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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
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Karbala International Journal of Modern Science
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  This is an Open Access Journal Open Access journal
ISSN (Print) 2405-609X - ISSN (Online) 2405-6103
Published by Digital Commons Homepage  [8 journals]
  • Heterogeneous Resources in Infrastructures of the Edge Network Paradigm: A
           Comprehensive Review

    • Authors: Qusay S. Alsaffar et al.
      Abstract: The late 1990s saw the rise of the edge computing network paradigm, as well as an increase in the number of IoT de-vices. This concept is viewed as a link between cloud servers and end-devices, bringing processing and storage re-sources closer to clients. As a result of its low latency and high performance, researchers and developers have expressed interest in it. However, this paradigm confronts a number of obstacles and restrictions, including restricted and hetero-geneous resources at network edges. In this paper, we provide a detailed review of heterogeneous resources in edge network infrastructures using a three-dimensional method. These three dimensions in this concept correspond to the edge computer layers, hardware layers, and software layers of the edge network paradigm infrastructure ecosystem. This review considers Artificial Intelligence (AI), which classifies cutting-edge works into two categories: AI-based and non-AI-based solutions based on research issues such as fault tolerance, power consumption, resource utilization, re-source allocation, latency, device ID, clustering, heuristic-based, and meta-heuristic-based. Because reviews in this field rarely address full research concerns linked to this research topic. This review provides a sufficient overview to address the majority of open research questions. We examine and compare outstanding issues in AI-based and non-AI-based systems, focusing on evaluation metrics for meeting Quality of Services (QoS) and Quality of Experience (QoE) stand-ards. We expect that this evaluation will assist developers and researchers in determining the appropriate solution from research issues to achieve their objectives in building IoT technology and edge computing networks.
      PubDate: Thu, 13 Jun 2024 21:57:40 PDT
  • Classification and removal of hazy images based on a transmission fusion
           strategy using the Alexnet network

    • Authors: Roa'a M. Al_airaji et al.
      Abstract: Outdoor images are used in many domains, such as surveillance, geospatial mapping, and autonomous vehicles. The occurrence of noise in outdoor images is a widely observed phenomenon. They are primarily attributed to extreme natural and manufactured meteorological conditions, such as haze, smog, and fog. In autonomous vehicle navigation, recovering the ground truth image is essential, enabling the system to make more informed decisions. Accurate air-light and transmission map calculation is vital in recovering the ground truth image. An efficient approach for image dehazing that utilizes the mean channel prior (MCP) is presented in this paper to estimate the transmission map, followed by Gamma transformation to correct the transmission map obtained by MCP. This paper presents two novel contributions: first, an Alexnet network transfer model classification of hazy images as a preprocessing, and second, an efficient image dehazing based on an image fusion strategy. In the image dehazing stage, the transmission map estimated by the mean channel is altered with Gamma correction first. Then, the initial transmission map and its modified copy are combined using the weighted average fusion technique to retain the information in the initial transmission map. Additionally, the fused transmission map undergoes filtration using a guided filter to mitigate block and halo artifacts within the dehazed image. Lastly, the dehazed image is recovered using the improved transmission map by utilizing an optical scattering model. The proposed Alexnet network transfers algorithm significantly and decreases the quantity of training data required compared to the traditional classification algorithm. In addition, the network's classification accuracy can reach 98%. The proposed image dehazing showed better performance in terms of computational time, natural image quality evaluator (NIQE) index, peak-signal-to-noise ratio (PSNR), and structural similarity index (SSIM) than that of existing methods.
      PubDate: Thu, 13 Jun 2024 21:57:36 PDT
  • Designing of Human Serum Albumin Nanoparticles for Drug Delivery: a
           Potential Use of Anticancer Treatment

