method is used to solve the suggested model. Finally, sensitivity analysis and managerial perspectives are offered. The numerical outcomes show that the suggested model leads to an efficient PSC, reducing cost, decreasing shortage, and increasing customer satisfaction with STW consideration.

Joint Optimization of Maintenance and Spare Parts Inventory Strategies for Emergency Engineering Equipment Considering Demand Priorities

To respond to emergencies in a timely manner, emergency engineering equipment has been an important tool to implement emergency strategies. However, random failures of the equipment may occur during operation. Therefore, appropriate maintenance and spare parts inventory strategies are crucial to ensure the smooth operation of the equipment. Furthermore, the urgency degree of emergencies varies in practice. Nevertheless, existing studies rarely consider the impact of urgency degree and demand priorities on the service order of the equipment. To bridge the research gaps, this paper establishes a joint optimization model of maintenance and spare parts inventory strategies for emergency engineering equipment considering demand priorities. The proposed model includes two types of emergency engineering equipment with different service rates. The more urgent demand can be fulfilled by the equipment with a higher priority. Corrective maintenance and spare parts inventory policies are simultaneously performed for the equipment. The Markov process imbedding method is utilized to derive the probabilistic indexes of the system. To maximize the system availability, the number of maintenance engineers and the spare parts inventory strategy is optimized via the construction of the joint optimization model. The optimal solution for the optimization problem is obtained using the branch-and-bound method. Finally, this study presents practical examples to verify the effectiveness of the model and methods.