Set Of Problems Research Articles

Guanabenz acetate, an antihypertensive drug repurposed as an inhibitor of Escherichia coli biofilm.

Biofilm-associated bacterial infections are one of the major problems in medical settings. There are currently limited biofilm inhibitors available for clinical use. Guanabenz acetate, a drug used to treat high blood pressure, was found to be an effective anti-biofilm agent against Escherichia coli. Our results show that this drug can inhibit the production of cellulose and curli amyloid protein, which are the two main components of E. coli biofilms. Our findings highlight the possibility of repurposing a drug to prevent E. coli biofilm formation.

Digital-analog counterdiabatic quantum optimization with trapped ions

Abstract We introduce a hardware-specific, problem-dependent digital-analog quantum algorithm of a counterdiabatic quantum dynamics tailored for optimization problems. Specifically, we focus on trapped-ion architectures, taking advantage from global Mølmer–Sørensen gates as the analog interactions complemented by digital gates, both of which are available in the state-of-the-art technologies. We show an optimal configuration of analog blocks and digital steps leading to a substantial reduction in circuit depth compared to the purely digital approach. This implies that, using the proposed encoding, we can address larger optimization problem instances, requiring more qubits, while preserving the coherence time of current devices. Furthermore, we study the minimum gate fidelity required by the analog blocks to outperform the purely digital simulation, finding that it is below the best fidelity reported in the literature. To validate the performance of the digital-analog encoding, we tackle the maximum independent set problem, showing that it requires fewer resources compared to the digital case. This hybrid co-design approach paves the way towards quantum advantage for efficient solutions of quantum optimization problems.

Using an app-based screening tool to predict deficits in written word spelling at school entry

IntroductionThe first year of schooling is crucial for the further development of spelling abilities in children, which makes early assessment and intervention essential. The aim of this study was to develop and validate an efficient and cost-free screening tool for identifying spelling problems in community school settings around the time of school entry.MethodsA broad range of precursors of spelling (vocabulary, grammar, letter knowledge, phonological awareness, phonological working memory, rapid automatized naming) were assessed in 522 Austrian first graders (6–7 years of age) in the first weeks of schooling. At the end of first grade, spelling abilities were assessed by newly developed spelling tasks based on the trochaic foot. By applying logistic regression with the least absolute shrinkage and selection operator (LASSO), we aimed to select a set of important predictors of spelling problems at the end of grade 1 (i.e., scoring below the 16th percentile in the spelling test).ResultsOur analysis identified letter knowledge (i.e., an aspect of phonological information processing) and sentence repetition (i.e., a measure of grammatical knowledge) as important predictors of spelling problems. The screening tool has acceptable diagnostic accuracy [area under the curve (AUC) = 0.0.725 and DeLong 95% CI (0.666, 0.784)]. Further analyses indicated that the AUC differs neither between boys and girls nor between children with and without German as their first language.DiscussionThese results suggest that administering the screening tool during the first weeks of schooling is a valid approach to identifying spelling deficits, which in turn enables early targeted pedagogical interventions. Practical implications for spelling instructions are discussed.

Efficiently Constructing Convex Approximation Sets in Multiobjective Optimization Problems

Convex approximation sets for multiobjective optimization problems are a well-studied relaxation of the common notion of approximation sets. Instead of approximating each image of a feasible solution by the image of some solution in the approximation set up to a multiplicative factor in each component, a convex approximation set only requires this multiplicative approximation to be achieved by some convex combination of finitely many images of solutions in the set. This makes convex approximation sets efficiently computable for a wide range of multiobjective problems: even for many problems for which (classic) approximations sets are hard to compute. In this article, we propose a polynomial-time algorithm to compute convex approximation sets that builds on an exact or approximate algorithm for the weighted sum scalarization and is therefore applicable to a large variety of multiobjective optimization problems. The provided convex approximation quality is arbitrarily close to the approximation quality of the underlying algorithm for the weighted sum scalarization. In essence, our algorithm can be interpreted as an approximate version of the dual variant of Benson’s outer approximation algorithm. Thus, in contrast to existing convex approximation algorithms from the literature, information on solutions obtained during the approximation process is utilized to significantly reduce both the practical running time and the cardinality of the returned solution sets while still guaranteeing the same worst-case approximation quality. We underpin these advantages by the first comparison of all existing convex approximation algorithms on several instances of the triobjective knapsack problem and the triobjective symmetric metric traveling salesman problem. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms–Discrete. Funding: This research was supported by the German Research Foundation [Project 398572517]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0220 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0220 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

An approximation algorithm for the prize-collecting connected dominating set problem

An approximation algorithm for the prize-collecting connected dominating set problem

Validity and reliability of the Japanese version of the Substance Use Stigma Mechanism Scale.

