Search results for: filter cake powder

Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

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Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

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Authors: Pravaree Phuneerub, Chanida Palanuvej, Nijsiri Ruangrungsi

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Cymbopogon nardus Rendel (Family Gramineae) is commonly known as citronella grass. The dried root of C. nardus is used for antipyretic, anti-inflammation, anti-analgesic and anticancer in traditional Thai medicine. Transverse sectional and pulverized C. nardus root were illustrated. The volatile oil was extracted from oil gland by hydrodistillation and analysed by GC/MS. Cymbopogon nardus root was exhaustively extracted by continuously maceration in ethanol and water respectively. The mutagenic and antimutagenic properties of the ethanol extract and fractionated water extract of C. nardus root were evaluated by Ames assay using the S. typhimurium strains TA98 and TA100 as the models. The result indicated that the anatomical character of root transverse section displayed epidermis, parenchyma, oil gland, phloem, xylem vessel, endodermis and pith. Histological characters of root powder showed parenchyma containing oleoresin, parenchyma in longitudinal view, reticulate vessel, annular vessel, starch granules and fragment of fiber. The root volatile oil was rich in sesquiterpenes dominated by elemol (22.87%) and alpha-eudesmol (16.09%). For mutagenic activity, the both extracts of C. nardus were no mutagenic toward S. typhimurium strains TA98 and TA100. Furthermore, the ethanol extract and fractionated water extract of C. nardus root demonstrated strong antimutagenic effect against of nitrite treated 1-aminopyrene to S. typhimurium strains TA98 and TA100. This present investigation suggested that the dried root extract of C. nardus can be further developed as promising antimutagenic agent.

Keywords: Cymbopogon nardus, volatile oil analysis, mutagenic, antimutagenic effect, Ames Salmonella assay

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Authors: Adel. M. Sharaf, Foad H. Gandoman

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Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PV-hybrid-Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid-Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6-pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Keywords: AC FACTS, smart grid, stabilization, PV-battery storage, Switched Filter-Compensation (SFC)

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Authors: M. K. Hossain, J. Keidel, O. Hensel, M. Diakite

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Fat reduced dairy products are holding a potential market due to health reason. Due to less creamy, and pleasantness, reduced and/or low-fat dairy products are getting less consumer acceptance whereas the fat molecule provides smooth, creamy and a pleasant mouthfeel in dairy products especially yogurt & ice cream. This study was aimed to investigate whether the application of microparticulated whey proteins (MWPs) processed by extrusion cooking, the reduced fat yogurt can achieve similar or higher creaminess compared to whole milk (3.8% fat) and skimmed milk (0.5% fat) yogurt. Full cream and skimmed milk were used to prepare natural stirred yogurt, as well as the dry matter content, also adjusted up to 16% with skimmed milk powder. Whey protein concentrates (WPC80) were used to produce MWPs in particle size of d50 > 5 µm, d50 3<5 µm and d50 < 3 µm through the hot-extrusion process with a screw speed of 400, 600 and 1000 rpm respectively. Furthermore, the commercially available microparticulated whey protein called Simplesse® was also applied in order to compare with extruded MWPs. The rheological and sensory properties of yogurt were assessed, and data were analyzed statistically. The applications of extruded MWPs with 600 and 1000 rpm were achieved significantly (p < 0.05) higher creaminess and preference compared to the whole and skimmed milk yogurt whereas, 400 rpm got lower preference. On the other hand, Simplesse® obtained the lowest creaminess and preference compared to other yogurts, although the contribution of dry matter in yogurt was same as extruded MWPs. The creaminess and viscosities were strongly (r = 0.62) correlated, furthermore, the viscosity from sensory evaluation and the dynamic viscosity of yogurt was also significantly (r = 0.72) correlated which clarifies that the performance of sensory panelists as well as the quality of the products.

Keywords: microparticulation, hot-extrusion, reduced-fat yogurt, whey protein concentrate

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Authors: Tatyana T. Tabakova, Elitsa N. Kolentsova, Dimitar Y. Dimitrov, Krasimir I. Ivanov, Yordanka G. Karakirova, Petya Cv. Petrova, Georgi V. Avdeev

