Search results for: double nearest proportion feature extraction

Authors: Donatella Cimini, Sergio D’ambrosio, Saba Sadiq, Chiara Schiraldi

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Chondroitin sulfate (CS), as well as modified CS, and unsulfated chondroitin, are largely applied in research today. CS is a linear glycosaminoglycan normally present in cartilage-rich tissues and bones in the form of proteoglycans decorated with sulfate groups in different positions. CS is used as an effective non-pharmacological alternative for the treatment of osteoarthritis, and other potential applications in the biomedical field are being investigated. Some bacteria, such as E. coli K4, produce a polysaccharide that is a precursor of CS (unsulfated chondroitin). This work focused on the construction of integrative E. coli K4 recombinant strains overexpressing genes (kfoA, kfoF, pgm and galU in different combinations) involved in the biosynthesis of the nucleotide sugars necessary for polysaccharide synthesis. Strain growth and polymer production were evaluated using renewable waste materials as substrates in shake flasks and small-scale batch fermentation processes. Results demonstrated the potential to replace pure sugars with cheaper medium components to establish environmentally sustainable and cost-effective production routes for potential industrial development. In fact, although excellent fermentation results have been described so far by employing strains that naturally produce chondroitin-like polysaccharides on semi-defined media, there is still the need to reduce manufacturing costs by providing a cost-effective biotechnological alternative to currently used animal-based extraction procedures.

Keywords: E. coli K4, chondroitin, microbial cell factories, glycosaminoglycans, renewable resources

Procedia PDF Downloads 78

Authors: Nicolas Haber

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The study addresses the design process of integrated product-service offerings as a measure of answering environmental sustainability concerns by replacing stand-alone physical artefacts with comprehensive solutions relying on functional results rather than conventional product sales. However, views regarding this transformation are dissimilar and differentiated: The study discusses the importance and requirements of product-service systems before analysing the theoretical studies accomplished in the extent of their design and development processes. Based on this, a framework, built on a design science approach, is proposed, where the distinct approaches from the literature are merged towards a unified structure serving as a generic methodology to designing product-service systems. Each stage of this model is then developed to present a holistic design proposal called the Functional Engineered Product-Service System (FEPSS) model. Product-service systems are portrayed as customisable solutions tailored to specific settings and defined circumstances. Moreover, the approaches adopted to guide the design process are diversified. A thorough analysis of the design strategies and development processes however, allowed the extraction of a design backbone, valid to varied situations and contexts whether they are product-oriented, use-oriented or result-oriented. The goal is to guide manufacturers towards an eased adoption of these integrated offerings, given their inherited environmental benefits, by proposing a robust all-purpose design process.

Keywords: functional product, integrated product-service offerings, product-service systems, sustainable design

Procedia PDF Downloads 289

Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Xianglu Tang, Zhenxue Jiang, Zhuo Li

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Characterization of shale multi scale heterogeneity is an important part to evaluate size and space distribution of shale gas reservoirs in sedimentary basins. The origin of shale heterogeneity has always been a hot research topic for it determines shale micro characteristics description and macro quality reservoir prediction. Shale multi scale heterogeneity was discussed based on thin section observation, FIB-SEM, QEMSCAN, TOC, XRD, mercury intrusion porosimetry (MIP), and nitrogen adsorption analysis from 30 core samples in Silurian Longmaxi formation. Results show that shale heterogeneity can be characterized by pore structure and mineral composition. The heterogeneity of shale pore is showed by different size pores at nm-μm scale. Macropores (pore diameter > 50 nm) have a large percentage of pore volume than mesopores (pore diameter between 2~ 50 nm) and micropores (pore diameter < 2nm). However, they have a low specific surface area than mesopores and micropores. Fractal dimensions of the pores from nitrogen adsorption data are higher than 2.7, what are higher than 2.8 from MIP data, showing extremely complex pore structure. This complexity in pore structure is mainly due to the organic matter and clay minerals with complex pore network structures, and diagenesis makes it more complicated. The heterogeneity of shale minerals is showed by mineral grains, lamina, and different lithology at nm-km scale under the continuous changing horizon. Through analyzing the change of mineral composition at each scale, random arrangement of mineral equal proportion, seasonal climate changes, large changes of sedimentary environment, and provenance supply are considered to be the main reasons that cause shale minerals heterogeneity from microcosmic to macroscopic. Due to scale effect, the change of shale multi scale heterogeneity is a discontinuous process, and there is a transformation boundary between homogeneous and in homogeneous. Therefore, a shale multi scale heterogeneity changing model is established by defining four types of homogeneous unit at different scales, which can be used to guide the prediction of shale gas distribution from micro scale to macro scale.

