Search results for: statistical techniques

Authors: Ben Nadler

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Cell adhesion plays a vital role in many cell activities. The motivation to model cell adhesion is to study important biological processes, such as cell spreading, cell aggregation, tissue formation, and cell adhesion, which are very challenging to study by experimental methods alone. This study provides important insight into cell adhesion, which can lead to improve regenerative medicine and tissue formation techniques. In this presentation the biological cells adhesion is mediated by receptors–ligands binding and the diffusivity of the receptor on the cell membrane surface. The ability of receptors to diffuse on the cell membrane surface yields a very unique and complicated adhesion mechanism, which is exclusive to cells. The phospholipid bilayer, which is the main component in the cell membrane, shows fluid-like behavior associated with the molecules’ diffusivity. The biological cell is modeled as a fluid-like membrane with negligible bending stiffness enclosing the cytoplasm fluid. The in-plane mechanical behavior of the cell membrane is assumed to depend only on the area change, which is motivated by the fluidity of the phospholipid bilayer. In addition, the presence of receptors influences on the local mechanical properties of the cell membrane is accounted for by including stress-free area change, which depends on the receptor density. Based on the physical properties of the receptors and ligands the attraction between the receptors and ligands is modeled as a charged-nonpolar which is a noncovalent interaction. Such interaction is a short-range type, which decays fast with distance. The mobility of the receptor on the cell membrane is modeled using the diffusion equation and Fick’s law is used to model the receptor–receptor interactions. The resultant interaction force, which includes receptor–ligand and receptor–receptor interaction, is decomposed into tangential part, which governs the receptor diffusion, and normal part, which governs the cell deformation and adhesion. The formulation of the governing equations and numerical simulations will be presented. Analysis of the adhesion characteristic and properties are discussed. The roles of various thermomechanical properties of the cell, receptors and ligands on the cell adhesion are investigated.

Keywords: cell adhesion, cell membrane, receptor-ligand interaction, receptor diffusion

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Authors: Aldé Belgard Tchicaya Loemba, Baraka Kichonge, Thomas Kivevele, Juma Rajabu Selemani

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Plants used for medicinal purposes are extremely perishable, owing to moisture-enhanced enzymatic and microorganism activity, climate change, and improper handling and storage. Experiments have shown that drying the medicinal plant without affecting the active nutrients and controlling the moisture content as much as possible can extend its shelf life. Different traditional and modern drying techniques for preserving medicinal plants have been developed, with some still being improved in Sub-Saharan Africa. However, many of these methods fail to address the most common issues encountered when drying medicinal plants, such as nutrient loss, long drying times, and a limited capacity to dry during the evening or cloudy hours. Heat pump drying is an alternate drying method that results in no nutritional loss. Furthermore, combining a heat pump dryer with a solar energy storage system appears to be a viable option for all-weather drying without affecting the nutritional values of dried products. In this study, a solar-assisted heat pump dryer integrated with thermal energy storage is developed for drying moringa leaves. The study also discusses the performance analysis of the developed dryer as well as the proximate analysis of the dried moringa leaves. All experiments were conducted from 11 a.m. to 4 p.m. to assess the dryer's performance in “daytime mode”. Experiment results show that the drying time was significantly reduced, and the dryer demonstrated high performance in preserving all of the nutrients. In 5 hours of the drying process, the moisture content was reduced from 75.7 to 3.3%. The average COP value was 3.36, confirming the dryer's low energy consumption. The findings also revealed that after drying, the content of protein, carbohydrates, fats, fiber, and ash greatly increased.

Keywords: heat pump dryer, efficiency, moringa leaves, proximate analysis

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Authors: I. Kamika, S. Azizi, M. Tekere

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Nanotechnology promises significant improvements of advanced materials and manufacturing techniques with a vast range of applications, which are critical for the future competitiveness of national industries. The manipulations and productions of materials, whilst, controlling the optical properties and surface area to a nanosize scale enabled a birth of a new field known as nanotechnology. However, their rapidly developing industry raises concerns about the environmental impacts of nanoparticles, as their effects on functional bacterial community in wastewater treatment remain unclear. The present research assessed the impact of cerium Oxide nanoparticles (nCeO) on the bacterial microbiome of an activated sludge system, which influenced its performance of this system on nutrient removal. Out of 15875 reads sequenced, a total of 13133 reads were non-chimeric. The wastewater samples were more dominant to the unclassified bacteria (51.07% of bacteria community) followed with the classified bacteria (48.93). Proteobacteria was the most dominant phylum in both classified and unclassified bacteria, whereas 18% of bacteria could even not be assigned a phylum and remained unclassified suggesting hitherto vast untapped microbial diversity. The bacterial operational taxonomic units (OTUs) ranged from 1014 to 2629 over the experimental period. The denitrification related species including Diaphorobacter species, Thauera species and those in the Sphaerotilus and Leptothrix group were found to be inhibited in a high concentration of CeO-NP. The diversity indices suggested that the bacterial community inhabiting the wastewater samples were less diverse as the concentration of CeO increases. The canonical correspondence analysis (CCA) results highlighted that the bacterial community variance had the strongest relationship with water temperature, conductivity, pH, and dissolved oxygen (DO) content as well as nCeO. The results provided the relationships between the microbial community and environmental variables in the wastewater samples.

Keywords: bacterial community, next generation, cerium oxide, wastewater, activated sludge, nanoparticles, nanotechnology

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Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: Bharti Singh, Shri K. Singh

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Child malnutrition is a multifaceted issue that transcends geographical boundaries. Malnutrition not only stunts physical growth but also leads to a spectrum of morbidities and child mortality. It is one of the leading causes of death (~50 %) among children under age five. Despite economic progress and advancements in healthcare, child malnutrition remains a formidable challenge for India. The objective is to investigate the impact of women's empowerment on child nutrition outcomes in India from 2006 to 2021. A composite index of women's empowerment was constructed using Confirmatory Factor Analysis (CFA), a rigorous technique that validates the measurement model by assessing how well-observed variables represent latent constructs. This approach ensures the reliability and validity of the empowerment index. Secondly, kernel density plots were utilised to visualise the distribution of key nutritional indicators, such as stunting, wasting, and overweight. These plots offer insights into the shape and spread of data distributions, aiding in understanding the prevalence and severity of malnutrition. Thirdly, linear polynomial graphs were employed to analyse how nutritional parameters evolved with the child's age. This technique enables the visualisation of trends and patterns over time, allowing for a deeper understanding of nutritional dynamics during different stages of childhood. Lastly, multilevel analysis was conducted to identify vulnerable levels, including State-level, PSU-level, and household-level factors impacting undernutrition. This approach accounts for hierarchical data structures and allows for the examination of factors at multiple levels, providing a comprehensive understanding of the determinants of child malnutrition. Overall, the utilisation of these statistical methodologies enhances the transparency and replicability of the study by providing clear and robust analytical frameworks for data analysis and interpretation. Our study reveals that NFHS-4 and NFHS-5 exhibit an equal density of severely stunted cases. NFHS-5 indicates a limited decline in wasting among children aged five, while the density of severely wasted children remains consistent across NFHS-3, 4, and 5. In 2019-21, women with higher empowerment had a lower risk of their children being undernourished (Regression coefficient= -0.10***; Confidence Interval [-0.18, -0.04]). Gender dynamics also play a significant role, with male children exhibiting a higher susceptibility to undernourishment. Multilevel analysis suggests household-level vulnerability (intra-class correlation=0.21), highlighting the need to address child undernutrition at the household level.

