Search results for: gene expression datasets

Authors: Zuzana Komrsková

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This paper shows the connection between emoticons and politeness in written computer-mediated communication. It studies if there are some differences in the use of emoticon between Czech and English written tweets. My assumptions about the use of emoticons were based on the use of greetings and thanks in real, face to face situations. The first assumption, that welcome greeting phrase would be accompanied by positive emoticon was correct. But for the farewell greeting both positive and negative emoticons are possible. My results show lower frequency of negative emoticons in this context. I also found quite often both positive and negative emoticon in the same tweet. The expression of gratitude is associated with positive emotions. The results show that emoticons accompany polite phrases of greeting and thanks very often both in Czech and English. The use of emoticons with studied polite phrases shows that emoticons have become an integral part of these phrases.

Keywords: Czech, emoticon, english, politeness, twitter

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Authors: Tian Zhang

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Unsupervised object segmentation aims at segmenting objects in sequential images and obtaining the mask of each object without any manual intervention. Unsupervised segmentation remains a challenging task due to the lack of prior knowledge about these objects. Previous methods often require manually specifying the action of each object, which is often difficult to obtain. Instead, this paper does not need action information of objects and automatically learns the actions and relations among objects from the structured environment. To obtain the object segmentation of sequential images, the relationships between objects and images are extracted to infer the action and interaction of objects based on the multi-head attention mechanism. Three types of objects’ relationships in the object segmentation task are proposed: the relationship between objects in the same frame, the relationship between objects in two frames, and the relationship between objects and historical information. Based on these relationships, the proposed model (1) is effective in multiple objects segmentation tasks, (2) just needs images as input, and (3) produces better segmentation results as more relationships are considered. The experimental results on multiple datasets show that this paper’s method achieves state-of-art performance. The quantitative and qualitative analyses of the result are conducted. The proposed method could be easily extended to other similar applications.

Keywords: unsupervised object segmentation, attention mechanism, contrastive learning, structured environment

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Authors: H. Boulahyaoui, S. Alaoui Amine, C. Loutfi, H. El Annaz, N. Touil, El M. El Fahim, S. Mrani

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Three Moroccan children fully vaccinated with Rotarix™ have been hospitalized for Rotavirus Gastroenteritis (RVGE) in the pediatric division of the Farabi Hospital, Oujda. Rotavirus G/P genotypes could not be typed because of their delayed crossing threshold (Ct) resolute with a group A rotavirus (RVA) real time RT-PCR. These strains were adapted to cell culture. All viruses replicated and caused extensive cytopathic effects after four or five passages in MA104 cell lines. Significant improvements have been obtained in the amount of viral particles. Each virus multiplied to a high titer (7.5 TCID50/ml). VP7 and VP4 partial gene sequencing revealed distinct genotypes compared to the Rotarix(®) vaccine strain. Two strains were of G2P[4] genotype whereas the third was G9P[8] genotype. Virus isolation while labor intensive, is recommended as a second test, especially when higher sensitivity for conventional RVA genotyping RT-PCR is needed. VP7 antigenic similarities between these strains and Rotarix were determined.

Keywords: esacpe-vaccine, Morocco, Rotarix, G2P[4], G9P[8]

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Authors: Md. Samsuddin Ansari, Ashish Arora

