Planning Model Research Articles

Cooperative game-based energy storage planning for wind power cluster aggregation station

It is possible to cut down the investment costs in energy storage and enhance the utilization of energy storage by planning the shared energy storage in the wind farm collection station to replace the dispersed energy storage of each wind farm. Considering the cluster complementary effects of multiple wind farms, this article proposes a cooperative game-based plan for the hybrid energy storage of battery and supercapacitor in the wind power cluster. Firstly, charging and discharging strategy for batteries follows the peak shaving and valley filling approach, while the strategy for supercapacitors aims to flatten power fluctuations and track power generation plans. Then, a dual-layer planning model for the shared energy storage station is established, and evaluation indicators for the energy storage configuration results are constructed. Finally, based on the improved Shapley value method, the profits of each wind farm are allocated, and the impact of energy storage investment costs on the results is analyzed. The case study results demonstrate that under this cooperative scheme, not only can the real-time output deviation of wind power be reduced, but also the investment costs of wind farms in energy storage systems can be reduced.

Two-stage planning model of power-to-gas station considering carbon emission flow

The widespread use of fossil fuels has substantially contributed to global climate change. One of the most crucial ways to address climate change is to minimize carbon emissions in the energy sector. Power-to-Gas (P2G) technology provides a potential solution. In this context, this paper introduces a novel two-stage P2G planning method for the electric-gas coupling system, using carbon emission flow technology. The carbon emission flow model employed facilitates the distribution of carbon emissions across the entire energy network. Central to our planning strategy is the identification of nodes with reduced carbon emissions for the siting of P2G facilities, predicated on the premise that such nodes are indicative of significant renewable energy utilization. Constructing P2G systems at these particular nodes is strategically advantageous for augmenting renewable energy consumption. In the initial phase, a P2G siting planning methodology predicated on a low-carbon criterion is advanced, resulting in a definitive siting scheme. Subsequently, the second phase involves establishing a P2G capacity optimization model that seeks to strike an economic equilibrium between the utilization of surplus wind power and P2G operational investment. An enhanced pigeon optimization algorithm is employed to resolve the proposed model. Our method is verified by simulation. Compared with other conventional models, the accommodation capacity of renewable energy with the proposed method is enhanced, and the carbon emissions and operating costs of IES are also reduced.

Fuzzy-Set QCA on Performance and Sustainability Determinants of Ports Supporting Floating Offshore Wind Farms

The present study explores the relationship between the characteristics, performance, and sustainability of ports that will, in the future, support the logistical chains of new floating offshore wind farms, considering the crucial advancement and expansion of the offshore wind energy sector for the transition to a low-carbon economy. Through a detailed analysis, which includes international case studies in America and Europe utilizing expert interviews and quantitative methods through surveys, the importance of the location, new types of infrastructure and superstructure, and new planning and governance models for the performance and sustainability of ports that will be involved in this new energy industry is highlighted. Also, the context in which ports associated with floating wind turbines are located influences the performance and sustainability. This research employs Fuzzy-Set Qualitative Comparative Analysis (fsQCA), based on a survey of 22 European sector company experts, to emphasize the critical port characteristics for the performance and sustainability. This study reveals the significant contribution of supporting ports for the future floating offshore wind sector for the gross added value and the expansion of regional employment, and the need for new planning, construction, operation, and management models for ports instead of the traditional models applied to simple cargo loading and unloading ports, offering valuable new insights for port managers, policymakers, and academics. However, a future research trajectory with a more geographically diverse sample is suggested to enhance the applicability and generalizability of the results.

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 SUSTAINABLE ECOTOURISM PLANNING MODEL: DOES IT MATTER?

