Search results for: adult weight

Authors: L. Kanoksak, N. Sukanya, L. Napatsorn, T. Siriporn

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A growing population and demand for packaging are driving up the usage of natural resources as raw materials in the pulp and paper industry. Long-term effects of environmental is disrupting people's way of life all across the planet. Finding pulp sources to replace wood pulp is therefore necessary. To produce wood pulp, various other potential plants or plant parts can be employed as substitute raw materials. For example, pulp and paper were made from agricultural residue that mainly included pulp can be used in place of wood. In this study, cocoa pod husks were an agricultural residue of the cocoa and chocolate industries. To develop composite materials to replace wood pulp in packaging materials. The paper was coated with polybutylene adipate-co-terephthalate (PBAT). By selecting and cleaning fresh cocoa pod husks, the size was reduced. And the cocoa pod husks were dried. The morphology and elemental composition of cocoa pod husks were studied. To evaluate the mechanical and physical properties, dried cocoa husks were extracted using the soda-pulping process. After selecting the best formulations, paper with a PBAT bioplastic coating was produced on a paper-forming machine Physical and mechanical properties were studied. By using the Field Emission Scanning Electron Microscope/Energy Dispersive X-Ray Spectrometer (FESEM/EDS) technique, the structure of dried cocoa pod husks showed the main components of cocoa pod husks. The appearance of porous has not been found. The fibers were firmly bound for use as a raw material for pulp manufacturing. Dry cocoa pod husks contain the major elements carbon (C) and oxygen (O). Magnesium (Mg), potassium (K), and calcium (Ca) were minor elements that were found in very small levels. After that cocoa pod husks were removed from the soda-pulping process. It found that the SAQ5 formula produced pulp yield, moisture content, and water drainage. To achieve the basis weight by TAPPI T205 sp-02 standard, cocoa pod husk pulp and modified starch were mixed. The paper was coated with bioplastic PBAT. It was produced using bioplastic resin from the blown film extrusion technique. It showed the contact angle, dispersion component and polar component. It is an effective hydrophobic material for rigid packaging applications.

Keywords: cocoa pod husks, agricultural residue, composite material, rigid packaging

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Venkata Srikanth Meka, Nur Arthirah Binti Ahmad Tarmizi Tan, Muhammad Syahmi Bin Md Nazir, Adinarayana Gorajana, Senthil Rajan Dharmalingam

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Biphasic drug delivery systems are designed to release drug at two different rates, either fast/prolonged or prolonged/fast. A fast/prolonged release system provides a burst drug release at initial stage followed by a slow release over a prolonged period of time and in case of prolonged/fast release system, the release pattern is vice versa. Terminalia catappa gum (TCG) is a natural polymer and was successfully proven as a novel pharmaceutical excipient. The main objective of the present research is to investigate the applicability of natural polymer, Terminalia catappa gum in the design of oral biphasic drug delivery system in the form of mini tablets by using a model drug, buspirone HCl. This investigation aims to produce a biphasic release drug delivery system of buspirone by combining immediate release and prolonged release mini tablets into a capsule. For immediate release mini tablets, a dose of 4.5 mg buspirone was prepared by varying the concentration of superdisintegrant; crospovidone. On the other hand, prolonged release mini tablets were produced by using different concentrations of the natural polymer; TCG with a buspirone dose of 3mg. All mini tablets were characterized for weight variation, hardness, friability, disintegration, content uniformity and dissolution studies. The optimized formulations of immediate and prolonged release mini tablets were finally combined in a capsule and was evaluated for release studies. FTIR and DSC studies were conducted to study the drug-polymer interaction. All formulations of immediate release and prolonged release mini tablets were passed all the in-process quality control tests according to US Pharmacopoeia. The disintegration time of immediate release mini tablets of different formulations was varied from 2-6 min, and maximum drug release was achieved in lesser than 60 min. Whereas prolonged release mini tablets made with TCG have shown good drug retarding properties. Formulations were controlled for about 4-10 hrs with varying concentration of TCG. As the concentration of TCG increased, the drug release retarding property also increased. The optimised mini tablets were packed in capsules and were evaluated for the release mechanism. The capsule dosage form has clearly exhibited the biphasic release of buspirone, indicating that TCG is a suitable natural polymer for this study. FTIR and DSC studies proved that there was no interaction between the drug and polymer. Based on the above positive results, it can be concluded that TCG is a suitable polymer for the biphasic drug delivery systems.

Keywords: Terminalia catappa gum, biphasic release, mini tablets, tablet in capsule, natural polymers

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Authors: Hachul Jung, Ahee Kim, Sanghoon Lee, Dahye Kwon, Songwoo Yoon, Jinhee Moon

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We fabricated a wearable patch device including novel patch type flexible dry electrode based on carbon nanofibers (CNFs) and silicone-based elastomer (MED 6215) for real-time ECG monitoring. There are many methods to make flexible conductive polymer by mixing metal or carbon-based nanoparticles. In this study, CNFs are selected for conductive nanoparticles because carbon nanotubes (CNTs) are difficult to disperse uniformly in elastomer compare with CNFs and silver nanowires are relatively high cost and easily oxidized in the air. Wearable patch is composed of 2 parts that dry electrode parts for recording bio signal and sticky patch parts for mounting on the skin. Dry electrode parts were made by vortexer and baking in prepared mold. To optimize electrical performance and diffusion degree of uniformity, we developed unique mixing and baking process. Secondly, sticky patch parts were made by patterning and detaching from smooth surface substrate after spin-coating soft skin adhesive. In this process, attachable and detachable strengths of sticky patch are measured and optimized for them, using a monitoring system. Assembled patch is flexible, stretchable, easily skin mountable and connectable directly with the system. To evaluate the performance of electrical characteristics and ECG (Electrocardiography) recording, wearable patch was tested by changing concentrations of CNFs and thickness of the dry electrode. In these results, the CNF concentration and thickness of dry electrodes were important variables to obtain high-quality ECG signals without incidental distractions. Cytotoxicity test is conducted to prove biocompatibility, and long-term wearing test showed no skin reactions such as itching or erythema. To minimize noises from motion artifacts and line noise, we make the customized wireless, light-weight data acquisition system. Measured ECG Signals from this system are stable and successfully monitored simultaneously. To sum up, we could fully utilize fabricated wearable patch devices for real-time ECG monitoring easily.

