Search results for: software transactional memory

Authors: Abdul Qadir Jangda, Khadija Mariam, Usman Ahmed, Sharib Ahmed

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The Gafchromic EBT3 film has the characteristic of high spatial resolution, weak energy dependence and near tissue equivalence which makes them viable to be used for in-vivo dosimetry in External Beam and Brachytherapy applications. The aim of this study is to assess the smallest film dimension that may be feasible for the use in in-vivo dosimetry. To evaluate the viability, the film sizes from 3 x 3 mm to 20 x 20 mm were calibrated with 6 MV Photon and 6 MeV electron beams. The Gafchromic EBT3 (Lot no. A05151201, Make: ISP) film was cut into five different sizes in order to establish the relationship between absorbed dose vs. film dimensions. The film dimension were 3 x 3, 5 x 5, 10 x 10, 15 x 15, and 20 x 20 mm. The films were irradiated on Varian Clinac® 2100C linear accelerator for dose range from 0 to 1000 cGy using PTW solid water phantom. The irradiation was performed as per clinical absolute dose rate calibratin setup, i.e. 100 cm SAD, 5.0 cm depth and field size of 10x10 cm2 and 100 cm SSD, 1.4 cm depth and 15x15 cm2 applicator for photon and electron respectively. The irradiated films were scanned with the landscape orientation and a post development time of 48 hours (minimum). Film scanning accomplished using Epson Expression 10000 XL Flatbed Scanner and quantitative analysis carried out with ImageJ freeware software. Results show that the dose variation with different film dimension ranging from 3 x 3 mm to 20 x 20 mm is very minimal with a maximum standard deviation of 0.0058 in Optical Density for a dose level of 3000 cGy and the the standard deviation increases with the increase in dose level. So the precaution must be taken while using the small dimension films for higher doses. Analysis shows that there is insignificant variation in the absorbed dose with a change in film dimension of EBT3 film. Study concludes that the film dimension upto 3 x 3 mm can safely be used up to a dose level of 3000 cGy without the need of recalibration for particular dimension in use for dosimetric application. However, for higher dose levels, one may need to calibrate the films for a particular dimension in use for higher accuracy. It was also noticed that the crystalline structure of the film got damage at the edges while cutting the film, which can contribute to the wrong dose if the region of interest includes the damage area of the film

Keywords: external beam radiotherapy, film calibration, film dosimetery, in-vivo dosimetery

Procedia PDF Downloads 494

Authors: V. E. Messerle, A. L. Mosse, O. A. Lavrichshev, A. N. Nikonchuk, A. B. Ustimenko

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One of the most serious environmental problems today is pollution by biomedical waste (BMW), which in most cases has undesirable properties such as toxicity, carcinogenicity, mutagenicity, fire. Sanitary and hygienic survey of typical solid BMW, made in Belarus, Kazakhstan, Russia and other countries shows that their risk to the environment is significantly higher than that of most chemical wastes. Utilization of toxic BMW requires use of the most universal methods to ensure disinfection and disposal of any of their components. Such technology is a plasma technology of BMW processing. To implement this technology a thermodynamic analysis of the plasma processing of BMW was fulfilled and plasma-box furnace was developed. The studies have been conducted on the example of the processing of bone. To perform thermodynamic calculations software package Terra was used. Calculations were carried out in the temperature range 300 - 3000 K and a pressure of 0.1 MPa. It is shown that the final products do not contain toxic substances. From the organic mass of BMW synthesis gas containing combustible components 77.4-84.6% was basically produced, and mineral part consists mainly of calcium oxide and contains no carbon. Degree of gasification of carbon reaches 100% by the temperature 1250 K. Specific power consumption for BMW processing increases with the temperature throughout its range and reaches 1 kWh/kg. To realize plasma processing of BMW experimental installation with DC plasma torch of 30 kW power was developed. The experiments allowed verifying the thermodynamic calculations. Wastes are packed in boxes weighing 5-7 kg. They are placed in the box furnace. Under the influence of air plasma flame average temperature in the box reaches 1800 OC, the organic part of the waste is gasified and inorganic part of the waste is melted. The resulting synthesis gas is continuously withdrawn from the unit through the cooling and cleaning system. Molten mineral part of the waste is removed from the furnace after it has been stopped. Experimental studies allowed determining operating modes of the plasma box furnace, the exhaust gases was analyzed, samples of condensed products were assembled and their chemical composition was determined. Gas at the outlet of the plasma box furnace has the following composition (vol.%): CO - 63.4, H2 - 6.2, N2 - 29.6, S - 0.8. The total concentration of synthesis gas (CO + H2) is 69.6%, which agrees well with the thermodynamic calculation. Experiments confirmed absence of the toxic substances in the final products.

Keywords: biomedical waste, box furnace, plasma torch, processing, synthesis gas

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Authors: Sara Segura, Diego Nuñez, Miryam Villamil

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In this work, we studied the microscale interaction of foreign substances with blood inside an artificial transparent artery system that represents medium and small muscular arteries. This artery system had channels ranging from 75 μm to 930 μm and was fabricated using glass and transparent polymer blends like Phenylbis(2,4,6-trimethylbenzoyl) phosphine oxide, Poly(ethylene glycol) and PDMS in order to be monitored in real time. The setup was performed using a computer controlled precision micropump and a high resolution optical microscope capable of tracking fluids at fast capture. Observation and analysis were performed using a real time software that reconstructs the fluid dynamics determining the flux velocity, injection dependency, turbulence and rheology. All experiments were carried out with fully computer controlled equipment. Interactions between substances like water, serum (0.9% sodium chloride and electrolyte with a ratio of 4 ppm) and blood cells were studied at microscale as high as 400nm of resolution and the analysis was performed using a frame-by-frame observation and HD-video capture. These observations lead us to understand the fluid and mixing behavior of the interest substance in the blood stream and to shed a light on the use of implantable devices for drug delivery at arteries with different Endothelial dysfunction. Several substances were tested using the artificial artery system. Initially, Milli-Q water was used as a control substance for the study of the basic fluid dynamics of the artificial artery system. However, serum and other low viscous substances were pumped into the system with the presence of other liquids to study the mixing profiles and behaviors. Finally, mammal blood was used for the final test while serum was injected. Different flow conditions, pumping rates, and time rates were evaluated for the determination of the optimal mixing conditions. Our results suggested the use of a very fine controlled microinjection for better mixing profiles with and approximately rate of 135.000 μm3/s for the administration of drugs inside arteries.