Objectives: This study aims to analyze the condition of tourism in the future and make a sustainable ecotourism planning model. The sample is East Java of areas, namely The Tapal Kuda region. This is because the tourism sector is one of the main sectors to increase economic growth in East Java. This potential is not only to increase the local revenue, but also to excess business opportunities, create new jobs, reduce unemployment and economic recovery. But, COVID-19 pandemic has a negative impact on tourism because decrease in tourist visits, thus providing a domino effect on the other sectors. In addition, tourism has threats, such as disaster; inflation; and the economic condition. Based on literature studies, the threats have a negative impact on the demand for tourists to visit and threatens tourism sustainability. Methods: This research used quantitative descriptive analysis with three steps, input; matching stage; and decision stage. The data in this research is primary with used a survey method. Observation collection data techniques used interviews, questionnaires, documentation and secondary data from literature. The strategy formulation techniques of decision-making stage can be integrated in three from identifying, evaluating, and selecting strategies can be applied to all types and sizes of organizations. Results: Tourism villages are one of the potentials that can be developed in the Tapal Kuda area, East Java. Tapal Kuda area consists of Pasuruan, Probolinggo, Bondowoso, and Banyuwangi. Based on the identification results, such as tourist attractions, tourism facilities, accessibility, community and environmental aspects, market aspects, management and services, linkages of tourist attractions, as well as community participation in the form of decision making, participation in implementation, participation in benefit-making, and evaluation, the results of almost all indicators have been met. A Sustainable ecotourism planning must pay attentionto various aspects economic, social, and environmental. Ecotourism development planning strategies with increasing human capital through community participation; stakeholder collaboration; integraty destination tourism; and promotion be the main factor to sustainability of tourism. Conclusion: A Sustainable ecotourism planning model must pay attention to various aspects economic, social, and environmental. Human capital through community participation and involvement of stakeholders in this development strategy is important, not only to increase tourism visiting and economic growth, but also integraty destination tourism, preserving the environment and welfare in the society.

Extraction of Emergency Elements and Business Process Model of Urban Rail Transit Plans

The emergency plan of the urban rail transit (URT) system is a guiding document for dealing with emergencies and formulating emergency plans. However, the emergency plan text described in natural language has some problems, such as poor visibility and enforceability. Effective help is difficult to provide for the rapid implementation of emergency response. Therefore, obtaining key emergency task information from the emergency response plan and visualizing the emergency disposal workflow are the main challenges. In this article, we propose a method of extracting emergency elements (EELs) from emergency plans and constructing a business process model. First, a nested entity extraction model incorporating adversarial training is proposed to extract EELs from the complex sentences in the emergency plan text. Second, the EELs are combined into emergency task units, and then the relations between emergency task units are identified to form the emergency task sequence flow, which is stored in matrix form. Finally, the emergency disposal workflow model is generated based on the emergency task sequence flow and the BPMN modeling method. Taking the actual emergency plan text as an example, the process from the extraction of EELs to the construction of the disposal workflow model is demonstrated. Experimental results prove that this method has advantages in comprehensively extracting EELs, visualizing the emergency disposal workflow, and improving the enforceability of emergency plans.

Three-dimensional printed models for surgery planning of post-traumatic stiff elbow: Current concepts

The post-traumatic stiff elbow is a challenge for the surgeon, requiring expertise for the treatment choice and accurate planning. Stiffness can result from traumatic injury involving the periarticular soft tissues and the joint articular surfaces. In this article, we want to assess the impact of three-dimensional (3D) printed models in selecting the appropriate surgical strategy for this pathology.Six cases of increasing complexity regarding post-traumatic stiff elbow were submitted to four expert elbow surgeons who had the possibility to evaluate videos and reports of clinical examination, plain radiograms and CT with 3D reconstruction for each case.After a first treatment proposition given by the experts for each patient, a three-dimensional printed model of each elbow based on the CT was provided to the surgeons, asking them to evaluate again all the cases having the possibility to assess also the 3D models.In the four most complex cases all surgeons found more beneficial the use of three-dimensional representation for treatment planning and rate the risk of complications than the sole CT imaging with 3D reconstruction and many of them changed surgical strategy after analysing the model.3D printing technology is a useful tool in surgery planning for treating complex cases of post traumatic elbow stiffness, especially in the presence of joint deformity. Level of EvidenceIV

Electric vehicle charging stations: Model, algorithm, simulation, location, and capacity planning