Keywords: carbon nanofibers, ECG monitoring, flexible dry electrode, wearable patch

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Authors: Taisiia Gorshkova

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Since the 1980s, spatial correlation models have been used more often to model regional indicators. An increasingly popular method for studying regional indicators is modeling taking into account spatial relationships between objects that are part of the same economic zone. In 2000s the new class of model – spatial vector autoregressions was developed. The main difference between standard and spatial vector autoregressions is that in the spatial VAR (SpVAR), the values of indicators at time t may depend on the values of explanatory variables at the same time t in neighboring regions and on the values of explanatory variables at time t-k in neighboring regions. Thus, VAR is a special case of SpVAR in the absence of spatial lags, and the spatial panel data model is a special case of spatial VAR in the absence of time lags. Two specifications of SpVAR were applied to Russian regional data for 2000-2017. The values of GRP and regional CPI are used as endogenous variables. The lags of GRP, CPI and the unemployment rate were used as explanatory variables. For comparison purposes, the standard VAR without spatial correlation was used as “naïve” model. In the first specification of SpVAR the unemployment rate and the values of depending variables, GRP and CPI, in neighboring regions at the same moment of time t were included in equations for GRP and CPI respectively. To account for the values of indicators in neighboring regions, the adjacency weight matrix is used, in which regions with a common sea or land border are assigned a value of 1, and the rest - 0. In the second specification the values of depending variables in neighboring regions at the moment of time t were replaced by these values in the previous time moment t-1. According to the results obtained, when inflation and GRP of neighbors are added into the model both inflation and GRP are significantly affected by their previous values, and inflation is also positively affected by an increase in unemployment in the previous period and negatively affected by an increase in GRP in the previous period, which corresponds to economic theory. GRP is not affected by either the inflation lag or the unemployment lag. When the model takes into account lagged values of GRP and inflation in neighboring regions, the results of inflation modeling are practically unchanged: all indicators except the unemployment lag are significant at a 5% significance level. For GRP, in turn, GRP lags in neighboring regions also become significant at a 5% significance level. For both spatial and “naïve” VARs the RMSE were calculated. The minimum RMSE are obtained via SpVAR with lagged explanatory variables. Thus, according to the results of the study, it can be concluded that SpVARs can accurately model both the actual values of macro indicators (particularly CPI and GRP) and the general situation in the regions

Keywords: forecasting, regional data, spatial econometrics, vector autoregression

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Authors: Juliet Sorensen, Anna Maitland

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Introduction: Characterized by lack of water and sanitation, food insecurity, and low access to hospitals and clinics, informal urban settlements in Lagos, Nigeria have very poor health outcomes. With little education and a general inability to demand basic rights, these communities are often disempowered and isolated from understanding, claiming, or owning their health needs. Utilizing community-based participatory research characterized by interdisciplinary, cross-cultural partnerships, evidence-based assessments, and both primary and secondary source research, a holistic health education and advocacy program was developed in Lagos to address health barriers for targeted communities. This includes a first of its kind guide formulated to teach community-based health educators how to transmit health information to low-literacy Nigerian audiences while supporting behavior change models and social support mechanisms. This paper discusses the interdisciplinary contributions to developing a health education program while also looking at the need for greater beneficiary ownership and implementation of health justice and access. Methods: In March 2016, an interdisciplinary group of medical, legal, and business graduate students and faculty from Northwestern University conduced a Health Needs Assessment (HNA) in Lagos with a partner and a local non-governmental organization. The HNA revealed that members of informal urban communities in Lagos were lacking basic health literacy, but desired to remedy this lacuna. Further, the HNA revealed that even where the government mandates specific services, many vulnerable populations are unable to access these services. The HNA concluded that a program focused on education, advocacy, and organizing around anatomy, maternal and sexual health, infectious disease and malaria, HIV/AIDS, emergency care, and water and sanitation would respond to stated needs while also building capacity in communities to address health barriers. Results: Based on the HNA, including both primary and secondary source research on integrated health education approaches and behavior change models and responsive, adaptive material development, a holistic program was developed for the Lagos partners and first implemented in November 2016. This program trained community-nominated health educators in adult, low-literacy, knowledge exchange approaches, utilizing information identified by communities as a priority. After a second training in March 2017, these educators will teach community-based groups and will support and facilitate behavior change models and peer-support methods around basic issues like hand washing and disease transmission. They will be supported by community paralegals who will help ensure that newly trained community groups can act on education around access, such as receiving free vaccinations, maternal health care, and HIV/AIDS medicines. Materials will continue to be updated as needs and issues arise, with a focus on identifying best practices around health improvements that can be shared across these partner communities. Conclusion: These materials are the first of their kind, and address a void of health information and understanding pervasive in informal-urban Lagos communities. Initial feedback indicates high levels of commitment and interest, as well as investment by communities in these materials, largely because they are responsive, targeted, and build community capacity. This methodology is an important step in dignity-based health justice solutions, albeit in the process of refinement.

Keywords: community health educators, interdisciplinary and cross cultural partnerships, health justice and access, Nigeria

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Authors: Sohyoung Won, Heebal Kim, Dajeong Lim

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Genomic prediction is an effective way to measure the abilities of livestock for breeding based on genomic estimated breeding values, statistically predicted values from genotype data using best linear unbiased prediction (BLUP). Using haplotypes, clusters of linked single nucleotide polymorphisms (SNPs), as markers instead of individual SNPs can improve the reliability of genomic prediction since the probability of a quantitative trait loci to be in strong linkage disequilibrium (LD) with markers is higher. To efficiently use haplotypes in genomic prediction, finding optimal ways to define haplotypes is needed. In this study, 770K SNP chip data was collected from Hanwoo (Korean cattle) population consisted of 2506 cattle. Haplotypes were first defined in three different ways using 770K SNP chip data: haplotypes were defined based on 1) length of haplotypes (bp), 2) the number of SNPs, and 3) k-medoids clustering by LD. To compare the methods in parallel, haplotypes defined by all methods were set to have comparable sizes; in each method, haplotypes defined to have an average number of 5, 10, 20 or 50 SNPs were tested respectively. A modified GBLUP method using haplotype alleles as predictor variables was implemented for testing the prediction reliability of each haplotype set. Also, conventional genomic BLUP (GBLUP) method, which uses individual SNPs were tested to evaluate the performance of the haplotype sets on genomic prediction. Carcass weight was used as the phenotype for testing. As a result, using haplotypes defined by all three methods showed increased reliability compared to conventional GBLUP. There were not many differences in the reliability between different haplotype defining methods. The reliability of genomic prediction was highest when the average number of SNPs per haplotype was 20 in all three methods, implying that haplotypes including around 20 SNPs can be optimal to use as markers for genomic prediction. When the number of alleles generated by each haplotype defining methods was compared, clustering by LD generated the least number of alleles. Using haplotype alleles for genomic prediction showed better performance, suggesting improved accuracy in genomic selection. The number of predictor variables was decreased when the LD-based method was used while all three haplotype defining methods showed similar performances. This suggests that defining haplotypes based on LD can reduce computational costs and allows efficient prediction. Finding optimal ways to define haplotypes and using the haplotype alleles as markers can provide improved performance and efficiency in genomic prediction.