    • Authors: Ali Al-Ani et al.
      Abstract: Human serum albumin (HSA) nanoparticles have been widely used as versatile drug delivery systems for improving the efficiency and pharmaceutical properties of drugs. The present study aimed to design HSA nanoparticle encapsulated with the hydrophobic anticancer pyridine derivative (2-((2-([1,1'-biphenyl]-4-yl)imidazo[1,2-a]pyrimidin-3-yl)methylene)hydrazine-1-carbothioamide (BIPHC)). The synthesis of HSA-BIPHC nanoparticles was achieved using a desolvation process. Atomic force microscopy (AFM) analysis showed the average size of HSA-BIPHC nanoparticles was 80.21 nm. The percentages of entrapment efficacy, loading capacity and production yield were 98.11%, 9.77% and 91.29%, respectively. An In vitro release study revealed that HSA-BIPHC nanoparticles displayed fast dissolution at pH 7.4 compared to pH 3.4. They have also showed a higher cytotoxic activity against MCF-7 human breast cancer cells. The possible binding of the BIPHC into the tyrosine threonine kinase (TTK) was studied using molecular modeling. The findings of this study introduced a promising candidate model of HSA nanoparticles for delivering of BIPHC anticancer drug. These novel nanoparticles are characterized by their ability to carry a hydrophobic BIPHC agent and control drug release with improved targeting of breast cancer cells.
      PubDate: Sat, 08 Jun 2024 03:38:07 PDT
  • Modified Toulmin's Argumentation Model Based on Prior Experiences

    • Authors: Ali Hadi Hasan et al.
      Abstract: Our work focuses on the usefulness of previously stored correct extracted results, which form a sort of stored knowledge got from previous experiences, from enhancing Toulmin's argument model that deals with drug conflict problems in therapeutic diagnostics. New patients are entered using friendly user interface to store in files and then they are matched with the records of previous results, patients’ symptoms and histories datasets which also contain the correct best drugs extracted results. If the new entered record of a patient is matching with any previous record then the correct result of drug will be found immediately and displayed. Otherwise, it will enter for processing by the argument improvement of Toulmin's model that deals with conflicting problems in medicine based on Naive Bayes' theory. The symptoms of each disease are linked to its relevant treatment by using the inference rules which at last give rise to diagnosis of the appropriate treatment. Many competent features of each drug will either support or attack the drug and then a decision is made by employing the Naive Bayes technique based on the features of both the treatment and the patient as extracting results which will be stored to be validated by human experts. Datasets are gathered from some educational hospitals in Iraq and they have been approved by experts from the medical sector. The samples used in the proposed system cover 325 cases with two kinds of diseases and the average percentages of accuracy with them were 93.03% (hypertension) 95.125% (angina pectoris).
      PubDate: Sat, 08 Jun 2024 03:38:01 PDT
  • Synthesis of Dyes Sulfamidazole: Characterization, Evaluation, Molecular
           Docking and Global Descriptors by Density Functional Theory (DFT).

    • Authors: Athra G. Sager et al.
      Abstract: In the present work, novel azo compounds of sulfamidazole were created via the reaction of diazonium salt of sulfamidazole with several aromatic molecules including (resorcinol, 2-nitro phenol, 3-nitro phenol, and 4-nitro phenol)) (Z1–Z4). The new compounds (Z1-Z4) were identified using FTIR, 1HNMR techniques, in addition to melting point measurements. The biological activity of compounds (Z1-Z4) was studied against four kinds of bacteria including E. coli, Klebsiella pneumonia, Salmonella, and Staphylococcus aureus. The findings showed that all compounds (Z1-Z4) were active against the examined bacteria. Theoretical studies of the antibacterial ability of the prepared compound against DNA gyrase enzyme using MOE.2015 were performed. Also, studying their inhibition ability against tested bacteria in vacuum media was carried out theoretically. This was achieved using the DFT [6-311/ B3LYP+G (2d, 2p)] method.
      PubDate: Fri, 31 May 2024 16:57:22 PDT
  • Novel in situ synthesis of copper oxide nanoparticles in epoxy network:
           kinetics, composite mechanical and dielectric properties