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The catalytic oxidation of CO and volatile organic compounds (VOCs) is considered as one of the most efficient ways to reduce harmful emissions from various chemical industries. The effectiveness of gold-based catalysts for many reactions of environmental significance was proven during the past three decades. The aim of this work was to combine the favorable features of Au and Cu-Ce mixed oxides in the design of new catalytic materials of improved efficiency and economic viability for removal of air pollutants in waste gases from formaldehyde production. Supported oxides of copper and cerium with Cu: Ce molar ratio 2:1 and 1:5 were prepared by wet impregnation of g-alumina. Gold (2 wt.%) catalysts were synthesized by a deposition-precipitation method. Catalysts characterization was carried out by texture measurements, powder X-ray diffraction, temperature programmed reduction and electron paramagnetic resonance spectroscopy. The catalytic activity in the oxidation of CO, CH₃OH and (CH₃)₂O was measured using continuous flow equipment with fixed bed reactor. Both Cu-Ce/alumina samples demonstrated similar catalytic behavior. The addition of gold caused significant enhancement of CO and methanol oxidation activity (100 % degree of CO and CH₃OH conversion at about 60 and 140 ^oC, respectively). The composition of Cu-Ce mixed oxides affected the performance of gold-based samples considerably. Gold catalyst on Cu-Ce/γ-Al₂O₃ 1:5 exhibited higher activity for CO and CH₃OH oxidation in comparison with Au on Cu-Ce/γ-Al₂O₃ 2:1. The better performance of Au/Cu-Ce 1:5 was related to the availability of highly dispersed gold particles and copper oxide clusters in close contact with ceria.

Keywords: CO and VOCs oxidation, copper oxide, Ceria, gold catalysts

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Authors: Tahereh Talebi, Reza Ghomashchi, Pejman Talemi, Sima Aminorroaya

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Electrophoretic deposition (EPD) of p-type Bi₂Te₃ material has been accomplished, and a high quality crack-free thick film has been achieved for thermoelectric (TE) applications. TE generators (TEG) can convert waste heat into electricity, which can potentially solve global warming problems. However, TEG is expensive due to the high cost of materials, as well as the complex and expensive manufacturing process. EPD is a simple and cost-effective method which has been used recently for advanced applications. In EPD, when a DC electric field is applied to the charged powder particles suspended in a suspension, they are attracted and deposited on the substrate with the opposite charge. In this study, it has been shown that it is possible to prepare a TE film using the EPD method and potentially achieve high TE properties at low cost. The relationship between the deposition weight and the EPD-related process parameters, such as applied voltage and time, has been investigated and a linear dependence has been observed, which is in good agreement with the theoretical principles of EPD. A stable EPD suspension of p-type Bi₂Te₃ was prepared in a mixture of acetone-ethanol with triethanolamine as a stabilizer. To achieve a high quality homogenous film on a copper substrate, the optimum voltage and time of the EPD process was investigated. The morphology and microstructures of the green deposited films have been investigated using a scanning electron microscope (SEM). The green Bi₂Te₃ films have shown good adhesion to the substrate. In summary, this study has shown that not only EPD of p-type Bi₂Te₃ material is possible, but its thick film is of high quality for TE applications.

Keywords: electrical conductivity, electrophoretic deposition, mechanical property, p-type Bi2Te3, Seebeck coefficient, thermoelectric materials, thick films

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Authors: Zh. Saffari, A. Naeimi, M. S. Ekrami-Kakhki, F. Hamidi

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Fe3O4 is one of the important magnetic oxides with spinel structure; it has exhibited unique electric and magnetic properties based on the electron transfer between Fe2+ and Fe3+ in the octahedral sites. Fe3O4 has received considerable attention in various areas such as cancer therapy, drug targeting, enzyme immobilization catalysis, magnetic cell separation, magnetic refrigeration systems and super-paramagnetic materials Fe3O4–TiO2 nanostructures were synthesized by simple, effective and new co-precipitation method assisted by ultrasonic reaction at room temperatures with organic surfactant. The effect of various parameters such as temperature, time, and power on the size and morphology of the product was investigated. Alternating gradient force magnetometer shows that Fe3O4 nanoparticles exhibit super-paramagnetic behaviour at room temperature. For preparation of nanocomposite, 1 g of TiO2 nanostructures were dispersed in 100 mL of ethanol. 0.25 g of Fe(NO3)2 and 2 mL of octanoic acid was added to the solution as a surfactant. Then, NaOH solution (1.5 M) was slowly added into the solution until the pH of the mixture was 7–8. After complete precipitation, the solution placed under the ultrasonic irradiation for 30 min. The product was centrifuged, washed with distilled water and dried in an oven at 100 °C for 3 h. The resulting red powder was calcinated at 800 °C for 3 h to remove any organic residue. The photocatalytic behaviour of Fe3O4–TiO2 nanoparticles was evaluated using the degradation of a Methyl Violet (MV) aqueous solution under ultraviolet light irradiation. As time increased, more and more MV was adsorbed on the nanoparticles catalyst, until the absorption peak vanish. The MV concentration decreased rapidly with increasing UV-irradiation time

Keywords: magnetic, methyl violet, nanocomposite, photocatalytic

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

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Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