Keywords: artificial artery, drug delivery, microfluidics dynamics, arteriosclerosis

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Authors: V. Jaime Contreras, S. Iliana Nunez, S. Mario Sanchez

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Inside a manufacturing facility, we can find innumerable automatic and manual operations, all of which are relevant to the production process. Some of these processes add more value to the products more than others. Manual operations tend to add value to the product since they can be found in the final assembly area o final operations of the process. In this areas, where a mistake or accident can increase the cost of waste exponentially. To reduce or mitigate these costly mistakes, one approach is to rely on automation to eliminate the operator from the production line - requires a hefty investment and development of specialized machinery. In our approach, the center of the solution is the operator through sufficient and adequate instrumentation, real-time reporting and ergonomics. Efficiency and reduced cycle time can be achieved thorough the integration of Internet-of-Things (IoT) ready technologies into assembly operations to enhance the ergonomics of the workstations. Augmented reality visual aids, RFID triggered personalized workstation dimensions and real-time data transfer and reporting can help achieve these goals. In this case study, a standard work cell will be used for real-life data acquisition and a simulation software to extend the data points beyond the test cycle. Three comparison scenarios will run in the work cell. Each scenario will introduce a dimension of the ergonomics to measure its impact independently. Furthermore, the separate test will determine the limitations of the technology and provide a reference for operating costs and investment required. With the ability, to monitor costs, productivity, cycle time and scrap/waste in real-time the ROI (return on investment) can be determined at the different levels to integration. This case study will help to show that ergonomics in the assembly lines can make significant impact when IoT technologies are introduced. Ergonomics can effectively reduce waste and increase productivity with minimal investment if compared with setting up to custom machine.

Keywords: augmented reality visual aids, ergonomics, real-time data acquisition and reporting, RFID triggered workstation dimensions

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Authors: Fikremariam Beyene, Getachew Bekele

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Ethiopia is currently on the move with various projects to raise the amount of power generated in the country. The progress observed in recent years indicates this fact clearly and indisputably. The rural electrification program, the modernization of the power transmission system, the development of wind farm is some of the main accomplishments worth mentioning. As it is well known, currently, wind power is globally embraced as one of the most important sources of energy mainly for its environmentally friendly characteristics, and also that once it is installed, it is a source available free of charge. However, integration of wind power plant with an existing network has many challenges that need to be given serious attention. In Ethiopia, a number of wind farms are either installed or are under construction. A series of wind farm is planned to be installed in the near future. Ashegoda Wind farm (13.2°, 39.6°), which is the subject of this study, is the first large scale wind farm under construction with the capacity of 120 MW. The first phase of 120 MW (30 MW) has been completed and is expected to be connected to the grid soon. This paper is concerned with the investigation of the wind farm interaction with the national grid under transient operating condition. The main concern is the fault ride through (FRT) capability of the system when the grid voltage drops to exceedingly low values because of short circuit fault and also the active and reactive power behavior of wind turbines after the fault is cleared. On the wind turbine side, a detailed dynamic modelling of variable speed wind turbine of a 1 MW capacity running with a squirrel cage induction generator and full-scale power electronics converters is done and analyzed using simulation software DIgSILENT PowerFactory. On the Ethiopian electric power corporation side, after having collected sufficient data for the analysis, the grid network is modeled. In the model, a fault ride-through (FRT) capability of the plant is studied by applying 3-phase short circuit on the grid terminal near the wind farm. The results show that the Ashegoda wind farm can ride from voltage deep within a short time and the active and reactive power performance of the wind farm is also promising.

Keywords: squirrel cage induction generator, active and reactive power, DIgSILENT PowerFactory, fault ride-through capability, 3-phase short circuit

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Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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Authors: Emre Bayamlıoğlu

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This paper aims to provide an account of the legal and the regulative aspects of the algorithmic reputation systems with a special emphasis on the sharing economy (i.e., Uber, Airbnb, Lyft) business model. The first section starts with an analysis of the legal and commercial nature of the tripartite relationship among the parties, namely, the host platform, individual sharers/service providers and the consumers/users. The section further examines to what extent an algorithmic system of reputational information could serve as an alternative to legal regulation. Shortcomings are explained and analyzed with specific examples from Airbnb Platform which is a pioneering success in the sharing economy. The following section focuses on the issue of governance and control of the reputational information. The section first analyzes the legal consequences of algorithmic filtering systems to detect undesired comments and how a delicate balance could be struck between the competing interests such as freedom of speech, privacy and the integrity of the commercial reputation. The third section deals with the problem of manipulation by users. Indeed many sharing economy businesses employ certain techniques of data mining and natural language processing to verify consistency of the feedback. Software agents referred as "bots" are employed by the users to "produce" fake reputation values. Such automated techniques are deceptive with significant negative effects for undermining the trust upon which the reputational system is built. The third section is devoted to explore the concerns with regard to data mobility, data ownership, and the privacy. Reputational information provided by the consumers in the form of textual comment may be regarded as a writing which is eligible to copyright protection. Algorithmic reputational systems also contain personal data pertaining both the individual entrepreneurs and the consumers. The final section starts with an overview of the notion of reputation as a communitarian and collective form of referential trust and further provides an evaluation of the above legal arguments from the perspective of public interest in the integrity of reputational information. The paper concludes with certain guidelines and design principles for algorithmic reputation systems, to address the above raised legal implications.

Keywords: sharing economy, design principles of algorithmic regulation, reputational systems, personal data protection, privacy

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Authors: Abigail Kusi Amponsah, Evans Frimpong Kyei, John Bright Agyemang, Hanson Boakye, Joana Kyei-Dompim, Collins Kwadwo Ahoto, Evans Oduro

