Optimal Strategy Research Articles

Jejunogastric intussusception associated with jejunojejunal intussusception (double telescoping) occurring 20 years after gastrojejunostomy.

Jejunogastric intussusception (JGI) is a rare but potentially lethal complication following gastrectomy or gastrojejunostomy surgeries. Diagnosis of this condition can be challenging due to its rarity and non-specific symptoms. This article presents a case report of a 60-year-old male with a history of trans mesocolic gastrojejunostomy who developed acute symptoms of JGI. The patient presented with acute epigastric pain, vomiting, and hematemesis. Physical examination and laboratory tests indicated dehydration, tachycardia, and leukocytosis. Computed tomography (CT) revealed intussuscepted loops within the stomach. Emergency laparotomy was performed, and the intussusception was manually reduced without the need for resection. The patient recovered well and was discharged five days post-surgery. Retrograde jejunogastric intussusception is a rare complication, often occurring years after gastric surgery. It can be classified into acute and chronic forms, with the former presenting with intense pain and potential hematemesis. The condition can arise in different surgical contexts and even spontaneously. The cause of JGI remains unclear, but factors such as hyperacidity, abnormal motility, and increased intra-abdominal pressure have been implicated. Diagnosis can be made through endoscopy or alternative imaging modalities such as CT. Surgical intervention is the treatment of choice, with various options available based on intraoperative findings. Retrograde jejunogastric intussusception is challenging to diagnose and treat due to its rarity and lack of understanding of its causes. Imaging techniques and endoscopy play important roles in diagnosis, while surgery remains the primary treatment option. Vigilance is necessary among medical professionals to consider JGI in cases of acute abdominal pain and vomiting following gastric surgery, allowing for prompt diagnosis and intervention to prevent bowel necrosis. Further research is needed to establish optimal surgical strategies and evaluate recurrence rates.

Establishment and characterization of two novel patient-derived cell lines from giant cell tumor of bone: NCC-GCTB8-C1 and NCC-GCTB9-C1.

Giant cell tumor of bone (GCTB) is a rare osteolytic bone tumor consisting of mononuclear stromal cells, macrophages, and osteoclast-like giant cells. Although GCTB predominantly exhibits benign behavior, the tumor carries a significant risk of high local recurrence. Furthermore, GCTB can occasionally undergo malignant transformation and distal metastasis, making it potentially fatal. The standard treatment is complete surgical resection; nonetheless, an optimal treatment strategy for advanced GCTB remains unestablished, necessitating expanded preclinical research to identify appropriate therapeutic options. However, only one GCTB cell line is publicly available from a cell bank for research use worldwide. The present study reports the establishment of two novel cell lines, NCC-GCTB8-C1 and NCC-GCTB9-C1, derived from the primary tumor tissues of two patients with GCTB. Both cell lines maintained the hallmark mutation in the H3-3A gene, which is associated with tumor formation and development in GCTB. Characterization of these cell lines revealed their steady growth, spheroid-formation capability, and invasive traits. Potential therapeutic agents were identified via extensive drug screening of the two cell lines and seven previously established GCTB cell lines. Among the 214 antitumor agents tested, romidepsin, a histone deacetylase inhibitor, and mitoxantrone, a topoisomerase inhibitor, were identified as potential therapeutic agents against GCTB. Conclusively, the establishment of NCC-GCTB8-C1 and NCC-GCTB9-C1 provides novel and crucial resources that are expected to advance GCTB research and potentially revolutionize treatment strategies.