Keywords: heterogeneity, homogeneous unit, multiscale, shale

Procedia PDF Downloads 445

Authors: Zahia Dorbane, Si Ammar Kadi, Dalila Boudouma, Thierry Gidenne

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In rabbits feeding, minimum fibre intake is essential to avoid digestive disorders. However, this concentration of fibre is not easy to obtain when formulating feeds, without reduction of nutritional value. Three stage olive cake, the residual material after oil extraction by centrifugation, including pulp and stones, can be used as a fibre source in rabbit diet. The incorporation of olive cake can allow a better balance between different fibre fractions and reduce health disorder. However, for practical use of any raw material, it is necessary to know its chemical and nutritive value. The aim of this study was to assess the nutritive value of three-stage olive cake (TSOC) for growing rabbits. Thus, 36 rabbits weaned at 35 days (702.8 ± 28.5) were divided into three groups of 12 receiving one of the following diets: control with 0% of TSOC, TSOC10 (10% of TSOC) and TSOC20 (20% TSOC). The rabbits were individually housed in digestibility cages and received ad libitum one of the three diets, fresh and clean water was provided ad libitum. After an adaptation period of 7d, feces were collected for 4d. Collected feces were frozen and stored for further analysis. The chemical composition of TSOC shows that it is a rich fiber raw material since it contains (%DM): 6% of CP; 7.4% of EE; 78.7% of NDF; 55.4% of ADF and 24.3% of ADL. The inclusion of TSOC at 20% of basal diet reduced the digestibility coefficient of organic matter, crude protein and NDF from 67.8 to 55.3%, 80.4 to 75.3% and from 31.5 to 18.4% (p < 0.001) respectively. The digestible energy and digestible protein content of the three-stage olive cake estimated by regression was 2.94 ± 0.52MJ DE/kg DM and 22.4 ± 6 g DP/kg DM respectively. In conclusion, based on the results of the present experiment, the three-stage olive cake can be used as a fibre source for rabbit.

Keywords: digestibility, nutritive value, olive cake, rabbit

Procedia PDF Downloads 149

Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: displacement deviation analysis, gear whine, ghost frequency, sound quality

Procedia PDF Downloads 142

Authors: Dani Sukkar, Ali Kanso, Philippe Laval-Gilly, Jairo Falla-Angel

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The honeybees' immune system is challenged by different risk factors that induce various responses. However, complex scenarios where bees are exposed to different pesticides simultaneously with immune activation are not well evaluated. The Toll pathway is one of the main signaling pathways studied in invertebrate immune responses, and it is a good indicator of the effect of such complex interactions in addition to key signaling elements of other pathways like Relish of the immune deficiency (IMD) pathway or Eater, the phagocytosis receptor or vitellogenin levels. Honeybee hemocytes extracted from 5th instar larvae were exposed to imidacloprid and/or amitraz with or without the presence of the zymosan a as an immune activator. The gene expression of multiple immune related genes were studied, including spaetzle, Toll, myD88, relish, eater and vitellogenin, by real-time polymerase chain reaction after RNA extraction. The results demonstrated that the Toll pathway is mainly affected by the pesticides; imidacloprid and amitraz, especially by their different combinations. Furthermore, immune activation by zymosan A, a fungal cell-wall component, acts to mitigate to some extent the effect of pesticides on the different levels of the Toll pathway. In addition, imidacloprid, amitraz, and zymosan A have complex and context-specific interactions depending on the levels of immune activation and the pathway evaluated affecting immune-gene expression differently.

Keywords: toll pathway, immune modulation, β-glucan, imidacloprid, amitraz, honeybees, immune genes

Procedia PDF Downloads 76

Authors: Hong Li, Haiyang Yu, Shiqing Cheng, Nai Cao, Zhiliang Shi

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Unconventional resources have gradually become the main direction for oil and gas exploration and development. However, the productivity of gas wells, the level of water production, and the seepage law in tight fractured gas reservoirs are very different. These are the reasons why production prediction is so difficult. Firstly, a three-dimensional multi-scale fracture and multiphase mathematical model based on an embedded discrete fracture model (EDFM) is established. And the material balance method is used to calculate the water body multiple according to the production performance characteristics of water-producing gas well. This will help construct a 'virtual water body'. Based on these, this paper presents a numerical simulation process that can adapt to different production modes of gas wells. The research results show that fractures have a double-sided effect. The positive side is that it can increase the initial production capacity, but the negative side is that it can connect to the water body, which will lead to the gas production drop and the water production rise both rapidly, showing a 'scissor-like' characteristic. It is worth noting that fractures with different angles have different abilities to connect with the water body. The higher the angle of gas well development, the earlier the water maybe break through. When the reservoir is a single layer, there may be a stable production period without water before the fractures connect with the water body. Once connected, a 'scissors shape' will appear. If the reservoir has multiple layers, the gas and water will produce at the same time. The above gas-water relationship can be matched with the gas well production date of the Xujiahe gas reservoir in the Sichuan Basin. This method is used to predict the productivity of a well with hydraulic fractures in this gas reservoir, and the prediction results are in agreement with on-site production data by more than 90%. It shows that this research idea has great potential in the productivity prediction of water-producing gas wells. Early prediction results are of great significance to guide the design of development plans.

