Cosmos Scholars Publishing House: Journals Management System
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Towards a Strategy for Designing Sustainable Zero-Energy Buildings Using Building Information Modeling (BIM)
Get PDFEnvironmental studies and reports have indicated the threat to the environment and their repercussions on humanity. The urgent need has emerged for creative ideas to work on confronting these dangers, and therefore calls have been raised to create a sustainable approach in all sectors. This resulted in the emergence of modern and advanced technologies in project management, which is an important stage for the transition to a more prosperous future in the world of construction, the most important of which is the Building Information Modeling (BIM) technology, which constitutes a radical transformation in the field of engineering projects, which means designing a model of the building, including all its information and data. The research aimed to develop a specific strategy for designing sustainable zero-energy buildings using Building Information Modeling (BIM). The research adopted the analytical approach and the case study approach by analyzing the theoretical ideas related to the concept of building information modeling technology and integrating the sustainable design strategy with this technology and achieving zero-energy buildings. The research study aims to integrate sustainable design strategies and concepts into BIM technology and harness the potential of BIM technology in facilitating sustainable design solutions to achieve zero-energy buildings. Methods for choosing the best methods to achieve zero architecture and the effect of building materials, thermal insulation, and type of glass on the thermal performance of the residential building in the hot dry climate, especially in the Greater Cairo region. Study of Sakan Masr units for workers’ housing in the New Administrative Capital, using the computer and simulation programs. This part studies the effect of different building materials, thermal insulation, and types of glass on energy efficiency in residential buildings
Role Of In- Situ Rutin Flavonoid Consisted Myristica Fragrans Silver Nano Particles (MF-Ag-Nps) Against Escherichia Coli and Bacillus Subtilis
Get PDFMost microbiological growth inhibitors are toxic and chemical solvents are harmful for human health. Copper, silver, and gold metallic nanoparticles have several uses in biotechnology and medicinal research. MF-Ag-NPs(silver nanoparticles)are potent anti-inflammatory, anti-proliferative, and anti-microbial agents. The purpose of this study was to biogenically generate silver nanoparticles by extracting rutin from nutmeg, a seed from the Myristica fragrans plant. In order to create Myristica fragrans MF-Ag-NPs, silver nitrate was dissolved in the extract. The transformation of the colour from dark brown to pale brown confirmed the conversion of Ag+ to Ag°. FTIR, EDX, and SEM were used to describe them. Images from scanning electron microscopy demonstrate the presence of silver nanoparticles between 20 and 300 nm in size. The presence of oxygen and silver, as well as the metal's oxidation state, were confirmed by EDAX analysis. The nanoparticles' distinctive functional groups were discovered using FTIR spectroscopy. The antibacterial activity of Myristica fragrans seed extract was assessed. The extract from the seeds of Myrsitica fragrans exhibited the strongest antibacterial properties. These findings imply that antibacterial MF-Ag-NPs phyto-formulated with nutmeg extracts might be used to treat microbial infections in the future
Role of Deep Learning in Diagnosis, Treatment, and Prognosis of Oncological Conditions
Get PDFDeep learning, a branch of artificial intelligence, excavates massive data sets for patterns and predictions using a machine learning method known as artificial neural networks. Research on the potential applications of deep learning in understanding the intricate biology of cancer has intensified due to its increasing applications among healthcare domains and the accessibility of extensively characterized cancer datasets. Although preliminary findings are encouraging, this is a fast-moving sector where novel insights into deep learning and cancer biology are being discovered. We give a framework for new deep learning methods and their applications in oncology in this review. Our attention was directed towards its applications for DNA methylation, transcriptomic, and genomic data, along with histopathological inferences. We offer insights into how these disparate data sets can be combined for the creation of decision support systems. Specific instances of learning applications in cancer prognosis, diagnosis, and therapy planning are presented. Additionally, the present barriers and difficulties in deep learning applications in the field of precision oncology, such as the dearth of phenotypical data and the requirement for more explicable deep learning techniques have been elaborated. We wrap up by talking about ways to get beyond the existing challenges so that deep learning can be used in healthcare settings in the future.  
