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Addressing the sustainability issues arising from construction and demolition waste management (DWM) has gained little traction due to the lack of incentives, stringent regulations, and systematic guidance. This study aims to empower systematic decision-making concerning DWM alternative selection by developing a sustainability assessment framework by coupling a modified Delphi method with the multicriteria decision analysis technique. First, the study identifies a comprehensive inventory of indicators across three dimensions of sustainability in the context of DWM. Next, the study combines a modified Delphi method with the analytic hierarchy process to validate and prioritize the selected sustainability indicators. For the first time, insights regarding the DWM sustainability indicators from China’s construction industry practitioners’ perspectives are elicited using a mixed method comprising online semistructured interviews and two rounds of questionnaire surveys. Experts participating in the research are mostly based in Guangzhou and Shenzhen, where local governments exhaust all efforts in promoting carbon-neutral and sustainable development. The findings reveal that eight sustainability indicators were regarded as the determinants for the sustainability performance of DWM, with the global warming potential (32%), energy efficiency (16.1%) and land use (13.5%) receiving the highest preference scores (weights) based on the experts’ judgment. Notably, the economic factors like the total cost (6.54%) appeared not highly prioritized by the local experts as typically did in the previous studies from developing countries.

Construction and demolition waste (C&DW) contribute to approximately 30% of the total waste generation worldwide, by which heterogeneous ecological impacts, such as resource depletion, global warming, and land degradation, are engendered. Despite ongoing research efforts to minimize construction waste via the Building Information Modeling (BIM)-aided design, there is a paucity of research on integrating BIM in demolition waste management (DWM). This study investigates prominent barriers and future research directions toward the wider adoption of BIM in C&DWM by conducting a systematic literature review. First, this study identifies the barriers that hinder the implementation of C&DWM in Australia; then, it explores the benefits and challenges of leveraging BIM applications for C&DWM. The findings suggest that, for existing buildings without up-to-date design drawings, it is imperative to improve the accuracy of data capturing and object recognition techniques to overcome the bottlenecks of BIM-DWM integration. Moreover, the development of regional-oriented material banks and their harmonization with life cycle assessment databases can extend the potential of BIM-based sustainability analysis, making it applicable to the DWM domain. This study proposes a research agenda on tackling these challenges to realize BIM’s full potential in facilitating DWM.

Three-dimensional (3D) printing technology is increasingly playing an essential role in the customization of prefabricated buildings. To demonstrate its high-quality, cost, and time-saving...

Ultraperformance convergence chromatography is an environmentally friendly analytical technique for dramatically reducing the use of organic solvents compared to conventional chromatographic methods. In this study, a rapid and sensitive ultraperformance convergence chromatography method was firstly established for quantification of thymol and carvacrol, two positional isomers of a major bioactive in the volatile oil of Thymi herba, the dried leaves and flowers of Thymus mongolicus or Thymus przewalskii, known in China as &ldquo, Dijiao.&rdquo, Using a TrefoilTM CEL1 column, thymol and carvacrol were separated in less than 2.5 min and resolution was enhanced. The method was validated with respect to precision, accuracy, and linearity according to the National Medical Products Administration guidelines. The optimized method exhibited good linear correlation (r = 0.9998&minus, 0.9999), excellent precision (relative standard deviations (RSDs) &lt, 1.50%), and acceptable recoveries (87.29&ndash, 102.89%). The limits of detection for thymol and carvacrol were 1.31 and 1.57 ng/L, respectively, while their corresponding limits of quantification were 2.63 and 3.14 ng/L. Finally, the quantities of the two compounds present in 16 T. mongolicus and four T. przewalskii samples were successfully evaluated by employing the developed method. It is hoped that the results of this study will serve as a guideline for the quality control of Thymi herba.