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Staff shortages, deficient knowledge, inappropriate attitudes, demanding workloads, analgesic shortages, and low prioritization of pain management have been identified in earlier studies as the nursing-related barriers to optimal children’s pain management. These studies have mainly been undertaken in developed countries, which have different healthcare dynamics than those in developing countries. The current study, therefore, sought to identify and understand the nursing-related barriers to children’s pain management in the Ghanaian context. A descriptive qualitative study was conducted among 28 purposively sampled nurses working in the pediatric units of five hospitals in the Ashanti region of Ghana. Over the course of three months, participants were interviewed on the barriers which prevented them from optimally managing children’s pain in practice. Recorded interviews were transcribed verbatim and deductively analysed based on a conceptual interest in pain assessment and management-related barriers. NVivo 12 plus software guided data management and analyses. The mean age of participating nurses was 30 years, with majority being females (n =24). Participants had worked in the nursing profession for an average of five years and in the pediatric care settings for an average of two years. The nursing-related barriers identified in the present study included communication difficulties in assessing and evaluating pain management interventions with children who have nonfunctional speech, insufficient training, misconceptions on the experience of pain in children, lack of assessment tools, and insufficient number of nurses to manage the workload and nurses’ inability to prescribe analgesics. The present study revealed some barriers which prevented Ghanaian nurses from optimally managing children’s pain. Nurses should be educated, empowered, and supported with the requisite material resources to effectively manage children’s pain and improve outcomes for families, healthcare systems, and the nation. Future studies should explore the facilitators and barriers from other stakeholders involved in pediatric pain management

Keywords: Nursing-Related Barriers, Children, Pain Management, Ghana

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Authors: Lukasz Grabowski, Konrad Pietrykowski, Michal Bialy

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This paper presents the results of the research to verify the combustion in aircraft piston engine Asz62-IR. This engine was modernized and a type of ignition system was developed. Due to the high costs of experiments of a nine-cylinder 1,000 hp aircraft engine, a simulation technique should be applied. Therefore, computational fluid dynamics to simulate the combustion process is a reasonable solution. Accordingly, the tests for varied ignition advance angles were carried out and the optimal value to be tested on a real engine was specified. The CFD model was created with the AVL Fire software. The engine in the research had two spark plugs for each cylinder and ignition advance angles had to be set up separately for each spark. The results of the simulation were verified by comparing the pressure in the cylinder. The courses of the indicated pressure of the engine mounted on a test stand were compared. The real course of pressure was measured with an optical sensor, mounted in a specially drilled hole between the valves. It was the OPTRAND pressure sensor, which was designed especially to engine combustion process research. The indicated pressure was measured in cylinder no 3. The engine was running at take-off power. The engine was loaded by a propeller at a special test bench. The verification of the CFD simulation results was based on the results of the test bench studies. The course of the simulated pressure obtained is within the measurement error of the optical sensor. This error is 1% and reflects the hysteresis and nonlinearity of the sensor. The real indicated pressure measured in the cylinder and the pressure taken from the simulation were compared. It can be claimed that the verification of CFD simulations based on the pressure is a success. The next step was to research on the impact of changing the ignition advance timing of spark plugs 1 and 2 on a combustion process. Moving ignition timing between 1 and 2 spark plug results in a longer and uneven firing of a mixture. The most optimal point in terms of indicated power occurs when ignition is simultaneous for both spark plugs, but so severely separated ignitions are assured that ignition will occur at all speeds and loads of engine. It should be confirmed by a bench experiment of the engine. However, this simulation research enabled us to determine the optimal ignition advance angle to be implemented into the ignition control system. This knowledge allows us to set up the ignition point with two spark plugs to achieve as large power as possible.

Keywords: CFD model, combustion, engine, simulation

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Authors: Ji Young Lee, Jong Woon Kim

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It is essential to secure high availability of railway vehicles to realize high quality and efficiency of railway service. Once the availability decreased, planned railway service could not be provided or more cars need to be reserved. additional cars need to be purchased or the frequency of railway service could be decreased. Such situation would be a big loss in terms of quality and cost related to railway service. Therefore, we make various efforts to get high availability of railway vehicles. Because it is a big loss to operators, we make various efforts to get high availability of railway vehicles. To secure high availability, the idle time of the vehicle needs to be reduced and the following methods are applied to railway vehicles. First, through modularization design, exchange time for line replaceable units is reduced which makes railway vehicles could be put into the service quickly. Second, to reduce periodic preventive maintenance time, preventive maintenance with short period would be proceeded test oriented to minimize the maintenance time, and reliability is secured through overhauls for each main component. With such design changes for railway vehicles, modularized components are exchanged first at the time of vehicle failure or overhaul so that vehicles could be put into the service quickly and exchanged components are repaired or overhauled. Therefore, spare components are required for any future failures or overhauls. And, as components are modularized and costs for components are high, it is considerably important to get reasonable quantities of spare components. Especially, when a number of railway vehicles were put into the service simultaneously, the time of overhauls come almost at the same time. Thus, for some vehicles, components need to be exchanged and overhauled before appointed overhaul period so that these components could be secured as spare parts for the next vehicle’s component overhaul. For this reason, components overhaul time and spare parts quantities should be decided at the same time. This study deals with the time of overhauls for repairable components of railway vehicles and the calculation of spare parts quantities in consideration of future failure/overhauls. However, as railway vehicles are used according to the service schedule, maintenance work cannot be proceeded after the service was closed thus it is quite difficult to resolve this situation mathematically. In this study, Simulation software system is used in this study for analyzing the time of overhauls for repairable components of railway vehicles and the spare parts for the railway systems.

Keywords: overhaul time, rolling stocks, simulation, spare parts

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Authors: Obuzor Eze Obuzor, Ekpoke Okurube Sliver

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The study was carried out at Debee farms at Ahoada West Local Government area, Rivers State, Nigeria. To evaluate the impact of two different cost-effective available feed composition on growth performance of weaned piglets. Thirty weaned uncontrolled cross bred (Large white x pietrain) piglets of average initial weight of 3.04 Kg weaned at 30days were assigned to three dietary treatments, comprising three replicates of 10 weaned piglets each, piglets were kept at 7 °C in different pens with dimensions of 4.50 × 4.50 m. The design of the experiment was completely randomized design, data from the study were subjected to one-way analysis of variance (ANOVA) and significant means were separated using Duncan's Multiple Range Test using Statistical Analysis System (SAS) software for windows (2 0 0 3), statistical significance was assessed at P < 0.05 (95% confidence interval) while survival rate was calculated using simple percentage. A standard diet was prepared to meet the nutrient requirements of weaned piglets at (20.8% crude protein). The three diets were fed to the animals in concrete feeding trough, control diet (C) had soybean meal while first treatment had spent grain (T1) and the second treatment had wheat offal (T2) respectively. The experiment was partitioned into four weeks periods (days 1-7, 8-14, 15-21 and 22-28). Feed and water were given unrestrictedly throughout the period of the experiment. The feed intake and weights of the pigs were recorded on weekly basis. Feed conversion ratio and daily weight gain were calculated and the study lasted for four weeks. There was no significant (P>0.05) effect of diet on survival rate, final body weight, average daily weight gain, daily feed intake and feed conversion ratio. The overall performance showed that treatment one (T1) had survival rate (93%), improved daily weight gain (36.21 g), average daily feed intake (120.14 g) and had the best feed conversion ratio (0.29) similar high mean value with the control while treatment two (T2) had lowest and negative response to all parameters. It could be concluded that feed formulated with spent grain is cheaper than control (soybean meal) and also improved the growth performance of weaned piglets.

