Set Of Problems Research Articles

Learning Activities in Mathematics Education: Application of Problem-Based Learning in Power Dominating Set for Electricity Network Optimization Problems

Learning activities in mathematics education play an important role in developing students' analytical and problem-solving skills, especially in applying mathematical concepts to real-world problems. This research aims to apply the Problem-Based Learning (PBL) method to the topic of Power Dominating Set to optimize the electricity network. Power Dominating Set is a concept in graph theory that can be used to minimize the number of control points in the electricity network, thus optimizing the use of resources and increasing the efficiency of the network. By using PBL, students are expected to understand the concept of Power Dominating Set both abstractly and in a practical context relevant to the real world. This research was conducted using an experimental method with two groups of students, namely the experimental group using the PBL method and the control group using the conventional learning method. The results showed that the group that learned with PBL had a deeper understanding and better analytical skills in applying Power Dominating Set to electricity network optimization problems. Discussion of the results showed that the PBL approach is not only effective in improving the understanding of abstract mathematical concepts, but also capable of enhancing students' skills in identifying and solving real-world electricity network problems. Thus, the application of PBL in mathematics education can be an effective alternative to connect abstract mathematical concepts with practical applications, especially in electricity network optimization.

Levocabastine ameliorates cyclophosphamide-induced hepatotoxicity in Swiss albino mice: modulation of Nrf2, NF-κB p65, cleaved caspase-3 and TGF-β signaling molecules.

Cyclophosphamide (CP)-induced hepatotoxicity is a significant problem in clinical settings. This study aimed to evaluate the protective effect of levocabastine (LEV) on CP-induced hepatotoxicity in Swiss albino mice. Mice were given CP (toxic drug) 200mg/kg, i.p., once on the 7th day, and LEV 50 and 100µg/kg, i.p., and fenofibrate (FF) 80mg/kg, p.o., daily for 14 days. On the 15th day, blood and liver samples were collected to assess biological parameters. CP 200mg/kg caused hepatotoxicity due to oxidative stress, inflammation, apoptosis, and fibrosis as manifested by a reduction in catalase, reduced glutathione (GSH), superoxide dismutase (SOD), and an increase in thiobarbituric acid reactive substance (TBARS), nitrite, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), transforming growth factor-beta 1 (TGF-β1), interleukin-1β (IL-1β), alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transferase (GGT) levels. Cleaved caspase-3 and nuclear factor kappa-B (NF-κB) expression was also increased and nuclear factor erythroid 2-related factor (Nrf2) expression was decreased as confirmed by Immunohistochemical analysis. It also caused histopathological abnormalities and fibrosis as manifested by Hematoxylin-Eosin (H&E) and Masson's trichrome (MT) staining. These alterations were returned to almost normal when treated with LEV 100µg/kg and FF 80mg/kg. Thus, LEV protected CP-induced hepatotoxicity by reversing inflammation, apoptosis, fibrosis, oxidative stress, hepatic injury, and histopathological damages. LEV can be helpful as an adjuvant in cancer patients who are on CP treatment, to minimize toxicity. However, its role in in-vivo cancer model is further needed to be confirmed.

Epidemiology and risk factors for Rotator cuff tears in Indian population

Introduction: Rotator cuff disorders are a prevalent shoulder problem in clinical settings. The incidence of rotator cuff tears in cadaveric studies ranges from 5% to 40%, with multifactorial etiology. Limited data exists on the epidemiology of rotator cuff tears in the Indian population. This study aims to evaluate risk factors and demographic features associated with symptomatic rotator cuff tears.Materials and Methods: This prospective observational study was conducted at a tertiary care center in Bangalore, India, involving 105 patients with MRI-confirmed full-thickness rotator cuff tears. A one-time evaluation assessed risk factors, demographic characteristics, and physical examination findings, including range of motion, strength, and impingement. Data were analyzed with descriptive statistics and the Chi-square test to explore associations between age, gender, comorbidities, and rotator cuff tears.Results: The age distribution showed 5.48% in 31-40 years, 23.81% in 41-50 years, 40.95% in 51-60 years, 22.86% in 61-70 years, and 6.90% in >70 years. The male-to-female ratio was 1.56:1, with a significant gender difference (p = 0.03). Right shoulder involvement was more common (68.10%), with the dominant shoulder affected in 65 patients. Hypertension (29.5%) and type 2 diabetes (24.8%) were the most common comorbidities.Conclusion: Increasing age is the primary risk factor for rotator cuff tears, with risk rising proportionately with age. Hypertension and diabetes mellitus are common comorbidities associated with rotator cuff disease in the Indian population.

