Search results for: Abnormal conditions

Authors: Helena M. Wilhelm, Paulo O. Fernandes, Laís P. Dill, Kethlyn G. Moscon

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The use of vegetable oil (or natural ester) as an insulating fluid in electrical transformers is a trend that aims to contribute to environmental preservation since it is biodegradable and non-toxic. Besides, vegetable oil has high flash and combustion points, being considered a fire safety fluid. However, vegetable oil is usually less stable towards oxidation than mineral oil. Both insulating fluids, mineral and vegetable oils, need to be tested periodically according to specific standards. Oxidation stability can be determined by the induction period measured by conductivity method (Rancimat) by monitoring the effectivity of oil’s antioxidant additives, a methodology already developed for food application and biodiesel but still not standardized for insulating fluids. Besides adequate oxidation stability, fluids must be compatible with transformer's construction materials under normal operating conditions to ensure that damage to the oil and parts of the transformer does not occur. ASTM standard and Brazilian normative differ in parameters evaluated, which reveals the need to regulate tests for each oil type. The aim of this study was to assess oxidation stability and compatibility of vegetable oils to suggest the best way to assure a viable performance of vegetable oil as transformer insulating fluid. The determination of the induction period for several vegetable insulating oils from the local market by using Rancimat was carried out according to BS EN 14112 standard, at different temperatures (110, 120, and 130 °C). Also, the compatibility of vegetable oil was assessed according to ASTM and ABNT NBR standards. The main results showed that the best temperature for use in the Rancimat test is 130 °C, which allows a better observation of conductivity change. The compatibility test results presented differences between vegetable and mineral oil standards that should be taken into account in oil testing since materials compatibility and oxidation stability are essential for equipment reliability.

Keywords: Compatibility, Rancimat, natural ester, vegetable oil.

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Authors: Mehran Koleini, Jan Louis Van Rooy, Adam Bumby

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The Salman Farsi dam project is constructed on the Ghareh Agahaj River about 140km south of Shiraz city in the Zagros Mountains of southwestern Iran. This tectonic province of south-western Iran is characterized by a simple folded sedimentary sequence. The dam foundation rocks compose of the Asmari Formation of Oligo-miocene and generally comprise of a variety of karstified carbonate rocks varying from strong to weak rocks. Most of the rocks exposed at the dam site show a primary porosity due to incomplete diagenetic recrystallization and compaction. In addition to these primary dispositions to weathering, layering conditions (frequency and orientation of bedding) and the subvertical tectonic discontinuities channeled preferably the infiltrating by deep-sited hydrothermal solutions. Consequently the porosity results to be enlarged by dissolution and the rocks are expected to be karstified and to develop cavities in correspondence of bedding, major joint planes and fault zones. This kind of karsts is named hypogenic karsts which associated to the ascendant warm solutions. Field observations indicate strong karstification and vuggy intercalations especially in the middle part of the Asmari succession. The biggest karst in the dam axis which identified by speleological investigations is Golshany Cave with volume of about 150,000 m³. The tendency of the Asmari limestone for strong dissolution can alert about the seepage from the reservoir and area of the dam locality.      

Keywords: Asmari Limestone, Karstification, Salman Farsi Dam, Tectonic Pattern.

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Authors: Abdulfatah Al-Jaradi, Marzoq Ali Odhah, Abdulnasser A. Haza’a

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Background: Antenatal care can be defined as the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure the best health conditions for both mother and baby during pregnancy. The components of Antenatal Care (ANC) include risk identification; prevention and management of pregnancy-related or concurrent diseases; and health education and health promotion. The aim of this study: to assess the knowledge, attitude, and practice of pregnant women regarding ANC. Methodology: A descriptive knowledge, attitude, and practice (KAP) study was conducted in public hospitals in Sana'a City, Yemen. The study population included all pregnant women that intended to the prenatal department and clinical outpatient department; the final sample size was 371 pregnant women. A self-administered questionnaire was used to collect the data, statistical package for social sciences SPSS was used to data analysis. The results: Most (79%) of pregnant women had correct answers in total knowledge regarding ANC, and about two-thirds (67%) of pregnant women had performance practice regarding ANC and two-third (68%) of pregnant women had a positive attitude. Conclusions: More than three quarter of pregnant women had good knowledge level, most of pregnant women had moderate practice level, and more than two-thirds of pregnant women had a positive attitude regarding antenatal care. There was a statistically significant association between overall knowledge and practice level toward ANC and demographic characteristics of pregnant women, at P-value ≤ 0.05. Recommendations: we recommended more education and training courses, lecturers, and education sessions in clinical facilitators focused on ANC, which relies on evidence-based interventions provided to women during pregnancy by skilled healthcare providers such as midwives, doctors, and nurses.

Keywords: Antenatal care, knowledge, practice, attitude, pregnant women.

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.