Keywords: EDFM, multiphase, multilayer, water body

Procedia PDF Downloads 190

Authors: Asep Sukohar, Ramadhan Triyandi, Muhammad Iqbal, Sahidin, Suharyani

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Introduction: Resveratrol is a class of bioactive chemicals found in melinjo, which has a wide range of biological actions. The purpose of this study is to determine the linarin content of the melinjo fraksi by using preparative-high-performance liquid chromatography (prep-HPLC). Method: Extraction used the soxhletation method with 96% ethanol solvent. Fractionation used ethyl acetate and ethanol in a ratio of 1:1. Tracing of linarin compound used prep-HPLC with a mobile phase ratio of distilled water: methanol (55: 45, v/v). The presence of linarin was detected using a wavelength of 215 nm. Fourier Transform Infrared (FTIR) was used to identify the functional groups of compound. Result: The retention time required to elute the ethyl acetate fraction was 2.601 minutes. Compound separation identification using Fourier Transform Infrared Spectroscopy - Quest Attenuated Total Reflectance (FTIR - QATR) has a similarity value range with standards from 0 to 1000. The elution results of the ethyl acetate fraction have similar values with the standard compounds linarin (668), resveratrol (578), and catechin (455). Conclusion: Tracing for active compound in the ethyl acetate fraction of Gnetum Gnemon L. using prep-HPLC showed a strong suspicion of the presence of linarin compound.

Keywords: Gnetum gnemon L., linarin, prep-HPLC, fraction ethyl acetate

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: S. Tireche, A. Tairi abdelaziz

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Environmental damage has increased steadily in recent decades: Depletion of natural resources, destruction of the ozone layer, greenhouse effect, degradation of the quality of life, land use etc. New terms have emerged as: "Prevention rather than cure" or "polluter pays" falls within the principles of common sense, their practical implementation still remains fragmented. Among the avenues to be explored, one of the most promising is certainly one that focuses on product design. Indeed, where better than during the design phase, can reduce the source of future impacts on the environment? What choices or those of design, they influence more on the environmental characteristics of products? The most currently recognized at the international level is the analysis of the life cycle (LCA) and Life Cycle Assessment, subject to International Standardization (ISO 14040-14043). LCA provides scientific and objective assessment of potential impacts of the product or service, considering its entire life cycle. This approach makes it possible to minimize impacts to the source in pollution prevention. It is widely preferable to curative approach, currently majority in the industrial crops, led mostly by a report of pollution. The "product" is to reduce the environmental impacts of a given product, taking into account all or part of its life cycle. Currently, there are emerging tools, known as eco-design. They are intended to establish an environmental profile of the product to improve its environmental performance. They require a quantity sufficient information on the product for each phase of its life cycle: raw material extraction, manufacturing, distribution, usage, end of life (recycling or incineration or deposit) and all stages of transport. The assessment results indicate the sensitive points of the product studied, points on which the developer must act.

Keywords: eco design, impact, life cycle analysis (LCA), sustainability

Procedia PDF Downloads 420

Authors: Ceyda Dadali, Yeşim Elmaci

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Coffee was introduced as an economic crop during the fifteenth century; nowadays it is the most important food commodity ranking second after crude oil. Desirable sensory properties make coffee one of the most often consumed and most popular beverages in the world. The coffee preparation method has a significant effect on flavor and composition of coffee brews. Three different extraction methodologies namely decoction, infusion and pressure methods have been used for coffee brew preparation. Each of these methods is related to specific granulation (coffee grind) of coffee powder, water-coffee ratio temperature and brewing time. Coffee is a mixture of 1500 chemical compounds. Chemical composition of coffee highly depends on brewing methods, coffee bean species and roasting time-temperature. Coffee contains a wide number of very important bioactive compounds, such as diterpenes: cafestol and kahweol, alkaloids: caffeine, theobromine and trigonelline, melanoidins, phenolic compounds. The phenolic compounds of coffee include chlorogenic acids (quinyl esters of hidroxycinnamic acids), caffeic, ferulic, p-coumaric acid. In coffee caffeoylquinic acids, feruloylquinic acids and di-caffeoylquinic acids are three main groups of chlorogenic acids constitues 6% -10% of dry weight of coffee. The bioavailability of chlorogenic acids in coffee depends on the absorption and metabolization to biomarkers in individuals. Also, the interaction of coffee polyphenols with other compounds such as dietary proteins affects the biomarkers. Since bioactive composition of coffee depends on brewing methods effect of coffee brewing method on bioactive compounds of coffee will be discussed in this study.