    • Authors: Elena Bobina et al.
      Abstract: >Mechanical properties of polymer composites with dispersed nanoparticles (CDNP) depend on interaction between the nanoparticles and the polymer matrix. Strength of polymer composites significantly decreases when there is no interaction between dispersed nanoparticles and the polymer. This limits the application of functional polymer composites with dispersed nanoparticles. In this study, CDNP based on ED-20 epoxy resin with dispersed copper oxide nanoparticles was obtained.These nanoparticles were synthesized in epoxy resin before curing: the nanoparticles were obtained by decomposition of copper hydroxide by heating its solution in ED-20 resin.The kinetics of copper oxide nanoparticles formation in CDNP samples were studied using two independent methods: electron microscopy and dielectric spectroscopy.The results of these studies demonstrate that complete decomposition of copper hydroxide to polycrystalline copper oxide nanoparticles in a solution of copper hydroxide in epoxy resin occurs after 10 hours at 90оС. Nanoparticles were needle-shaped: the average length was 310 nm, the width was 80 nm.Copper oxide nanoparticles volume fraction in the samples after their exposure to high temperature for more than 10 hours was 0.28%. It was demonstrated that mechanical properties of epoxy-based polymer composite increased when the size of copper oxide nanoparticles decreased. After the complete transition of copper hydroxide into copper oxide nanoparticles, a significant increase in mechanical properties was observed. Flexural modulus increased from 3.4±0.2GPa(for the samples without nanoparticles) to 5.5±0.6GPa, the ultimate strength increased accordingly from 53.3±4 N/mm2 to 85±5 N/mm2. A two-fold decrease in ultimate strain should be noted: 1.5±0.1% compared to ED-20 epoxy resin-based polymer without nanoparticles.
      PubDate: Mon, 27 May 2024 00:57:29 PDT
  • ELM and LIGHTGBM: A Hybrid Machine Learning Technique with Intelligent IOT
           to Predict the cardiovascular disease

    • Authors: Gorapalli Srinivasa Rao et al.
      Abstract: Cardiologists can more accurately classify a patient's condition by performing an accurate diagnostic and prognosis of cardiovascular disease (CVD). The clinical diagnosis, and therapies processes within the medical field have been substantially accelerated by ML-based approaches enabled by IoT-based systems. This structure is based on IoT-based system with enabled ML approach. This study investigates an approach known as ensemble categorization, which enhances the precision of weak algorithms by integrating multiple classifiers. For effective CVD classification, we utilized Ensemble learning machine (ELM) and Light GBM. The appropriate traits are chosen to speed up the categorization process using the Gorilla Troops Optimizer technique. The investigation findings demonstrate that ensemble techniques are beneficial in improving the predictive ability of weak categorizers.
      PubDate: Mon, 27 May 2024 00:57:24 PDT
  • Analysing an imbalanced stroke prediction dataset using machine learning

    • Authors: Viswapriya Subramaniyam Elangovan et al.
      Abstract: A stroke is a medical condition characterized by the rupture of blood vessels within the brain which can lead to brain damage. various symptoms may be exhibited when the brain's supply of blood and essential nutrients is disrupted. To forecast the possibility of brain stroke occurring at an early stage using Machine Learning and Deep Learning is the main objective of this study. Timely detection of the various warning signs of a stroke can significantly reduce its severity. This paper performed a comprehensive analysis of features to enhance stroke prediction effectiveness. A reliable dataset for stroke prediction is taken from Kaggle website to gauge the effectiveness of the proposed algorithm. The dataset has a class imbalance problem which means a total number of negative samples is higher than a total number of positive samples. The results are reported based on a balanced dataset created using oversampling techniques. The proposed work used Smote and Adasyn to handle imbalanced problem for better evaluation metrics. Additionally, the hybrid Neural Network and Random Forest (NN-RF) utilizing the balanced dataset by using Adasyn oversampling achieves the highest F1-score of 75% compared to the original unbalanced dataset and other benchmarking algorithms.
      PubDate: Sun, 19 May 2024 21:42:23 PDT
  • Potential enhancement of microbial disinfection using oxygen enriched cold
           atmospheric-pressure argon (Ar/O2) plasma jet

    • Authors: Waleed O. Younis et al.
      Abstract: Oxygen activated cold-atmospheric-pressure-argon plasma jet (APPJ) has gained prominence over the regular argon plasma especially in disinfection and decontamination. As an objective of the current research, an oxygen-enriched argon system was built, where plasma produced through a vessel metallic tube that is introduced into alumina one. A sinusoidal high voltage signal of 25 kHz was used to generate plasma jet. Potential impact of oxygen enriched APP jet (Ar/O2) in decontamination of different microbial cells was observed. For examination, suspension of each tested microbe was placed in contact with plasma jet nearly 10 mm away from the jet nozzle and the lethal effect of activated plasma was evaluated. Results showed that the Ar/O2 -APP plasma enhanced reactive hydroxyl and other reactive oxygen species generation and hence, antimicrobial activities. For E. coli cells approximately 96.27% and 90.50% reduction in living cell count were recorded after 30 s of exposure to oxygen-activated plasma, on water and LB medium, with a D-value of 36.21 s and 588.24 s, respectively. Also, reduction in S. aureus cells was 92.8% and 96.6% after 30 s, with the D-values of 33.9 s and 181.8 s in water and LB media, respectively. Moreover, C. albicans fungal cells revealed 95% reduction in viable cell count after 10 s. However, the D-value showed only 6.3 s increase due to the impact of organic materials as a component of LB nutritive medium. Generally, the activated argon plasma works effectively even in the presence of organic debris in an exposed medium. Therefore, APPJ can be considered as a prominent straightforward technology for medication of diseases caused by antimicrobial drug-resistant pathogens.
      PubDate: Sun, 19 May 2024 21:17:56 PDT
  • A Potential of Watercress Nasturtium officinale Bioactive Compounds in
           Inhibiting Infectious Myonecrosis Virus (IMNV) by Targeting RNA-dependent
           RNA polymerase (RdRp) Virus from Several Countries: In Silico Approach

