Search results for: housing characteristics

Authors: Kennedy Zinn, Chris Anderson

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Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

Procedia PDF Downloads 132

Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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Authors: Ekin Esen, Mohammad Alipour, Riza Kizilel

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Rechargeable lithium-ion batteries have been replacing lead-acid batteries for the last decade due to their outstanding properties such as high energy density, long shelf life, and almost no memory effect. Besides these, being very light compared to lead acid batteries has gained them their dominant place in the portable electronics market, and they are now the leading candidate for electric vehicles (EVs) and hybrid electric vehicles (HEVs). However, their performance strongly depends on temperature, and this causes some inconveniences for their utilization in extreme temperatures. Since weather conditions vary across the globe, this situation limits their utilization for EVs and HEVs and makes a thermal management system obligatory for the battery units. The objective of this study is to understand thermal characteristics of Li-ion battery modules for various operation conditions and design a thermal management system to enhance battery performance in EVs and HEVs. In the first part of our study, we investigated thermal behavior of commercially available pouch type 20Ah LiFePO₄ (LFP) cells under various conditions. Main parameters were chosen as ambient temperature and discharge current rate. Each cell was charged and discharged at temperatures of 0°C, 10°C, 20°C, 30°C, 40°C, and 50°C. The current rate of charging process was 1C while it was 1C, 2C, 3C, 4C, and 5C for discharge process. Temperatures of 7 different points on the cells were measured throughout charging and discharging with N-type thermocouples, and a detailed temperature profile was obtained. In the second part of our study, we connected 4 cells in series by clinching and prepared 4S1P battery modules similar to ones in EVs and HEVs. Three reference points were determined according to the findings of the first part of the study, and a thermocouple is placed on each reference point on the cells composing the 4S1P battery modules. In the end, temperatures of 6 points in the module and 3 points on the top surface were measured and changes in the surface temperatures were recorded for different discharge rates (0.2C, 0.5C, 0.7C, and 1C) at various ambient temperatures (0°C – 50°C). Afterwards, aluminum plates with channels were placed between the cells in the 4S1P battery modules, and temperatures were controlled with airflow. Airflow was provided with a regular compressor, and the effect of flow rate on cell temperature was analyzed. Diameters of the channels were in mm range, and shapes of the channels were determined in order to make the cell temperatures uniform. Results showed that the designed thermal management system could help keeping the cell temperatures in the modules uniform throughout charge and discharge processes. Other than temperature uniformity, the system was also beneficial to keep cell temperature close to the optimum working temperature of Li-ion batteries. It is known that keeping the temperature at an optimum degree and maintaining uniform temperature throughout utilization can help obtaining maximum power from the cells in battery modules for a longer time. Furthermore, it will increase safety by decreasing the risk of thermal runaways. Therefore, the current study is believed to be beneficial for wider use of Li batteries for battery modules of EVs and HEVs globally.

Keywords: lithium ion batteries, thermal management system, electric vehicles, hybrid electric vehicles

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Authors: Mitsuhiro Hirai, Satoshi Ajito, Nobutaka Shimizu, Noriyuki Igarashi, Hiroki Iwase, Shinichi Takata

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Sugars and polyols are known to be bioprotectants preventing such as protein denaturation and enzyme deactivation and widely used as a nontoxic additive in various industrial and medical products. The mechanism of their protective actions has been explained by specific bindings between biological components and additives, changes in solvent viscosities, and surface tension and free energy changes upon transfer of those components into additive solutions. On the other hand, some organisms having tolerances against extreme environment produce stress proteins and/or accumulate sugars in cells, which is called cryptobiosis. In particular, trehalose has been drawing attention relevant to cryptobiosis under external stress such as high or low temperature, drying, osmotic pressure, and so on. The function of cryptobiosis by trehalose has been explained relevant to the restriction of the intra-and/or-inter-molecular movement by vitrification or from the replacement of water molecule by trehalose. Previous results suggest that the structure and interaction between sugar and water are a key determinant for understanding cryptobiosis. Recently, we have shown direct evidence that the protein hydration (solvation) and structural stability against chemical and thermal denaturation significantly depend on sugar species and glycerol. Sugar and glycerol molecules tend to be preferentially or weakly excluded from the protein surface and preserved the native protein hydration shell. Due to the protective action of the protein hydration shell by those molecules, the protein structure is stabilized against chemical (guanidinium chloride) and thermal denaturation. The protective action depends on sugar species. To understand the above trend and difference in detail, it is essentially important to clarify the characteristics of solutions containing those additives. In this study, by using wide-angle X-ray scattering technique covering a wide spatial region (~3-120 Å), we have clarified structures of sugar solutions with the concentration from 5% w/w to 65% w/w. The sugars measured in the present study were monosaccharides (glucose, fructose, mannose) and disaccharides (sucrose, trehalose, maltose). Due to observed scattering data with a wide spatial resolution, we have succeeded in obtaining information on the internal structure of individual sugar molecules and on the correlation between them. Every sugar gradually shortened the average inter-molecular distance as the concentration increased. The inter-molecular interaction between sugar molecules was essentially showed an exclusive tendency for every sugar, which appeared as the presence of a repulsive correlation hole. This trend was more weakly seen for trehalose compared to other sugars. The intermolecular distance and spread of individual molecule clearly showed the dependence of sugar species. We will discuss the relation between the characteristic of sugar solution and its protective action of biological materials.

Keywords: hydration, protein, sugar, X-ray scattering

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Authors: Dustin Schöder

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The potential benefits of the utilization of highly automated and autonomous trucks in logistics operations are the subject of interest to the entire logistics industry. The benefits of the use of these new technologies were scientifically investigated and implemented in roadmaps. So far, reliable data and experiences from real life use cases are still limited. A German research consortium of both academics and industry developed a highly automated (SAE level 4) vehicle for yard operations at railports and container depots. After development and testing, a several month field test at the DUSS Terminal in Ulm-Dornstadt (Germany) and the nearby DB Intermodal Services Container Depot in Ulm-Dornstadt was conducted. The truck was piloted in a shuttle service between both sites. In a holistic automation approach, the vehicle was integrated into a digital communication platform so that the truck could move autonomously without a driver and his manual interactions with a wide variety of stakeholders. The main goal is to investigate the effects of highly automated trucks in the key processes of container loading, unloading and container relocation on holistic railport yard operation. The field test data were used to investigate changes in process efficiency of key processes of railport and container yard operations. Moreover, effects on the capacity utilization and potentials for smothering peak workloads were analyzed. The results state that process efficiency in the piloted use case was significantly higher. The reason for that could be found in the digitalized data exchange and automated dispatch. However, the field test has shown that the effect is greatly varying depending on the ratio of highly automated and manual trucks in the yard as well as on the congestion level in the loading area. Furthermore, the data confirmed that under the right conditions, the capacity utilization of highly automated trucks could be increased. In regard to the potential for smothering peak workloads, no significant findings could be made based on the limited requirements and regulations of railway operation in Germany. In addition, an empirical survey among railport managers, operational supervisors, innovation managers and strategists (n=15) within the logistics industry in Germany was conducted. The goal was to identify key characteristics of future railports and terminals as well as requirements that railports will have to meet in the future. Furthermore, the railport processes where automation and autonomization make the greatest impact, as well as hurdles and challenges in the introduction of new technologies, have been surveyed. Hence, further potential use cases of highly automated and autonomous applications could be identified, and expectations have been mapped. As a result, a highly detailed and practice-based roadmap towards a ‘terminal 4.0’ was developed.

