Search results for: universal values

Authors: Roopa Singh, Anurag Singh, Ajay

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Agriculture contributes a major share in the national economy of India. A major portion of Indian economy (about 70%) depends upon agriculture as it forms the main source of income. About 43% of India’s geographical area is used for agricultural activity which involves 65-75% of total population of India. The given work deals with the Fast moving Consumer Goods (FMCG) industries and their inventories which use agricultural produce as their raw material or input for their final product. Since the beginning of inventory practices, many developments took place which can be categorised into three phases, based on the review of various works. The first phase is related with development and utilization of Economic Order Quantity (EOQ) model and methods for optimizing costs and profits. Second phase deals with inventory optimization method, with the purpose of balancing capital investment constraints and service level goals. The third and recent phase has merged inventory control with electrical control theory. Maintenance of inventory is considered negative, as a large amount of capital is blocked especially in mechanical and electrical industries. But the case is different in food processing and agro-based industries and their inventories due to cyclic variation in the cost of raw materials of such industries which is the reason for selection of these industries in the mentioned work. The application of electrical control theory in inventory control makes the decision-making highly instantaneous for FMCG industries without loss in their proposed profits, which happened earlier during first and second phases, mainly due to late implementation of decision. The work also replaces various inventories and work-in-progress (WIP) related errors with their monetary values, so that the decision-making is fully target-oriented.

Keywords: control theory, inventory control, manufacturing sector, EOQ, feedback, FMCG sector

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Authors: Samsher Gautam, Apoorva Roy, Bhuvan Aggarwal

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Vapor absorption refrigeration systems can replace vapor compression systems in many applications as they can operate on a low-grade heat source and are environment-friendly. Widely used refrigerants such as CFCs and HFCs cause significant global warming. Natural refrigerants can be an alternative to them, among which carbon dioxide is promising for use in automotive air conditioning systems. Its inherent safety, ability to withstand high pressure and high heat transfer coefficient coupled with easy availability make it a likely choice for refrigerant. Various properties of the ionic liquid [bmim][PF₆], such as non-toxicity, stability over a wide temperature range and ability to dissolve gases like carbon dioxide, make it a suitable absorbent for a vapor absorption refrigeration system. In this paper, an absorption chiller consisting of a generator, condenser, evaporator and absorber was studied at an operating temperature of 70⁰C. A thermodynamic model was set up using the Peng-Robinson equations of state to predict the behavior of the refrigerant and absorbent pair at different points in the system. A MATLAB code was used to obtain the values of enthalpy and entropy at selected points in the system. The exergy destruction in each component and exergetic coefficient of performance (ECOP) of the system were calculated by performing an exergy analysis based on the second law of thermodynamics. Graphs were plotted between varying operating conditions and the ECOP obtained in each case. The effect of every component on the ECOP was examined. The exergetic coefficient of performance was found to be lesser than the coefficient of performance based on the first law of thermodynamics.

Keywords: [bmim][PF₆] as absorbent, carbon dioxide as refrigerant, exergy analysis, Peng-Robinson equations of state, vapor absorption refrigeration

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Salman Ahmad, Muhammad Aown Sammar Raza, Muhammad Farrukh Saleem, Rashid Iqbal, Muhammad Saqlain Zaheer, Muhammad Usman Aslam, Imran Haider, Muhammad Adnan Nazar, Muhammad Ali

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Among the various abiotic stresses, drought stress is one of the most challenging for field crops. Wheat is one of the major staple food of the world, which is highly affected by water deficit stress in the current scenario of climate change. In order to ensure food security by depleting water resources, there is an urgent need to adopt technologies which result in sufficient crop yield with less water consumption. Mulching and partial rootzone drying (PRD) are two important management techniques used for water conservation and to mitigate the negative impacts of drought. The experiment was conducted to screen out the best-suited mulch for wheat under PRD system. Two water application techniques (I1= full irrigation I2= PRD irrigation) and four mulch treatments (M0= un-mulched, M1= black plastic mulch, M2= wheat straw mulch and M4= cotton sticks mulch) were conducted in completely randomized design with four replications. The treatment, black plastic mulch was performed the best than other mulch treatments. For irrigation levels, higher values of growth, physiological and water-related parameters were recorded in control treatment while, quality traits and enzymatic activities were higher under partial root zone drying. The current study concluded that adverse effects of drought on wheat can be significantly mitigated by using mulches but black plastic mulch was best suited for partial rootzone drying irrigation system in wheat.