Keywords: piglets, weaning, feed conversions ratio, daily weight gain

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Authors: Oscar Orlando Ortiz Rodriguez, Raquel A. Villamizar-G, Alexander Araque

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There is a total of 1027 municipal development plants in Colombia, 70% of municipalities had Potable Water Treatment Plants (PWTPs) in urban areas and 20% in rural areas. These PWTPs are typically supplied by surface waters (mainly rivers) and resort to gravity, pumping and/or mixed systems to get the water from the catchment point, where the first stage of the potable water process takes place. Subsequently, a series of conventional methods are applied, consisting in a more or less standardized sequence of physicochemical and, sometimes, biological treatment processes which vary depending on the quality of the water that enters the plant. These processes require energy and chemical supplies in order to guarantee an adequate product for human consumption. Therefore, in this paper, we applied the environmental methodology of Life Cycle Assessment (LCA) to evaluate the environmental loads of a potable water treatment plant (PWTP) located in northeastern Colombia following international guidelines of ISO 14040. The different stages of the potable water process, from the catchment point through pumping to the distribution network, were thoroughly assessed. The functional unit was defined as 1 m³ of water treated. The data were analyzed through the database Ecoinvent v.3.01, and modeled and processed in the software LCA-Data Manager. The results allowed determining that in the plant, the largest impact was caused by Clarifloc (82%), followed by Chlorine gas (13%) and power consumption (4%). In this context, the company involved in the sustainability of the potable water service should ideally reduce these environmental loads during the potable water process. A strategy could be the use of Clarifloc can be reduced by applying coadjuvants or other coagulant agents. Also, the preservation of the hydric source that supplies the treatment plant constitutes an important factor, since its deterioration confers unfavorable features to the water that is to be treated. By concluding, treatment processes and techniques, bioclimatic conditions and culturally driven consumption behavior vary from region to region. Furthermore, changes in treatment processes and techniques are likely to affect the environment during all stages of a plant’s operation cycle.

Keywords: climate change, environmental impact, life cycle assessment, treated water

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Authors: Jonathan Ogwal, Louis H. Kamulegeya, John M. Bwanika, Davis Musinguzi

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Introduction: Community retail Pharmacy drug distribution points (CRPDDP) were implemented in the Lango sub-region as part of the Ministry of Health’s response to improving access and adherence to antiretroviral treatment (ART). Clients received their ART refills from nearby local pharmacies; as such, the need for continuous engagement through mobile phone appointment reminders and health messages. We share learnings from the implementation of mobile text reminders and voice call follow-ups among ART clients attending the CRPDDP program in northern Uganda. Methods: A retrospective data review of electronic medical records from four pharmacies allocated for CRPDDP in the Lira and Apac districts of the Lango sub-region in Northern Uganda was done from February to August 2022. The process involved collecting phone contacts of eligible clients from the health facility appointment register and uploading them onto a messaging platform customized by Rapid-pro, an open-source software. Client information, including code name, phone number, next appointment date, and the allocated pharmacy for ART refill, was collected and kept confidential. Contacts received appointment reminder messages and other messages on positive living as an ART client. Routine voice call follow-ups were done to ascertain the picking of ART from the refill pharmacy. Findings: In total, 1,354 clients were reached from the four allocated pharmacies found in urban centers. 972 clients received short message service (SMS) appointment reminders, and 382 were followed up through voice calls. The majority (75%) of the clients returned for refills on the appointed date, 20% returned within four days after the appointment date, and the remaining 5% needed follow-up where they reported that they were not in the district by the appointment date due to other engagements. Conclusion: The use of mobile text reminders and voice call follow-ups improves the attendance of community retail pharmacy refills.

Keywords: antiretroviral treatment, community retail drug distribution points, mobile text reminders, voice call follow-up

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Authors: Barbara Rebecca Mutonyi, Chukwuemeka Echebiri, Terje Slåtten, Gudbrand Lien

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The concept of affective commitment to change has been scarcely explored among employees in the higher education literature. The present study addresses this knowledge gap in the literature by examining how various psychological factors, such as psychological empowerment (PsyEmp), and psychological capital (PsyCap), promotes affective commitment to change. As affective commitment to change has been identified by previous studies as an important aspect to implementation behavior, the study examines the correlation of affective commitment to change on employee innovative behavior (EIB) in higher education. The study proposes mediation relationship between PsyEmp, PsyCap, and affective commitment to change. 250 employees in higher education in Norway were sampled for this study. The study employed online survey for data collection, utilizing Stata software to perform Partial least square equation modeling to test the proposed hypotheses of the study. Through bootstrapping, the study was able to test for mediating effects. Findings of the study shows a strong direct relationship between the leadership factor PsyEmp on the individual factor PsyCap ( = 0.453). In addition, the findings of the study reveal that both PsyEmp and PsyCap are related to affective commitment to change ( = 0.28 and  = 0.249, respectively). In total, PsyEmp and PsyCap explains about 10% of the variance in the concept of affective commitment to change. Further, the direct effect of effective commitment to change and EIB is also supported ( = 0.183). The three factors, PsyEmp, PsyCap, and affective commitment to change, explains nearly 40% (R2 = 0.39) of the variance found in EIB. The relationship between PsyEmp, PsyCap, and affective commitment to change are mediated through the individual factor PsyCap. In order to effectively promote affective commitment to change among higher education employees, higher education managers should focus on both the leadership factor, PsyEmp, as well as the individual factor, PsyCap, of their employees. In this regard, higher education managers should strengthen employees EIB through providing autonomy, creating a safe environment that encourages innovation thinking and action, and providing employees in higher education opportunities to be involved in changes occurring at work. This contributes to strengthening employees´ affective commitment to change, that further improves their EIB in their work roles as higher education employees. As such, the results of this study implicate the ambidextrous nature of the concepts of affective commitment to change and EIB that should be considered in future studies of innovation in higher education research.