Keywords: bioactive compounds of coffee, biomarkers, coffee brew, effect of brewing

Procedia PDF Downloads 191

Authors: Jae-Hyuk Hyun, Dong-Sung Bae, Jea-Sun Lee

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The COVID-19 pandemic emphasized the benefits of natural green space on mental health in pandemic situations. The effects of greenspace on reducing mental health disorder are detected, but limitations impede highlighting the overall effectiveness of greenspace on mental health to be valid and significant. Therefore, this study aims to comprehensively and quantitatively analyze the effectiveness and significance of greenspace in reducing mental disorders after the COVID-19 outbreak. This study adopted a systematic review to select adequate, necessary studies with significant associations between greenspace and mental health after COVID-19. Meta-analysis is performed using the selected studies for calculating and analyzing the combined effect size of greenspace on reducing mental disorder, difference of effect size in various factors of greenspace or mental health, and variables’ effects on greenspace or mental health. Also, a correlation test using MQRS and effect size is performed to determine significant correlations of factors in greenspace and mental health. The analysis confirmed the combined effect size of the association between greenspace and mental health to be interpreted as large enough (medium effect size, 0.565). Various factors consisting of greenspace or mental health had considerable effect sizes, with heterogeneity existing between studies of different greenspace and mental health aspects (subgroups). A significant correlation between factors in greenspace and mental health was identified, with correlations satisfying both reliability and effectiveness used for suggesting necessary greenspace policies with mental health benefits during the pandemic situation. Different variables of the study period, female proportion, and mean age significantly affected certain factors of greenspace or mental health, while the increase in effects of greenspace on mental health was detected as the COVID-19 period continued. Also, the regional heterogeneity of effects on the association between greenspace and mental health is recognized in all factors consisting of greenspace and mental health except for the visitation of greenspace. In conclusion, valid and significant effects were detected in various associations between greenspace and mental health. Based on the results of this study, conducting elaborate research and establishing adequate and necessary greenspace policies and strategies are recommended to effectively benefit the mental health of citizens in future pandemic situations.

Keywords: greenspace, natural environment, mental health, mental disorder, COVID-19, pandemic, systematic review, meta-analysis

Procedia PDF Downloads 62

Authors: Maria Vargas Hernandez, Jose Rojas Suarez, Carmelo Dueñas Castell, Sandra Contreras, Camilo Bello, Diana Borre, Walter Anichiarico, Harold Vasquez, Eduard Perez, Jose Santacruz

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In the last two decades, there have been outbreaks of emerging infectious diseases, with an impact on both the general population and the obstetric population. These infections, which affect the general population, pose a high risk for adverse maternal and perinatal outcomes, taking into account that physiological and immunological changes that occur during pregnancy can increase their risk or severity. Among these, the pandemics of viral infections, Influenza A/H1N1 and SARS-CoV-2/COVID-19, stand out. In 2009, Influenza A/H1N1 infection (H1N1 2009pdm) affected approximately 3,110 obstetric patients, with data reported from 29 countries, including 1,625 (52.3%) cases that were hospitalized, 378 (23.3%) admissions to ICU and 130 (8%) deaths; and since the end of 2019, the Severe Acute Respiratory Syndrome - 2 (SARS-CoV-2) has been identified, causing the COVID-19 pandemic, with global mortality that is around 2-4% for the general population, and higher mortality in patients requiring admission to the intensive care unit. Its impact on the obstetric population is still unknown. Objectives: To evaluate the impact on maternal and perinatal outcomes of COVID-19 infection in reference to influenza A/H1N1 infection in the obstetric population. Methodology: Systematic review of the literature and meta-analysis. Results: Mortality from maternal infection with influenza A/H1N1 appears to be higher (8%) than mortality due to maternal infection with COVID-19 (3%). The rates of ICU admission, hospitalization, the requirement for invasive mechanical ventilation, and fetal death also appear to be higher in the maternal population with A/H1N1 infection, in reference to the maternal population with COVID-19 infection. Within perinatal outcomes, the admission to the neonatal ICU appears to be higher in the infants born to mothers with COVID-19 infection (28% vs. 15% for COVID-19 and A/H1N1, respectively). Conclusion: A/H1N1 infection in the obstetric population seems to be associated with a higher proportion of adverse outcomes in relation to COVID-19 infection. The actual impact of maternal influenza A/H1N1 infection on perinatal outcomes is unknown. More COVID-19 studies are needed to understand the impact of maternal infection on perinatal outcomes in this population.

Keywords: A/H1N1, COVID-19, maternal outcomes, perinatal outcomes

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Authors: Jiping Cai, Ningzhi Wangyang, Jun Shao

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Traumatic brain injury (TBI) is one of the major causes of morbidity and mortality that leads to structural and functional damage in several parts of the brain, such as cranial nerves, optic nerve tract or other circuitry involved in vision and occipital lobe, depending on its location and severity. As a result, the function associated with vision processing and perception are significantly affected and cause blurred vision, double vision, decreased peripheral vision and blindness. Here two cases complaining of monocular vision loss (actually temporal hemianopia) due to traumatic chiasmal syndrome after frontal head injury were reported, and were compared the findings with individual case reports published in the literature. Reported cases of traumatic chiasmal syndrome appear to share some common features, such as injury to the frontal bone and fracture of the anterior skull base. The degree of bitemporal hemianopia and visual loss acuity have a variable presentation and was not necessarily related to the severity of the craniocerebral trauma. Chiasmal injury may occur even in the absence bony chip impingement. Isolated bitemporal hemianopia is rare and clinical improvement usually may not occur. Mechanisms of damage to the optic chiasm after trauma include direct tearing, contusion haemorrhage and contusion necrosis, and secondary mechanisms such as cell death, inflammation, edema, neurogenesis impairment and axonal damage associated with TBI. Beside visual field test, MRI evaluation of optic pathways seems to the strong objective evidence to demonstrate the impairment of the integrity of visual systems following TBI. Therefore, traumatic chiasmal syndrome should be considered as a differential diagnosis by both neurosurgeons and ophthalmologists in patients presenting with visual impairment, especially bitemporal hemianopia after head injury causing frontal and anterior skull base fracture.

