scholarly journals Study on the Potential of Hyperaccumulator Leersia hexandra swartz to Repair Chromium Contamination of Heavy Metals

2018 ◽  
Vol 175 ◽  
pp. 04026
Author(s):  
Zhiyi Lin ◽  
Hua Lin ◽  
Yian Wang ◽  
Yuhang Yuan
Keyword(s):  
Research Direction ◽  
Polluted Water ◽  
Future Research ◽  
Polluted Environment ◽  
Tolerance Mechanism ◽  
Large Area ◽  
Considerable Potential ◽  
Detoxification Mechanism ◽  
Leersia Hexandra ◽  
Leersia Hexandra Swartz

In order to control the environmental pollution caused by chromium better, this paper summaries the study about the accumulation charac-teristics, tolerance mechanism, detoxification mechanism and enrichment efficiency of chromium in Leersia hexandra swartz in recent years. It concluded that Leersia hexandra swartz has considerable potential for remediation of polluted environment, especially large-area, low-concentration polluted water, and prospects of its future research direction.

scholarly journals Advances in remediation of heavy metal contaminated soil and water by Leersia hexandra Swartz

2020 ◽  
Vol 194 ◽  
pp. 04035
Author(s):  
Hui Qin ◽  
Hua Lin
Keyword(s):  
Heavy Metal ◽  
Environmentally Friendly ◽  
Treatment Method ◽  
Polluted Water ◽  
Human Beings ◽  
Current Application ◽  
Development Direction ◽  
Leersia Hexandra ◽  
Leersia Hexandra Swartz ◽  
Enrichment Characteristics

Heavy metal pollution is extremely harmful to human beings. Looking for an efficient and environmentally friendly treatment method is the focus of current research. Using plants to treat contaminated water and soil has proven to be an effective and environmentally friendly method. Leersia hexandra Swartz is a chromium hyperaccumulator, and it can also enrich copper and nickel. Since the super enrichment characteristics of Leersia hexandra Swartz were discovered, many scholars have poured into the research on Leersia hexandra Swartz. This article will give an overview of the current application status of Leersia hexandra Swartz’s purification of polluted water and soil, analyze the methods and principles used, and discuss the future development direction of Leersia hexandra Swartz’s plant remediation technology.

ECONOMIC GROWTH ANALYSIS: A STUDY ON MALAYSIAN MARKET

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Suhaily Maizan Abdul Manaf ◽  
Shuhada Mohamed Hamidi ◽  
Nur Shafini Mohd Said ◽  
Siti Rapidah Omar Ali ◽  
Nur Dalila Adenan
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Inflation Rate ◽  
Government Expenditure ◽  
Correlation Method ◽  
Research Direction ◽  
Least Square ◽  
Future Research ◽  
Internal And External Factors

Economic performance of a country is mostly determined by the growth and any other internal and external factors. In this study, researchers purposely focused on Malaysian market by examining the relationship between export, inflation rate, government expenditure and foreign direct investment towards economic growth in Malaysia by applying the yearly data of 47 years from 1970 to 2016 using descriptive statistics, regression model and correlation method analysis. By applying Ordinary Least Square (OLS) method, the result suggests that export, government expenditure and foreign direct investment are positively and significantly correlated with the economic growth. However, inflation rate has negative and insignificant relationship with the economic growth. The outcome of the study is suggested to be useful in providing the future research direction towards the economic growth in Malaysia. Keywords: economic growth; export; inflation rate; government expenditure

Co-Enzyme Q10 to Treat Neurological Disorders: Basic Mechanisms, Clinical Outcomes, and Future Research Direction

2013 ◽  
Vol 12 (5) ◽  
pp. 641-664 ◽  
Author(s):  
Mohamed Salama ◽  
Ti-Fei Yuan ◽  
Sergio Machado ◽  
Eric Murillo-Rodriguez ◽  
Jose Vega ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Neurological Disorders ◽  
Research Direction ◽  
Future Research ◽  
Future Research Direction

scholarly journals Structural and Functional Remodeling of Mitochondria in Cardiac Diseases

2021 ◽  
Vol 22 (8) ◽  
pp. 4167
Author(s):  
Xiaonan Sun ◽  
Jalen Alford ◽  
Hongyu Qiu
Keyword(s):  
Regulatory Network ◽  
Molecular Basis ◽  
Therapeutic Potential ◽  
Research Direction ◽  
Future Research ◽  
Cardiac Diseases ◽  
Functional Remodeling ◽  
Underlying Mechanisms ◽  
Mitochondrial Remodeling ◽  
Normal Cellular Function

Mitochondria undergo structural and functional remodeling to meet the cell demand in response to the intracellular and extracellular stimulations, playing an essential role in maintaining normal cellular function. Merging evidence demonstrated that dysregulation of mitochondrial remodeling is a fundamental driving force of complex human diseases, highlighting its crucial pathophysiological roles and therapeutic potential. In this review, we outlined the progress of the molecular basis of mitochondrial structural and functional remodeling and their regulatory network. In particular, we summarized the latest evidence of the fundamental association of impaired mitochondrial remodeling in developing diverse cardiac diseases and the underlying mechanisms. We also explored the therapeutic potential related to mitochondrial remodeling and future research direction. This updated information would improve our knowledge of mitochondrial biology and cardiac diseases’ pathogenesis, which would inspire new potential strategies for treating these diseases by targeting mitochondria remodeling.

