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With the growth of global energy demand and the pressure of environmental protection, ocean energy has received widespread attention as a clean and sustainable form of energy. The purpose of this paper is to analyze various forms of ocean energy, explore its working principles, power generation technologies and application potential, and evaluate its research progress on a global scale. This paper details the working principle and power generation technology of ocean current, tidal, wave, temperature difference and salt difference energy. Especially in terms of salt differential energy, this paper analyzes the key role of permeable membrane technology and the large-scale production of low-cost special membranes. The analysis shows that countries have made significant progress in research in the field of ocean energy, especially in ocean current energy and tidal energy. China has also made breakthroughs in ocean current, wave and temperature difference energy. In short, ocean energy has great potential for development as a clean and sustainable energy source. Future development trends will focus on improving power generation efficiency, reducing costs, and reducing ecological environmental impact. As technology advances and costs fall, ocean energy is expected to occupy a more important position in the global energy system. [ABSTRACT FROM AUTHOR]

Health and medicine has gained a lot of importance in today's digital world, where evolving technology is being used to fight against almost all the known diseases thoroughly. But, according to reports, more than two lakh people in China and one lakh in United States of America are dead every year due to the mistakes made while prescribing errors. This paper aims to propose a system which takes as input the symptoms from the patient to predict the disease, which is followed by recommending the correct medicine. This system consists of database system module where disease dataset contains attributes like "DiseaseID", "Disease", "Symptoms" and "count of occurrences" and drug dataset has additional attributes such as "drug" and "drug_rating". In the data preparation module, a new data frame is created where each disease with its associated symptom is given "1" and "0" if it is not the symptom related. After all these steps of preprocessing are performed on the raw dataset, the dataset is now ready to be acted upon by a machine learning algorithm. Models like Decision Tree, Random Forest and Naive Bayes were applied on the training-dataset. Entire knowledge database was fitted in models and it was seen if not much dataset is used Random Forest And Naïve Bayes classifiers showed 84% accuracy whereas Decision Tree gives 92%. But Random Forest also gives accuracy similar to Decision Tree for large dataset. Hence for disease prediction we use Decision Tree. The recommendation is done on the basis of the rating of the drug. After this, only the drug with the highest rating is included in a newly formed dataset and the rest of the drugs are ignored. The system is implemented for user access by making use of Tkinter a python GUI Library for constructing the desktop end user interface. This paper deals with the design and implementation of a system which performs the function of prediction of diseases and the recommendation of medicines, which adds to the capabilities of the present systems in health infrastructure. [ABSTRACT FROM AUTHOR]

The United States and China are strong trading partners of Malaysia, with about 23% of total exports in 2017. Therefore, the trade war pressures since 2018 between the United States and China have affected the Malaysian economy. Thus, this paper aims to analyse the effects of the war on the Malaysian stock market using a threshold network approach. Then, the networks examine the changes of important stocks before, during and after the trade war in which the periods are taken from 16th March 2017 until 31st May 2021. The important stocks are determined by four standard centrality approaches, namely degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. This paper uses 240 companies of the FTSE Bursa Malaysia Emas Index to create the Malaysian stock market networks. The results show that Dagang Nexchange Berhad and Jaya Tiasa Holdings Berhad have higher connectivity with other stocks during the turmoil period and after the turmoil period respectively. Besides, Dagang Nexchange Berhad acts as the most important stock according to all centrality measures. The findings of this study give an insight to the government regulators and investors with information regarding the current topological structure of Malaysia's stock market. [ABSTRACT FROM AUTHOR]

Acrylonitrile Butadiene Styrene (ABS) is a tough, long-lasting substance which have high tolerance toward high-temperature that are suitable for filament fabrication. ABS is known to be perfect for 3D printing due to low melting point and facile to utilize. In this work, the temperature processing parameter (220 to 270°C) of ABS (from China) filaments for Fused Filament Fabrication (FFF) by using the Desktop Filament Extruder machine was studied. The printed specimens were fabricated according to ASTM standards for tensile test (D638) and Izod impact test (D256). From the findings, the filament of 3D printers were successfully fabricated at temperatures of 220 °C, 230 °C, and 240 °C. The sample were tested on mechanical characteristics, given tensile strength, elastic modulus, impact strength and impact energy of 40.146 MPa, 1691.12 MPa, 11.01 kJ/m2, and 1.84 J, respectively. The findings indicate that the strongest filament are the one that produce at extrusion temperature of 220 °C. For the better understanding in future research, this paper concluded proof of the variety of ABS pellets can be designated as an extruded filament fabrication. [ABSTRACT FROM AUTHOR]

