Search results for: Aspen HYSYS software

Authors: Richele P. Severino, Maria M. F. Alchaar, Lorena R. F. De Sousa, Patrik S. Vital, Ana G. Silva, Rosy I. M. A. Ribeiro

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Recognized as a global biodiversity hotspot, the Cerrado (Brazil) presents an extreme abundance of endemic species and it is considered to be one of the biologically richest tropical savanna regions in the world. Erythroxylum genus is found in Cerrado and chemically is characterized by the presence of tropane alkaloids, among them cocaine, a natural alkaloid produced by Erythroxylum coca Lam., which was used as a local anesthetic in small surgeries. However, cocaine gained notoriety due to its psychoactive activity in the Central Nervous System (CNS), becoming one of the major problems of public health today. Some species of Erythroxylum are referred to in the literature as having pharmacological potential, which provide alkaloids, terpenoids, and flavonoids. E. vacciniifolium Mart., commonly known as 'catuaba', is used as a central nervous system stimulant and has aphrodisiac properties and E. pelleterianum A. St.-Hil. in the treatment of stomach pains. Already E. myrsinites Mart. and E. suberosum A. St.-Hil. are used in the tannery industry. Species of Erythroxylum are also used in folk medicine for various diseases, against diabetes, antiviral, fungicidal, cytotoxicity, among others. The Cerrado is recognized as the richer savannah in the world in biodiversity but little explored from the chemical view. In our on-going study of the chemistry of Erythroxylum genus, we have investigated four specimens collected in central Cerrado of Brazil: E. campestre (EC), E. deciduum (ED), E. suberosum (ES) and E. tortuosum (ET). The cytotoxic activity of extracts was evaluated using HeLa cells, in vitro assays. The chemical investigation was performed preparing the extracts using n-hexane (H), dichloromethane (D), ethyl acetate (E) and methanol (M). The cells were treated with increasing concentrations of extracts (50, 75 and 100 μg/mL) diluted in DMSO (1%) and DMEM (0.5% FBS and 1% P/S). The IC₅₀ values were determined measured spectrophotometrically at 570 nm, after incubation of HeLa cell line for 48 hours using the MTT (SIGMA M5655), and calculated by nonlinear regression analysis using GraphPad Prism software. All the assays were done in triplicate and repeated at least two times. The cytotoxic assays showed some promising results with IC₅₀ values less than 100 μg/mL (ETD = 38.5 μg/mL; ETM = 92.3 μg/mL; ESM = 67.8 μg/mL; ECD = 24.0 μg/mL; ECM = 32.9; EDA = 44.2 μg/mL). The chemical profile study of ethyl acetate (E) and methanolic (M) extracts of E. tortuosum leaves was performed by LC-MS, and the structures of the compounds were determined by analysis of ¹H, HSQC and HMBC spectra, and confirmed by comparison with the literature data. The investigation led to six substances: α-amyrin, β-amyrin, campesterol, stigmastan-3,5-diene, β-sitosterol and 7,4’-di-O-methylquercetin-3-O-β-rutinoside, with flavonoid the major compound of extracts. By alkaline extraction of the methanolic extract, it was possible to identify three alkaloids: tropacocaine, cocaine and 6-methoxy-8-methyl-8-azabicyclo[3.2.1]octan-3-ol. The results obtained are important for the chemical knowledge of the Cerrado biodiversity and brought a contribution to the chemistry of Erythroxylum genus.

Keywords: cytotoxicity, Erythroxylum, chemical profile, secondary metabolites

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Authors: Kimberly M. Cacciato, Steven J. Singer, Allison R. Shapiro, Julianna F. Kamenakis

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This study examines the dynamics of communication among researchers and participants who have various levels of hearing, use multiple languages, have various disabilities, and who come from different social strata. This qualitative methodological study focuses on the strategies employed in an ethnographic research study examining the communication choices of six sets of parents who have Deaf-Disabled children. The participating families varied in their communication strategies and preferences including the use of American Sign Language (ASL), visual-gestural communication, multiple spoken languages, and pidgin forms of each of these. The research team consisted of two undergraduate students proficient in ASL and a Deaf principal investigator (PI) who uses ASL and speech as his main modes of communication. A third Hard-of-Hearing undergraduate student fluent in ASL served as an objective facilitator of the data analysis. The team created reflexive journals by audio recording, free writing, and responding to team-generated prompts. They discussed interactions between the members of the research team, their evolving relationships, and various social and linguistic power differentials. The researchers reflected on communication during data collection, their experiences with one another, and their experiences with the participating families. Reflexive journals totaled over 150 pages. The outside research assistant reviewed the journals and developed follow up open-ended questions and prods to further enrich the data. The PI and outside research assistant used NVivo qualitative research software to conduct open inductive coding of the data. They chunked the data individually into broad categories through multiple readings and recognized recurring concepts. They compared their categories, discussed them, and decided which they would develop. The researchers continued to read, reduce, and define the categories until they were able to develop themes from the data. The research team found that the various communication backgrounds and skills present greatly influenced the dynamics between the members of the research team and with the participants of the study. Specifically, the following themes emerged: (1) students as communication facilitators and interpreters as barriers to natural interaction, (2) varied language use simultaneously complicated and enriched data collection, and (3) ASL proficiency and professional position resulted in a social hierarchy among researchers and participants. In the discussion, the researchers reflected on their backgrounds and internal biases of analyzing the data found and how social norms or expectations affected the perceptions of the researchers in writing their journals. Through this study, the research team found that communication and language skills require significant consideration when working with multiple and complex communication modes. The researchers had to continually assess and adjust their data collection methods to meet the communication needs of the team members and participants. In doing so, the researchers aimed to create an accessible research setting that yielded rich data but learned that this often required compromises from one or more of the research constituents.

Keywords: American Sign Language, complex communication, deaf-disabled, methodology

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Areej Al-Khabbaz, Swapna Goerge, Majedah Abdul-Rasoul

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Introduction: The most prevalent periodontal disease among children is gingivitis, and it usually becomes more severe in adolescence. A number of intervention studies suggested that resolution of periodontal inflammation can improve metabolic control in patients diagnosed with diabetes mellitus. Aim: to assess the effect of non-surgical periodontal therapy on glycemic control of children diagnosed with diabetes mellitus. Method: Twenty-eight children diagnosed with diabetes mellitus were recruited with established diagnosis diabetes for at least 1 year. Informed consent and child assent form were obtained from children and parents prior to enrolment. The dental examination for the participants was performed on the same week directly following their annual medical assessment. All patients had their glycosylated hemoglobin (HbA1c%) test one week prior to their annual medical and dental visit and 3 months following non-surgical periodontal therapy. All patients received a comprehensive periodontal examination The periodontal assessment included clinical attachment loss, bleeding on probing, plaque score, plaque index and gingival index. All patients were referred for non-surgical periodontal therapy, which included oral hygiene instruction and motivation followed by supra-gingival and subg-ingival scaling using ultrasonic and hand instruments. Statistical Analysis: Data were entered and analyzed using the Statistical Package for Social Science software (SPSS, Chicago, USA), version 18. Statistical analysis of clinical findings was performed to detect differences between the two groups in term of periodontal findings and HbA1c%. Binary logistic regression analysis was performed in order to examine which factors were significant in multivariate analysis after adjusting for confounding between effects. The regression model used the dependent variable ‘Improved glycemic control’, and the independent variables entered in the model were plaque index, gingival index, bleeding %, plaque Statistical significance was set at p < 0.05. Result: A total of 28 children. The mean age of the participants was 13.3±1.92 years. The study participants were divided into two groups; Compliant group (received dental scaling) and non-complaints group (received oral hygiene instructions only). No statistical difference was found between compliant and non-compliant group in age, gender distribution, oral hygiene practice and the level of diabetes control. There was a significant difference between compliant and non-compliant group in term of improvement of HBa1c before and after periodontal therapy. Mean gingival index was the only significant variable associated with improved glycemic control level. In conclusion, this study has demonstrated that non-surgical mechanical periodontal therapy can improve HbA1c% control. The result of this study confirmed that children with diabetes mellitus who are compliant to dental care and have routine professional scaling may have better metabolic control compared to diabetic children who are erratic with dental care.