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Every year 10 million people fall ill with one of the oldest diseases known as tuberculosis, caused by Mycobacterium tuberculosis. The success of M. tuberculosis as a pathogen is because of its ability to persist in host tissues. Multidrug resistance (MDR) mycobacteria cases increase every day, which is associated with efflux pumps controlled at the level of transcription. The transcription regulators of MDR transporters in bacteria belong to one of the following four regulatory protein families: AraC, MarR, MerR, and TetR. Phenolic acid decarboxylase repressor (PadR), like a family of transcription regulators, is closely related to the MarR family. Phenolic acid decarboxylase repressor (PadR) was first identified as a transcription factor involved in the regulation of phenolic acid stress response in various microorganisms (including Mycobacterium tuberculosis H37Rv). Recently research has shown that the PadR family transcription factors are global, multifunction transcription regulators. Rv0047c is a PadR subfamily-1 protein. We are exploring the biophysical and structural characterization of Rv0047c. The Rv0047 gene was amplified by PCR using the primers containing EcoRI and HindIII restriction enzyme sites cloned in pET-NH6 vector and overexpressed in DH5α and BL21 (λDE3) cells of E. coli following purification with Ni2+-NTA column and size exclusion chromatography. We did DSC to know the thermal stability; the Tm (transition temperature) of protein is 55.29ºC, and ΔH (enthalpy change) of 6.92 kcal/mol. Circular dichroism to know the secondary structure and conformation and fluorescence spectroscopy for tertiary structure study of protein. To understand the effect of pH on the structure, function, and stability of Rv0047c we employed spectroscopy techniques such as circular dichroism, fluorescence, and absorbance measurements in a wide range of pH (from pH-2.0 to pH-12). At low and high pH, it shows drastic changes in the secondary and tertiary structure of the protein. EMSA studies showed the specific binding of Rv0047c with its own 30-bp promoter region. To determine the effect of complex formation on the secondary structure of Rv0047c, we examined the CD spectra of the complex of Rv0047c with promoter DNA of rv0047. The functional role of Rv0047c was characterized by over-expressing the Rv0047c gene under the control of hsp60 promoter in Mycobacterium tuberculosis H37Rv. We have predicted the three-dimensional structure of Rv0047c using the Swiss Model and Modeller, with validity checked by the Ramachandra plot. We did molecular docking of Rv0047c with dnaA, through PatchDock following refinement through FireDock. Through this, it is possible to easily identify the binding hot-stop of the receptor molecule with that of the ligand, the nature of the interface itself, and the conformational change undergone by the protein pattern. We are using X-crystallography to unravel the structure of Rv0047c. Overall the studies show that Rv0047c may have transcription regulation along with providing an insight into the activity of Rv0047c in the pH range of subcellular environment and helps to understand the protein-protein interaction, a novel target to kill dormant bacteria and potential strategy for tuberculosis control.

Keywords: mycobacterium tuberculosis, phenolic acid decarboxylase repressor, Rv0047c, Circular dichroism, fluorescence spectroscopy, docking, protein-protein interaction

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: S. Aizikovich, L. Krenev, Y. Tokovyy, Y. C. Wang

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An approximate analytical-numerical solution to the axisymmetric problem on thermo-mechanical indentation of a flat cylindrical punch into an arbitrarily non-homogeneous elastic half-space is constructed by making use of the bilateral asymptotic method. The key point of this method lies in evaluation of the ker¬nels in the obtained integral equations by making use of a numerical technique. Once the structure of the kernel is defined, it then is approximated by an analytical expression of special kind so that the solution of the integral equation can be achieved analytically. This fact allows for construction of the solution in an analytical form, which is convenient for analysis of the mechanical effects concerned with arbitrarily presumed non-homogeneity of the material.

Keywords: contact problem, circular punch, arbitrarily-nonhomogeneous halfspace

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Authors: Arturo Maldonado

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In the iron ore mining industry, the intact strength of rock units is defined using the uniaxial compressive strength (UCS). This parameter is very important for the classification of shale materials, allowing the split between rock and cohesive soils based on the magnitude of UCS. For this research, it is assumed that UCS less than or equal to 1 MPa is representative of soils. Several researchers have anticipated that the magnitude of UCS reduces with weathering progression, also since UCS is a directional property, its magnitude depends upon the rock fabric orientation. Thus, the paper presents how the UCS of shales is affected by both weathering grade and bedding orientation. The mineralogy of shales has been defined using Hyper-spectral and chemical assays to define the mineral constituents of shale and other non-shale materials. Geological classification tools have been used to define distinct lithological types, and in this manner, the author uses mineralogical datasets to recognize and isolate shales from other rock types and develop tertiary plots for fresh and weathered shales. The mineralogical classification of shales has reduced the contamination of lithology types and facilitated the study of the physical factors affecting the intact strength of shales, like anisotropic strength due to bedding orientation. The analysis of mineralogical characteristics of shales is perhaps the most important contribution of this paper to other researchers who may wish to explore similar methods.