Green Synthesis, Characterization, and Assessment of Iron Oxide Nanoparticles' Antibacterial Activity Using Blumea lacera Root Extract
Get PDFIron and copper nanoparticles produced through green methods underwent analysis using UV-visible absorption spectrophotometry, X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and EDS. Findings indicated that iron oxide nanoparticles displayed an irregular spherical shape, with sizes ranging from 15.73 nm to 32.37 nm. The antimicrobial efficacy of iron and copper oxide nanoparticles synthesized through green techniques was evaluated against four bacterial strains causing human diseases. Results showed that these nanoparticles exhibited the highest antibacterial activity at a concentration of 20 mm/disc, while their effectiveness was lowest at 13 mm/disc concentrations. This study underscores the potential of iron and copper oxide nanoparticles produced via environmentally friendly methods to serve as antibacterial agents
Guided Waves in the Optical Carbon Nanotube Wave Guide
Get PDFThe cylindrical carbon nanotube is an optical wave guide in which the monochromatic guided wave propagates and formulated by Maxwell’s wave equations that described by the components of the electric and magnetic fields with different modes. The roots of wave equation are obtained as Bessel’s functions that explain the characteristics of guided wave in the carbon nanotube with phase components. The transverse electric and magnetic fields in linearly polarized waves are parallel and orthogonal over cross section. The normalized propagation function is found with the normalized frequency parameters for the lower order of modes. The guided mode as linearly polarized modes of electromagnetic wave with the axial conductivity and the propagation frequency in the carbon nanotube
Experimental Study of Adobe Type Vernacular Structures Under Dynamic Loading
No full textThe experimental analysis was carried out to understand the effect of earthquake resistant features on the behaviour and damage or failure pattern of adobe and concrete masonry structure under earthquake or dynamic force. To attain this objective two series of tests were performed: A material testing programme for reduced scaling of material and Shake table testing programme for dynamic testing on 6 reduced scale masonry house models (3 from adobe brick masonry and another 3 from concrete brick masonry). 3 models can distinguish as a simple reduced scale masonry structure with no extra or additional features, a similar masonry structure aided with horizontal RC (reinforced concrete) bands at sill, lintel and roof level as earthquake resistant feature and a similar masonry structure aided with horizontal RC (reinforced concrete) bands at sill, lintel and roof level and vertical Aluminium containment reinforcement as earthquake resistant features. After testing it is concluded that masonry structure aided with horizontal EQ (Earthquake). bands and vertical containment reinforcement shows more ductile behaviour which avoids life-threatening collapse of structure
Membranes Targeting Industrial O2 Production from Air – A Short Review
Get PDFAbstract: Some of the most promising membranes for O2/N2 gas separation (air separation) mentioned in literature so far are selected, in terms of meeting a O2-gas-production breakeven cost that is lower than that of competing air separation unit (ASU) technologies, based on latest reported technoeconomic studies. An overview regarding most important applications of O2 and N2 gases is first given, in respect with the demanded purity limits for each case, since the purity parameter is crucial in defining the minimum breakeven cost.
Keywords: oxygen production; air separation technologies; membrane technology; industrial O2 production processes
Antibiotic Resistance in the Vibrio species isolated from the estuarine sediments of Uttara Kannada Karnataka
Get PDFVibrio species are the marine pathogenic bacterium which causes the health issues in the infected organisms. Antibiotic resistance in the Vibrio species is the threat to the human health by the transfer of the resistant gene in the human from the food chain. The present study was carried out to isolate the Vibrio species and to study antibiotic resistance from the sediments of two estuaries Kali and Aghanashini from Uttara Kannada, Karnataka. The sampling was done during low tide for the period of ten months from September 2021 to June 2022. The total vibrio count was observed in range between 3.86 to 4.83 Log X101 CFU/g. Vibrio parahaemolyticus, Vibrio alginolyticus, Vibrio navarrensis and Vibrio vulnificus were isolated and identified from the sediments. The identified Vibrio species were resistant to ampicillin and sensitive to chloramphenicol and tetracycline. Due the over use of antibiotics in the aquaculture and mariculture activities there is a possibility of organism to show multiple resistance towards the antibiotics
Pure Electric Vehicle using Hybrid Energy Storage System
Get PDFThe improvement of energy storage capability of pure electric vehicles (PEVs) is a crucial factor in promoting sustainable transportation. Hybrid Energy Storage Systems (HESS) have emerged as a promising solution to address the energy storage limitations of PEVs. HESS combines two or more energy storage devices with complementary characteristics to optimize the power and energy density of the system. The use of HESS in PEVs allows for efficient energy management, reducing the overall weight, cost, and volume of the system while improving its performance. Additionally, HESS can be integrated with advanced energy management systems to further optimize the energy consumption of the vehicle. This paper reviews the use of HESS in PEVs and its potential to improve the energy storage capability of these vehicles. It discusses the advantages of using HESS, such as reducing the battery size and improving the energy efficiency and driving range of the vehicle. The paper also presents several studies that demonstrate the effectiveness of using HESS in PEVs, especially when combined with energy-saving strategies. The results of these studies show that HESS has the potential to significantly improve the performance of PEVs, which can help to accelerate the adoption of EVs and promote sustainable transportation
Prediction of Purchase Intention for Medical Cannabis Products: Case Study in Medellín Colombia
Get PDFThis article provides information on the level of acceptance of medical cannabis, the intention to use it and the factors involved in the decision-making process of individuals. Despite the studies developed for the use of medicinal cannabis, it has some difficulties to enter the market due to existing prejudices as a recreational drug. In order to provide valuable information to make the right decisions and generate marketing strategies, the relationships between the use of medical cannabis and the Theory of Planned Behavior in the purchase and consumption decision are explored using factor analysis techniques, and relevance analysis. Besides, a purchase intention prediction model based on machine learning is proposed. The results show that the dimensions ”attitudes” and ”perceived behavioral control” have a positive and statistically significant relationship with consumption and purchase. The purchase intention prediction model achieved a performance with an accuracy greater than 94%