Keywords: antioxidants, leaf water relations, Mulches, osmolytes, partial root zone drying, photosynthesis

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Authors: Foo Shen Hwang, Thomas Confrey, Stephen Scully, Barry Flannery

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Thermal characterization plays an important role in battery pack design. Lithium-ion batteries have to be maintained between 15-35 °C to operate optimally. Heat is generated (Q) internally within the batteries during both the charging and discharging phases. This can be quantified using several standard methods. The most common method of calculating the batteries heat generation is through the addition of both the joule heating effects and the entropic changes across the battery. In addition, such values can be derived by identifying the open-circuit voltage (OCV), nominal voltage (V), operating current (I), battery temperature (T) and the rate of change of the open-circuit voltage in relation to temperature (dOCV/dT). This paper focuses on experimental characterization and comparative modelling of the heat generation rate (Q) across several current discharge rates (0.5C, 1C, and 1.5C) of a 18650 cell. The analysis is conducted utilizing several non-linear mathematical functions methods, including polynomial, exponential, and power models. Parameter fitting is carried out over the respective function orders; polynomial (n = 3~7), exponential (n = 2) and power function. The generated parameter fitting functions are then used as heat source functions in a 3-D computational fluid dynamics (CFD) solver under natural convection conditions. Generated temperature profiles are analyzed for errors based on experimental discharge tests, conducted at standard room temperature (25°C). Initial experimental results display low deviation between both experimental and CFD temperature plots. As such, the heat generation function formulated could be easier utilized for larger battery applications than other methods available.

Keywords: computational fluid dynamics, curve fitting, lithium-ion battery, voltage drop

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Authors: Wern Lin Yeo, Choo Kim Tan, Sook Ling Lew

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Mathematics anxiety refers to the feeling of anxious when one having difficulties in solving mathematical problem. Mathematics anxiety is the most common type of anxiety among other types of anxiety which occurs among the students. However, level of anxiety among males and females are different. There were few past study were conducted to determine the relationship of anxiety and gender but there were still did not have an exact results. Hence, the purpose of this study is to determine the relationship of anxiety level between male and female undergraduates at a private university in Malaysia. Convenient sampling method used in this study in which the students were selected based on the grouping assigned by the faculty. There were 214 undergraduates who registered the probability courses had participated in this study. Mathematics Anxiety Rating Scale (MARS) was the instrument used in study which used to determine students’ anxiety level towards probability. Reliability and validity of instrument was done before the major study was conducted. In the major study, students were given briefing about the study conducted. Participation of this study were voluntary. Students were given consent form to determine whether they agree to participate in the study. Duration of two weeks were given for students to complete the given online questionnaire. The data collected will be analyzed using Statistical Package for the Social Sciences (SPSS) to determine the level of anxiety. There were three anxiety level, i.e., low, average and high. Students’ anxiety level were determined based on their scores obtained compared with the mean and standard deviation. If the scores obtained were below mean and standard deviation, the anxiety level was low. If the scores were at below and above the mean and between one standard deviation, the anxiety level was average. If the scores were above the mean and greater than one standard deviation, the anxiety level was high. Results showed that both of the gender were having average anxiety level. Males having high frequency of three anxiety level which were low, average and high anxiety level as compared to females. Hence, the mean values obtained for males (M = 3.62) was higher than females (M = 3.42). In order to be significant of anxiety level among the gender, the p-value should be less than .05. The p-value obtained in this study was .117. However, this value was greater than .05. Thus, there was no significant difference of anxiety level among the gender. In other words, there was no relationship of anxiety level with the gender.

Keywords: anxiety level, gender, mathematics anxiety, probability and statistics

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Authors: Dafna Knani, Sarit S. Sivan

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Aggrecan, one of the main components of the intervertebral disc (IVD), belongs to the family of proteoglycans (PGs) that are composed of glycosaminoglycan (GAG) chains covalently attached to a core protein. Its primary function is to maintain tissue hydration and hence disc height under the high loads imposed by muscle activity and body weight. Significant PG loss is one of the first indications of disc degeneration. A possible solution to recover disc functions is by injecting a synthetic hydrogel into the joint cavity, hence mimicking the role of PGs. One of the hydrogels proposed is GAG-analogues, based on sulfate-containing polymers, which are responsible for hydration in disc tissue. In the present work, we used molecular dynamics (MD) to study the effect of the hydrogel crosslinking (type and degree) on the swelling behavior of the suggested GAG-analogue biomimetics by calculation of cohesive energy density (CED), solubility parameter, enthalpy of mixing (ΔEmix) and the interactions between the molecules at the pure form and as a mixture with water. The simulation results showed that hydrophobicity plays an important role in the swelling of the hydrogel, as indicated by the linear correlation observed between solubility parameter values of the copolymers and crosslinker weight ratio (w/w); this correlation was found useful in predicting the amount of PEGDA needed for the desirable hydration behavior of (CS)₄-peptide. Enthalpy of mixing calculations showed that all the GAG analogs, (CS)₄ and (CS)₄-peptide are water-soluble; radial distribution function analysis revealed that they form interactions with water molecules, which is important for the hydration process. To conclude, our simulation results, beyond supporting the experimental data, can be used as a useful predictive tool in the future development of biomaterials, such as disc replacement.