Keywords: rock mechanics, mineralogy, shales, weathering, anisotropy

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Authors: Jing Zhang

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To reduce the carbon footprint of mankind and become more sustainable is one of the major challenges in our era. Internet of Things (IoT) mainly resolves three problems: Things to Things (T2T), Human to Things, H2T), and Human to Human (H2H). Borrowing the classification of IoT, we can find carbon prints of industries also can be divided in these three ways. Therefore, monitoring the routes of generation and circulation of products may help calculate product carbon print. This paper does not consider any technique used by IoT itself, but the ideas of it look at the connection of products. Carbon prints are like a gene or mark of a product from raw materials to the final products, which never leave the products. The contribution of this paper is to combine the characteristics of IoT and the methodology of network science to find a way to calculate the product's carbon footprint. Life cycle assessment, LCA is a traditional and main tool to calculate the carbon print of products. LCA is a traditional but main tool, which includes three kinds.

Keywords: product carbon footprint, Internet of Things, network science, life cycle assessment

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Authors: Fang Gong

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Distance measures are an indispensable part of many instance-based learning (IBL) and machine learning (ML) algorithms. The value difference metrics (VDM) and inverted specific-class distance measure (ISCDM) are among the top-performing distance measures that address nominal attributes. VDM performs well in some domains owing to its simplicity and poorly in others that exist missing value and non-class attribute noise. ISCDM, however, typically works better than VDM on such domains. To maximize their advantages and avoid disadvantages, in this paper, a selection approach: a discriminative model for nominal attributes-based distance measures is proposed. More concretely, VDM and ISCDM are built independently on a training dataset at the training stage, and the most credible one is recorded for each training instance. At the test stage, its nearest neighbor for each test instance is primarily found by any of VDM and ISCDM and then chooses the most reliable model of its nearest neighbor to predict its class label. It is simply denoted as a discriminative distance measure (DDM). Experiments are conducted on the 34 University of California at Irvine (UCI) machine learning repository datasets, and it shows DDM retains the interpretability and simplicity of VDM and ISCDM but significantly outperforms the original VDM and ISCDM and other state-of-the-art competitors in terms of accuracy.

Keywords: distance measure, discriminative model, nominal attributes, nearest neighbor

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Authors: B. Atika, S. Lehmann, E. Wimmer

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The defense strategy is very common in the insect world. Defensive substances play a wide variety of functions for beetles, such as repellents, toxicants, insecticides, and antimicrobics. Beetles react to predators, invaders, and parasitic microbes with the release of toxic and repellent substances. Defensive substances are directed against a large array of potential target organisms or may function for boiling bombardment or as surfactants. Usually, Coleoptera biosynthesize and store their defensive compounds in a complex secretory organ, known as odoriferous defensive stink glands. The red flour beetle, Tribolium castaneum (Coleoptera: Tenebrionidae), uses these glands to produce antimicrobial p-benzoquinones and 1-alkenes. In the past, the morphology of stink gland has been studied in detail in tenebrionid beetles; however, very little is known about the genes that are involved in the production of gland secretion. In this study, we studied a subset of genes that are essential for the benzoquinone production in red flour beetle. In the first phase, we selected 74 potential candidate genes from a genome-wide RNA interference (RNAi) knockdown screen named 'iBeetle.' All these 74 candidate genes were functionally characterized by RNAi-mediated gene knockdown. Therefore, they were selected for a subsequent gas chromatography-mass spectrometry (GC-MS) analysis of secretion volatiles in respective RNAi knockdown glands. 33 of them were observed to alter the phenotype of stink gland. In the GC-MS analysis, 7 candidate genes were noted to display a strongly altered gland, in terms of secretion color and chemical composition, upon knockdown, showing their key role in the biosynthesis of gland secretion. Morphologically altered stink glands were found for odorant receptor and protein kinase superfamily. Subsequent GC-MS analysis of secretion volatiles revealed reduced benzoquinone levels in LIM domain, PDZ domain, PBP/GOBP family knockdowns and a complete lack of benzoquinones in the knockdown of sulfatase-modifying factor enzyme 1, sulfate transporter family. Based on stink gland transcriptome data, we analyzed the function of sulfatase-modifying factor enzyme 1 and sulfate transporter family via RNAi-mediated gene knockdowns, GC-MS, in situ hybridization, and enzymatic activity assays. Morphologically altered stink glands were noted in knockdown of both these genes. Furthermore, GC-MS analysis of secretion volatiles showed a complete lack of benzoquinones in the knockdown of these two genes. In situ hybridization showed that these two genes are expressed around the vesicle of certain subgroup of secretory stink gland cells. Enzymatic activity assays on stink gland tissue showed that these genes are involved in p-benzoquinone biosynthesis. These results suggest that sulfatase-modifying factor enzyme 1 and sulfate transporter family play a role specifically in benzoquinone biosynthesis in red flour beetles.