Keywords: children, diabetes, metabolic control, periodontal therapy

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Authors: Line Massé, Claire Baudry, Claudia Verret, Marie-France Nadeau, Anne Brault-Labbé

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Little research has been conducted on educational services adapted for twice exceptional students. Within an action research, a cluster grouping was set up in an elementary school in Quebec, bringing together gifted or doubly exceptional (2E) students (n = 11) and students not identified as gifted (n = 8) within a multilevel class (3ᵣ𝒹 and 4ₜₕ years). 2E students had either attention deficit hyperactivity disorder (n = 8, including 3 with specific learning disability) or autism spectrum disorder (n = 2). Differentiated instructions strategies were implemented, including the possibility of progressing at their own pace of learning, independent study or research projects, flexible accommodation, tutoring with older students and the development of socio-emotional learning. A specialized educator also supported the teacher in the class for behavioural and socio-affective aspects. Objectives: The study aimed to assess the impacts of the grouping on all students, their academic motivation, and their socio-emotional adaptation. Method: A mixed method was used, combining a qualitative approach with a quantitative approach. Semi-directed interviews were conducted with students (N = 18, 4 girls and 14 boys aged 8 to 9) and one of their parents (N = 18) at the end of the school year. Parents and students completed two questionnaires at the beginning and end of the school year: the Behavior Assessment System for Children-3, children or parents versions (BASC-3, Reynolds and Kampus, 2015) and the Academic Motivation in Education (Vallerand et al., 1993). Parents also completed the Multidimensional Student Life Satisfaction Scale (Huebner, 1994, adapted by Fenouillet et al., 2014) comprising three domains (school, friendships, and motivation). Mixed thematic analyzes were carried out on the data from the interviews using the N'Vivo software. Related-samples Wilcoxon rank-sums tests were conducted for the data from the questionnaires. Results: Different themes emerge from the students' comments, including a positive impact on school motivation or attitude toward school, improved school results, reduction of their behavioural difficulties and improvement of their social relations. These remarks were more frequent among 2E students. Most 2E students also noted an improvement in their academic performance. Most parents reported improvements in attitudes toward school and reductions in disruptive behaviours in the classroom. Some parents also observed changes in behaviours at home or in the socio-emotional well-being of their children, here again, particularly parents of 2E children. Analysis of questionnaires revealed significant differences at the end of the school year, more specifically pertaining to extrinsic motivation identified, problems of conduct, attention, emotional self-control, executive functioning, negative emotions, functional deficiencies, and satisfaction regarding friendships. These results indicate that this approach could benefit not only gifted and doubly exceptional students but also students not identified as gifted.

Keywords: Cluster grouping, elementary school, giftedness, mixed methods, twice exceptional students

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Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

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The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

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Authors: Maureen Kamau, Gulnaz Mohamoud, Adelaide Lusambili, Njeri Nyanja

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Life expectancy has increased over the last century amongst older individuals, and in particular, those 60 years and over. The World Health Organization estimates that the world's population of persons over 60 years will rise to 22 per cent by the year 2050. Ageing is associated with increasing disability, multiple chronic conditions, and an increase in the use of health services. These multiple chronic conditions are managed with polypharmacy. Polypharmacy has numerous adverse effects including non-adherence, poor compliance to the various medications, reduced appetite, and risk of fall. Studies on polypharmacy and ageing are few and poorly understood especially in low and middle - income countries. The aim of this study was to explore the knowledge, attitudes and beliefs of older people towards polypharmacy. A qualitative study of 15 patients aged 60 years and above, taking more than five medications per day were conducted at the Aga Khan University using Semi-structured in-depth interviews. Three interviews were pilot interviews, and data analysis was performed on 12 interviews. Data were analyzed using NVIVO 12 software. A thematic qualitative analysis was carried out guided by Braun and Clarke (2006) framework. Themes identified; - knowledge of their co-morbidities and of the medication that older persons take, sources of information about medicines, and storage of the medication, experiences and attitudes of older patients towards polypharmacy both positive and negative, older peoples beliefs and their coping mechanisms with polypharmacy. The study participants had good knowledge on their multiple co-morbidities, and on the medication they took. The patients had positive attitudes towards medication as it enhanced their health and well-being, and enabled them to perform their activities of daily living. There was a strong belief among older patients that the medications were necessary for their health. All these factors enhanced compliance to the multiple medication. However, some older patients had negative attitudes due to the pill burden, side effects of the medication, and stigma associated with being ill. Cost of healthcare was a concern, with most of the patients interviewed relying on insurance to cover the cost of their medication. Older patients had accepted that the medication they were prescribed were necessary for their health, as it enabled them to complete their activities of daily living. Some concerns about the side effects of the medication arose, and brought about the need for patient education that would ensure that the patients are aware of the medications they take, and potential side effects. The effect that the COVID 19 pandemic had in the healthcare of the older patients was evident by the number of the older patients avoided coming to the hospital during the period of the pandemic. The relationship with the primary care physician and the older patients is an important one, especially in LMICs such as Kenya, as many of the older patients trusted the doctors wholeheartedly to make the best decision about their health and about their medication. Prescription review is important to avoid the use of potentially inappropriate medication.

Keywords: polypharmacy, older patients, multiple chronic conditions, Kenya, Africa, qualitative study, indepth interviews, primary care

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Authors: Monisha Elumalai, Joana Guerreiro, Joana Carvalho, Marta Prado

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DNA biosensors popularity has been increasing over the past few years. Traditional analytical techniques tend to require complex steps and expensive equipment however DNA biosensors have the advantage of getting simple, fast and economic. Additionally, the combination of DNA biosensors with nanomaterials offers the opportunity to improve the selectivity, sensitivity and the overall performance of the devices. DNA biosensors are based on oligonucleotides as sensing elements. These oligonucleotides are highly specific to complementary DNA sequences resulting in the hybridization of the strands. DNA biosensors are not only an advantage in the clinical field but also applicable in numerous research areas such as food analysis or environmental control. Zebra Mussels (ZM), Dreissena polymorpha are invasive species responsible for enormous negative impacts on the environment and ecosystems. Generally, the detection of ZM is made when the observation of adult or macroscopic larvae's is made however at this stage is too late to avoid the harmful effects. Therefore, there is a need to develop an analytical tool for the early detection of ZM. Here, we present a portable plasmonic biosensor for the detection of environmental DNA (eDNA) released to the environment from this invasive species. The plasmonic DNA biosensor combines gold nanoparticles, as transducer elements, due to their great optical properties and high sensitivity. The detection strategy is based on the immobilization of a short base pair DNA sequence on the nanoparticles surface followed by specific hybridization in the presence of a complementary target DNA. The hybridization events are tracked by the optical response provided by the nanospheres and their surrounding environment. The identification of the DNA sequences (synthetic target and probes) to detect Zebra mussel were designed by using Geneious software in order to maximize the specificity. Moreover, to increase the optical response enzyme amplification of DNA might be used. The gold nanospheres were synthesized and characterized by UV-visible spectrophotometry and transmission electron microscopy (TEM). The obtained nanospheres present the maximum localized surface plasmon resonance (LSPR) peak position are found to be around 519 nm and a diameter of 17nm. The DNA probes modified with a sulfur group at one end of the sequence were then loaded on the gold nanospheres at different ionic strengths and DNA probe concentrations. The optimal DNA probe loading will be selected based on the stability of the optical signal followed by the hybridization study. Hybridization process leads to either nanoparticle dispersion or aggregation based on the presence or absence of the target DNA. Finally, this detection system will be integrated into an optical sensing platform. Considering that the developed device will be used in the field, it should fulfill the inexpensive and portability requirements. The sensing devices based on specific DNA detection holds great potential and can be exploited for sensing applications in-loco.