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Authors: María D. Groppa, Andrea Trentini, Myriam Zawoznik, Roxana Bigi, Carlos Nadra, Patricia L. Marconi

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In the present work, a remediation bioprocess based on the use of a local isolate of the microalgae Chlorella vulgaris immobilized in alginate beads is proposed. This process was shown to be effective for the reduction of several chemical and microbial contaminants present in Cildáñez stream, a water course that is part of the Matanza-Riachuelo Basin (Buenos Aires, Argentina). The bioprocess, involving the culture of the microalga in autotrophic conditions in a stirred-tank bioreactor supplied with a marine propeller for 6 days, allowed a significant reduction of Escherichia coli and total coliform numbers (over 95%), as well as of ammoniacal nitrogen (96%), nitrates (86%), nitrites (98%), and total phosphorus (53%) contents. Pb content was also significantly diminished after the bioprocess (95%). Standardized cytotoxicity tests using Allium cepa seeds and Cildáñez water pre- and post-remediation were also performed. Germination rate and mitotic index of onion seeds imbibed in Cildáñez water subjected to the bioprocess was similar to that observed in seeds imbibed in distilled water and significantly superior to that registered when untreated Cildáñez water was used for imbibition. Our results demonstrate the potential of this simple and cost-effective technology to remove urban-water contaminants, offering as an additional advantage the possibility of an easy biomass recovery, which may become a source of alternative energy.

Keywords: Bioreactor, bioremediation, Chlorella vulgaris, Matanza-Riachuelo basin, microalgae.

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Authors: L. Nikakhtar, S. Zare

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One of the main practical difficulties attended with tunnel construction is related to underground water. Uncontrolled water behavior may cause extra loads on the lining, mechanical instability, and unfavorable environmental problems. Estimating underground water inflow rate to the tunnels is a complex skill. The common calculation methods are: empirical methods, analytical solutions, numerical solutions based on the equivalent continuous porous media. In this research the rate of underground water inflow to the Tabriz metro first line tunnel has been investigated by numerical finite difference method using FLAC^2D software. Comparing results of Heuer analytical method and numerical simulation showed good agreement with each other. Fully coupled and one-way coupled hydro mechanical states as well as water-free conditions in the soil around the tunnel are used in numerical models and these models have been applied to evaluate the loading value on the tunnel support system. Results showed that the fully coupled hydro mechanical analysis estimated more axial forces, moments and shear forces in linings, so this type of analysis is more conservative and reliable method for design of tunnel lining system. As sensitivity analysis, inflow water rates into the tunnel were evaluated in different soil permeability, underground water levels and depths of the tunnel. Result demonstrated that water level in constant depth of the tunnel is more sensitive factor for water inflow rate to the tunnel in comparison of other parameters investigated in the sensitivity analysis.

Keywords: Coupled hydro mechanical analysis, FLAC2D, Tabriz Metro, inflow rate.

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Authors: Domenica Tambasco, Riina Bray

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Fibromyalgia is a chronic condition characterized by widespread musculoskeletal pain, fatigue, and reduced function. Management of symptoms include medications, physical treatments and mindfulness therapies. Myofascial Release is a modality that has been successfully applied in various musculoskeletal conditions. However, to the author’s best knowledge, it is not yet recognized as a self-management therapy option in Fibromyalgia. In this study, we investigated whether Self-applied Myofascial Release (SMR) is associated with overall improved function and symptoms in Fibromyalgia. Eligible adult patients with a confirmed diagnosis of Fibromyalgia at Women’s College Hospital were recruited to SMR. Sessions ran for 1 hour once a week for 7 weeks, led by the same two physiotherapists knowledgeable in this physical treatment modality. The main outcome measure was an overall impact score for function and symptoms based on the validated assessment tool for fibromyalgia, the Revised Fibromyalgia Impact Questionnaire (FIQR), measured pre- and post-intervention. Both descriptive and analytical methods were applied and reported. We analyzed results using a paired t-test to determine if there was a statistically significant difference in mean FIQR scores between initial (pre-intervention) and final (post-intervention) scores. A clinically significant difference in FIQR was defined as a reduction in score by 10 or more points. Our pilot study showed that SMR appeared to be a safe and effective intervention for our fibromyalgia participants and the overall impact on function and symptoms occurred in only 7 weeks. Further studies with larger sample sizes comparing SMR to other physical treatment modalities (such as stretching) in an randomized control trial (RCT) are recommended.

Keywords: Fibromyalgia, myofascial release, fibromyalgia impact questionnaire, fibromyalgia assessment status.