Keywords: child nutrition, India, NFHS, women’s empowerment

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Authors: Rajkumar Ghosh

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India faces a critical task of water shortage, specifically during dry seasons, which adversely impacts agricultural productivity and food protection. Natural farming, specializing in sustainable practices, demands green water management in smart cities in India. This paper examines how rooftop rainwater harvesting (RRWH) can alleviate water scarcity and support sustainable organic farming practices in India. RRWH emerges as a promising way to increase water availability for the duration of dry intervals and decrease reliance on traditional water sources in smart cities. The look at explores the capacity of RRWH to enhance water use performance, help crop growth, enhance soil health, and promote ecological stability inside the farming ecosystem. The medical paper delves into the advantages, challenges, and implementation techniques of RRWH in organic farming. It addresses demanding situations, including seasonal variability of rainfall, limited rooftop vicinity, and monetary concerns. Moreover, it analyses broader environmental and socio-economic implications of RRWH for sustainable agriculture, emphasizing water conservation, biodiversity protection, and the social properly-being of farming communities. The belief underscores the importance of RRWH as a sustainable solution for reaching the aim of sustainable agriculture in natural farming in India. It emphasizes the want for further studies, policy advocacy, and capacity-building initiatives to promote RRWH adoption and assist the transformation in the direction of sustainable organic farming systems. The paper proposes adaptive strategies to triumph over demanding situations and optimize the advantages of RRWH in organic farming. By way of doing so, India can make vast development in addressing water scarcity issues and making sure a greater resilient and sustainable agricultural future in smart cities.

Keywords: rooftop rainwater harvesting, organic farming, green water management, food protection, ecological stabilty

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Authors: E. Nemes-Nagy, E. Fogarasi, M. Croitoru, A. Nyárádi, K. Komlódi, S. Pál, A. Kovács, O. Kopácsy, R. Tripon, Z. Fazakas, C. Uzun, Z. Simon-Szabó, V. Balogh-Sămărghițan, E. Ernő Nagy, M. Szabó, M. Tilinca

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Intense oxidative stress, increased glycated hemoglobin and mineral imbalance represent risk factors for complications in diabetic patients. Cardiovascular complications are most common in these patients, including nephropathy. This study was conducted in 2015 at the Procardia Laboratory in Tîrgu Mureș, Romania on 40 type 2 diabetic adults. Routine biochemical tests were performed on the Konleab 20XTi analyzer (serum glucose, total cholesterol, LDL and HDL cholesterol, triglyceride, creatinine, urea). We also measured serum uric acid, magnesium and calcium concentration by photometric procedures, potassium, sodium and chloride by ion selective electrode, and chromium by atomic absorption spectrometry in a group of patients. Glycated hemoglobin (HbA1c) dosage was made by reflectometry. Urine analysis was performed using the HandUReader equipment. The level of oxidative stress was measured by serum malondialdehyde dosage using the thiobarbituric acid reactive substances method. MDRD (Modification of Diet in Renal Disease) formula was applied for calculation of creatinine-derived glomerular filtration rate. GraphPad InStat software was used for statistical analysis of the data. The diabetic subject included in the study presented high MDA concentrations, showing intense oxidative stress. Calcium was deficient in 5% of the patients, chromium deficiency was present in 28%. The atherogenic cholesterol fraction was elevated in 13% of the patients. Positive correlation was found between creatinine and MDRD-creatinine values (p<0.0001), 68% of the patients presented increased creatinine values. The majority of the diabetic patients had good control of their diabetes, having optimal HbA1c values, 35% of them presented fasting serum glucose over 120 mg/dl and 18% had glucosuria. Intense oxidative stress and mineral deficiencies can increase the risk of cardiovascular complications in diabetic patients in spite of their good metabolic balance. More than two third of the patients present biochemical signs of nephropathy, cystatin C dosage and microalbuminuria could reveal better the kidney disorder, but glomerular filtration rate calculation formulas are also useful for evaluation of renal function.

Keywords: cardiovascular risk, homocysteine, malondialdehyde, metformin, minerals, type 2 diabetes, vitamin B12

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Authors: Nemat Sokhandan Bashir

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Threats from viruses to agricultural crops could be even larger than the losses caused by the other pathogens because, in many cases, the viral infection is latent but crucial from an epidemic point of view. Wild vegetation can be a source of many viruses that eventually find their destiny in crop plants. Although often asymptomatic in wild plants due to adaptation, they can potentially cause serious losses in crops. Therefore, exploring viruses in wild vegetation is very important. Recently, omics have been quite useful for exploring plant viruses from various plant sources, especially wild vegetation. For instance, we have discovered viruses such as Ambrossia asymptomatic virus I (AAV-1) through the application of metagenomics from Oklahoma Prairie Reserve. Accordingly, extracts from randomly-sampled plants are subjected to high speed and ultracentrifugation to separated virus-like particles (VLP), then nucleic acids in the form of DNA or RNA are extracted from such VLPs by treatment with phenol—chloroform and subsequent precipitation by ethanol. The nucleic acid preparations are separately treated with RNAse or DNAse in order to determine the genome component of VLPs. In the case of RNAs, the complementary cDNAs are synthesized before submitting to DNA sequencing. However, for VLPs with DNA contents, the procedure would be relatively straightforward without making cDNA. Because the length of the nucleic acid content of VPLs can be different, various strategies are employed to achieve sequencing. Techniques similar to so-called "chromosome walking" may be used to achieve sequences of long segments. When the nucleotide sequence data were obtained, they were subjected to BLAST analysis to determine the most related previously reported virus sequences. In one case, we determined that the novel virus was AAV-l because the sequence comparison and analysis revealed that the reads were the closest to the Indian citrus ringspot virus (ICRSV). AAV—l had an RNA genome with 7408 nucleotides in length and contained six open reading frames (ORFs). Based on phylogenies inferred from the replicase and coat protein ORFs of the virus, it was placed in the genus Mandarivirus.

