134 research outputs found

    Study on methylene blue adsorption using cashew nut shell-based activated carbon

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    Adsorption is a widely used technique for the treatment of wastewater containing dyes, which are pollutants that can have serious impacts on the aquatic ecosystems. In this work, activated carbon (AC) was prepared from cashew nut shell (CNS) and used to adsorb methylene blue (MB) from solution. The CNS AC was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and nitrogen adsorption-desorption isotherms. The adsorption behavior of MB on CNS AC was investigated by varying the initial solution pH, adsorbent dosage, and initial MB concentration. The results showed that the CNS AC was effective for MB removal, with an adsorption capacity of 24.8 mg/g. The adsorption nature of MB onto the CNS AC surface was explored by analyzing the experimental data using isotherm and kinetic models. The Freundlich and Dubinin-Radushkevich (D-R) isotherm models showed good agreement with the experimental adsorption equilibrium results. The mean adsorption energy was found to be 22.4 kJ/mol, indicating chemical adsorption. The adsorption of MB on the CNS AC followed pseudo-second-order kinetics. This study demonstrates the potential application of CNS AC for MB removal

    Analysis of the Dynamic Performance of Serial 3R Orthogonal Manipulators

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    International audienceSerial 3R orthogonal manipulators have been studied recently and it has been proved that they can exhibit good performances in term of workspace size and kinematic properties. The aim of this work is to analyze their dynamic performances, and compare them with anthropomorphic manipulators, which are very popular in industry. Static and dynamic analyses based on the evaluation of the maximal input torques required for moving the manipulator are achieved. It is shown that, as in kinematics, the dynamic performances of the serial 3R orthogonal manipulators are better

    A new stability results for the backward heat equation

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    In this paper, we regularize the nonlinear inverse time heat problem in the unbounded region by Fourier method. Some new convergence rates are obtained. Meanwhile, some quite sharp error estimates between the approximate solution and exact solution are provided. Especially, the optimal convergence of the approximate solution at t = 0 is also proved. This work extends to many earlier results in (f2,f3, hao1,Quan,tau1, tau2, Trong3,x1).Comment: 13 page

    Thermoresistance of p-Type 4H–SiC Integrated MEMS Devices for High-Temperature Sensing

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    There is an increasing demand for the development and integration of multifunctional sensing modules into power electronic devices that can operate in high temperature environments. Here, the authors demonstrate the tunable thermoresistance of p‐type 4H–SiC for a wide temperature range from the room temperature to above 800 K with integrated flow sensing functionality into a single power electronic chip. The electrical resistance of p‐type 4H–SiC is found to exponentially decrease with increasing temperature to a threshold temperature of 536 K. The temperature coefficient of resistance (TCR) shows a large and negative value from −2100 to −7600 ppm K−1, corresponding to a thermal index of 625 K. From the threshold temperature of 536–846 K, the electrical resistance shows excellent linearity with a positive TCR value of 900 ppm K−1. The authors successfully demonstrate the integration of p–4H–SiC flow sensing functionality with a high sensitivity of 1.035 μA(m s−1)−0.5 mW−1. These insights in the electrical transport of p–4H–SiC aid to improve the performance of p–4H–SiC integrated temperature and flow sensing systems, as well as the design consideration and integration of thermal sensors into 4H–SiC power electronic systems operating at high temperatures of up to 846 K

    Life Cycle Carbon Dioxide Emissions Assessment in the Design Phase: A Case of a Green Building in Vietnam

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    Buildings are responsible for about 30% of the total CO2 emissions globally. To reduce this amount of CO2, developing green buildings is one of the best approaches. However, this approach is undeveloped in Vietnam due to lacking methods to evaluate design alternatives to meet the criteria of green buildings. This paper presents a life-cycle CO2 analysis (LCCO2A) as a tool to support the decision-making process in the design phase of a 75-year-lifespan green building in Vietnam. The study conducts LCCO2A for two design alternatives (with different bricks usage and glass types) and points out the reasons for the differences. Comparing the first alternative with the second one, the results show slight variations in the amount of CO2 emissions in the erection and demolition phases (with an increase of 21.81 tons and a reduction of 106.1 tons of CO2eq, respectively), and a significant difference in the operation phase (10,631.52 tons of CO2eq or 58.34% reduction). For the whole life-cycle, the second design scenario, which uses “greener” materials shows a great decrease of 10,715.81 tons of CO2eq or 37.54%. By comparing its results with the findings in the literature, this research proves the environmental dominance of green buildings over other building categories