Keywords: affective commitment to change, psychological capital, innovative behavior, psychological empowerment, higher education

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Anita Bela, Marta Juhasz

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Adapting to the always-changing environment comes with complex determinants. The authors are zooming into one aspect only when the current workforce comes with obstacles by being less keen to stay engaged, even short or mid-term, resulting in additional challenges impacting the business performance. Seeing these occurring in practice made the researchers eager to gain a better understanding of the reasons behind. The paper aims to provide an overview of the theoretical background and research methods planned for the different stages of the research. The theoretical part takes the leadership behaviors under lens while the focus is on finding ways to attract and retain those who prefer working under more flexible employment conditions (e.g. contractor, contingent worker, etc.). These are considered as the organizational values and along with the power of people management are having their engaging relevance. The organizational culture (visible or invisible level) is clearly the mirror of the set of shared values guiding all members of the companies towards acceptable behavior. The applied research method, inductive reasoning was selected since the focus and questions raised in this research are results of specific observations made on the employees (various employment types) and leaders of start-ups and corporates. By comparing the similarities and differences, the researchers are hoping to prove the readiness and agility of the start-up culture for the desired leadership behaviours of the current and future workforce against the corporate culture. While exploring the preferences and engaging factors of the 21st-century workforce the data gathering would happen through website analysis – using ATLAS.ti qualitative software – followed by interview sessions where demographics will be collected and preferred leadership behaviors - using the Critical Incident Technique. Moreover, a short engagement survey will be administered to understand the linkage between the organizational culture type and engagement level. To conclude, after gaining theoretical understanding, we will zoom back to the employees to reveal the behaviors to be followed to achieve engagement in an environment where nothing is stable and where the companies always must keep their agile eyes and reactions vivid.

Keywords: leadership behaviours, organizational culture, qualitative analysis, workforce engagement

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Authors: Janet Modu, Jean-Francois Georgin, Laurent Briancon, Eric Antoinet

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The current practice during the repowering phase of wind turbines is deconstruction of existing foundations and construction of new foundations to accept larger wind loads or once the foundations have reached the end of their service lives. The ongoing research project FUI25 FEDRE (Fondations d’Eoliennes Durables et REpowering) therefore serves to propose scalable wind turbine foundation designs to allow reuse of the existing foundations. To undertake this research, numerical models and laboratory-scale models are currently being utilized and implemented in the GEOMAS laboratory at INSA Lyon following instrumentation of a reference wind turbine situated in the Northern part of France. Sensors placed within both the foundation and the underlying soil monitor the evolution of stresses from the foundation’s early age to stresses during service. The results from the instrumentation form the basis of validation for both the laboratory and numerical works conducted throughout the project duration. The study currently focuses on the effect of coupled mechanisms (Thermal-Hydro-Mechanical-Chemical) that induce stress during the early age of the reinforced concrete foundation, and scale factor considerations in the replication of the reference wind turbine foundation at laboratory-scale. Using THMC 3D models on COMSOL Multi-physics software, the numerical analysis performed on both the laboratory-scale and the full-scale foundations simulate the thermal deformation, hydration, shrinkage (desiccation and autogenous) and creep so as to predict the initial damage caused by internal processes during concrete setting and hardening. Results show a prominent effect of early age properties on the damage potential in full-scale wind turbine foundations. However, a prediction of the damage potential at laboratory scale shows significant differences in early age stresses in comparison to the full-scale model depending on the spatial position in the foundation. In addition to the well-known size effect phenomenon, these differences may contribute to inaccuracies encountered when predicting ultimate deformations of the on-site foundation using laboratory scale models.

Keywords: cement hydration, early age behavior, reinforced concrete, shrinkage, THMC 3D models, wind turbines

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Authors: Shveta Bathla, Preeti Rawat, Sudarshan Kumar, Rubina Baithalu, Jogender Singh Rana, Tushar Kumar Mohanty, Ashok Kumar Mohanty

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Pregnancy is a complex process which includes series of events such as fertilization, formation of blastocyst, implantation of embryo, placental formation and development of fetus. The success of these events depends on various interactions which are synchronized by endocrine interaction between a receptive dam and competent embryo. These interactions lead to change in expression of hormones and proteins. But till date no protein biomarker is available which can be used to detect successful completion of these events. We employed quantitative proteomics approach to develop putative serological biomarker which has diagnostic applicability for early detection of pregnancy in cows. For this study, sera were collected from control (non-pregnant, n=6) and pregnant animals on successive days of pregnancy (7, 19, 45, n=6). The sera were subjected to depletion for removal of albumin using Norgen depletion kit. The tryptic peptides were labeled with iTRAQ. The peptides were pooled and fractionated using bRPLC over 80 min gradient. Then 12 fractions were injected to nLC for identification and quantitation in DDA mode using ESI. Identification using Mascot search revealed 2056 proteins out of which 352 proteins were differentially expressed. Twenty proteins were upregulated and twelve proteins were down-regulated with fold change > 1.5 and < 0.6 respectively (p < 0.05). The gene ontology studies of DEPs using Panther software revealed that majority of proteins are actively involved in catalytic activities, binding and enzyme regulatory activities. The DEP'S such as NF2, MAPK, GRIPI, UGT1A1, PARP, CD68 were further subjected to pathway analysis using KEGG and Cytoscape plugin Cluego that showed involvement of proteins in successful implantation, maintenance of pluripotency, regulation of luteal function, differentiation of endometrial macrophages, protection from oxidative stress and developmental pathways such as Hippo. Further efforts are continuing for targeted proteomics, western blot to validate potential biomarkers and development of diagnostic kit for early pregnancy diagnosis in cows.