Subscription Pricing for Free Delivery Services

Many firms that offer home delivery of products purchased online now provide consumers the option of subscribing to a membership plan for free delivery of limited or unlimited number of orders instead of customers paying delivery charges for each order. This paper seeks to understand the benefits to firms and consumers of introducing such free-delivery subscription (FDS) plans to complement their traditional pay-for-delivery (PFD) option, characterize the firm's optimal FDS subscription pricing strategy, and study the effects of product, consumer, and market characteristics on the subscription fees and firm's profits. We develop and analyze an economic model that incorporates salient features of product delivery settings that prior models of subscription pricing do not fully capture. The features include simultaneous availability of PFD and FDS options, lift in a consumer's demand when she switches from PFD to FDS, the possibility of attracting new consumers when the firm introduces FDS, and order batching by customers due to per-order delivery charges and free-delivery order allowances. Our utility-based approach to model consumers’ purchasing choices incorporates consumer heterogeneity both in terms of their utility for the product and their shopping preference under the PFD option. For homogeneous consumers, we show that introducing a FDS plan raises the firm's profit, establish the optimality of offering unlimited free-delivery allowance, and analyze comparative statics. With multiple customer types, our analysis of two subscription pricing strategies for FDS plans—a single “Universal” plan and multiple “Tiered” plans with varying subscription fees and free-delivery limits—leads to several interesting insights on delivery pricing strategies, as well as drivers and sensitivity of the optimal policy, profits, and number of subscribers. We supplement this analysis with extensive computational experiments that reveal a substantial increase in profits when a firm adds one or more FDS plans to its PFD option even though the optimal subscription fee(s) only covers part of the firm's actual shipping costs. These results also permit us to gauge the influence and understand the trends in the profitability of the Universal and Tiered plans as various parameters change.

ELUCIDATING THE MECHANISMS OF NEUTROPHIL EXTRACELLULAR TRAPS IN ACUTE RESPIRATORY DISTRESS SYNDROME PATHOGENESIS

This article critically examines the scientific literature related to the formation of neutrophil extracellular traps and their impact on the pathogenesis and clinical course of acute respiratory distress syndrome (ARDS). The available evidence indicates that the formation and accumulation of neutrophil extracellular traps in the lung tissue are implicated in the development and progression of ARDS. Moreover, recent studies have shed light on the potential mechanisms by which neutrophil extracellular traps contribute to impaired ventilationperfusion relationships in ARDS. The findings presented in this review suggest that further research into the phenomenon of neutrophil extracellular traps may lead to new insights into the pathophysiology of ARDS and inform the development of novel therapeutic strategies. Specifically, targeting neutrophil extracellular traps may offer a promising approach to attenuate the severity of ARDS and improve clinical outcomes. However, the complexity of the underlying mechanisms and the heterogeneity of ARDS patients necessitate further investigation to identify optimal therapeutic targets and treatment strategies.

Checkpointing Strategies to Tolerate Non-Memoryless Failures on HPC Platforms

This article studies checkpointing strategies for parallel applications subject to failures. The optimal strategy to minimize total execution time, or makespan, is well known when failure IATs obey an Exponential distribution, but it is unknown for non-memoryless failure distributions. We explain why the latter fact is misunderstood in recent literature. We propose a general strategy that maximizes the expected efficiency until the next failure, and we show that this strategy achieves an asymptotically optimal makespan, thereby establishing the first optimality result for arbitrary failure distributions. Through extensive simulations, we show that the new strategy is always at least as good as the Young/Daly strategy for various failure distributions. For distributions with high infant mortality (such as LogNormal with shape parameter k =2.51 or Weibull with shape parameter 0.5), the execution time is divided by a factor of 1.9 on average, and up to a factor 4.2 for recently deployed platforms.

Power sector carbon reduction review for South Korea in 2030

This study investigates the cost-effectiveness and decarbonization of four essential carbon reduction strategies to achieve Korea’s recent 2030 NDC (Nationally Determined Contribution) goal in the power sector. Examining overseas experiences and identifying potentials and challenges in implementing these strategies in Korea, this study explores the performance of future Korean power systems under fifty-four configurations combining these strategies. The evaluation results indicate that: 1) Thirty-one of the fifty-four tested configurations can achieve the emission target (149.9 MtCO2e) with carbon abatement costs (COA) ranging from -$89 to $105/tCO2e. The optimal configuration with the lowest COA is a combination of nuclear restoration and renewable expansion strategies. 2) Renewable expansion significantly reduces the COA and levelized cost of electricity (LCOE). A pure renewable expansion strategy with photovoltaics of 68 GW and wind turbines of 35 GW attains the emission goal at a COA of -$54/tCO2e, in which the generation share of renewables reaches 42%. 3) A carbon tax of $104/tCO2e achieves the target if complemented by nuclear restoration. Otherwise, $120/tCO2e is needed. The COA and LCOE are increases by switching from cheap coal to expensive natural gas in both cases. 4) Twenty percent coal–ammonia co-firing combined with a carbon tax of $32/tCO2e and nuclear restoration can achieve the goal with relatively high costs compared with the optimal strategies. However, a co-firing strategy is limited because the generation shrinks at a minimum level when 40%∼ mixing ratios are applied, or when the fuel price gap between ammonia and natural gas becomes large.

