Novel eco-friendly low cost and energy efficient synthesis of (Nd–Pr–Dy)2Fe14B magnetic powder from monazite concentrate

Syntheses of Nd2Fe14B magnetic powder by conventional method is a complicated multi-step process, which produces harmful pollutants and consumes a huge amount of energy and resources. Herein we report a simple chemical route for the preparation of (Nd–Pr)2Fe14B magnetic powder using monazite concentrate as a precursor. Th, U, Sm, and La impurities were removed from monazite leachate by roasting, solvent extraction and leaching the concentrate. Purified leachate consisting of Nd and Pr Chlorides was added to the FeCl3 solution, and the solution produced was co-precipitated with NaOH. RE and Fe hydroxide precipitates were converted to the oxides by annealing at 700 °C. Boric acid and CaH2 were added in the RE and Fe oxides produced, and this mixture was reduced and diffused to (Nd–Pr)2Fe14B. Magnetic properties of the (Nd–Pr)2Fe14B produced were enhanced by introducing antiferromagnetic coupling, induced by Dy addition and efficient removal of CaO byproduct through ball milling in ethanol which increased the BHmax from 3.9 to 11.45 MGOe. Process reported is energy efficient, environment-friendly, time saving and low-cost.

Is Expensive More Environment Friendly? Comparative LCA of Three Home Appliances

Due to rise in income and living standards in the developing world, there is a substantial growth in the use of home appliances. This growth is responsible for several environmental issues. Hence, there is a growing demand for energy efficient, environment friendly, and sustainable appliances. This study compares the environmental impacts of three home appliances using Life Cycle Assessment (LCA). Three irons of same power rating but with different prices (low, medium, and high) were selected for this study. First, energy consumption of these irons was measured and then they were disassembled to generate a detailed list of components, materials, and processes used to manufacture them. Next, LCA was conducted using SimaPro to compare the environmental impacts of these irons. Life cycle stages including material extraction, component manufacturing, assembly, distribution, and use were considered in LCA. Both ReCiPe mid-point and end-point environmental impacts were calculated. The results of this study showed that high-price iron was more environment friendly than the low-price iron.

Hybrid SDN Networks: A multi-parameter server load balancing scheme

Software-defined networking (SDN) provides many benefits, including traffic programmability, agility, and network automation. However, budget constraints burdened with technical (e.g., scalability, fault tolerance, security issues) and, sometimes, business challenges (user acceptance and confidence of network operators) make providers indecisive for full SDN deployment. Therefore, incremental deployment of SDN functionality through the placement of a limited set of SDN devices among traditional devices represents a rational and efficient environment that can offer customers modern and more data-intensive services. However, while hybrid SDN provides many benefits, it also has specific challenges addressed in the literature. This paper answers one of these challenges by presenting the research and development of a new load balancing scheme in the hybrid SDN environment built with a minimal SDN device set (controller and one switch). We propose a novel load balancing scheme to monitor current server load indicators and apply multi-parameter metrics for scheduling connections to balance the load on the servers as efficiently as possible. The base of the new load balancing scheme is continuous monitoring of server load indicators and implementations of multi-parameter metrics (CPU load, I/O Read, I/O Write, Link Upload, Link Download) for scheduling connections. The testing performed on servers aims to balance the server's load as efficiently as possible. The obtained results have shown that this mechanism achieves better results than existing load balancing schemes in traditional and SDN networks. Moreover, a proposed load balancing scheme can be used with various services and applied in any client-server environment.

Teaching and learning robotic surgery at the dual console: a video-based qualitative analysis

Robotic-assisted surgery (RAS) involves training processes and challenges that differ from open or laparoscopic surgery, particularly regarding the possibilities of observation and embodied guidance. The video recording and the dual-console system creates a potential opportunity for participation. Our research, conducted within the department of visceral surgery of a big Swiss, public, academic hospital, uses a methodology based on the co-analysis of video recordings with surgeons in self-confrontation interviews, to investigate the teaching activity of the lead surgeon supervising a surgeon in training at the dual console. Three short sequences have been selected for the paper. Our analysis highlights the skills-in-construction of the surgeon in training regarding communication with the operating team, fluency of working with three hands, and awareness of the whole operating site. It also shows the divergent necessities of enabling verbalization for professional training, while ensuring a quiet and efficient environment for medical performance. To balance these requirements, we argue that dedicated briefing and debriefing sessions may be particularly effective; we also suggest that the self-confrontation video technique may be valuable to support the verbalization on both the mentor’s and the trainee’s side during such debriefing, and to enhance the mentor’s reflexivity regarding didactic choices.

Pilot test of environment-friendly catalysts for the DeNOx of low-temperature flue gas from a coal-fired plant

Efficient, environment-friendly, and energy-saving low-temperature denitration (DeNOx) catalysts, applicable in practical flue gas, has a widespread market for use in small-scale boilers. A novel Ce-based low-temperature honeycomb catalyst was tested...

On the Ergodicity of an Autonomous Robot for Efficient Environment Explorations

This paper addresses the autonomous robot ergodicity problem for efficient environment exploration. The spatial distribution as a reference distribution is given by a mixture of Gaussian and the mass generation of the robot is assumed to be skinny Gaussian. The main problem to solve is then to find out proper timing for the robot to visit as well as leave each component-wise Gaussian for the purpose of achieving the ergodicity. The novelty of the proposed method is that no approximation is required for the developed method. Given the definition of the ergodic function, a convergence condition is derived based on the timing analysis. Also, a formal algorithm to achieve the ergodicity is provided. To support the validity of the proposed algorithm, simulation results are provided.

Real-Time Compact Environment Representation for UAV Navigation

Recently, unmanned aerial vehicles (UAVs) have attracted much attention due to their on-demand deployment, high mobility, and low cost. For UAVs navigating in an unknown environment, efficient environment representation is needed due to the storage limitation of the UAVs. Nonetheless, building an accurate and compact environment representation model is highly non-trivial because of the unknown shape of the obstacles and the time-consuming operations such as finding and eliminating the environmental details. To overcome these challenges, a novel vertical strip extraction algorithm is proposed to analyze the probability density function characteristics of the normalized disparity value and segment the obstacles through an adaptive size sliding window. In addition, a plane adjustment algorithm is proposed to represent the obstacle surfaces as polygonal prism profiles while minimizing the redundant obstacle information. By combining these two proposed algorithms, the depth sensor data can be converted into the multi-layer polygonal prism models in real time. Besides, a drone platform equipped with a depth sensor is developed to build the compact environment representation models in the real world. Experimental results demonstrate that the proposed scheme achieves better performance in terms of precision and storage as compared to the baseline.