Stigma against people who have alcohol and drug problems severely affects their health and well-being. An instrument based on stigma theory assessing individual-level stigma is essential for a comprehensive understanding of their stigma. We evaluated the validity and reliability of the Japanese version of the Substance Use Stigma Mechanism Scale (SU-SMS-J) among a population who had alcohol or drug use problems. Adults with experience in substance use disorders from psychiatry outpatient departments and rehabilitation facilities participated in the self-administered questionnaire survey. Confirmatory factor analysis was conducted to test the structural validity of the 5-factor model proposed in other language versions, and factor loadings and correlation between the subscales were confirmed. The correlations between the SU-SMS-J and psychometric properties related to substance use (e.g., severity of substance use, motivation to change) were investigated to assess concurrent validity. Internal consistency was assessed using Cronbach's alpha coefficients. Data from 126 participants were analyzed. The 5-factor model was acceptable with good or reasonable model fit indices. The correlations between subscales were weak to moderate, and this result suggested the SU-SMS-J assessed different but related components of stigma: enacted, anticipated, and internalized stigma from different stigma sources (family and healthcare workers). The SU-SMS-J and subscales showed moderate concurrent validity. Internal consistency was mostly sufficient, with Cronbach's alpha coefficients of 0.86 for all items and 0.66-0.93 for subscales. The SU-SMS-J is valid and reliable for use among populations with substance use problems in various settings in Japan.

Students’ commognitive conflicts in solving absolute value inequalities

The material of absolute value inequalities is considered more difficult to study. There are still many undergraduate students who still make mistakes in understanding and solving problems related to this topic. Moreover, some of them do not yet know how to read the symbols. Therefore, these issues need to be studied more thoroughly. This research was conducted to explore the undergraduate students’ discourse on absolute value inequality tasks through commognitive analysis. A qualitative approach was applied, involving 78 participants; 11 of them were further interviewed. The analysis of the absolute value inequality tasks and the interview results revealed that there were commognitive conflicts that needed to be addressed. The findings of this research showed that commognitive conflicts arose when the undergraduate students applied the definition of absolute value and determined the solution set for the absolute value inequality problems.

Non-existence of cusps for a free-boundary problem for water waves

In Varvaruca and Weiss (2011), Varvaruca and Weiss eliminate the existence of cusps for a free-boundary problem for two-dimensional water waves under assumptions that hold for solutions for which \{u>0\} is a “strip-like” domain in the sense of Varvaruca (2008). In this paper, it is proven that cusps do not exist in the natural setting for these free-boundary problems. In particular, non-strip-like domains are also allowed. This qualitative result follows from quantitative results which, roughly speaking, give lower bounds on the “slope” at which the free boundary approaches a stagnation point. This builds upon recent work on non-existence of cusps in McCurdy and Naples (2022) for local minimizers.

On greedy approximation algorithm for the minimum resolving dominating set problem

On greedy approximation algorithm for the minimum resolving dominating set problem

Existence and density theorems of Henig global proper efficient points

In this work, we provide some novel results that establish both the existence of Henig global proper efficient points and their density in the efficient set for vector optimization problems in arbitrary normed spaces. Our results do not require the assumption of convexity, and in certain cases, can be applied to unbounded sets. However, it is important to note that a weak compactness condition on the set (or on a section of it) and a separation property between the order cone and its conical neighbourhoods remains necessary. The weak compactness condition ensures that certain convergence properties hold. The separation property enables the interpolation of a family of Bishop-Phelps cones between the order cone and each of its conic neighbourhoods. This interpolation, combined with the proper handling of two distinct types of conic neighbourhoods, plays a crucial role in the proofs of our results, which include as a particular case other results that have already been established under more restrictive conditions.