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Authors: David Ruiz, Carlos Nava, Roberto Carbajal

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The psychological profile has become one of the most important sources of information when it comes to individual selection and the hiring process in any organization. Psychological instruments are used to collect data about variables that are considered critically important for performance in work. However, because of conceptual chaos in organizational psychology, most of the information provided by psychological testing is not directly useful for Mexican human resources professionals to take hiring decisions. The aims of this paper are 1) to underline the lack of conceptual precision in theoretical testing foundations in Mexico and 2) presenting a reliability and validity analysis of a frustration tolerance instrument created as an alternative to a heuristically conduct individual assessment in organizations. First, a description of assessment conditions in Mexico is made. Second, an instrument and a theoretical framework is presented as an alternative to the assessment practices in the country. A total of 65 Psychology Iztacala Superior Studies Faculty students were assessed. Cronbach´s alpha coefficient was calculated and an exploratory factor analysis was carried out to prove the scale unidimensionality. Reliability analysis revealed good internal consistency of the scale (Cronbach’s α = 0.825). Factor analysis produced 4 factors for the scale. However, factor loadings and explained variation give proof to the scale unidimensionality. It is concluded that the instrument has good psychometric properties that will allow human resources professionals to collect useful data. Different possibilities to conduct psychological assessment are suggested for future development.

Keywords: Psychological assessment, frustration tolerance, human resources, organizational psychology.

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Authors: S. B. Kulkarni, Hasim A. Chikte, V. Murali Mohan

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Exact solution of an unsteady MHD flow of elasticoviscous fluid through a porous media in a tube of elliptic cross section under the influence of magnetic field and constant pressure gradient has been obtained in this paper. Initially, the flow is generated by a constant pressure gradient. After attaining the steady state, the pressure gradient is suddenly withdrawn and the resulting fluid motion in a tube of elliptical cross section by taking into account of the porosity factor and magnetic parameter of the bounding surface is investigated. The problem is solved in two-stages the first stage is a steady motion in tube under the influence of a constant pressure gradient, the second stage concern with an unsteady motion. The problem is solved employing separation of variables technique. The results are expressed in terms of a non-dimensional porosity parameter, magnetic parameter and elastico-viscosity parameter, which depends on the Non-Newtonian coefficient. The flow parameters are found to be identical with that of Newtonian case as elastic-viscosity parameter, magnetic parameter tends to zero, and porosity tends to infinity. The numerical results were simulated in MATLAB software to analyze the effect of Elastico-viscous parameter, porosity parameter, and magnetic parameter on velocity profile. Boundary conditions were satisfied. It is seen that the effect of elastico-viscosity parameter, porosity parameter and magnetic parameter of the bounding surface has significant effect on the velocity parameter.

Keywords: Elastico-viscous fluid, Porous media, Elliptic cross-section, Magnetic parameter, Numerical Simulation.

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Authors: Maliheh Raji, Hossein Abolghasemi, Jaber Safdari, Ali Kargari

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Dysprosium is a rare earth element which is essential for many growing high-technology applications. Dysprosium along with neodymium plays a significant role in different applications such as metal halide lamps, permanent magnets, and nuclear reactor control rods preparation. The purification and separation of rare earth elements are challenging because of their similar chemical and physical properties. Among the various methods, membrane processes provide many advantages over the conventional separation processes such as ion exchange and solvent extraction. In this work, selective extraction and separation of dysprosium from aqueous solutions containing an equimolar mixture of dysprosium and neodymium by emulsion liquid membrane (ELM) was investigated. The organic membrane phase of the ELM was a nanofluid consisting of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as carrier, kerosene as base fluid, and nitric acid solution as internal aqueous phase. Factors affecting separation of dysprosium such as carrier concentration, MWCNT concentration, feed phase pH and stripping phase concentration were analyzed using Taguchi method. Optimal experimental condition was obtained using analysis of variance (ANOVA) after 10 min extraction. Based on the results, using MWCNT nanofluid in ELM process leads to increase the extraction due to higher stability of membrane and mass transfer enhancement and separation factor of 6 for dysprosium over neodymium can be achieved under the optimum conditions. Additionally, demulsification process was successfully performed and the membrane phase reused effectively in the optimum condition.

Keywords: Emulsion liquid membrane, MWCNT nanofluid, separation, Taguchi Method.

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Authors: R. Hocine, A. Boudjemai, A. Amrani, K. Belkacemi

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Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. The ability of a PV module to withstand the effects of periodic hot-spot heating that occurs when cells are operated under reverse biased conditions is closely related to the properties of the cell semi-conductor material.

In addition, the thermal effect also influences the estimation of the maximum power point (MPP) and electrical parameters for the PV modules, such as maximum output power, maximum conversion efficiency, internal efficiency, reliability, and lifetime. The cells junction temperature is a critical parameter that significantly affects the electrical characteristics of PV modules. For practical applications of PV modules, it is very important to accurately estimate the junction temperature of PV modules and analyze the thermal characteristics of the PV modules. Once the temperature variation is taken into account, we can then acquire a more accurate MPP for the PV modules, and the maximum utilization efficiency of the PV modules can also be further achieved.

In this paper, the three-Dimensional Transmission Line Matrix (3D-TLM) method was used to map the surface temperature distribution of solar cells while in the reverse bias mode. It was observed that some cells exhibited an inhomogeneity of the surface temperature resulting in localized heating (hot-spot). This hot-spot heating causes irreversible destruction of the solar cell structure. Hot spots can have a deleterious impact on the total solar modules if individual solar cells are heated. So, the results show clearly that the solar cells are capable of self-generating considerable amounts of heat that should be dissipated very quickly to increase PV module's lifetime.