    • Authors: Qurrota A’yunin et al.
      Abstract: Infectious myonecrosis virus (IMNV) disease causes mass mortality and decreased shrimp production. The RdRp region projects to the interior, where it may function in transcription. The focus of this study was to determine the effect of amino acid polymorphisms from several countries on the structure of RdRp and identify the potential of watercress in inhibiting IMNV by targeting the RdRp protein of IMNV through an in silico approach. The results showed that the structure of the IMNV RdRp protein from Indonesia was similar to Mexico, and the protein structure from India_QDN was identical to India_QIL. Ligand binding affinity values showed that Rhamnetin 3-sophoroside in RdRp samples from Indonesia and India_QDN had the lowest values of -7.8 kcal/mol and -8.7 kcal/mol. Meanwhile, Rhamnazin 3-sophoroside had the lowest binding affinity value of -8.2 kcal/mol in RdRp protein samples from Mexico and India_QIL. The structure of the RdRp protein is still stable after interacting with rhamnetin and rhamnazin as indicated by the RMSD backbone value, ligand structure, and number of hydrogen bonds. Polymorphisms of amino acids from various countries have altered the structure of the RdRp protein of IMNV. The bioactive constituents in watercress N. officinale, specifically, rhamnetin and rhamnazin, have shown stable binding to RdRp protein. This suggests that the compound might inhibit the viral activity of the RdRp protein of IMNV from several countries.
      PubDate: Sun, 19 May 2024 21:07:49 PDT
  • Extraction of Morphometric Features the shape of mangrove leaves based on
           digital images and classification using the Support Vector Machine

    • Authors: Ishak Ariawan et al.
      Abstract: At present, several botanists still rely on the use of manual estimating methods to assess the carbon content in mangrove. However, these methods have been reported to be extremely time-consuming, showing the need to develop a system for prediction. An effective solution lies in the creation of an artificial intelligence application, which can provide rapid and cost-effective results. In constructing this application, careful consideration must be given to the selection of parameters or attributes. Species is an essential parameter for the assessment of carbon content, but its determination has proven to be challenging due to the similarities of mangrove. The occurrence of errors in identifying species can lead to inaccurate prediction in a given tree. To address this challenge, the identification process can be greatly improved by leveraging plant morphology, particularly leaf. Previous reports have shown that leaf exhibits distinctive morphological features, and the application of geometric mathematics proved instrumental in extracting these characteristics. Therefore, this study aimed to extract the shape of mangrove leaf images using morphometric features. Based on the features obtained, a classification was performed to identify mangrove species using a machine learning algorithm, Support Vector Machine (SVM). The results showed that the geometric method was effective in extracting values for roundness, solidity, eccentricity, convexity, compactness, elongation, rectangularity, and aspect ratio. The analysis of each feature showed that the roundness feature could be used to effectively distinguish the 4 mangrove species. Furthermore, the classification results using SVM obtained the highest average accuracy of 91.26%.
      PubDate: Sun, 19 May 2024 21:07:45 PDT
  • Removal of phenol from oilfield produced water using non-conventional
           adsorbent medium by an eco-friendly approach