Keywords: best linear unbiased predictor, genomic prediction, haplotype, linkage disequilibrium

Procedia PDF Downloads 139

Authors: Krupali Mehta, Sandip Bhatt, Umesh Trivedi, Bhavesh Bharatiya, Mukesh Ranjan, Atindra D. Shukla

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Owing to the dominating surface forces and large-scale surface interactions, the nano-scale particles face difficulties in getting suspended in various media. Magnetic nanoparticles of iron oxide offer a great deal of promise due to their ease of preparation, reasonable magnetic properties, low cost and environmental compatibility. We intend to modify the surface of magnetic Fe₂O₃ nanoparticles with selected surface modifying agents using simple and effective single-step chemical reactions in order to enhance dispersibility of magnetic nanoparticles in non-polar media. Magnetic particles were prepared by hydrolysis of Fe²⁺/Fe³⁺ chlorides and their subsequent oxidation in aqueous medium. The dried particles were then treated with Octadecyl quaternary ammonium silane (Terrasil™), stearic acid and gallic acid ester of stearyl alcohol in ethanol separately to yield S-2 to S-4 respectively. The untreated Fe₂O₃ was designated as S-1. The surface modified nanoparticles were then analysed with Dynamic Light Scattering (DLS), Fourier Transform Infrared spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Gravimetric Analysis (TGA) and Scanning Electron Microscopy and Energy dispersive X-Ray analysis (SEM-EDAX). Characterization reveals the particle size averaging 20-50 nm with and without modification. However, the crystallite size in all cases remained ~7.0 nm with the diffractogram matching to Fe₂O₃ crystal structure. FT-IR suggested the presence of surfactants on nanoparticles’ surface, also confirmed by SEM-EDAX where mapping of elements proved their presence. TGA indicated the weight losses in S-2 to S-4 at 300°C onwards suggesting the presence of organic moiety. Hydrophobic character of modified surfaces was confirmed with contact angle analysis, all modified nanoparticles showed super hydrophobic behaviour with average contact angles ~129° for S-2, ~139.5° for S-3 and ~151° for S-4. This indicated that surface modified particles are super hydrophobic and they are easily dispersible in non-polar media. These modified particles could be ideal candidates to be suspended in oil-based fluids, polymer matrices, etc. We are pursuing elaborate suspension/sedimentation studies of these particles in various oils to establish this conjecture.

Keywords: iron nanoparticles, modification, hydrophobic, dispersion

Procedia PDF Downloads 140

Authors: Saddam Husain Dhobi, Bikrant Karki

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The main objective of this paper is save money, balance ecosystem of the terrestrial organism, control global warming, and enhancing the storage capacity of the battery with requiring weight and thinness by using Cyanobacteria in the battery. To fulfill this purpose of paper we can use different methods: Analysis, Biological, Chemistry, theoretical and Physics with some engineering design. Using this different method, we can produce the special type of battery that has the long life, high storage capacity, and clean environment, save money so on and by using the byproduct of Cyanobacteria i.e. glucose. Cyanobacteria are a special type of bacteria that produces different types of extracellular glucoses and oxygen with the help of little sunlight, water, and carbon dioxide and can survive in freshwater, marine and in the land as well. In this process, O₂ is more in the comparison to plant due to rapid growth rate of Cyanobacteria. The required materials are easily available in this process to produce glucose with the help of Cyanobacteria. Since CO₂, is greenhouse gas that causes the global warming? We can utilize this gas and save our ecological balance and the byproduct (glucose) C₆H₁₂O₆ can be utilized for raw material for the battery where as O₂ escape is utilized by living organism. The glucose produce by Cyanobateria goes on Krebs's Cycle or Citric Acid Cycle, in which glucose is complete, oxidizes and all the available energy from glucose molecule has been release in the form of electron and proton as energy. If we use a suitable anodes and cathodes, we can capture these electrons and protons to produce require electricity current with the help of byproduct of Cyanobacteria. According to "Virginia Tech Bio-battery" and "Sony" 13 enzymes and the air is used to produce nearly 24 electrons from a single glucose unit. In this output power of 0.8 mW/cm, current density of 6 mA/cm, and energy storage density of 596 Ah/kg. This last figure is impressive, at roughly 10 times the energy density of the lithium-ion batteries in your mobile devices. When we use Cyanobacteria in battery, we are able to reduce Carbon dioxide, Stop global warming, and enhancing the storage capacity of battery more than 10 times that of lithium battery, saving money, balancing ecology. In this way, we can produce energy from the Cyanobacteria and use it in battery for different benefits. In addition, due to the mass, size and easy cultivation, they are better to maintain the size of battery. Hence, we can use Cyanobacteria for the battery having suitable size, enhancing the storing capacity of battery, helping the environment, portability and so on.

Keywords: anode, byproduct, cathode, cyanobacteri, glucose, storage capacity

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Authors: Alexander Chinyere Nwankpa, Nneka Ngozi Nwankpa

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In Nigeria, the Federal government is trying to make sure that everyone has access to enough food that is nutritiously adequate and safe. But in the southwest of Nigeria, notably in Ondo State, the most valuable minerals such as oil and gas, bitumen, kaolin, limestone talc, columbite, tin, gold, coal, and phosphate are abundant. Therefore, some regions of Ondo State are now linked to large quantities of natural radioactivity as a result of the mineral presence. In this work, the baseline radioactivity levels in some of the most important food crops in Ondo State were analyzed, allowing for the prediction of probable radiological health impacts. To this effect, maize (Zea mays), yam (Dioscorea alata) and cassava (Manihot esculenta) tubers were collected from the farmlands in the State because they make up the majority of food's nutritional needs. Ondo State was divided into eight zones in order to provide comprehensive coverage of the research region. At room temperature, the maize (Zea mays), yam (Dioscorea alata), and cassava (Manihot esculenta) samples were dried until they reached a consistent weight. They were pulverized, homogenized, and 250 g packed in a 1-liter Marinelli beaker and kept for 28 days to achieve secular equilibrium. The activity concentrations of Radium-226 (Ra-226), Thorium-232 (Th-232), and Potassium-40 (K-40) were determined in the food samples using Gamma-ray spectrometry. Firstly, the Hyper Pure Germanium detector was calibrated using standard radioactive sources. The gamma counting, which lasted for 36000s for each sample, was carried out in the Centre for Energy Research and Development, Obafemi Awolowo University, Ile-Ife, Nigeria. The mean activity concentration of Ra-226, Th-232 and K-40 for yam were 1.91 ± 0.10 Bq/kg, 2.34 ± 0.21 Bq/kg and 48.84 ± 3.14 Bq/kg, respectively. The content of the radionuclides in maize gave a mean value of 2.83 ± 0.21 Bq/kg for Ra-226, 2.19 ± 0.07 Bq/kg for Th-232 and 41.11 ± 2.16 Bq/kg for K-40. The mean activity concentrations in cassava were 2.52 ± 0.31 Bq/kg for Ra-226, 1.94 ± 0.21 Bq/kg for Th-232 and 45.12 ± 3.31 Bq/kg for K-40. The average committed effective doses in zones 6-8 were 0.55 µSv/y for the consumption of yam, 0.39 µSv/y for maize, and 0.49 µSv/y for cassava. These values are higher than the annual dose guideline of 0.35 µSv/y for the general public. Therefore, the values obtained in this work show that there is radiological contamination of some foodstuffs consumed in some parts of Ondo State. However, we recommend that systematic and appropriate methods also need to be established for the measurement of gamma-emitting radionuclides since these constitute important contributors to the internal exposure of man through ingestion, inhalation, or wound on the body.

