GLOBAL SOLUTIONS FOR ABSTRACT FUNCTIONAL DIFFERENTIAL EQUATIONS WITH NONLOCAL CONDITIONS

In this paper we study the existence of global solutions for a class of abstract functional differential equation with nonlocal conditions. An application is considered

Existence Results for Abstract Partial Neutral Integro-differential Equation with Unbounded Delay

In this paper we study the existence and regularity of mild solutions for a class of abstract partial neutral integro-differential equations with unbounded delay.FONDECYT-CONICYT[1050314]FONDECYT-CONICYT[7050034]Capes, Brasi

Design and development of Knowledge Based System for Integrated Maintenance Strategy and Operations

YesThe importance of maintenance has escalated significantly by the increase in automation in manufacturing processes. This condition changed the perspective of maintenance from being considered as an inevitable cost to being seen as a key business function to drive competitiveness. Consequently, maintenance decisions need to be aligned with the business competitive strategy as well as the requirements of manufacturing/quality functions in order to support manufacturing equipment performance. Therefore, it is required to synchronise the maintenance strategy and operations with business and manufacturing/quality aspects. This article presents the design and development of a Knowledge Based System for Integrated Maintenance Strategy and Operations. The developed framework of the Knowledge Based System for Integrated Maintenance Strategy and Operations is elaborated to show how the Knowledge Based System for Integrated Maintenance Strategy and Operations can be applied to support maintenance decisions. The knowledge-based system integrates the Gauging Absences of Prerequisites methodology in order to deal with different decision-making priorities and to facilitate benchmarking with a target performance state. This is a new contribution to this area. The Knowledge Based System for Integrated Maintenance Strategy and Operations is useful in reviewing the existing maintenance system and provides reasonable recommendations for maintenance decisions with respect to business and manufacturing perspectives. In addition, it indicates the roadmap from the current state to the benchmark goals for the maintenance system.Ministry of Research, Technology and Higher Education of the Republic of Indonesia and the University of Bradford, UK

Learning on a Budget Using Distributional RL

Agents acting in real-world scenarios often have constraints such as finite budgets or daily job performance targets. While repeated (episodic) tasks can be solved with existing RL algorithms, methods need to be extended if the repetition depends on performance. Recent work has introduced a distributional perspective on reinforcement learning, providing a model of episodic returns. Inspired by these results we contribute the new budget- and risk-aware distributional reinforcement learning (BRAD-RL) algorithm that bootstraps from the C51 distributional output and then uses value iteration to estimate the value of starting an episode with a certain amount of budget. With this strategy we can make budget-wise action selection within each episode and maximize the return across episodes. Experiments in a grid-world domain highlight the benefits of our algorithm, maximizing discounted future returns when low cumulative performance may terminate repetition

Closing the dark photon window to thermal dark matter

The nature of dark matter remains a central question in particle physics, cosmology, and astrophysics. The prevailing hypothesis postulates that dark matter consists of particles that interact only weakly with Standard Model particles. However, the knowledge of dark matter properties beyond these interactions is limited. This study explores a scenario involving a dark photon as a mediator between dark matter and the Standard Model, akin to the photon's role in electromagnetism. Recent cosmological and experimental evidence impose constraints on this scenario, focusing on results from direct detection experiments such as PICO-60, XENON-1T, and PANDAX-4T. The results reveal severe constraints, effectively closing the window for laboratory searches for dark photons as mediators between the Standard Model and the dark sector (dark electrons) in the secluded dark matter scenario. The findings underscore the need for alternative explanations and offer fresh perspectives on the ongoing quest to understand dark matter and its interactions since they are nearly independent of the dark electron fraction content for the total dark matter. This analysis significantly narrows down the parameter space for thermal dark matter scenarios involving a dark photon portal, reinforcing the urgency of exploring alternative models and designing new experiments to unravel the mysteries surrounding the nature of dark matter.Comment: 11 pages, 5 figure

The unusually large Plasmodium telomerase reverse-transcriptase localizes in a discrete compartment associated with the nucleolus

Telomerase replicates chromosome ends, a function necessary for maintaining genome integrity. We have identified the gene that encodes the catalytic reverse transcriptase (RT) component of this enzyme in the malaria parasite Plasmodium falciparum (PfTERT) as well as the orthologous genes from two rodent and one simian malaria species. PfTERT is predicted to encode a basic protein that contains the major sequence motifs previously identified in known telomerase RTs (TERTs). At ∼2500 amino acids, PfTERT is three times larger than other characterized TERTs. We observed remarkable sequence diversity between TERT proteins of different Plasmodial species, with conserved domains alternating with hypervariable regions. Immunofluorescence analysis revealed that PfTERT is expressed in asexual blood stage parasites that have begun DNA synthesis. Surprisingly, rather than at telomere clusters, PfTERT typically localizes into a discrete nuclear compartment. We further demonstrate that this compartment is associated with the nucleolus, hereby defined for the first time in P.falciparum

Using EWGM Method to Optimise the FMEA as a Risk Assessment Methodology

YesFailure Modes and Effect Analysis (FMEA) is a proactive, highly structured, and systematic approach for failure analysis. It has been also applied as a risk assessment tool, by ranking potential risks based on the estimation of Risk Priority Numbers (RPNs). This paper develops an improved FMEA methodology for strategic risk analysis. The proposed approach combines the Analytic Hierarchy Process (AHP) technique with the Exponential and Weighted Geometric Mean method (EWGM) to support risk analysis. AHP is applied to estimate the weights of three risk factors: Severity (S), Occurrence (O) and Detection (D), which integrate the RPN for each risk. The EWGM method is applied for ranking RPNs. Combining AHP with EWGM allows avoiding repetition of FMEA results. The results of the developed methodology reveal that duplication of RPNs has been decreased, and facilitating an effective risk ranking by offering a unique value for each risk. The proposed methodology focuses not only on high severity values for risk ranking but also it considers other risk factors (O and D), resulting in an enhanced risk assessment process. Furthermore, the weights of the three risk factors are considered. In this way, the developed methodology offers unique value for each risk in a simple way which makes the risk assessment results more accurate. This methodology provides a practical and systematic approach to support decision-makers in assessing and ranking risks that could affect long-term strategy implementation. The methodology was validated through the case study of a power plant in the Middle East, assessing 84 risks within 9 risk categories. The case study revealed that top management should pay more attention to key risks associated with electricity price, gas emissions, lost-time injuries, bad odor, and production.This research has been supported by Hashemite University, Jordan