Keywords: Thermal effect, Conduction, Heat dissipation, Thermal conductivity, Solar cell, PV module, Nodes, 3D-TLM.

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Authors: Hala S. Mekawy

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Affordable housing delivery for low and lower middle income families is a prominent problem in many developing countries; governments alone are unable to address this challenge due to diverse financial and regulatory constraints, and the private sector's contribution is rare and assists only middle-income households even when institutional and legal reforms are conducted to persuade it to go down market. Also, the market-enabling policy measures advocated by the World Bank since the early nineties have been strongly criticized and proven to be inappropriate to developing country contexts, where it is highly unlikely that the formal private sector can reach low income population. In addition to governments and private developers, affordable housing delivery systems involve an intricate network of relationships between a diverse range of actors. Collaboration between them was proven to be vital, and hence, an approach towards partnership schemes for affordable housing delivery has emerged. The basic premise of this paper is that addressing housing affordability challenges in Egypt demands direct public support, as markets and market actors alone would never succeed in delivering decent affordable housing to low and lower middle income groups. It argues that this support would ideally be through local level partnership schemes, with a leading decentralized local government role, and partners being identified according to specific local conditions. It attempts to identify major attributes that would ensure the fulfillment of the goals of such schemes in the Egyptian context. This is based upon evidence from diversified worldwide experiences, in addition to the main outcomes of a questionnaire that was conducted to specialists and chief actors in the field.

Keywords: Affordable housing, partnership schemes.

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Authors: Siti Nor Hafizah binti Mohd Zaid, Mohamed Abdel-Maguid, Abdel-Hamid Soliman

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An Advance Driver Assistance System (ADAS) is a computer system on board a vehicle which is used to reduce the risk of vehicular accidents by monitoring factors relating to the driver, vehicle and environment and taking some action when a risk is identified. Much work has been done on assessing vehicle and environmental state but there is still comparatively little published work that tackles the problem of driver state. Visual attention is one such driver state. In fact, some researchers claim that lack of attention is the main cause of accidents as factors such as fatigue, alcohol or drug use, distraction and speeding all impair the driver-s capacity to pay attention to the vehicle and road conditions [1]. This seems to imply that the main cause of accidents is inappropriate driver behaviour in cases where the driver is not giving full attention while driving. The work presented in this paper proposes an ADAS system which uses an image based template matching algorithm to detect if a driver is failing to observe particular windscreen cells. This is achieved by dividing the windscreen into 24 uniform cells (4 rows of 6 columns) and matching video images of the driver-s left eye with eye-gesture templates drawn from images of the driver looking at the centre of each windscreen cell. The main contribution of this paper is to assess the accuracy of this approach using Receiver Operating Characteristic analysis. The results of our evaluation give a sensitivity value of 84.3% and a specificity value of 85.0% for the eye-gesture template approach indicating that it may be useful for driver point of regard determinations.

Keywords: Advanced Driver Assistance Systems, Eye-Tracking, Hazard Detection.

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Authors: Krasimir I. Ivanov, Elitsa N. Kolentsova, Dimitar Y. Dimitrov, Georgi V. Avdeev, Tatyana T. Tabakova

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In recent research copper and manganese systems were found to be the most active in CO and organic compounds oxidation among the base catalysts. The mixed copper manganese oxide has been widely studied in oxidation reactions because of their higher activity at low temperatures in comparison with single oxide catalysts. The results showed that the formation of spinel CuxMn3−xO4 in the oxidized catalyst is responsible for the activity even at room temperature. That is why the most of the investigations are focused on the hopcalite catalyst (CuMn2O4) as the best coppermanganese catalyst. Now it’s known that this is true only for CO oxidation, but not for mixture of CO and VOCs. The purpose of this study is to investigate the alumina supported copper-manganese catalysts with different Cu/Mn molar ratio in terms of oxidation of CO, methanol and dimethyl ether. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and the catalytic activity measurements were carried out in two stage continuous flow equipment with an adiabatic reactor for simultaneous oxidation of all compounds under the conditions closest possible to the industrial. Gas mixtures on the input and output of the reactor were analyzed with a gas chromatograph, equipped with FID and TCD detectors. The texture characteristics were determined by low-temperature (- 196oС) nitrogen adsorption in a Quantachrome Instruments NOVA 1200e (USA) specific surface area & pore analyzer. Thermal, XRD and TPR analyses were performed. It was established that the active component of the mixed Cu- Mn/γ–alumina catalysts strongly depends on the Cu/Mn molar ratio. Highly active alumina supported Cu-Mn catalysts for CO, methanol and DME oxidation were synthesized. While the hopcalite is the best catalyst for CO oxidation, the best compromise for simultaneous oxidation of all components is the catalyst with Cu/Mn molar ratio 1:5.