Keywords: ZM DNA, DNA probes, nicking enzyme, gold nanoparticles

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Authors: Hyppolite Aignon, Souleymane Yorou, Martin Ryberg, Anneli Svanholm

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Climate change and human actions cause the extinction of wild mushrooms. In Benin, the diversity of fungi is large and may still contain species new to science but the inventory effort remains low and focuses on particularly edible species (Russula, Lactarius, Lactifluus, and also Amanita). In addition, inventories have started recently and some groups of fungi are not sufficiently sampled, however, the degradation of fungal habitat continues to increase and some species are already disappearing. (Yorou and De Kesel, 2011), however, the degradation of fungi habitat continues to increase and some species may disappear without being known. This genus (Inocybe) overlooked has a worldwide distribution and includes more than 700 species with many undiscovered or poorly known species worldwide and particularly in tropical Africa. It is therefore important to orient the inventory to other genera or important families such as Inocybe (Fungi, Agaricales) in order to highlight their diversity and also to know their phylogenetic positions with a combined approach of gene regions. This study aims to evaluate the species richness and phylogenetic position of Inocybe species and affiliated taxa in West Africa. Thus, in North Benin, we visited the Forest Reserve of Ouémé Supérieur, the Okpara forest and the Alibori Supérieur Forest Reserve. In the center, we targeted the Forest Reserve of Toui-Kilibo. The surveys have been carried during the raining season in the study area meaning from June to October. A total of 24 taxa were collected, photographed and described. The DNA was extracted, the Polymerase Chain Reaction was carried out using primers (ITS1-F, ITS4-B) for Internal transcribed spacer (ITS), (LROR, LWRB, LR7, LR5) for nuclear ribosomal (LSU), (RPB2-f5F, RPB2-b6F, RPB2- b6R2, RPB2-b7R) for RNA polymerase II gene (RPB2) and sequenced. The ITS sequences of the 24 collections of Inocybaceae were edited in Staden and all the sequences were aligned and edited with Aliview v1.17. The sequences were examined by eye for sufficient similarity to be considered the same species. 13 different species were present in the collections. In addition, sequences similar to the ITS sequences of the thirteen final species were searched using BLAST. The nLSU and RPB2 markers for these species have been inserted in a complete alignment, where species from all major Inocybaceae clades as well as from all continents except Antarctica are present. Our new sequences for nLSU and RPB2 have been manually aligned in this dataset. Phylogenetic analysis was performed using the RAxML v7.2.6 maximum likelihood software. Bootstrap replications have been set to 100 and no partitioning of the dataset has been performed. The resulting tree was viewed and edited with FigTree v1.4.3. The preliminary tree resulting from the analysis of maximum likelihood shows us that these species coming from Benin are much diversified and are distributed in four different clades (Inosperma, Inocybe, Mallocybe and Pseudosperma) on the seven clades of Inocybaceae but the phylogeny position of 7 is currently known. This study marks the diversity of Inocybe in Benin and the investigations will continue and a protection plan will be developed in the coming years.

Keywords: Benin, diversity, Inocybe, phylogeny placement

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Authors: Shagufta Jabeen, Faez Jesse Firdaus Abdullah, Zunita Zakaria, Nurulfiza Mat Isa, Yung Chie Tan, Wai Yan Yee, Abdul Rahman Omar

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Pasteurella multocida is associated with acute, as well as, chronic infections in avian and bovine such as pasteurellosis and hemorrhagic septicemia (HS) in cattle and buffaloes. Iron is one of the most important nutrients for pathogenic bacteria including Pasteurella and acts as a cofactor or prosthetic group in several essential enzymes and is needed for amino acid, pyrimidine, and DNA biosynthesis. In our recent study, we showed that 2% of Pasteurella multocida serotype A strain PMTB2.1 encode for iron regulating genes (Accession number CP007205.1). Genome sequencing of other Pasteurella multocida serotypes namely PM70 and HB01 also indicated up to 2.5% of the respective genome encode for iron regulating genes, suggesting that Pasteurella multocida genome comprises of multiple systems for iron uptake. Since P. multocida PMTB2.1 has more than 40 CDs out of 2097 CDs (approximately 2%), encode for iron-regulated. The gene expression profiling of four iron-regulating genes namely fbpb, yfea, fece and fur were characterized under iron-restricted environment. The P. multocida strain PMTB2.1 was grown in broth with and without iron chelating agent and samples were collected at different time points. Relative mRNA expression profile of these genes was determined using Taqman probe based real-time PCR assay. The data analysis, normalization with two house-keeping genes and the quantification of fold changes were carried out using Bio-Rad CFX manager software version 3.1. Results of this study reflect that iron reduced environment has significant effect on expression profile of iron regulating genes (p < 0.05) when compared to control (normal broth) and all evaluated genes act differently with response to iron reduction in media. The highest relative fold change of fece gene was observed at early stage of treatment indicating that PMTB2.1 may utilize its periplasmic protein at early stage to acquire iron. Furthermore, down-regulation expression of fece with the elevated expression of other genes at later time points suggests that PMTB2.1 control their iron requirements in response to iron availability by down-regulating the expression of iron proteins. Moreover, significantly high relative fold change (p ≤ 0.05) of fbpb gene is probably associated with the ability of P. multocida to directly use host iron complex such as hem, hemoglobin. In addition, the significant increase (p ≤ 0.05) in fbpb and yfea expressions also reflects the utilization of multiple iron systems in P. multocida strain PMTB2.1. The findings of this study are very much important as relative scarcity of free iron within hosts creates a major barrier to microbial growth inside host and utilization of outer-membrane proteins system in iron acquisition probably occurred at early stage of infection with P. multocida. In conclusion, the presence and utilization of multiple iron system in P. multocida strain PMTB2.1 revealed the importance of iron in the survival of P. multocida.

Keywords: iron-related genes, real-time PCR, gene expression profiling, fold changes

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Authors: Shradha Parsekar, Suma Nair, Ajay Bailey, Binu V. S.

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Background: Concealing of cancer-related information is seen in many low-and-middle-income countries and may be associated with multiple factors. Comparatively, there is lack of information about, how breast cancers diagnosed women disclose cancer-related information to their social contacts and vice versa. To get more insights on the participant’s experience, opinions, expectations, and attitudes, a qualitative study is a suitable approach. Therefore, this study involving in-depth interviews was planned to lessen this gap. Methods: Interviews were conducted separately among breast cancer patients and their caregivers with semi-structured qualitative interview guide. Purposive and convenient sampling was being used to recruit patients and caregivers, respectively. Ethical clearance and permission from the tertiary hospital were obtained and participants were selected from the Udupi district, Karnataka, India. After obtaining a list of breast cancer diagnosed cases, participants were contacted in person and their willingness to take part in the study was taken. About 39 caregivers and 35 patients belonging to different breast cancer stages were recruited. Interviews were recorded with prior permission. Data was managed by Atlas.ti 8 software. The recordings were transcribed, translated and coded in two cycles. Most of the patients belonged to stage II and III cancer. Codes were grouped together into to whom breast cancer status was concealed to and underneath reason for the same. Main findings: followings are the codes and code families which emerged from the data. 1) Concealing the breast cancer status from social contacts other than close family members (such as extended family, neighbor and friends). Participants perceived the reasons as, a) to avoid questions which people probe (which doesn’t have answers), b) to avoid people paying courtesy visit (to inquire about the health as it is Indian culture to visit the sick person) making it inconvenient for patient and caregivers have to offer something and talk to them, c) to avoid people getting shocked (react as if cancer is different from other diseases) or getting emotional/sad, or getting fear of death d) to avoid getting negative suggestion or talking anything in front of patient as it may affect patient negatively, e) to avoid getting stigmatized, f) to avoid getting obstacle in child’s marriage. 2) Participant concealed the breast cancer status of young children as they perceived that it may a) affect studies, b) affect emotionally, c) children may get scared. 3) Concealing the breast cancer status from patients as the caregivers perceived that they have fear of a) worsening patient’s health, b) patient getting tensed, c) patient getting shocked, and d) patient getting scared. However, some participants stressed important in disclosing the cancer status to social contact/patient to make the people aware of the disease. Conclusion: The news of breast cancer spreads like electricity in the wire, therefore, patient or family avoid it for many reasons. Although, globally, due to physicians’ ethical obligations, there is an inclination towards more disclosure of cancer diagnosis and status of prognosis to the patient. However, it is an ongoing argument whether patient/social contacts should know the status especially in a country like India.