Energy performance analysis of alternative building retrofit interventions for the four climatic zones of Greece

Climatic conditions determine which retrofit strategy can result in a satisfactory improvement of a building's thermal performance. This study systematically investigates alternative retrofit actions, as standalone and in combination, and assesses their energy performance. The retrofit actions include i) insulation on the external walls, ii) the incorporation of phase change material (PCM) on the roof and the increase of the building thermal inertia, iii) a mechanical ventilation system with a summer period operation, and iv) a cool roof coating. The energy analysis concerns a typical two-story family building and the four climatic categories of Greece and is conducted with the INTEMA.building tool, a dynamic energy analysis software developed in Modelica language. The importance of the present study is that it serves as a guideline for the selection of the energetically optimum single retrofit or multiple-retrofit strategy regarding a building's location climatic data, and provides calculations concerning the annual heating and cooling loads, and the corresponding heat pump electricity consumption. The retrofit actions of external wall insulation and PCM roof addition are characterized as more effective in reducing a building's heating energy loads, while the mechanical ventilation system and cool roof coating are more effective in reducing a building's cooling loads. The quadruple retrofit strategy results in the maximum electricity savings for Heraklion (28.01%), Athens (21.15%), and Thessaloniki (16.54%), while the triple retrofit strategy which does not include the cool roof coating, results in the maximum electricity savings for Kastoria (10.79%). Lastly, an economic analysis of the energetically optimum renovation strategies is conducted.

A New Method to Solve Matrix Game with Interval Payoffs and its MATLAB Code

Game theory is of substantial significance in diverse domains, acting as a potent instrument to comprehend and assess strategic engagements among rational decision-makers. It formulates mathematical models to represent strategic interactions among rational decision-makers in the competitive world. Due to ambiguity in the real-world problems, acquiring the precise payoff values of a matrix game proves challenging. However, in numerous scenarios, these payoffs fluctuate within specific ranges, making them suitable for consideration as interval numbers. This leads to the formulation of a special form of game problem known as the interval valued game problem (IVGP). Some methodologies exist in the literature to find the optimal strategies as well as the value of game for IVGP, but most of them possess some limitations, resulting in the need for proposing a new methodology to find the optimal strategies and value of game. Thus, in this paper, a new solution method for game problems with payoffs represented as interval numbers is presented, utilizing the fuzzy concept. The process begins by transforming the interval payoffs into fuzzy numbers using a ranking function. Subsequently, these fuzzy payoffs are converted into crisp values, leading to the formulation of the crisp matrix game. The resulting crisp matrix game is then solved using linear programming approach. Additionally, MATLAB code for the proposed method is developed and proposed to streamline the computation process, enhancing comparison and decision-making efficiency, particularly when dealing with large payoff matrices. Furthermore, three numerical examples are provided to illustrate the validity of the proposed approach as well as its MATLAB code. A real-life example of IVGP in the realm of tourism industry is also provided. Finally, a comparative analysis is conducted, comparing the proposed method with some existing methods.

Information and selling mode strategies in a supply chain with an outsourced private label product

AbstractThis paper examines the interplay between the information strategy of an e‐commerce platform and the selling mode strategy of a manufacturer within a co‐opetitive supply chain, as well as the identification of the optimal supply chain strategy. We develop a supply chain model where a platform outsources production of its private label product to a manufacturer, who also sells its national brand product through the platform. The platform must decide whether to acquire consumer quality preference information at a cost and share it with the manufacturer, while the manufacturer needs to choose between the reselling mode or the agency selling mode for its national brand product. The two driving effects (competition‐intensification effect and mode differentiation effect) are identified. Our findings show that the platform will acquire and share information when the acquisition cost is sufficiently low, leading to the “competition‐intensification effect.” Additionally, the manufacturer prefers the agency selling mode when cost‐quality efficiency is low, and the reselling mode otherwise, driven by the “mode differentiation effect.” In cases where information sharing is absent, the manufacturer is more likely to choose the agency selling mode. Interestingly, when the cost‐quality efficiency of the manufacturer's product is moderate and the information acquisition cost is low, the “competition‐intensification effect” and the “mode differentiation effect” offset each other, resulting in the expansion of the region where the manufacturer chooses the reselling mode due to the platform's information‐sharing strategy. As a result, this enhances a cooperative relationship between the manufacturer and the platform. We also derive the optimal supply chain strategy, providing insights into both the manufacturer's selling mode and the platform's information strategies in online retailing.

