Exact Technique Research Articles

Wijsman Ideal Convergence Sequence in Neutrosophic Metric Spaces

Objectives: An examination of convergence for a sequence of closed sets in Neutrosophic Metric Spaces is the main goal of this research. Particularly, the focus of this study is directed at Wijsman -convergence ( and Wijsman -convergence . Methods: The various properties of Neutrosophic Metric Spaces are investigated in this study. Using exact mathematical techniques, this study comprehends the features of convergent sequences in these domains. Furthermore, this study expresses particular views on Wijsman -Cauchy and Wijsman -Cauchy sequences. Findings: The convergence behaviour of closed sets in Neutrosophic Metric Spaces is a result of this research. it presents findings and remarks about the sequences of Wijsman - convergence, Wijsman - convergence, Wijsman -Cauchy, and Wijsman -Cauchy. These findings improve the current understanding of convergence in relation to NMS. Novelty: What makes this work unique is that it focuses on convergence notions in Neutrosophic Metric Spaces, specifically on Wijsman and Wijsman - convergence enriches the current body of information in this domain. Keywords: Neutrosophic Metric Spaces, Wijsman I ­convergent and Wijsman I ¿ ­ convergent sequences, Wijsman I ¿ ­Cauchy and Wijman I ­Cauchy sequences

Numerically Exact Simulation of Photodoped Mott Insulators.

A description of long-lived photodoped states in Mott insulators is challenging, as it needs to address exponentially separated timescales. We demonstrate how properties of such states can be computed using numerically exact steady state techniques, in particular, the quantum Monte Carlo algorithm, by using a time-local ansatz for the distribution function with separate Fermi functions for the electron and hole quasiparticles. The simulations show that the Mott gap remains robust to large photodoping, and the photodoped state has hole and electron quasiparticles with strongly renormalized properties.

Choosing a Suitable Requirement Prioritization Method: A Survey

Software requirements prioritization plays a crucial role in software development. It can be viewed as the process of ordering requirements by determining which requirements must be done first and which can be done later. Powerful requirements prioritization techniques are of paramount importance to finish the implementation on time and budget. Many factors affect requirement prioritization such as stakeholder expectations, complexity, dependency, scalability, risk and cost. Therefore, finding the proper order of requirements is a challenging process. Hence, different types of requirements prioritization techniques have been developed to support this task. In this survey we propose a novel classification that can classify the prioritization techniques under two major classes: relative and exact prioritization techniques class where each class is divided into two subclasses. We also provide an overview about fifteen different requirements prioritization techniques that are classified under our proposed classification. Moreover, we make a comparison between methods that are related to the same subclass to analyze their strengths and weakness. Based on the comparison results, the properties for each proposed subclass of techniques are identified. Depending on these properties, we present some recommendations to help project managers in the process of selection the most suitable technique to prioritize requirements based on their project characteristics.

Stark Many-Body Localization in Interacting Infinite Dimensional Systems.

We study bulk particle transport in a Fermi-Hubbard model on an infinite-dimensional Bethe lattice, driven by a constant electric field. Previous numerical studies showed that one dimensional analogs of this system exhibit a breakdown of diffusion due to Stark many-body localization at least up to time that scales exponentially with the system size. Here, we consider systems initially in a spin density wave state using a combination of numerically exact and approximate techniques. We show that for sufficiently weak electric fields, the wave's momentum component decays exponentially with time in a way consistent with normal diffusion. By studying different wavelengths, we extract the dynamical exponent and the generalized diffusion coefficient at each field strength. Interestingly, we find a nonmonotonic dependence of the dynamical exponent on the electric field. As the field increases toward a critical value proportional to the Hubbard interaction strength, transport slows down, becoming subdiffusive. At large interaction strengths, however, transport speeds up again with increasing field, exhibiting superdiffusive characteristics when the electric field is comparable to the interaction strength. Eventually, at the large field limit, localization occurs and the current through the system is suppressed.