Curriculum Reform of Preschool Education: An Innovative Path based on Gamification and Project-style Integration

This paper focuses on the curriculum reform of preschool education, and expounds the importance, purpose and challenges of preschool education curriculum reform under the background of educational needs in the new era. This paper analyzes the guiding significance of multiple intelligence theory, Montessori education method, gamification and project learning to preschool education courses. It is pointed out that there are some problems of single curriculum setting, limited teaching methods and means, and the challenges of teacher staff construction and resource allocation and concept change. This paper proposes the curriculum innovation of gamification and project-style integration, demonstrates its feasibility, expounds the design principles and implementation steps of the integrated curriculum, and makes a prospect for the future.

Construction of Virtual Experiment Teaching Platform based on 5E Teaching Mode and VI Technology

Virtual instruments have many advantages such as low cost, comprehensive functionality, easy scalability, and easy replication. At the same time, they can also meet the special requirements of time and space for remote experiments. Based on Web technology and virtual instrument technology, a virtual experiment system is constructed, which combines data sharing, remote control, and real-time operation. More conducive to utilizing experimental and scientific research resources. At the same time, virtual instruments have high flexibility and are no longer limited by traditional experimental teaching modes, which can save a lot of repeated investment costs. They can also keep the teaching equipment in the laboratory up-to-date and closely follow the development trend of science and technology. As a compulsory course for mechanical engineering majors, although the existing experimental system has achieved certain results, there are still limitations to 'Mechanical Engineering Testing Technology'. This article aims to address the problems of insufficient instrument sets and outdated equipment in the experimental teaching of "Mechanical Engineering Testing Technology", as well as students' poor ability to apply theory to practice and insufficient innovation ability. By integrating the 5E teaching mode, a virtual experimental teaching platform based on VI (Virtual Instrument) technology is established. Students can break through traditional experimental methods and conduct various experiments through the network, obtaining experimental experiences that are very similar to real experiments. At the same time, it can deepen their understanding and recognition of experiments, and better grasp theoretical knowledge.

Latent profiles of home behaviour problems in Trinidad and Tobago.

Caregivers who interact with children at home can provide a critical, complementary perspective on a child's behaviour functioning. This research used a parent-administered measure of problem behaviours to study perceptions of child behaviours across home situations. We applied latent profile analysis to identify subgroups of children with common behavioural tendencies in a nationally representative sample (N = 709) of 4- to 13-year-old children in Trinidad and Tobago. This study (a) identified latent profiles of children's over- and underactive behaviour problems in varied home settings and (b) examined how profile membership predicted academic skills and teacher-observed problem behaviours. The best-fitting four-profile model included one profile of adjusted behaviours (56%), one of the elevated attention-seeking behaviours (21%), a profile featuring withdrawn and disengaged behaviours (15%) and a relatively rare profile emphasising aggressive behaviours (8%). Children classified in the last profile displayed the poorest academic outcomes and the highest levels of teacher-observed behaviour problems.

Providing a new transdiagnostic emotion-focused pain treatment in a clinical context: therapists' experiences of facilitators and barriers.

Providing new psychological treatments in clinical settings requires implementation strategies adapted to the organizational context. This study explored how licensed psychologists experienced their context when providing a new transdiagnostic psychological treatment, "the hybrid treatment", to treat comorbid pain and emotional problems in a clinical setting. We aimed to identify which contextual factors the therapists experienced as facilitating or hindering, to gain a better understanding of important considerations when planning a future implementation strategy. Contextual factors were identified using the Consolidated Framework of Implementation Research (CFIR) in data collection and analysis. Data were collected through semi-structured interviews (N = 9). Thematic analysis resulted in the identification of five main influencing factors: Perception of the intervention's adaptability, prioritization of the patient's needs, leadership engagement, structure for collaboration, and therapists' professional engagement. The results highlight the importance of ensuring a clearly stated mandate for the key individuals involved. The findings may guide future implementation of new psychological treatments into regular care, to enhance facilitators and overcome barriers.

Influence of personal and career burnout on female employers' subjective evaluation of workplace acoustic environment.