Keywords: bRPLC, Cluego, ESI, iTRAQ, KEGG, Panther

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Authors: Pei-Ru Yang, Yu-Chen Lin, Jia-Min Wu

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Background: A 58-year-old man with a history of osteoporosis and diabetes presented with chronic pain in his left knee due to severe knee joint degeneration. The knee replacement surgery was recommended by the doctor. But the patient suffered from low pain tolerance and wondered if virtual reality could relieve acute postoperative wound pain. Methods: We used the PICO (patient, intervention, comparison, and outcome) approach to generate indexed keywords and searched systematic review articles from 2017 to 2021 on the Cochran Library, PubMed, and Clinical Key databases. Results: The initial literature results included 38 articles, including 12 Cochrane library articles and 26 PubMed articles. One article was selected for further analysis after removing duplicates and off-topic articles. The eight trials included in this article were published between 2013 and 2019 and recruited a total of 723 participants. The studies, conducted in India, Lebanon, Iran, South Korea, Spain, and China, included adults who underwent hemorrhoidectomy, dental surgery, craniotomy or spine surgery, episiotomy repair, and knee surgery, with a mean age (24.1 ± 4.1 to 73.3 ± 6.5). Virtual reality is an emerging non-drug postoperative analgesia method. The findings showed that pain control was reduced by a mean of 1.48 points (95% CI: -2.02 to -0.95, p-value < 0.0001) in minor surgery and 0.32 points in major surgery (95% CI: -0.53 to -0.11, p-value < 0.03), and the overall postoperative satisfaction has improved. Discussion: Postoperative pain is a common clinical problem in surgical patients. Research has confirmed that virtual reality can create an immersive interactive environment, communicate with patients, and effectively relieve postoperative pain. However, virtual reality requires the purchase of hardware and software and other related computer equipment, and its high cost is a disadvantage. We selected the best literature based on clinical questions to answer the patient's question and used share decision making (SDM) to help the patient make decisions based on the clinical situation after knee replacement surgery to improve the quality of patient-centered care.

Keywords: knee replacement surgery, postoperative pain, share decision making, virtual reality

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Authors: Vasupradaa Manivannan, Santosh Maruthy

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Background/Aims: Preliminary evidence suggests that code-switching and code-mixing may act as one of the voluntary coping behavior to avoid the stuttering characteristics in children and adults; however, less is known about the types and patterns of code-mixing (CM) and code-switching (CS). Further, it is not known how it is different between children to adults who stutter. This study aimed to identify and compare the CM and CS patterns between Kannada-English bilingual children and adults who stutter. Method: A standard group comparison was made between five children who stutter (CWS) in the age range of 9-13 years and five adults who stutter (AWS) in the age range of 20-25 years. The participants who are proficient in Kannada (first language- L1) and English (second language- L2) were considered for the study. There were two tasks given to both the groups, a) General conversation (GC) with 10 random questions, b) Narration task (NAR) (Story / General Topic, for example., A Memorable Life Event) in three different conditions {Mono Kannada (MK), Mono English (ME), and Bilingual (BIL) Condition}. The children and adults were assessed online (via Zoom session) with a high-quality internet connection. The audio and video samples of the full assessment session were auto-recorded and manually transcribed. The recorded samples were analyzed for the percentage of dysfluencies using SSI-4 and CM, and CS exhibited in each participant using Matrix Language Frame (MLF) model parameters. The obtained data were analyzed using the Statistical Package for the Social Sciences (SPSS) software package (Version 20.0). Results: The mean, median, and standard deviation values were obtained for the percentage of dysfluencies (%SS) and frequency of CM and CS in Kannada-English bilingual children and adults who stutter for various parameters obtained through the MLF model. The inferential results indicated that %SS significantly varied between population (AWS vs CWS), languages (L1 vs L2), and tasks (GC vs NAR) but not across free (BIL) and bound (MK, ME) conditions. It was also found that the frequency of CM and CS patterns varies between CWS and AWS. The AWS had a lesser %SS but greater use of CS patterns than CWS, which is due to their excessive coping skills. The language mixing patterns were more observed in L1 than L2, and it was significant in most of the MLF parameters. However, there was a significantly higher (P<0.05) %SS in L2 than L1. The CS and CS patterns were more in conditions 1 and 3 than 2, which may be due to the higher proficiency of L2 than L1. Conclusion: The findings highlight the importance of assessing the CM and CS behaviors, their patterns, and the frequency of CM and CS between CWS and AWS on MLF parameters in two different tasks across three conditions. The results help us to understand CM and CS strategies in bilingual persons who stutter.

Keywords: bilinguals, code mixing, code switching, stuttering

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Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

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Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

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Authors: Onyinyechi Joy Kingdom

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Mergers and Acquisitions (M&A) have been proposed as a mechanism through which, problems associated with inefficiency or poor performance in financial institution could be addressed. The aim of this study is to examine the proposition that recapitalization of banks, which encouraged Mergers and Acquisitions in Nigeria banking system, would strengthen the domestic banks, improve financial deepening and the confidence of depositors. Hence, this study examines the impact of the 2005 M&A in the Nigerian-banking sector on financial deepening using mixed method (quantitative and qualitative approach). The quantitative process of this study utilised annual time series for financial deepening indicator for the period of 1997 to 2012. While, the qualitative aspect adopted semi-structured interview to collate data from three merged banks and three stand-alone banks to explore, understand and complement the quantitative results. Furthermore, a framework thematic analysis is employed to analyse the themes developed using NVivo 11 software. Using the quantitative approach, findings from the equality of mean test (EMT) used suggests that M&A have significant impact on financial deepening. However, this method is not robust enough given its weak validity as it does not control for other potential factors that may determine financial deepening. Thus, to control for other factors that may affect the level of financial deepening, a Multiple Regression Model (MRM) and Interrupted Times Series Analysis (ITSA) were applied. The coefficient for M&A dummy turned negative and insignificant using MRM. In addition, the estimated linear trend of the post intervention when ITSA was applied suggests that after M&A, the level of financial deepening decreased annually; however, this was statistically insignificant. Similarly, using the qualitative approach, the results from the interview supported the quantitative results from ITSA and MRM. The result suggests that interest rate should fall when capital base is increased to improve financial deepening. Hence, this study contributes to the existing literature the importance of other factors that may affect financial deepening and the economy when policies that will enhance bank performance and the economy are made. In addition, this study will enable the use of valuable policy instruments relevant to monetary authorities when formulating policies that will strengthen the Nigerian banking sector and the economy.