Keywords: Supported copper-manganese catalysts, CO and VOCs oxidation.

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Authors: U K Chakrabarti, Jigisha Parikh

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Hazardous Material transportation by road is coupled with inherent risk of accidents causing loss of lives, grievous injuries, property losses and environmental damages. The most common type of hazmat road accident happens to be the releases (78%) of hazardous substances, followed by fires (28%), explosions (14%) and vapour/ gas clouds (6 %.). The paper is discussing initially the probable 'Impact Zones' likely to be caused by one flammable (LPG) and one toxic (ethylene oxide) chemicals being transported through a sizable segment of a State Highway connecting three notified Industrial zones in Surat district in Western India housing 26 MAH industrial units. Three 'hotspots' were identified along the highway segment depending on the particular chemical traffic and the population distribution within 500 meters on either sides. The thermal radiation and explosion overpressure have been calculated for LPG / Ethylene Oxide BLEVE scenarios along with toxic release scenario for ethylene oxide. Besides, the dispersion calculations for ethylene oxide toxic release have been made for each 'hotspot' location and the impact zones have been mapped for the LOC concentrations. Subsequently, the maximum Initial Isolation and the protective zones were calculated based on ERPG-3 and ERPG-2 values of ethylene oxide respectively which are estimated taking the worst case scenario under worst weather conditions. The data analysis will be helpful to the local administration in capacity building with respect to rescue / evacuation and medical preparedness and quantitative inputs to augment the District Offsite Emergency Plan document.

Keywords: Hotspot, Ethylene Oxide, LPG, MAH (MajorAccident Hazard).

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.

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Authors: Rohit Sharma, Fabio Cozzi

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A 3C-2D PIV technique was applied to investigate the swirling flow generated by an axial plus tangential type swirl generator. This work is focused on the near-exit region of an isothermal swirling jet to characterize the effect of swirl on the flow field and to identify the large coherent structures both in unconfined and confined conditions for geometrical swirl number, S_g = 4.6. Effects of the Reynolds number on the flow structure were also studied. The experimental results show significant effects of the confinement on the mean velocity fields and its fluctuations. The size of the recirculation zone was significantly enlarged upon confinement compared to the free swirling jet. Increasing in the Reynolds number further enhanced the recirculation zone. The frequency characteristics have been measured with a capacitive microphone which indicates the presence of periodic oscillation related to the existence of precessing vortex core, PVC. Proper orthogonal decomposition of the jet velocity field was carried out, enabling the identification of coherent structures. The time coefficients of the first two most energetic POD modes were used to reconstruct the phase-averaged velocity field of the oscillatory motion in the swirling flow. The instantaneous minima of negative swirl strength values calculated from the instantaneous velocity field revealed the presence of two helical structures located in the inner and outer shear layers and this structure fade out at an axial location of approximately z/D = 1.5 for unconfined case and z/D = 1.2 for confined case. By phase averaging the instantaneous swirling strength maps, the 3D helical vortex structure was reconstructed.

Keywords: Acoustic probes, 3C-2D particle image velocimetry, PIV, precessing vortex core, PVC, recirculation zone.

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Authors: Brody R. Clark, Chaminda Gallage, John Yeaman

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Multigrade bitumen asphalt is a quality asphalt product that is not utilised in many places globally. Multigrade bitumen is believed to be less sensitive to temperature, which gives it an advantage over conventional binders. Previous testing has shown that asphalt temperature changes greatly with depth, but currently the industry standard is to nominate a single temperature for design. For detailed design of asphalt roads, perhaps asphalt layers should be divided into nominal layer depths and different modulus and fatigue equations/values should be used to reflect the temperatures of each respective layer. A collaboration of previous laboratory testing conducted on multigrade bitumen asphalt beams under a range of temperatures and loading conditions was analysed. The samples tested included 0% or 15% recycled asphalt pavement (RAP) to determine what impact the recycled material has on the fatigue life and stiffness of the pavement. This paper investigated the temperature susceptibility of multigrade bitumen asphalt pavements compared to conventional binders by combining previous testing that included conducting a sweep of fatigue tests, developing complex modulus master curves for each mix and a study on how pavement temperature changes through pavement depth. This investigation found that the final design of the pavement is greatly affected by the nominated pavement temperature and respective material properties. This paper has outlined a potential revision to the current design approach for asphalt pavements and proposes that further investigation is needed into pavement temperature and its incorporation into design.

Keywords: Asphalt, complex modulus, fatigue life, flexural stiffness, four-point bending, master curves, multigrade bitumen, thermal gradient.

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Authors: L. Basha, E. Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine learning methods, such as Random Forest (RF), are used to predict cereal yield responses to climacteric and other variables. RF showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the RF method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods: multiple linear regression and lasso regression method.

Keywords: Cereal yield, climate change, machine learning, multiple regression model, random forest.