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Authors: Nazanin Sheibanian, Raffaella Sesana, Sedat Ozbilen

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In recent years, high-entropy alloys (HEAs) have attracted considerable attention due to their unique properties and potential applications. In this study, novel HEA coatings were prepared on Mg substrates using mechanically alloyed HEA powder feedstocks based on Al_(0.1-0.5)CoCrCuFeNi and MnCoCrCuFeNi multi-material systems. The coatings were deposited by the Cold Spray (CS) process using three different temperatures of the process gas (N2) (650°C, 750°C, and 850°C) to examine the effect of gas temperature on coating properties. In this study, Infrared Thermography (non-destructive) was examined as a possible quality control technique for HEA coatings applied to magnesium substrates. Active Thermography was employed to characterize coating properties using the thermal response of the coating. Various HEA chemical compositions and deposition temperatures have been investigated. As a part of this study, a comprehensive macro and microstructural analysis of Cold Spray (CS) HEA coatings has been conducted using macrophotography, optical microscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM+EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), microhardness tests, roughness measurements, and porosity assessments. These analyses provided insight into phase identification, microstructure characterization, deposition, particle deformation behavior, bonding mechanisms, and identifying a possible relationship between physical properties and thermal responses. Based on the figures and tables, it is evident that the Maximum Relative Radiance (∆RMax) of each sample differs depending on both the chemical composition of HEA and the temperature at which Cold Spray is applied.

Keywords: active thermography, coating, cold spray, high- entropy alloy, material characterization

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Authors: Marta Błażkiewicz-Mazurek, Adam Konefał

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The project can be divided into three main parts: i. modeling the Cf-252 neutron source and conducting an experiment to verify the correctness of the obtained results, ii. design of the BNCT system infrastructure, iii. analysis of the results from the logical detector. Modeling of the Cf-252 source included designing the shape and size of the source as well as the energy and spatial distribution of emitted neutrons. Two options were considered: a point source and a cylindrical spatial source. The energy distribution corresponded to various spectra taken from specialized literature. Directionally isotropic neutron emission was simulated. The simulation results were compared with experimental values determined using the activation detector method using indium foils and cadmium shields. The relative fluence rate of thermal and resonance neutrons was compared in the chosen places in the vicinity of the source. The second part of the project related to the modeling of the BNCT infrastructure consisted of developing a simulation program taking into account all the essential components of this system. Materials with moderating, absorbing, and backscattering properties of neutrons were adopted into the project. Additionally, a gamma radiation filter was introduced into the beam output system. The analysis of the simulation results obtained using a logical detector located at the beam exit from the BNCT infrastructure included neutron energy and their spatial distribution. Optimization of the system involved changing the size and materials of the system to obtain a suitable collimated beam of thermal neutrons.

Keywords: BNCT, Monte Carlo, neutrons, simulation, modeling

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Authors: Diego Cruz, Helbert Arevalo, Diana Vernot

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In 2013, the Food and Agriculture Organization of the United Nations (FAO) said that insect production for food and feed could become an economic opportunity for rural women in developing countries. However, since then, just a few initiatives worldwide had tried to implement this kind of project in zones of tropical countries without previous experience in cricket production and insect human consumption, such as Colombia. In this project, ArthroFood company and the University of La Sabana join efforts to make a holistic multi-perspective analysis from biological, economic, culinary, and social sides of the Gryllodes sigillatus production by rural women of the municipality of La Mesa, Cundinamarca, Colombia. From a biological and economic perspective, G. sigillatus production in a 60m2 greenhouse was evaluated considering the effect of rearing density and substrates on final weight and length, developing time, survival rate, and proximate composition. Additionally, the production cost and labor hours were recorded for five months. On the other hand, from a socio- economic side, the intention of the rural women to implement cricket farms or micro-entrepreneurship around insect production was evaluated after developing ethnographies and empowerment, entrepreneurship, and cricket production workshops. Finally, the results of the elaboration of culinary recipes with cricket powder incorporating cultural aspects of the context of La Mesa, Cundinamarca, will be presented. This project represents Colombia's first attempt to create a social business model of cricket production involving rural women, academies, the private sector, and local authorities.