Keywords: contamination, environment, radioactivity, radionuclides

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Authors: Marios Papaevripidou, Yvoni Pavlou, Zacharias Zacharia

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Embodied cognition and additional (touch) sensory channel theories indicate that physical manipulation is crucial to learning since it provides, among others, touch sensory input, which is needed for constructing knowledge. Given these theories, the use of Physical Manipulatives (PM) becomes a prerequisite for learning. On the other hand, empirical research on Virtual Manipulatives (VM) (e.g., simulations) learning has provided evidence showing that the use of PM, and thus haptic sensory input, is not always a prerequisite for learning. In order to investigate which means of experimentation, PM or VM, are required for enhancing student science learning at the kindergarten level, an empirical study was conducted that sought to investigate the impact of haptic feedback on the conceptual understanding of pre-school students (n=44, age mean=5,7) in three science domains: beam balance (D1), sinking/floating (D2) and springs (D3). The participants were equally divided in two groups according to the type of manipulatives used (PM: presence of haptic feedback, VM: absence of haptic feedback) during a semi-structured interview for each of the domains. All interviews followed the Predict-Observe-Explain (POE) strategy and consisted of three phases: initial evaluation, experimentation, final evaluation. The data collected through the interviews were analyzed qualitatively (open-coding for identifying students’ ideas in each domain) and quantitatively (use of non-parametric tests). Findings revealed that the haptic feedback enabled students to distinguish heavier to lighter objects when held in hands during experimentation. In D1 the haptic feedback did not differentiate PM and VM students' conceptual understanding of the function of the beam as a mean to compare the mass of objects. In D2 the haptic feedback appeared to have a negative impact on PM students’ learning. Feeling the weight of an object strengthen PM students’ misconception that heavier objects always sink, whereas the scientifically correct idea that the material of an object determines its sinking/floating behavior in the water was found to be significantly higher among the VM students than the PM ones. In D3 the PM students outperformed significantly the VM students with regard to the idea that the heavier an object is the more the spring will expand, indicating that the haptic input experienced by the PM students served as an advantage to their learning. These findings point to the fact that PMs, and thus touch sensory input, might not always be a requirement for science learning and that VMs could be considered, under certain circumstances, as a viable means for experimentation.

Keywords: haptic feedback, physical and virtual manipulatives, pre-school science learning, science experimentation

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Authors: Barbara Farinon, Maurizio E. Picarella, Lorenzo Mancini, Andrea Mazzucato

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Italy is notoriously a secondary center of diversification for cultivated tomatoes (Solanum lycopersicum L.). The study of phenotypic and genetic diversity in landrace collections is important for germplasm conservation and biodiversity protection. Here, we set up to study the germplasm collected in the region of Lazio in Central Italy with a focus on the distinctiveness among landraces and the attribution of membership to unnamed accessions. Our regional collection included 30 accessions belonging to six different locally recognized landraces and 21 unnamed accessions. All accessions were gathered in Lazio and belonged to the collection held at the Regional Agency for the Development and Innovation of Agriculture in Lazio (ARSIAL, in the application of the Regional Act n. 15/2000, funded by Lazio Rural Development Plan 2014 – 2020 Agro-environmental Measure, Action 10.2.1) and at the University of Tuscia. We included 13 control genotypes as references. The collection showed wide phenotypic variability for several traits, such as fruit weight (range 14-277 g), locule number (2-12), shape index (0.54-2.65), yield (0.24-3.08 kg/plant), and soluble solids (3.4-7.5 °B). A few landraces showed uncommon phenotypes, such as potato leaf, colorless fruit epidermis, or delayed ripening. Multivariate analysis of 25 cardinal phenotypic variables grouped the named varieties and allowed to assign of some of the unnamed to recognized groups. A case study for distinctiveness is presented for the flattened-ribbed types that presented overlapping distribution according to the phenotypic data. Molecular markers retrieved by previous studies revealed differences compared to the phenotyping clustering, indicating that the named varieties “Scatolone di Bolsena” and “Pantano Romanesco” belong to the Marmande group, together with the reference landrace from Tuscany “Costoluto Fiorentino”. Differently, the landrace “Spagnoletta di Formia e Gaeta” was clearly distinct from the former at the molecular level. Therefore, a genotypic analysis of the analyzed collection appears needed to better define the molecular distinctiveness among the flattened-ribbed accessions, as well as to properly attribute the membership group of the unnamed accessions.

Keywords: distinctiveness, flattened-ribbed fruits, regional landraces, tomato

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Authors: Belay Mulat Fentie

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In today’s high decrement figure of the global economy, nations are facing many economic, social, and political challenges; universally, there is high distress of food and other survival insecurity. Further, as a result of conflict, natural disaster, and leadership influences, youths are existentially less empowered and unemployed, especially in developing countries. With this situation to handle well challenges, it’s important to search, investigate and deliberate about youth, unemployment, empowerment, and possible management fashions, as youths has a potential to carry and fight such battles. The method adopted is qualitative analysis of secondary data sources in youth empowerment, unemployment, and development as inclusive framework. Youth unemployment is a major development headache for most African countries. In Ethiopia, following weak youth empowerment, youth unemployment has been increased time to time; and quality education and organizations linkage matters as an important constraint. As a management challenge, although accessibility of quality education for Ethiopian youths is an important constraint; the country youths fortified deceptively and harassed in a vicious political challenge in their struggle to fetch social and economic changes in the country. Further, thousands of youths inactivated, criminalized, and lost their lives, and this makes youths to be hopeless, anger in their lives and pushes further to expose for addictions, prostitution, violence, and illegitimate migrations. This youth challenge didn’t only destinate in African countries, rather, indeed, the global burden and headed as a global agenda. As a resolution, the construction of a healthy education system can create independent youths that acquire success and accelerate development. Developing countries should ensue development in cultivation of empowerment tool through long and short-term education, implementing policy in action, diminishing wide ranged gaps of (religion, ethnicity & region), and take the high youth population as an opportunity and empower them. And further manage and empower youths to involve in decision making, in giving political weight and build a network on organizations to easily access jobs opportunities are important suggestion to alive youths in work, for both increasing their income and country food security balance.

Keywords: development, Ethiopia, management, unemployment, youth empowerment

Procedia PDF Downloads 137

Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: Ziara Carmelli G. Tan, Irene Carmelle S. Tan