    • Authors: Salem Jawad Alhamd et al.
      Abstract: Petroleum extraction generates substantial quantities of produced water, a challenge compounded by water scarcity in oil-producing regions, notably the Middle East. Leveraging produced water effectively, adhering to environmental standards, can offer a viable solution to the issue of water scarcity. This study explores the potential of mandarin peels as an available, cost-effective adsorbent for treating synthetic aqueous solution simulated to oil-field produced water, specifically targeting phenol, a dangerous pollutant. Employing a batch-mode adsorption unit, six operational factors—phenol concentration, acidity, agitation speed, contact time, adsorbent dose, and temperature—were investigated. Results revealed an inverse relationship between phenol removal and pH, concentration, and temperature, while direct correlations were observed with other variables. Mandarin peels exhibited notable phenol recovery, reaching a maximum efficiency of 74.43% at pH 1, 450 rpm agitation speed, 38 ppm initial concentration, 5 g dose, time of 180 minutes, and 20°C temperature. Isothermal and kinetic analyses favored the Langmuir and intra-particle diffusion models. Thermodynamically, the process proved exothermic, marked by low entropy, and spontaneous within the tested temperature range. Adhering to the zero residues level concept, exploring beneficial and safe disposal methods for contaminated residues led to investigating toxic mandarin peel residue as a rodenticide, displaying promising efficacy on laboratory albino rats. Consequently, this study proposes a sustainable approach, treating produced water laden with toxic pollutants using readily available agricultural waste while concurrently repurposing the toxic waste into an environmentally friendly material, aligning with the zero waste level concept.
      PubDate: Thu, 09 May 2024 01:52:21 PDT
  • A Comparative Analysis of Field Electron Emission from Carbon Black
           Embedded within Insulated Copper Hollowed Wires and Glass Tubes

    • Authors: Hatem A. Al-Braikat et al.
      Abstract: In this study, two different methods are used to investigate carbon black as a cold field electron emitter. The first method is to incorporate carbon black into a specially designed insulated copper hollowed wire. The wire has a cup-shaped structure created by electrochemical etching. The second method involves the incorporation of carbon black into narrow glass tubes. A Comparative analyses is carried out to evaluate the effectiveness of each method. To evaluate the performance of the samples, the current-voltage characteristics will be examined using field electron microscopes. This analysis will provide an understanding of the emission of the carbon black under different conditions. Furthermore, the obtained data will be are analysed and interpreted using Murphy-Good plots. Murphy-Good plots are a common graphical tool for measuring electron emission. The aim of this research is to identify the most effective and reliable techniques for the use the carbon black as a cold-field electron emitter. The research findings will contribute to the development of advanced electron emission technologies. They will also provide valuable information for the design and optimization of carbon black-based electron sources.
      PubDate: Tue, 30 Apr 2024 05:37:34 PDT

    • Authors: Haider. M. Umran et al.
      Abstract: Biaxial-oriented polypropylene (BOPP) films are characterized by unfavorable aging behavior because of their poor susceptibility to high temperatures, humidity, and high electric fields. This makes them unqualified to withstand harsh operating conditions, such as in capacitor applications. This study investigates the impact of annealing BOPP samples at 100 °C for five hours after fluorination at different times (15, 30, and 60 minutes) on their electrical and mechanical performance under electro-thermal stresses. Scanning electron microscope (SEM) images confirm that there is an increase in surface roughness and the formation of a dense layer of fluorine-containing groups monotonically with fluorination time. So, these roughness increases can probably change the electrical properties of the film. Based on the isothermal surface potential decay (ISPD) technique, the treated samples show slower surface potential decay than the original sample. Compared to 54% for the original sample, the surface potential remains at approximately 87.6% of its initial value after 7200 s. During aging, Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) analysis revealed changes in the surface chemical composition and crystallinity development, respectively. The treated samples show improved aging behavior in terms of a lower dissipation factor and AC conductivity compared to the original sample. In the dynamic mechanical analysis (DMA), it was demonstrated that the strong polar bonding of C-F integrated into the polymer chain enhanced film mechanical performance.
      PubDate: Sun, 28 Apr 2024 21:17:55 PDT
  • One-Pot Synthesis Green Zinc Oxide Nanoparticles immobilized on Activated
           Carbon derived from Pineapple Peel for Adsorption of Pb(II)