Keywords: breast cancer, concealing cancer status, India, qualitative study

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Authors: Manushi Srivastava

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Introduction: Doctor’s role, and relation with respect to patient care is at the core of medical ethics. The rapid pace of medical advances along with increasing consumer awareness about their rights and hike in cost of effective health care demand a robust, transparent and patient-friendly medical care system. However, doctors’ role performance is still in the frame of activity-passivity model of Doctor-Patient Relationship (DPR) where doctors act as parent and use to instruct their patients, without their consensus that is not going to help in the 21st century. Thus the current situation is a new challenge for traditional doctor-patient relationship after the introduction of Consumer Protection Act (CPA) in medical profession and the same is evidenced by increasing cases of medical litigation. To strengthen this system of medical services, the doctor plays a vital role, and the same should be reviewed in the present context. Objective: To understand the opinion of consultants regarding medical negligence and effect of Consumer Protection Act in terms of current practices of patient care. Method: This is a cross-sectional study in which both quantitative and qualitative methods are applied. Total 69 consultants were selected from multi-specialty hospitals of densely populated Varanasi city catering a population of about 1.8 million. Two-stage sampling was used for selection of respondents. At the first stage, selection of major wards (Medicine, Surgery, Ophthalmology, Gynaecology, Orthopaedics, and Paediatrics) was carried out, which are more susceptible to medical negligence. At the second stage, selection of consultants from the respective wards was carried out. In-depth Interviews were conducted with the help of semi-structured schedule. Two case studies of medical negligence were also carried out as part of the qualitative study. Analysis: Data were analyzed with the help of SPSS software (21.0 trial version). Semi-structured research tool was used to know consultant’s opinion about the pattern of medical negligence cases, litigations and claims made by patient community and inclusion of government medical services in CPA. Statistical analysis was done to describe data, and non-parametric test was used to observe the association between the variables. Analysis of Verbatim was used in case-study. Findings and Conclusion: Majority (92.8%) of consultants felt changes in the behaviour of community (patient) after implementation of CPA, as it had increased awareness about their rights. Less than half of the consultants opined that Medical Negligence is an Unintentional act of doctors and generally occurs due to communication gap and behavioural problem between doctor and patients. Experienced consultants ( > 10 years) pointed out that unethical practice by doctors and mal-intention of patient to harass doctors were additional reasons of Medical Negligence. In-depth interview revealed that now patients’ community expects more transparency and hence they demand cafeteria approach in diagnosis and management of cases. Thus as study results, we propose ‘Agreement Model’ of DPR to re-ensure ethical practice in medical profession.

Keywords: doctors, communication, consumer protection act (CPA), medical error

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Authors: Geremew Geidare Kailo, Igor Gáspár, András Koris, Ivana Pajčin, Flóra Vitális, Vanja Vlajkov

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Three-dimension (3D) printing, a very popular additive manufacturing technology, has recently undergone rapid growth and replaced the use of conventional technology from prototyping to producing end-user parts and products. The 3D Printing technology involves a digital manufacturing machine that produces three-dimensional objects according to designs created by the user via 3D modeling or computer-aided design/manufacturing (CAD/CAM) software. The most popular 3D printing system is Fused Deposition Modeling (FDM) or also called Fused Filament Fabrication (FFF). A 3D-printed object is considered food safe if it can have direct contact with the food without any toxic effects, even after cleaning, storing, and reusing the object. This work analyzes the processing timeline of the filament (material for 3D printing) from unboxing to the extrusion through the nozzle. It is an important task to analyze the growth of bacteria on the 3D printed surface and in gaps between the layers. By default, the 3D-printed object is not food safe after longer usage and direct contact with food (even though they use food-safe filaments), but there are solutions for this problem. The aim of this work was to evaluate the 3D-printed object from different perspectives of food safety. Firstly, testing antimicrobial 3D printing filaments from a food safety aspect since the 3D Printed object in the food industry may have direct contact with the food. Therefore, the main purpose of the work is to reduce the microbial load on the surface of a 3D-printed part. Coating with epoxy resin was investigated, too, to see its effect on mechanical strength, thermal resistance, surface smoothness and food safety (cleanability). Another aim of this study was to test new temperature-resistant filaments and the effect of high temperature on 3D printed materials to see if they can be cleaned with boiling or similar hi-temp treatment. This work proved that all three mentioned methods could improve the food safety of the 3D printed object, but the size of this effect variates. The best result we got was with coating with epoxy resin, and the object was cleanable like any other injection molded plastic object with a smooth surface. Very good results we got by boiling the objects, and it is good to see that nowadays, more and more special filaments have a food-safe certificate and can withstand boiling temperatures too. Using antibacterial filaments reduced bacterial colonies to 1/5, but the biggest advantage of this method is that it doesn’t require any post-processing. The object is ready out of the 3D printer. Acknowledgements: The research was supported by the Hungarian and Serbian bilateral scientific and technological cooperation project funded by the Hungarian National Office for Research, Development and Innovation (NKFI, 2019-2.1.11-TÉT-2020-00249) and the Ministry of Education, Science and Technological Development of the Republic of Serbia. The authors acknowledge the Hungarian University of Agriculture and Life Sciences’s Doctoral School of Food Science for the support in this study

Keywords: food safety, 3D printing, filaments, microbial, temperature

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Authors: A. Falenski, A. Kaesbohrer, M. Filter

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Introduction: Risk assessments can be performed in various ways and in different degrees of complexity. In order to assess risks associated with imported foods additional information needs to be taken into account compared to a risk assessment on regional products. The present review is an overview on currently available best practise approaches and data sources used for food import risk assessments (IRAs). Methods: A literature review has been performed. PubMed was searched for articles about food IRAs published in the years 2004 to 2014 (English and German texts only, search string “(English [la] OR German [la]) (2004:2014 [dp]) import [ti] risk”). Titles and abstracts were screened for import risks in the context of IRAs. The finally selected publications were analysed according to a predefined questionnaire extracting the following information: risk assessment guidelines followed, modelling methods used, data and software applied, existence of an analysis of uncertainty and variability. IRAs cited in these publications were also included in the analysis. Results: The PubMed search resulted in 49 publications, 17 of which contained information about import risks and risk assessments. Within these 19 cross references were identified to be of interest for the present study. These included original articles, reviews and guidelines. At least one of the guidelines of the World Organisation for Animal Health (OIE) and the Codex Alimentarius Commission were referenced in any of the IRAs, either for import of animals or for imports concerning foods, respectively. Interestingly, also a combination of both was used to assess the risk associated with the import of live animals serving as the source of food. Methods ranged from full quantitative IRAs using probabilistic models and dose-response models to qualitative IRA in which decision trees or severity tables were set up using parameter estimations based on expert opinions. Calculations were done using @Risk, R or Excel. Most heterogeneous was the type of data used, ranging from general information on imported goods (food, live animals) to pathogen prevalence in the country of origin. These data were either publicly available in databases or lists (e.g., OIE WAHID and Handystatus II, FAOSTAT, Eurostat, TRACES), accessible on a national level (e.g., herd information) or only open to a small group of people (flight passenger import data at national airport customs office). In the IRAs, an uncertainty analysis has been mentioned in some cases, but calculations have been performed only in a few cases. Conclusion: The current state-of-the-art in the assessment of risks of imported foods is characterized by a great heterogeneity in relation to general methodology and data used. Often information is gathered on a case-by-case basis and reformatted by hand in order to perform the IRA. This analysis therefore illustrates the need for a flexible, modular framework supporting the connection of existing data sources with data analysis and modelling tools. Such an infrastructure could pave the way to IRA workflows applicable ad-hoc, e.g. in case of a crisis situation.

Keywords: import risk assessment, review, tools, food import

Procedia PDF Downloads 302

Authors: Gachara Grace, Kebira Anthony, Harvey Jagger, Wainaina James

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Aflatoxin contamination of maize in Africa poses a major threat to food security and the health of many African people. In Kenya, aflatoxin contamination of maize is high due to the environmental, agricultural and socio-economic factors. Many studies have been conducted to understand the scope of the problem, especially at pre-harvest level. This research was carried out to gather scientific information on the fungi population, diversity and aflatoxin level during the post-harvest period. The study was conducted in three geographical locations of; Kitui, Kitale and Nakuru. Samples were collected from storage structures of farmers and transported to the Biosciences eastern and central Africa (BecA), International Livestock and Research Institute (ILRI) hub laboratories. Mycoflora was recovered using the direct plating method. A total of five fungal genera (Aspergillus, Penicillium, Fusarium, Rhizopus and Bssyochlamys spp.) were isolated from the stored maize samples. The most common fungal species that were isolated from the three study sites included A. flavus at 82.03% followed by A.niger and F.solani at 49% and 26% respectively. The aflatoxin producing fungi A. flavus was recovered in 82.03% of the samples. Aflatoxin levels were analysed on both the maize samples and in vitro. Most of the A. flavus isolates recorded a high level of aflatoxin when they were analysed for presence of aflatoxin B1 using ELISA. In Kitui, all the samples (100%) had aflatoxin levels above 10ppb with a total aflatoxin mean of 219.2ppb. In Kitale, only 3 samples (n=39) had their aflatoxin levels less than 10ppb while in Nakuru, the total aflatoxin mean level of this region was 239.7ppb. When individual samples were analysed using Vicam fluorometer method, aflatoxin analysis revealed that most of the samples (58.4%) had been contaminated. The means were significantly different (p=0.00<0.05) in all the three locations. Genetic relationships of A. flavus isolates were determined using 13 Simple Sequence Repeats (SSRs) markers. The results were used to generate a phylogenetic tree using DARwin5 software program. A total of 5 distinct clusters were revealed among the genotypes. The isolates appeared to cluster separately according to the geographical locations. Principal Coordinates Analysis (PCoA) of the genetic distances among the 91 A. flavus isolates explained over 50.3% of the total variation when two coordinates were used to cluster the isolates. Analysis of Molecular Variance (AMOVA) showed a high variation of 87% within populations and 13% among populations. This research has shown that A. flavus is the main fungal species infecting maize grains in Kenya. The influence of aflatoxins on human populations in Kenya demonstrates a clear need for tools to manage contamination of locally produced maize. Food basket surveys for aflatoxin contamination should be conducted on a regular basis. This would assist in obtaining reliable data on aflatoxin incidence in different food crops. This would go a long way in defining control strategies for this menace.

