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A significant number of injuries and fatalities occur annually due to fire in buildings. The proactive use of fire safety measures at the design stage can potentially lead to a considerable improvement in reducing casualties by assisting occupants in a safe evacuation. In this study, a framework is developed to obtain a set of appropriate fire safety measures while considering their effects on safe evacuation (i.e., increasing the percentage of survived occupants) and budget limits. The framework consists of four phases, namely (1) initial preparation, (2) optimisation with a meta-heuristic algorithm, (3) decision making when the designer should select appropriate measures considering the budget limit, and (4) applying the selected measures into BIM. A binary version of Billiards-inspired Optimisation Algorithm (BOA) is developed and utilised in the optimisation phase. A case study approach is adopted for this research and the performance of the proposed framework is evaluated by implementing it in two case projects: a residential building and a hospital building. The results indicate that the framework is a beneficial approach for designers to modify building designs in terms of safe evacuation at the design stage by using fire safety measures effectively and economically. It is expected that the output of this framework will help decrease fatalities of building users during a fire.

Calcium hydroxide Ca(OH) 2 has been used as an intracanal medicament to targets microbial biofilms and avert secondary infection in the root canal system. This study evaluated the effects of this material on the morphology and physicochemical properties of an established in-vitro biofilm of Enterococcus faecalis . A biofilm of E. faecalis was grown in multichannel plates. The chemicals including Ca 2+ , OH − , and saturated Ca(OH) 2 (ie 21.6 mM) were prepared in order to evaluate which component eradicated or amplified biofilm structure. Various biochemical and microscopic methods were used to investigate the properties of the biofilm. Biofilms treated with Ca(OH) 2 absorbed more Ca 2+ because of the alkaline pH of the environment and the ions affected the physicochemical properties of the E. faecalis biofilm. A denser biofilm with more cavities and a granular surface was observed in the presence of Ca 2+ ions. This resulted in a decrease in the surface-to-biofilm ratio with increases in its biomass, thickness, colony size, and volume. Calcium hydroxide did not destroy E. faecalis biofilms but rather contributed to the biofilm structure. This in-vitro study sheds light on a missing link in the formation of E. faecalis biofilm in which the Ca 2+ in Ca(OH) 2

Participation of distributed energy resources in the load restoration procedure, known as intentional islanding, can significantly improve the distribution system reliability. Distribution system reconfiguration can effectively alter islanding procedure and thus provide an opportunity to supply more demanded energy and reduce distribution system losses. In addition, high-impact events such as hurricanes and earthquake may complicate the procedure of load restoration, due to disconnection of the distribution system from the upstream grid or concurrent component outages. This paper presents a two-level method for intentional islanding of a reconfigurable distribution system, considering high impact events. In the first level, optimal islands are selected according to the graph model of the distribution system. In the second level, an optimal power flow (OPF) problem is solved to meet the operation constraints of the islands by reactive power control and demand side management. The proposed problem in the first level is solved by a combination of depth first search and particle swarm optimization methods. The OPF problem in the second level is solved in DIgSILENT software. The proposed method is implemented in the IEEE 69-bus test system, and the results show the validity and effectiveness of the proposed algorithm.

Examining the structure of dependence between financial assets and the effects of their Co-movement is one of the important issues in financial markets. The corresponding copula is one of the most computationally convenient ways to describe the dependency structure. This paper examines regime change probability and the best copula model between Bitcoin and six other assets from 2018 to 2021. First, using the ARMA-GARCH model, the marginal distribution functions for all assets and residuals are calculated. Then, by using the obtained residuals, 11 models of copula and six models of combined Copula with Markov switching were implemented. The model that has the best function for constructing combined distribution functions is selected. Finally, the regime probabilities each time are calculated from the best-fitted model. The results show that in the study period, for Bitcoin-Ethereum, Bitcoin-Cardano, and Bitcoin-Gold pairs MS-CT, for Bitcoin-Binance coin and Bitcoin-Ripple pairs MS-CRG and MS-CN for Bitcoin-Oil pair have the best performance. Furthermore, the probabilities of regime change between each asset at each time were calculated and described.

Objectives File fracture represents a common and occasionally unavoidable occurrence during root canal procedures, carrying substantial negative implications for dental practitioners. This study explores dentists’ encounters with file fracture incidents during root canal treatment. Methods In this qualitative study using a phenomenological approach, 13 dentists were included through purposive sampling. The sampling continued until data saturation and semi-structured in-depth interviews were used to collect data. The 7-step Colaizzi approach was employed to analyze the collected data, and Lincoln and Guba’s criteria were used to ensure data credibility. Results The participant cohort comprised eight male and five female dentists, boasting an average of 10.15 ± 5.35 years of professional experience and an average age of 36.53 ± 6.35 years. Data segmentation revealed four themes alongside 18 sub-themes. These themes encompassed the fear of consequences, professional impasse, Integration decline, and the dilemma between moral and immoral decision-making. Conclusion The experiences of dentists during file fracture showed Fear of Consequences, Professional Impasse, Integration Decline, and the Dilemma between Moral and Immoral Decision-Making. File fracture episodes are distressing and taxing for dentists, harboring significant personal and professional repercussions. Such incidents precipitate emotional strain, compromise treatment efficacy, tarnish professional standing and identity, result in financial setbacks, and contribute to professional burnout. Consequently, policymakers must implement several measures, including strengthening legal and insurance protections, establishing secure reporting systems, developing a comprehensive, standardized, and practical document by the endodontic association, and mandating informed consent forms. Clinical Significance The experience of file fracture during root canal treatment manifests in various ways for dentists, often resulting in adverse effects. It is crucial to implement practical strategies to prevent these adverse outcomes.