Keywords: cricket production, developing country, edible insects, entrepreneurship, insect culinary recipes

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Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

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Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

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Authors: Seong Woon Lee, Soo Min Lim, Sung Sik Jeong, Jung Hoon Park

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The atmospheric concentration of greenhouse gas (GHG, Green House Gas) is increasing continuously as a result of the combustion of fossil fuels and industrial development. In response to this trend, many researches have been conducted on the reduction of GHG. Landfill gas (LFG, Land Fill Gas) is one of largest sources of GHG emissions containing the methane (CH₄) as a major constituent and can be considered renewable energy sources as well. In order to use LFG by connecting to the city pipe network, it required a process for removing impurities. In particular, oxygen must be removed because it can cause corrosion of pipes and engines. In this study, methane oxidation was used to eliminate oxygen from LFG and perovskite-type ceramic catalysts of La-Sr-Co-Fe-O composition was selected as a catalyst. Hollow fiber catalysts (HFC, Hollow Fiber Catalysts) have attracted attention as a new concept alternative because they have high specific surface area and mechanical strength compared to other types of catalysts. HFC was prepared by a phase-inversion/sintering technique using commercial La-Sr-Co-Fe-O powder. In order to measure the catalysts' activity, simulated LFG was used for feed gas and complete oxidation reaction of methane was confirmed. Pore structure of the HFC was confirmed by SEM image and perovskite structure of single phase was analyzed by XRD. In addition, TPR analysis was performed to verify the oxygen adsorption mechanism of the HFC. Acknowledgement—The project is supported by the ‘Global Top Environment R&D Program’ in the ‘R&D Center for reduction of Non-CO₂ Greenhouse gases’ (Development and demonstration of oxygen removal technology of landfill gas) funded by Korea Ministry of Environment (ME).

Keywords: complete oxidation, greenhouse gas, hollow fiber catalyst, land fill gas, oxygen removal, perovskite catalyst

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Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

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Authors: R. F. Vieira, S. A. Figueiredo, O. M. Freitas, V. F. Domingues, C. Delerue-Matos

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The presence of sulphur compounds like hydrogen sulphide and mercaptans is one of the reasons for waste-water treatment and waste management being associated with odour emissions. In this context having a quantifying method for these compounds helps in the optimization of treatment with the goal of their elimination, namely biofiltration processes. The aim of this study was the development of a method for quantification of odorous gases in waste treatment plants air samples. A method based on head space solid phase microextraction (HS-SPME) coupled with gas chromatography - flame photometric detector (GC-FPD) was used to analyse H2S and Metil Mercaptan (MM). The extraction was carried out with a 75-μm Carboxen-polydimethylsiloxane fiber coating at 22 ºC for 20 min, and analysed by a GC 2010 Plus A from Shimadzu with a sulphur filter detector: splitless mode (0.3 min), the column temperature program was from 60 ºC, increased by 15 ºC/min to 100 ºC (2 min). The injector temperature was held at 250 ºC, and the detector at 260 ºC. For calibration curve a gas diluter equipment (digital Hovagas G2 - Multi Component Gas Mixer) was used to do the standards. This unit had two input connections, one for a stream of the dilute gas and another for a stream of nitrogen and an output connected to a glass bulb. A 40 ppm H2S and a 50 ppm MM cylinders were used. The equipment was programmed to the selected concentration, and it automatically carried out the dilution to the glass bulb. The mixture was left flowing through the glass bulb for 5 min and then the extremities were closed. This method allowed the calibration between 1-20 ppm for H2S and 0.02-0.1 ppm and 1-3.5 ppm for MM. Several quantifications of air samples from inlet and outlet of a biofilter operating in a waste management facility in the north of Portugal allowed the evaluation the biofilters performance.

Keywords: biofiltration, hydrogen sulphide, mercaptans, quantification

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Authors: S. I. Usenko, V. N. Golubeva, I. A. Konopkina, I. V. Astakhova, O. V. Vakhnina, A. A. Korableva, A. A. Kalinina, K. B. Zhogova

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Gold can be determined in natural objects and manufactured articles of different origin. The up-to-date status of research and problems of high gold level determination in alloys and manufactured articles are described in detail in the literature. No less important is the task of this metal determination in minerals, process products and waste pieces. The latters, as objects of gold content chemical analysis, are most hard-to-study for two reasons: Because of high requirements to accuracy of analysis results and because of difference in chemical and phase composition. As a rule, such objects are characterized by compound, variable and very often unknown matrix composition that leads to unpredictable and uncontrolled effect on accuracy and other analytical characteristics of analysis technique. In this paper, the methods for the determination of gold are described, using flame atomic-absorption spectrophotometry and gravimetric analysis technique. The techniques are aimed at gold determination in a solution for gold etching (KJ+J2), in the technological mixture formed after cleaning stainless steel members of vacuum-deposit installation with concentrated nitric and hydrochloric acids as well as in gold-containing powder resulted from liquid wastes reprocessing. Optimal conditions for sample preparation and analysis of liquid and solid waste specimens of compound and variable matrix composition were chosen. The boundaries of relative resultant error were determined for the methods within the range of gold mass concentration from 0.1 to 30g/dm3 in the specimens of liquid wastes and mass fractions from 3 to 80% in the specimens of solid wastes.