Multi-Objective BiLevel Optimization by Bayesian Optimization

In a multi-objective optimization problem, a decision maker has more than one objective to optimize. In a bilevel optimization problem, there are the following two decision-makers in a hierarchy: a leader who makes the first decision and a follower who reacts, each aiming to optimize their own objective. Many real-world decision-making processes have various objectives to optimize at the same time while considering how the decision-makers affect each other. When both features are combined, we have a multi-objective bilevel optimization problem, which arises in manufacturing, logistics, environmental economics, defence applications and many other areas. Many exact and approximation-based techniques have been proposed, but because of the intrinsic nonconvexity and conflicting multiple objectives, their computational cost is high. We propose a hybrid algorithm based on batch Bayesian optimization to approximate the upper-level Pareto-optimal solution set. We also extend our approach to handle uncertainty in the leader’s objectives via a hypervolume improvement-based acquisition function. Experiments show that our algorithm is more efficient than other current methods while successfully approximating Pareto-fronts.

Investigating and mitigating blockchain poisoning attacks

With the burgeoning adoption of smart contracts and the intrinsic anonymity that blockchain technology provides, the past few years have witnessed an exponential surge in the deployment of blockchain platforms for managing crypto assets. While Ether stands as a paragon of blockchains equipped with smart contract capabilities, its noteworthy to mention that such blockchains present a blank canvas in the form of a data list, dedicated for unbridled program storage. This vacant space, though pivotal for various operations, can become a potential Achilles heel. Specifically, if this repository gets tainted with malicious data, the repercussions can reverberate across the entire blockchain, disrupting its core functions. The research in focus shines a spotlight on a particularly insidious threat, termed blockchain poisoning attack. Through this stratagem, malevolent actors can, with minimal expense, embed detrimental files within the data space, thereby extensively polluting the blockchain. This isnt just a theoretical hazard; its practical implications are stark and can jeopardize the integrity of countless transactions. In a commendable feat of investigative rigor, the research meticulously decoded the modus operandi behind these blockchain poisoning attacks. By employing a multi-pronged research approach, encompassing in-depth studies and iterative inquiries, it successfully deconstructed the exact techniques that malefactors employ.

Protein Homology Modeling in the Low Sequence Similarity Regime

Predicting the 3-D structure of a protein from its sequence based on a template protein structure is still one of the most exact modeling techniques present today. However, template-based modeling is heavily dependent on the selection of a single template structure and the sequence alignment between target and template. Mainly when the target and template sequence identity is low, the error from the alignment introduces larger errors to the model structure. An iterative method to correct such alignment mistakes is used in this study with a benchmark set from CASP in the extremely low sequence-identity regime. This is a protocol developed and tested before and it evaluates the alignment quality by building rough 3-D models for each alignment. Then by using a genetic algorithm it iteratively creates a new set of alignments. Since the method evaluates models, not sequence alignments, structural features are automatically incorporated into the alignment protocol. In the current study, models from structural alignment have been built by Modeller program to show the maximum possible quality of the model that can be obtained from that template structure with the iterative modeling protocol. Then the results and correctly aligned segments from the iterative modeling protocol are analyzed. Finally, it has been shown that if a good local fragment assessment scoring function is developed, the correctly aligned segments exist in the pool of alignments created by the protocol. Thus, the improvement of modeling in the low sequence identity regime is conceivable.

Re-considering Re-partnering: New Insights about Gender and Sexuality in the Study of Second Union Formation

Abstract Past studies have established the existence of a persistent gender gap in re-partnering, wherein women are less likely to re-partner than men in the general population. Existing theories and explanations focus on women’s and men’s socio-demographic characteristics as mechanisms determining their opportunities, needs, and attractiveness in the re-partnering process. However, this work assumes that people are heterosexual and overlooks sexual minorities despite growing scholarly interest in union formation and dissolution among Lesbian, Gay, and Bisexual (LGB) people. We investigate whether and how the gender gap in re-partnering intersects with sexual identity to highlight the role of gender relations as a social force that shapes union formation outcomes among both the heterosexual and LGB population. We use retrospective data on cohabitation and marriage histories from the British Understanding Society survey (UKHLS) to estimate event history models. We confirm the existence of a gender gap favoring men among heterosexuals but find that lesbian women are more likely to re-partner than gay men. We do not observe a gender gap among bisexuals. Results are robust to accounting for compositional differences between groups using exact matching techniques. These findings suggest that the persistent gender gap found in past studies is not as universal as previously presumed and that sexual identity plays a vital role in re-partnering outcomes. Therefore, sociologists should explicitly incorporate the gender relational context into models and theories that explain gender differences in union formation outcomes.

Paediatric voice disorder: who to refer and how to assess? A summary of recent literature.

