On the effective viscosity of fresh concrete: A homogenization approach

Two new homogenization schemes together with the classical generalized self-consistent scheme (GSC) and its extension are proposed to deal with the effective viscosity of fresh concrete. All these models exploit the composite sphere morphology of suspension made of a viscous fluid and spherical particles. They differ from each other by the ways the extra fluid zone (EFZ) located in between the composite sphere are treated. The comparison with experimental data shows that the GSC provides very good result for a well arranged particle size scale that allows mapping the whole medium by composite spheres of different size scales. However, the GSC cannot be used for a suspension with a non negligible volume of the EFZ. For such a case, extensions of the GSC those take into account the contribution of the EFZ to the overall viscous behavior of the system is necessary to fit with experimental data. Two of them work very well for non-cohesive particles and the other can be employed for suspension with cohesive particles such as the case of fresh cement paste

Quantum-based Distributed Algorithms for Edge Node Placement and Workload Allocation

Edge computing is a promising technology that offers a superior user experience and enables various innovative Internet of Things applications. In this paper, we present a mixed-integer linear programming (MILP) model for optimal edge server placement and workload allocation, which is known to be NP-hard. To this end, we explore the possibility of addressing this computationally challenging problem using quantum computing. However, existing quantum solvers are limited to solving unconstrained binary programming problems. To overcome this obstacle, we propose a hybrid quantum-classical solution that decomposes the original problem into a quadratic unconstrained binary optimization (QUBO) problem and a linear program (LP) subproblem. The QUBO problem can be solved by a quantum solver, while the LP subproblem can be solved using traditional LP solvers. Our numerical experiments demonstrate the practicality of leveraging quantum supremacy to solve complex optimization problems in edge computing

A closed-form solution for free vibration of multiple cracked Timoshenko beam and application

A closed-form solution for free vibration is constructed and used for obtaining explicit frequency equation and mode shapes of  Timoshenko beams with arbitrary number of cracks. The cracks are represented by the rotational springs of stiffness calculated from the crack depth.  Using the obtained frequency equation, the sensitivity of natural frequencies to crack of the beams is examined in comparison with the  Euler-Bernoulli beams. Numerical results demonstrate that the Timoshenko beam theory is efficiently applicable not only for short or fat beams but also for the long or slender ones. Nevertheless, both the theories are equivalent in sensitivity analysis of fundamental frequency to cracks and they get to be different for higher frequencies

Advancements, Challenges, and Future Directions in Rainfall-Induced Landslide Prediction: A Comprehensive Review

Rainfall-induced landslides threaten lives and properties globally. To address this, researchers have developed various methods and models that forecast the likelihood and behavior of rainfall-induced landslides. These methodologies and models can be broadly classified into three categories: empirical, physical-based, and machine-learning approaches. However, these methods have limitations in terms of data availability, accuracy, and applicability. This paper reviews the current state-of-the-art of rainfall-induced landslide prediction methods, focusing on the methods, models, and challenges involved. The novelty of this study lies in its comprehensive analysis of existing prediction techniques and the identification of their limitations. By synthesizing a vast body of research, it highlights emerging trends and advancements, providing a holistic perspective on the subject matter. The analysis points out that future research opportunities lie in interdisciplinary collaborations, advanced data integration, remote sensing, climate change impact analysis, numerical modeling, real-time monitoring, and machine learning improvements. In conclusion, the prediction of rainfall-induced landslides is a complex and multifaceted challenge, and no single approach is universally superior. Integrating different methods and leveraging emerging technologies offer the best way forward for improving accuracy and reliability in landslide prediction, ultimately enhancing our ability to manage and mitigate this geohazard

Advancements, Challenges, and Future Directions in Rainfall-Induced Landslide Prediction: A Comprehensive Review

Rainfall-induced landslides threaten lives and properties globally. To address this, researchers have developed various methods and models that forecast the likelihood and behavior of rainfall-induced landslides. These methodologies and models can be broadly classified into three categories: empirical, physical-based, and machine-learning approaches. However, these methods have limitations in terms of data availability, accuracy, and applicability. This paper reviews the current state-of-the-art of rainfall-induced landslide prediction methods, focusing on the methods, models, and challenges involved. The novelty of this study lies in its comprehensive analysis of existing prediction techniques and the identification of their limitations. By synthesizing a vast body of research, it highlights emerging trends and advancements, providing a holistic perspective on the subject matter. The analysis points out that future research opportunities lie in interdisciplinary collaborations, advanced data integration, remote sensing, climate change impact analysis, numerical modeling, real-time monitoring, and machine learning improvements. In conclusion, the prediction of rainfall-induced landslides is a complex and multifaceted challenge, and no single approach is universally superior. Integrating different methods and leveraging emerging technologies offer the best way forward for improving accuracy and reliability in landslide prediction, ultimately enhancing our ability to manage and mitigate this geohazard