Keywords: microelectronics waste pieces, gold, sample preparation, atomic-absorption spectrophotometry, gravimetric analysis technique

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Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Berhan Fikru

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The objective of this study was to develop new complementary food from maize, soybean and moringa for young children. The complementary foods were formulated with linear programming (LP Nutri-survey software) and Faffa (corn soya blend) use as control. Analysis were made for formulated blends and compared with the control and recommended daily intake (RDI). Three complementary foods composed of maize, soya bean, moringa and sugar with ratio of 65:20:15:0, 55:25:15:5 and 65:20:10:5 for blend 1, 2 and 3, respectively. The blends were formulated based on the protein, energy, mineral (iron, zinc an calcium) and vitamin (vitamin A and C) content of foods. The overall results indicated that nutrient content of faffa (control) was 16.32 % protein, 422.31 kcal energy, 64.47 mg calcium, 3.8 mg iron, 1.87mg zinc, 0.19 mg vitamin A and 1.19 vitamin C; blend 1 had 17.16 % protein, 429.84 kcal energy, 330.40 mg calcium, 6.19 mg iron, 1.62 mg zinc, 6.33 mg vitamin A and 4.05 mg vitamin C; blend 2 had 20.26 % protein, 418.79 kcal energy, 417.44 mg calcium, 9.26 mg iron, 2.16 mg zinc, 8.43 mg vitamin A and 4.19 mg vitamin C whereas blend 3 exhibited 16.44 % protein, 417.42 kcal energy, 242.4 mg calcium, 7.09 mg iron, 2.22 mg zinc, 3.69 mg vitamin A and 4.72 mg vitamin C, respectively. The difference was found between all means statically significance (P < 0.05). Sensory evaluation showed that the faffa control and blend 3 were preferred by semi-trained panelists. Blend 3 had better in terms of its mineral and vitamin content than FAFFA corn soya blend and comparable with WFP proprietary products CSB+, CSB++ and fulfills the WHO recommendation for protein, energy and calcium. The suggested formulation with Moringa powder can therefore be used as a complementary food to improve the nutritional status and also help solve problems associated with protein energy and micronutrient malnutrition for young children in developing countries, particularly in Ethiopia.

Keywords: corn soya blend, proximate composition, micronutrient, mineral chelating agents, complementary foods

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Authors: Juan Manuel Uriarte Lopez, Hector Raul Guemez Gaxiola, Javier Alonso Romo Rubio, Juan Manuel Romo Valdez

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The objective of this investigation was to determine the influence of the use of recycled vegetable oil from restaurants in the productive performance of sows in lactation. Twenty-four hybrids lactating sows (Landrace x Yorkshire) were divided into three treatments with eight sows per treatment. On day 107 of gestation, the sows were moved to the mesh floor maternity cages in an environment regulated by the environment regulated (2.4 × 0.6 m) contained an area (2.4 × 0.5 m) for newborn pigs on each side, all diets were provided as a dry powder, and the sows received free access to water throughout the experimental period. After farrowing, the sows were fasted for 12 hours, the daily feed ration gradually increased, and the sows had ad libitum access to feed on the fourth day. The diets used were corn-soybean meal-based, containing 0 (CONT), recycled vegetable oil 1.0 % (RVOL), or recycled vegetable oil 1.5 % (RVOH) for 30 days. The diets contained similar calculated levels of crude protein and metabolizable energy and contained vitamins and minerals that exceeded National Research Council (1998) recommendations; sows were fed three times daily. On day 30, piglets were weaned, and performances of lactating sows and nursery piglets were recorded. Results indicated that average daily feed intake (5.58, 5.55, and 5.49 kg for CONT, RVOL, and RVO, respectively) of sows were not affected (P > 0.05) by different dietary. There was no difference in the average body weight of piglets on the day of birth, with 1.33, 1.36, and 1.35 kg, respectively (P > 0.05). There was no difference in average body weight of piglets on day 30, with 6.91, 6.75, and 7.05 kg, respectively 0.05) between treatments numbers of weaned piglets per sow (9.95, 9.80, and 9.80) were not affected by treatments (P > 0.05).In conclusion, the substitution of virgin vegetable oil for recycled vegetable oil in the diet does not affect the productive performance of lactating sows.