Keywords: highly automated driving, autonomous driving, SAE level 4, railport operations, container depot, intermodal logistics, potentials of autonomization

Procedia PDF Downloads 80

Authors: Lesibana Rafapa

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Accounts exist of circumcision-anchored cultural initiation in central Africa, East Africa, Southern Africa, North Africa, and West Africa -straddling states like Botswana, Kenya, Lesotho, Malawi, Senegal, South Africa, Zambia, and Zimbabwe. This attests to the continent-wide spread of this cultural practice. In this paper, the writer relates the cultural aspect of circumcision-subsuming initiation among black African cultural groups across the continent to the notion that African cultures are varied yet subscribe to a common central concept. The premise of the paper is that the common practice of initiation for both male and female children that have to be initiated by adults to the tradition and customs of a people coincides with such a central concept. The practice of traditional initiation is as broad as to encompass aspects of spirituality, morality, and social organisation, in the nature of the central concept of which it is a trans-sectional part. Cultural initiation, sometimes referred to as traditional circumcision, constitutes culture-determined rites of passage for the initiates. The study’s aim, the findings of which are presented in this paper, was to probe gender equality in the development and promotion of the cultural practice of initiation. The researcher intended to demonstrate how in South Africa, female circumcision is treated equally or marginalised in efforts of the democratic government to regulate and strengthen the practice of circumcision as part of its broader liberation programme meant to reverse politico-cultural bondage experienced during apartheid rule that the present black regime helped bring to an end. It is argued that the failure to regard female circumcision as equal to its male counterpart is a travesty of the black government’s legislation and policies espousing equality and the protection and empowerment of vulnerable and previously marginalised population groups that include black women. The writer did a desk-top study of the history and characteristics of female circumcision among the black Northern Sotho, VaTsonga, and VhaVenda cultural groups of the Limpopo Province, stretching north to the border of South Africa with Zimbabwe, as well as literature on how political and other authorities exert efforts to preserve and empower the practice. The findings were that male initiation is foregrounded and totalised to represent the practice of initiation as a whole, at the expense of its female counterpart facing marginalisation and unequal regard. It is outlined in this paper how such impoverishment of an otherwise woman-empowering cultural practice deprives hitherto black cultures that suffered brutal repression during apartheid of a fuller recovery much needed in the democratic era. The writer applies some aspects of postcolonial theory and some tropes of feminism in the discussion of an uneven status of cultural circumcision at the hands of present day powers that be.

Keywords: African cultures, female circumcision, gender equality, women empowerment

Procedia PDF Downloads 185

Authors: Brian Yulianto, Syachrial, Saeful Aziz, Anggita Clara Shinta

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Indonesia, with a population of about two hundred and fifty million people in quantity, indicates the outstanding wealth of human resources. Hundreds of millions of the population scattered in various communities in various regions in Indonesia with the different characteristics of economic, social and unique culture. Broadly speaking, the community in Indonesia is divided into two classes, namely urban communities and rural communities. The rural communities characterized by low potential and management of natural and human resources, limited access of development, and lack of social and economic infrastructure, and scattered and isolated population. West Java is one of the provinces with the largest population in Indonesia. Based on data from the Central Bureau of Statistics in 2015 the number of population in West Java reached 46.7096 million souls spread over 18 districts and 9 cities. The big difference in geographical and social conditions of people in West Java from one region to another, especially the south to the north causing the gap is high. It is closely related to the flow of investment to promote the area. Poverty and underdevelopment are the classic problems that occur on a massive scale in the region as the effects of inequity in development. South Cianjur and Tasikmalaya area South became one of the portraits area where the existing potential has not been capable of prospering society. Tri Dharma College not only define the College as a pioneer implementation of education and research to improve the quality of human resources but also demanded to be a pioneer in the development through the concept of public service. Bandung Institute of Technology as one of the institutions of higher education to implement community service system through collaborative community work program "one of the university community" as one approach to developing villages. The program is based Community Service, where students are not only required to be able to take part in community service, but also able to develop a community development strategy that is comprehensive and integrity in cooperation with government agencies and non-government related as a real form of effort alignment potential, position and role from various parties. Areas of western Java in particular have high poverty rates and disparity. On the other hand, there are three fundamental pillars in the development of rural communities, namely economic development, community development, and the integrated infrastructure development. These pillars require the commitment of all components of community, including the students and colleges for upholding success. College’s community program is one of the approaches in the development of rural communities. ITB is committed to implement as one form of student community service as community-college programs that integrate all elements of the community which is called Kuliah Kerja Nyata-Thematic.

Keywords: development in rural area, collaborative, student community service, Kuliah Kerja Nyata-Thematic ITB

Procedia PDF Downloads 225

Authors: Angelis P. Barlampas

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Learning Objectives: The purpose of this study is to inform briefly the reader about the applications of AI in chest radiology. Background: Currently, there are 190 FDA-approved radiology AI applications, with 42 (22%) pertaining specifically to thoracic radiology. Imaging findings OR Procedure details Aids of AI in chest radiology1: Detects and segments pulmonary nodules. Subtracts bone to provide an unobstructed view of the underlying lung parenchyma and provides further information on nodule characteristics, such as nodule location, nodule two-dimensional size or three dimensional (3D) volume, change in nodule size over time, attenuation data (i.e., mean, minimum, and/or maximum Hounsfield units [HU]), morphological assessments, or combinations of the above. Reclassifies indeterminate pulmonary nodules into low or high risk with higher accuracy than conventional risk models. Detects pleural effusion . Differentiates tension pneumothorax from nontension pneumothorax. Detects cardiomegaly, calcification, consolidation, mediastinal widening, atelectasis, fibrosis and pneumoperitoneum. Localises automatically vertebrae segments, labels ribs and detects rib fractures. Measures the distance from the tube tip to the carina and localizes both endotracheal tubes and central vascular lines. Detects consolidation and progression of parenchymal diseases such as pulmonary fibrosis or chronic obstructive pulmonary disease (COPD).Can evaluate lobar volumes. Identifies and labels pulmonary bronchi and vasculature and quantifies air-trapping. Offers emphysema evaluation. Provides functional respiratory imaging, whereby high-resolution CT images are post-processed to quantify airflow by lung region and may be used to quantify key biomarkers such as airway resistance, air-trapping, ventilation mapping, lung and lobar volume, and blood vessel and airway volume. Assesses the lung parenchyma by way of density evaluation. Provides percentages of tissues within defined attenuation (HU) ranges besides furnishing automated lung segmentation and lung volume information. Improves image quality for noisy images with built-in denoising function. Detects emphysema, a common condition seen in patients with history of smoking and hyperdense or opacified regions, thereby aiding in the diagnosis of certain pathologies, such as COVID-19 pneumonia. It aids in cardiac segmentation and calcium detection, aorta segmentation and diameter measurements, and vertebral body segmentation and density measurements. Conclusion: The future is yet to come, but AI already is a helpful tool for the daily practice in radiology. It is assumed, that the continuing progression of the computerized systems and the improvements in software algorithms , will redder AI into the second hand of the radiologist.

Keywords: artificial intelligence, chest imaging, nodule detection, automated diagnoses

