Multiple Problems Research Articles

An efficient global optimization algorithm for a class of linear multiplicative problems based on convex relaxation

An efficient global optimization algorithm for a class of linear multiplicative problems based on convex relaxation

Robust Multiple Stopping—A Duality Approach

We develop a method to solve, theoretically and numerically, general optimal stopping problems. Our general setting allows for multiple exercise rights—that is, optimal multiple stopping—for a robust evaluation that accounts for model uncertainty with a dominated family of priors and for general reward processes driven by multidimensional jump-diffusions. Our approach relies on first establishing robust martingale dual representation results for the multiple stopping problem that satisfy appealing almost sure pathwise optimality properties. Next, we exploit these theoretical results to develop upper and lower bounds that, as we formally show, not only converge to the true solution asymptotically, but also constitute genuine prelimiting upper and lower bounds. We illustrate the applicability of our approach in a few examples and analyze the impact of model uncertainty on optimal multiple stopping strategies. Funding: R. J. A. Laeven received financial support from the Netherlands Organization for Scientific Research (NWO) [Grants NWO-Vidi and NWO-Vici]. J. G. M. Schoenmakers received financial support from the Deutsche Forschungsgemeinschaft Excellence Cluster Math+ Berlin [Project AA4-2]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/moor.2021.0237 .

A simulation-based DEA approach for multiple criterion decision-making problems with uncertain mixed-criteria values

In ex-ante decision scenarios, predicting criterion values accurately is difficult for decision makers (DMs). Inconsiderable work is normally required for measuring criteria by uncertain random values or ordinal values. However, in the classical data envelopment analysis (DEA) model, criterion values are the constants that limit the application of the classical DEA model in ex-ante decision scenarios. This paper presents a simulation-based DEA approach, which captures random and ordinal criterion values by a simple and direct simulation-based approach. The approach includes three steps. In the first step, Monte Carlo simulation methods are used to convert uncertain random values or ordinal values into cardinal data. In the second step, we use traditional DEA methods to compute the efficiency score of decision-making units (DMUs). In the third step, we ranked all DMUs by calculating the DEA-efficient acceptability of each DMU in multiple simulations and then selected the optimal DMU. The proposed approach is illustrated by experimental examples and a case study of a municipal wastewater treatment system.

LEADERSHIP CHALLENGES IN DEVELOPING COUNTRIES: A CASE STUDY OF PAKISTANI HIGHER SECONDARY SCHOOLS

The main objective of the research was to explore public school principals’ leadership problems and the techniques they used to overcome those problems. A qualitative research case study was conducted involving 10 public school principals (5 male and 5 female) from district Mardan of Pakistan. The data were gathered through semi-structured interviews and analyzed using the thematic analysis process. The results show that public school principals in Pakistan face multiple problems, including lack of authority, insufficient assistance from higher authorities, lack of resources, and teacher recruitment and retention issues. Additionally, the research also found that public school principals in Pakistan combat their problems with a variety of techniques, including creating a friendly rapport with teachers, engaging the community in the educational process, seeking help from higher authorities, and effectively leveraging resources. Moreover, this research has also examined Pakistani female public school principals’ problems and tactics. The results show that female public-school principals in Pakistan experience typical male principals’ problems, including lack of autonomy, insufficient resources, and support from higher authorities, as well as gender inequity. The results of the study have significant implications for policy and practice as the results of the study can inform specific policies and practices that can help in enlightening public schools’ leadership in Pakistan to improve the quality of education for students.

What can social workers do to help the growing number of people experiencing homelessness? The view from an urban hospital Emergency Department

Homelessness is a growing problem nationwide. According to the U.S. Department of Housing and Urban Development (HUD), the number of people experiencing homelessness rose 12% from 2022 to 2023 (HUD Exchange, 2024b). Low vacancy rates, increased rent costs, and income inequality all comprise difficult structural factors locking people out of the housing market. Those who most harshly bear the brunt of this crisis are people with social vulnerabilities. This paper analyzes the social problem of homelessness from the perspective of an urban hospital Emergency Department (ED), Yale New Haven Hospital (YNHH) in New Haven, Connecticut. Social workers in these settings have a dual role: working directly with individuals and families to connect them with available services and resources and advocating for structural interventions that can ultimately ease this problem. Social workers are also at the forefront of combating any stigma unhoused persons face by both approaching patients experiencing homelessness with dignity and respect while educating others that this problem is not one of the individual, but is rather a consequence of multiple other social problems we have collectively failed to address.