Keywords: Red Flour Beetle, defensive stink gland, benzoquinones, sulfate transporter, sulfatase-modifying factor enzyme 1

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Authors: Z. Giagkazoglou, D. Loukovitis, C. Gubili, A. Imsiridou

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Along with the increase in human population, demand for seafood has increased. Despite the strict labeling regulations that exist for most marketed species in the European Union, seafood substitution remains a persistent global issue. Food fraud occurs when food products are traded in a false or misleading way. Mislabeling occurs when one species is substituted and traded under the name of another, and it can be intentional or unintentional. Crustaceans are one of the most regularly consumed seafood in Greece. Shrimps, prawns, lobsters, crayfish, and crabs are considered a delicacy and can be encountered in a variety of market presentations (fresh, frozen, pre-cooked, peeled, etc.). With most of the external traits removed, products as such are susceptible to species substitution. DNA barcoding has proven to be the most accurate method for the detection of fraudulent seafood products. To our best knowledge, the DNA barcoding methodology is used for the first time in Greece, in order to investigate the labeling practices for crustacean products available in the market. A total of 100 tissue samples were collected from various retailers and markets across four Greek cities. In an effort to cover the highest range of products possible, different market presentations were targeted (fresh, frozen and cooked). Genomic DNA was extracted using the DNeasy Blood & Tissue Kit, according to the manufacturer's instructions. The mitochondrial gene selected as the target region of the analysis was the cytochrome c oxidase subunit I (COI). PCR products were purified and sequenced using an ABI 3500 Genetic Analyzer. Sequences were manually checked and edited using BioEdit software and compared against the ones available in GenBank and BOLD databases. Statistical analyses were conducted in R and PAST software. For most samples, COI amplification was successful, and species-level identification was possible. The preliminary results estimate moderate mislabeling rates (25%) in the identified samples. Mislabeling was most commonly detected in fresh products, with 50% of the samples in this category labeled incorrectly. Overall, the mislabeling rates detected by our study probably relate to some degree of unintentional misidentification, and lack of knowledge surrounding the legal designations by both retailers and consumers. For some species of crustaceans (i.e. Squila mantis) the mislabeling appears to be also affected by the local labeling practices. Across Greece, S. mantis is sold in the market under two common names, but only one is recognized by the country's legislation, and therefore any mislabeling is probably not profit-motivated. However, the substitution of the speckled shrimp (Metapenaus monoceros) for the distinct, giant river prawn (Macrobranchium rosenbergii), is a clear example of deliberate fraudulent substitution, aiming for profit. To our best knowledge, no scientific study investigating substitution and mislabeling rates in crustaceans has been conducted in Greece. For a better understanding of Greece's seafood market, similar DNA barcoding studies in other regions with increased touristic importance (e.g., the Greek islands) should be conducted. Regardless, the expansion of the list of species-specific designations for crustaceans in the country is advised.

Keywords: COI gene, food fraud, labelling control, molecular identification

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Authors: Aghamusa Azizov

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This study investigates the correlation between solar activity and sentiment in news media coverage, using a large-scale dataset of solar activity since 1750 and over 15 million articles from "The New York Times" dating from 1851 onwards. Employing Pearson's correlation coefficient and multiple Natural Language Processing (NLP) tools—TextBlob, Vader, and DistillBERT—the research examines the extent to which fluctuations in solar phenomena are reflected in the sentiment of historical news narratives. The findings reveal that the correlation between solar activity and media sentiment is generally negligible, suggesting a weak influence of solar patterns on the portrayal of events in news media. Notably, a moderate positive correlation was observed between the sentiments derived from TextBlob and Vader, indicating consistency across NLP tools. The analysis provides insights into the historical impact of solar activity on human affairs and highlights the importance of using multiple analytical methods to understand complex relationships in large datasets. The study contributes to the broader understanding of how extraterrestrial factors may intersect with media-reported events and underlines the intricate nature of interdisciplinary research in the data science and historical domains.