The transition to sustainable transportation is imperative in mitigating environmental impacts, with electric vehicles (EVs) at the forefront of this shift. Despite their environmental benefits, the global adoption of EVs is curtailed by challenges such as nascent battery technology, high costs, and insufficient charging infrastructure. This study addresses the optimizing electric vehicle charging station (EVCS) locations as a critical step toward enhancing EV adoption rates. Thus, establishing efficient charging stations is critical to meet the increasing demand. By integrating location modeling with demand forecasts and market penetration, we propose a comprehensive approach to determine optimal locations and capacities for EVCS. Firstly, review existing literature, highlighting the significance of facility location models in optimizing EV charging infrastructure and identifying gaps in addressing demand and market penetration. Our methodology uses a genetic algorithm to solve the p-median problem for location selection and Arena 14 simulation software to model station traffic and optimize charging unit types and quantities. The model prioritizes public areas, considering potential demand points and station locations to propose optimal charging areas. Results indicate that our model minimizes travel distances and waiting times, offering a scalable solution adaptable to future EV market growth. This study contributes to the field by presenting a sustainable and economical model for EVCS placement and capacity planning, underlining the importance of a robust charging network in the broader adoption of electric transportation. The findings suggest that proactive infrastructure development, guided by accurate demand predictions and optimized location strategies, can significantly enhance the feasibility and attractiveness of EVs, supporting global efforts towards a cleaner, more sustainable transportation system.

A single-objective optimization model for power systems with the introduction of line-heavy load rate index constraints

The increasing penetration of new energy sources in new power systems has exacerbated the volatility and complexity of power system currents. Grid planning is facing higher challenges. Established grid planning models usually use the upper and lower limits of grid transmission capacity as constraints, but this may lead to long-term heavy load operation of certain lines and increase system risks. Therefore, this paper designs a line-heavy load rate constraint and establishes a single-objective optimization model for grid planning based on this constraint. Example analyses verify the effectiveness of adding line-heavy load rate constraints in planning and the reasonableness of the single-objective optimization model.

Developing a Dynamic Conceptual Model of a Home-Based Palliative Care Plan Using the Comprehensive Primary Health Care (PHC) Approach

Background: Palliative Care (PC) was a core component of Primary Health Care services during the World Health Assembly Resolution, 2014. The study aims to develop a Comprehensive Palliative Care Model (CPCM) for patients with life-threatening conditions compliant with the local context and unmet needs. Materials and Methods: A mixed-methods approach will be adopted for the three-phased study in two districts of Telangana. Phase I, a literature review, will be performed to explore globally available PC models, followed by an on-ground observational study. Phase II will address the gaps in existing models while identifying the unmet needs of the patients and caregivers. The outcome of the above phases will help develop a CPCM in Phase III. The developed model will be validated using the Delphi technique. Results: The expected outcomes of the study are a) Phase-I: Details of the PC models available globally and locally, b) Phase-II: Availability of essential resources in the Health and Wellness Centers (HWCs), Knowledge and Attitude of the PC team, Barriers to provide PC, Unmet needs, and c) Phase-III: CPCM model Conclusion: The study attempts to provide a holistic PC model, considering the health system, patients, and caregivers and offering policy suggestions to the state.

Estimation of energy demand and carbon emissions for the road transport sector: A case study of Douala, Cameroon

Road transport is one of the main causes of air pollution around the world. Nowadays, the notion of sustainable development is one of the major pillars for a healthy environment. However, faced with its major challenges, it is more than necessary and important to understand a set of elements which contribute to better understanding the level of planning for sustainable road transport. This study aims to estimate energy demand and greenhouse gas emissions, namely from road CO2 transport, for the city of Douala in Cameroon from 2010 to 2035. In order to achieve our objective, we used the Long range Energy Alternative Planning (LEAP) model. Based on the LEAP model, the estimates were evaluated based on three scenarios Business As Usual (BAU), Energy Optimization and Mitigation (EOM) and Sustainability Mobility (SM). The aim of this work was to identify suitable potential policies with a view to reducing energy consumption and emissions carbon dioxide (CO2) for road transport in Douala. The results tell us that the EOM and SM scenarios have advantages over the BAU scenario with the SM scenario being more optimistic than the other two scenarios. In addition, the SM scenario has a growth rate of 87.408 % in energy demand smaller than the other two scenarios BAU and EOM respectively 151.598 % and 132.073 %. We also note that the SM scenario contributed to a reduction of 60.661 kilo ton emissions of CO2 less than the BAU scenario. At present, with a view to reducing energy consumption and reducing carbon emissions, road vehicles in circulation in the city of Douala should emphasize structural optimization measures through the use of clean energy by promoting the use of biofuels in mass transport, eliminating old cars and finally considering improving energy efficiency through the implementation of technological development in the automobile sector. Policy makers must take this study into consideration in order to better integrate the notion of energy sustainable road transport.