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Background: Trichotillomania (TTM) and Major Depressive Disorder (MDD) are two psychiatric conditions that frequently co-occur, presenting a significant challenge for treatment due to their complex interplay. TTM involves repetitive hair-pulling, leading to noticeable hair loss and distress, while MDD is characterized by persistent low mood and loss of interest or pleasure, leading to dysfunctionality. This case report examines the intricate relationship between TTM and MDD in a young adult female, emphasizing the need for a comprehensive, multifaceted therapeutic approach to address both disorders effectively. Case Presentation: The patient is a 21-year-old female college student and youth church leader who presented with chronic hair-pulling and depressive symptoms. Her premorbid personality was marked by low self-esteem and a strong need for external validation. Despite her academic and social responsibilities and achievements, she struggled with managing her emotional distress, which was exacerbated by her family dynamics and her role within her church community. Her hair-pulling and mood symptoms were particularly triggered by self-esteem threats and feelings of inadequacy. She was diagnosed with Trichotillomania, Scalp and Major Depressive Disorder. Intervention/Management: The patient’s treatment plan was comprehensive, incorporating both pharmacological and non-pharmacological interventions. Initial pharmacologic management was Fluoxetine 20mg/day up, titrated to 40mg/day with no improvement; hence, shifted to Escitalopram 20mg/day and started with N-acetylcysteine 600mg/day with noted significant improvement in symptoms. Psychotherapeutic strategies played a crucial role in her treatment. These included supportive-expressive psychodynamic psychotherapy, which helped her explore and understand underlying emotional conflicts. Cognitive-behavioral techniques were employed to modify her maladaptive thoughts and behaviors. Grief processing was integrated to help her cope with significant losses. Family therapy was done to address conflicts and collaborate with the treatment process. Psychoeducation was provided to enhance her understanding of her condition and to empower her in her treatment journey. A suicide safety plan was developed to ensure her safety during critical periods. An interprofessional approach, which involved coordination with the Dermatology service for co-management, was also a key component of her treatment. Outcome: Over the course of 15 therapy sessions, the patient demonstrated significant improvement in both her depressive symptoms and hair-pulling behavior. Her active engagement in therapy, combined with pharmacological support, facilitated better emotional regulation and a more cohesive sense of self. Her adherence to the treatment plan, along with the collaborative efforts of the interprofessional team, contributed to her positive outcomes. Discussion: This case underscores the significance of addressing both TTM and its comorbid conditions to achieve effective treatment outcomes. The intricate interplay between TTM and MDD in the patient’s case highlights the importance of a comprehensive treatment plan that includes both pharmacological and psychotherapeutic approaches. Supportive-expressive psychodynamic psychotherapy, Cognitive-behavioral techniques, and Family therapy were particularly beneficial in addressing the complex emotional and behavioral aspects of her condition. The involvement of an interprofessional team, including dermatology co-management, was crucial in providing holistic care. Future practice should consider the benefits of such a multidisciplinary approach to managing complex cases like this, ensuring that both the psychological and physiological aspects of the disorders are adequately addressed.

Keywords: cognitive-behavioral therapy, interprofessional approach, major depressive disorder, psychodynamic psychotherapy, trichotillomania

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Authors: Ali Kamal M. Sami, Safa Almukhtar, Alaa Al-Krush, Ismael Hama-Amin Akha Weas, Ruqaya Ahmed Alqais

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Introduction and Objectives Lower urinary tract symptoms (LUTS) are common among men with benign prostatic hyperplasia (BPH). The combination of 5 alpha-reductase inhibitors and alpha-blockers has been used as a conservative treatment of male LUTS secondary to BPH. Nanotechnology structured water magnalife is a type of water that is produced by modulators and specific frequency and energy fields that transform ordinary water into this Nanowater. In this study, we evaluated the use of Nano-water with the conservative treatment and to see if it improves the outcome and gives better results in those patients with LUTS/BPH. Material and methods For a period of 3 months, 200 men with International Prostate Symptom Score (IPSS)≥13, maximum flow rate (Qmax)≤ 15ml/s, and prostate volume > 30 and <80 ccs were randomly divided into two groups. Group A 100 men were given Nano-water with the (tamsulosindutasteride) and group B 100 men were given ordinary bottled water with the (tamsulosindutasteride). The water bottles were unlabeled and were given in a daily dose of 20ml/kg body weight. Dutasteride 0.5mg and tamsulosin 0.4 mg daily doses. Both groups were evaluated for the IPSS, Qmax, Residual Urine (RU), International Index of Erectile Function–Erectile Function (IIEF-EF) domain at the beginning (baseline data), and at the end of the 3 months. Results Of the 200 men with LUTS who were included in this study, 193 men were followed, and 7 men dropped out of the study for different reasons. In group A which included 97 men with LUTS, IPSS decreased by 16.82 (from 20.47 to 6.65) (P<0.00001) and Qmax increased by 5.73 ml/s (from 11.71 to 17.44) (P<0.00001) and RU <50 ml in 88% of patients (P<0.00001) and IIEF-EF increased to 26.65 (from 16.85) (P<0.00001). While in group B, 96 men with LUTS, IPSS decreased by 8.74(from 19.59 to 10.85)(P<0.00001) and Qmax increased by 4.67 ml/s(from 10.74 to 15.41)(P<0.00001), RU<50 ml in 75% of patients (P<0.00001), and IIEF-EF increased to 21(from 15.87)(P<0.00001). Group A had better results than group B. IPSS in group A decreased to 6.65 vs 10.85 in group B(P<0.00001), also Qmax increased to 17.44 in group A vs 15.41 in group B(P<0.00001), group A had RU <50 ml in 88% of patients vs 75% of patients in group B(P<0.00001).Group A had better IIEF-EF which increased to 26.65 vs 21 in group B(P<0.00001). While the differences between the baseline data of both groups were statistically not significant. Conclusion The use of nanotechnology structured water magnalife gives a better result in terms of LUTS and scores in patients with BPH. This combination is showing improvements in IPSS and even in erectile function in those men after 3 months.

Keywords: nano water, lower urinary tract symptoms, benign prostatic hypertrophy, erectile dysfunction

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Authors: Mohamed Abdelkareem

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Remote sensing data contributed on predicting the prospective areas of water resources. Integration of microwave and multispectral data along with climatic, hydrologic, and geological data has been used here. In this article, Sentinel-2, Landsat-8 Operational Land Imager (OLI), Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), and Advanced Land Observing Satellite (ALOS) Phased Array Type L‐band Synthetic Aperture Radar (PALSAR) data were utilized to identify the geological, hydrologic and structural features of Wadi Asyuti which represents a defunct tributary of the Nile basin, in the eastern Sahara. The image transformation of Sentinel-2 and Landsat-8 data allowed characterizing the different varieties of rock units. Integration of microwave remotely-sensed data and GIS techniques provided information on physical characteristics of catchments and rainfall zones that are of a crucial role for mapping groundwater prospective zones. A fused Landsat-8 OLI and ALOS/PALSAR data improved the structural elements that difficult to reveal using optical data. Lineament extraction and interpretation indicated that the area is clearly shaped by the NE-SW graben that is cut by NW-SE trend. Such structures allowed the accumulation of thick sediments in the downstream area. Processing of recent OLI data acquired on March 15, 2014, verified the flood potential maps and offered the opportunity to extract the extent of the flooding zone of the recent flash flood event (March 9, 2014), as well as revealed infiltration characteristics. Several layers including geology, slope, topography, drainage density, lineament density, soil characteristics, rainfall, and morphometric characteristics were combined after assigning a weight for each using a GIS-based knowledge-driven approach. The results revealed that the predicted groundwater potential zones (GPZs) can be arranged into six distinctive groups, depending on their probability for groundwater, namely very low, low, moderate, high very, high, and excellent. Field and well data validated the delineated zones.