Keywords: wild, plant, novel, metagenomics

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Authors: Khan Md. Abdus Subhan, Rabeya Bushra

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Bangladesh has already seen significant growth in Islamic banking and finance, contributing to the rapid expansion of this sector in the global banking and finance industry. The objective of this study is to analyse the Islamic finance and banking industry's ability to contribute to sustainable development in Bangladesh. It aims to assess the current state, potential, and limitations of Islamic banking and finance in the country. Bangladesh has significant growth potential for Islamic banking and finance. However, addressing several challenges is imperative. These challenges include the absence of a well-developed infrastructure for Islamic banking and finance, a lack of a solid legal framework, limited attention from the central bank, the absence of an Islamic capital market, and a shortage of experts in Sharia law as well as public awareness. Bangladesh, a nation characterized by a primarily Muslim populace, has acknowledged the importance of Islamic finance and banking in promoting sustainable development. Islamic banking principles advocate for ethical practices, risk sharing, and the avoidance of interest-based transactions. This article examines the impact of Islamic finance and banking on promoting sustainable development in Bangladesh and emphasizes its capacity to tackle socio-economic difficulties. The Islamic banking sector, as a trailblazer in funding sustainable development, has the potential to play a significant role in facilitating the shift toward a circular economy. According to Shari'ah rules and the Sustainable Development Goals (SDGs), Islamic finance principles will help change the linear economy into a circular one. They will also provide a strong framework and a lot of funding sources. This study aims to offer crucial recommendations and techniques for the successful implementation of Islamic finance institutions in Bangladesh. The study will use quantitative research methodology, collecting data from secondary sources. This research offers a thorough understanding of the reasoning for the payment of Zakat and its socio-economic importance. Furthermore, the study provides significant insights that could assist Bangladeshi policymakers and governments in implementing Islamic financing systems.

Keywords: sustainable development, Islamic fintech, Islamic banking, Bangladesh

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Authors: Shiv Mohan Singh, Gwyneth Matcher

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To understand the culturable microbial composition and diversity patterns, soil samples were collected from inland nunataks of Jutulsessen and Ahlmannryggen ranges in Dronning Maud Land, Antarctica. 16S rRNA, ITS and the D1/D2 domain sequencing techniques were used for characterization of microbial communities of these geographical areas. The total 37 species of bacteria such as Arthrobacter agilis, Acinetobacter baumannii, Arthrobacter flavus, Arthrobacter ginsengisoli, Arthrobacter oxydans, Arthrobacter oryzae, Arthrobacter polychromogenes, Arthrobacter sulfonivorans, Bacillus altitudinis, Bacillus cereus, Bacillus paramycoides, Brevundimonas vesicularis, Brachybacterium rhamnosum, Curtobacterium luteum, Dermacoccus nishinomiyaensis, Dietzia aerolata, Janibacter indicus, Knoellia subterranean, Kocuria palustris, Kytococcus aerolatus, Lysinibacillus sphaericus, Microbacterium phyllosphaerae, Micrococcus yunnanensis, Methylobacterium rhodesianum, Moraxella osloensis, Paracoccus acridae, Pontibacter amylolyticus, Pseudomonas hunanensis, Pseudarthrobacter siccitolerans, Pseudarthrobacter phenanthrenivorans, Rhodococcus aerolatus, Rhodococcus sovatensis, Sphingomonas daechungensis, Sphingomonas sanguinis, Stenotrophomonas pavanii, Staphylococcus gallinarum, Staphylococcus arlettae and 9 species of fungi such as Candida davisiana, Cosmospora arxii, Geomyces destructans, Lecanicillium muscarium, Memnoniella humicola, Paecilomyces lilacinus, Pseudogymnoascus verrucosus, Phaeophlebiopsis ignerii and Thyronectria caraganae were recorded. Fatty acid methyl esters (FAME) analyses of representative species of each genus have shown predominance branched and unsaturated fatty acids indicate its adaptation strategy in Antarctic cold environment. To the best of our knowledge, this is the first record of culturable bacterial communities from Jutulsessen and Ahlmannryggen ranges in Western Dronning Maud Land, Antarctica.

Keywords: antarctica, microbe, adaptation, polar

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Authors: Leila Baghaarabani, Parvin Razzaghi, Mennatolla Magdy Mostafa, Ahmad Albaqsami, Al Warith Al Rushaidi, Masoud Al Rawahi

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Predicting the interaction between drugs and their molecular targets is pivotal for advancing drug development processes. Due to the time and cost limitations, computational approaches have emerged as an effective approach to drug-target interaction (DTI) prediction. Most of the introduced computational based approaches utilize the drug molecule and protein sequence as input. This study does not only utilize these inputs, it also introduces a protein representation developed using a masked protein language model. In this representation, for every individual amino acid residue within the protein sequence, there exists a corresponding probability distribution that indicates the likelihood of each amino acid being present at that particular position. Then, the similarity between each pair of amino acids is computed to create a similarity matrix. To encode the knowledge of the similarity matrix, Bi-Level Routing Attention (BiFormer) is utilized, which combines aspects of transformer-based models with protein sequence analysis and represents a significant advancement in the field of drug-protein interaction prediction. BiFormer has the ability to pinpoint the most effective regions of the protein sequence that are responsible for facilitating interactions between the protein and drugs, thereby enhancing the understanding of these critical interactions. Thus, it appears promising in its ability to capture the local structural relationship of the proteins by enhancing the understanding of how it contributes to drugprotein interactions, thereby facilitating more accurate predictions. To evaluate the proposed method, it was tested on two widely recognized datasets: Davis and KIBA. A comprehensive series of experiments was conducted to illustrate its effectiveness in comparison to cutting edge techniques.

Keywords: BiFormer, transformer, protein language processing, self-attention mechanism, binding affinity, drug target interaction, similarity matrix, protein masked representation, protein language model

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Authors: Theresa Belema Chris-Biriowu

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The change in trends in relation to gender representation in beer brand commercials was the thrust of the study. The study investigated how beer brand commercials reflect societal realities in their portrayals of gender roles within the span of a decade. The major objective of the study was to find out how gender was contextualized in selected beer brand commercials that both air on Nigerian television and stream on YouTube. The study was anchored on the muted group theory. The population of the study was in two streams: the total number of beer beverages that are produced by the eleven breweries in Nigeria and the registered advertising agencies in Lagos, Nigeria. The sample size was also two-pronged: the purposive selection of beer brands that have their commercials on television and YouTube and the purposive selection of an ad agency that has produced running commercials for beer brands within the period between 2010s and 2020s. They adopted visual framing analysis and narrative analysis research techniques. The study qualitatively analyzed the contents of beer brand commercials and conducted an interview with the management of the ad agency for data collection. The data was presented in images and words. The findings showed that females are underrepresented and misrepresented in the beer brand commercials and that the beer brands are not producing commercials that adequately reflect the realities of present times. It was also found that very little has changed in the ad industry between the periods studied, and commercial screenplays are not written with a specific aim to either target the female demographics or give them equal opportunities to thrive in the beer economy. The study concluded that the gender gap in beer commercials subsists and translates to gender discrimination, especially since it is established that females are also stakeholders in the beer economy. The study recommends that beer brands should produce commercials that appeal to their audience irrespective of gender, reflect contemporary realities, and give all genders equal opportunities to thrive in the increasingly competitive industry.