    • Authors: Vienna Saraswaty et al.
      Abstract: The current study introduces a one-pot technique for synthesizing an environmentally benign and cheap composite adsorbent, namely ZnO-PPAC, for the adsorption of Pb(II). The designated adsorbent was prepared by incorporating green synthesized zinc oxide (ZnO) nanoparticles on activated carbon-derived from pineapple peel. The prepared adsorbents were characterized using XRD, SEM, EDS, FTIR, and BET techniques. The XRD pattern verifies that the ZnO was successfully synthesized and immobilized onto the PPAC in a one pot synthesis system. The surface areas of ZnOPPAC and PPAC adsorbents were 13.62 m2/g and 961.96 m2/g, respectively. The FTIR evaluation of the ZnO-PPAC adsorbent revealed several characteristic absorption peaks corresponding to -OH groups, C-O groups, C=C groups, C-N groups, and M-O groups. It was revealed that the adsorption of Pb(II) on the ZnO/PPAC adsorbent would not require any pH adjustment. The adsorption kinetics demonstrated that the adsorption of Pb(II) ions on PPAC and ZnO-PPAC better fitted pseudo-second-order kinetics (R2 = 0.999, both for PPAC and ZnO/PPAC) and followed the Freundlich model (R2 = 0.989 and 0.987 for PPAC and ZnO/PPAC adsorbent). According to the Freundlich model, the adsorption of Pb(II) ions onto the designated adsorbents involves a multilayer process. The maximum adsorption capacities of ZnO/PPAC and PPAC were calculated as 769 mg/g and 667 mg/g, respectively. Thermodynamic analysis indicated an exothermic and spontaneous nature, as suggested by the negative values of ΔHº and ΔGº. In summary, both the prepared adsorbents greatly exhibited a high adsorption capacity of Pb(II) ions that can be used for environmental remediation.
      PubDate: Mon, 22 Apr 2024 00:52:31 PDT
  • Antioxidant Properties of Kombucha Beverage Infused with Ganoderma lucidum
           and Green Tea from Camellia sinensis (L.) Kuntze with Several Fermentation

    • Authors: Rizki Rabeca Elfirta et al.
      Abstract: Kombucha is a functional beverage produced through the fermentation of infused tea or Camelia sinensis (L.) Kuntze (CS) by a symbiotic culture of bacteria and yeast. Apparently, the substrate of kombucha can be substituted to enhance its functional properties. Ganoderma lucidum (GL) is a potential substrate reported to have health benefits. This study aims to evaluate antioxidant properties by comparing different formulations and fermentation times. The formulations prepared in the present study varied in the compositions of GL and CS substrates, namely F1 (100% GL), F2 (75% GL: 25% CS), F3 (50% GL: 50% CS), F4 (25% GL: 75% CS), and F5 (100% CS). The kombucha beverages were fermented for several fermentation times, including 8, 11, 14 and 17 days. The antioxidant activity was evaluated using the free radical scavenging activity of DPPH and the FRP assay. Total phenolics, total flavonoids, and total acids were also determined to support the antioxidant properties, employing the Folin Ciocalteu method, Dowd method, and titration, respectively. Antioxidant activity, total phenolics, and total flavonoids were observed to decrease with the addition of GL substrate, with F5 being identified as the optimum formula based on antioxidant properties. In contrast, total acids were found to increase with an increasing proportion of GL substrate. The use of GL substrate did not prove to enhance the antioxidant properties of kombucha, although a well-produced kombucha beverages continued to be yielded by the fermentation process. Further research should be conducted to evaluate other functional properties of kombucha beverage using GL substrate.
      PubDate: Thu, 29 Feb 2024 23:52:40 PST
  • Overview of The Zoonotic Potential and Coinfection of SARS-CoV-2 in

    • Authors: Muhammad Khaliim Jati Kusala et al.
      Abstract: In the ASEAN region, Indonesia has the highest overall COVID-19 infection score. The SARS-CoV-2 pandemic first emerged in China and then transmitted sporadically throughout the world. Animals and humans can be infected with the corona virus, so this disease is classified as a zoonotic disease. This review aims to gather information regarding the potential of SARS-CoV-2 as a zoonotic disease and coinfections with several other pathogens in Indonesia. This study collected data demonstrating the potential for COVID-19 to be transmitted from humans to animals, as an evidenced by positive test results for the Bat Coronavirus Antigen in bats. Cats have also been confirmed to carry SARS-CoV-2. Tests conducted on dogs and cats in Indonesia revealed the presence of SARS-CoV-2 antibodies in their body. SARS-CoV-2 coinfection with several pathogens, including H. influenzae, S. pneumoniae, Dengue virus, S. aureus, Acinetobacter baumannii, Influenza A, Influenza B, Adenovirus, K. pneumoniae, Mycobacterium tuberculosis, Human Immunodeficiency Virus (HIV), Salmonella thypi and Malaria has been documented in several Indonesian regions. The lack of research data in Indonesia render difficult a comprehensive understanding of the zoonotic potential involving various animal species and coinfection with other pathogens.
      PubDate: Thu, 29 Feb 2024 23:52:36 PST
  • Investigations of the Eutectic Formation and Skin Rejuvenation by
           Hyaluronan - Kojic Acid Dipalmitate System