Procedia PDF Downloads 72

Authors: R. P. Hewawasam, M. H. A. D. de Silva, M. A. G. Iresha

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Obesity is associated with an increased risk of developing insulin resistance. Insulin resistance often progresses to type-2 diabetes mellitus and is linked to a wide variety of other pathophysiological features including hypertension, hyperlipidemia, atherosclerosis (metabolic syndrome) and polycystic ovarian syndrome. Macrosomia is common in infants born to not only women with gestational diabetes mellitus but also non-diabetic obese women. During the past two decades, obesity in children and adolescents has risen significantly in Asian populations including Sri Lanka. There is increasing evidence to believe that infants who are born large for gestational age (LGA) are more likely to be obese in childhood. It is also established from previous studies that Asian populations have higher percentage body fat at a lower body mass index compared to Caucasians. High leptin levels in cord blood have been reported to correlate with fetal adiposity at birth. Previous studies have also shown that cord blood C-peptide and insulin levels are significantly and positively correlated with birth weight. Therefore, the objective of this preliminary study was to determine the relationship between parameters of fetal insulin resistance such as leptin, C-peptide and insulin and the birth weight of the newborn in a study population in Southern Sri Lanka. Umbilical cord blood was collected from 90 newborns and the concentration of insulin, leptin, and C-peptide were measured by ELISA technique. Birth weight, length, occipital frontal, chest, hip and calf circumferences of newborns were measured and characteristics of the mother such as age, height, weight before pregnancy and weight gain were collected. The relationship between insulin, leptin, C-peptide, and anthropometrics were assessed by Pearson’s correlation while the Mann-Whitney U test was used to assess the differences in cord blood leptin, C-peptide, and insulin levels between groups. A significant difference (p < 0.001) was observed between the insulin levels of infants born LGA (18.73 ± 0.64 µlU/ml) and AGA (13.08 ± 0.43 µlU/ml). Consistently, A significant increase in concentration (p < 0.001) was observed in C-peptide levels of infants born LGA (9.32 ± 0.77 ng/ml) compared to AGA (5.44 ± 0.19 ng/ml). Cord blood leptin concentration of LGA infants (12.67 ng/mL ± 1.62) was significantly higher (p < 0.001) compared to the AGA infants (7.10 ng/mL ± 0.97). Significant positive correlations (p < 0.05) were observed among cord leptin levels and the birth weight, pre-pregnancy maternal weight and BMI between the infants of AGA and LGA. Consistently, a significant positive correlation (p < 0.05) was observed between the birth weight and the C peptide concentration. Significantly high concentrations of leptin, C-peptide and insulin levels in the cord blood of LGA infants suggest that they may be involved in regulating fetal growth. Although previous studies suggest comparatively high levels of body fat in the Asian population, values obtained in this study are not significantly different from values previously reported from Caucasian populations. According to this preliminary study, maternal pre-pregnancy BMI and weight may contribute as significant indicators of cord blood parameters of insulin resistance and possibly the birth weight of the newborn.

Keywords: large for gestational age, leptin, C-peptide, insulin

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Authors: Mindaugas Liaudanskas, Darius Kviklys, Kristina Zymonė, Raimondas Raudonis, Jonas Viškelis, Norbertas Uselis, Pranas Viškelis, Valdimaras Janulis

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Apples are among the most commonly consumed fruits in the world. Based on data from the year 2014, approximately 84.63 million tons of apples are grown per annum. Apples are widely used in food industry to produce various products and drinks (juice, wine, and cider); they are also used unprocessed. Apples in human diet are an important source of different groups of biological active compounds that can positively contribute to the prevention of various diseases. They are a source of various biologically active substances – especially vitamins, organic acids, micro- and macro-elements, pectins, and phenolic, triterpenic, and other compounds. Triterpenic compounds, which are characterized by versatile biological activity, are the biologically active compounds found in apples that are among the most promising and most significant for human health. A specific analytical procedure including sample preparation and High Performance Liquid Chromatography (HPLC) analysis was developed, optimized, and validated for the detection of triterpenic compounds in the samples of different apples, their peels, and flesh from widespread apple cultivars 'Aldas', 'Auksis', 'Connel Red', 'Ligol', 'Lodel', and 'Rajka' grown in Lithuanian climatic conditions. The conditions for triterpenic compound extraction were optimized: the solvent of the extraction was 100% (v/v) acetone, and the extraction was performed in an ultrasound bath for 10 min. Isocratic elution (the eluents ratio being 88% (solvent A) and 12% (solvent B)) for a rapid separation of triterpenic compounds was performed. The validation of the methodology was performed on the basis of the ICH recommendations. The following characteristics of validation were evaluated: the selectivity of the method (specificity), precision, the detection and quantitation limits of the analytes, and linearity. The obtained parameters values confirm suitability of methodology to perform analysis of triterpenic compounds. Using the optimised and validated HPLC technique, four triterpenic compounds were separated and identified, and their specificity was confirmed. These compounds were corosolic acid, betulinic acid, oleanolic acid, and ursolic acid. Ursolic acid was the dominant compound in all the tested apple samples. The detected amount of betulinic acid was the lowest of all the identified triterpenic compounds. The greatest amounts of triterpenic compounds were detected in whole apple and apple peel samples of the 'Lodel' cultivar, and thus apples and apple extracts of this cultivar are potentially valuable for use in medical practice, for the prevention of various diseases, for adjunct therapy, for the isolation of individual compounds with a specific biological effect, and for the development and production of dietary supplements and functional food enriched in biologically active compounds. Acknowledgements. This work was supported by a grant from the Research Council of Lithuania, project No. MIP-17-8.

Keywords: apples, HPLC, triterpenic compounds, validation

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Authors: Elham Bagheri, Yalda Mohsenzadeh

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Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.

Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

Procedia PDF Downloads 111

Authors: Danjuma Bawa

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This paper aimed at exploring the capabilities of Location-Allocation model in complementing the strides of the existing physical planning models in the location and distribution of facilities for regional consumption. The paper was designed to provide a blueprint to the Nigerian government and other donor agencies especially the Fertilizer Distribution Initiative (FDI) by the federal government for the revitalization of the terrorism ravaged regions. Theoretical underpinnings of central place theory related to spatial distribution, interrelationships, and threshold prerequisites were reviewed. The study showcased how Location-Allocation Model (L-AM) alongside Central Place Theory (CPT) was applied in Geographic Information System (GIS) environment to; map and analyze the spatial distribution of settlements; exploit their physical and economic interrelationships, and to explore their hierarchical and opportunistic influences. The study was purely spatial qualitative research which largely used secondary data such as; spatial location and distribution of settlements, population figures of settlements, network of roads linking them and other landform features. These were sourced from government ministries and open source consortium. GIS was used as a tool for processing and analyzing such spatial features within the dictum of CPT and L-AM to produce a comprehensive spatial digital plan for equitable and judicious location and distribution of fertilizer deports in the study area in an optimal way. Population threshold was used as yardstick for selecting suitable settlements that could stand as service centers to other hinterlands; this was accomplished using the query syntax in ArcMapTM. ArcGISTM’ network analyst was used in conducting location-allocation analysis for apportioning of groups of settlements around such service centers within a given threshold distance. Most of the techniques and models ever used by utility planners have been centered on straight distance to settlements using Euclidean distances. Such models neglect impedance cutoffs and the routing capabilities of networks. CPT and L-AM take into consideration both the influential characteristics of settlements and their routing connectivity. The study was undertaken in two terrorism ravaged Local Government Areas of Adamawa state. Four (4) existing depots in the study area were identified. 20 more depots in 20 villages were proposed using suitability analysis. Out of the 300 settlements mapped in the study area about 280 of such settlements where optimally grouped and allocated to the selected service centers respectfully within 2km impedance cutoff. This study complements the giant strides by the federal government of Nigeria by providing a blueprint for ensuring proper distribution of these public goods in the spirit of bringing succor to these terrorism ravaged populace. This will ardently at the same time help in boosting agricultural activities thereby lowering food shortage and raising per capita income as espoused by the government.