Fast Matrix Multiplication for Query Processing

This paper studies how to use fast matrix multiplication to speed up query processing. As observed, computing a two-table join and then projecting away the join attribute is essentially the Boolean matrix multiplication problem, which can be significantly improved with fast matrix multiplication. Moving beyond this basic two-table query, we introduce output-sensitive algorithms for general join-project queries using fast matrix multiplication. These algorithms have achieved a polynomially large improvement over the classic Yannakakis framework. To the best of our knowledge, this is the first theoretical improvement for general acyclic join-project queries since 1981.

YouTube Videos Are a Moderately Comprehensive, Reliable, and Quality Option to Learn About “Multiple Sclerosis and Sexuality”

Objectives This study aimed to evaluate the performance, comprehensiveness, reliability, and quality of English-language YouTube videos addressing the subject of multiple sclerosis and sexuality. Methods In August 2023, a search was conducted on a computer using the keywords “multiple sclerosis and sexuality,” “multiple sclerosis and sexual health,” “multiple sclerosis and sexual health problems,” and “multiple sclerosis and sexual dysfunction” for this descriptive study. According to predetermined inclusion and exclusion criteria, 38 videos that met the research purpose were examined. The related URLs were recorded. For each video, the following information was collected: content producers, performance with YouTube statistics, comprehensiveness with a form developed by researchers, reliability with Singh’s Reliability Evaluation Form, and quality with Global Quality Scale. Two researchers independently evaluated the videos. Results Eighty-nine and a half percent of the videos contained information presented by professionals. The average number of views was 2699.132 ± 3382.848, the comprehensiveness score was 4.2 ± 1.711, the reliability score was 3.184 ± 1.182, and the quality score was 3.421 ± 1.2. Nearly half (42.2%) contained good and useful information for viewers, and half (50%) had high video quality. The reliability and quality scores of videos containing each item in terms of comprehensiveness were higher compared to videos that did not include that item (p < 0.05). In addition, the videos with higher comprehensiveness scores had higher quality and reliability scores (p < 0.001). Conclusion These results underscore the constrained performance attributes of YouTube videos addressing multiple sclerosis and sexuality, with their content exhibiting a moderate level of comprehensiveness, reliability, and quality. These results may provide a basis for increasing the effectiveness of YouTube videos on multiple sclerosis and sexuality.

Providing optimal care in the neonatal care units in India: How Covid-19 exacerbated existing barriers.

Nearly one quarter (600,000) of all neonatal deaths worldwide per year occur in India. To reduce neonatal mortality, the Indian Ministry of Health and Family Welfare established neonatal care units, including neonatal intensive care units and specialized neonatal care units to provide immediate care at birth, resuscitation for asphyxiation, postnatal care, follow up for high-risk newborns, immunization, and referral for additional or complex healthcare services. Despite these efforts, neonatal mortality remains high, and measures taken to reduce mortality have been severely challenged by multiple problems caused by the Covid-19 pandemic. In this qualitative study, we conducted seven focus group discussions with newborn care unit nurses and pediatric residents and 35 key informant interviews with pediatricians, residents, nurses, annual equipment maintenance contractors, equipment manufacturers, and Ministry personnel in the Vidarbha region of Maharashtra between December 2019 and November 2020. The goal of the study was to understand barriers and facilitators to providing optimal care to neonates, including the challenges imposed by the Covid-19 pandemic. Covid-19 exacerbated existing barriers to providing optimal care to neonates in these newborn care units. As a result of Covid-19, we found the units were even more short-staffed than usual, with trained pediatric nurses and essential equipment diverted from newborn care to attend to patients with Covid-19. Regular training of neonatal nursing staff was also disrupted due to Covid-19, leaving many staff without the skills to provide optimate care to neonates. Infection control was also exacerbated by Covid-19. This study highlights the barriers to providing optimal care for neonates were made even more challenging during Covid-19 because of the diversion of critically important neonatal equipment and staff trained to use that equipment to Covid-19 wards. The barriers at the individual, facility, and systems levels will remain challenging as the Covid-19 pandemic continues.

