H+3 in the jovian planets

Jupiter has long been a subject of fascination and curiosity. Recently it has become the focus of numerous studies first with ground-based telescopes and then of unmaned spacecraft, notably the Pioneers and Voyagers series. The discovery of the ionic species H+3 on Jupiter presented the scientific community with an important tool for probing and studying the jovian ionosphere. Earth based observations have answered some questions but raised a number of others concerning the production and maintenance of the jovian ionosphere. Infrared images of Jupiter were taken and analysed for morphology and distribution of H+3. Auroral emission was discovered to have a well defined structure and found to be fairly stable over a long period of time. The main area of emission was found to be located at the footprints of high L-shells, possibly above L-shell = 30 (Connerney's O6 magnetic field model 1991, 1993). The northern H+3 emission appears to occur in a large patch around ?III = 150° and in a series of bright spots forming a possible oval. In the south the emission seems more diffuse with none of the bright spots similar to those observed in the north. The emission appears to come from an oval, but due to the geometry of the southern aurora it is hard to say whether this is true or not. Spectra of Jupiter taken at wavelengths sensitive to H+3 emissions are presented in this study. Results of fitting a theoretical H+3 spectrum to the data are reported. H+3 emission was found to originate from the whole disk of Jupiter on the day side. Mapping the H3 emission onto a longitude, latitude grid shows that the results agrees with the imaging work. The low latitude emission is found to correlate closely with the magnetic field dip angles as predicted by Connerney's O6 model (1991, 1993)

Auto-Denoising for EEG Signals Using Generative Adversarial Network.

The brain-computer interface (BCI) has many applications in various fields. In EEG-based research, an essential step is signal denoising. In this paper, a generative adversarial network (GAN)-based denoising method is proposed to denoise the multichannel EEG signal automatically. A new loss function is defined to ensure that the filtered signal can retain as much effective original information and energy as possible. This model can imitate and integrate artificial denoising methods, which reduces processing time; hence it can be used for a large amount of data processing. Compared to other neural network denoising models, the proposed model has one more discriminator, which always judges whether the noise is filtered out. The generator is constantly changing the denoising way. To ensure the GAN model generates EEG signals stably, a new normalization method called sample entropy threshold and energy threshold-based (SETET) normalization is proposed to check the abnormal signals and limit the range of EEG signals. After the denoising system is established, although the denoising model uses the different subjects' data for training, it can still apply to the new subjects' data denoising. The experiments discussed in this paper employ the HaLT public dataset. Correlation and root mean square error (RMSE) are used as evaluation criteria. Results reveal that the proposed automatic GAN denoising network achieves the same performance as the manual hybrid artificial denoising method. Moreover, the GAN network makes the denoising process automatic, representing a significant reduction in time

Interoperability for Industrial Internet of Things Based on Service-oriented Architecture

The new Industry 4.0 envisions a future for agile and effective integration of the physical operational technologies (OT) and the cyber information technologies (IT) as well as autonomous cooperation among them. However, the wide variety and heterogeneity of industrial systems and field devices -especially on the factory floor - increase integration complexity. To address these challenges, new technologies and concepts such as the Industrial Internet of Things (IIoT), Service-oriented Architecture (SoA), Semantic Technologies, Machine Learning and Artificial Intelligence are being introduced to the industrial environment. In this paper, we focus on how industrial automation systems and field devices can be integrated into the IIoT framework and coordinated to adapt to dynamic operating environment. Specifically, this paper proposed an interoperability solution that makes use of SoA and Semantic Technologies to achieve supervised coordination of IIoT application systems. To illustrate the potential of this approach, the Service-oriented Architecture-based Arrowhead Framework is used as the fundamental framework for the implementation of the approach.acceptedVersio