Keywords: lactating, sow, vegetable, oil

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Authors: Adil Basuki Ahza, Michael Liong, Subarna Suryatman

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Healthy chips now dominating the snack market shelves. More than 80% processed snack foods in the market are chips. This research takes the advantages of twin extrusion technology to produce two types of product, i.e. directly expanded and intermediate ready-to-fry or microwavable chips. To improve the functional quality, the cereal-tuber based mix was enriched with antioxidant rich mix of temurui, celery, carrot and isolated soy protein (ISP) powder. Objectives of this research were to find best composite cassava-sorghum ratio, i.e. 60:40, 70:30 and 80:20, to optimize processing conditions of extrusion and study the microstructural, physical and sensorial characteristics of the final products. Optimization was firstly done by applying metering section of extruder barrel temperatures of 120, 130 and 140 °C with screw speeds of 150, 160 and 170 rpm to produce direct expanded product. The intermediate product was extruded in 100 °C and 100 rpm screw speed with feed moisture content of 35, 40 and 45%. The directly expanded products were analyzed for color, hardness, density, microstructure, and organoleptic properties. The results showed that interaction of ratio of cassava-sorghum and cooking methods affected the product's color, hardness, and bulk density (p<0.05). Extrusion processing conditions also significantly affected product's microstructure (p<0.05). The direct expanded snacks of 80:20 cassava-sorghum ratio and fried expanded one 70:30 and 80:20 ratio shown the best organoleptic score (slightly liked) while baking the intermediate product with microwave were resulted sensorial not acceptable quality chips.

Keywords: cassava-sorghum composite, extrusion, microstructure, physical characteristics

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Authors: Hwasuk Jung, Seoi Lee, Dongchoon Ryou, Pyungjong Yoo, Seokmo Lee

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The Nakdong River being used as drinking water sources for Pusan metropolitan city has the vulnerability of water management due to the fact that industrial areas are located in the upper Nakdong River. Most citizens of Busan think that the water quality of Nakdong River is not good, so they boil or use home filter to drink tap water, which causes unnecessary individual costs to Busan citizens. We need to diversify water intake to reduce the cost and to change the weak water source. Under this background, this study was carried out for the environmental accounting of Namgang dam water treatment system compared to Nakdong River water treatment system by using emergy analysis method to help making reasonable decision. Emergy analysis method evaluates quantitatively both natural environment and human economic activities as an equal unit of measure. The emergy transformity of Namgang dam’s water was 1.16 times larger than that of Nakdong River’s water. Namgang Dam’s water shows larger emergy transformity than that of Nakdong River’s water due to its good water quality. The emergy used in making 1 m3 tap water from Namgang dam water treatment system was 1.26 times larger than that of Nakdong River water treatment system. Namgang dam water treatment system shows larger emergy input than that of Nakdong river water treatment system due to its construction cost of new pipeline for intaking Namgang daw water. If the Won used in making 1 m3 tap water from Nakdong river water treatment system is 1, Namgang dam water treatment system used 1.66. If the Em-won used in making 1 m3 tap water from Nakdong river water treatment system is 1, Namgang dam water treatment system used 1.26. The cost-benefit ratio of Em-won was smaller than that of Won. When we use emergy analysis, which considers the benefit of a natural environment such as good water quality of Namgang dam, Namgang dam water treatment system could be a good alternative for diversifying intake source.

Keywords: emergy, emergy transformity, Em-won, water treatment system

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Authors: Amit Keshav, Alok Sharma, Bidyut Mazumdar

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Colocasia esculenta leaves and roots are widely used in Asian countries, such as, India, Srilanka and Pakistan, as food and feed material. The root is high in carbohydrates and rich in zinc. The leaves and stalks are often traditionally preserved to be eaten in dry season. Leaf juice is stimulant, expectorant, astringent, appetizer, and otalgia. Looking at the medicinal uses of the plant leaves; phytochemicals were extracted from the plant leaves and were characterized using Fourier-transform infrared spectroscopy (FTIR) to find the functional groups. Phytochemical analysis of Colocasia esculenta (L.) leaf was studied using three solvents (methanol, chloroform, and ethanol) with soxhlet apparatus. Powder of the leaves was employed to obtain the extracts, which was qualitatively and quantitatively analyzed for phytochemical content using standard methods. Phytochemical constituents were abundant in the leave extract. Leaf was found to have various phytochemicals such as alkaloids, glycosides, flavonoids, terpenoids, saponins, oxalates and phenols etc., which could have lot of medicinal benefits such as reducing headache, treatment of congestive heart failure, prevent oxidative cell damage etc. These phytochemicals were identified using UV spectrophotometer and results were presented. In order to find the antioxidant activity of the extract, DPPH (2,2-diphenyl-1-picrylhydrazyl) method was employed using ascorbic acid as standard. DPPH scavenging activity of ascorbic acid was found to be 84%, whereas for ethanol it was observed to be 78.92%, for methanol: 76.46% and for chloroform: 72.46%. Looking at the high antioxidant activity, Colocasia esculenta may be recommended for medicinal applications. The characterizations of functional groups were analyzed using FTIR spectroscopy.