Local regularity for nonlocal double phase equations in the Heisenberg group

We prove interior boundedness and Hölder continuity for the weak solutions of nonlocal double phase equations in the Heisenberg group $\mathbb{H}^n$ . This solves a problem raised by Palatucci and Piccinini et al. in 2022 and 2023 for the nonlinear integro-differential problems in Heisenberg setting. Our proof of the a priori estimates bases on De Giorgi–Nash–Moser theory, where the important ingredients are Caccioppoli-type inequality and Logarithmic estimate. To achieve this goal, we establish a new and crucial Sobolev–Poincaré type inequality in local domain, which may be of independent interest and potential applications.

On simpliciality of function spaces not containing constants

We investigate simpliciality of function spaces without constants. We prove, in particular, that several properties characterizing simpliciality in the classical case differ in this new setting. We also show that it may happen that a given point is not represented by any measure pseudosupported by the Choquet boundary, illustrating so limits of possible generalizations of the representation theorem. Moreover, we address the abstract Dirichlet problem in the new setting and establish some common points and nontrivial differences with the classical case.

Generating representative sets for multiobjective discrete optimization problems with specified coverage errors

Generating representative sets for multiobjective discrete optimization problems with specified coverage errors

Computing the EHZ capacity is 𝑁𝑃-hard

The Ekeland–Hofer–Zehnder capacity (EHZ capacity) is a fundamental symplectic invariant of convex bodies. We show that computing the EHZ capacity of polytopes is N P NP -hard. For this we reduce the feedback arc set problem in bipartite tournaments to computing the EHZ capacity of simplices.

Follow-up by telephone questionnaire in outpatient oral and maxillofacial surgery.

The SARS-CoV2 pandemic introduced a new problem in postoperative outpatient care: If I set a follow-up appointment at the clinic, will I endanger my patient? This study presents a different way to identify problems in the postoperative setting after outpatient procedures in our field- the telephone interview. A study nurse conducted the telephone interview using a structured questionnaire within one week of minor outpatient oral and maxillofacial surgery. She asked about pain, swelling, numbness, and mouth opening limitations. Certain red flag answers (numbness, increasing pain, increasing swelling, pain keeping patient from sleeping, pain on swallowing) caused her to book an appointment for the patient in our clinic within the following 24hours. 52 Patients completed the telephone questionnaire. Of those 3 (5.7%) had red flag answers that resulted in an appointment at the hospital within 24hours. 2 (3.8%) of them were due to numbness. 24 (46.2%) patients reported no pain. On the numerical rating scale from 0 (no pain) to 10 (worst pain), the average reported pain was 2.24 (SE 0.30). Swelling was reported by 39 (75%) patients. 22 (42.3%) reported the swelling to be mild, 10 (19.2%) moderate, and 7 (13.5%) to be severe. 13 (25%) patients reported a limitation to mouth opening. None reported the interincisal distance to be smaller than one finger. A structured telephone questionnaire can be a useful tool to discern postoperative complications and initiate necessary treatment. At the same time, it minimizes overtreatment. It can be used as a standard tool in the ambulatory treatment. It can be delegated to a secretary or ambulatory nurse with a standardized questionnaire to optimize resource use for selected patients. Moreover, patients describe it as a service to be called at home and they avoid unnecessary travel.

A Combined Capacity Planning and Simulation Approach for the Optimization of AGV Systems in Complex Production Logistics Environments

Background: The capacity planning of production systems is one of the most fundamental strategic problems in the creation of a production plant. However, the implementation of increasingly complex production systems combined with sophisticated automated material handling justifies the development of novel approaches to solve the combined capacity planning and material handling problem, which is also the objective of the current study. Methods: The presented approach combines the use of capacity planning formulas and discrete event simulation for optimizing extensive automated guided vehicle (AGV) systems from the aspect of the number of required vehicles. Extensive series of simulation experiments are applied in the case of each model variant for optimal results and to account for machine failures in the system. Results: The application of the proposed method is demonstrated through a realistic sample problem in a plastic industry setting with the use of the Siemens Tecnomatix Plant Simulation software (version 2302.0003, Educational license). Conclusions: The results from the sample problem demonstrate the usefulness of the approach, as a non-intuitive solution proved to be the most efficient. Additionally, the main advantage of the method is that it provides a standardized framework for the simulation-based optimization of AGV systems starting out from the comprehensive production capacity parameters.