Keywords: central place theory, GIS, location-allocation, network analysis, urban and regional planning, welfare economics

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Authors: Xuechun Kan, Dongdong Li, Fan Li, Peidang Liu

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Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer with a poor prognosis, and radiotherapy is one of the main treatment methods. However, due to the obvious resistance of tumor cells to radiotherapy, high dose of ionizing radiation is required during radiotherapy, which causes serious damage to normal tissues near the tumor. Therefore, how to improve radiotherapy resistance and enhance the specific killing of tumor cells by radiation is a hot issue that needs to be solved in clinic. Recent studies have shown that silver-based nanoparticles have strong radiosensitization, and silver nanoclusters (AgNCs) also provide a broad prospect for tumor targeted radiosensitization therapy due to their ultra-small size, low toxicity or non-toxicity, self-fluorescence and strong photostability. Aptamer 5TR1 is a 25-base oligonucleotide aptamer that can specifically bind to mucin-1 highly expressed on the membrane surface of TNBC 4T1 cells, and can be used as a highly efficient tumor targeting molecule. In this study, AgNCs were synthesized by DNA template based on 5TR1 aptamer (NC-T5-5TR1), and its role as a targeted radiosensitizer in TNBC radiotherapy was investigated. The optimal DNA template was first screened by fluorescence emission spectroscopy, and NC-T5-5TR1 was prepared. NC-T5-5TR1 was characterized by transmission electron microscopy, ultraviolet-visible spectroscopy and dynamic light scattering. The inhibitory effect of NC-T5-5TR1 on cell activity was evaluated using the MTT method. Laser confocal microscopy was employed to observe NC-T5-5TR1 targeting 4T1 cells and verify its self-fluorescence characteristics. The uptake of NC-T5-5TR1 by 4T1 cells was observed by dark-field imaging, and the uptake peak was evaluated by inductively coupled plasma mass spectrometry. The radiation sensitization effect of NC-T5-5TR1 was evaluated through cell cloning and in vivo anti-tumor experiments. Annexin V-FITC/PI double staining flow cytometry was utilized to detect the impact of nanomaterials combined with radiotherapy on apoptosis. The results demonstrated that the particle size of NC-T5-5TR1 is about 2 nm, and the UV-visible absorption spectrum detection verifies the successful construction of NC-T5-5TR1, and it shows good dispersion. NC-T5-5TR1 significantly inhibited the activity of 4T1 cells and effectively targeted and fluoresced within 4T1 cells. The uptake of NC-T5-5TR1 reached its peak at 3 h in the tumor area. Compared with AgNCs without aptamer modification, NC-T5-5TR1 exhibited superior radiation sensitization, and combined radiotherapy significantly inhibited the activity of 4T1 cells and tumor growth in 4T1-bearing mice. The apoptosis level of NC-T5-5TR1 combined with radiation was significantly increased. These findings provide important theoretical and experimental support for NC-T5-5TR1 as a radiation sensitizer for TNBC.

Keywords: 5TR1 aptamer, silver nanoclusters, radio sensitization, triple-negative breast cancer

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Authors: Abida Mariam, Anwaar Ahmed, Asif Ahmad, Muhammad Sheeraz Ahmad, Muhammad Akram Khan, Muhammad Mazahir

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The plant olive (Olea europaea L.) is known for its commercial significance due to nutritional and health benefits. Pakistan is ranked 4th among countries who import olive oil whereas, 70% of edible oil is imported to fulfil the needs of the country. There exists great potential for Olea europaea cultivation in Pakistan. The popularity and cultivation of olive fruit has increased in recent past due to its high socio-economic and health significance. There exist almost negligible data on the chemical composition of extra virgin olive oil extracted from cultivars grown in Pothwar, an area with arid climate conducive for growth of olive trees. Keeping in view these factors a study has been conducted to characterize the olive oil extracted from olive cultivars collected from Pothwar regions of Pakistan for their nutritional potential and value addition. Ten olive cultivars (Gemlik, Coratina, Sevillano, Manzanilla, Leccino, Koroneiki, Frantoio, Arbiquina, Earlik and Ottobratica) were collected from Barani Agriculture Research Institute, Chakwal. Extra Virgin Olive Oil (EVOO) was extracted by cold pressing and centrifuging of olive fruits. The highest amount of oil was yielded in Coratina (23.9%) followed by Frantoio (23.7%), Koroneiki (22.8%), Sevillano (22%), Ottobratica (22%), Leccino (20.5%), Arbiquina (19.2%), Manzanilla (17.2%), Earlik (14.4%) and Gemllik (13.1%). The extracted virgin olive oil was studied for various physico- chemical properties and fatty acid profile. The Physical and chemical properties i.e., characteristic odor and taste, light yellow color with no foreign matter, insoluble impurities (≤0.08), fee fatty acid (0.1 to 0.8), acidity (0.5 to 1.6 mg/g acid), peroxide value (1.5 to 5.2 meqO2/kg), Iodine value (82 to 90), saponification value (186 to 192 mg/g) and unsaponifiable matter (4 to 8g/kg), ultraviolet spectrophotometric analysis (k232 and k270), showed values in the acceptable range, established by PSQCA and IOOC set for extra virgin olive oil. Olive oil was analyzed by Near Infra-Red spectrophotometry (NIR) for fatty acids sin olive oils which were found as: palmitic, palmitoleic, stearic, oleic, linoleic and alpha-linolenic. Major fatty acid was Oleic acid in the highest percentage ranging from (55 to 66.1%), followed by linoleic (10.4 to 20.4%), palmitic (13.8 to 19.5%), stearic (3.9 to 4.4%), palmitoleic (0.3 to 1.7%) and alpha-linolenic (0.9 to 1.7%). The results were significant with differences in parameters analyzed for all ten cultivars which confirm that genetic factors are important contributors in the physico-chemical characteristics of oil. The olive oil showed superior physical and chemical properties and recommended as one of the healthiest forms of edible oil. This study will help consumers to be more aware of and make better choices of healthy oils available locally thus contributing towards their better health.

Keywords: characterization, extra virgin olive oil, oil yield, fatty acids

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Authors: Kylie Mueller, Nijole Bernaitis, Shailendra Anoopkumar-Dukie

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Background: Vitamin K antagonists particularly warfarin is the most frequently used oral medication for deep vein thrombosis (DVT) treatment and prophylaxis. Time in therapeutic range (TITR) of the international normalised ratio (INR) is widely accepted as a measure to assess the quality of warfarin therapy. Multiple factors can affect warfarin control and the subsequent adverse outcomes including thromboembolic and bleeding events. Predictor models have been developed to assess potential contributing factors and measure the individual risk of these adverse events. These predictive models have been validated in atrial fibrillation (AF) patients, however, there is a lack of literature on whether these can be successfully applied to other warfarin users including DVT patients. Therefore, the aim of the study was to assess the ability of these risk models (HAS BLED and CHADS2) to predict haemorrhagic and ischaemic incidences in DVT patients treated with warfarin. Methods: A retrospective analysis of DVT patients receiving warfarin management by a private pathology clinic was conducted. Data was collected from November 2007 to September 2014 and included demographics, medical and drug history, INR targets and test results. Patients receiving continuous warfarin therapy with an INR reference range between 2.0 and 3.0 were included in the study with mean TITR calculated using the Rosendaal method. Bleeding and thromboembolic events were recorded and reported as incidences per patient. The haemorrhagic risk model HAS BLED and ischaemic risk model CHADS2 were applied to the data. Patients were then stratified into either the low, moderate, or high-risk categories. The analysis was conducted to determine if a correlation existed between risk assessment tool and patient outcomes. Data was analysed using GraphPad Instat Version 3 with a p value of <0.05 considered to be statistically significant. Patient characteristics were reported as mean and standard deviation for continuous data and categorical data reported as number and percentage. Results: Of the 533 patients included in the study, there were 268 (50.2%) female and 265 (49.8%) male patients with a mean age of 62.5 years (±16.4). The overall mean TITR was 78.3% (±12.7) with an overall haemorrhagic incidence of 0.41 events per patient. For the HAS BLED model, there was a haemorrhagic incidence of 0.08, 0.53, and 0.54 per patient in the low, moderate and high-risk categories respectively showing a statistically significant increase in incidence with increasing risk category. The CHADS2 model showed an increase in ischaemic events according to risk category with no ischaemic events in the low category, and an ischaemic incidence of 0.03 in the moderate category and 0.47 high-risk categories. Conclusion: An increasing haemorrhagic incidence correlated to an increase in the HAS BLED risk score in DVT patients treated with warfarin. Furthermore, a greater incidence of ischaemic events occurred in patients with an increase in CHADS2 category. In an Australian population of DVT patients, the HAS BLED and CHADS2 accurately predicts incidences of haemorrhage and ischaemic events respectively.