Keywords: antioxidant activity, Colocasia esculenta, leaves, characterization, FTIR

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Authors: Sophia Shi

Abstract:

Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Ayesha Aihetasham, Najma Arshad, Sobia Khan

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Damage causes by subterranean termites are of major concern today. Termites majorly treated with pesticides resulted in several problems related to health and environment. For this reason, plant-derived natural products specifically essential oils have been evaluated in order to control termites. The aim of the present study was to investigate the antitermitic potential of six essential oils on Heterotermes indicola subterranean termite. No-choice bioassay was used to assess the termiticidal action of essential oils. Further, gut from each set of treated termite group was extracted and analyzed for reduction in number of protozoa and bacteria by protozoal count method using haemocytometer and viable bacterial plate count (dilution method) respectively. In no-choice bioassay it was found that Foeniculum vulgare oil causes high degree of mortality 90 % average mortality at 10 mg oil concentration (10mg/0.42g weight of filter paper). Least mortality appeared to be due to Citrus sinensis oil (43.33 % average mortality at 10 mg/0.42g). The highest activity verified to be of Foeniculum vulgare followed by Eruca sativa, Trigonella foenum-graecum, Peganum harmala, Syzygium cumini and Citrus sinensis. The essential oil which caused maximum reduction in number of protozoa was P. harmala followed by T. foenum-graecum and E. sativa. In case of bacterial count E. sativa oil indicated maximum decrease in bacterial number (6.4×10⁹ CFU/ml). It is concluded that F. vulgare, E. sativa and P. harmala essential oils are highly effective against H. indicola termite and its gut microflora.

Keywords: bacterial count, essential oils, Heterotermes indicola, protozoal count

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Authors: Vedant Janapaty

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Estuaries are wetlands where fresh water from streams mixes with salt water from the sea. Also known as “kidneys of our planet”- they are extremely productive environments that filter pollutants, absorb floods from sea level rise, and shelter a unique ecosystem. However, eutrophication and loss of native species are ailing our wetlands. There is a lack of uniform data collection and sparse research on correlations between satellite data and in situ measurements. Remote sensing (RS) has shown great promise in environmental monitoring. This project attempts to use satellite data and correlate metrics with in situ observations collected at five estuaries. Images for satellite data were processed to calculate 7 bands (SIs) using Python. Average SI values were calculated per month for 23 years. Publicly available data from 6 sites at ELK was used to obtain 10 parameters (OPs). Average OP values were calculated per month for 23 years. Linear correlations between the 7 SIs and 10 OPs were made and found to be inadequate (correlation = 1 to 64%). Fourier transform analysis on 7 SIs was performed. Dominant frequencies and amplitudes were extracted for 7 SIs, and a machine learning(ML) model was trained, validated, and tested for 10 OPs. Better correlations were observed between SIs and OPs, with certain time delays (0, 3, 4, 6 month delay), and ML was again performed. The OPs saw improved R² values in the range of 0.2 to 0.93. This approach can be used to get periodic analyses of overall wetland health with satellite indices. It proves that remote sensing can be used to develop correlations with critical parameters that measure eutrophication in situ data and can be used by practitioners to easily monitor wetland health.

Keywords: estuary, remote sensing, machine learning, Fourier transform

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Authors: K. Tomolya, D. Janovszky, A. Sycheva, M. Sveda, A. Roosz

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CuZrAl amorphous alloys have attracted high interest due to unique physical and mechanical properties, which can be enhanced by adding of Ni and Ti elements. It is known that this properties can be enhanced by crystallization of amorphous alloys creating nanocrystallines in the matrix. The present work intends to produce nanosized crystalline parti-cle reinforced amorphous matrix composite powders by crystallization of amorphous powders. As the first step the amorphous powders were synthe-tized by ball-milling of crystalline powders. (Cu49Zr45Al6) 80Ni10Ti10 and (Cu49Zr44Al7) 80Ni10Ti10 (at%) alloys were ball-milled for 12 hours in order to reach the fully amorphous structure. The impact en-ergy of the balls during milling causes the change of the structure in the powders. Scanning electron microscopical (SEM) images shows that the phases mixed first and then changed into a fully amorphous matrix. Furthermore, nanosized particles in the amorphous matrix were crystallized by heat treatment of the amorphous powders that was confirmed by TEM measurement. It was of importance to define the tem-perature when the amorphous phase starts to crystal-lize. Amorphous alloys have a special heating curve and characteristic temperatures, which can be meas-ured by differential scanning calorimetry (DSC). A typical DSC curve of an amorphous alloy exhibits an endothermic event characteristic of the equilibrium glass transition (Tg) and a distinct undercooled liquid region, followed by one or two exothermic events corresponding to crystallization processes (Tp). After measuring the DSC traces of the amorphous powders, the annealing temperatures should be determined between Tx and Tp. In our experiments several temperatures from the annealing temperature range were selected and de-pendency of crystallized nanoparticles fraction on their hardness was investigated.