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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Owing to the lack of synchronization between the solar energy availability and the heat demands in a specific application, the energy storing sub-system is necessary to maintain the continuity of thermal process. The present work is dealing with an active solar heating storing system in which an air solar collector is connected to storing unit where this energy is distributed and provided to the heated space in a controlled manner. The solar collector is a box type absorber where the air flows between a number of vanes attached between the collector absorber and the bottom plate. This design can improve the efficiency due to increasing the heat transfer area exposed to the flowing air, as well as the heat conduction through the metal vanes from the top absorbing surface. The storing unit is a packed bed type where the air is coming from the air collector and circulated through the bed in order to add/remove the energy through the charging / discharging processes, respectively. The major advantage of the packed bed storage is its high degree of thermal stratification. Numerical solution of the packed bed energy storage is considered through dividing the bed into a number of equal segments for the bed particles and solved the energy equation for each segment depending on the neighbor ones. The studied design and performance parameters in the developed simulation model including, particle size, void fraction, etc. The final results showed that the collector efficiency was fluctuated between 55%-61% in winter season (January) under the climatic conditions of Misurata in Libya. Maximum temperature of 52ºC is attained at the top of the bed while the lower one is 25ºC at the end of the charging process of hot air into the bed. This distribution can satisfy the required load for the most house heating in Libya.

Keywords: Solar energy, thermal process, performance, collector, packed bed, numerical analysis, simulation.

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Authors: M. F. Nawaz, S. Gul, T. H. Farooq, M. T. Siddiqui, M. Asif, I. Ahmad, N. K. Niazi

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In Pakistan, major demands of fuel wood and timber wood are fulfilled by agroforestry. However, the information regarding economic significance of agroforestry and its productivity in Pakistan is still insufficient and unreliable. Survey of field conditions to examine the agroforestry status at local level helps us to know the future trends and to formulate the policies for sustainable wood supply. The objectives of this research were to examine the actual status and potential of agroforestry and to point out the barriers that are faced by farmers in the adoption of agroforestry. Research was carried out in Chiniot district, Pakistan because it is the famous city for furniture industry that is largely dependent on farm trees. A detailed survey of district Chiniot was carried out from 150 randomly selected farmer respondents using multi-objective oriented and pre-tested questionnaire. It was found that linear tree planting method was more adopted (45%) as compared to linear + interplanting (42%) and/or compact planting (12.6%). Chi-square values at P-value <0.5 showed that age (11.35) and education (17.09) were two more important factors in the quick adoption of agroforestry as compared to land holdings (P-value of 0.7). The major reason of agroforestry adoption was to obtain income, fodder and fuelwood. The most dominant species in farmlands was shisham (Dalbergia sissoo) but since last five years, mostly farmers were growing Sufeida (Eucalyptus camaldulensis), kikar (Acacia nilotica) and popular (Populus deltoides) on their fields due to “Shisham die-back” problem. It was found that agro-forestry can be increased by providing good quality planting material to farmers and improving wood markets.

Keywords: Agroforestry, trees, services, agriculture, farmers.

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Authors: Verónica Díaz

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A Cartesian graph, as a mathematical object, becomes a tool for configuration of change. Its best comprehension is done through everyday life problem-solving associated with its representation. Despite this, the current educational framework favors general graphs, without consideration of their argumentation. Students are required to find the mathematical function without associating it to the development of graphical language. This research describes the use made by students of configurations made prior to Cartesian graphs with regards to an everyday life problem related to a time and distance variation phenomenon. The theoretical framework describes the function conditions of study and their modeling. This is a qualitative, descriptive study involving six undergraduate case studies that were carried out during the first term in 2016 at University of Los Lagos. The research problem concerned the graphic modeling of a real person’s movement phenomenon, and two levels of analysis were identified. The first level aims to identify local and global graph interpretations; a second level describes the iconicity and referentiality degree of an image. According to the results, students were able to draw no figures before the Cartesian graph, highlighting the need for students to represent the context and the movement of which causes the phenomenon change. From this, they managed Cartesian graphs representing changes in position, therefore, achieved an overall view of the graph. However, the local view only indicates specific events in the problem situation, using graphic and verbal expressions to represent movement. This view does not enable us to identify what happens on the graph when the movement characteristics change based on possible paths in the person’s walking speed.

Keywords: Cartesian graphs, higher education, movement modeling, problem solving.

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Authors: Ruoyang Tang, Jianguo Nie

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Lateral-torsional bracing members are critical to the stability of girder systems during the construction phase of steel-concrete composite bridges, and the interaction effect of multiple girders plays an essential role in the determination of buckling load. In this paper, an investigation is conducted on the lateral-torsional buckling behavior of the steel girder system which is composed of three or four I-shaped girders and braced by solid web crossbeams. The buckling load for such girder system is comprehensively analyzed and an analytical solution is developed for uniform pressure loading conditions. Furthermore, post-buckling analysis including initial geometric imperfections is performed and parametric studies in terms of bracing density, stiffness ratio as well as the number and spacing of girders are presented in order to find the optimal bracing plans for an arbitrary girder layout. The theoretical solution of critical load on account of local buckling mode shows good agreement with the numerical results in eigenvalue analysis. In addition, parametric analysis results show that both bracing density and stiffness ratio have a significant impact on the initial stiffness, global stability and failure mode of such girder system. Taking into consideration the effect of initial geometric imperfections, an increase in bracing density between adjacent girders can effectively improve the bearing capacity of the structure, and higher beam-girder stiffness ratio can result in a more ductile failure mode.