Keywords: beer brands, commercials, gender representation, visuals, television, YouTube

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Authors: M. R. Vijayakumar, Sanjay Kumar Singh, Lakshmi, Hithesh Dewangan, Sanjay Singh

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Trans resveratrol (RES) is a natural molecule proved for cancer preventive and therapeutic activities devoid of any potential side effects. However, the therapeutic application of RES in disease management is limited because of its rapid elimination from blood circulation thereby low biological half life in mammals. Therefore, the main objective of this study is to enhance the circulation as well as therapeutic efficacy using PEGylated liposomes. D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS) is applied as steric surface decorating agent to prepare RES liposomes by thin film hydration method. The prepared nanoparticles were evaluated by various state of the art techniques such as dynamic light scattering (DLS) technique for particle size and zeta potential, TEM for shape, differential scanning calorimetry (DSC) for interaction analysis and XRD for crystalline changes of drug. Encapsulation efficiency and invitro drug release were determined by dialysis bag method. Cancer cell viability studies were performed by MTT assay, respectively. Pharmacokinetic studies were performed in sprague dawley rats. The prepared liposomes were found to be spherical in shape. Particle size and zeta potential of prepared formulations varied from 64.5±3.16 to 262.3±7.45 nm and -2.1 to 1.76 mV, respectively. DSC study revealed absence of potential interaction. XRD study revealed presence of amorphous form in liposomes. Entrapment efficiency was found to be 87.45±2.14 % and the drug release was found to be controlled up to 24 hours. Minimized MEC in MTT assay and tremendous enhancement in circulation time of RES PEGylated liposomes than its pristine form revealed that the stearic stabilized PEGylated liposomes can be an alternative tool to commercialize this molecule for chemopreventive and therapeutic applications in cancer.

Keywords: trans resveratrol, cancer nanotechnology, long circulating liposomes, bioavailability enhancement, liposomes for cancer therapy, PEGylated liposomes

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Zahid Ali Ghazi

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Supercapacitors (SCs) have emerged as auspicious energy storage devices because of their fast charge-discharge characteristics and high power densities. In the current study, a simple approach is used to coat activated carbon (AC) with a thin layer of nickel (Ni) by an electroless deposition process to enhance the electrochemical performance of the SC. The synergistic combination of large surface area and high electrical conductivity of the AC, as well as the pseudocapacitive behavior of the metallic Ni, has shown great potential to overcome the limitations of traditional SC materials. First, the materials were characterized using X-ray diffraction (XRD) for crystallography, scanning electron microscopy (SEM) for surface morphology and energy dispersion X-ray (EDX) for elemental analysis. The electrochemical performance of the nickel-coated activated carbon (Ni-AC) is systematically evaluated through various techniques, including galvanostatic charge-discharge (GCD), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). The GCD results revealed that Ni/AC has a higher specific capacitance (1559 F/g) than bare AC (222 F/g) at 1 A/g current density in a 2 M KOH electrolyte. Even at a higher current density of 20 A/g, the Ni/AC showed a high capacitance of 944 F/g as compared to 77 F/g by AC. The specific capacitance (1318 F/g) calculated from CV measurements for Ni-AC at 10mV/sec was in close agreement with GCD data. Furthermore, the bare AC exhibited a low energy of 15 Wh/kg at a power density of 356 W/kg whereas, an energy density of 111 Wh/kg at a power density of 360 W/kg was achieved by Ni/AC-850 electrode and demonstrated a long life cycle with 94% capacitance retention over 50000 charge/discharge cycles at 10 A/g. In addition, the EIS study disclosed that the Rs and Rct values of Ni/AC electrodes were much lower than those of bare AC. The superior performance of Ni/AC is mainly attributed to the presence of excessive redox active sites, large electroactive surface area and corrosive resistance properties of Ni. We believe that this study will provide new insights into the controlled coating of ACs and other porous materials with metals for developing high-performance SCs and other energy storage devices.

Keywords: supercapacitor, cyclic voltammetry, coating, energy density, activated carbon

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, David Chernobylsky, Omar Durra

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Background: It is crucial to detect the patient’s existing anxiety to assist patients in a perioperative setting which is to be caused by the fear associated with surgical and anesthetic complications. However, the current gold standard for assessing patient anxiety, the STAI, is problematic to use in the preoperative setting, given the duration and concentration required to complete the 40-item questionnaire. Our primary aim in the study is to investigate the correlation of the Yumul Visual Facial Anxiety Scale (VFAS) and Numerical Verbal Rating Scale (NVRS) to State-Trait Anxiety Inventory (STAI) to determine the optimal anxiety scale to use in the perioperative setting. Methods: A clinical study of patients undergoing various surgeries was conducted utilizing each of the preoperative anxiety scales. Inclusion criteria included patients undergoing elective surgeries, while exclusion criteria included patients with anesthesia contraindications, inability to comprehend instructions, impaired judgement, substance abuse history, and those pregnant or lactating. 293 patients were analyzed in terms of demographics, anxiety scale survey results, and anesthesia data via Spearman Coefficients, Chi-Squared Analysis, and Fischer’s exact test utilized for comparative analysis. Results: Statistical analysis showed that VFAS had a higher correlation to STAI than NVRS (rs=0.66, p<0.0001 vs. rs=0.64, p<0.0001). The combined VFAS-Categorization Scores showed the highest correlation with the gold standard (rs=0.72, p<0.0001). Subgroup analysis showed similar results. STAI evaluation time (247.7 ± 54.81 sec) far exceeds VFAS (7.29 ± 1.61 sec), NVRS (7.23 ± 1.60 sec), and Categorization scales (7.29 ± 1.99 sec). Patients preferred VFAS (54.4%), Categorization (11.6%), and NVRS (8.8%). Anesthesiologists preferred VFAS (63.9%), NVRS (22.1%), and Categorization Scales (14.0%). Of note, the top five causes of preoperative anxiety were determined to be waiting (56.5%), pain (42.5%), family concerns (40.5%), no information about surgery (40.1%), or anesthesia (31.6%). Conclusıons: Both VFAS and Categorization tests also take significantly less time than STAI, which is critical in the preoperative setting. Combined VFAS-Categorization Score (VCS) demonstrates the highest correlation to the gold standard, STAI. Among both patients and anesthesiologists, VFAS was the most preferred scale. This forms the basis of the Yumul Faces Anxiety Scale, designed for quick quantization and assessment in the preoperative setting while maintaining a high correlation to the golden standard. Additional studies using the formulated Yumul Faces Anxiety Scale are merited.