Keywords: solar activity correlation, media sentiment analysis, natural language processing, historical event patterns

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Authors: Muhammad Sohail Khan, Rehan Ali Shah

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The present paper applies the optimal homotopy perturbation method (OHPM) and the optimal homotopy asymptotic method (OHAM) introduced recently to obtain analytic approximations of the non-linear equations modeling the flow of polymer in case of wire coating of a corotational Maxwell fluid. Expression for the velocity field is obtained in non-dimensional form. Comparison of the results obtained by the two methods at different values of non-dimensional parameter l₁₀, reveal that the OHPM is more effective and easy to use. The OHPM solution can be improved even working in the same order of approximation depends on the choices of the auxiliary functions.

Keywords: corotational Maxwell model, optimal homotopy asymptotic method, optimal homotopy perturbation method, wire coating die

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Authors: Yahia Massinissa, Melakhessou Med Akram, Mezahdia Mehdi, Marref Salah Eddine

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Cytokines are natural proteins which act as true intercellular communication signals in immune and inflammatory responses. Reverse signaling pathways that activate cytokines help to regulate different functions at the target cell, causing its activation, its proliferation, the differentiation, its survival or death. It was shown that malfunctioning of the cytokine regulation, particularly over-expression, contributes to the onset and development of certain serious diseases such as chronic rheumatoid arthritis, Crohn's disease, psoriasis, lupus. The action mode of Kinoid® technology is based on the principle vaccine: The patient's immune system is activated so that it neutralizes itself and the factor responsible for the disease. When applied specifically to autoimmune diseases, therapeutic vaccination allows the body to neutralize cytokines (proteins) overproduced through a highly targeted stimulation of the immune system.

Keywords: cytokines, Kinoid tech, auto-immune diseases, vaccination

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Authors: Alaa Abdellatif, Gabrièle Breda

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Background. Advanced therapy medicinal products (ATMPs) are innovative therapies that mainly target orphan diseases and high unmet medical needs. ATMP includes gene therapy medicinal products (GTMP), somatic cell therapy medicinal products (CTMP), and tissue-engineered therapies (TEP). Since legislation opened the way in 2007, 25 ATMPs have been approved in the EU, which is about the same amount as the U.S. Food and Drug Administration. However, not all of the ATMPs that have been approved have successfully reached the market and retained their approval. Objectives. We aim to understand all the factors limiting the market access to very promising therapies in a systemic approach, to be able to overcome these problems, in the future, with scientific, regulatory and commercial innovations. Further to recent reviews that focus either on specific countries, products, or dimensions, we will address all the challenges faced by ATMP development today. Methodology. We used mixed methods and a multi-level approach for data collection. First, we performed an updated academic literature review on ATMP development and their scientific and market access challenges (papers published between 2018 and April 2023). Second, we analyzed industry feedback from cell and gene therapy webinars and white papers published by providers and pharmaceutical industries. Finally, we established a comparative analysis of the regulatory guidelines published by EMA and the FDA for ATMP approval. Results: The main challenges in bringing these therapies to market are the high development costs. Developing ATMPs is expensive due to the need for specialized manufacturing processes. Furthermore, the regulatory pathways for ATMPs are often complex and can vary between countries, making it challenging to obtain approval and ensure compliance with different regulations. As a result of the high costs associated with ATMPs, challenges in obtaining reimbursement from healthcare payers lead to limited patient access to these treatments. ATMPs are often developed for orphan diseases, which means that the patient population is limited for clinical trials which can make it challenging to demonstrate their safety and efficacy. In addition, the complex manufacturing processes required for ATMPs can make it challenging to scale up production to meet demand, which can limit their availability and increase costs. Finally, ATMPs face safety and efficacy challenges: dangerous adverse events of these therapies like toxicity related to the use of viral vectors or cell therapy, starting material and donor-related aspects. Conclusion. As a result of our mixed method analysis, we found that ATMPs face a number of challenges in their development, regulatory approval, and commercialization and that addressing these challenges requires collaboration between industry, regulators, healthcare providers, and patient groups. This first analysis will help us to address, for each challenge, proper and innovative solution(s) in order to increase the number of ATMPs approved and reach the patients

Keywords: advanced therapy medicinal products (ATMPs), product development, market access, innovation

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Authors: Chukwuma Anya, Mekwa Eme

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The term ‘’FORM’’ in design could be referred to as the combination of various shapes of different sizes and assembling them in appropriate positions to achieve a unique figure of high aesthetic value. A deduction from this definition is that forms contribute immensely to the actualization of aesthetics in a building. When these various shapes and figures are properly assembled, it may give rise to a concept in design. However some architects and other designers either misuse or abuse the use of these shapes, hence resulting to a design imbalance, lack of uniformity and expression. This academic work is designed to educate the public on the proper usage of some regular shapes like circles, rectangles, pentagons, hexagons, triangles etc, to achieve a unique form in design. By the end of this work, one should be able to assemble different shapes to express different emotions of the mind, such as peace, love, confusion, war, and unity. Some elements of design, such as balance, stability, functionality and aesthetics, will also be achieved even as the building maintains its unique form.