Optimized Design of a H2-Powered Moped for Urban Mobility

Micro-mobility plays an increasingly important role in the current energy transition thanks to its low energy consumption and reduced contribution to urban congestion. In this scenario, fuel cell hybrid electric vehicles have several advantages over state-of-the-art battery electric vehicles, such as increased driving ranges and reduced recharge times. In this paper, we study the conversion of a commercial electric moped (Askoll eS3®) into a fuel cell hybrid electric vehicle by finding the optimal design of the components through an optimization methodology based on backward dynamic programming. This optimal design and operation strategy can also be implemented with a rules-based approach. The results show that a system composed of a 1 kW proton exchange membrane fuel cell, a 2000 Sl metal hydride hydrogen tank, and a 240 Wh buffer battery can cover the same driving range as the batteries in an electric moped (119 km). Such a hybrid system occupies considerably less volume (almost 40 L) and has a negligibly higher mass. The free volume can be used to extend the driving range up to almost three times the nominal value. Moreover, by using a high-pressure composite tank, it is possible to increase the mass energy density of the onboard energy storage (although compression can require up to 10% of the hydrogen’s chemical energy). The fuel cell hybrid electric vehicle can be recharged with green hydrogen that is locally produced. In detail, we analyze a residential scenario and a shared mobility scenario in the small Italian city of Viterbo.

Cultivation of Vitamin C-Rich Vegetables for Space-Radiation Mitigation

Space exploration introduces astronauts to challenges, such as space radiation and microgravity. Researchers have investigated vitamin C as a potential radiation mitigator, as well as antioxidants for sustaining astronaut health. Our own studies demonstrate vitamin C’s life-saving radioprotective effects and its potential as a radiation mitigator, thus highlighting promise, even when administered 24 h post-exposure. This is particularly relevant in scenarios where astronauts may be exposed to sudden large solar particle events, potentially resulting in lethal doses of space radiation. The success of vegetable cultivation on the International Space Station using NASA’s Veggie system offers fresh, vitamin C-rich food. While approved supplements address somatic function, further research is needed to optimize vitamin C’s efficacy in humans, and to develop appropriate antioxidant cocktails for space missions. The variable vitamin C content in vegetables underscores the necessity for the utilization of artificial intelligence (AI) to assist astronauts in selecting and cultivating the vitamin C-rich vegetables best-suited to combat high levels of space radiation and microgravity. Particularly, AI algorithms can be utilized to analyze various factors, such as nutritional content, growth patterns, and cultivation methods. In conclusion, vitamin C shows significant potential for mitigating space radiation, and ongoing research aims to enhance astronaut health through optimal dietary strategies.

Current Challenges in Operation, Performance, and Maintenance of Photovoltaic Panels

The installed solar capacity in the European Union has expanded rapidly in recent years. The production of these plants is stochastic and highly dependent on the weather. However, many factors should be considered together to estimate the expected output according to the weather forecast so that these new PV plants can operate at maximum capacity. Plants must be operated in coordination with maintenance operations and considering actual energy market prices. Various methods have recently been developed in the literature, ranging from the most impactful artificial-intelligence-based generation estimation methods to various diagnostic and maintenance methods. Moreover, the optimal operational and maintenance strategy usually depends on market regulation, and there are many concerns related to the distribution system operator. This review article aims to summarize and illustrate the challenges of operating and maintaining solar power plants and the economic and technical importance of these problems.

Exploring optimal outsourcing strategy with and without transfer payment

AbstractThis study investigates an original equipment manufacturer's (OEM's) outsourcing choice between a competing manufacturer (CP) and a non‐competing manufacturer (NP). We develop a benchmark self‐produce strategy and two outsourcing strategies to differentiate two manufacturing service providers, and examine the optimal strategy alongside an analysis of the respective incentives (e.g., a lump‐sum payment) from the two service providers. The optimal strategy depends on the difference in production efficiency, degree of product substitution, and joint effect of the transfer payments. The transfer payments contribute to a greater range of Pareto improvements, increasing the possibility of outsourcing cooperation while highlighting the role of competition intensity on the model and outsourcing cooperation partner. Effect analysis shows that in the absence of transfer payment, the optimal strategy is beneficial to social welfare. With transfer payment, the optimal strategy is changed and the firms will be more profitable, but at the expense of customers' surplus, which may result in worse social welfare. An extended analysis of mixed strategies, in which the OEM produces part of the products and outsources the rest to CP/NP, shows that while the mixed‐CP strategy can be an optimal choice, the mixed‐NP strategy will degenerate to either self‐produce or complete outsourcing to NP under certain conditions.