Keywords: aflatoxin, Aspergillus flavus, genotyping, Kenya

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Authors: Sinisa J. Vukicevic

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Edmonton is currently one of the youngest North American cities and has achieved significant growth over the past 40 years. Strong urban shift requires a new approach to how the city is envisioned, planned, and built. This approach is evidence-based scenario development, and an urban growth model was a key support tool in framing Edmonton development strategies, developing urban policies, and assessing policy implications. The urban growth model has been developed using the Metronamica software platform. The Metronamica land use model evaluated the dynamic of land use change under the influence of key development drivers (population and employment), zoning, land suitability, and land and activity accessibility. The model was designed following the Big City Moves ideas: become greener as we grow, develop a rebuildable city, ignite a community of communities, foster a healing city, and create a city of convergence. The Big City Moves were converted to three development scenarios: ‘Strong Central City’, ‘Node City’, and ‘Corridor City’. Each scenario has a narrative story that expressed scenario’s high level goal, scenario’s approach to residential and commercial activities, to transportation vision, and employment and environmental principles. Land use demand was calculated for each scenario according to specific density targets. Spatial policies were analyzed according to their level of importance within the policy set definition for the specific scenario, but also through the policy measures. The model was calibrated on the way to reproduce known historical land use pattern. For the calibration, we used 2006 and 2011 land use data. The validation is done independently, which means we used the data we did not use for the calibration. The model was validated with 2016 data. In general, the modeling process contain three main phases: ‘from qualitative storyline to quantitative modelling’, ‘model development and model run’, and ‘from quantitative modelling to qualitative storyline’. The model also incorporates five spatial indicators: distance from residential to work, distance from residential to recreation, distance to river valley, urban expansion and habitat fragmentation. The major finding of this research could be looked at from two perspectives: the planning perspective and technology perspective. The planning perspective evaluates the model as a tool for scenario development. Using the model, we explored the land use dynamic that is influenced by a different set of policies. The model enables a direct comparison between the three scenarios. We explored the similarities and differences of scenarios and their quantitative indicators: land use change, population change (and spatial allocation), job allocation, density (population, employment, and dwelling unit), habitat connectivity, proximity to objects of interest, etc. From the technology perspective, the model showed one very important characteristic: the model flexibility. The direction for policy testing changed many times during the consultation process and model flexibility in applying all these changes was highly appreciated. The model satisfied our needs as scenario development and evaluation tool, but also as a communication tool during the consultation process.

Keywords: urban growth model, scenario development, spatial indicators, Metronamica

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Authors: Maryam Ziaee

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This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

Procedia PDF Downloads 90

Authors: Martha E. Aguiar-Barrera, Humberto Gutierrez-Pulido, Veronica Vargas-Alejo

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Identifying and modeling random phenomena is a fundamental cognitive process to understand and transform reality. Recognizing situations governed by chance and giving them a scientific interpretation, without being carried away by beliefs or intuitions, is a basic training for citizens. Hence the importance of generating teaching-learning processes, supported using technology, paying attention to model creation rather than only executing mathematical calculations. In order to develop the student's knowledge about basic probability distributions and decision making; in this work a model eliciting activity (MEA) is reported. The intention was applying the Model and Modeling Perspective to design an activity related to civil engineering that would be understandable for students, while involving them in its solution. Furthermore, the activity should imply a decision-making challenge based on sample data, and the use of the computer should be considered. The activity was designed considering the six design principles for MEA proposed by Lesh and collaborators. These are model construction, reality, self-evaluation, model documentation, shareable and reusable, and prototype. The application and refinement of the activity was carried out during three school cycles in the Probability and Statistics class for Civil Engineering students at the University of Guadalajara. The analysis of the way in which the students sought to solve the activity was made using audio and video recordings, as well as with the individual and team reports of the students. The information obtained was categorized according to the activity phase (individual or team) and the category of analysis (sample, linearity, probability, distributions, mechanization, and decision-making). With the results obtained through the MEA, four obstacles have been identified to understand and apply the binomial distribution: the first one was the resistance of the student to move from the linear to the probabilistic model; the second one, the difficulty of visualizing (infering) the behavior of the population through the sample data; the third one, viewing the sample as an isolated event and not as part of a random process that must be viewed in the context of a probability distribution; and the fourth one, the difficulty of decision-making with the support of probabilistic calculations. These obstacles have also been identified in literature on the teaching of probability and statistics. Recognizing these concepts as obstacles to understanding probability distributions, and that these do not change after an intervention, allows for the modification of these interventions and the MEA. In such a way, the students may identify themselves the erroneous solutions when they carrying out the MEA. The MEA also showed to be democratic since several students who had little participation and low grades in the first units, improved their participation. Regarding the use of the computer, the RStudio software was useful in several tasks, for example in such as plotting the probability distributions and to exploring different sample sizes. In conclusion, with the models created to solve the MEA, the Civil Engineering students improved their probabilistic knowledge and understanding of fundamental concepts such as sample, population, and probability distribution.

Keywords: linear model, models and modeling, probability, randomness, sample

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Authors: Siphesihle Hlongwane

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Background: Globally, alcohol consumption, smoking, and the use of illicit drugs kill more than 11.8 million people each year. In sub-Saharan Africa, substance abuse is responsible for more than 6.4% of all deaths recorded and about 4.7% of all Disability Adjusted Life Years (DALYs), with numbers still expected to grow if no drastic measures are taken to curb and address drug use. In a setting where substance use is rife, understanding contextual factors that influence an individual’s perceived eligibility to seek rehabilitation is paramount. Using the candidacy framework, we unpack how situational factors influence an individual’s perceived eligibility for healthcare uptake in adolescents and youth with substance use disorder (SUD). Methods: The candidacy framework is concerned with how people consider their eligibility for accessing a health service. The study collected and analyzed primary qualitative data to answer the research question. Data were collected between January and July 2022 on participants aged between 18 and 35 for drug users and 18 to 60 for family members. Participants include 20 previous and current drug users and 20 family members that experience the effects of addiction. A pre-drafted semi-structured interview guide was administered to a conveniently sampled population supplemented with a referral sampling method. Data were thematically analyzed using the NVivo 12pro software to manage the data. Findings: Our findings show that people with substance use disorders are aware of their drug use habits and acknowledge their candidacy for health services. Candidacy for health services is also acknowledged by those around them, such as family members and peers, and as such, information on the navigation of health services for drug users is shared by those who have attended health services, those affected by drug use, and this includes health service research by family members to identify accessible health services. While participants reported willingness to quit drug use if assistance is provided, the permeability of health care services is hindered by both individual determinations to quit drug use from long-time use and the availability of health services for drug users, such as rehabilitation centers. Our findings also show that drug users are conscious and can articulate their ailments; however, the hunt for the next dose of drugs and long waiting cues for health service acquisition overshadows their claim to health services. Participants reported a mixture of treatments prescribed, with some more gruesome than others prescribed, thus serving as both a facilitator and barrier for health service uptake. Despite some unorthodox forms of treatments prescribed in health care, the majority of those who enter treatment complete the process of treatment, although some are met with setbacks and sometimes relapse after treatment has finished. Conclusion: Drug users are able to ascertain their candidacy for health services; however, individual and environmental characteristics relating to drug use hinder the use of health services. Drug use interventions need to entice health service uptake as a way to improve candidacy for health use.