Keywords: numerical verbal anxiety scale, preoperative anxiety, state-trait anxiety inventory, visual facial anxiety scale

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Authors: Alberto Enrique Molina Lozano, María Teresa Cortés Montañez

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Polyaniline (PANI) photoelectrodes were electrochemically synthesized through electrodeposition employing three techniques: chronoamperometry (CA), cyclic voltammetry (CV), and potential pulse (PP) methods. The substrate used for electrodeposition was a fluorine-doped tin oxide (FTO) glass with dimensions of 2.5 cm x 1.3 cm. Subsequently, structural and optical characterization was conducted utilizing Fourier-transform infrared (FTIR) spectroscopy and UV-visible (UV-vis) spectroscopy, respectively. The FTIR analysis revealed variations in the molar ratio of benzenoid to quinonoid rings within the PANI polymer matrix, indicative of differing oxidation states arising from the distinct electropolymerization methodologies employed. In the optical characterization, differences in the energy band gap (Eg) values and positions of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were observed, attributable to variations in doping levels and structural irregularities introduced during the electropolymerization procedures. To assess the charge transfer properties of the PANI photoelectrodes, electrochemical impedance spectroscopy (EIS) experiments were carried out within a 0.1 M sodium sulfate (Na₂SO₄) electrolyte. The results displayed a substantial decrease in charge transfer resistance with the PANI coatings compared to uncoated substrates, with PANI obtained through cyclic voltammetry (CV) presenting the lowest charge transfer resistance, contrasting PANI obtained via chronoamperometry (CA) and potential pulses (PP). Subsequently, the photoactive response of the PANI photoelectrodes was measured through linear sweep voltammetry (LSV) and chronoamperometry. The photoelectrochemical measurements revealed a discernible photoactivity in all PANI-coated electrodes. However, PANI electropolymerized through CV displayed the highest photocurrent. Interestingly, PANI derived from chronoamperometry (CA) exhibited the highest degree of stable photocurrent over an extended temporal interval.

Keywords: PANI, photocurrent, photoresponse, charge separation, recombination

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Authors: Ana Maria Igual-Munoz, Juan Gilabert, Marta Garcia, Alfredo Quijano-Lopez

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Nowadays, several lithium-ion battery technologies are being commercialized. These chemistries present different properties that make them more suitable for different purposes. However, comparative studies showing the advantages and disadvantages of different chemistries are incomplete or scarce. Different non-destructive techniques are currently being employed to detect how ageing affects the active materials of lithium-ion batteries (LIBs). For instance, electrochemical impedance spectroscopy (EIS) is one of the most employed ones. This technique allows the user to identify the variations on the different resistances present in LIBs. On the other hand, differential voltage analysis (DVA) has shown to be a powerful technique to detect the processes affecting the different capacities present in LIBs. This technique shows variations in the state of health (SOH) and the capacities for one or both electrodes depending on their chemistry. Finally, incremental capacity analysis (ICA) is a widely known technique for being capable of detecting phase equilibria. It reminds of the commonly used cyclic voltamperometry, as it allows detecting some reactions taking place in the electrodes. In these studies, a set of ageing procedures have been applied to commercial batteries of different chemistries (NCA, NMC, and LFP). Afterwards, results of EIS, DVA, and ICA have been used to correlate them with the processes affecting each cell. Ciclability, overpotential, and temperature cycling studies envisage how the charge-discharge rates, cut-off voltage, and operation temperatures affect each chemistry. These studies will serve battery pack manufacturers, as for common battery users, as they will determine the different conditions affecting cells for each of the chemistry. Taking this into account, each cell could be adjusted to the final purpose of the battery application. Last but not least, all the degradation parameters observed are focused to be integrated into degradation models in the future. This fact will allow the implementation of the widely known digital twins to the degradation in LIBs.

Keywords: lithium ion batteries, non-destructive analysis, different chemistries, ante-mortem studies, ICA, DVA, EIS

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Authors: Suveen Kumar

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Oral cancer (OC) is the sixth most death causing cancer in world which includes tumour of lips, floor of the mouth, tongue, palate, cheeks, sinuses, throat, etc. Conventionally, the techniques used for OC detection are toluidine blue staining, biopsy, liquid-based cytology, visual attachments, etc., however these are limited by their highly invasive nature, low sensitivity, time consumption, sophisticated instrument handling, sample processing and high cost. Therefore, we developed biosensing chips for non-invasive detection of OC via CYFRA-21-1 biomarker. CYFRA-21-1 (molecular weight: 40 kDa) is secreted in saliva of OC patients which is a non-invasive biological fluid with a cut-off value of 3.8 ng mL-1, above which the subjects will be suffering from oral cancer. Therefore, in first work, 3-aminopropyl triethoxy silane (APTES) functionalized zirconia (ZrO2) nanoparticles (APTES/nZrO2) were used to successfully detect CYFRA-21-1 in a linear detection range (LDR) of 2-16 ng mL-1 with sensitivity of 2.2 µA mL ng-1. Successively, APTES/nZrO2-RGO was employed to prevent agglomeration of ZrO2 by providing high surface area reduced graphene oxide (RGO) support and much wider LDR (2-22 ng mL-1) was obtained with remarkable limit of detection (LOD) as 0.12 ng mL-1. Further, APTES/nY2O3/ITO platform was used for oral cancer bioseneor development. The developed biosensor (BSA/anti-CYFRA-21-1/APTES/nY2O3/ITO) have wider LDR (0.01-50 ng mL-1) with remarkable limit of detection (LOD) as 0.01 ng mL-1. To improve the sensitivity of the biosensing platform, nanocomposite of yattria stabilized nanostructured zirconia-reduced graphene oxide (nYZR) based biosensor has been developed. The developed biosensing chip having ability to detect CYFRA-21-1 biomolecules in the range of 0.01-50 ng mL-1, LOD of 7.2 pg mL-1 with sensitivity of 200 µA mL ng-1. Further, the applicability of the fabricated biosensing chips were also checked through real sample (saliva) analysis of OC patients and the obtained results showed good correlation with the standard protein detection enzyme linked immunosorbent assay (ELISA) technique.