STUDY ON TREATMENT OF THE LEACHATE FROM LANDFILL SITE AT NAMSON, SOCSON, HANOI

Joint Research on Environmental Science and Technology for the Eart

Post-mortem Reproduction from a Vietnamese Perspective—an Analysis and Commentary

Post-mortem reproduction is a complex and contested matter attracting attention from a diverse group of scholars and resulting in various responses from a range of countries. Vietnam has been reluctant to deal directly with this matter and has, accordingly, permitted post-mortem reproduction implicitly. First, by analysing Vietnam’s post-mortem reproduction cases, this paper reflects on the manner in which Vietnamese authorities have handled each case in the context of the contemporary legal framework, and it reveals the moral questions arising therefrom. The article then offers an account of Vietnamese social norms as an explanation for the tendency to conduct post-mortem reproduction. In arguing that a deeper and more thorough examination of the moral and ethical reasoning is required, the paper advocates in favour of supportive post-mortem reproduction regulation. In doing so, the paper seeks to reconcile the Vietnamese legal framework and post-mortem reproduction experiences of other countries. The article concludes that Vietnam and countries sharing the similar cultural traits should permit post-mortem reproduction explicitly. This would require full engagement with the ethical and legal issues arising, and careful promulgation of regulations and guidelines based on comparative experiences of a range of countries in handling this matter

MINING TOP-K FREQUENT SEQUENTIAL PATTERN IN ITEM INTERVAL EXTENDED SEQUENCE DATABASE

Abstract. Frequent sequential pattern mining in item interval extended sequence database (iSDB) has been one of interesting task in recent years. Unlike classic frequent sequential pattern mining, the pattern mining in iSDB also consider the item interval between successive items; thus, it may extract more meaningful sequential patterns in real life. Most previous frequent sequential pattern mining in iSDB algorithms needs a minimum support threshold (minsup) to perform the mining. However, it’s not easy for users to provide an appropriate threshold in practice. The too high minsup value will lead to missing valuable patterns, while the too low minsup value may generate too many useless patterns. To address this problem, we propose an algorithm: TopKWFP – Top-k weighted frequent sequential pattern mining in item interval extended sequence database. Our algorithm doesn’t need to provide a fixed minsup value, this minsup value will dynamically raise during the mining proces

Biocompatible chitosan-functionalized upconverting nanocomposites

Simultaneous integration of photon emission and biocompatibility into nanoparticles is an interesting strategy to develop applications of advanced optical materials. In this work, we present the synthesis of biocompatible optical nanocomposites from the combination of near-infrared luminescent lanthanide nanoparticles and water-soluble chitosan. NaYF4:Yb,Er upconverting nanocrystal guests and water-soluble chitosan hosts are prepared and integrated together into biofunctional optical composites. The control of aqueous dissolution, gelation, assembly, and drying of NaYF4:Yb,Er nanocolloids and chitosan liquids allowed us to design novel optical structures of spongelike aerogels and beadlike microspheres. Well-defined shape and near-infrared response lead upconverting nanocrystals to serve as photon converters to couple with plasmonic gold (Au) nanoparticles. Biocompatible chitosan-stabilized Au/NaYF4:Yb,Er nanocomposites are prepared to show their potential use in biomedicine as we find them exhibiting a half-maximal effective concentration (EC50) of 0.58 mg mL–1 for chitosan-stabilized Au/NaYF4:Yb,Er nanorods versus 0.24 mg mL–1 for chitosan-stabilized NaYF4:Yb,Er after 24 h. As a result of their low cytotoxicity and upconverting response, these novel materials hold promise to be interesting for biomedicine, analytical sensing, and other applications

Eliciting patients’ health concerns in consulting rooms and wards in Vietnamese public hospitals

This article examines the doctor’s elicitation of the patient’s presenting health concern in two clinical settings in the Vietnamese public hospital system: the consulting room and the ward. The data were taken from 66 audio-recorded consultations. Our analysis shows that the elicitors used by the doctor in the consulting room often communicate a weak epistemic stance towards the patient’s health issue, while those used in the ward tend to signal a strong epistemic stance. In addition, this contrast between the elicitors employed in the consulting room and the ward is evident in our data regardless of whether the consultation is a first visit or a same follow-up (in which the doctor is the same one that treated the patient on their last visit), though the contrast is less clear for different follow-ups (in which the doctor has not treated the patient before). An additional finding is that the clinical setting has some bearing on the use of inappropriate elicitation formats (in which the doctor opens the visit with an elicitor which is more appropriate for another type of visit). The precise way in which each of the consulting room and the ward operates is, of course, a feature of the Vietnamese public hospital system itself. Hence, the overall contrast between the elicitors and elicitation formats used in these two settings illustrates how, on a more general level, the institutional context can have an impact on doctor-patient communication