Keywords: GIS, remote sensing, groundwater, Egypt

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Authors: Hany Elsaid Fawaz Abdallah

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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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Authors: Amit Mallik, Anil K. Barik, Biswajit Pal

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The galloping advancement of research work on glass-ceramics stems from their wide applications in electronic industry and also to some extent in application oriented medical dentistry. TiO2, even in low concentration has been found to strongly influence the physical and mechanical properties of the glasses. Glass-ceramics is a polycrystalline ceramic material produced through controlled crystallization of glasses. Crystallization is accomplished by subjecting the suitable parent glasses to a regulated heat treatment involving the nucleation and growth of crystal phases in the glass. Mica glass-ceramics is a new kind of glass-ceramics based on the system SiO2•MgO•K2O•F. The predominant crystalline phase is synthetic fluormica, named fluorophlogopite. Mica containing glass-ceramics flaunt an exceptional feature of machinability apart from their unique thermal and chemical properties. Machinability arises from the randomly oriented mica crystals with a 'house of cards' microstructures allowing cracks to propagate readily along the mica plane but hindering crack propagation across the layers. In the present study, we have systematically investigated the crystallization, microstructure and mechanical behavior of barium fluorophlogopite mica-containing glass-ceramics of composition BaO•4MgO•Al2O3•6SiO2•2MgF2 nucleated by addition of 2, 4, 6 and 8 wt% TiO2. The glass samples were prepared by the melting technique. After annealing, different batches of glass samples for nucleation were fired at 730°C (2wt% TiO2), 720°C (4 wt% TiO2), 710°C (6 wt% TiO2) and 700°C (8 wt% TiO2) batches respectively for 2 h and ultimately heated to corresponding crystallization temperatures. The glass batches were analyzed by differential thermal analysis (DTA) and x-ray diffraction (XRD), scanning electron microscopy (SEM) and micro hardness indenter. From the DTA study, it is found that the fluorophlogopite mica crystallization exotherm appeared in the temperature range 886–903°C. Glass transition temperature (Tg) and crystallization peak temperature (Tp) increased with increasing TiO2 content up to 4 wt% beyond this weight% the glass transition temperature (Tg) and crystallization peak temperature (Tp) start to decrease with increasing TiO2 content up to 8 wt%. Scanning electron microscopy confirms the development of an interconnected ‘house of cards’ microstructure promoted by TiO2 as a nucleating agent. The increase in TiO2 content decreases the vicker’s hardness values in glass-ceramics.

Keywords: crystallization, fluormica glass, ‘house of cards’ microstructure, hardness

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Authors: Yumeho Obata, Mariko Era, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

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Dermatophagoides farinae is major mite allergens in indoors. D. farinae is often swarm over powder products (e.g. wheat flour), because it feeds on starch or protein that are included in them. Eating powder products which are mixed D.farinae causes various allergic symptoms. Therefore, the creation of food additive agents with high safety and control of mite effect is required. Fatty acid salts and spices are known that have pesticidal activities. This study describes the effects of fatty acid salts and spices against Dermatophagoides farinae. Materials and Methods: Potassium salts of 9 fatty acids (C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C18:1, C18:2, C18:3) were prepared by mixing the fatty acid with the appropriate amount of KOH solution to a concentration of 175 mM and pH 10.5. C12Cu and C12Zn were selected as other fatty acid salts. Cayenne pepper, habanero, Japanese pepper, mustard, jalapeno pepper, curry aroma and cinnamon were selected as spices. D. farina, have been cultured in laboratory. To rear the mites, double-soled dishes containing of sterilized food were put on the big plastic container (30.0 × 20.0 × 20.0cm) which had 100% ammonium nitrate solution in the bottom. Plastic container was placed on incubator at 25 °C and 64 % relative humidity (RH) under dark condition. Sterilized food composed of dried bonito flakes and dried yeast (Ebios), 1:1 by weight. The antiproliferative method, sample and medium culture were mixed in double-soled dish and kept at 25 °C and 64 % RH. Decrease rates were determined 1 week and 4 week after treatment under microscope. D. farina was considered to be dead if appendages did not move when prodded with a pin. Results and Conclusions: The results show that the fatty acids potassium showed no antiproliferative effects against D. farinae. On the other hand, Japanese pepper, mustard, curry aroma and cinnamon were effective to decrease propagative rate (over 80 %) after treatment for 1 week against D. farina. Japanese pepper, curry aroma and cinnamon were effective to decrease propagative rate (approximately 100 %) after treatment for 4 weeks against D. farina. Especially, Japanese pepper and cinnamon showed the fasted and the most consecutive antiproliferative effects. These results indicate that Japanese pepper and cinnamon have high antiproliferative effects against D. farina and suggest spices will be used as a food additive agent.

Keywords: fatty acid salts, spices, antiproliferative effects, dermatophagoides farinae

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Authors: Paule Olivia Akotto

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The recent literature suggests spending between 50%-85% of oil rents. However, there are not yet clear guidelines for allocating this windfall in the public investment system, while most of the resource-rich countries fail to improve their intergenerational mobility. We study a design of the optimal spending system in Senegal, a low-income developing country featuring newly discovered oil fields and low intergenerational mobility. We build a dynamic general equilibrium model in which rural and urban (Dakar and other urban centers henceforth OUC) households face different health, education, and employment opportunities based on their location, affecting their intergenerational mobility. The model captures the relationship between oil rents, public investment, and multidimensional inequality of opportunity. The government invests oil rents in three broad sectors: health and education, road and industries, and agriculture. Through endogenous productivity externality and human capital accumulation, our model generates the predominant position of Dakar and OUC households in terms of access to health, education, and employment in line with Senegal data. Rural households are worse off in all dimensions. We compute the optimal spending policy under two sets of simulation scenarios. Under the current Senegal public investment strategy, which weighs more health and education investments, we find that the reform maximizing the decline in inequality of opportunity between households, frontloads investment during the first eight years of the oil exploitation and spends the perpetual value of oil wealth thereafter. We will then identify the marginal winners and losers associated with this policy and its redistributive implications. Under our second set of scenarios, we will test whether the Senegalese economy can reach better equality of opportunity outcomes under this frontloading reform, by allowing the sectoral shares of investment to vary. The trade-off will be between cutting human capital investment in favor of agricultural and productive infrastructure or increasing the former. We will characterize the optimal policy by specifying where the higher weight should be. We expect that the optimal policy of the second set strictly dominates in terms of equality of opportunity, the optimal policy computed under the current investment strategy. Finally, we will quantify this optimal policy's aggregate and distributional effects on poverty, well-being, and gender earning gaps.