Keywords: substance use disorder, rehabilitation, drug use, relapse, South Africa, candidacy framework

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Authors: Asegid Belay Kebede, Getachew Biru Worku

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The Earth and its inhabitants have faced an existential threat as a result of severe manmade actions. Global warming and climate change have been the most apparent manifestations of this threat throughout the world, with increasingly intense heat waves, temperature rises, flooding, sea-level rise, ice sheet melting, and so on. One of the major contributors to this disaster is the ever-increasing production and consumption of energy, which is still primarily fossil-based and emits billions of tons of hazardous GHG. The transportation industry is recognized as the biggest actor in terms of emissions, accounting for 24% of direct CO2 emissions and being one of the few worldwide sectors where CO2 emissions are still growing. Rail transportation, which includes all from light rail transit to high-speed rail services, is regarded as one of the most efficient modes of transportation, accounting for 9% of total passenger travel and 7% of total freight transit. Nonetheless, there is still room for improvement in the transportation sector, which might be done by incorporating alternative and/or renewable energy sources. As a result of these rapidly changing global energy situations and rapidly dwindling fossil fuel supplies, we were driven to analyze the possibility of renewable energy sources for traction applications. Even a small achievement in energy conservation or harnessing might significantly influence the total railway system and have the potential to transform the railway sector like never before. As a result, the paper begins by assessing the potential for photovoltaic (PV) power generation on train rooftops and existing infrastructure such as railway depots, passenger stations, traction substation rooftops, and accessible land along rail lines. As a result, a method based on a Google Earth system (using Helioscopes software) is developed to assess the PV potential along rail lines and on train station roofs. As an example, the Addis Ababa light rail transit system (AA-LRTS) is utilized. The case study examines the electricity-generating potential and economic performance of photovoltaics installed on AALRTS. As a consequence, the overall capacity of solar systems on all stations, including train rooftops, reaches 72.6 MWh per day, with an annual power output of 10.6 GWh. Throughout a 25-year lifespan, the overall CO2 emission reduction and total profit from PV-AA-LRTS can reach 180,000 tons and 892 million Ethiopian birrs, respectively. The PV-AA-LRTS has a 200% return on investment. All PV stations have a payback time of less than 13 years, and the price of solar-generated power is less than $0.08/kWh, which can compete with the benchmark price of coal-fired electricity. Our findings indicate that PV-AA-LRTS has tremendous potential, with both energy and economic advantages.

Keywords: sustainable development, global warming, energy crisis, photovoltaic energy conversion, techno-economic analysis, transportation system, light rail transit

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Authors: Gulhan Sen

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Disasters could result in many deaths and injuries. In these difficult times, accessible resources are limited, demand and supply balance is distorted, and there is a need to make urgent interventions. Disproportionateness between accessible resources and intervention capacity makes triage a necessity in every stage of disaster response. Healthcare professionals, who are in charge of triage, have to evaluate swiftly and make ethical decisions about which patients need priority and urgent intervention given the limited available resources. For such critical times in disaster triage, 'doing the greatest good for the greatest number of casualties' is adopted as a code of practice. But there is no guide for healthcare professionals about ethical decision-making during disasters, and this study is expected to use as a source in the preparation of the guide. This study aimed to examine whether the qualities healthcare professionals in Izmir related to disaster triage were adequate and whether these qualities influence their capacity to make ethical decisions. The researcher used a survey developed for data collection. The survey included two parts. In part one, 14 questions solicited information about socio-demographic characteristics and knowledge levels of the respondents on ethical principles of disaster triage and allocation of scarce resources. Part two included four disaster scenarios adopted from existing literature and respondents were asked to make ethical decisions in triage based on the provided scenarios. The survey was completed by 215 healthcare professional working in Emergency-Medical Stations, National Medical Rescue Teams and Search-Rescue-Health Teams in Izmir. The data was analyzed with SPSS software. Chi-Square Test, Mann-Whitney U Test, Kruskal-Wallis Test and Linear Regression Analysis were utilized. According to results, it was determined that 51.2% of the participants had inadequate knowledge level of ethical principles of disaster triage and allocation of scarce resources. It was also found that participants did not tend to make ethical decisions on four disaster scenarios which included ethical dilemmas. They stayed in ethical dilemmas that perform cardio-pulmonary resuscitation, manage limited resources and make decisions to die. Results also showed that participants who had more experience in disaster triage teams, were more likely to make ethical decisions on disaster triage than those with little or no experience in disaster triage teams(p < 0.01). Moreover, as their knowledge level of ethical principles of disaster triage and allocation of scarce resources increased, their tendency to make ethical decisions also increased(p < 0.001). In conclusion, having inadequate knowledge level of ethical principles and being inexperienced affect their ethical decision-making during disasters. So results of this study suggest that more training on disaster triage should be provided on the areas of the pre-impact phase of disaster. In addition, ethical dimension of disaster triage should be included in the syllabi of the ethics classes in the vocational training for healthcare professionals. Drill, simulations, and board exercises can be used to improve ethical decision making abilities of healthcare professionals. Disaster scenarios where ethical dilemmas are faced should be prepared for such applied training programs.

Keywords: disaster triage, medical ethics, ethical principles of disaster triage, ethical decision-making

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Authors: Arturo Galvan, Jatziri Y. Moreno-Martinez, Daniel Arroyo-Montoya, Jose M. Gutierrez-Villalobos

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Bridges are one of the most seismically vulnerable structures on highway transportation systems. The general process for assessing the seismic vulnerability of a bridge involves the evaluation of its overall capacity and demand. One of the most common procedures to obtain this capacity is by means of pushover analysis of the structure. Typically, the bridge capacity is assessed using non-linear static methods or non-linear dynamic analyses. The non-linear dynamic approaches use step by step numerical solutions for assessing the capacity with the consuming computer time inconvenience. In this study, a nonlinear static analysis (‘pushover analysis’) was performed to predict the collapse mechanism of a typical bridge built in the central zone of Mexico (Celaya, Guanajuato). The bridge superstructure consists of three simple supported spans with a total length of 76 m: 22 m of the length of extreme spans and 32 m of length of the central span. The deck width is of 14 m and the concrete slab depth is of 18 cm. The bridge is built by means of frames of five piers with hollow box-shaped sections. The dimensions of these piers are 7.05 m height and 1.20 m diameter. The numerical model was created using a commercial software considering linear and non-linear elements. In all cases, the piers were represented by frame type elements with geometrical properties obtained from the structural project and construction drawings of the bridge. The deck was modeled with a mesh of rectangular thin shell (plate bending and stretching) finite elements. The moment-curvature analysis was performed for the sections of the piers of the bridge considering in each pier the effect of confined concrete and its reinforcing steel. In this way, plastic hinges were defined on the base of the piers to carry out the pushover analysis. In addition, time history analyses were performed using 19 accelerograms of real earthquakes that have been registered in Guanajuato. In this way, the displacements produced by the bridge were determined. Finally, pushover analysis was applied through the control of displacements in the piers to obtain the overall capacity of the bridge before the failure occurs. It was concluded that the lateral deformation of the piers due to a critical earthquake occurred in this zone is almost imperceptible due to the geometry and reinforcement demanded by the current design standards and compared to its displacement capacity, they were excessive. According to the analysis, it was found that the frames built with five piers increase the rigidity in the transverse direction of the bridge. Hence it is proposed to reduce these frames of five piers to three piers, maintaining the same geometrical characteristics and the same reinforcement in each pier. Also, the mechanical properties of materials (concrete and reinforcing steel) were maintained. Once a pushover analysis was performed considering this configuration, it was concluded that the bridge would continue having a “correct” seismic behavior, at least for the 19 accelerograms considered in this study. In this way, costs in material, construction, time and labor would be reduced in this study case.