Ultraperformance convergence chromatography is an environmentally friendly analytical technique for dramatically reducing the use of organic solvents compared to conventional chromatographic methods. In this study, a rapid and sensitive ultraperformance convergence chromatography method was firstly established for quantification of thymol and carvacrol, two positional isomers of a major bioactive in the volatile oil of Thymi herba, the dried leaves and flowers of Thymus mongolicus or Thymus przewalskii, known in China as “Dijiao.” Using a TrefoilTM CEL1 column, thymol and carvacrol were separated in less than 2.5 min and resolution was enhanced. The method was validated with respect to precision, accuracy, and linearity according to the National Medical Products Administration guidelines. The optimized method exhibited good linear correlation (r = 0.9998−0.9999), excellent precision (relative standard deviations (RSDs) < 1.50%), and acceptable recoveries (87.29–102.89%). The limits of detection for thymol and carvacrol were 1.31 and 1.57 ng/L, respectively, while their corresponding limits of quantification were 2.63 and 3.14 ng/L. Finally, the quantities of the two compounds present in 16 T. mongolicus and four T. przewalskii samples were successfully evaluated by employing the developed method. It is hoped that the results of this study will serve as a guideline for the quality control of Thymi herba.

International Journal on Bioinformatics & Biosciences (IJBB) ISSN : 1839-9614 https://wireilla.com/ijbb/index.html TI Implant Hole Quality Improvement with new Tool Designed ABSTRACT Ti-implant is drilled to get hole in nearly each operation and hole quality took great effect on success of operation .This paper aims at the research of drilling characteristics of through hole on ti-implant, specially the macro-burrs formed after drilling which determined the cost of implant largely. Series experiments were conducted to analysis the effect of processing parameter on formed burr, particularly the axial feed, had a great effect on volume burr. Experiments finds that, the volume of burr at hole entrant is less than that at hole exit, and the burr volume has great effect on workpiece quality and product cost, the burr height formed easily decreases because great attention from scholars and engineers has been paid to, while the burr width size despised naturally plays a great influence on product quality and machining cost. Finally, The new de-burring tool are designed and applied in experiment, the decrease in burr width is obviously found, so the removal of burrs becomes much little than that gotten in traditional tool. The result indicates a promising future of de-burring in practical application. KEYWORDS Drilling, Burr, De-Burr, Hole Exit, Hole Entrance. For More Details: https://wireilla.com/papers/ijbb/V9N1/9119ijbb01.pdf

Ti-implant is drilled to get hole in nearly each operation and hole quality took great effect on success of operation .This paper aims at the research of drilling characteristics of through hole on ti-implant, specially the macro-burrs formed after drilling which determined the cost of implant largely. Series experiments were conducted to analysis the effect of processing parameter on formed burr, particularly the axial feed, had a great effect on volume burr. Experiments finds that, the volume of burr at hole entrant is less than that at hole exit, and the burr volume has great effect on workpiece quality and product cost, the burr height formed easily decreases because great attention from scholars and engineers has been paid to, while the burr width size despised naturally plays a great influence on product quality and machining cost. Finally, The new de-burring tool are designed and applied in experiment, the decrease in burr width is obviously found, so the removal of burrs becomes much little than that gotten in traditional tool. The result indicates a promising future of de-burring in practical application.KEYWORDSDrilling, Burr, De-Burr, Hole Exit, Hole Entrance.

Molybdenum disulfide (MoS2) is reckoned as one of the most positive low-cost HER catalysts to replace platinum-based precious metals in acid media. Unfortunately, some issues preclude MoS2 from being truly applicable including limited active sites, poor conductivity and lack of intrinsic activity. Herein, we report a Cu, Pd co-doped MoS2 nanomaterial as an efficient and stable HER electrocatalysts, which partially resolve the above-mentioned problems and leads to high overall performance. Specifically, we improve the electric conductivity of the MoS2 by Cu dopant and realize the phase transition of MoS2 from pristine 2H phase to stable 1T phase by Pd dopant. More importantly, we increase active site density to facilitate fast electrocatalytic Faradaic process via synergistic effects of Cu and Pd doping, and tune electronic energy states of MoS2 to improve HER intrinsic activity. In acidic media, the performance of Cu-Pd-MoS2 catalyst in terms of a low overpotential (−93 mV) at 10 mA cm−2, a small Tafel slope of 77 mV dec−1, and an excellent stability is better than that of single-doped catalysts.