Keywords: bitemporal hemianopia, brain injury, optic chiasma, traumatic chiasmal syndrome.

Procedia PDF Downloads 72

Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Basyir Yaman, Fades Br. Gultom

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The picture and pattern of Islamic education in the Prophet's period in Mecca and Medina is the history of the past that we need to bring back. The Basic Education Institute called Kuttab. Kuttab or Maktab comes from the word kataba which means to write. The popular Kuttab in the Prophet’s period aims to resolve the illiteracy in the Arab community. In Indonesia, this Institution has 25 branches; one of them is located in Semarang (i.e. Kuttab Al-Fatih). Kuttab Al-Fatih as a non-formal institution of Islamic education is reserved for children aged 5-12 years. The independently designed curriculum is a distinctive feature that distinguishes between Kuttab Al-Fatih curriculum and the formal institutional curriculum in Indonesia. The curriculum includes the faith and the Qur’an. Kuttab Al-Fatih has been licensed as a Community Activity Learning Center under the direct supervision and guidance of the National Education Department. Here, we focus to describe the implementation of curriculum Kuttab Al-Fatih Semarang (i.e. faith and al-Qur’an). After that, we determine the relevance between the implementation of the Kuttab Al-Fatih education system with the formal education system in Indonesia. This research uses literature review and field research qualitative methods. We obtained the data from the head of Kuttab Al-Fatih Semarang, vice curriculum, faith coordinator, al-Qur’an coordinator, as well as the guardians of learners and the learners. The result of this research is the relevance of education system in Kuttab Al-Fatih Semarang about education system in Indonesia. Kuttab Al-Fatih Semarang emphasizes character building through a curriculum designed in such a way and combines thematic learning models in modules.

Keywords: Islamic education system, implementation of curriculum, Kuttab Al-Fatih Semarang, formal education system, Indonesia

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Authors: Pasquali Frederique, Manfreda Chiara, Crippa Cecilia, Indio Valentina, Ianieri Adriana, De Cesare Alessandra

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Microbiological hazards can be transmitted to humans through milk. In this study, we compared the microbiome composition and presence of foodborne pathogens in organic milk (n=6), organic hay milk (n=6), standard milk (n=6) and high-quality milk (n=6). The milk samples were collected during six samplings between December 2022 to January 2023 and between April and May 2024 to take into account seasonal variations. The 24 milk samples were submitted to DNA extraction and library preparation before shotgun sequencing on the Illumina HiScan™ SQ System platform. The total sequencing output was 600 GB. In all the milk samples, the phyla with the highest relative abundances were Pseudomonadota, Bacillota, Ascomycota, Actinomycetota and Apicomplexa, while the most represented genera were Pseudomonas, Streptococcus, Geotrichum, Acinetobacter and Babesia. The alpha and beta diversity indexes showed a clear separation between the microbiome of high-quality milk and those of the other milk types. Moreover, in the high-quality milk, the relative abundance of Staphylococcus (4.4%), Campylobacter (4.5%), Bacillus (2.5%), Enterococcus (2.4%), Klebsiella (1.3%) and Escherichia (0 .7%) was significantly higher in comparison to other types of milk. On the contrary, the relative abundance of Geotrichum (0.5%) was significantly lower. The microbiome results collected in this study showed significant differences in terms of the relative abundance of bacteria genera, including foodborne pathogen species. These results should be incorporated into risk assessment models tailored to different types of milk.

Keywords: raw milk, foodborne pathogens, microbiome, risk assessment

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Swati Srivastava, Ashish Kumar Upadhyay

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Background: According to United Nation Children’s Fund, it has been estimated that worldwide about 165 million children were stunted in 2012 and India alone accounts for 38% of global burden of stunting. In terms of incidence, India is home of more than 60 million stunted children worldwide. Our study aims to examine the effect of pregnancy intention and maternal postnatal depressive symptoms on early childhood stunting in India. We hypothesized that effect of pregnancy intention and postnatal maternal depressive symptoms were mediated by social support. Methods: We used data from first wave of Young Lives Study India. Out of 2011 children recruited in original cohort, 1833 children had complete information on pregnancy intention, maternal depression and other variables. A series of multivariate logistic regression model were used to examine the effect of pregnancy intention and postnatal depressive symptoms on early childhood stunting. Results: Bivariate result indicates that a higher percent of children born after unintended pregnancy (40%) were stunted than children of intended pregnancy (26%). Likewise, proportion of stunted children was also higher among women of high postnatal depressive symptoms (35%) than low level of depression (24%). Results of multivariate logistic regression model indicate that children born after unintended pregnancy were significantly more likely to be stunted than children born after intended pregnancy (Coefficient: 1.70, CI: 1.17, 2.48). Likewise, early childhood stunting was also associated with maternal postnatal depressive symptoms among women (Coefficient: 1.48, CI: 1.16, 1.88). The effect of pregnancy intention and postnatal depressive symptoms on early childhood stunting remains unchanged after controlling for social support and other variables. Conclusions: The findings of this study provide conclusive evidence regarding consequences of pregnancy intention and postnatal depressive symptoms on early childhood stunting in India. Therefore, there is need to identify the women with unintended pregnancy and incorporate the promotion of mental health into their national reproductive and child health programme.