Keywords: aesthetics, form, balance, stability

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Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

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Authors: Morello Sara, Pederiva Sabina, Bianchi Manila, Martucci Francesca, Marchis Daniela, Decastelli Lucia

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Vegetables represent an integral part of a healthy diet due to their valuable nutritional properties and the growth in consumer demand in recent years is particularly remarkable for a diet rich in vitamins and micronutrients. However, plant-based products are involved in several food outbreaks connected to various sources of contamination and quite often, bacteria responsible for side effects showed high resistance to antibiotics. The abuse of antibiotics can be one of the main mechanisms responsible for increasing antibiotic resistance (AR). Plants grown for food use can be contaminated directly by spraying antibiotics on crops or indirectly by treatments with antibiotics due to the use of manure, which may contain both antibiotics and genes of antibiotic resistance (ARG). Antibiotic residues could represent a potential way of human health risk due to exposure through the consumption of plant-based foods. The presence of antibiotic-resistant bacteria might pose a particular risk to consumers. The present work aims to investigate through a multidisciplinary approach the occurrence of ARG by means of a biomolecular approach (PCR) and the prevalence of antibiotic residues using a multi residues LC-MS/MS method, both in different plant-based products. During the period from July 2020 to October 2021, a total of 74 plant samples (33 lettuces and 41 tomatoes) were collected from 57 farms located throughout the Piedmont area, and18 out of 74 samples (11 lettuces and 7 tomatoes) were selected to LC-MS/MS analyses. DNA extracted (ExtractME, Blirt, Poland) from plants used on crops and isolated bacteria were analyzed with 6 sets of end-point multiplex PCR (Qiagen, Germany) to detect the presence of resistance genes of the main antibiotic families, such as tet genes (tetracyclines), bla (β-lactams) and mcr (colistin). Simultaneous detection of 43 molecules of antibiotics belonging to 10 different classes (tetracyclines, sulphonamides, quinolones, penicillins, amphenicols, macrolides, pleuromotilines, lincosamides, diaminopyrimidines) was performed using Exion LC system AB SCIEX coupled to a triple quadrupole mass spectrometer QTRAP 5500 from AB SCIEX. The PCR assays showed the presence of ARG in 57% (n=42): tetB (4.8%; n=2), tetA (9.5%; n=4), tetE (2.4%; n=1), tetL (12%; n=5), tetM (26%; n=11), blaSHV (21.5%; n=9), blaTEM (4.8%; n =2) and blaCTX-M (19%; n=8). In none of the analyzed samples was the mcr gene responsible for colistin resistance detected. Results obtained from LC-MS/MS analyses showed that none of the tested antibiotics appear to exceed the LOQ (100 ppb). Data obtained confirmed the presence of bacterial populations containing antibiotic resistance determinants such as tet gene (tetracycline) and bla genes (beta-lactams), widely used in human medicine, which can join the food chain and represent a risk for consumers, especially with raw products. The presence of traces of antibiotic residues in vegetables, in concentration below the LOQ of the LC-MS/MS method applied, cannot be excluded. In conclusion, traces of antibiotic residues could be a health risk to the consumer due to potential involvement in the spread of AR. PCR represents a useful and effective approach to characterize and monitor AR carried by bacteria from the entire food chain.

Keywords: plant-based products, ARG, PCR, antibiotic residues

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Huang Bai-Cheng

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When deploying the Oriented Fast and Rotated Binary Robust Independent Elementary Feature (BRIEF) (ORB) extraction algorithm on field-programmable gate arrays (FPGA), the access of global storage for 31×31 pixel patches of the features has become the bottleneck of the system efficiency. Therefore, a feature zone strategy has been proposed. Zones are searched as features are detected. Pixels around the feature zones are extracted from global memory and distributed into patches corresponding to feature coordinates. The proposed FPGA structure is targeted on a Xilinx FPGA development board of Zynq UltraScale+ series, and multiple datasets are tested. Compared with the streaming pixel patch extraction method, the proposed architecture obtains at least two times acceleration consuming extra 3.82% Flip-Flops (FFs) and 7.78% Look-Up Tables (LUTs). Compared with the non-streaming one, the proposed architecture saves 22.3% LUT and 1.82% FF, causing a latency of only 0.2ms and a drop in frame rate for 1. Compared with the related works, the proposed strategy and hardware architecture have the superiority of keeping a balance between FPGA resources and performance.