Keywords: developing countries, general equilibrium, inequality of opportunity, oil rents

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Authors: Shokooh Moghadam, Mohammad Taghi Khorasani, Sajjad Seifi Mofarah, M. Daliri

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Through the recent two decades, the use of magnetic-property materials with the aim of target cell’s separation and eventually cancer treatment has incredibly increased. Numerous factors can alter the efficacy of this method on curing. In this project, the effect of magnetic field on adhesion of PDL and L929 cells on nanocomposite of iron oxide/PHB with different density of iron oxides (1%, 2.5%, 5%) has been studied. The nanocamposite mentioned includes a polymeric film of poly hydroxyl butyrate and γ-Fe2O3 particles with the average size of 25 nanometer dispersed in it and during this process, poly vinyl alcohol with 98% hydrolyzed and 78000 molecular weight was used as an emulsion to achieve uniform distribution. In order to get the homogenous film, the solution of PHB and iron oxide nanoparticles were put in a dry freezer and in liquid nitrogen, which resulted in a uniform porous scaffold and for removing porosities a 100◦C press was used. After the synthesis of a desirable nanocomposite film, many different tests were performed, First, the particles size and their distribution in the film were evaluated by transmission electron microscopy (TEM) and even FTIR analysis and DMTA test were run in order to observe and accredit the chemical connections and mechanical properties of nanocomposites respectively. By comparing the graphs of case and control samples, it was established that adding nano particles caused an increase in crystallization temperature and the more density of γ-Fe2O3 lead to more Tg (glass temperature). Furthermore, its dispersion range and dumping property of samples were raised up. Moreover, the toxicity, morphologic changes and adhesion of fibroblast and cancer cells were evaluated by a variety of tests. All samples were grown in different density and in contact with cells for 24 and 48 hours within the magnetic fields of 2×10^-3 Tesla. After 48 hours, the samples were photographed with an optic and SEM and no sign of toxicity was traced. The number of cancer cells in the case of sample group was fairly more than the control group. However, there are many gaps and unclear aspects to use magnetic field and their effects in cancer and all diseases treatments yet to be discovered, not to neglect that there have been prominent step on this way in these recent years and we hope this project can be at least a minimum movement in this issue.

Keywords: nanocomposite, cell attachment, magnetic field, cytotoxicity

Procedia PDF Downloads 257

Authors: M. Saleem, M. Shahnawaz, A. W. Gandahi, S. M. Bhatti

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The micronutrients boron and zinc deficiencies are extensive in the areas of rice-wheat cropping system. Optimum levels of these nutrients in soil are necessary for healthy crop growth. Since rice and wheat are major staple food of worlds’ populace, the higher yields and nutrition status of these crops has direct effect on the health of human being and economy of the country. A field study was conducted to observe the direct and residual effect of two selected micronutrients boron (B) and zinc (Zn)) on rice and wheat crop growth and its grain nutrient status. Each plot received either B or Zn at the rates of 0, 1, 2, 3 and 4 kg B ha⁻¹, and 5, 10, 15 and 20 kg Zn ha⁻¹, combined B and Zn application at 1 kg B and 5 kg Zn ha⁻¹, 2 kg B and 10 kg Zn ha⁻¹. Colemanite ore were used as source of B and zinc sulfate for Zn. The second season wheat crop was planted in the same plots after the interval period of 30 days and during this time gap soil was fallow. Boron and Zn application significantly enhanced the plant height, number of tillers, Grains panicle⁻¹ seed index fewer empty grains panicle⁻¹ and yield of rice crop at all defined levels as compared to control. The highest yield (10.00 tons/ha) was recorded at 2 Kg B, 10 Kg Zn ha⁻¹ rates. Boron and Zn concentration in grain and straw significantly increased. The application of B also improved the nutrition status of rice as B, protein and total carbohydrates content of grain augmented. The analysis of soil samples collected after harvest of rice crop showed that the B and Zn content in post-harvest soil samples was high in colemanite and zinc sulfate applied plots. The residual B and Zn were also effectual for the second season wheat crop, as the growth parameters plant height, number of tillers, earhead length, weight 1000 grains, B and Zn content of grain significantly improved. The highest wheat grain yield (4.23 tons/ha) was recorded at the residual rates of 2 kg B and 10 kg Zn ha⁻¹ than the other treatments. This study showed that one application of B and Zn can increase crop yields for at least two consecutive seasons and the mineral colemanite can confidently be used as source of B for rice crop because very small quantities of these nutrients are consumed by first season crop and remaining amount was present in soil which were used by second season wheat crop for healthy growth. Consequently, there is no need to apply these micronutrients to the following crop when it is applied on the previous one.

Keywords: residual boron, zinc, rice, wheat

Procedia PDF Downloads 154

Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Ashti Morovati, Hushyar Azari, Bahram Pourghassem Gargari

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Objectives and goals: The prevalence of metabolic syndrome (MetS), as a major health burden for societies, is increasing. This clinical trial was conducted to evaluate the effects of CuEO supplementation on anthropometric indices, systolic and diastolic blood pressure, blood glucose level, insulin resistance and serum lipid level in patients suffering from MetS. Methods: This was a randomized, triple‐blind, placebo‐controlled clinical trial in which 56 patients with MetS aged 18–60 years who fulfilled the eligibility criteria were randomly allocated to an intervention or a control group. Inclusion criteria for the study were comprised of diagnosis of MetS according to the new International Federation of Diabetes. The exclusion criteria were defined as: taking herbal supplements, use of drugs having evident interaction with cumin such as anti‐depressant drugs, vitamin D, omega 3, selenium, zinc, smoking, pregnancy, or breastfeeding, suffering from cancer, having any history of gastrointestinal and hepatic, cardiovascular, thyroid and kidney disorders, and menopause. 75 mg CuEO or placebo soft gels were administered three times daily to the participants for eight weeks. The soft gel consumption was checked by asking the participants to bring the medication containers in the follow‐up visits at the 4th and the 8th weeks of the study. Data pertaining to blood pressure, height, weight, waist circumference, hip circumference and BMI, as well as food consumption were collected at the beginning and end of the study. Fasting blood samples ( glucose, triglyceride, total cholesterol, HDL-cholesterol and LDL-cholesterol) were obtained and biochemical measurements were assessed at the beginning and end of the study. Results: At eight weeks, a total of 44 patients completed this study. Except for diastolic blood pressure (DBP), the other assessed variables were not significantly different between the two groups. In intra group analysis, placebo and CuEO groups both had insignificant decrements in DBP (mean difference [MD] with 95% CI: −3.31 [−7.11, 0.47] and −1.77 [−5.95, 2.40] mmHg, respectively). However, DBP was significantly lower in CuEO compared with the placebo group at the end of study (81.41 ± 5.88 vs. 84.09 ± 5.54 mmHg, MD with 95% CI: −3.98 [−7.60, −0.35] mmHg, p < .05). Conclusions: The results of this study indicated that CuEO does not have any effect on MetS components, except for DBP in patients with MetS.

Keywords: blood pressure, fasting blood glucose, lipid profile, waist circumference

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Authors: Javier Alfonso Bonilla-Chávez, Angélica Lozano

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In North America, more than 2,000 people annually die in accidents related to railroad tracks. In 2020, collisions at grade crossings were the main cause of deaths related to railway accidents in Mexico. Railway networks have constant interaction with motor transport users, cyclists, and pedestrians, mainly in grade crossings, where is the greatest vulnerability and risk of accidents. Usually, accidents at grade crossings are directly related to risky behavior and non-compliance with regulations by motorists, cyclists, and pedestrians, especially in developing countries. Around the world, countries classify these crossings in different ways. In Mexico, according to their dangerousness (high, medium, or low), types A, B and C have been established, recommending for each one different type of auditive and visual signaling and gates, as well as horizontal and vertical signaling. This classification is based in a weighting, but regrettably, it is not explained how the weight values were obtained. A review of the variables and the current approach for the grade crossing classification is required, since it is inadequate for some crossings. In contrast, North America (USA and Canada) and European countries consider a broader classification so that attention to each crossing is addressed more precisely and equipment costs are adjusted. Lack of a proper classification, could lead to cost overruns in the equipment and a deficient operation. To exemplify the lack of a good classification, six crossings are studied, three located in the rural area of Mexico and three in Mexico City. These cases show the need of: improving the current regulations, improving the existing infrastructure, and implementing technological systems, including informative signals with nomenclature of the involved crossing and direct telephone line for reporting emergencies. This implementation is unaffordable for most municipal governments. Also, an inventory of the most dangerous grade crossings in urban and rural areas must be obtained. Then, an approach for improving the classification of grade crossings is suggested. This approach must be based on criteria design, characteristics of adjacent roads or intersections which can influence traffic flow through the crossing, accidents related to motorized and non-motorized vehicles, land use and land management, type of area, and services and economic activities in the zone where the grade crossings is located. An expanded classification of grade crossing in Mexico could reduce accidents and improve the efficiency of the railroad.