Burnout is an increasingly common problem in modern work settings that significantly affects people's health and well-being. Several studies have emphasized the impact of career burnout on employees' performance and efficiency. It is unknown whether career burnout mediated by personal burnout may affect employees' perception of their workplace physical environment attributes. This research aims to understand if personal and career burnout can affect employers' acoustic environment evaluation of their workplace. Considering commonly experienced or highly experienced personal and career burnout among working women, the study targeted female university faculty members. The research involved stratified sampling and employed data from 272 individuals across five public and private universities in Tehran. Collected data were analyzed using SmartPLS (latest release 4.1). The results revealed a significant link between personal and career burnout and the subjective evaluation of workplace acoustic environment. Career burnout mediated the relationship between personal burnout and negative evaluation of the workplace acoustic environment. This study provides compelling evidence that experiences of burnout, whether related to personal or career aspects, substantially impact the subjective assessment of the acoustic environment within the workplace. The results underscore the complex interplay between an individual's degree of burnout and their subjective perception of the acoustic dimensions of their work environment. The findings extend our understanding of how psychological factors might shape our interpretation of the physical workplace.

New applications of linear semi-infinite optimization theory in copositive optimization

This paper provides a review and update of the theory of linear semi-infinite optimization, followed by its direct application to derive existence theorems, results on the geometry of the feasible set, duality theorems, and optimality conditions for copositive optimization problems.

A distributed algorithm for secure dominating set problem in IoT networks

A distributed algorithm for secure dominating set problem in IoT networks

An approximation algorithm for the k-prize-collecting hitting set problem

An approximation algorithm for the k-prize-collecting hitting set problem

Land cover and drought risk assessment in Türkiye's mountain regions using neutrosophic decision support system.

Earth observation (EO) provides dynamic scientific methods for tracking and defining ecological parameters in mountainous regions. Open-source platforms are frequently utilized in this context to efficiently collect and evaluate spatial data. In this study, we used Collect Earth (CE), an open-source land monitoring platform, to reveal and assess land cover, land cover change, and relevant ecological parameters such as drought risk. Mountain ecosystems were subject to an evaluation for the first time by combining remote sensing with a hybridization of Decision-Making Trial and Evaluation Laboratory (DEMATEL), analytic hierarchy process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for neutrosophic sets in risk assessment problems of several connected criteria. The high and dispersed high alpine environment of Türkiye accommodates land with relatively less human influence, making it suitable to observe climate change impacts. In the framework of the study, we evaluated more than two decades (2000-2022) of land use and land cover (LULC) changes in the mountain regions of the country. Using nine identified ecological parameters, we also evaluated drought risk. The parameters included were the LULC classes and their change, elevation, slope, aspect, precipitation, temperature, normalized difference vegetation index (NDVI), water deficit, and evapotranspiration (ET). The risk map we produced revealed a high to very high drought risk for almost throughout the Türkiye's mountainous areas. We concluded that integrating geospatial techniques with hybridization is promising for mapping drought risk, helping policymakers prepare effective drought mitigation measures to reasonably adapt to climate change impacts.

MDSA: A Dynamic and Greedy Approach to Solve the Minimum Dominating Set Problem

The graph theory is one of the fundamental structures in computer science used to model various scientific and engineering problems. Many problems within the graph theory are categorized as NP-hard and NP-complete. One such problem is the minimum dominating set (MDS) problem, which seeks to identify the minimum possible subsets in a graph such that every other node in the subset is directly connected to a node in this subset. Due to its inherent complexity, developing an efficient polynomial-time method to address the MDS problem remains a significant challenge in graph theory. This paper introduces a novel algorithm that utilizes a centrality measure known as the Malatya Centrality to effectively address the MDS problem. The proposed algorithm, called the Malatya Dominating Set Algorithm (MDSA), leverages centrality values to identify dominating sets within a graph. It extends the Malatya centrality by incorporating a second-level centrality measure, which enhances the identification of dominating nodes. Through a systematic and algorithmic approach, these centrality values are employed to pinpoint the elements of the dominating set. The MDSA uniquely integrates greedy and dynamic programming strategies. At each step, the algorithm selects the most optimal (or near-optimal) node based on the centrality values (greedy approach) while updating the neighboring nodes’ criteria to influence subsequent decisions (dynamic programming). The proposed algorithm demonstrates efficient performance, particularly in large-scale graphs, with time and space requirements scaling proportionally with the size of the graph and its average degree. Experimental results indicate that our algorithm outperforms existing methods, especially in terms of time complexity when applied to large datasets, showcasing its effectiveness in addressing the MDS problem.