Keywords: mergers and acquisitions, recapitalization, financial deepening, efficiency, financial crisis

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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The increase in the demand for precision optics, coupled with the absence of much research output in the ultra high precision grinding of precision optics as compared to the ultrahigh precision diamond turning of optical metals has fostered the need for more research in the ultra high precision grinding of an optical lens. Furthermore, the increase in the stringent demands for nanometric surface finishes through lapping, polishing and grinding processes necessary for the use of borosilicate-crown glass in the automotive and optics industries has created the demand to effectively monitor the surface roughness during the production process. Acoustic emission phenomenon has been proven as useful monitoring technique in several manufacturing processes ranging from monitoring of bearing production to tool wear estimation. This paper introduces a rare and unique approach with the application of acoustic emission technique to monitor the surface roughness of borosilicate-crown glass during an ultra high precision grinding process. This research was carried out on a 4-axes Nanoform 250 ultrahigh precision lathe machine using an ultra high precision grinding spindle to machine the flat surface of the borosilicate-crown glass with the tip of the grinding wheel. A careful selection of parameters and design of experiment was implemented using Box-Behnken method to vary the wheel speed, feed rate and depth of cut at three levels with a 3-center point design. Furthermore, the average surface roughness was measured using Taylor Hobson PGI Dimension XL optical profilometer, and an acoustic emission data acquisition device from National Instruments was utilized to acquire the signals while the data acquisition codes were designed with National Instrument LabVIEW software for acquisition at a sampling rate of 2 million samples per second. The results show that the raw and root mean square amplitude values of the acoustic signals increased with a corresponding increase in the measured average surface roughness values for the different parameter combinations. Therefore, this research concludes that acoustic emission monitoring technique is a potential technique for monitoring the surface roughness in the ultra high precision grinding of borosilicate-crown glass.

Keywords: acoustic emission, borosilicate-crown glass, surface roughness, ultra high precision grinding

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Authors: Anne Mastamet-Mason

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Crimes against women is a global concern, and South Africa, in particular, is in a dilemma of dealing with constant criminal acts that face the country. Debates on violence against women in South Africa cannot be overemphasised any longer as crimes continue to rise year by year. The recent death of a university student at the University of Cape Town, as well as many other cases, continues to strengthen the need to find solutions from all the spheres of South African society. The advanced textiles market contains a high number and variety of technologies, many of which have protected status and constitute a relatively small portion of the textiles used for the consumer market. Examples of advanced textiles include nanomaterials, such as silver, titanium dioxide and zinc oxide, designed to create an anti-microbial and self-cleaning layer on top of the fibers, thereby reducing body smell and soiling. Smart textiles propose materials and fabrics versatile and adaptive to different situations and functions. Integrating textiles and computing technologies offer an opportunity to come up with differentiated characteristics and functionality. This paper presents a proposal to design a smart camisole/Yoga sports brazier and a smart Yoga sports pant garment to be worn by women while alone and while in purported danger zones. The smart garments are to be worn under normal clothing and cannot be detected or seen, or suspected by perpetrators. The garments are imbued with devices to sense any physical aggression and any abnormal or accelerated heartbeat that may be exhibited by the victim of violence. The signals created during the attack can be transmitted to the police and family members who own a mobile application system that accepts signals emitted. The signals direct the receiver to the exact location of the offence, and the victim can be rescued before major violations are committed. The design of the Yoga sports garments will be done by Professor Mason, who is a fashion designer by profession, while the mobile phone application system will be developed by Mr. Amos Yegon, who is an independent software developer.

Keywords: smart clothing, wearable technology, south africa, 4th industrial revolution

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Authors: Norhidayu Muhamad Zain

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Gelatin, a purified protein derived mostly from porcine and bovine sources, is used widely in food manufacturing, pharmaceutical, and cosmetic industries. However, the presence of any porcine-related products are strictly forbidden for Muslim and Jewish consumption. Therefore, analytical methods offering reliable results to differentiate the sources of gelatin are needed. The aim of this study was to differentiate the sources of gelatin (porcine and tilapia fish) using Fourier transform infrared- attenuated total reflection (FTIR-ATR) combined with two dimensional infrared (2DIR) correlation analysis. Porcine gelatin (PG) and tilapia fish gelatin (FG) samples were diluted in distilled water at concentrations ranged from 4-20% (w/v). The samples were then analysed using FTIR-ATR and 2DIR correlation software. The results showed a significant difference in the pattern map of synchronous spectra at the region of 1000 cm⁻¹ to 1100 cm⁻¹ between PG and FG samples. The auto peak at 1080 cm⁻¹ that attributed to C-O functional group was observed at high intensity in PG samples compared to FG samples. Meanwhile, two auto peaks (1080 cm⁻¹ and 1030 cm⁻¹) at lower intensity were identified in FG samples. In addition, using 2D correlation analysis, the original broad water OH bands in 1D IR spectra can be effectively differentiated into six auto peaks located at 3630, 3340, 3230, 3065, 2950 and 2885 cm⁻¹ for PG samples and five auto peaks at 3630, 3330, 3230, 3060 and 2940 cm⁻¹ for FG samples. Based on the rule proposed by Noda, the sequence of the spectral changes in PG samples is as following: NH₃⁺ amino acid > CH₂ and CH₃ aliphatic > OH stretch > carboxylic acid OH stretch > NH in secondary amide > NH in primary amide. In contrast, the sequence was totally in the opposite direction for FG samples and thus both samples provide different 2D correlation spectra ranged from 2800 cm-1 to 3700 cm⁻¹. This method may provide a rapid determination of gelatin source for application in food, pharmaceutical, and cosmetic products.

Keywords: 2 dimensional infrared (2DIR) correlation analysis, Fourier transform infrared- attenuated total reflection (FTIR-ATR), porcine gelatin, tilapia fish gelatin

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Authors: Atoui Oussama, Maazoun Azer, Belkassem Bachir, Pyl Lincy, Lecompte David

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For many decades, researchers have been focused on understanding the dynamic behavior of different structures and materials subjected to fragment impact or blast loads separately. The explosion mechanics, as well as the impact physics studies dealing with the numerical modeling of the response of protective structures under the synergistic effect of a blast wave and the impact of fragments, are quite limited in the literature. This article numerically evaluates the nonlinear dynamic behavior and damage mechanisms of Aluminum plates EN AW-1050A- H24 under different combined loading scenarios varied by the sequence of the applied loads using the commercial software LS-DYNA. For one hand, with respect to the terminal ballistic field investigations, a Lagrangian (LAG) formulation is used to evaluate the different failure modes of the target material in case of a fragment impact. On the other hand, with respect to the blast field analysis, an Arbitrary Lagrangian-Eulerian (ALE) formulation is considered to study the fluid-structure interaction (FSI) of the shock wave and the plate in case of a blast loading. Four different loading scenarios are considered: (1) only blast loading, (2) only fragment impact, (3) blast loading followed by a fragment impact and (4) a fragment impact followed by blast loading. From the numerical results, it was observed that when the impact load is applied to the plate prior to the blast load, it suffers more severe damage due to the hole enlargement phenomenon and the effects of crack propagation on the circumference of the damaged zone. Moreover, it was found that the hole from the fragment impact loading was enlarged to about three times in diameter as compared to the diameter of the projectile. The validation of the proposed computational model is based in part on previous experimental data obtained by the authors and in the other part on experimental data obtained from the literature. A good correspondence between the numerical and experimental results is found.