Apical dose versus volume dose of Ruthenium-106 brachytherapy for uveal melanoma

ObjectiveRuthenium-106 brachytherapy is commonly used to treat uveal melanomas. Most centres prescribe a radiation dose to the tumour apex that is calculated with the tumour located in the centre of the plaque. Recent work suggests that D99%—the minimum radiation dose delivered to 99% of tumour volume—may be a better predictor of tumour control than apex dose. Both dosing regimens may be affected by tumour and treatment variables differently. We explored the effect of differences in these variables on volume and apex dose using a 3-dimensional planning model. MethodsThe time required to deliver 100 Gy to the tumour apices of representative tumours ranging from 2- to 6-mm thickness with central plaque positioning was calculated in Plaque Simulator™. This treatment time was used for further calculations, including D99% with central plaque placement, and apical and tumour volume doses when tumour and plaque characteristics were altered, including eccentric plaque placement, either away from (tilt) or along (offset) scleral surface, tumour shape, and plaque type. ResultsD99% was always greater than the apex dose when plaques were placed centrally, and the difference increased with tumour thickness. Increasing degrees of tumour offset reduced apical dose and D99%, with a greater effect on apical dose for thicker and D99% for thinner tumours, respectively. Differences in tumour shape and plaque type had idiosyncratic effects on apical and volume dosing. ConclusionD99% and apex dose are affected by tumour and treatment characteristics in different ways, highlighting the complexity of radiation delivery to uveal tumours.

Three-dimensional unmanned aerial vehicle path planning utilizing artificial gorilla troops optimizer incorporating combined mutation and quadratic interpolation operators

In real terrain and dynamic obstacle scenarios, the complexity of the 3D UAV path planning problem greatly increases. Thus, to procure the optimal flight path for UAVs in such scenarios, an augmented Artificial Gorilla Troops Optimizer, denoted as OQMGTO, is proposed. The proposed OQMGTO algorithm introduces three strategies: combination mutation, quadratic interpolation, and random opposition-based learning, aiming to enhance the ability to timely escape from local optimal path areas and rapidly converge to the global optimal path. Given the flight distance, smoothness, terrain collision, and other five realistic factors of UAVs, specific constraint conditions are proposed to address complex scenarios, aiming to construct a path planning model. By optimizing this model, OQMGTO algorithm solves the path planning problem in complex scenarios. The extensive validation of OQMGTO algorithm on CEC2017 test suite enhances its credibility as a powerful optimization tool. Comparison experiments are conducted in simulated terrain scenarios, including six multi-obstacle terrain scenarios and three dynamic obstacle scenarios. The experimental findings validate OOMGTO algorithm can assist UAV in searching for excellent flight paths, featuring high safety and reliability characteristics, which confirms the superiority of OOMGTO algorithm for path planning in simulated terrain scenarios. Furthermore, in four flight missions carried out in real terrains, OQMGTO algorithm demonstrates superior search performance, planning smooth trajectories without mountain collision.

Directions for the formation of «City Intelligent models» using artificial intelligence for the post-war reconstruction of historical buildings

Addressing the limitations of current digital simulations for historical buildings, this paper suggests a specific technical task for the development of a simulation analysis platform based on City Intelligent Modelling (CIM). The objective is to establish a systematic approach for digitally maintaining and managing historical dwellings. The technique presented in this paper focuses on constructing sophisticated parametric models that offer numerous modelling benefits, allowing for convenient updates to the Historic Building Information Modelling (HBIM). The text discusses various applications and integrations of Building Information Modelling (BIM) in urban planning, construction projects, and historic building renovations. CIM is presented as a comprehensive digital platform that visually represents cities, aiding urban planners in decision-making for sustainable development. The text delves into the use of advanced analytical tools within CIM for diverse data analysis, predictive modelling, and simulation to forecast trends. The focus shifts to the evolution of BIM, progressing from 3D to 5D models, influencing construction project management and cost estimation. The integration of BIM in historic building projects is explored, emphasising the challenges and proposing innovative solutions using HBIM. The paper also introduces the concept of Infrastructural Building Information Modelling (InfraBIM) in construction management, incorporating Virtual and Augmented Reality for enhanced visualisation.