A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics.

Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 fecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: (i) 20 Gbp of Illumina short-read data, (ii) 40 Gbp of short-read data, (iii) 20 Gbp of PacBio HiFi long-read data, and (iv) 40 Gbp of hybrid (20 Gbp of short-read +20 Gbp of long-read) data. No strategy was best for all metrics; instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific and depends on how researchers assess the trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.

Optimal treatment strategy and prognostic analysis of salvage liver transplantation for patients with earlyhepatocellular carcinoma recurrence after hepatectomy.

We aimed to investigate the prognostic factors for salvage liver transplant in patients with early hepatocellular carcinoma recurrence after hepatectomy. This retrospective analysis included 53 patients who underwent salvage living-donor liver transplantation between January 2007 and January 2018. There were 24 and 29 patients in the early (recurrence ≤24months after primary liver resection) and the late recurrence groups, respectively. In the multivariate Cox regression model, pre-liver transplant downstaging therapy, early recurrence (ER) after primary liver resection , and recurrence-to-liver-transplant ≥12months were independent risks to predict recurrent hepatocellular carcinoma recurrence after salvage living-donor liver transplantation. Compared with the late recurrence group, the ER group showed lower disease-free survival rates (p<0.001); however, the overall survival rates did not differ between the two groups (p=0.355). The 1-, 3-, and 5-year disease-free survival rates were 83.3%, 70.6%, and 66.2%, and 96.0%, 91.6%, and 91.6% in the early and late recurrence groups, respectively. When stratified by recurrence-to-liver transplant time and pre-liver transplant downstaging therapy in the ER group, disease-free survival and overall survival rates were significantly different. ER after primary liver resection with advanced tumor status and a longer period of recurrence-to-liver-transplant (≥12months) have a negative impact on salvage liver transplant. Our findings provide novel recommendations for treatment strategies and eligibility for salvage liver transplant candidates.

Analyzing Microsoft stock price trends, factors, and market efficiency for optimal investment strategies

Microsoft, one of the tech giants, has seen significant fluctuations in its stock prices in recent years. This article delves into an analytical study of these changes using data sourced from Yahoo Finance. The background for this research stems from the desire to understand the intricacies of stock price movements and the factors influencing them, especially for prominent companies like Microsoft that have a vast impact on global markets. The methodology adopted for this study is the technical approach, where the moving average is calculated to determine the stocks trend. Moving averages are a cornerstone of technical analysis and can provide insights into potential buy and sell signals. By employing this method, the research aims to validate the appropriateness of certain investment strategies based on historical data. The primary objective of the study is not just to chart the course of the stocks price but to delve deeper into the causative factors behind its movement. Various external and internal factors can influence stock prices, from global economic trends to company-specific news. By analyzing these factors, the research also seeks to test the efficiency of the market, a long-debated topic among economists and investors. In conclusion, while past data can offer insights, the stock markets volatile nature demands continuous adaptation of investment strategies. The findings from this study can serve as a foundation for developing more refined prediction tools and investment tactics. Future studies might consider integrating more sophisticated models or incorporating other predictive variables to enhance accuracy and investment outcomes.

Personalizing renal replacement therapy initiation in the intensive care unit: a reinforcement learning-based strategy with external validation on the AKIKI randomized controlled trials.

The timely initiation of renal replacement therapy (RRT) for acute kidney injury (AKI) requires sequential decision-making tailored to individuals' evolving characteristics. To learn and validate optimal strategies for RRT initiation, we used reinforcement learning on clinical data from routine care and randomized controlled trials. We used the MIMIC-III database for development and AKIKI trials for validation. Participants were adult ICU patients with severe AKI receiving mechanical ventilation or catecholamine infusion. We used a doubly robust estimator to learn when to start RRT after the occurrence of severe AKI for three days in a row. We developed a "crude strategy" maximizing the population-level hospital-free days at day 60 (HFD60) and a "stringent strategy" recommending RRT when there is significant evidence of benefit for an individual. For validation, we evaluated the causal effects of implementing our learned strategies versus following current best practices on HFD60. We included 3748 patients in the development set and 1068 in the validation set. Through external validation, the crude and stringent strategies yielded an average difference of 13.7 [95% CI -5.3 to 35.7] and 14.9 [95% CI -3.2 to 39.2] HFD60, respectively, compared to current best practices. The stringent strategy led to initiating RRT within 3 days in 14% of patients versus 38% under best practices. Implementing our strategies could improve the average number of days that ICU patients spend alive and outside the hospital while sparing RRT for many. We developed and validated a practical and interpretable dynamic decision support system for RRT initiation in the ICU.