How to arrange the robotic environment? Leveraging experience in both motion planning and environment optimization.

This study presents an experience-based hierarchical-structure optimization algorithm to address the robotic system environment design problem, which combines motion planning and environment arrangement problems together. The motion planning problem, which could be defined as a multiple-degree-of-freedom (m-DOF) problem, together with the environment arrangement problem, which could be defined as a free DOF problem, is a high-dimensional optimization problem. Therefore, the hierarchical structure was established, with the higher layer solving the environment arrangement problem and lower layer solving the problem of motion planning. Previously planned trajectories and past results for this design problem were first constructed as datasets; however, they cannot be seen as optimal. Therefore, this study proposed an experience-reuse manner, which selected the most "useful" experience from the datasets and reused it to query new problems, optimize the results in the datasets, and provide better environment arrangement with shorter path lengths within the same time. Therefore, a hierarchical structural caseGA-ERTC algorithm was proposed. In the higher layer, a novel approach employing the case-injected genetic algorithm (GA) was implemented to tackle optimization challenges in robot environment design, leveraging experiential insights. Performance indices in the arrangement of the robot system's environment were determined by the robotic arm's motion and path length calculated using an experience-driven random tree (ERT) algorithm. Moreover, the effectiveness of the proposed method is illustrated with the 12.59% decrease in path lengths by solving different settings of hard problems and 5.05% decrease in easy problems compared with other state-of-the-art methods in three small robots.

Comparing options for screening of reading difficulties in middle school: Do teacher ratings improve accuracy?

Reading problems may emerge beyond the primary grades when the linguistic and cognitive demands of reading comprehension increase in middle school. The accurate identification of students requiring supplemental reading instruction is critical to provide remediation and decrease the prevalence and likelihood of reading problems in secondary settings and beyond. Nevertheless, research guidance on middle school reading screening is scarce. This study analyzed data from 193 sixth-grade students across 12 classrooms to examine (a) how well various reading screeners predicted proficiency on the year-end state assessment, (b) what combinations of reading screeners were most accurate, (c) the extent to which a brief teacher rating improved classification accuracy, and (d) the agreement rates between the most accurate combinations of screeners. Screeners included the Sight Word Efficiency, oral reading fluency (ORF), maze, and a multiple-choice reading comprehension (MCRC) assessment. Results from logistic regressions and receiver operating characteristic curve analyses suggested that no single screener was appropriate for use and that combinations of two or three screeners assessing different reading skills improved classification accuracy (i.e., ORF + MCRC, ORF + maze + MCRC). Moreover, teacher ratings further improved classification accuracy but its predictive value depended on the combination of screeners. Finally, there was a high agreement regarding which students were identified as needing intervention between these combinations of screeners. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Horizon problem and capital expenditures: evidence from the public sector in Indonesia

PurposeThis study investigates whether horizon problems affect the allocation of capital budgets and their implementation in a government setting.Design/methodology/approachWe use data from 2005 to 2020 for local governments in Indonesia, which apply a limit of two five-year terms for mayors. We use regression analyses for panel data with total observations of 4,541 local government years from 448 unique local governments. We also use graphical analyses and t-tests to provide robustness to our results.FindingsMayors allocated lower capital expenditures in the second term than in the first. Capital budget allocation is lower for local governments whose mayors are older than 60. Our additional analysis shows that incumbents seeking re-election allocate more capital expenditure than those not seeking re-election.Research limitations/implicationsThis study contributes to the literature on the behavioral effect of term limits on local government's allocation and implementation of capital budgets. Limiting elected government officials to a certain number of terms will prevent the monopoly of power. However, it may negatively affect budget allocation on capital programs in their last term. Our findings should interest public policymakers in discerning the costs and benefits of term limits for elected offices.Originality/valueMost studies on horizon problems have focused on the corporate setting. This study provides evidence of the effects of horizon problems in the government setting, especially in Asia.