Novel path planning method using marine predator algorithm for mobile robot

The main goal of robot path planning is to design an optimal path for a robot to navigate from its starting point to its goal while avoiding obstacles and optimizing certain criteria. A novel method using marine predator algorithm which is used in the field of robot path planning is presented. The proposed method has two steps. First step is to build a mathematical model of path planning while second step is optimization process using marine predator algorithm. Simulation results show that the proposed method works well and has good performance in different situations. Therefore, this method is an effective method for robot path planning and related applications.

Design of a mathematical model for staff planning in an emergency department

The emergency department plays a fundamental role in hospitals and critically affects a hospital's overall efficiency. Inadequate staff planning in emergency departments generates high costs, overcrowding, and patient dissatisfaction due to long waiting times, possibly putting the patient's health and life at risk. This research designed two mixed integer linear programming mathematical models. The first determined the optimal number of physicians required per shift and weekday in an adult emergency department to minimize the deviation between available and required capacity. The results of the optimization model would reduce by 16.07 % the required medical office staff per week, from 56 physicians in the current situation to 47, reducing staffing costs without impacting waiting times. Moreover, the overall physician utilization would be 95.01 % compared to 77.79 % in the current situation, indicating an adequate distribution of physicians on each shift of each day according to patient demand. These results contribute to the problem of high medical staff costs and overcrowding without sacrificing timeliness and quality of care. In contrast, the second model that minimized the number of physicians considering capacity constraints would increase the staff by 7.14 % concerning the current situation. This research was based on a model presented in the literature, but the objective function included the deviation variables as unrestricted in sign and a constraint to ensure that they were positive. The first model designed is presented as a tool to support emergency department managers in the medium-term planning of medical staff, ensuring an optimal solution to this problem

Thermoviscosimetric characteristics of borosilicate glasses with regard to the promising area of low-melting compositions currently being developed for the removable small-scale melter designed by Mayak Production Association

Relevance. The need to obtain experimental data on dependence of thermoviscosimetric properties of the examined borosilicate glasses on temperature, in order to solve the problem of developing a low-melting composition of borosilicate glass for a small-scale melter designed by Mayak Production Association. Aim. To get the most complete characterization of the glasses under study using thermoviscometric measurements. Methods. Mathematical modelling, simplex-lattice design. Results and conclusions. One of the most effective methods of experiment planning, which allows, with a relatively small number of experiments, obtaining a mathematical model reflecting the dependence of the studied property of the mixture on the content of components in it, is the simplex experiment planning method. To simplify the solution of such a task, a group or groups of components are usually distinguished, in which the ratio of the mass fraction of the components does not change. In this article, three groups of components are taken – simulators of high-level radioactive waste, sodium and boron oxides, and glass frit. The authors have identified the most promising area, where the mass fraction of glass frit is from 67.5 to 75%, the mass fraction of sodium and boron is from 25 to 32.5% and the mass fraction of high-level waste components is from 0 to 20%. The paper presents the results of thermoviscometric measurements of 15 melts of low-melting borosilicate glasses of different compositions at temperatures ranging from 700 to 1,200°C. Using simplex-based mathematical models of experiment planning, domains of dependence of thermoviscosimetric characteristics of glass melts on their compositions were created. The authors identified the compositions of glass melts that are found within the viscosity limits determined as allowable for glass melt discharge during operation of the removable small-scale melter of Mayak Production Association design.

Compact rover surveying and laser scanning for BIM development.