Manufacturer’s optimal distribution strategy in the platform supply chain: Bundling or add-on?

AbstractThis study delves into the realm of distribution strategies employed in retail markets, particularly focusing on the widely utilized bundle-and-add-on strategy. Three distinct distribution strategies are examined: bundled-by-the-base-manufacturer (BBBM), bundled-by-the-platform, and the add-on approach within a platform supply chain context. Through comprehensive analysis, this paper investigates the optimal distribution strategy for manufacturers. Significantly, our research reveals that in cases where only bundling is feasible, base manufacturers can reap benefits from a self-bundling strategy when both the platform’s commission rate and the marginal cost of the bundled product are low. Additionally, the platform stands to gain from this approach when the commission rate is low, and the marginal cost of the bundled product is either moderate or very high. Notably, win–win scenarios can emerge for both manufacturers and platforms through specific bundling or platform bundling strategies under specific conditions. Furthermore, the study demonstrates that the price of bundles under the add-on strategy will be lower, attracting more consumers, especially when the commission rate is low. Intriguingly, when the marginal cost of the base product is low, the add-on strategy consistently emerges as the optimal choice; as costs escalate, BBBM might be optimal, especially when the commission rate is low, showcasing a nuanced understanding of the interplay between costs and strategic choices in distribution. The major contribution of this paper lies in its nuanced analysis of these strategies and their implications for both manufacturers and platforms in the retail landscape.

Pain Correlates in Endodontic Procedures: A Narrative Review Examining the Causative Factors and Clinical Approaches for Management.

Endodontic treatment, encompassing the diagnosis and management of dental pulp and periapical conditions, is pivotal in preserving dental health. Root canal treatment, a common endodontic procedure, involves the removal, cleaning, and sealing of the tooth's root system to address issues like pain and infections. Patients undergoing endodontic procedures often encounter pain due to the sensitivity of dental pulp nerves to caries, inflammation, infections, or treatment manipulations. The severity of pain is variable and influenced by individual factors such as pain threshold, anxiety levels, gender, and the extent of dental infection. In conclusion, despite advancements in endodontics, pain management remains a significant concern. The narrative review emphasizes the importance of adopting comprehensive clinical management strategies encompassing the entire treatment process. A thorough assessment of the patient's medical history and dental condition is crucial to identify risk factors for increased pain. Effective communication with patients regarding the procedure and potential discomfort aids in managing expectations and reducing anxiety. Continuous professional development is highlighted as essential for dental professionals to stay abreast of the latest advancements, enabling the implementation of optimal pain management strategies and the delivery of enhanced patient care.

The Role of The Marketing Mix Factors in Hospital Selection

Background: The problems faced by Soerojo Hospital is currently decreasing the number of outpatient visits and decreasing customer satisfaction. Marketing mix analysis based on satisfaction surveys which on average are good based on hospital customer perceptions and targeted revenue targets from out-of-pocket sources of 30 percent require the right marketing mix tactics for potential customers in the comunity. This study will help Soerojo Hospital choose dominant factor of the marketing mix in hospital selection for making optimal marketing strategy. The aims of this study was to identify the role of the marketing mix factors on people's decisions in hospital selection. Materials and Methods: This study was conducted with a descriptive, quantitative approach, cross sectional research design, 385 respondents were surveyed with questionnaires and data analysis was carried out with program packages. Results: The components of the marketing mix that occupy the top three positions are the location component with a median of 4.67(1-5), the process component with a median of 4.60 (1-5) and the cost component with a median of 4.50 (1-5). There was a significant difference between the groups who choose and did not choose Soerojo mental hospital in the doctor/staff and promotion (p value &lt;0.05). Conclusion: The location, process and cost components are the components of the marketing mix that most influence the decision to choose a hospital. Suggestions for improvements that can be made by RSJ Prof. Dr. Soerojo Magelang based on the results of this study.