Keywords: pregnancy intention, postnatal depressive symptoms, social support, childhood stunting, young lives study, India

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Authors: S. Visetpotjanakit, N. Nakkaew

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Determination of ⁹⁰Sr in environmental samples has been widely developed with several radioanlytical methods and radiation measurement techniques since ⁹⁰Sr is one of the most hazardous radionuclides produced from nuclear reactors. Liquid extraction technique using di-(2-ethylhexyl) phosphoric acid (HDEHP) to separate and purify ⁹⁰Y and Cherenkov counting using liquid scintillation counter to determine ⁹⁰Y in secular equilibrium to ⁹⁰Sr was developed and performed at our institute, the Office of Atoms for Peace. The approach is inexpensive, non-laborious, and fast to analyse ⁹⁰Sr in environmental samples. To validate our analytical performance for the accurate and precise criteria, determination of ⁹⁰Sr using the IAEA-TEL-2016-04 ALMERA proficiency test samples were performed for statistical evaluation. The experiment used two spiked tap water samples and one naturally contaminated spruce needles sample from Austria collected shortly after the Chernobyl accident. Results showed that all three analyses were successfully passed in terms of both accuracy and precision criteria, obtaining “Accepted” statuses. The two water samples obtained the measured results of 15.54 Bq/kg and 19.76 Bq/kg, which had relative bias 5.68% and -3.63% for the Maximum Acceptable Relative Bias (MARB) 15% and 20%, respectively. And the spruce needles sample obtained the measured results of 21.04 Bq/kg, which had relative bias 23.78% for the MARB 30%. These results confirm our analytical performance of ⁹⁰Sr determination in water and spruce needles samples using the same developed method.

Keywords: ALMERA proficiency test, Cerenkov counting, determination of 90Sr, environmental samples

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Authors: Xiaoquan Huang, Congcong Li, Tingting Wei, Changcun Bai, Na Liu, Meng Tang

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Silver is often doped on nano-titanium dioxide photocatalysts (Ag-TiO₂) by photodeposition method to improve their utilization of visible-light while increasing the toxicity of TiO₂。 However, it is not known what factors influence this toxicity and how to reduce toxicity while maintaining the maximum catalytic activity. In this study, Ag-TiO₂ photocatalysts were synthesized by the photodeposition method with different silver content (AgC) and photodeposition time (PDT). Characterization and catalytic experiments demonstrated that silver was well assembled on TiO₂ with excellent visible-light catalytic activity, and the size of silver increased with PDT. In vitro, the cell viability of lung epithelial cells A549 and BEAS-2B showed that the higher content and smaller size of silver doping caused higher toxicity. In vivo, Ag-TiO₂ catalysts with lower AgC or larger silver particle size obviously caused less pulmonary pro-inflammatory and pro-fibrosis responses. However, the visible light catalytic activity decreased with the increase in silver size. Therefore, in order to optimize the Ag-TiO₂ photocatalyst with the lowest pulmonary toxicity and highest catalytic performance, response surface methodology (RSM) was further performed to optimize the two independent variables of AgC and PDT. Visible-light catalytic activity was evaluated by the degradation rate of Rhodamine B, the antibacterial property was evaluated by killing log value for Escherichia coli, and cytotoxicity was evaluated by IC50 to BEAS-2B cells. As a result, the RSM model showed that AgC and PDT exhibited an interaction effect on catalytic activity in the quadratic model. AgC was positively correlated with antibacterial activity. Cytotoxicity was proportional to AgC while inversely proportional to PDT. Finally, the optimization values were AgC 3.08 w/w% and PDT 28 min. Under this optimal condition, the relatively high silver proportion ensured the visible-light catalytic and antibacterial activity, while the longer PDT effectively reduced the cytotoxicity. This study is of significance for the safe and efficient application of silver-doped TiO₂ photocatalysts.