Keywords: feature extraction, real-time, ORB, FPGA implementation

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Authors: Sneha Bhatnagar, Sachin Bhatnagar

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Denim presently is the most widely accepted textile product and shows its hold even in future with its growing popularity. Denim today is no longer restricted to only a pair of jeans but has diversified in all different product categories. Although denim is considered as an expression of youth and demonstrates durability and comfort, denim raises issues of sustainability. Through an exploratory research, the researcher aims at addressing the possibilities of denim fashion promoting environmental sustainability by means of creativity, awareness, recycle and artisan appreciation. It also touches on how eco conscious fashion brands involve in development in terms of ideation and modification of denim as a fabric or product into diversified sustainable fashion. In conclusion, it is shown that blue denim fashion continues to evolve and shows eventual transformation in becoming green denim in future, nurturing values of both quality and sustainability.

Keywords: arts, craft, creativity, denim, fashion, recycle, sustainability

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Sandy Black, Calum McLaughlin, Alessandro Pranzitelli, Marc Laing

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Multiphase flow structures of two-phase multicomponent fluids were experimentally investigated in a large diameter high-pressure pipeline up to 130 bar at TÜV SÜD’s National Engineering Laboratory Advanced Multiphase Facility. One of the main objectives of the experimental test campaign was to evaluate the impact of pressure on multiphase flow patterns as much of the existing information is based on low-pressure measurements. The experiments were performed in a horizontal and vertical orientation in both 4-inch and 6-inch pipework using nitrogen, ExxsolTM D140 oil, and a 6% aqueous solution of NaCl at incremental pressures from 10 bar to 130 bar. To visualise the detailed structure of the flow of the entire cross-section of the pipe, a fast response X-ray tomography system was used. A wide range of superficial velocities from 0.6 m/s to 24.0 m/s for gas and 0.04 m/s and 6.48 m/s for liquid was examined to evaluate different flow regimes. The results illustrated the suppression of instabilities between the gas and the liquid at the measurement location and that intermittent or slug flow was observed less frequently as the pressure was increased. CFD modellings of low and high-pressure simulations were able to successfully predict the likelihood of intermittent flow; however, further tuning is necessary to predict the slugging frequency. The dataset generated is unique as limited datasets exist above 100 bar and is of considerable value to multiphase flow specialists and numerical modellers.

Keywords: computational fluid dynamics, high pressure, multiphase, X-ray tomography

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Authors: Foad Alzoughool

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Conflicting studies on the association between the rs5219 polymorphism and type 2 diabetes, some studies have confirmed a strong relationship between this variant and type2 diabetes, on the other hand, many studies denied the existence of this association. This study aimed to provide evidence about whether the rs5219 polymorphism has or hasn't a role as a risk factor for diabetes and meta-analysis to investigate the role of the control age group in the association. Genotyping of the rs5219 polymorphism was performed in a cohort of 266 healthy elderly subjects with a mean age (60.2 ± 5.1) with no history of diabetes (HbA1c < 6%) using standard Sanger sequencing methods. Lys/Lys alleles were detected in 20 persons (7.5%), Lys/Glu alleles in 96 persons (36.1%), and Glu/Glu in 150 persons (56.4%). The genotype distribution was consistent with Hardy–Weinberg equilibrium (P =0.7). Meta-analysis notably indicates no association between rs5219 polymorphism and type 2 diabetes in all studies used the younger age of the control group compared to the patient's age. In conclusion, our study sheds light on the importance of age factor among the control group recruited in case-control studies.