Keywords: collapse mechanism, moment-curvature analysis, overall capacity, push-over analysis

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Authors: Raja Umer Sajjad, Chang Hee Lee

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Stormwater runoff is the leading contributor to pollution of receiving waters. In response, an efficient stormwater monitoring program is required to quantify and eventually reduce stormwater pollution. The overall goals of stormwater monitoring programs primarily include the identification of high-risk dischargers and the development of total maximum daily loads (TMDLs). The challenge in developing better monitoring program is to reduce the variability in flux estimates due to sampling errors; however, the success of monitoring program mainly depends on the accuracy of the estimates. Apart from sampling errors, manpower and budgetary constraints also influence the quality of the estimates. This study attempted to develop optimum stormwater monitoring design considering both cost and the quality of the estimated pollutants flux. Three years stormwater monitoring data (2012 – 2014) from a mix land use located within Geumhak watershed South Korea was evaluated. The regional climate is humid and precipitation is usually well distributed through the year. The investigation of a large number of water quality parameters is time-consuming and resource intensive. In order to identify a suite of easy-to-measure parameters to act as a surrogate, Principal Component Analysis (PCA) was applied. Means, standard deviations, coefficient of variation (CV) and other simple statistics were performed using multivariate statistical analysis software SPSS 22.0. The implication of sampling time on monitoring results, number of samples required during the storm event and impact of seasonal first flush were also identified. Based on the observations derived from the PCA biplot and the correlation matrix, total suspended solids (TSS) was identified as a potential surrogate for turbidity, total phosphorus and for heavy metals like lead, chromium, and copper whereas, Chemical Oxygen Demand (COD) was identified as surrogate for organic matter. The CV among different monitored water quality parameters were found higher (ranged from 3.8 to 15.5). It suggests that use of grab sampling design to estimate the mass emission rates in the study area can lead to errors due to large variability. TSS discharge load calculation error was found only 2 % with two different sample size approaches; i.e. 17 samples per storm event and equally distributed 6 samples per storm event. Both seasonal first flush and event first flush phenomena for most water quality parameters were observed in the study area. Samples taken at the initial stage of storm event generally overestimate the mass emissions; however, it was found that collecting a grab sample after initial hour of storm event more closely approximates the mean concentration of the event. It was concluded that site and regional climate specific interventions can be made to optimize the stormwater monitoring program in order to make it more effective and economical.

Keywords: first flush, pollutant load, stormwater monitoring, surrogate parameters

Procedia PDF Downloads 240

Authors: Antero J. S. Kivinen, Suvi-Sadetta Kaarakainen

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Digitalization touches every aspect of contemporary society, changing the way we live our everyday life. Contemporary society is sometimes described as knowledge society including unprecedented amount of information people face daily. The tools to manage this information flow are ICT-skills which are both technical skills and reflective skills needed to manage incoming information. Therefore schools are under constant pressure of revision. In the latest Programme for International Student Assessment (PISA) girls have been outperforming boys in all Organization for Economic Co-operation and Development (OECD) member countries and the gender gap between girls and boys is widest in Finland. This paper presents results of the Comprehensive Schools in the Digital Age project of RUSE, University of Turku. The project is in connection with Finnish Government Analysis, Assessment and Research Activities. First of all, this paper examines gender differences in ICT-skills of Finnish upper comprehensive school students. Secondly, it explores in which way differences are changing when students proceed to upper secondary and vocational education. ICT skills are measured using a performance-based ICT-skill test. Data is collected in 3 phases, January-March 2017 (upper comprehensive schools, n=5455), September-December 2017 (upper secondary and vocational schools, n~3500) and January-March 2018 (Upper comprehensive schools). The age of upper comprehensive school student’s is 15-16 and upper secondary and vocational school 16-18. The test is divided into 6 categories: basic operations, productivity software, social networking and communication, content creation and publishing, applications and requirements for the ICT study programs. Students have filled a survey about their ICT-usage and study materials they use in school and home. Cronbach's alpha was used to estimate the reliability of the ICT skill test. Statistical differences between genders were examined using two-tailed independent samples t-test. Results of first data from upper comprehensive schools show that there is no statistically significant difference in ICT-skill tests total scores between genders (boys 10.24 and girls 10.64, maximum being 36). Although, there were no gender difference in total test scores, there are differences in above mentioned six categories. Girls get better scores on school related and social networking test subjects while boys perform better on more technical oriented subjects. Test scores on basic operations are quite low for both groups. Perhaps these can partly be explained by the fact that the test was made on computers and majority of students ICT-usage consist of smartphones and tablets. Against this background it is important to analyze further the reasons for these differences. In a context of ongoing digitalization of everyday life and especially working life, the significant purpose of this analyses is to find answers how to guarantee the adequate ICT skills for all students.

Keywords: basic education, digitalization, gender differences, ICT-skills, upper comprehensive education, upper secondary education, vocational education

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Authors: Maximilian Engelhardt, Stephan Seeck

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The COVID-19 pandemic is accelerating the already growing field of e-commerce. The resulting urban freight transport volume leads to traffic and negative environmental impact. Furthermore, the service level of parcel logistics service provider is lacking far behind the expectations of consumer. These challenges can be solved by radically reorganize the urban last mile distribution structure: parcels could be consolidated in a micro hub within the inner city and delivered within time windows by cargo bike. This approach leads to a significant improvement of consumer satisfaction with their overall delivery experience. However, this approach also leads to significantly increased costs per parcel. While there is a relevant share of online shoppers that are willing to pay for such a delivery service there are no deeper insights about this target group available in the literature. Being aware of the importance of knowing target groups for businesses, the aim of this paper is to elaborate the most important factors that determine the willingness to pay for sustainable and service-oriented parcel delivery (factor analysis) and to derive customer segments (cluster analysis). In order to answer those questions, a data set is analyzed using quantitative methods of multivariate statistics. The data set was generated via an online survey in September and October 2020 within the five largest cities in Germany (n = 1.071). The data set contains socio-demographic, living-related and value-related variables, e.g. age, income, city, living situation and willingness to pay. In a prior work of the author, the data was analyzed applying descriptive and inference statistical methods that only provided limited insights regarding the above-mentioned research questions. The analysis in an exploratory way using factor and cluster analysis promise deeper insights of relevant influencing factors and segments for user behavior of the mentioned parcel delivery concept. The analysis model is built and implemented with help of the statistical software language R. The data analysis is currently performed and will be completed in December 2021. It is expected that the results will show the most relevant factors that are determining user behavior of sustainable and service-oriented parcel deliveries (e.g. age, current service experience, willingness to pay) and give deeper insights in characteristics that describe the segments that are more or less willing to pay for a better parcel delivery service. Based on the expected results, relevant implications and conclusions can be derived for startups that are about to change the way parcels are delivered: more customer-orientated by time window-delivery and parcel consolidation, more environmental-friendly by cargo bike. The results will give detailed insights regarding their target groups of parcel recipients. Further research can be conducted by exploring alternative revenue models (beyond the parcel recipient) that could compensate the additional costs, e.g. online-shops that increase their service-level or municipalities that reduce traffic on their streets.

Keywords: customer segmentation, e-commerce, last mile delivery, parcel service, urban logistics, willingness-to-pay

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Authors: Ife Elegbeleye, Nnditshedzeni Eric, Regina Maphanga, Femi Elegbeleye, Femi Agunbiade

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The global potential of other renewable energy sources such as wind, hydroelectric, bio-mass, and geothermal is estimated to be approximately 13 %, with hydroelectricity constituting a larger percentage. Sunlight provides by far the largest of all carbon-neutral energy sources. More energy from the sunlight strikes the Earth in one hour (4.3 × 1020 J) than all the energy consumed on the planet in a year (4.1 × 1020 J), hence, solar energy remains the most abundant clean, renewable energy resources for mankind. Photovoltaic (PV) devices such as silicon solar cells, dye sensitized solar cells are utilized for harnessing solar energy. Polyene-diphenylaniline organic molecules are important sets of molecules that has stirred many research interest as photosensitizers in TiO₂ semiconductor-based dye sensitized solar cells (DSSCs). The advantages of organic dye molecule over metal-based complexes are higher extinction coefficient, moderate cost, good environmental compatibility, and electrochemical properties. The polyene-diphenylaniline organic dyes with basic configuration of donor-π-acceptor are affordable, easy to synthesize and possess chemical structures that can easily be modified to optimize their photocatalytic and spectral properties. The enormous interest in polyene-diphenylaniline dyes as photosensitizers is due to their fascinating spectral properties which include visible light to near infra-red-light absorption. In this work, density functional theory approach via GPAW software, Avogadro and ASE were employed to study the effect of methoxy functionalized group on the spectral properties of polyene-diphenylaniline dyes and their photons absorbing characteristics in the visible region to near infrared region of the solar spectrum. Our results showed that the two-phenyl based complexes D5 and D7 exhibits maximum absorption peaks at 750 nm and 850 nm, while D9 and D11 with methoxy group shows maximum absorption peak at 800 nm and 900 nm respectively. The highest absorption wavelength is notable for D9 and D11 containing additional polyene and methoxy groups. Also, D9 and D11 chromophores with the methoxy group shows lower energy gap of 0.98 and 0.85 respectively than the corresponding D5 and D7 dyes complexes with energy gap of 1.32 and 1.08. The analysis of their electron injection kinetics ∆Ginject into the band gap of TiO₂ shows that D9 and D11 with the methoxy group has higher electron injection kinetics of -2.070 and -2.030 than the corresponding polyene-diphenylaniline complexes without the addition of polyene group with ∆Ginject values of -2.820 and -2.130 respectively. Our findings suggest that the addition of functionalized group as an extension of the organic complexes results in higher light harvesting efficiencies and bathochromic shift of the absorption spectra to higher wavelength which suggest higher current densities and open circuit voltage in DSSCs. The study suggests that the photocatalytic properties of organic chromophores/complexes with donor-π-acceptor configuration can be enhanced by the addition of functionalized groups.