Keywords: Ag-doped TiO₂, cytotoxicity, inflammtion, fibrosis, response surface methodology

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Authors: J. T. Johnson, R. A. Atule, E. Gbodo

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The widespread problem of infant malnutrition in developing countries has stirred efforts in research, development and extension by both local and international organizations. As a result, the formulation and development of nutritious weaning foods from local and readily available raw materials which are cost effective has become imperative in many developing countries. Thus, local and readily available raw materials where used to compound and develop nutritious new infant formulae. The materials used for this study include maize, millet, cowpea, pumpkin, fingerlings, and fish bone. The materials where dried and blended to powder. The powders were weighed in the ratio of 4:4:4:3:1:1 respectively and were then mixed properly. Analysis of nutritive value was conducted on the formulae and compared with NAN-2 standard and results reveals that the formulae had reasonable amount of moisture, lipids, carbohydrate, protein, and fibre. Although NAN-2 was superior in both carbohydrate and protein, the new infant formula was higher in mineral elements, vitamins, fibre, and lipids. All the essentials vitamins and both macro and micro minerals where found in appreciable quantity capable of meeting the biochemical and physiological demand of the body while the anti-nutrients composition were significantly below FAO and WHO safe limits. Finally, the compounded infant formulae was feed to a set of albino Wistar rats while some other set of rats was feed with NAN-2 for the period of twenty seven (27) days and body weight was measure at three days intervals. The results of body weight changes was spectacular as their body weight over shot or almost double that of those animals that were feed with NAN-2 at each point of measurement. The results suggest that the widespread problem of infant malnutrition in the developing world especially among the low income segment of the society can now be reduced if not totally eradicated since nutritive and cost effective weaning formulae can be prepared locally from common readily available materials.

Keywords: formulation, nutritive value, local, materials

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Authors: Cora Fernandez Dacosta, John A. Posada, Andrea Ramirez

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The biodegradable family of polymers polyhydroxyalkanoates are interesting substitutes for convectional fossil-based plastics. However, the manufacturing and environmental impacts associated with their production via intracellular bacterial fermentation are strongly dependent on the raw material used and on energy consumption during the extraction process, limiting their potential for commercialization. Industrial wastewater is studied in this paper as a promising alternative feedstock for waste valorization. Based on results from laboratory and pilot-scale experiments, a conceptual process design, techno-economic analysis and life cycle assessment are developed for the large-scale production of the most common type of polyhydroxyalkanoate, polyhydroxbutyrate. Intracellular polyhydroxybutyrate is obtained via fermentation of microbial community present in industrial wastewater and the downstream processing is based on chemical digestion with surfactant and hypochlorite. The economic potential and environmental performance results help identifying bottlenecks and best opportunities to scale-up the process prior to industrial implementation. The outcome of this research indicates that the fermentation of wastewater towards PHB presents advantages compared to traditional PHAs production from sugars because the null environmental burdens and financial costs of the raw material in the bioplastic production process. Nevertheless, process optimization is still required to compete with the petrochemicals counterparts.

Keywords: circular economy, life cycle assessment, polyhydroxyalkanoates, waste valorization

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Authors: Jacinta Musyoka, Wesley Too

Abstract:

Cervical cancer is the second leading cause of cancer-related deaths in Kenya and the second most common cancer among women, yet preventable following prevention strategies put in place, which includes vaccination with Human Papilloma Virus Vaccine (HPPV) among the young adolescent girls. Kenya has the highest burden of cervical cancer and the leading cause of death among women of reproductive age and is a known frequent type of cancer amongst women. This is expected to double by 2025 if the necessary steps are not taken, which include vaccinating girls between the ages of 9 and 14 and screening women. Parental decision is critical in ensuring that their daughters receive this vaccine. Hence this study sought to establish parental willingness and factors associate with the acceptability to vaccine adolescent daughters against the human papilloma virus for cervical cancer prevention in Machakos County, Eastern Region of Kenya. Method: Cross-sectional study design utilizing a mixed methods approach was used to collect data from Nguluni Health Centre in Machakos County; Matungulu sub-county, Kenya. This study targeted all parents of adolescent girls seeking health care services in the Matungulu sub-county area who were aged 18 years and above. A total of 220 parents with adolescent girls aged 10-14 years were enrolled into the study after informed consent were sought. All ethical considerations were observed. Quantitative data were analyzed using Multivariate regression analysis, and thematic analysis was used for qualitative data related to perceptions of parents on HPVV. Results, conclusions, and recommendations- ongoing. We expect to report findings and articulate contributions based on the study findings in due course before October 2022

Keywords: adolescents, human papilloma virus, kenya, parents

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Authors: Marju Ben Sayed, Shigeko Haruyama

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Among all kinds of natural disaster, the flood is a common feature in rapidly urbanizing Dhaka city. In this research, assessment of flood risk of Dhaka metropolitan area has been investigated by using an integrated approach of GIS, remote sensing and socio-economic data. The purpose of the study is to measure the flooding risk concerning with the flood protection embankment in big flooding events (1988, 1998 and 2004) and urbanization of Dhaka metropolitan zone. In this research, we considered the Dhaka city into two parts; East Dhaka (outside the flood protection embankment) and West Dhaka (inside the flood protection embankment). Using statistical data, we explored the socio-economic status of the study area population by comparing the density of population, land price and income level. We have drawn the cross section profile of the flood protection embankment into three different points for realizing the flooding risk in the study area, especially in the big flooding year (1988, 1998 and 2004). According to the physical condition of the study area, the land use/land cover map has been classified into five classes. Comparing with each land cover unit, historical weather station data and the socio-economic data, the flooding risk has been evaluated. Moreover, we compared between DEM data and each land cover units to find out the relationship with flood. It is expected that, this study could contribute to effective flood forecasting, relief and emergency management for a future flood event in Dhaka city.