Keywords: Bracing member, construction stage, lateral-torsional buckling, steel girder system.

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Authors: M. I. Equbal, R.K. Ohdar, B. Singh, P. Talukdar

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Micro-alloyed steel components are used in automotive industry for the necessity to make the manufacturing process cycles shorter when compared to conventional steel by eliminating heat treatment cycles, so an important saving of costs and energy can be reached by reducing the number of operations. Microalloying elements like vanadium, niobium or titanium have been added to medium carbon steels to achieve grain refinement with or without precipitation strengthening along with uniform microstructure throughout the matrix. Present study reports the applicability of medium carbon vanadium micro-alloyed steel in hot forging. Forgeability has been determined with respect to different cooling rates, after forging in a hydraulic press at 50% diameter reduction in temperature range of 900-11000C. Final microstructures, hardness, tensile strength, and impact strength have been evaluated. The friction coefficients of different lubricating conditions, viz., graphite in hydraulic oil, graphite in furnace oil, DF 150 (Graphite, Water-Based) die lubricant and dry or without any lubrication were obtained from the ring compression test for the above micro-alloyed steel. Results of ring compression tests indicate that graphite in hydraulic oil lubricant is preferred for free forging and dry lubricant is preferred for die forging operation. Exceptionally good forgeability and high resistance to fracture, especially for faster cooling rate has been observed for fine equiaxed ferrite-pearlite grains, some amount of bainite and fine precipitates of vanadium carbides and carbonitrides. The results indicated that the cooling rate has a remarkable effect on the microstructure and mechanical properties at room temperature.

Keywords: Cooling rate, Hot forging, Micro-alloyed, Ring compression.

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Authors: E. Sarauskis, L. Masilionyte, Z. Kriauciuniene, K. Romaneckas, S. Buragiene

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In maize growing technologies, tillage technological operations are the most time-consuming and require the greatest fuel input. Substitution of conventional tillage, involving deep ploughing, by other reduced tillage methods can reduce technological production costs, diminish soil degradation and environmental pollution from greenhouse gas emissions, as well as improve economic competitiveness of agricultural produce.

Experiments designed to assess energy and environmental aspects associated with different reduced tillage systems, applied in maize cultivation were conducted at Aleksandras Stulginskis University taking into account Lithuania’s economic and climate conditions. The study involved 5 tillage treatments: deep ploughing (DP, control), shallow ploughing (SP), deep cultivation (DC), shallow cultivation (SC) and no-tillage (NT).

Our experimental evidence suggests that with the application of reduced tillage systems it is feasible to reduce fuel consumption by 13-58% and working time input by 8.4% to nearly 3-fold, to reduce the cost price of maize cultivation technological operations, decrease environmental pollution with CO₂ gas by 30 to 146 kg ha^-1, compared with the deep ploughing.

Keywords: Reduced tillage, energy and environmental assessment, fuel consumption, CO2 emission, maize.

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Authors: Albana Hasimi, Edlira Tako, Partizan Malkaj, Elvin Çomo, Blerina Papajani, Mirela Ndrita, Ledjan Malaj

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Many endeavors have been exerted during the last years for developing new artificial polymeric membranes, which fulfill the demanded conditions for biomedical uses. One of the most tested polymers is Poly(vinyl alcohol) [PVA]. Our teams are based on the possibility of using PVA for personal protective equipment against COVID-19. In personal protective equipment, we explore the possibility of modifying the properties of the polymer by adding Montmorillonite [MMT]. Heat-treatment above the glass transition temperature is used to improve mechanical properties mainly by increasing the crystallinity of the polymer, which acts as a physical network. Temperature-Modulated Differential Scanning Calorimetry (TMDSC) measurements indicated that the presence of 0.5% MMT in PVA causes a higher Tg value and shaped peak of crystallinity. Decomposition is observed at two of the melting points of the crystals during heating 25-240 oC and overlap of the recrystallization ridges during cooling 240-25 oC. This is indicative of the presence of two types (quality or structure) of polymer crystals. On the other hand, some indication of improvement of the quality of the crystals by heat-treatment is given by the distinct non-reversing contribution to melting. Data on sorption and transport of water in PVA films: PVA pure and PVA/MMT matrix, modified by thermal treatment are presented. The membranes become more rigid as a result of the heat treatment and because of this the water uptake is significantly lower in membranes. That is indicated by analysis of the resulting water uptake kinetics. The presence of 0.5% w/w of MMT has no significant impact on the properties of PVA membranes. Water uptake kinetics deviate from Fick’s law due to slow relaxation of glassy polymer matrix for all types of membranes.