Accelerating Process Development and Product Formulation.

Currently, the lengthy time needed to bring new drugs to market or to implement postapproval changes causes multiple problems, such as delaying patients access to new lifesaving or life-enhancing medications and slowing the response to emergencies that require new treatments. However, new technologies are available that can help solve these problems. The January 2023 NIPTE pathfinding workshop on accelerating drug product development and approval included a session in which participants considered the current state of product formulation and process development, barriers to acceleration of the development timeline, and opportunities for overcoming these barriers using new technologies. The authors participated in this workshop, and in this article have shared their perspective of some of the ways forward, including advanced manufacturing techniques and adaptive development. In addition, there is a need for paradigm shifts in regulatory processes, increased pre-competitive collaboration, and a shared strategy among regulators, industry, and academia.

Causality-aware social recommender system with network homophily informed multi-treatment confounders

Typical recommender systems utilize observed ratings of users as inputs to learn their preferences and aim to output recommendations of new items that users will like by predicting their potential ratings. The real world is driven by causality given that whether or not a user is made exposed to the item may significantly affect the rating. While some recent methods have taken a causal view to mitigate the confounding bias in observed rating data, few have recognized recommendation as a multiple causal inference problem that concerns numerous items simultaneously in practice. By framing the recommendation as a multiple causal inference problem, this paper develops a causality-aware social recommender that incorporates underlying social network structures with matrix factorization methods for deconfounding in networked observational data to enhance social recommendations. Leveraging social network information, which inherently confounds with the preferences of users, is particularly crucial but not trivial for inferring unobserved confounders in social recommender systems. Considering that connected users in a social network share similar attributes, we propose to incorporate the network homophily into the matrix factorization models through regularization to better learn the latent variables. The extracted latent variables then capture the network informed multi-treatment confounders to mitigate the confounding bias and improve the rating prediction accuracy. The models are estimated through a proximal gradient-based optimization framework, which not only eases the incorporation of the network structure constraints but also improves the computational efficiency of the proposed method. Simulation and case studies are conducted to validate the proposed method.

Surgical aortic valve replacement in a patient with severe scoliosis

Aortic valve replacement for severe symptomatic Aortic stenosis is a low-risk procedure, but when compounded with coexisting conditions, procedural risk may increase. We present the case of a middle-aged female patient presenting with a constellation of complexities, including oblique sternum, severe dextroscoliosis, severe symptomatic aortic stenosis with bicuspid aortic valve, aortic root distortion, and a relatively rare blood group. Despite multiple problems, she underwent successful surgical aortic valve replacement. This case highlights the importance of a multidisciplinary approach in complex cardiac patients with the utmost need for a heart team concept for patient-centric decision-making.

A Study of the scattering analysis of the multiplicative Sturm-Liouville problem

A Study of the scattering analysis of the multiplicative Sturm-Liouville problem

Multiple Table Models Based on Queuing Theory for Firefighting Traffic Problems

With the development of global urbanization, urban planning has been a hot spot of most concern. Since the traditional urban fire station setting method has been gradually unable to meet the emergency needs of a city. In this paper, a series of methods are developed to achieve the best balance between economic expenditure and reliability. According to the heat maps about emergency calls in a city in recent years, different types of alarm phones have obvious regional distribution characteristics. Inspired by the Queuing Theory algorithm, we abstract this complex problem into a parallel multi-server waiting queuing model to find each average queue length of three kinds of alarm calls and success in converting the multiplicity problem into solving the vehicle number and location problems respectively. Based on this planning problem, new combinations with different numbers of vehicles can be gotten. Then based on the assignment model, the optimal deployment plan can also be different with different numbers and geographical locations of the three kinds of stations. Our method significantly improves the firefighting traffic problems and can be applied in the actual situation.

Development of aids to relieve vulvodynia during the postpartum period.