    • Authors: Syed Waqar Hussain Shah et al.
      Abstract: Eutectic phenomenon has been investigated in binary system based on biopolymer hyaluronan (HN) and kojic acid dipalmitate (KAD). Solid-liquid phase diagram showed a significant dependence of melting points on weight fraction of KAD up to KAD < 0.5. A negligible regain to melting temperature of pure KAD occurred later. Simulations of molecular mechanics using a four-unit segment of HN and KAD revealed the interaction between carbonyl of KAD with 4-OH on N-acetylglucosamine unit of oligomer. Infrared vibrational spectroscopy also endorsed the existence of a weakly interacting system. Such behavior was expected due to steric hinderance and rigidity of biopolymer. The thermal decomposition temperature of HN (i.e., 215 °C) was increased to 322 °C in HK50 having HN and KAD in 1:50 w/w. Bioelectric impedance analysis revealed that these green materials could promote skin health in humans.
      PubDate: Thu, 22 Feb 2024 23:02:32 PST
  • Synthesis and Characterization of Renewable Heterogeneous Catalyst ZnO
           Supported Biogenic Silica from Pineapple Leaves Ash for Sustainable
           Biodiesel Conversion

    • Authors: Nadila Pratiwi et al.
      Abstract: This study reports on the first case of the low-cost and environmentally friendly ZnO/SiO2 heterogeneous catalyst from pineapple leaves ash (PLA). Catalyst shows excellent performance in catalyzing the transesterification of waste cooking oil (WCO) with methanol for biodiesel conversion. This study focuses on assessing the influence of Zn content on physicochemical characteristics, using XRD, FTIR, SEM, and N2 adsorption-desorption methods. In addition, three different Zn content levels (20, 25, and 30 %wt) were applied. The results showed that all ZnO/SiO2 samples exhibited characteristics suitable for use as catalyst with an average crystallite size of 31.83-34.15 nm, and a surface area of 88.97 m2/g to 93.41 m2/g. Importantly, the sample shows efficient catalytic activity for conversion of biodiesel from WCO with the largest conversion using a ZnO/SiO2-30 catalyst of 96.17% with the carbon chain of C12-C20. The optimum reaction conditions used 3 g of ZnO/SiO2-30, reaction time 6 hours at 57.5 oC and WCO to methanol ratio of 3:1 with a yield of 98.62%. The resulting catalyst has extraordinary durability up to sixth cycles. It shows that the material has the potential to be a renewable catalyst from sustainable resources. The ZnO/SiO2 catalyst production using PLA for biodiesel production from WCO represents the potential for using agricultural waste into valuable materials in future energy.
      PubDate: Thu, 22 Feb 2024 23:02:29 PST
  • Butterworth filter to reduce reactivity fluctuations

    • Authors: Daniel Suescún-Díaz et al.
      Abstract: In this study, we introduce the calculation of reactivity in nuclear reactors. The proposed method uses the Euler-Maclaurin series to approximate the integral in the inverse equation of point kinetics. The approximation is done with the first three terms, the first term represents the approximation of a zero-order sum, the second term the trapezoidal rule and the third term the first Bernoulli number. These three terms improve the approximation, along with an estimate of the neutron density using the prompt jump approximation. To reduce neutron density fluctuations, a second-order Butterworth filter for the reactivity calculation was implemented, which offers the advantage of minimal delay based on only three data points. Whereas the methods reported in literature that consider noise in the neutron population, it is necessary to consider a much higher number of 225 samples, as in the case of the Savitzky-Golay filter and the first order delay low-pass filter. These filters reduce fluctuations in the calculation of reactivity but with a longer delay. To assess the accuracy of these enhancements a comparison was done for results obtained with different numerical simulations using a filter based on least squares fitting, varying the data window, the time step and fixing a polynomial of order d, using physical parameters for thermal reactors. The results of the numerical simulations indicate that the proposed method can be used to calculate the reactivity with high precision and with a high reduction of fluctuations by applying the Butterworth filter when the noise level increases.
      PubDate: Thu, 15 Feb 2024 04:27:25 PST
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School of Mathematical and Computer Sciences
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