Because of the complex and fine structure, visualization of the heart still remains a challenging task, which makes it an active research topic. In this paper, we present a visualization system for medical data, which takes advantage of the recent graphics processing unit (GPU) and can provide real-time cardiac visualization. This work focuses on investigating the anatomical structure visualization of the human heart, which is fundamental to the cardiac visualization, medical training and diagnosis assistance. Several state-of-the-art cardiac visualization methods are integrated into the proposed system and a task specified visualization method is proposed. In addition, auxiliary tools are provided to generate user specified visualization results. The contributions of our work lie in two-fold: for doctors and medical staff, the system can provide task specified visualization with interactive visualization tools; for researchers, the proposed platform can serve as a baseline for comparing different rendering methods and can easily incorporate new rendering methods. Experimental results show that the proposed system can provide favorable cardiac visualization results in terms of both effectiveness and efficiency.

In this study, we develop an adaptive-critic-based controller to steer an agile missile that has a constraint on the minimum flight Mach number from various initial Mach numbers to a given final Mach number in minimum time while completely reversing its flightpath angle. This class of bounded state space, free final time problems is very difficult to solve due to discontinuities in costates at the constraint boundaries. We use a two-neural-network structure called "adaptive critic" in this study to carry out the optimization process. This structure obtains an optimal controller through solving optimal control-related equations resulting from a Hamiltonian formulation. Detailed derivations of equations and conditions on the constraint boundary are provided. For numerical experiments, we consider vertical plane scenarios. Flight Mach number and the flightpath angle are the states and the aerodynamic angle of attack is treated as the control. Numerical results bring out some attractive features of the adaptive critic approach and show that this formulation works very well in guiding the missile to its final conditions for this state constrained optimization problem from an envelope of initial conditions.

A neural-network-based synthesis of an optimal midcourse guidance law is presented in this study. We use a set of two neural networks; the first network called a “critic” outputs the Lagrange's multipliers arising in an optimal control formulation and second network, called an “action” network, outputs the optimal guidance/control. The system equations, the optimality conditions, the costate equations are used in conjunction with the network outputs to provide the targets for the neural networks. When the critic and action network are mutually consistent, the output of the action network yields optimal guidance/control. Numerical results for a number of scenarios show that the network performance is excellent. Corroboration for optimality is provided by comparisons of the numerical solutions using a shooting method for a number of scenarios.

Transfer function design is a challenging issue of volume visualization. Some simulation and medical applications which require visualization often produce at least two values per sampling point in the so called multi-modal data, which makes transfer function design even more complex. In this paper, we present a novel visualization method for assisting the assessment of electrophysiological simulation results. The main idea of the proposed method is that the anatomical data of the heart is added as background information to enhance the illustration results of the tissue with electrophysiological behaviour. A improved context-preserving model is proposed to enhance the boundary information of different tissue. The two modalities data of both tissue with electrophysiological simulation and the other tissues are rendering by the proposed fusion rendering method with user friendly interactive facilities. Compared to conventional visualization method, our method can not only provide rendering result of tissue with electrophysiological simulation, but also can provide the spatial information of the given tissue in the heart.

We investigate the use of an 'adaptive critic' based controller to steer an agile missile with a constraint on the angle of attack from various initial Mach numbers to a given final Mach number in minimum time while completely reversing its flightpath angle. We use neural networks with a two-network structure called 'adaptive critic' to carry out the optimization process. This structure obtains an optimal controller through solving Hamiltonian equations. This approach needs no external training; each network along with the optimality equations generates the output for the other network. When the outputs are mutually consistent, the controller output is optimal. Though the networks are trained off-line, the resulting control is a feedback control.