Postpartum women live with a low quality of life due to pain caused by episiotomy and perineal laceration. In particular, they endure pain when sitting for long periods of time to breastfeed. The purpose of this study is to develop a sitting aid to alleviate postpartum vulvodynia. This study was conducted in the following four phases from July 2017 to May 2019. They are: material selection and molding, cleaning and disinfection testing, pressure distribution measurement testing, and trial testing by postpartum women. The main material was a 100% polypropylene object with a three-dimensional reticular fiber spring structure and fiber density of 3.8 kg/m2. As a result, a sitting aid that withstands washing and disinfection well in the medical field and is breathable. It had moderate resilience and elasticity and reduced pressure on the seating surface for women weighing approximately 45 kg and 55 kg, but we were skeptical about its use for women weighing more than that. The completed sitting aid is noninvasively effective in improving the quality of life of many postpartum women, but the density and thickness of the main material should be reexamined to meet the needs of women in a wider weight range. In addition, a self-administered questionnaire survey of trial users revealed that some women did not experience relief from vulvodynia even after using the sitting aid. Such women also had physical problems such as discomfort in the lower back, difficulty breastfeeding, and difficulty standing up. For women with multiple physical problems, individual causes should be addressed.

A conceptual framework on pre- and post-displacement stressors: the case of Syrian refugees.

Researchers have documented multiple stressors and mental health problems along the journey of refugees as they are displaced to seek refuge in nearby and remote host countries. This article examines published research on Syrian refugees to propose a framework to conceptualize Syrian refugees' pre- and post-stressors and their collective impact on their mental health. The proposed framework provides a comprehensive understanding of the interconnected pathways between pre-displacement stressors, post-displacement stressors, and mental health outcomes for Syrian refugees. Pre-displacement stressors are best captured by the concept of trauma centrality and emotional suppression. Post-displacement stressors, categorized under financial, political, and social themes, have a direct impact on the mental health of the refugees, but could also play a partial mediating role on the impact of pre-displacement stressors on mental health. The framework suggests a direct pathway between the experience of war-related traumatic events and mental health and introduces the country of residence as a potential moderator of the severity of mental health. The latter is primarily influenced by local policies and the host communities' acceptance of refugees. We believe that the proposed framework can guide the work of researchers, policymakers, and practitioners concerned with the mental health and well-being of Syrian refugees. Additionally, although based on the experience of Syrian refugees, it presents a holistic perspective that could be adapted in other refugee settings.

Relationship Between Sleep Problems and Memory Impairment Among Nurses.

Sleep problems are common among nurses and can lead to various health problems. Further, the relationship between multiple sleep problems and memory impairment in clinical nurses remains unknown. Therefore, in this study, we aimed to explore the relationship between sleep problems and memory impairment among nurses. Multistage cluster-stratified random sampling was performed from tertiary hospitals in Shandong, China. Overall, a total of 1833 nurses were included in the final analysis. The Chinese version of the Pittsburgh Sleep Quality Index and prospective and retrospective memory questionnaire were administered to the participants. The sleep quality of the nurses decreased during the normal epidemic prevention and control period compared with that before the epidemic in terms of sleep duration, sleep efficiency, and sleep disturbances. Nurses who reported cumulative or specific sleep problems (e.g., high sleep latency, sleep disturbances, and daytime dysfunction) and those in the "daily disturbances" and "poor sleep quality" groups had a higher risk of memory impairment than the others. Sleep problems might be important for memory impairment among nurses. These findings may help identify nurses at considerable risk of memory impairment in clinical practice.

Modified crayfish optimization algorithm for solving multiple engineering application problems

Crayfish Optimization Algorithm (COA) is innovative and easy to implement, but the crayfish search efficiency decreases in the later stage of the algorithm, and the algorithm is easy to fall into local optimum. To solve these problems, this paper proposes an modified crayfish optimization algorithm (MCOA). Based on the survival habits of crayfish, MCOA proposes an environmental renewal mechanism that uses water quality factors to guide crayfish to seek a better environment. In addition, integrating a learning strategy based on ghost antagonism into MCOA enhances its ability to evade local optimality. To evaluate the performance of MCOA, tests were performed using the IEEE CEC2020 benchmark function and experiments were conducted using four constraint engineering problems and feature selection problems. For constrained engineering problems, MCOA is improved by 11.16%, 1.46%, 0.08% and 0.24%, respectively, compared with COA. For feature selection problems, the average fitness value and accuracy are improved by 55.23% and 10.85%, respectively. MCOA shows better optimization performance in solving complex spatial and practical application problems. The combination of the environment updating mechanism and the learning strategy based on ghost antagonism significantly improves the performance of MCOA. This discovery has important implications for the development of the field of optimization.Graphical