An Experimental Study on the Effects of Environmental Education in China

In recent years, collaborative governance has been used as an innovative approach by government, NGOs, and business for consensus building in the process of policy making and service delivery (Ansell and Gash, 2008, Brown et al., 2006). However, little has been written on the psychological aspects of collaborative governance. What are the antecedents of collaborative decisions? To what extent and in what ways can NGOs’ advocacy impact community residents’ opinions? For example, in the field of environmental protection, the conflict between environmental conservation and economic development has been a key issue, which presents a fundamental challenge to the formation of collaborative environmental governance. Environmental NGOs have used educational approaches to influence key stakeholders; but it remains an intriguing issue as in what ways and to what extent their educational efforts have impacted these stakeholders. To answer these questions, we explored the attitudinal antecedents of collaborative governance by conducting an experimental study on the effects of environmental education in rural China. Specifically, we focus on two types of environmental education programs: Environmental Education (EE) and Education for Sustainability (ESD). While EE focuses on providing scientific education in raising environmental awareness, ESD incorporates economic, social, and environmental factors to bring about solutions to achieve sustainability. We found that ESD is more effective in stimulating attitudinal changes towards environmental conservation, and EE is more powerful in generating a hidden effect: the anti-development attitude, among participants in China. We also studied the moderating effects of economic pressure, place attachment, and we found that being poor and being nonlocal may strengthen a participant’s likelihood to develop attitudinal changes towards economic development. Overall, our research contributes to a better understanding of the psychological aspects of collaborative governance, and it calls a more balanced approach in environmental education

CONCEPTS AND AWARENESS ABOUT SELF-HARM AND SUICIDAL THOUGHTS AMONG HIGH SCHOOL STUDENTS CURRENTLY

The article focuses on understanding concepts and awareness of suicidal thoughts and self – harm behaviors based on quantitative and qualitative data. The quantitative database will be taken from a survey of high school students living and studying in Ho Chi Minh City. The qualitative database is taken from in-depth interviews focusing on teachers, parents, and students. The article presents the main results of the research. First, focus on the research basis including subjects, objects, and research methodology. Second, include views on suicidal thoughts and self-harm from many different perspectives, manifestations and causes of these behaviors, the prevalence of self-harm/suicidal thoughts, and consequences. Third, conclude and propose some recommendations to minimize the problem

Electroosmotic Flow in Microchannel with Black Silicon Nanostructures

Although electroosmotic flow (EOF) has been applied to drive fluid flow in microfluidic chips, some of the phenomena associated with it can adversely affect the performance of certain applications such as electrophoresis and ion preconcentration. To minimize the undesirable effects, EOF can be suppressed by polymer coatings or introduction of nanostructures. In this work, we presented a novel technique that employs the Dry Etching, Electroplating and Molding (DEEMO) process along with reactive ion etching (RIE), to fabricate microchannel with black silicon nanostructures (prolate hemispheroid-like structures). The effect of black silicon nanostructures on EOF was examined experimentally by current monitoring method, and numerically by finite element simulations. The experimental results showed that the EOF velocity was reduced by 13 ± 7%, which is reasonably close to the simulation results that predict a reduction of approximately 8%. EOF reduction is caused by the distortion of local electric field at the nanostructured surface. Numerical simulations show that the EOF velocity decreases with increasing nanostructure height or decreasing diameter. This reveals the potential of tuning the etching process parameters to generate nanostructures for better EOF suppression. The outcome of this investigation enhances the fundamental understanding of EOF behavior, with implications on the precise EOF control in devices utilizing nanostructured surfaces for chemical and biological analyses

Analyzing Post-Disaster Reconstruction Stakeholder Networks: Malaysian rural housing

This article uses the social network analysis to identify resource coordination and information exchange of stakeholders in the inter-organizational network by studying the project-related interactions of rural housing reconstruction in Temerloh, Pahang that were funded by the Malaysian government, His Majesty the King and NGO. The data was collected through content analysis and interviews with 23 government agencies, NGOs, and community stakeholders. Findings from the analysis established that government agencies had the highest actor centralities, with the Rural Development Ministry and the local government level being the most central among the government agencies, whereas the homeowners had the lowest centralities. Keywords: post-disaster housing reconstruction, social network analysis, rural Malaysia eISSN: 2398-4287 © 2023. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under the responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v8i23.4511