Keywords: non-invasive, oral cancer, nanomaterials, biosensor, biochip

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Authors: Dong Tang, Yongli Zhao

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The study of the microstructure of asphalt is of great importance for the analysis of its macroscopic properties. However, the peculiarities of the chemical composition of the asphalt itself and the limitations of existing direct imaging techniques have caused researchers to face many obstacles in studying the microstructure of asphalt. The advantage of small-angle X-ray scattering (SAXS) is that it allows quantitative determination of the internal structure of opaque materials and is suitable for analyzing the microstructure of materials. Therefore, the SAXS technique was used to study the evolution of microstructures on the nanoscale during asphalt aging. And the reasons for the change in scattering contrast during asphalt aging were also explained with the help of Fourier transform infrared spectroscopy (FTIR). SAXS experimental results show that the SAXS curves of asphalt are similar to the scattering curves of scattering objects with two-level structures. The Porod curve for asphalt shows that there is no obvious interface between the micelles and the surrounding mediums, and there is only a fluctuation of the hot electron density between the two. The Beaucage model fit SAXS patterns shows that the scattering coefficient P of the asphaltene clusters as well as the size of the micelles, gradually increase with the aging of the asphalt. Furthermore, aggregation exists between the micelles of asphalt and becomes more pronounced with increasing aging. During asphalt aging, the electron density difference between the micelles and the surrounding mediums gradually increases, leading to an increase in the scattering contrast of the asphalt. Under long-term aging conditions due to the gradual transition from maltenes to asphaltenes, the electron density difference between the micelles and the surrounding mediums decreases, resulting in a decrease in the scattering contrast of asphalt SAXS. Finally, this paper correlates the macroscopic properties of asphalt with microstructural parameters, and the results show that the high-temperature rutting resistance of asphalt is enhanced and the low-temperature cracking resistance decreases due to the aggregation of micelles and the generation of new micelles. These results are useful for understanding the relationship between changes in microstructure and changes in properties during asphalt aging and provide theoretical guidance for the regeneration of aged asphalt.

Keywords: asphalt, Beaucage model, microstructure, SAXS

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Authors: Tatyana Savchuk, Yelena Grinvald, Mohamed Ali, Ramune Sepetiene, Dinara Sadvakassova, Saniya Saussakova, Kuralay Zhangazieva, Dulat Imashpayev

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Introduction. The problem of viral hepatitis B (HBV) takes a vital place in the global health system. The existing risk of HBV transmission through blood transfusions is associated with transfusion of blood taken from infected individuals during the “serological window” period or from patients with latent HBV infection, the marker of which is anti-HBcore. In the absence of information about other markers of hepatitis B, the presence of anti-HBcore suggests that a person may be actively infected or has suffered hepatitis B in the past and has immunity. Aim. To study the risk factors influencing the positive anti-HBcore indicators among the donor population. Materials and Methods. The study was conducted in 2021 in the Scientific and Production Center of Transfusiology of the Ministry of Healthcare in Kazakhstan. The samples taken from blood donors were tested for anti-HBcore, by CLIA on the Architect i2000SR (ABBOTT). A special questionnaire was developed for the blood donors’ socio-demographic characteristics. Statistical analysis was conducted by the R software (version 4.1.1, USA, 2021). Results.5709 people aged 18 to 66 years were included in the study, the proportion of men and women was 68.17% and 31.83%, respectively. The average age of the participants was 35.7 years. A weighted multivariable mixed effects logistic regression analysis showed that age (p<0.001), ethnicity (p<0.05), and marital status (p<0.05) were statistically associated with anti-HBcore positivity. In particular, analysis adjusting for gender, nationality, education, marital status, family history of hepatitis, blood transfusion, injections, and surgical interventions, with a one-year increase in age (adjOR=1.06, 95%CI:1.05-1.07), showed an 6% growth in odds of having anti-HBcore positive results. Those who were russian ethnicity (adjOR=0.65, 95%CI:0.46-0.93) and representatives of other nationality groups (adjOR=0.56, 95%CI:0.37-0.85) had lower odds of having anti-HBcore when compared to Kazakhs when controlling for other covariant variables. Among singles, the odds of having a positive anti-HBcore were lower by 29% (adjOR = 0.71, 95%CI:0.57-0.89) compared to married participants when adjusting for other variables. Conclusions.Kazakhstan is one of the countries with medium endemicity of HBV prevalence (2%-7%). Results of the study demonstrated the possibility to form a profile of risk factors (age, nationality, marital status). Taking into account the data, it is recommended to increase attention to donor questionnaires by adding leading questions and to improve preventive measures to prevent HBV. Funding. This research was supported by a grant from Abbott Laboratories.

Keywords: anti-HBcore, blood donor, donation, hepatitis B virus, occult hepatitis

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Authors: Imran Dayan, Ashiqul Khan

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Internal corporate fraud, which is fraud carried out by internal stakeholders of a company, affects the well-being of the organisation just like its external counterpart. Even if such an act is carried out for the short-term benefit of a corporation, the act is ultimately harmful to the entity in the long run. Internal fraud is often carried out by relying upon aberrations from usual business processes. Business processes are the lifeblood of a company in modern managerial context. Such processes are developed and fine-tuned over time as a corporation grows through its life stages. Modern corporations have embraced technological innovations into their business processes, and Enterprise Resource Planning (ERP) systems being at the heart of such business processes is a testimony to that. Since ERP systems record a huge amount of data in their event logs, the logs are a treasure trove for anyone trying to detect any sort of fraudulent activities hidden within the day-to-day business operations and processes. This research utilises the ERP systems in place within corporations to assess the likelihood of prospective internal fraud through developing a framework for measuring the risks of fraud through Process Mining techniques and hence finds risky designs and loose ends within these business processes. This framework helps not only in identifying existing cases of fraud in the records of the event log, but also signals the overall riskiness of certain business processes, and hence draws attention for carrying out a redesign of such processes to reduce the chance of future internal fraud while improving internal control within the organisation. The research adds value by applying the concepts of Process Mining into the analysis of data from modern day applications of business process records, which is the ERP event logs, and develops a framework that should be useful to internal stakeholders for strengthening internal control as well as provide external auditors with a tool of use in case of suspicion. The research proves its usefulness through a few case studies conducted with respect to big corporations with complex business processes and an ERP in place.