Keywords: land use, land cover change, socio-economic, Dhaka city, GIS, flood

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Authors: Sumattana Glangkarn, Vorapoj Promasatayaprot

Abstract:

Background: Proportion of population ageing in Thailand has been increased rapidly in the past decades according to living longer and the fertility rates have decreased. The most important challenge related to this situation is to consider how to improve quality and years of healthy of life. This study aimed to implement the older persons’ long term care (LTC) system for elderly care by family and community. Method: The Consolidated Framework for Implementation Research (CFIR) was employed for guiding and evaluating an implementation process in ageing care. The CFIR composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Results: most elderly participants were couples, educating primary school and living with children and grandchildren. More than half of them had chronic diseases such as diabetes mellitus and hypertension. Factor analysis revealed factors related to health care of older participants which consisted of exercise, diet, accidental prevention, relaxation, self-care capacity, joyfulness, family relationship, and personal hygiene. A pre-implementation phase showed intervention characteristics included facilities and services of the LTC policy from the Ministry of Public Health. The complexities of the LTC and relative advantages were explained. Community leaders, public health volunteers, care givers and health professionals had participated in the LTC activities. Outer and inner settings consisted of context of community, culture, and readiness. Characteristics of the individuals related to knowledge, self-efficacy, perceptions, and believes. The process consisted of planning, acting, observing, and reflecting. The implementation outcomes and service outcomes had been evaluated during-implementation phase. Conclusion: the participation of caregivers, community leaders, public health volunteers, and health professionals had supported the LTC services. Thus, family and community care could improve quality of life of the ageing.

Keywords: ageing, CFIR, long term care, implementation

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Authors: Corinna Barraco, Ornella Salimbene

Abstract:

This research involves the Ethiopian locality of Jeldi (North Africa), an area particularly affected by water shortage and in which the pumping and treatment of drinking water are extremely sensitive issues. The study aims to develop and apply low-cost tools for the design of solar water pumping and water purification systems in a not developed country. Consequently, two technical tools have been implemented in Excel i) Solar photovoltaic Pumping (Spv-P) ii) Water treatment (Wt). The Spv-P tool was applied to the existing well (depth 110 [m], dynamic water level 90 [m], static water level 53 [m], well yield 0.1728 [m³h⁻¹]) in the Jeldi area, where estimated water demand is about 50 [m3d-1]. Through the application of the tool, it was designed the water extraction system of the well, obtaining the number of pumps and solar panels necessary for water pumping from the well of Jeldi. Instead, the second tool Wt has been applied in the subsequent phase of extracted water treatment. According to the chemical-physical parameters of the water, Wt returns as output the type of purification treatment(s) necessary to potable the extracted water. In the case of the well of Jeldi, the tool identified a high criticality regarding the turbidity parameter (12 [NTU] vs 5 [NTU]), and a medium criticality regarding the exceeding limits of sodium concentration (234 [mg/L Na⁺] vs 200 [mg/L Na⁺]) and ammonia (0.64 [mg/L NH³-N] vs 0.5 [mg/L NH³-N]). To complete these tools, two specific manuals are provided for the users. The joint use of the two tools would help reduce problems related to access to water resources compared to the current situation and represents a simplified solution for the design of pumping systems and analysis of purification treatments to be performed in undeveloped countries.

Keywords: drinking water, Ethiopia, treatments, water pumping

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Authors: M. N. Khajavi, S. Nasiri, E. Farokhi, M. R. Bavir

Abstract:

Alcohol fuels are renewable, have low pollution and have high octane number; therefore, they are important as fuel in internal combustion engines. Percentage detection of these alcoholic fuels with gasoline is a complicated, time consuming, and expensive process. Nowadays, these processes are done in equipped laboratories, based on international standards. The aim of this research is to determine percentage detection of different fuels based on vibration analysis of engine block signals. By doing, so considerable saving in time and cost can be achieved. Five different fuels consisted of pure gasoline (G) as base fuel and combination of this fuel with different percent of ethanol and methanol are prepared. For example, volumetric combination of pure gasoline with 10 percent ethanol is called E10. By this convention, we made M10 (10% methanol plus 90% pure gasoline), E30 (30% ethanol plus 70% pure gasoline), and M30 (30% Methanol plus 70% pure gasoline) were prepared. To simulate real working condition for this experiment, the vehicle was mounted on a chassis dynamometer and run under 1900 rpm and 30 KW load. To measure the engine block vibration, a three axis accelerometer was mounted between cylinder 2 and 3. After acquisition of vibration signal, eight time feature of these signals were used as inputs to an Adaptive Neuro Fuzzy Inference System (ANFIS). The designed ANFIS was trained for classifying these five different fuels. The results show suitable classification ability of the designed ANFIS network with 96.3 percent of correct classification.

Keywords: internal combustion engine, vibration signal, fuel composition, classification, ANFIS

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