    Combining content and social features in a deep learning approach to Vietnamese email prioritization

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    The email overload problem has been discussed in numerous email-related studies. One of the possible solutions to this problem is email prioritization, which is the act of automatically predicting the importance levels of received emails and sorting the user’s inbox accordingly. Several learning-based methods have been proposed to address the email prioritization problem using content features as well as social features. Although these methods have laid the foundation works in this field of study, the reported performance is far from being practical. Recent works on deep neural networks have achieved good results in various tasks. In this paper, the authors propose a novel email prioritization model which incorporates several deep learning techniques and uses a combination of both content features and social features from email data. This method targets Vietnamese emails and is tested against a self-built Vietnamese email corpus. Conducted experiments explored the effects of different model configurations and compared the effectiveness of the new method to that of a previous work

    Soft Robotic Link with Controllable Transparency for Vision-based Tactile and Proximity Sensing

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    Robots have been brought to work close to humans in many scenarios. For coexistence and collaboration, robots should be safe and pleasant for humans to interact with. To this end, the robots could be both physically soft with multimodal sensing/perception, so that the robots could have better awareness of the surrounding environment, as well as to respond properly to humans' action/intention. This paper introduces a novel soft robotic link, named ProTac, that possesses multiple sensing modes: tactile and proximity sensing, based on computer vision and a functional material. These modalities come from a layered structure of a soft transparent silicon skin, a polymer dispersed liquid crystal (PDLC) film, and reflective markers. Here, the PDLC film can switch actively between the opaque and the transparent state, from which the tactile sensing and proximity sensing can be obtained by using cameras solely built inside the ProTac link. In this paper, inference algorithms for tactile proximity perception are introduced. Evaluation results of two sensing modalities demonstrated that, with a simple activation strategy, ProTac link could effectively perceive useful information from both approaching and in-contact obstacles. The proposed sensing device is expected to bring in ultimate solutions for design of robots with softness, whole-body and multimodal sensing, and safety control strategies.Comment: Submitted to RoboSoft 2023 for review. Final content subjected to chang

    Optimization for continuous overflow proteolytic hydrolysis of spent brewer’s yeast by using proteases

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    A large amount of spent yeast as by-product is annually generated from brewing industry and it contains about 50-55% protein with good balance of amino acids. The hydrolysate produced from spent brewer’s yeast may be used in food application. The yield of proteolylic hydrolysis for spent brewer’s yeast and amino acid contents of hydrolysates depend on factors such as temperature, pH value, type of used enzyme and ratio enzyme/substrate, time. Besides, applied hydrolysing methods (batch-, or continuous method) has effected on degree of hydrolysis. With the purpose of how proteolytic hydrolysis having effects on the spent brewer’s yeast for food application in industrial scale, continuous overflow method was used in this study. Bitterness of hydrolysate and the yield of continuous overflow proteolytic hydrolysis process are the two interested factors for protein hydrolysis. In this report, it is dealt with determination for optimal conditions to obtain the highest yield of hydrolysis process and the lowest bitterness of hydrolysate. Response surface methodology (RSM) was used to determine optimal condition for continuous overflow proteolytic hydrolysis of spent brewer’s yeast. The optimal conditions for obtaining high degree of hydrolysis and low bitterness are determined as followings: ratio of enzyme mixture (alcalase 7.5 U/g and flavourzyme 10 U/g), pH at 7.5, hydrolysis temperature at 51oC and hydrolysis time of 9 hours. Under the optimal conditions, the yield of hydrolysis was 59.62% ± 0.027 and the bitterness equivalently with concentration of quinine was 7.86 ± 0.033 μmol /ml
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