Keywords: anticoagulant agent, deep vein thrombosis, risk assessment, warfarin

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Authors: Barbara Urasinska-Wojcik, Neil Chilton, Peter Todd, Christopher Elsworthy, Gregory J. Gibbons

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The recent increase in the application of Additive Manufacturing (AM) of products has resulted in new demands on capability. The ability to integrate both form and function within printed objects is the next frontier in the 3D printing area. To move beyond prototyping into low volume production, we demonstrate a UK-designed and built AM hybrid system that combines polymer based structural deposition with digital deposition of electrically conductive elements. This hybrid manufacturing system is based on a multi-planar build approach to improve on many of the limitations associated with AM, such as poor surface finish, low geometric tolerance, and poor robustness. Specifically, the approach involves a multi-planar Material Extrusion (ME) process in which separated build stations with up to 5 axes of motion replace traditional horizontally-sliced layer modeling. The construction of multi-material architectures also involved using multiple print systems in order to combine both ME and digital deposition of conductive material. To demonstrate multi-material 3D printing, three thermoplastics, acrylonitrile butadiene styrene (ABS), polyamide 6,6/6 copolymers (CoPA) and polyamide 12 (PA) were used to print specimens, on top of which our high viscosity Ag-particulate ink was printed in a non-contact process, during which drop characteristics such as shape, velocity, and volume were assessed using a drop watching system. Spectroscopic analysis of these 3D printed materials in the IR region helped to determine the optimum in-situ curing system for implementation into the AM system to achieve improved adhesion and surface refinement. Thermal Analyses were performed to determine the printed materials glass transition temperature (Tg), stability and degradation behavior to find the optimum annealing conditions post printing. Electrical analysis of printed conductive tracks on polymer surfaces during mechanical testing (static tensile and 3-point bending and dynamic fatigue) was performed to assess the robustness of the electrical circuits. The tracks on CoPA, ABS, and PA exhibited low electrical resistance, and in case of PA resistance values of tracks remained unchanged across hundreds of repeated tensile cycles up to 0.5% strain amplitude. Our developed AM printer has the ability to fabricate fully functional objects in one build, including complex electronics. It enables product designers and manufacturers to produce functional saleable electronic products from a small format modular platform. It will make 3D printing better, faster and stronger.

Keywords: additive manufacturing, conductive tracks, hybrid 3D printer, integrated manufacture

Procedia PDF Downloads 168

Authors: Arinze Ezieke, Antonio Serrano, William Clarke, Denys Villa-Gomez

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Berry cultivation results in discharge of high organic strength putrescible solid waste which potentially contributes to environmental degradation, making it imperative to assess options for its complete management. Anaerobic digestion (AD) could be an ideal option when the target is energy generation; however, due to berry fruit characteristics high carbohydrate composition, the technology could be limited by its high alkalinity requirement which suggests dosing of additives such as buffers and trace elements supplement. Overcoming this limitation in an economically viable way could entail replacement of synthetic additives with recycled by-product waste. Consequently, ash from co-smouldering of high COD characteristic AD digestate and coco-coir could be a promising material to be used to enhance the AD of berry fruit waste, given its characteristic high pH, alkalinity and metal concentrations which is typical of synthetic additives. Therefore, the aim of the research was to evaluate the stability and process performance from the AD of BFW when ash from co-smoldered digestate and coir are supplemented as alkalinity and trace elements (TEs) source. Series of batch experiments were performed to ascertain the necessity for alkalinity addition and to see whether the alkalinity and metals in the co-smouldered digestate ash can provide the necessary buffer and TEs for AD of berry fruit waste. Triplicate assays were performed in batch systems following I/S of 2 (in VS), using serum bottles (160 mL) sealed and placed in a heated room (35±0.5 °C), after creating anaerobic conditions. Control experiment contained inoculum and substrates only, and inoculum, substrate and NaHCO3 for optimal total alkalinity concentration and TEs assays, respectively. Total alkalinity concentration refers to alkalinity of inoculum and the additives. The alkalinity and TE potential of the ash were evaluated by supplementing ash (22.574 g/kg) of equivalent total alkalinity concentration to that of the pre-determined optimal from NaHCO3, and by dosing ash (0.012 – 7.574 g/kg) of varying concentrations of specific essential TEs (Co, Fe, Ni, Se), respectively. The result showed a stable process at all examined conditions. Supplementation of 745 mg/L CaCO3 NaHCO3 resulted to an optimum TAC of 2000 mg/L CaCO3. Equivalent ash supplementation of 22.574 g/kg allowed the achievement of this pre-determined optimum total alkalinity concentration, resulting to a stable process with a 92% increase in the methane production rate (323 versus 168 mL CH4/ (gVS.d)), but a 36% reduction in the cumulative methane production (103 versus 161 mL CH4/gVS). Addition of ashes at incremental dosage as TEs source resulted to a reduction in the Cumulative methane production, with the highest dosage of 7.574 g/kg having the highest effect of -23.5%; however, the seemingly immediate bioavailability of TE at this high dosage allowed for a +15% increase in the methane production rate. With an increased methane production rate, the results demonstrated that the ash at high dosages could be an effective supplementary material for either a buffered or none buffered berry fruit waste AD system.

Keywords: anaerobic digestion, alkalinity, co-smoldered digestate ash, trace elements

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Authors: Oscar Nieto-Garzón, Angélica Lozano

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In urban areas, on-road freight transportation creates several social and environmental externalities. Then, it is crucial that freight transport considers not only economic aspects, like retailer distribution cost reduction and service improvement, but also environmental effects such as global CO2 and local emissions (e.g. Particulate Matter, NOX, CO) and noise. Inadequate infrastructure development, high rate of urbanization, the increase of motorization, and the lack of transportation planning are characteristics that urban areas from developing countries share. The Metropolitan Area of Mexico City (MAMC), the Metropolitan Area of São Paulo (MASP), and Bogota are three of the largest urban areas in Latin America where air pollution is often a problem associated with emissions from mobile sources. The effect of the lockdown due to COVID-19 was analyzedfor these urban areas, comparing the same period (January to August) of years 2016 – 2019 with 2020. A strong reduction in the concentration of primary criteria pollutants emitted by road traffic were observed at the beginning of 2020 and after the lockdown measures.Daily mean concentration of NOx decreased 40% in the MAMC, 34% in the MASP, and 62% in Bogota. Daily mean ozone levels increased after the lockdown measures in the three urban areas, 25% in MAMC, 30% in the MASP and 60% in Bogota. These changes in emission patterns from mobile sources drastically changed the ambient atmospheric concentrations of CO and NOX. The CO/NOX ratioat the morning hours is often used as an indicator of mobile sources emissions. In 2020, traffic from cars and light vehicles was significantly reduced due to the first lockdown, but buses and trucks had not restrictions. In theory, it implies a decrease in CO and NOX from cars or light vehicles, maintaining the levels of NOX by trucks(or lower levels due to the congestion reduction). At rush hours, traffic was reduced between 50% and 75%, so trucks could get higher speeds, which would reduce their emissions. By means an emission model, it was found that an increase in the average speed (75%) would reduce the emissions (CO, NOX, and PM) from diesel trucks by up to 30%. It was expected that the value of CO/NOXratio could change due to thelockdownrestrictions. However, although there was asignificant reduction of traffic, CO/NOX kept its trend, decreasing to 8-9 in 2020. Hence, traffic restrictions had no impact on the CO/NOX ratio, although they did reduce vehicle emissions of CO and NOX. Therefore, these emissions may not adequately represent the change in the vehicle emission patterns, or this ratio may not be a good indicator of emissions generated by vehicles. From the comparison of the theoretical data and those observed during the lockdown, results that the real NOX reduction was lower than the theoretical reduction. The reasons could be that there are other sources of NOX emissions, so there would be an over-representation of NOX emissions generated by diesel vehicles, or there is an underestimation of CO emissions. Further analysis needs to consider this ratioto evaluate the emission inventories and then to extend these results forthe determination of emission control policies to non-mobile sources.