Keywords: Type 2 diabetes, rs5219 polymorphism, E23K, KCNJ11 gene

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Authors: Joanna Pietrzak, Anna Stefanska, Wieslaw Rokicki

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Contemporary high-rise buildings constructed in recent years are often tremendous examples of original and unique architectural forms, being at the same time the affirmation of technical and technological progress accomplishments. The search for more efficient, sophisticated generations of structures also concerns the shaping of high-quality details. The concept of structural detail designing is connected with the rationalization of engineering solutions as well as through the optimisation and reduction of used material. Contemporary structural detail perceived through the development of building technologies is often a very aesthetic technical and material solution, which significantly influences the visual perception of architecture. Structural details are more often seen in shaping the forms of high-rise buildings, which are erected in many culturally different countries.

Keywords: aesthetic expression, high-rise buildings, structural detail, tall buildings

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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

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Authors: Gürkan Dağbaşı

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Translation is a vitally important activity like as the expression the thought and emotions of humanbeing, providing reciprocal cultural transfer, shaping future by establishing a connection with the past, and like as being exist in an other language. Translation is also an important instrument providing cross-cultural coalescence between nations. Although the first translations from Arabic to Turkish was restricted to only religious texts, over time, the importance of translation was found out via translations of works about literature. Later on, some literature genres like novel and poems were also translated from Arabic to Turkish. Works of many men of Arabic literature were translated to Turkish, including Nejib Mahfuz, owner of Nobel Prize, Tawfiq al-Hakim, Adonis, Gibran Khalil Gibran and etc. In this study, novels and poems translated from Arabic to Turkish between 1980-2015 years are examined.

Keywords: poem, novel, Arabic, translation

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Authors: Georgina Cherry, Taranpreet Rai, Luke Boyden, Sitira Williams, Andrea Wright, Richard Brown, Viva Chu, Alasdair Cook, Kevin Wells

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Estimating population-level burden, abilities of pet-parents to identify disease and demand for veterinary services worldwide is challenging. The purpose of this study is to compare a feline pruritus survey with social media listening (SML) data discussing this condition. Surveys are expensive and labour intensive to analyse, but SML data is freeform and requires careful filtering for relevancy. This study considers data from a survey of owner-observed symptoms of 156 pruritic cats conducted using Pet Parade® and SML posts collected through web-scraping to gain insights into the characterisation and management of feline pruritus. SML posts meeting a feline body area, behaviour and symptom were captured and reviewed for relevance representing 1299 public posts collected from 2021 to 2023. The survey involved 1067 pet-parents who reported on pruritic symptoms in their cats. Among the observed cats, approximately 18.37% (n=196) exhibited at least one symptom. The most frequently reported symptoms were hair loss (9.2%), bald spots (7.3%) and infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin (8.2%). Notably, bald spots were the primary symptom reported for short-haired cats, while other symptoms were more prevalent in medium and long-haired cats. Affected body areas, according to pet-parents, were primarily the head, face, chin, neck (27%), and the top of the body, along the spine (22%). 35% of all cats displayed excessive behaviours consistent with pruritic skin disease. Interestingly, 27% of these cats were perceived as non-symptomatic by their owners, suggesting an under-identification of itch-related signs. Furthermore, a significant proportion of symptomatic cats did not receive any skin disease medication, whether prescribed or over the counter (n=41). These findings indicate a higher incidence of pruritic skin disease in cats than recognized by pet owners, potentially leading to a lack of medical intervention for clinically symptomatic cases. The comparison between the survey and social media listening data revealed bald spots were reported in similar proportions in both datasets (25% in the survey and 28% in SML). Infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin accounted for 31% of symptoms in the survey, whereas it represented 53% of relevant SML posts (excluding bumpy skin). Abnormal licking or chewing behaviours were mentioned by pet-parents in 40% of SML posts compared to 38% in the survey. The consistency in the findings of these two disparate data sources, including a complete overlap in affected body areas for the top 80% of social media listening posts, indicates minimal biases in each method, as significant biases would likely yield divergent results. Therefore, the strong agreement across pruritic symptoms, affected body areas, and reported behaviours enhances our confidence in the reliability of the findings. Moreover, the small differences identified between the datasets underscore the valuable insights that arise from utilising multiple data sources. These variations provide additional depth in characterising and managing feline pruritus, allowing for more comprehensive understanding of the condition. By combining survey data and social media listening, researchers can obtain a nuanced perspective and capture a wider range of experiences and perspectives, supporting informed decision-making in veterinary practice.

Keywords: social media listening, feline pruritus, surveys, felines, cats, pet owners

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Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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Authors: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

Procedia PDF Downloads 44