Crown Ether Electrolyte Induced Li2O2 Amorphization for Low Polarization and Long Lifespan Li‐O2 batteries

Lithium‐oxygen batteries possess an extremely high theoretical energy density, rendering them a prime candidate for next‐generation secondary batteries. However, they still face multiple problems such as huge charge polarization and poor cycle life, which lay a significant gap between laboratory research and commercial applications. In this work, we adapt 15‐crown‐5 ether (C15) as solvent to regulate the generation of discharge products in lithium‐oxygen batteries. The coronal structure endows C15 with strong affinity to Li+, firmly stabilizes the intermediate LiO2 and discharge product Li2O2. Thus, the crystalline Li2O2 is amorphized into easily decomposable amorphous products. The lithium‐oxygen batteries assembled with 0.5 M C15 electrolyte show an increased discharge capacity from 4.0 mAh cm−2 to 5.7 mAh cm−2 and a low charge overpotential of 0.88 V during the whole lifespan at 0.05 mA cm−2. The batteries with 1 M C15 electrolyte can cycle stably for 140 cycles. Furthermore, the amorphous characteristic of Li2O2 product is preserved when matched with redox mediators such as LiI, with the charge polarization further decreasing to 0.74 V over a cycle life of 190 cycles. This provides new possibilities for electrolyte design to promote Li2O2 amorphization and reduce charge overpotential in lithium‐oxygen batteries.

Crown Ether Electrolyte Induced Li2O2 Amorphization for Low Polarization and Long Lifespan Li-O2 batteries.

Lithium-oxygen batteries possess an extremely high theoretical energy density, rendering them a prime candidate for next-generation secondary batteries. However, they still face multiple problems such as huge charge polarization and poor cycle life, which lay a significant gap between laboratory research and commercial applications. In this work, we adapt 15-crown-5 ether (C15) as solvent to regulate the generation of discharge products in lithium-oxygen batteries. The coronal structure endows C15 with strong affinity to Li+, firmly stabilizes the intermediate LiO2 and discharge product Li2O2. Thus, the crystalline Li2O2 is amorphized into easily decomposable amorphous products. The lithium-oxygen batteries assembled with 0.5 M C15 electrolyte show an increased discharge capacity from 4.0 mAh cm-2 to 5.7 mAh cm-2 and a low charge overpotential of 0.88 V during the whole lifespan at 0.05 mA cm-2. The batteries with 1 M C15 electrolyte can cycle stably for 140 cycles. Furthermore, the amorphous characteristic of Li2O2 product is preserved when matched with redox mediators such as LiI, with the charge polarization further decreasing to 0.74 V over a cycle life of 190 cycles. This provides new possibilities for electrolyte design to promote Li2O2 amorphization and reduce charge overpotential in lithium-oxygen batteries.

Testing the Weak Efficient Market Hypothesis of Chinese Stock Market--Based on the Market Performance of Representative Stock Investment Portfolios in the HS300 Index

Chinas domestic stock market has developed very quickly overall in the more than 30 years since it was established, but information effectiveness in the Chinese stock market still faces multiple problems, so testing the weak efficient market hypothesis of the Chinese stock market is a good way to test its information quality and give investors relevant advice. This article selected representative stocks from the HS300 index, gathered the stocks historical data, used the index model to construct an optimal portfolio, and used another part of historical data to test if the portfolio has continuous excess return compared with the market portfolio and risk-free asset. The article finds excess return for the optimal portfolio during a long period and cannot prove that the Chinese stock market is weak and efficient. This result will provide a certain theoretical basis for investors who use technical analysis for stock investment and may also indicate that many issues still need to be addressed in the Chinese stock market, such as information asymmetry, high transaction costs, and insufficient regulation.