An original infection has spread over the global village in form of pandemic and the regular lifestyle of human beings got stuck with misfortunes. As it has been declared by the global organization of health sector namely WHO, this Covid got initiated from southern city of China during the last weeks of the year 2019. Based on the multiple observations, it was declared as most infectious as well contagious spread through wind or by coming in close contact with a tainted individual. Various methods have been implemented to cease off the fast spreading infectious disease. For example, keeping a social separation, that is to say, keeping a legitimate actual separation among individuals and reducing close contact with one another, and wearing a facial covering to stay away from the beads that are passed by means of wind air. Consequently, this paper put forth the observation made to explore the initiatives for maintaining physical distance in the public domain and to identify whether a Face Mask is worn or not. The architectural framework provides the exact location and position of an object along with an acknowledgment about facial coverage as per the WHO norms under the moving images of the persons who are into public domain. Our suggested model implements the existing procedures such as dual shot face detector, You look only once and finally ResNet algorithms. Irrespective of the origin location of an individual and their interaction among themselves taking into consideration the space between them and the facial expressions in a continuous form were recognized. A general outcomes dashboard has displayed the result composing the measures with regard to the abuses of an individual person and breaking the protocol of maintaining separate distance measures. Subsequent to carrying out and conveying the procedures of process, the above said exploration model accomplished an accuracy of maximum performance. Subsequently, this exploration project had come up with demonstrated realities that maintaining physical distance along with the usage of facial mask decreases the escalation of the disease, which lead to consequently constructs a procedures to assist with identifying the mentioned actions. [ABSTRACT FROM AUTHOR]

Construction industry as one of the sectors that causes climate change must start paying attention to environmental impacts. Through the provision of numerous ecosystem services, Green infrastructure (GI) is one of the essential strategies for achieving sustainable development since it can effectively coordinate social, economic, and environmental growth. Thus, GI has been highlighted as a promising strategy to aid cities in adapting to climate change. 197 papers published between 2016 and 2021 were organized and classified using the 7th version of Publish or Perish software as part of this study's literature review methodology. Results show that there has been a significant growth in research on green infrastructure in recent years, with Sustainability Journal dominating the field. The initial top three cited journals that cover GI research are China Earth Sciences, Construction & Building Materials, and Cities. Another set of findings reveals that issues with water, materials, heat, air pollution, and policies-regulation & cost have been particularly focused on. Future research is needed and quite promising, such as: green materials, solutions to water & flood problems, urban heat, and GI regulation are topics that need further research, especially in Indonesia. [ABSTRACT FROM AUTHOR]

Globally, pesticide use continues to rise, estimated to be over four million tonnes yearly. In 2020, it was almost 2.7 million metric tons, up 57% from 1990. Nanotechnology is an innovative and exciting technology that offers new nanoscale molecule designs, formulations, and delivery systems to diminish the hazardous pesticide effects. Many studies on nano-pesticide production have been published, whereas nano-biopesticides are still limited. The purpose of this research is to answer the question of whether nano-biopesticide formulations will emerge along the development of nano-pesticides. The research was conducted by using bibliometric analysis. All nano-pesticide and nano-biopesticide-related publications are extracted from the Scopus with no limitations year. Using VOSviewer, data on research scope, authorship contributions, number of citations, and global research trends are evaluated and mapped. The results show that the publishing of nanoparticles has an exponential trend, with 125 nano-pesticide documents. However, only 14 nano-biopesticide documents are available. India is the most productive country, publishing both nano-pesticides and biopesticides articles, 52 and 9 publications. India connects the Australian and European continents regarding nano-pesticide publications. China is next, with 36 articles about nano-pesticides currently published. Al-Whaibi (average of 86 citations) and Iavicoli have extremely high citation counts (average of 125.5 citations). In synthesizing nano-biopesticide formulations, we found that essential oils are the most common ingredient in nano-biopesticides. In future, the topic related to the impact of nano-biopesticides on crop production and resistance; the combination of nano-biopesticides and nano-fertilizers; the study of nano-biopesticides' effects on the environment; and microbial as nano-biopesticides are some trend in the nano-biopesticide formulation. We predict that research on nano-biopesticides will increase rapidly in the context of eco-friendly issues. Finally, this paper can serve as a basis for the upcoming research on nano-biopesticide formulations, particularly those involving microorganisms as bioactive substances. [ABSTRACT FROM AUTHOR]