Keywords: enterprise resource planning, fraud risk framework, internal corporate fraud, process mining

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Authors: Raed Fawzi Mohammed Ameen, Haider I. Alyasari, Maryam Altaweel

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Due to rapid urbanization, developing countries faced significant urban challenges that accompanied the population growth such as the inability to provide adequate housing; sustain human and community's health and wellbeing; ensure the safety in urban areas; the prevalence corruption; lack of jobs; and a shortage of investment. The destruction, degradation, and lack of planning are acute in countries such as Iraq that have suffered for more than four decades because of war and international sanctions, resulting in severe damages to the ecology sector, social utilities, housing, infrastructure, as well as the disruption of the economic sector. Many of significant urban development, housing, and regeneration projects are currently underway in different regions in Iraq, labelled as a means to reform the environmental, social, and economic sectors. However, most often with absence of public participation. Hence, there is an urgent need for understanding public perception, especially of urban socio-economic challenges, which represents a crucial concern for many planners, designers, and policy-makers in order to develop effective policies in addition to increasing their participation. The aim of this study is to investigate stakeholder perceptions of the socio-economic challenges of urban development and their priorities in the all Iraqi provinces. A nationwide questionnaire has been conducted (N = 643) across Iraq, using 19- item structured questionnaire where the stakeholder’s perspectives were collected on a 5-point Likert-type scale. The indicators were identified through deep investigation in previous studies. Principal component analysis (PCA) and statistical tests were utilized to the collected responses in order to investigate the linkage between the perceptions of socio- economic challenges and demographic factors. A high value of internal consistency and reliability of the instrument has been achieved (Cronbach’s alpha= 0.867). Five principal components have been identified, namely: economic, cultural aspects, design context, employment, security and housing demands. The item ‘safety of public places' was ranked as the most important, followed by the items 'minimize unplanned housing', and ‘provision of affordable housing’, respectively. Promote high-rise housing from the housing demands group, was ranked the lowest component between all indicators. 'Using sustainable local materials in construction' item had the second lowest mean score. The results also illustrate a link between deficiencies in the social and economic infrastructure because of the destruction and degradation caused by political instability in Iraq in the last few decades.

Keywords: public participation in development, socio-economic challenges, urban development, urban sustainability

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Authors: Carmela Nardelli, Laura Iaffaldano, Valentina Capobianco, Antonietta Tafuto, Maddalena Ferrigno, Angela Capone, Giuseppe Maria Maruotti, Maddalena Raia, Rosa Di Noto, Luigi Del Vecchio, Pasquale Martinelli, Lucio Pastore, Lucia Sacchetti

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Maternal obesity and nutrient excess in utero increase the risk of future metabolic diseases in the adult life. The mechanisms underlying this process are probably based on genetic, epigenetic alterations and changes in foetal nutrient supply. In mammals, the placenta is the main interface between foetus and mother, it regulates intrauterine development, modulates adaptive responses to sub optimal in uterus conditions and it is also an important source of human amniotic mesenchymal stem cells (hA-MSCs). We previously highlighted a specific microRNA (miRNA) profiling in amnion from obese (Ob) pregnant women, here we compared the miRNA expression profile of hA-MSCs isolated from (Ob) and control (Co) women, aimed to search for any alterations in metabolic pathways that could predispose the new-born to the obese phenotype. Methods: We isolated, at delivery, hA-MSCs from amnion of 16 Ob- and 7 Co-women with pre-pregnancy body mass index (mean/SEM) 40.3/1.8 and 22.4/1.0 kg/m2, respectively. hA-MSCs were phenotyped by flow cytometry. Globally, 384 miRNAs were evaluated by the TaqMan Array Human MicroRNA Panel v 1.0 (Applied Biosystems). By the TargetScan program we selected the target genes of the miRNAs differently expressed in Ob- vs Co-hA-MSCs; further, by KEGG database, we selected the statistical significant biological pathways. Results: The immunophenotype characterization confirmed the mesenchymal origin of the isolated hA-MSCs. A large percentage of the tested miRNAs, about 61.4% (232/378), was expressed in hA-MSCs, whereas 38.6% (146/378) was not. Most of the expressed miRNAs (89.2%, 207/232) did not differ between Ob- and Co-hA-MSCs and were not further investigated. Conversely, 4.8% of miRNAs (11/232) was higher and 6.0% (14/232) was lower in Ob- vs Co-hA-MSCs. Interestingly, 7/232 miRNAs were obesity-specific, being expressed only in hA-MSCs isolated from obese women. Bioinformatics showed that these miRNAs significantly regulated (P<0.001) genes belonging to several metabolic pathways, i.e. MAPK signalling, actin cytoskeleton, focal adhesion, axon guidance, insulin signaling, etc. Conclusions: Our preliminary data highlight an altered miRNA profile in Ob- vs Co-hA-MSCs and suggest that an epigenetic miRNA-based mechanism of gene regulation could affect pathways involved in placental growth and function, thereby potentially increasing the newborn’s risk of metabolic diseases in the adult life.

Keywords: hA-MSCs, obesity, miRNA, biosystem

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Authors: Ozan Kahraman, Hao Feng

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Manothermosonication (MTS), which consists of the simultaneous application of heat and ultrasound under moderate pressure (100-700 kPa), is one of the technologies which destroy microorganisms and inactivates enzymes. Transmission electron microscopy (TEM) is a microscopy technique in which a beam of electrons is transmitted through an ultra-thin specimen, interacting with the specimen as it passes through it. The environmental scanning electron microscope or ESEM is a scanning electron microscope (SEM) that allows for the option of collecting electron micrographs of specimens that are "wet," uncoated. These microscopy techniques allow us to observe the processing effects on the samples. This study was conducted to investigate the effects of MTS and HTST treatments on the morphology of apple-carrot juices by using TEM and ESEM microscopy. Apple-carrot juices treated with HTST (72 0C, 15 s), MTS 50 °C (60 s, 200 kPa), and MTS 60 °C (30 s, 200 kPa) were observed in both ESEM and TEM microscopy. For TEM analysis, a drop of the solution dispersed in fixative solution was put onto a Parafilm ® sheet. The copper coated side of the TEM sample holder grid was gently laid on top of the droplet and incubated for 15 min. A drop of a 7% uranyl acetate solution was added and held for 2 min. The grid was then removed from the droplet and allowed to dry at room temperature and presented into the TEM. For ESEM analysis, a critical point drying of the filters was performed using a critical point dryer (CPD) (Samdri PVT- 3D, Tousimis Research Corp., Rockville, MD, USA). After the CPD, each filter was mounted onto a stub and coated with gold/palladium with a sputter coater (Desk II TSC Denton Vacuum, Moorestown, NJ, USA). E.Coli O157:H7 cells on the filters were observed with an ESEM (Philips XL30 ESEM-FEG, FEI Co., Eindhoven, The Netherland). ESEM (Environmental Scanning Electron Microscopy) and TEM (Transmission Electron Microscopy) images showed extensive damage for the samples treated with MTS at 50 and 60 °C such as ruptured cells and breakage on cell membranes. The damage was increasing with increasing exposure time.