Keywords: renewable energy resource, solar energy, dye sensitized solar cells, polyene-diphenylaniline organic chromophores

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Authors: Monika Soni, Shovonlal Bhowmick, Chandra Bhattacharya, Jitendra Sharma, Prafulla Dutta, Jagadish Mahanta

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Aedes aegypti and Aedes albopictus are considered as two major vectors to transmit dengue virus. In North-east India, two states viz. Assam and Arunachal Pradesh are known to be high endemic zone for dengue and Chikungunya viral infection. The taxonomical classification of medically important vectors are important for mapping of actual evolutionary trends and epidemiological studies. However, misidentification of mosquito species in field-collected mosquito specimens could have a negative impact which may affect vector-borne disease control policy. DNA barcoding is a prominent method to record available species, differentiate from new addition and change of population structure. In this study, a combined approach of a morphological and molecular technique of DNA barcoding was adopted to explore sequence variation in mitochondrial cytochrome c oxidase subunit I (COI) gene within dengue vectors. The study has revealed the map distribution of the dengue vector from two states i.e. Assam and Arunachal Pradesh, India. Approximate five hundred mosquito specimens were collected from different parts of two states, and their morphological features were compared with the taxonomic keys. The analysis of detailed taxonomic study revealed identification of two species Aedes aegypti and Aedes albopictus. The species aegypti comprised of 66.6% of the specimen and represented as dominant dengue vector species. The sequences obtained through standard DNA barcoding protocol were compared with public databases, viz. GenBank and BOLD. The sequences of all Aedes albopictus have shown 100% similarity whereas sequence of Aedes aegypti has shown 99.77 - 100% similarity of COI gene with that of different geographically located same species based on BOLD database search. From dengue prevalent different geographical regions fifty-nine sequences were retrieved from NCBI and BOLD databases of the same and related taxa to determine the evolutionary distance model based on the phylogenetic analysis. Neighbor-Joining (NJ) and Maximum Likelihood (ML) phylogenetic tree was constructed in MEGA6.06 software with 1000 bootstrap replicates using Kimura-2-Parameter model. Data were analyzed for sequence divergence and found that intraspecific divergence ranged from 0.0 to 2.0% and interspecific divergence ranged from 11.0 to 12.0%. The transitional and transversional substitutions were tested individually. The sequences were deposited in NCBI: GenBank database. This observation claimed the first DNA barcoding analysis of Aedes mosquitoes from North-eastern states in India and also confirmed the range expansion of two important mosquito species. Overall, this study insight into the molecular ecology of the dengue vectors from North-eastern India which will enhance the understanding to improve the existing entomological surveillance and vector incrimination program.

Keywords: COI, dengue vectors, DNA barcoding, molecular identification, North-east India, phylogenetics

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Authors: Andrew N. Saylor, James R. Peters

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Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

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Authors: Bhupendra G. Prajapati, Alpesh R. Patel

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The aim of this research work is to develop sustained release multi-particulates dosage form of Dexketoprofen trometamol, which is the pharmacologically active isomer of ketoprofen. The objective is to utilization of active enantiomer with minimal dose and administration frequency, extended release multi-particulates dosage form development for better patience compliance was explored. Drug loaded and sustained release coated pellets were prepared by fluidized bed coating principle by wurster coater. Microcrystalline cellulose as core pellets, povidone as binder and talc as anti-tacking agents were selected during drug loading while Kollicoat SR 30D as sustained release polymer, triethyl citrate as plasticizer and micronized talc as an anti-adherent were used in sustained release coating. Binder optimization trial in drug loading showed that there was increase in process efficiency with increase in the binder concentration. 5 and 7.5%w/w concentration of Povidone K30 with respect to drug amount gave more than 90% process efficiency while higher amount of rejects (agglomerates) were observed for drug layering trial batch taken with 7.5% binder. So for drug loading, optimum Povidone concentration was selected as 5% of drug substance quantity since this trial had good process feasibility and good adhesion of the drug onto the MCC pellets. 2% w/w concentration of talc with respect to total drug layering solid mass shows better anti-tacking property to remove unnecessary static charge as well as agglomeration generation during spraying process. Optimized drug loaded pellets were coated for sustained release coating from 16 to 28% w/w coating to get desired drug release profile and results suggested that 22% w/w coating weight gain is necessary to get the required drug release profile. Three critical process parameters of Wurster coating for sustained release were further statistically optimized for desired quality target product profile attributes like agglomerates formation, process efficiency, and drug release profile using central composite design (CCD) by Minitab software. Results show that derived design space consisting 1.0 to 1.2 bar atomization air pressure, 7.8 to 10.0 gm/min spray rate and 29-34°C product bed temperature gave pre-defined drug product quality attributes. Scanning Image microscopy study results were also dictate that optimized batch pellets had very narrow particle size distribution and smooth surface which were ideal properties for reproducible drug release profile. The study also focused on optimized dexketoprofen trometamol pellets formulation retain its quality attributes while administering with common vehicle, a liquid (water) or semisolid food (apple sauce). Conclusion: Sustained release multi-particulates were successfully developed for dexketoprofen trometamol which may be useful to improve acceptability and palatability of a dosage form for better patient compliance.

Keywords: dexketoprofen trometamol, pellets, fluid bed technology, central composite design

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Authors: Same Noel Ngando, Yakub Abdulfatai Olatunji

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Renewable energy micro-grids, such as those powered by solar or wind energy, are often intermittent in nature. This means that the amount of energy generated by these systems can vary depending on weather conditions or other factors, which can make it difficult to ensure a steady supply of power. To address this issue, energy storage systems have been developed to increase the reliability of renewable energy micro-grids. Battery systems have been the dominant energy storage technology for renewable energy micro-grids. Batteries can store large amounts of energy in a relatively small and compact package, making them easy to install and maintain in a micro-grid setting. Additionally, batteries can be quickly charged and discharged, allowing them to respond quickly to changes in energy demand. However, the process involved in recycling batteries is quite costly and difficult. An alternative energy storage system that is gaining popularity is hydrogen storage. Hydrogen is a versatile energy carrier that can be produced from renewable energy sources such as solar or wind. It can be stored in large quantities at low cost, making it suitable for long-distance mass storage. Unlike batteries, hydrogen does not degrade over time, so it can be stored for extended periods without the need for frequent maintenance or replacement, allowing it to be used as a backup power source when the micro-grid is not generating enough energy to meet demand. When hydrogen is needed, it can be converted back into electricity through a fuel cell. Energy consumption data is got from a particular residential area in Daegu, South Korea, and the data is processed and analyzed. From the analysis, the total energy demand is calculated, and different hybrid energy system configurations are designed using HOMER Pro (Hybrid Optimization for Multiple Energy Resources) and MATLAB software. A techno-economic and environmental comparison and life cycle assessment (LCA) of the different configurations using battery and hydrogen as storage systems are carried out. The various scenarios included PV-hydrogen-grid system, PV-hydrogen-grid-wind, PV-hydrogen-grid-biomass, PV-hydrogen-wind, PV-hydrogen-biomass, biomass-hydrogen, wind-hydrogen, PV-battery-grid-wind, PV- battery -grid-biomass, PV- battery -wind, PV- battery -biomass, and biomass- battery. From the analysis, the least cost system for the location was the PV-hydrogen-grid system, with a net present cost of about USD 9,529,161. Even though all scenarios were environmentally friendly, taking into account the recycling cost and pollution involved in battery systems, all systems with hydrogen as a storage system produced better results. In conclusion, hydrogen is becoming a very prominent energy storage solution for renewable energy micro-grids. It is easier to store compared with electric power, so it is suitable for long-distance mass storage. Hydrogen storage systems have several advantages over battery systems, including flexibility, long-term stability, and low environmental impact. The cost of hydrogen storage is still relatively high, but it is expected to decrease as more hydrogen production, and storage infrastructure is built. With the growing focus on renewable energy and the need to reduce greenhouse gas emissions, hydrogen is expected to play an increasingly important role in the energy storage landscape.

Keywords: renewable energy systems, microgrid, hydrogen production, energy storage systems

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