This paper presents a custom made small rover based surveying, mapping and building information modeling solution. Majority of the commercially available mobile surveying systems are larger in size which restricts their maneuverability in the targeted indoor vicinities. Furthermore their functional cost is unaffordable for low budget projects belonging to developing markets. Keeping in view these challenges, an economical indigenous rover based scanning and mapping system has developed using orthogonal integration of two low cost RPLidar A1 laser scanners. All the instrumentation of the rover has been interfaced with Robot Operating System (ROS) for online processing and recording of all sensorial data. The ROS based pose and map estimations of the rover have performed using Simultaneous Localization and Mapping (SLAM) technique. The perceived class 1 laser scans data belonging to distinct vicinities with variable reflective properties have been successfully tested and validated for required structural modeling. Systematically the recorded scans have been used in offline mode to generate the 3D point cloud map of the surveyed environment. Later the structural planes extraction from the point cloud data has been done using Random Sampling and Consensus (RANSAC) technique. Finally the 2D floor plan and 3D building model have been developed using point cloud processing in appropriate software. Multiple interiors of existing buildings and under construction indoor sites have been scanned, mapped and modelled as presented in this paper. In addition, the validation of the as-built models have been performed by comparing with the actual architecture design of the surveyed buildings. In comparison to available surveying solutions present in the local market, the developed system has been found faster, accurate and user friendly to produce more enhanced structural results with minute details.

Marketing Strategy Plan of Coca-Cola Company in the UK

Marketing is crucial to the success of an enterprise. This report is to develop a marketing strategy plan for Coca-Cola company, including seven parts: introduction, situation analysis, market segmentation, innovation, resource allocation, conclusion and recommendation. Situational analysis includes macro-environmental factors, such as policy, economy, society and technology; Industry elements like competitors, suppliers and substitutes; Internal factors, such as the strengths and weaknesses of Coca-Cola. Coca-Cola divided the market into different segments and target each segment with suitable products, which including provides Coca Cola range with different varieties for age segment (18-35); Multiple size of bottles target family size segment; Multiple bottles with different materials target income group; Sugar and calories-free drink target health-conscious group; “Christmas Celebration Bottle Bow” target specific occasion - Christmas. In terms of innovation, Coca-Cola launched new products, including Coca-Cola energy, Simply smoothie and Honest cold brew coffee. Moreover, it also developed new packaging material which is KeelClip™ and is going to replace all the plastic packaging from all can multi-packs. In addition, Coca-Cola innovated its service, which is the adding of loyalty scheme to vending machine. Coca-Cola uses financial planning model to determine the budget and other resources that should be allocated to each project, it invested lots of money into Diet coke and new packaging technology. The recommendation for the future development is expanding markets to health and food areas as well as target other age group (50-54) and introduce suitable products.

Nomogram for Predicting Infectious Complications Following Curative Gastrectomy Using Clinical and Laboratory Parameters.

Postoperative infectious complications are prevalent and significantly impact the prognosis and hospital stay duration after curative gastrectomy. This study aimed to identify predictive factors and develop a nomogram for predicting infectious complications prior to patient discharge. Between April 2019 and December 2023, clinicopathological data of 237 patients with gastric cancer who underwent curative gastrectomy at the Eunpyeong St. Mary's Hospital were retrospectively reviewed. C-reactive protein (CRP), white blood cell (WBC) count, neutrophil-lymphocyte ratio (NLR), and procalcitonin (PCT) levels were analyzed. Overall, 58 patients experienced postoperative complications, with 33 patients developing infectious complications. Univariate analysis revealed that the open approach, esophagus involving resection, advanced stage, and operation time were risk factors for infectious complications among clinicopathologic characteristics. Significant associations with laboratory parameters and body temperature (BT) were observed from postoperative day (POD) 1 to 5, with the highest area under the curve (AUC) observed for POD 5 data in receiver operating characteristic (ROC) analysis. Multivariate analysis incorporating clinicopathologic features and laboratory parameters on POD 5 identified age (OR=2.98), approach (OR=4.05), operation time (OR=2.74), WBC count (OR=4.09), NLR (OR=9.74), and CRP (OR=2.62) as selected factors. The developed nomogram stratified patients into low-risk (<10%), intermediate-risk (10~50%), and high-risk (≥50%) groups, corresponding to actual infectious complication rates of 1.84%, 28.3%, and 71.43%, respectively. This study presents a novel estimating model for infectious complications following curative gastrectomy. The utilization of this model in patient discharge planning can aid in identifying individuals who require additional treatment, thereby minimizing unexpected readmissions.