Keywords: COVID-19, emissions, freight transport, latin American metropolis

Procedia PDF Downloads 137

Authors: Violetta Cataldo, Renata Savy, Simona Sbranna

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Background: Foreign Language Learning (FLL) is characterised by prosodic transfer phenomena regarding pitch accents placement, intonation patterns, and pitch range excursion from the learners’ mother tongue to their Foreign Language (FL) which suggests that the gradual development of general linguistic competence in FL does not imply an equally correspondent improvement of the prosodic competence. Topic: The present study aims to monitor the development of prosodic competence of learners of Italian and German throughout the FLL process. The primary object of this study is to investigate the intonational features and the f₀ range excursion of Italian and German from a cross-linguistic perspective; analyses of native speakers’ productions point out the differences between this pair of languages and provide models for the Target Language (TL). A following crosscheck compares the L2 productions in Italian and German by non-native speakers to the Target Language models, in order to verify the occurrence of prosodic interference phenomena, i.e., type, degree, and modalities. Methodology: The subjects of the research are university students belonging to two groups: Italian native speakers learning German as FL and German native speakers learning Italian as FL. Both of them have been divided into three subgroups according to the FL proficiency level (beginners, intermediate, advanced). The dataset consists of wh-questions placed in situational contexts uttered in both speakers’ L1 and FL. Using a phonetic approach, analyses have considered three domains of intonational contours (Initial Profile, Nuclear Accent, and Terminal Contour) and two dimensions of the f₀ range parameter (span and level), which provide a basis for comparison between L1 and L2 productions. Findings: Results highlight a strong presence of prosodic transfer phenomena affecting L2 productions in the majority of both Italian and German learners, irrespective of their FL proficiency level; the transfer concerns all the three domains of the contour taken into account, although with different modalities and characteristics. Currently, L2 productions of German learners show a pitch span compression on the domain of the Terminal Contour compared to their L1 towards the TL; furthermore, German learners tend to use lower pitch range values in deviation from their L1 when improving their general linguistic competence in Italian FL proficiency level. Results regarding pitch range span and level in L2 productions by Italian learners are still in progress. At present, they show a similar tendency to expand the pitch span and to raise the pitch level, which also reveals a deviation from the L1 possibly in the direction of German TL. Conclusion: Intonational features seem to be 'resistant' parameters to which learners appear not to be particularly sensitive. By contrast, they show a certain sensitiveness to FL pitch range dimensions. Making clear which the most resistant and the most sensitive parameters are when learning FL prosody could lay groundwork for the development of prosodic trainings thanks to which learners could finally acquire a clear and natural pronunciation and intonation.

Keywords: foreign language learning, German, Italian, L2 prosody, pitch range, transfer

Procedia PDF Downloads 286

Authors: Maia Kharadze, Indira Djaparidze, Maia Vanidze, Aleko Kalandia

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Modern scientific world studies chemical components and antioxidant activity of different kinds of vines according to their breed purity and location. To our knowledge, this kind of research has not been conducted in Georgia yet. The object of our research was to study Chkhaveri vine, which is included in the oldest varieties of the Black Sea basin vine. We have studied different-altitude Chkaveri grapes, juice, and wine (half dry rose-colored produced with European technologies) and their technical markers, qualitative and quantitive composition of their biologically active compounds and their antioxidant activity. We were determining the amount of phenols using Folin-Ciocalteu reagent, Flavonoids, Catechins and Anthocyanins using Spectral method and antioxidant activity using DPPH method. Several compounds were identified using –HPLC-UV-Vis, UPLC-MS methods. Six samples of Chkhaveri species– 5, 300, 360, 380, 400, 780 meter altitudes were taken and analyzed. The sample taken from 360 m altitude is distinguished by its cluster mass (383.6 grams) and high amount of sugar (20.1%). The sample taken from the five-meter altitude is distinguished by having high acidity (0.95%). Unlike other grapes varieties, such concentration of sugar and relatively low levels of citric acid ultimately leads to Chkhaveri wine individuality. Biologically active compounds of Chkhaveri were researched in 2014, 2015, 2016. The amount of total phenols in samples of 2016 fruit varies from 976.7 to 1767.0 mg/kg. Amount of Anthocians is 721.2-1630.2 mg/kg, and the amount of Flavanoids varies from 300.6 to 825.5 mg/kg. Relatively high amount of anthocyanins was found in the Chkhaveri at 780-meter altitude - 1630.2 mg/kg. Accordingly, the amount of Phenols and Flavanoids is high- 1767.9 mg/kg and 825.5 mg/kg. These characteristics are low in samples gathered from 5 meters above sea level, Anthocyanins-721.2 mg/ kg, total Phenols-976.7 mg/ kg, and Flavanoids-300.6 mg/kg. The highest amount of bioactive compounds can be found in the Chkhaveri samples of high altitudes because with rising height environment becomes harsh, the plant has to develop a better immune system using Phenolic compounds. The technology that is used for the production of wine also plays a huge role in the composition of the final product. Optimal techniques of maceration and ageing were worked out. While squeezing Chkhaveri, there are no anthocyanins in the juice. However, the amount of Anthocyanins rises during maceration. After the fermentation of dregs, the amount of anthocyanins is 55%, 521.3 gm/l, total Phenols 80% 1057.7 mg/l and Flavanoids 23.5 mg/l. Antioxidant activity of samples was also determined using the effect of 50% inhibition of the samples. All samples have high antioxidant activity. For instance, in samples at 780 meters above the sea-level antioxidant activity was 53.5%. It is relatively high compared to the sample at 5 m above sea-level with the antioxidant activity of 30.5%. Thus, there is a correlation between the amount Anthocyanins and antioxidant activity. The designated project has been fulfilled by financial support of the Georgia National Science Foundation (Grant AP/96/13, Grant 216816), Any idea in this publication is possessed by the author and may not represent the opinion of the Georgia National Science Foundation.

Keywords: antioxidants, bioactive content, wine, chkhaveri

Procedia PDF Downloads 230

Authors: Mauro Callejas-Cuervo, Andrea C. Alarcon-Aldana, Andres F. Ruiz-Olaya, Juan C. Alvarez

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Motion capture (MC) is the construction of a precise and accurate digital representation of a real motion. Systems have been used in the last years in a wide range of applications, from films special effects and animation, interactive entertainment, medicine, to high competitive sport where a maximum performance and low injury risk during training and competition is seeking. This paper presents an inertial and magnetic sensor based technological platform, intended for particular amplitude monitoring and telerehabilitation processes considering an efficient cost/technical considerations compromise. Our platform particularities offer high social impact possibilities by making telerehabilitation accessible to large population sectors in marginal socio-economic sector, especially in underdeveloped countries that in opposition to developed countries specialist are scarce, and high technology is not available or inexistent. This platform integrates high-resolution low-cost inertial and magnetic sensors with adequate user interfaces and communication protocols to perform a web or other communication networks available diagnosis service. The amplitude information is generated by sensors then transferred to a computing device with adequate interfaces to make it accessible to inexperienced personnel, providing a high social value. Amplitude measurements of the platform virtual system presented a good fit to its respective reference system. Analyzing the robotic arm results (estimation error RMSE 1=2.12° and estimation error RMSE 2=2.28°), it can be observed that during arm motion in any sense, the estimation error is negligible; in fact, error appears only during sense inversion what can easily be explained by the nature of inertial sensors and its relation to acceleration. Inertial sensors present a time constant delay which acts as a first order filter attenuating signals at large acceleration values as is the case for a change of sense in motion. It can be seen a damped response of platform virtual in other images where error analysis show that at maximum amplitude an underestimation of amplitude is present whereas at minimum amplitude estimations an overestimation of amplitude is observed. This work presents and describes the platform virtual as a motion capture system suitable for telerehabilitation with the cost - quality and precision - accessibility relations optimized. These particular characteristics achieved by efficiently using the state of the art of accessible generic technology in sensors and hardware, and adequate software for capture, transmission analysis and visualization, provides the capacity to offer good telerehabilitation services, reaching large more or less marginal populations where technologies and specialists are not available but accessible with basic communication networks.