The purpose of this review is to update the reader with recent advances and current opinion on the assessment and management of paediatric voice disorders. Access to advanced multidisciplinary paediatric voice clinics has increased over the last decade. Often the assessment is combined between speech therapy/pathology and ENT surgery. Vocal fold nodules remain the most prevalent diagnosis at a paediatric voice clinic, but significant diseases will also present, for example laryngeal papilloma. Recently, more consideration of the psychosocial aspect of voice disorders and evaluation of auditory processing disorders have shown how these can have a negative impact. There also appears to be a lack of parental and teacher awareness of paediatric voice disorders and their significance. We would recommend multiparametric assessment and analysis of all children with a voice disorder. Most paediatric voice conditions will respond to skilled voice therapy. However, the exact techniques and dosage requires further evaluation and research. Paediatric voice conditions are common and should not be dismissed, as they may represent significant disease, for example papilloma, vagal palsy or have a significant psychosocial impact on the child.

Exact and Heuristic Solution Techniques for Mixed-Integer Quantile Minimization Problems

We consider mixed-integer linear quantile minimization problems that yield large-scale problems that are very hard to solve for real-world instances. We motivate the study of this problem class by two important real-world problems: a maintenance planning problem for electricity networks and a quantile-based variant of the classic portfolio optimization problem. For these problems, we develop valid inequalities and present an overlapping alternating direction method. Moreover, we discuss an adaptive scenario clustering method for which we prove that it terminates after a finite number of iterations with a global optimal solution. We study the computational impact of all presented techniques and finally show that their combination leads to an overall method that can solve the maintenance planning problem on large-scale real-world instances provided by the ROADEF/EURO challenge 2020 1 and that they also lead to significant improvements when solving a quantile-version of the classic portfolio optimization problem. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms–Discrete. Funding: This work was supported by the Deutsche Forschungsgemeinschaft [CRC TRR 154], Fonds De La Recherche Scientifique [PDR T0098.18], and Bundesministerium für Bildung und Forschung. Supplemental Material: The online appendix is available at https://doi.org/10.1287/ijoc.2022.0105 .

The Outcome of the Miniaturized Percutaneous Nephrolithotomy in Lateral Position with Guidance of Non-Rotational C-Arm.

Evaluation of the outcome of the miniaturized percutaneous nephrolithotomy in the treatment of nephrolithiasis with a lateral position based on the principle of a right triangle under the guidance of a C-Arm without contrast fluid. Sixty-nine cases of Mini-PCNL with the assistance of a vacuum-assisted sheath in the lateral position were performed at Central Hospital from March 2021 to August 2022. Percutaneous renal access was under the guidance of a non-rotational C-arm without contrast medium, and we determined the puncture location and depth of the needle based on the principle of right triangles. The median age was 51.6 ± 12.5 years, and males accounted for 68.1% of the cases. 60.9% of all patients had normal weight. The median stone surface area was 361.1mm2, and 59.4% of all cases were graded as 2 regarding Guy's stone score. The successful renal access rate was 100%. The tunnel access from the middle and lower calyx accounted for 94.2%. The median access duration, fluoroscopy duration, and hospital length of stay were 271.7 seconds, 14.79 seconds, and 6.3 days, respectively. The complete stone clearance rate was 78.3%. Bleeding complications occurred in 2 patients without mortality. Three patients required an additional procedure. The puncture technique into the renal calyxes based on the principle of the right triangle under the guidance of a non-rotational C-Arm without contrast medium in PCNL is a fast, exact, and safe technique.

Optimal guidance track generation for precision agriculture: A review of coverage path planning techniques

AbstractThe Complete Coverage Path Planning (CCPP) problem is a subfield of industrial motion planning that has applications in various domains, ranging from mobile robotics to treatment applications. Especially in precision agriculture with a high level of automation, the use of CCPP techniques is essential for efficient resource utilization, reduced soil compaction, and increased yields. This paper reviews the CCPP problem in the context of machines operating in agricultural fields and proposes a methodological approach consisting of three steps: Generating the Guidance Tracks (i.e., the track system along which the path should be oriented), determining the traversing sequence through these tracks, and planning a smooth and drivable path. This paper provides an in‐depth review of optimization‐based approaches that deal with the first step, the generation of the guidance track system. Thereby, a comprehensive and pedagogical approach for the generation of guidance tracks for arbitrarily shaped two‐dimensional regions of interest is provided, along with an overview and detailed elaboration on different exact cellular decomposition techniques found in literature. Furthermore, cost functions are outlined for the different approaches presented in this work, which are utilized to generate optimal guidance tracks. Finally, this survey serves as an introductory guide for research and practitioners to solve the CCPP problem effectively and efficiently.