Keywords: Crystallinity, montmorillonite, nanocomposite, poly(vinyl alcohol).

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Authors: K. Nirmala Devi, V. Murali Bhaskaran

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Traditional document representation for classification follows Bag of Words (BoW) approach to represent the term weights. The conventional method uses the Vector Space Model (VSM) to exploit the statistical information of terms in the documents and they fail to address the semantic information as well as order of the terms present in the documents. Although, the phrase based approach follows the order of the terms present in the documents rather than semantics behind the word. Therefore, a semantic concept based approach is used in this paper for enhancing the semantics by incorporating the ontology information. In this paper a novel method is proposed to forecast the intraday stock market price directional movement based on the sentiments from Twitter and money control news articles. The stock market forecasting is a very difficult and highly complicated task because it is affected by many factors such as economic conditions, political events and investor’s sentiment etc. The stock market series are generally dynamic, nonparametric, noisy and chaotic by nature. The sentiment analysis along with wisdom of crowds can automatically compute the collective intelligence of future performance in many areas like stock market, box office sales and election outcomes. The proposed method utilizes collective sentiments for stock market to predict the stock price directional movements. The collective sentiments in the above social media have powerful prediction on the stock price directional movements as up/down by using Granger Causality test.

Keywords: Bag of Words, Collective Sentiments, Ontology, Semantic relations, Sentiments, Social media, Stock Prediction, Twitter, Vector Space Model and wisdom of crowds.

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Authors: K. N. Dinesh Babu, P. K. Gargava

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Energization of a transformer results in sudden flow of current which is an effect of core magnetization. This current will be dominated by the presence of second harmonic, which in turn is used to segregate fault and inrush current, thus guaranteeing proper operation of the relay. This additional security in the relay sometimes obstructs or delays differential protection in a specific scenario, when the 2^nd harmonic content was present during a genuine fault. This kind of scenario can result in isolation of the transformer by Buchholz and pressure release valve (PRV) protection, which is acted when fault creates more damage in transformer. Such delays involve a huge impact on the insulation failure, and chances of repairing or rectifying fault of problem at site become very dismal. Sometimes this delay can cause fire in the transformer, and this situation becomes havoc for a sub-station. Such occurrences have been observed in field also when differential relay operation was delayed by 10-15 ms by second harmonic blocking in some specific conditions. These incidences have led to the need for an alternative solution to eradicate such unwarranted delay in operation in future. Modern numerical relay, called as intelligent electronic device (IED), is embedded with advanced protection features which permit higher flexibility and better provisions for tuning of protection logic and settings. Such flexibility in transformer protection IEDs, enables incorporation of alternative methods such as dynamic switching of second harmonic feature for blocking the differential protection with additional security. The analysis and precautionary measures carried out in this case, have been simulated and discussed in this paper to ensure that similar solutions can be adopted to inhibit analogous issues in future.

Keywords: Differential protection, intelligent electronic device (IED), 2nd harmonic, inrush inhibit.

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Authors: Muftah H. El-Naas, Ameera F. Mohammad, Mabruk I. Suleiman, Mohamed Al Musharfy, Ali H. Al-Marzouqi

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CO₂ capture and storage technologies play a significant role in contributing to the control of climate change through the reduction of carbon dioxide emissions into the atmosphere. The present study evaluates and optimizes CO₂ capture through a process, where carbon dioxide is passed into pH adjusted high salinity water and reacted with sodium chloride to form a precipitate of sodium bicarbonate. This process is based on a modified Solvay process with higher CO₂ capture efficiency, higher sodium removal, and higher pH level without the use of ammonia. The process was tested in a bubble column semi-batch reactor and was optimized using response surface methodology (RSM). CO₂ capture efficiency and sodium removal were optimized in terms of major operating parameters based on four levels and variables in Central Composite Design (CCD). The operating parameters were gas flow rate (0.5–1.5 L/min), reactor temperature (10 to 50 ^oC), buffer concentration (0.2-2.6%) and water salinity (25-197 g NaCl/L). The experimental data were fitted to a second-order polynomial using multiple regression and analyzed using analysis of variance (ANOVA). The optimum values of the selected variables were obtained using response optimizer. The optimum conditions were tested experimentally using desalination reject brine with salinity ranging from 65,000 to 75,000 mg/L. The CO₂ capture efficiency in 180 min was 99% and the maximum sodium removal was 35%. The experimental and predicted values were within 95% confidence interval, which demonstrates that the developed model can successfully predict the capture efficiency and sodium removal using the modified Solvay method.

Keywords: Bubble column reactor, CO2 capture, Response Surface Methodology, water desalination.

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: Human machine interface, industrial internet of things, internet of things, optical character recognition, video analytic.

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