Keywords: inertial sensors, joint amplitude measurement, MEMS, telerehabilitation

Procedia PDF Downloads 260

Authors: C. Mazilu, D. P. Georgescu, A. Apostu, R. Deju

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Cement mortars and concretes are some of the most used construction materials in the world, global cement production being expected to grow to approx. 5 billion tons, until 2030. But, cement is an energy intensive material, the cement industry being responsible for cca. 7% of the world's CO2 emissions. Also, natural aggregates represent non-renewable resources, exhaustible, which must be used efficiently. A way to reduce the negative impact on the environment is the use of additional hydraulically active materials, as a partial substitute for cement in mortars and concretes and/or the use of recycled concrete aggregates (RCA) for the recovery of construction waste, according to EU Directive 2018/851. One of the most effective active hydraulic admixtures is microsilica and more recently, with the technological development on a nanometric scale, nanosilica. Studies carried out in recent years have shown that the introduction of SiO2 nanoparticles into cement matrix improves the properties, even compared to microsilica. This is due to the very small size of the nanosilica particles (<100nm) and the very large specific surface, which helps to accelerate cement hydration and acts as a nucleating agent to generate even more calcium hydrosilicate which densifies and compacts the structure. The cementitious compositions containing recycled concrete aggregates (RCA) present, in generally, inferior properties compared to those obtained with natural aggregates. Depending on the degree of replacement of natural aggregate, decreases the workability of mortars and concretes with RAC, decrease mechanical resistances and increase drying shrinkage; all being determined, in particular, by the presence to the old mortar attached to the original aggregate from the RAC, which makes its porosity high and the mixture of components to require more water for preparation. The present study aims to use micro and nanosilica for increase the performance of some mortars and concretes obtained with RCA. The research focused on two types of cementitious systems: a special mortar composition used for encapsulating Low Level radioactive Waste (LLW); a composition of structural concrete, class C30/37, with the combination of exposure classes XC4+XF1 and settlement class S4. The mortar was made with 100% recycled aggregate, 0-5 mm sort and in the case of concrete, 30% recycled aggregate was used for 4-8 and 8-16 sorts, according to EN 206, Annex E. The recycled aggregate was obtained from a specially made concrete for this study, which after 28 days was crushed with the help of a Retsch jaw crusher and further separated by sieving on granulometric sorters. The partial replacement of cement was done progressively, in the case of the mortar composition, with microsilica (3, 6, 9, 12, 15% wt.), nanosilica (0.75, 1.5, 2.25% wt.), respectively mixtures of micro and nanosilica. The optimal combination of silica, from the point of view of mechanical resistance, was later used also in the case of the concrete composition. For the chosen cementitious compositions, the influence of micro and/or nanosilica on the properties in the fresh state (workability, rheological characteristics) and hardened state (mechanical resistance, water absorption, freeze-thaw resistance, etc.) is highlighted.

Keywords: cement, recycled concrete aggregates, micro/nanosilica, durability

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Authors: Monica Sanchez

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What responsibility does urban planning have on climate changes? How does the territory give us answers of resilience? Historically, urban plans have civilized territories: waters are channeled, grounds are sealed, foreign species are incorporated, native ones are extinguished, and/or enclosed spaces are heated or cooled. Socially this facilitates coexistence, but in turn brings negative environmental consequences. The past fifty years, mankind has tried to redirect these consequences through different strategies. Research studies produced strategies designed to alleviate climate change. Exploring the nature of territories has been incorporated in urban planning to discover natures response. The case to be studied is Santiago, Chile: for its combined impacts of climate change and the significant response by this city on climate governance in the last decades. Warmer areas in Santiago are seen in the areas of high-density buildings such as the commune of Recoleta, while the coldest are characterized by the predominance of low residential densities as the commune of Providencia. These two communes are separated and complemented by an undulating body that comes from the Andes mountains called San Cristobal Hill. What if the hill were taken into account when making roads, zoning and buildings? Was it difficult to prolong in the urban plans the hill characteristics to the city solving the intersection with other natural areas? Apparently it was, because the projected-profile informs us that the planned strategies used correspond to the same operations used in the flat areas of Santiago. This research focuses on: explaining the geographic relationships between city-hill; explaining the planning process around the hill with a morphological analysis; evaluating how the hill has been considered the in the city in the plans that intended to cushion the environmental impacts and studying what is missing on the hill and city to strengthen their integration. Therefore, the research will have different scales of understanding: addressing territorial scale -understanding the vegetation, topography and hydrology; a city scale -analyzing urban plans that Santiago has dealt with the environment and city; and a local scale -studying the integration and public spaces and coverage- norms of the adjacent communes. The expected outcome is to decipher possible deficits and capabilities of the current urban plans for climate change. It is anticipated that the hill and valley is now trying to reconcile after such a long separation. Yet it seems that never will prevail all the Rules of Nature, but the Urban Rules. The plans will require pruning, irrigation, control of invasive alien species and public safety standards, but will be rejoining a dose of nature with the building environment -this will protect us better from it from the time that we feared from it and knew little about it. Today we know a little more, enough to adapt to the process. Although nature is not perceived and we ignore it, it has a remarkable ability to respond.

Keywords: resilience, climate change, urban plans, land use, hills and cities, heat islands, morphology

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Ieva Jokubauskaite, Alvyra Slepetiene, Danute Karcauskiene, Inga Liaudanskiene, Kristina Amaleviciute

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Soil organic carbon (SOC) is the key soil quality and ecological stability indicator, therefore, carbon accumulation in stable forms not only supports and increases the organic matter content in the soil, but also has a positive effect on the quality of soil and the whole ecosystem. Soil liming is one of the most common ways to improve the carbon sequestration in the soil. Determination of the optimum intensity and combinations of liming in order to ensure the optimal carbon quantitative and qualitative parameters is one of the most important tasks of this work. The field experiments were carried out at the Vezaiciai Branch of Lithuanian Research Centre for Agriculture and Forestry (LRCAF) during the 2011–2013 period. The effect of liming with different intensity (at a rate 0.5 every 7 years and 2.0 every 3-4 years) was investigated in the topsoil of acid moraine loam Bathygleyic Dystric Glossic Retisol. Chemical analyses were carried out at the Chemical Research Laboratory of Institute of Agriculture, LRCAF. Soil samples for chemical analyses were taken from the topsoil after harvesting. SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) at 590 nm wavelength using glucose standards. SOC fractional composition was determined by Ponomareva and Plotnikova version of classical Tyurin method. Dissolved organic carbon (DOC) was analyzed using an ion chromatograph SKALAR in water extract at soil-water ratio 1:5. Spectral properties (E4/E6 ratio) of humic acids were determined by measuring the absorbance of humic and fulvic acids solutions at 465 and 665 nm. Our study showed a negative statistically significant effect of periodical liming (at 0.5 and 2.0 liming rates) on SOC content in the soil. The content of SOC was 1.45% in the unlimed treatment, while in periodically limed at 2.0 liming rate every 3–4 years it was approximately by 0.18 percentage points lower. It was revealed that liming significantly decreased the DOC concentration in the soil. The lowest concentration of DOC (0.156 g kg-1) was established in the most intensively limed (2.0 liming rate every 3–4 years) treatment. Soil liming exerted an increase of all humic acids and fulvic acid bounded with calcium fractions content in the topsoil. Soil liming resulted in the accumulation of valuable humic acids. Due to the applied liming, the HR/FR ratio, indicating the quality of humus increased to 1.08 compared with that in unlimed soil (0.81). Intensive soil liming promoted the formation of humic acids in which groups of carboxylic and phenolic compounds predominated. These humic acids are characterized by a higher degree of condensation of aromatic compounds and in this way determine the intensive organic matter humification processes in the soil. The results of this research provide us with the clear information on the characteristics of SOC change, which could be very useful to guide the climate policy and sustainable soil management.