A Sequential Hybrid Optimization Algorithm (SHOA) to Solve the Hybrid Flow Shop Scheduling Problems to Minimize Carbon Footprint

In today’s world, a situational awareness of sustainability is becoming increasingly important. Leaving a better world for future generations is becoming the main interest of many studies. It also puts pressure on managers to change production methods in most industries. Reducing carbon emissions in industry today is crucial to saving our planet. Theoretical research and practical industry requirements diverge, even though numerous researchers have tackled various strategies to handle carbon emission problems. Therefore, this work considers the carbon emission problem of the furniture manufacturing industry in Hosur, Tamilnadu, India. The case study company has a manufacturing system that resembles a hybrid flow shop (HFS) environment. As the HFS scheduling problems are NP-hard in nature, exact solution techniques could not be used to solve the problems. Hence, a sequential hybrid optimization algorithm (SHOA) has been developed in this paper to minimize the carbon footprint. In the SHOA, the pigeon-inspired optimization algorithm (PIOA) is hybridized sequentially with the firefly algorithm (FA). A computational experimental design is proposed to analyze the efficiency of the introduced strategy, and the solutions indicate that the developed approach could reduce the carbon footprint by up to 9.82%. The results motivate us to implement the proposed algorithm in the manufacturing industry to reduce the carbon footprint.

Inference of Probabilistic Programs with Moment-Matching Gaussian Mixtures

Computing the posterior distribution of a probabilistic program is a hard task for which no one-fit-for-all solution exists. We propose Gaussian Semantics, which approximates the exact probabilistic semantics of a bounded program by means of Gaussian mixtures. It is parametrized by a map that associates each program location with the moment order to be matched in the approximation. We provide two main contributions. The first is a universal approximation theorem stating that, under mild conditions, Gaussian Semantics can approximate the exact semantics arbitrarily closely. The second is an approximation that matches up to second-order moments analytically in face of the generally difficult problem of matching moments of Gaussian mixtures with arbitrary moment order. We test our second-order Gaussian approximation (SOGA) on a number of case studies from the literature. We show that it can provide accurate estimates in models not supported by other approximation methods or when exact symbolic techniques fail because of complex expressions or non-simplified integrals. On two notable classes of problems, namely collaborative filtering and programs involving mixtures of continuous and discrete distributions, we show that SOGA significantly outperforms alternative techniques in terms of accuracy and computational time.

The swab site of the upper airways influences the diagnostic sensitivity for the omicron variant of SARS-CoV-2.

The cycle-threshold-value (CT -value) is a quantitative value of the polymerase chain reaction (PCR), which represents the gold standard for the detection of severe acute respiratory syndrome coronavirus 2 (SARS CoV 2). The CT -value can be used to indicate the viral load in swabs of the airways. The collection of a specimen is the only part of the testing process, which is performed manually and carries, therefore, a high potential for increasing measurement variability. The comparison of different PCR results is often difficult since the exact swabbing technique of each test and how do swabs relate in a direct comparison is unknown. For these reasons, the infection course in a patient can be hard infer even after multiple swabs. As the Omicron variant spread from 06/2022 to 08/2022, all common modalities of the upper airway swabs (nasopharyngeal, oropharyngeal, combined naso-oropharyngeal, nasal orifice swabs as well as swabs of the buccal mucosa), which were performed on patients with a suspected infection with SARS CoV 2. RT-PCR was used for SARS CoV 2 RNA detection and the sample comparison was based on the CT -values obtained. Viral loads can vary significantly depending on the swab sites of the upper airways. For the maximum clinical sensitivity, a combined naso-oropharyngeal swab should be considered. In case a single point and single sample measurement is the norm, a nasopharyngeal swab can deliver the highest viral load at the presumed beginning of the infection. Furthermore, the findings of this study can be valuable to correctly interpret results of different PCR with different sampling techniques.

Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

Potreba za filozofijom u savremenom svetu

To think about essential questions, the meaning of human existence, social-historical and ontological riddles of the World, necessarily means being in the chambers of philosophy. Unfortunately, our (post)modern, globalized and busy world is turning its back on the wisdom of all ages. In this paper, the authors point to the rejection of philosophy in the modern consumer society and search for answers to questions about the need to study philosophy today. Also, about its importance for man, people and humanity. The work consists of three parts, in which a contribution is made to the understanding of the importance of philosophy for man, society and humanity. The authors pointed the reasons for the rejection of philosophy in the modern age are explored, and the relationship between philosophy and science is examined. Philosophy is needed by modern man/ society/humanity for the same reasons it was needed in the past, but the need for it is hidden in modern consumer society. Philosophy is eternal and everlasting. If the root of philosophy is about 27 centuries deep and has survived all radical changes in the world and all (r)evolutions, rulers and dynasties, political and social movements, all wars and destructions, all geographical discoveries and the exploring of the Cosmos, is it wise to voluntarily deny such a deep source of wisdom? In contrast to today's consumer lost in his own life, philosophy gives us an insight that can be healing and beneficial. But we should have a fruitful conversation with philosophy, but not just have a historical retrospective. Because we who are still alive need philosophers and their wisdom of the ages. A philosopher looks for the essential and the necessary in everything, and this separates him from those people who deal with unimportant things, phenomena and processes. Of course, a philosophically minded person never underestimates the knowledge and meaning of exact sciences and techniques and technical progress. Communicating with the wisdom of the ages is both healing and valuable and benefits both the individual and the community to which he or she belongs.

Application of Exact Femoral Nerve Block Technique in Patella Fracture Anesthesia and Postoperative Analgesia

Application of Exact Femoral Nerve Block Technique in Patella Fracture Anesthesia and Postoperative Analgesia

Development and Validation of new RP-HPLC Method for the Simultaneous Estimation of Elbasvir and Grazoprevir in Combined Pharmaceutical Dosage Form

A reliable and exact technique was formulated for concurrently determining Elbasvir and Grazoprevir in tablet dosage forms. Chromatogram was developed by running a sample through Zodiac C18 column (4.6 x 150 mm, 5 µm) with the mobile phase containing Orthophosphoric acid (0.1%) and Acetonitrile in the ratio 50:50 v/v. The solution was pumped through the column at a flow rate of 1 ml/min, while maintaining the column temperature at 30°C. The optimized wavelength selected was 260 nm. The retention times for Elbasvir and Grazoprevir were determined to be 2.32 min and 3.30 min, respectively. The percentage recovery was found to be 100.16% for Elbasvir and 99.49% for Grazoprevir. The LOD and LOQ values obtained from the regression equations for Elbasvir were 0.30 mg/ml and 0.92 mg/ml, and for Grazoprevir were 0.28 mg/ml and 0.86 mg/ml, respectively. The regression equation for Elbasvir was found to be y = 2282.5x + 2407.2, and for Grazoprevir, it was y = 2366.5x + 7740.4. In conclusion, the developed method proved to be simple and economical, demonstrating successful application for the simultaneous estimation of both Elbasvir and Grazoprevir in bulk and combined tablet formulations. Keywords: Elbasvir, Grazoprevir, RP­HPLC, Validation, Simultaneous estimation

An exact decomposition technique for the deadline-constrained discrete time/cost trade-off problem with discounted cash flows

This paper addresses the deadline-constrained discrete time/cost trade-off problem with discounted cash flows in project scheduling optimization. Our objective is to optimize the net present value (NPV) of cash flows by selecting execution modes for activities while considering project deadlines. To address this problem, we propose an adapted model that combines the activity-on-node representation of the project network with the milestone activity payment system commonly used in real-world scenarios. This enhanced model accurately depicts project dynamics, enabling improved decision-making in NPV optimization. To solve the problem, we employ the generalized benders decomposition technique, which provides an exact solution approach to handle the computational complexity of the problem. Our approach introduces three types of feasibility cuts. The first type eliminates infeasible solutions by analyzing subproblem infeasibility. The second type enhances the generation of high-quality optimality cuts by iteratively introducing constraints to the master problem, utilizing dominated paths in the project network graph. Lastly, the third type targets the elimination of inferior infeasible solutions. Additionally, we generate a comprehensive dataset encompassing various scenarios and parameter ranges from existing literature. This dataset serves as a valuable resource for further research, with online accessibility and the latest solutions available for approximately 32,400 generated instances. Through our research, we demonstrate the superiority of our proposed solution procedure compared to existing methods in the field. By considering the specific requirements of project scheduling with NPV optimization and project deadlines, our approach contributes to more effective project planning and decision-making in real-world contexts.