Keywords: MTS, HTST, ESEM, TEM, E.COLI O157:H7

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Authors: Fazl Ullah, Rahmat Ullah

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This paper shows a comprehensive learning focused on the optimization of gas production in shale gas reservoirs through hydraulic fracturing. Shale gas has emerged as an important unconventional vigor resource, necessitating innovative techniques to enhance its extraction. The key objective of this study is to examine the influence of fracture parameters on reservoir productivity and formulate strategies for production optimization. A sophisticated model integrating gas flow dynamics and real stress considerations is developed for hydraulic fracturing in multi-stage shale gas reservoirs. This model encompasses distinct zones: a single-porosity medium region, a dual-porosity average region, and a hydraulic fracture region. The apparent permeability of the matrix and fracture system is modeled using principles like effective stress mechanics, porous elastic medium theory, fractal dimension evolution, and fluid transport apparatuses. The developed model is then validated using field data from the Barnett and Marcellus formations, enhancing its reliability and accuracy. By solving the partial differential equation by means of COMSOL software, the research yields valuable insights into optimal fracture parameters. The findings reveal the influence of fracture length, diversion capacity, and width on gas production. For reservoirs with higher permeability, extending hydraulic fracture lengths proves beneficial, while complex fracture geometries offer potential for low-permeability reservoirs. Overall, this study contributes to a deeper understanding of hydraulic cracking dynamics in shale gas reservoirs and provides essential guidance for optimizing gas production. The research findings are instrumental for energy industry professionals, researchers, and policymakers alike, shaping the future of sustainable energy extraction from unconventional resources.

Keywords: fluid-solid coupling, apparent permeability, shale gas reservoir, fracture property, numerical simulation

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

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Authors: Mahmood Iqbal, Khalid Nawab, Tachibana Satoshi

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Farmer Field School (FFS) is constantly aims to assist farmers to determine and learn about field ecology and integrated crop management. The study was conducted to examine the change in productivity of tomato crop in the study area; to determine increase in per acre yield of the crop, and find out reduction in per acre input cost. A study of tomato crop was conducted in ten villages namely Jabban, Bijligar Colony, Palonow, Heroshah, Zara Maira, Deghar Ghar, Sidra Jour, Anar Thangi, Miangano Korona and Wartair of district Malakand. From each village 15 respondents were selected randomly on the basis of identical allocation making sample size of 150 respondents. The research was based on primary as well as secondary data. Primary data was collected from farmers while secondary data were taken from Agriculture Extension Department Dargai, District Malakand. Interview schedule was planned and each farmer was interviewed personally. The study was based on comparison of cost, yield and income of tomato before and after FFS. Paired t-test and Statistical Package for Social Sciences (SPSS) was used for analysis; outcome of the study show that integrated pest management project has brought a positive change in the attitude of farmers of the project area through FFS approach. In district Malakand 66.0% of the respondents were between the age group of 31-50 years, 11.3% of respondents had primary level of education, 12.7% of middle level, 28.7% metric level, 3.3% of intermediate level and 2.0% of graduate level of education while 42.0% of respondents were illiterate and have no education. Average land holding size of farmers was 6.47 acres, cost of seed, crop protection from insect pest and crop protection from diseases was reduced by Rs. 210.67, Rs. 2584.43 and Rs. 3044.16 respectively, the cost of fertilizers and cost of farm yard manure was increased by Rs.1548.87 and Rs. 1151.40 respectively while tomato yield was increased by 1585.03 kg/acre from 7663.87 to 9248.90 kg/acre. The role of FFS initiate by integrated pest management project through department of agriculture extension for the development of agriculture was worth mentioning. It has brought enhancement in crop yield of tomato and their income through FFS approach. On the basis of results of the research studies, integrated pest management project should spread their developmental activities for maximum participation of the complete rural masses through participatory FFS approach.

Keywords: agriculture, Farmers field schools, extension education, tomato

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Authors: P. Tardi, B. Szilagyi, A. Makai, P. Acs, M. Hock, M. Jaromi

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Osteoporosis is becoming a major public health problem, particularly in postmenopausal women, as the incidence of this disease is getting higher. Nowadays, one of the most common chronic musculoskeletal diseases is osteoporosis. Osteoporosis-related knowledge is an important contributor to prevent or to treat osteoporosis. The most important strategies to prevent or treat the disease are increasing the level of physical activity at all ages, cessation of smoking, reduction of alcohol consumption, adequate dietary calcium, and vitamin D intake. The aim of the study was to measure the osteoporosis-related knowledge and physical activity among women age over 50 years. For the measurements, we used the osteoporosis questionnaire (OPQ) to examine the disease-specific knowledge and the global physical activity questionnaire (GPAQ) to measure the quantity and quality of the physical activity. The OPQ is a self-administered 20-item questionnaire with five categories: general information, risk factors, investigations, consequences, and treatment. There are four choices per question (one of them is the 'I do not know'). The filler gets +1 for a good answer, -1 point for a bad answer, and 0 for 'I do not know' answer. We contacted with 326 women (63.08 ± 9.36 year) to fill out the questionnaires. Descriptive analysis was carried out, and we calculated Spearman's correlation coefficient to examine the relationship between the variables. Data were entered into Microsoft Excel, and all statistical analyses were performed using SPSS (Version 24). The participants of the study (n=326) reached 8.76 ± 6.94 points on OPQ. Significant (p < 0.001) differences were found in the results of OPQ according to the highest level of education. It was observed that the score of the participants with osteoporosis (10.07 ± 6.82 points) was significantly (p=0.003) higher than participants without osteoporosis (9.38 ± 6.66 points) and the score of those women (6.49 ± 6.97 points) who did not know that osteoporosis exists in their case. The GPAQ results showed the sample physical activity in the dimensions of vigorous work (479.86 ± 684.02 min/week); moderate work (678.16 ± 804.5 min/week); travel (262.83 ± 380.27 min/week); vigorous recreation (77.71 ± 123.46 min/week); moderate recreation (115.15 ± 154.82 min/week) and total weekly physical activity (1645.99 ± 1432.88 min/week). Significant correlations were found between the osteoporosis-related knowledge and the physical activity in travel (R=0.21; p < 0.001), vigorous recreation (R=0.35; p < 0.001), moderate recreation (R=0.35; p < 0.001), total vigorous minutes/week (R=0.15; p=0.001) and total moderate minutes/week (R=0.13; p=0.04) dimensions. According to the results that were achieved, the highest level of education significantly determines osteoporosis-related knowledge. Physical activity is an important contributor to prevent or to treat osteoporosis, and it showed a significant correlation with osteoporosis-related knowledge. Based on the results, the development of osteoporosis-related knowledge may help to improve the level of physical activity, especially recreation. Acknowledgment: Supported by the ÚNKP-20-1 New National Excellence Program of The Ministry for Innovation and Technology from the Source of the National Research, Development and Innovation Fund.

Keywords: osteoporosis, osteoporosis-related knowledge, physical activity, prevention

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