Mathematical Techniques in the Design of Robust Control Systems

Solid control frameworks are exceptionally imperative for making beyond any doubt that energetic frameworks remain steady and work well in a parcel of diverse circumstances and with a parcel of questions. This diagram tells you everything you wish to know about the numerical strategies utilized to form steady control systems. Strong control tries to bargain with issues like unknowns within the system model, stuns from the exterior, and changes within the system's parameters. It does this to form beyond any doubt that the framework keeps working well and remaining steady in spite of these issues. Lyapunov soundness hypothesis and the H-infinity (H∞) optimization strategy are two of the foremost critical arithmetic apparatuses. Lyapunov steadiness hypothesis gives us a way to see at how steady a framework is, and H∞ minimizes the worst-case pick up from unsettling influence to yield. State-space representations are moreover utilized to show and ponder multi-input multi-output (MIMO) frameworks, which makes control plan more organized. When making controls that guarantee steady execution, strategies like Direct Framework Disparities (LMIs) and Riccati conditions are utilized. The thought of unwavering quality limits is additionally displayed to degree how well the framework can handle factors. The solid control plan incorporates frequency-domain apparatuses, such as the Nyquist and Bode plots, to see at how the framework acts at distinctive frequencies. This makes it simpler to form controllers that can bargain with high-frequency occasions. We conversation around progressed strategies like α-synthesis and strong shaft situation that can offer assistance with certain control problems in dubious settings. Down to earth illustrations appear how these scientific strategies can be used, showing how vital they are in numerous building areas, such as the airplane, vehicle, and prepare control industries. The unique emphasizes how imperative these numerical strategies are for making beyond any doubt that solid control frameworks can handle the challenges of the genuine world, which improves system security, execution, and steadfastness in a wide run of circumstances. The abstract's objective with this outline is to provide you a basic idea of the math that's critical to the field of solid control framework plan.

Co-existence of antibiotic resistance and virulence factors in carbapenem resistant Klebsiella pneumoniae clinical isolates from Alexandria, Egypt

BackgroundThe emergence and spread of carbapenem resistance among Enterobacteriaceae, particularly Klebsiella pneumoniae, constitute a serious threat to public health, since carbapenems are the last line of defense in the treatment of life-threatening infections caused by drug-resistant Enterobacteriaceae. The current study investigated the co-existence of different virulence factors and carbapenemases in carbapenem-resistant Klebsiella pneumoniae clinical isolates from Alexandria, Egypt.ResultsPhenotypic characterization of virulence factors indicated that 41.5% of the isolates were strong biofilm producers, while hypermucoviscosity was detected in 14.9% of the isolates. All isolates harbored five or more virulence factor encoding genes. entB, ycfM, mrkD and fimH were detected in all isolates, while only one isolate was negative for ybtS. uge, iutA, rmpA and kpn were detected in 61 (64.8%), 55 (58.5%), 41 (43.6%) and 27 (28.7%) isolates, respectively, while all isolates lacked magA and k2A. Phenotypic detection of carbapenemases was explored by performing CarbaNP and mCIM/eCIM. CarbaNP test showed positive results in 98.9% of the isolates and positive mCIM tests were observed in all isolates, while 68 (72.3%) isolates showed positive eCIM tests. blaNDM was the most prevalent carbapenemase encoding gene (92.5%) followed by the blaOXA−48 (51.1%), while blaKPC was detected in only one (1.06%) isolate. blaVIM, blaIMP and blaGES were not detected in any of the tested isolates.ConclusionsThe widespread of carbapenem-resistant Klebsiella pneumoniae represents a major problem in health care settings. A significant association between certain virulence factors and carbapenemase-encoding genes was observed. Antibiotic stewardship programs and infection control policies should be effectively implemented especially in hospitals to limit the spread of such highly virulent pathogens.

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

An overhaul cycle performance degradation modeling method for marine gas turbines

A degradation modeling method of marine gas turbines for the overhaul cycle is proposed to address the problem of insufficient data sets for fault diagnosis and trend prediction algorithm validation. First, a nonlinear model of the marine three-shaft gas turbine gas path was established. The degradation path and component degradation models were subsequently obtained. The distribution of the washing cycle and degradation factors in the overhaul cycle were solved using an optimization algorithm, and degradation data in the washing cycle were obtained. The model's feasibility is validated with a segment of actual degradation data. The change rule of the gas turbine operating data during the overhaul cycle was also obtained. The degradation data of marine gas turbines under different boundary conditions are simulated using the established degradation model. This model provides data sets essential for validating fault diagnosis and trend prediction algorithms. Furthermore, it provides a reference for modeling the degradation of other mechanical equipment.