This study proposes a new method which aims to optimally install tie-lines and distributed generations simultaneously. This is done to optimize the post-outage reconfiguration and minimize energy losses and energy not supplied of distribution systems. The number and location of tie-lines, as well as the number, size, and location of DGs, are pinpointed through teaching the learning-based optimization (TLBO) method. The objective function in the current research is to minimize the costs pertaining to the investment, operation, energy losses, and energies not supplied. In addition to the normal operational condition, fault operational condition is also evaluated. Therefore, the optimal post-fault reconfigurations for fault occurrences in all lines are established. Moreover, the operational constraints such as the voltage and line current limits are taken into account in both normal and post-fault operational modes. Finally, the modified IEEE 33-bus and 69-bus distribution test systems are selected and tested to demonstrate the effectiveness of the simultaneous placement of DGs and tie-line technique proposed in this paper.

In the banking sector, managing liquidity risk is paramount to ensure financial stability and resilience. This study is motivated by a quest to determine the appropriate research methodology that satisfies both theoretical and practical aspects of designing and developing a system that integrates qualitative factors, specifically news sentiment, into liquidity risk forecasting for risk managers to rely on and use the predicted results. Previous works reveal a significant theoretical gap in liquidity risk prediction, highlighting the necessity for a methodology that bridges theoretical advancements and practical applications. The primary questions focus on evaluating how well Design Science Research (DSR) handles short-term liquidity risk prediction and the influence of qualitative factors on these predictions. The DSR approach in this study involved iterative phases of problem identification, artifact creation, and rigorous evaluation. A predictive model was developed, intertwining news sentiment analysis with quantitative liquidity ratios derived from Basel III principles. The results demonstrate that the model achieves an 86% accuracy rate in theoretical evaluations and an impressive 95.5% in real-world scenarios, outperforming traditional methods. This integration of qualitative factors into the predictive model enhances accuracy, providing a more comprehensive understanding of liquidity risk dynamics. By meeting its objectives, this study answers the posed questions that DSR can be used as a research methodology that validates not only the theoretical aspect of the problem but also the practical application of the framework. The study contributes to advancing risk management practices and suggests future work directions, reinforcing the importance of DSR methodology and similar methods considering qualitative dimensions in banking liquidity risk assessment. This advancement paves the way for more proactive and informed decision-making processes in banking institutions.

In recent decades, the variety of building materials has grown a great deal causing the selection of suitable materials from a wide range of candidates to be complex and difficult. One of the main criteria to be considered in this area, besides reducing procurement cost, is paying attention to various aspects affecting the dimensions of sustainable development, such as increasing energy saving, applying recyclable materials and localization.This paper proposes a framework in the BIM environment - as one of the successful approaches in the AEC industry - which allows the project stakeholders to choose the most desired and optimal combination for their building components with least human interference in the selection process makes systematic choices. In order to achieve the purposes embedded in the framework phases, several methods such as ENSCBO, DEA and VIKOR have been utilized in order to evaluate and depict the selection process, this is implemented as a Revit plugin and eventually applied to a case study.

Aims Investigate the association between oral and dental health (ODH) and metabolic syndrome (MetS) in adults aged 35–70 years. Methods The study utilized data from the enrollment phase of Dehgolan prospective cohort study in the west of Iran. A cross‐sectional assessment was conducted on a total of 3996 participants, involving a comprehensive oral examination and the assessment of their oral hygiene behavior (ODH). MetS was defined according to the updated National Cholesterol Education Program Adult Treatment Panel III. Logistic regression used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for sociodemographic characteristics. Results MetS was more prevalent among those who not daily brushing and flossing. Participants with missing teeth (MT) show higher prevalent of MetS. Being female, lower age, illiteracy, family history of diabetes, low physical activity, and salt at table were independently associated with increase odds of MetS (p < 0.05). Odds of MetS were significantly decreased with use flossing (OR = 0.75; CI = 0.60–0.93), decayed (OR = 0.83; CI = 0.72–0.97), filled (OR = 0.84; CI = 0.71–0.99), and increased with MT (OR = 1.45; CI = 1.16–1.81) as long as adjusted for ODH factors. When other potential confounder such as sociodemographic, personal and nutritional habits were adjusted, daily flossing was the only factor that still statistically decreased (OR = 0.79; CI = 0.62–0.99) the odds of MetS. Conclusion Daily flossing was the only factor that independently associated with MetS. Relationship of other ODH factors with Mets were confounded by sociodemographic characteristics of the participants.

This study addresses the critical challenge of predicting liquidity risk in the banking sector, as emphasized by the Basel Committee on Banking Supervision. Liquidity risk serves as a key metric for evaluating a bank’s short-term resilience to liquidity shocks. Despite limited prior research, particularly in anticipating upcoming positions of bank liquidity risk, especially in Iranian banks with high liquidity risk, this study aimed to develop an AI-based model to predict the liquidity coverage ratio (LCR) under Basel III reforms, focusing on its direction (up, down, stable) rather than on exact values, thus distinguishing itself from previous studies. The research objectively explores the influence of external signals, particularly news sentiment, on liquidity prediction, through novel data augmentation, supported by empirical research, as qualitative factors to build a model predicting LCR positions using AI techniques such as deep and convolutional neural networks. Focused on a semi-private Islamic bank in Iran incorporating 4,288,829 Persian economic news articles from 2004 to 2020, this study compared various AI algorithms. It revealed that real-time news content offers valuable insights into impending changes in LCR, particularly in Islamic banks with elevated liquidity risks, achieving a predictive accuracy of 88.6%. This discovery underscores the importance of complementing traditional qualitative metrics with contemporary news sentiments as a signal, particularly when traditional measures require time-consuming data preparation, offering a promising avenue for risk managers seeking more robust liquidity risk forecasts.