Keywords: computational analysis, combined loading, explosion mechanics, hole enlargement phenomenon, impact physics, synergistic effect, terminal ballistic

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Authors: Carla Idely Palencia-Aguilar

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Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

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Authors: Colleen McMillan, Alice Schmidt-Hanbidge, Beth Archer-Kuhn, Heather Boynton, Judith Hughes

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It is well known that social work students enter the profession with higher scores of adverse childhood experiences (ACE). Add to that the fact that COVID-19 has forced higher education institutions to shift to online teaching and learning, where students, faculty and field educators in social work education have reported increased stressors as well as posing challenges in developing relationships with students and being able to identify mental health challenges including those related to trauma. This multi-institutional project included three Canadian post-secondary institutions at five sites (the University of Waterloo, the University of Calgary and the University of Manitoba) and partners; Desire To Learn (D2L), The Centre for Teaching Excellence at the University of Waterloo and the Taylor Institute for Teaching and Learning. A sequential mixed method research design was used. Survey data was collected from students, faculty and field education staff from the 3 universities using the Qualtrics Insight Platform, followed by virtual focus group data with students to provide greater clarity to the quantitative data. Survey data was analyzed using SPSS software, while focus group data was transcribed verbatim and organized with N-Vivo 12. Thematic analysis used line-by-line coding and constant comparative methods within and across focus groups. The following three objectives of the study were achieved: 1) Establish a Canadian baseline on trauma informed pedagogy and student experiences of trauma informed teaching in the online higher education environment during a pandemic; 2) Identify and document educator and student experiences of online learning regarding the ability to process trauma experiences; and, 3) Transfer the findings into a trauma informed pedagogical model for Social Work as a first step toward developing a universal trauma informed teaching model. The trauma informed pedagogy model would be presented in relation to the study findings.

Keywords: trauma informed pedagogy, higher education, social work, mental health

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Authors: Nada Mohamed, Abdel Aziz Mohamed

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Climate change in coastal areas is a global issue that can be felt on local scale and will be around for decades and centuries to come to an end; it also has critical risks on the city’s economy, communities, and the natural environment. One of these changes that cause a huge risk on coastal cities is the sea level rise (SLR). SLR is a result of scarcity and reduction in global environmental system. The main cause of climate change and global warming is the countries with high development index (HDI) as Japan and Germany while the medium and low HDI countries as Egypt does not have enough awareness and advanced tactics to adapt with this changes that destroy urban areas and cause loss in land and economy. This is why Climate Resilience is one of the UN sustainable development goals 2030, which is calling for actions to strengthen climate change resilience through mitigation and adaptation. For many reasons, adaptation has received less attention than mitigation and it is only recently that adaptation has become a focal global point of attention. This adaption can be achieved through some actions such as upgrading the use and the design of the land, adjusting business and activities of people, and increasing community understanding of climate risks. To reach the adaption goals, and we have to apply a strategic pathway to Climate Resilience, which is the Urban Bioregionalism Paradigm. Resiliency has been framed as persistence, adaptation, and transformation. Climate Resilience decision support system includes a visualization platform where ecological, social, and economic information can be viewed alongside with specific geographies that's why Urban Bioregionalism is a socio-ecological system which is defined as a paradigm that has potential to help move social attitudes toward environmental understanding and deepen human-environment connections within ecological development. The research aim is to achieve an adaptive integrated urban development model throughout the analyses of tactics and strategies that can be used to adapt urban areas and coastal communities to the challenges of climate changes especially SLR and also simulation model using advanced technological software for a coastal city corridor to elaborates the suitable strategy to apply.

Keywords: climate resilience, sea level rise, SLR, coastal resilience, adaptive development simulation

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Authors: Allan Kiptanui Kimisto, Geoffrey Odhiambo Ongondo, Anastasia Wairimu Muia, Cyrus Ndungu Kimani

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The major challenge to proper sewage sludge treatment processes is the poor understanding of sludge microbiome diversities. This study applied the whole-genome. shotgun metagenomics technique to profile the microbial composition of sewage sludge in two active digestion lagoons at the Nyeri-Kangemi Wastewater Treatment Plant in Nyeri County, Kenya. Total microbial community DNA was extracted from samples using the available ZymoBIOMICS™ DNA Miniprep Kit and sequenced using Shotgun metagenomics. Samples were analyzed using MG-RAST software (Project ID: mgp100988), which allowed for comparing taxonomic diversity before β-diversities studies for Bacteria, Archaea and Eukaryotes. The study identified 57 phyla, 145 classes, 301 orders, 506 families, 963 genera, and 1980 species. Bacteria dominated the microbes and comprised 28 species, 51 classes, 110 orders, 243 families, 597 genera, and 1518 species. The Bacteroides(6.77%) were dominant, followed by Acinetobacter(1.44%) belonging to the Gammaproteobacteria and Acidororax (1.36%), Bacillus (1.24%) and Clostridium (1.02%) belonging to Betaproteobacteria. Archaea recorded 5 phyla, 13 classes, 19 orders, 29 families, 60 genera,and87 species, with the dominant genera being Methanospirillum (16.01%), methanosarcina (15.70%), and Methanoregula(14.80%) and Methanosaeta (8.74%), Methanosphaerula(5.48%) and Methanobrevibacter(5.03%) being the subdominant group. The eukaryotes were the least in abundance and comprised 24 phyla, 81 classes, 301 orders, 506 families, 963 genera, and 980 species. Arabidopsis (4.91%) and Caenorhabditis (4.81%) dominated the eukaryotes, while Dityostelium (3.63%) and Drosophila(2.08%) were the subdominant genera. All these microbes play distinct roles in the anaerobic treatment process of sewage sludge. The local sludge microbial composition and abundance variations may be due to age difference differences between the two digestion lagoons in operation at the plant and the different degradation rales played by the taxa. The information presented in this study can help in the genetic manipulation or formulation of optimal microbial ratios to improve their effectiveness in sewage sludge treatment. This study recommends further research on how the different taxa respond to environmental changes over time and space.

Keywords: shotgun metagenomics, sludge, bacteria, archaea, eukaryotes

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