Keywords: acid soil, carbon sequestration, long–term liming, soil organic carbon

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Authors: Basiru Amuneni

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Astronomy is one domain with a rise in data. Traditional tools for data management have been employed in the quest for knowledge discovery. However, these traditional tools become limited in the face of big. One means of maximizing knowledge discovery for big data is the use of scientific visualisation. The aim of the work is to explore the possibilities offered by emerging creative technologies of Virtual Reality (VR) systems and game engines to visualize multiwavelength datasets. Game Engines are primarily used for developing video games, however their advanced graphics could be exploited for scientific visualization which provides a means to graphically illustrate scientific data to ease human comprehension. Modern astronomy is now in the era of multiwavelength data where a single galaxy for example, is captured by the telescope several times and at different electromagnetic wavelength to have a more comprehensive picture of the physical characteristics of the galaxy. Visualising this in an immersive environment would be more intuitive and natural for an observer. This work presents a standalone VR application that accesses galaxy FITS files. The application was built using the Unity Game Engine for the graphics underpinning and the OpenXR API for the VR infrastructure. The work used a methodology known as Design Science Research (DSR) which entails the act of ‘using design as a research method or technique’. The key stages of the galaxy modelling pipeline are FITS data preparation, Galaxy Modelling, Unity 3D Visualisation and VR Display. The FITS data format cannot be read by the Unity Game Engine directly. A DLL (CSHARPFITS) which provides a native support for reading and writing FITS files was used. The Galaxy modeller uses an approach that integrates cleaned FITS image pixels into the graphics pipeline of the Unity3d game Engine. The cleaned FITS images are then input to the galaxy modeller pipeline phase, which has a pre-processing script that extracts, pixel, galaxy world position, and colour maps the FITS image pixels. The user can visualise image galaxies in different light bands, control the blend of the image with similar images from different sources or fuse images for a holistic view. The framework will allow users to build tools to realise complex workflows for public outreach and possibly scientific work with increased scalability, near real time interactivity with ease of access. The application is presented in an immersive environment and can use all commercially available headset built on the OpenXR API. The user can select galaxies in the scene, teleport to the galaxy, pan, zoom in/out, and change colour gradients of the galaxy. The findings and design lessons learnt in the implementation of different use cases will contribute to the development and design of game-based visualisation tools in immersive environment by enabling informed decisions to be made.

Keywords: astronomy, visualisation, multiwavelenght dataset, virtual reality

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Authors: Pakize Ozlem Kurt Polat

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GMO (genetically modified organism) is the result of a laboratory process where genes from the DNA of one species are extracted and artificially forced into the genes of an unrelated plant or animal. This technology includes; nucleic acid hybridization, recombinant DNA, RNA, PCR, cell culture and gene cloning techniques. The studies are divided into three groups of properties transferred to the transgenic plant. Up to 59% herbicide resistance characteristic of the transfer, 28% resistance to insects and the virus seems to be related to quality characteristics of 13%. Transgenic crops are not included in the commercial production of each product; mostly commercial plant is soybean, maize, canola, and cotton. Day by day increasing GMO interest can be listed as follows; Use in the health area (Organ transplantation, gene therapy, vaccines and drug), Use in the industrial area (vitamins, monoclonal antibodies, vaccines, anti-cancer compounds, anti -oxidants, plastics, fibers, polyethers, human blood proteins, and are used to produce carotenoids, emulsifiers, sweeteners, enzymes , food preservatives structure is used as a flavor enhancer or color changer),Use in agriculture (Herbicide resistance, Resistance to insects, Viruses, bacteria, fungi resistance to disease, Extend shelf life, Improving quality, Drought , salinity, resistance to extreme conditions such as frost, Improve the nutritional value and quality), we explain all this methods step by step in this research. GMO has advantages and disadvantages, which we explain all of them clearly in full text, because of this topic, worldwide researchers have divided into two. Some researchers thought that the GMO has lots of disadvantages and not to be in use, some of the researchers has opposite thought. If we look the countries law about GMO, we should know Biosafety law for each country and union. For this Biosecurity reasons, the problems caused by the transgenic plants, including Turkey, to minimize 130 countries on 24 May 2000, ‘the United Nations Biosafety Protocol’ signed nudes. This protocol has been prepared in addition to Cartagena Biosafety Protocol entered into force on September 11, 2003. This protocol GMOs in general use by addressing the risks to human health, biodiversity and sustainable transboundary movement of all GMOs that may affect the prevention, transit covers were dealt and used. Under this protocol we have to know the, ‘US Regulations GMO’, ‘European Union Regulations GMO’, ‘Turkey Regulations GMO’. These three different protocols have different applications and rules. World population increasing day by day and agricultural fields getting smaller for this reason feeding human and animal we should improve agricultural product yield and quality. Scientists trying to solve this problem and one solution way is molecular biotechnology which is including the methods of GMO too. Before decide to support or against the GMO, should know the GMO protocols and it effects.

Keywords: biotechnology, GMO (genetically modified organism), molecular marker

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Authors: Baguma Daniel Kajura

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The study explores socio-economic factors, health related and individual factors that influence the breastfeeding habits of mothers and their effect on the nutritional status of their infants in the Rwenzori region of Western Uganda. A cross-sectional research design was adopted, and it involved the use of self-administered questionnaires, interview guides, and focused group discussion guides to assess the extent to which socio-demographic factors associated with breastfeeding practices influence child malnutrition. Using this design, data was collected from 276 mother-paired infants out of the selected 318 mother-paired infants over a period of ten days. Using a sample size formula by Kish Leslie for cross-sectional studies N= Zα2 P (1- P) / δ2, where N= sample size estimate of paired mother paired infants. P= assumed true population prevalence of mother–paired infants with malnutrition cases, P = 29.3%. 1-P = the probability of mother-paired infants not having malnutrition, so 1-P = 70.7% Zα = Standard normal deviation at 95% confidence interval corresponding to 1.96.δ = Absolute error between the estimated and true population prevalence of malnutrition of 5%. The calculated sample size N = 1.96 × 1.96 (0.293 × 0.707) /0,052= 318 mother paired infants. Demographic and socio-economic data for all mothers were entered into Microsoft Excel software and then exported to STATA 14 (StataCorp, 2015). Anthropometric measurements were taken for all children by the researcher and the trained assistants who physically weighed the children. The use of immunization card was used to attain the age of the child. The bivariate logistic regression analysis was used to assess the relationship between socio-demographic factors associated with breastfeeding practices and child malnutrition. The multivariable regression analysis was used to draw a conclusion on whether or not there are any true relationships between the socio-demographic factors associated with breastfeeding practices as independent variables and child stunting and underweight as dependent variables in relation to breastfeeding practices. Descriptive statistics on background characteristics of the mothers were generated and presented in frequency distribution tables. Frequencies and means were computed, and the results were presented using tables, then, we determined the distribution of stunting and underweight among infants by the socioeconomic and demographic factors. Findings reveal that children of mothers who used milk substitutes besides breastfeeding are over two times more likely to be stunted compared to those whose mothers exclusively breastfed them. Feeding children with milk substitutes instead of breastmilk predisposes them to both stunting and underweight. Children of mothers between 18 and 34 years of age are less likely to be underweight, as were those who were breastfed over ten times a day. The study further reveals that 55% of the children were underweight, and 49% were stunted. Of the underweight children, an equal number (58/151) were either mildly or moderately underweight (38%), and 23% (35/151) were severely underweight. Empowering community outreach programs by increasing knowledge and increased access to services on integrated management of child malnutrition is crucial to curbing child malnutrition in rural areas.

Keywords: infant and young child feeding, breastfeeding, child malnutrition, maternal health

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