Keywords: accidents, grade crossing, railroad, traffic safety

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Authors: Asif Hasan

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Among the reported suitable mariculture species in Bangladesh, seabass and mullet are the two most popular candidates due to their high market values. Several field studies conducted on the culture of seabass in Bangladesh, it still remains a challenge to commercially grow this species due to its exclusive carnivorous nature. In contrast, the grey mullet (M. cephalus) is a fast-growing, omnivorous euryhaline fish that has shown excellent growth in many areas including South Asia. Choice of a sustainable aquaculture technique must consider the productivity and yield as well as their environmental suitability. This study was designed to elucidate the ecologically suitable culture technique of M. cephalus in brakishwater ponds by comparing the biotic and abiotic components of pond ecosystem. In addition to growth parameters (yield, ADG, SGR, weight gain, FCR), Physicochemical parameters (Temperature, DO, pH, salinity, TDS, transparency, ammonia, and Chlorophyll-a concentration) and biological community composition (phytoplankton, zooplankton and benthic macroinvertebrates) were investigated from ponds under Semi-intensive, Improve extensive and Traditional culture system. While temperature were similar in the three culture types, ponds under improve-extensive showed better environmental conditions with significantly higher mean DO and transparency, and lower TDS and Chlorophyll-a. The abundance of zooplankton, phytoplankton and benthic macroinvertebrates were apparently higher in semi-intensive ponds. The Analysis of Similarity (ANOSIM) suggested moderate difference in the planktonic community composition. While the fish growth parameters of M. cephalus and total yield did not differ significantly between three systems, M. cephalus yield (kg/decimal) was apparently higher in semi-intensive pond due to high stocking density and intensive feeding. The results suggested that the difference between the three systems were due to more efficient utilization of nutrients in improve extensive ponds which affected fish growth through trophic cascades. This study suggested that different culture system of M. cephalus is an alternative and more beneficial method owing to its ecological and economic benefits in brackishwater ponds.

Keywords: Mugil cephalus, pond ecosystem, mariculture, fisheries management

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

Abstract:

Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

Procedia PDF Downloads 328

Authors: Mohammed Ahmed, Ziba Nazarlou

Abstract:

Mild steels have a limited alloying content which makes them vulnerable to excessive corrosion rates in the harsh medium. To overcome this issue, some protective coatings are used to prevent corrosion on the steel surface. The use of specialized coatings, mainly organic coatings (such as epoxies, polyurethanes, and acrylics) and inorganic coatings (such as Polysiloxanes) is the most common method of mitigating corrosion of carbon steel. Incorporating the benefits of organic and inorganic hybrid (OIH) compounds for the designing of hybrid protective coatings is still challenging for industrial applications. There are advantages of inorganic coatings have, but purely inorganic siloxane-based coatings are difficult to use on industrial applications unless they are used at extremely low thicknesses (< 1-2 microns). Hence, most industrial applications try to have a combination of Polysiloxanes with organic compounds.  A hybrid coating possesses an organic section, which transports flexibility and impact resistance, and an inorganic section, which usually helps in the decreasing of porosity and increasing thermal stability and hardness. A number of polymers including polyethylene glycol and polyvinyl pyrrolidone have been reported to inhibit the corrosion mild steel in acidic media. However, reports on the effect of polyethylene oxide (PEO) or its blends on corrosion inhibition of metals is very scarce. Different composition of OIH coatings was synthesized by using silica sol-gel, epoxy, and PEO. The effect of different coating types on the corrosion behavior of carbon steel in harsh solution has been studied by weight loss and electrochemical measurements using Gamry 1000 Interface Potentiostat. Coating structures were investigated by SEM. İt revealed a considerable reduction in corrosion rate for coated sample. Based on these results, OIH coating prepared by epoxy-silica sol gel-PEO and epoxy-silica sol-gel exhibit had a %99.5 and %98 reduction of (Corrosion rate) CR compares to baseline. Cathodic Tafel constant (βc) shows that coatings change both Tafel constants but had more effect on the cathodic process. The evolution of the Potentiostatic scan with time displays stability in potential, some of them in a high value while the other in a low value which can be attributed to the formation of an oxide film covering substrate surface. The coated samples with the group of epoxy coating have a lower potential along with the time test, while the silica group shows higher in potential with respect to time.

Keywords: electrostatic, hybrid coating, corrosion tests, silica sol gel

Procedia PDF Downloads 117

Authors: Debananda Mohapatra, Subramanya Badrayyana, Smrutiranjan Parida

Abstract:

Carbon nano-onions (CNOs) are the spherical graphitic nanostructures composed of concentric shells of graphitic carbon can be hypothesized as the intermediate state between fullerenes and graphite. These are very important members in fullerene family also known as the multi-shelled fullerenes can be envisioned as promising supercapacitor electrode with high energy & power density as they provide easy access to ions at electrode-electrolyte interface due to their curvature. There is still very sparse report concerning on CNOs as electrode despite having an excellent electrodechemical performance record due to their unavailability and lack of convenient methods for their high yield preparation and purification. Keeping all these current pressing issues in mind, we present a facile scalable and straightforward flame synthesis method of pure and highly dispersible CNOs without contaminated by any other forms of carbon; hence, a post processing purification procedure is not necessary. To the best of our knowledge, this is the very first time; we developed an extremely simple, light weight, novel inexpensive, flexible free standing pristine CNOs electrode without using any binder element. Locally available daily used cotton wipe has been used for fabrication of such an ideal electrode by ‘dipping and drying’ process providing outstanding stretchability and mechanical flexibility with strong adhesion between CNOs and porous wipe. The specific capacitance 102 F/g, energy density 3.5 Wh/kg and power density 1224 W/kg at 20 mV/s scan rate are the highest values that ever recorded and reported so far in symmetrical two electrode cell configuration with 1M Na2SO4 electrolyte; indicating a very good synthesis conditions employed with optimum pore size in agreement with electrolyte ion size. This free standing CNOs electrode also showed an excellent cyclic performance and stability retaining 95% original capacity after 5000 charge –discharge cycles. Furthermore, this unique method not only affords binder free - freestanding electrode but also provide a general way of fabricating such multifunctional promising CNOs based nanocomposites for their potential device applications in flexible solar cells and lithium-ion batteries.

Keywords: binder-free, flame synthesis, flexible, carbon nano onion

Procedia PDF Downloads 203