Keywords: amorphous structure, composite, mechanical milling, powder, scanning electron microscopy (SEM), differential scanning calorimetry (DSC), transmission electronmocroscopy (TEM)

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Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

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Authors: Bekan Bogale, Tsegaye Girma Asere, Tilahun Yai, Fekadu Melak

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Aims: To study photocatalytic degradation of methylene blue dye on cuprous oxide/graphene nanocomposite. Background: Cuprous oxide (Cu2O) nanoparticles are among the metal oxides that demonstrated photocatalytic activity. However, the stability of Cu2O nanoparticles due to the fast recombination rate of electron/hole pairs remains a significant challenge in their photocatalytic applications. This, in turn, leads to mismatching of the effective bandgap separation, tending to reduce the photocatalytic activity of the desired organic waste (MB). To overcome these limitations, graphene has been combined with cuprous oxides, resulting in cuprous oxide/graphene nanocomposite as a promising photocatalyst. Objective: In this study, Cu2O/graphene nanocomposite was synthesized and evaluated for its photocatalytic performance of methylene blue (MB) dye degradation. Method: Cu2O/graphene nanocomposites were synthesized from graphite powder and copper nitrate using the facile sol-gel method. Batch experiments have been conducted to assess the applications of the nanocomposites for MB degradation. Parameters such as contact time, catalyst dosage, and pH of the solution were optimized for maximum MB degradation. The prepared nanocomposites were characterized by using UV-Vis, FTIR, XRD, and SEM. The photocatalytic performance of Cu2O/graphene nanocomposites was compared against Cu2O nanoparticles for cationic MB dye degradation. Results: Cu2O/graphene nanocomposite exhibits higher photocatalytic activity for MB degradation (with a degradation efficiency of 94%) than pure Cu2O nanoparticles (67%). This has been accomplished after 180 min of irradiation under visible light. The kinetics of MB degradation by Cu2O/graphene composites can be demonstrated by the second-order kinetic model. The synthesized nanocomposite can be used for more than three cycles of photocatalytic MB degradation. Conclusion: This work indicated new insights into Cu2O/graphene nanocomposite as high-performance in photocatalysis to degrade MB, playing a great role in environmental protection in relation to MB dye.

Keywords: methylene blue, photocatalysis, cuprous oxide, graphene nanocomposite

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Authors: Michella Alnajjar, Frederic Christien, Krzysztof Wolski, Cedric Bosch

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Additive manufacturing (AM) has gained more interest in the past few years because it allows 3D parts often having a complex geometry to be directly fabricated, layer by layer according to a CAD model. One of the AM techniques is the selective laser melting (SLM) which is based on powder bed fusion. In this work, the corrosion resistance of 17-4 PH steel obtained by SLM is investigated. Wrought 17-4 PH steel is a martensitic precipitation hardenable stainless steel. It is widely used in a variety of applications such as aerospace, medical and food industries, due to its high strength and relatively good corrosion resistance. However, the combined findings of X-Ray diffraction and electron backscatter diffraction (EBSD) proved that SLM-ed 17-4 PH steel has a fully ferritic microstructure, more specifically δ ferrite. The microstructure consists of coarse ferritic grains elongated along the build direction, with a pronounced solidification crystallographic texture. These results were associated with the high cooling and heating rates experienced throughout the SLM process (10⁵-10⁶ K/s) that suppressed the austenite formation and produced a 'by-passing' phenomenon of this phase during the numerous thermal cycles. Furthermore, EDS measurements revealed a uniform distribution of elements without any dendritic structure. The extremely high cooling kinetics induced a diffusionless solidification, resulting in a homogeneous elemental composition. Consequently, the corrosion properties of this steel are altered from that of conventional ones. By using electrochemical means, it was found that SLM-ed 17-4 PH is more resistant to general corrosion than the wrought steel. However, the SLM-ed material exhibits metastable pitting due to its high porosity density. In addition, the hydrogen embrittlement of SLM-ed 17-4 PH steel is investigated, and a correlation between its behavior and the observed microstructure is made.

Keywords: corrosion resistance, 17-4 PH stainless steel, selective laser melting, hydrogen embrittlement

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