scholarly journals Federated Quantum Machine Learning

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 460
Author(s):  
Samuel Yen-Chi Chen ◽  
Shinjae Yoo
Keyword(s):  
Machine Learning ◽  
Data Privacy ◽  
Research Direction ◽  
Future Research ◽  
Quantum Computers ◽  
Training Time ◽  
Quantum Neural Network ◽  
Distributed Training ◽  
Machine Learning Model ◽  
Quantum Machine Learning

Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects.

scholarly journals Recent Progress of Fluxgate Magnetic Sensors: Basic Research and Application

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1500
Author(s):  
Songrui Wei ◽  
Xiaoqi Liao ◽  
Han Zhang ◽  
Jianhua Pang ◽  
Yan Zhou
Keyword(s):  
Recent Progress ◽  
Electronic Devices ◽  
Basic Research ◽  
Research Direction ◽  
Magnetic Sensor ◽  
Magnetic Sensors ◽  
Future Research ◽  
Calibration Methods ◽  
Wearable Electronic ◽  
Wearable Electronic Devices

Fluxgate magnetic sensors are especially important in detecting weak magnetic fields. The mechanism of a fluxgate magnetic sensor is based on Faraday’s law of electromagnetic induction. The structure of a fluxgate magnetic sensor mainly consists of excitation windings, core and sensing windings, similar to the structure of a transformer. To date, they have been applied to many fields such as geophysics and astro-observations, wearable electronic devices and non-destructive testing. In this review, we report the recent progress in both the basic research and applications of fluxgate magnetic sensors, especially in the past two years. Regarding the basic research, we focus on the progress in lowering the noise, better calibration methods and increasing the sensitivity. Concerning applications, we introduce recent work about fluxgate magnetometers on spacecraft, unmanned aerial vehicles, wearable electronic devices and defect detection in coiled tubing. Based on the above work, we hope that we can have a clearer prospect about the future research direction of fluxgate magnetic sensor.

scholarly journals Flow and Particle Modelling of Dry Powder Inhalers: Methodologies, Recent Development and Emerging Applications

Pharmaceutics ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 189
Author(s):  
Zhanying Zheng ◽  
Sharon Shui Yee Leung ◽  
Raghvendra Gupta
Keyword(s):  
Dry Powder Inhaler ◽  
Research Direction ◽  
Particle Methods ◽  
Future Research ◽  
High Dose ◽  
Dry Powder ◽  
Multi Scale ◽  
Wide Range ◽  
Computational Fluid Dynamics Cfd ◽  
Discrete Element Methods

Dry powder inhaler (DPI) is a device used to deliver a drug in dry powder form to the lungs. A wide range of DPI products is currently available, with the choice of DPI device largely depending on the dose, dosing frequency and powder properties of formulations. Computational fluid dynamics (CFD), together with various particle motion modelling tools, such as discrete particle methods (DPM) and discrete element methods (DEM), have been increasingly used to optimise DPI design by revealing the details of flow patterns, particle trajectories, de-agglomerations and depositions within the device and the delivery paths. This review article focuses on the development of the modelling methodologies of flow and particle behaviours in DPI devices and their applications to device design in several emerging fields. Various modelling methods, including the most recent multi-scale approaches, are covered and the latest simulation studies of different devices are summarised and critically assessed. The potential and effectiveness of the modelling tools in optimising designs of emerging DPI devices are specifically discussed, such as those with the features of high-dose, pediatric patient compatibility and independency of patients’ inhalation manoeuvres. Lastly, we summarise the challenges that remain to be addressed in DPI-related fluid and particle modelling and provide our thoughts on future research direction in this field.

scholarly journals Desulfurization and Denitrification Performance of Modified Rice Husk Ash-Carbide Slag Absorbent

Materials ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 68
Author(s):  
Yali Wang ◽  
Xiaoning Han ◽  
Meina Chen ◽  
Suping Cui ◽  
Xiaoyu Ma ◽  
...  
Keyword(s):  
Functional Groups ◽  
Rice Husk ◽  
Rice Husk Ash ◽  
Research Direction ◽  
Cement Industry ◽  
Hydration Process ◽  
Air Pollution Control ◽  
Large Area ◽  
Carbide Slag ◽  
High Investment

In the cement industry, SO2 and NOx are generally removed separately. There are many problems, such as large area, high investment cost, secondary pollution and so on. Desulfurization and denitrification technology have become a frontier research direction in the field of air pollution control. In this paper, rice husk ash and carbide slag were compounded and modified to prepare modified rice husk ash-carbide slag composite absorbent, and its desulfurization and denitrification performance and mechanism were studied. The results showed that the NO conversion and SO2 conversion of the modified rice husk ash-carbide slag composite absorbent increased by 44% and 2%, respectively, at 700 °C. Fibrous calcium silicate and calcium silicoaluminate hydrates were formed during the hydration process, which made the specific surface area of the absorbent larger and provided more reactive sites. The hydration process increases the content of oxygen-containing functional groups, decreases the hydroxyl/ether C–O functional groups, and increases the content of carboxyl–COO functional groups are conducive to the denitrification reaction.

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