Keywords: molecular dynamics, proteoglycans, enthalpy of mixing, swelling

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Authors: Nurcan Cetinkaya

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The aim of the study was to estimate the microbial-N flow to small intestine based on daily urinary purine derivatives(PD) mainly xanthine, hypoxanthine, uric acid and allantoin excretion in Angora goats fed by grass hay and concentrate (Period I); barley straw and concentrate (Period II). Daily urine samples were collected during last 3 days of each period from 10 individually penned Angora bucks( LW 30-35 Kg, 2-3 years old) receiving ad libitum grass hay or barley straw and 300 g/d concentrate. Fresh water was always available. 4N H2SO4 was added to collected daily urine .samples to keep pH under 3 to avoid of uric acid precipitation. Diluted urine samples were stored at -20°C until analysis. Urine samples were analyzed for xanthine, hypoxanthine, uric acid, allantoin and creatinine by High-Performance Liquid Chromatographic Method (HPLC). Urine was diluted 1:15 in ratio with water and duplicate samples were prepared for HPLC analysis. Calculated mean levels (n=60) for urinary xanthine, hypoxanthine, uric acid, allantoin, total PD and creatinine excretion were 0.39±0.02 , 0.26±0.03, 0.59±0.06, 5.91±0.50, 7.15±0.57 and 3.75±0.40 mmol/L for Period I respectively; 0.35±0.03, 0.21±0.02, 0.55±0.05, 5.60±0.47, 6.71±0.46 and 3.73±0.41 mmol/L for Period II respectively.Mean values of Period I and II were significantly different (P< 0.05) except creatinine excretion. Estimated mean microbial-N supply to the small intestine for Period I and II in Angora goats were 5.72±0.46 and 5.41±0.61 g N/d respectively. The effects of grass hay and barley straw feeding on microbial-N supply to small intestine were found significantly different (P< 0.05). In conclusion, grass hay showed a better effect on the ruminal microbial protein synthesis compared to barley straw, therefore; grass hay is suggested as roughage source in Angora goat feeding.

Keywords: angora goat, HPLC method, microbial-N supply to small intestine, urinary purine derivatives

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Authors: Jasna Čanadanović-Brunet, Gordana Ćetković, Sonja Djilas, Vesna Tumbas-Šaponjac, Jelena Vulić, Sladjana Stajčić

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Honey, produced by the honeybee, is a natural saturated sugar solution, which is mainly composed of a complex mixture of carbohydrates. Besides this, it also contains certain minor constituents, proteins, enzymes, amino and organic acids, lipids, vitamins, phenolic acids, flavonoids and carotenoids. Honey serves as a source of natural antioxidants, which are effective in reducing the risk of heart disease, cancer, immune-system decline, cataracts, and different inflammatory processes. Honey is consumed in its natural form alone, but also in combination with nuts and various kinds of dried fruits (plums, figs, cranberries, apricots etc.). The aim of this research was to investigate the contribution of dried apricot addition to polyphenols and flavonoids contents and antioxidant activities of honey. Some individual phenolic compounds in Serbian polyfloral honey (PH), linden honey (LH) and also in their mixtures with dried apricot, in 40% mass concentrations (PH40; LH40), were identified and quantified by HPLC. The most dominant phenolic compound was: gallic acid in LH (11.14 mg/100g), LH40 (42.65 mg/100g), PH (7.24 mg/100g) and catehin in PH40 (11.83 mg/100g). The antioxidant activity of PH, LH, PH40 and LH40 was tested by measuring their ability to scavenge hydroxyl radicals (OH) by electron spin resonance spectroscopy (ESR). Honey samples with 40% dried apricot exhibited better antioxidant activity measured by hydroxyl radical scavenging activity. The EC50 values, the amount of antioxidant necessary to decrease the initial concentration of OH radicals by 50%, were: EC50PH=3.36 mg/ml, EC50LH=13.36 mg/ml, EC50PH40=2.29 mg/ml, EC50 LH40=7.78 mg/ml. Our results indicate that supplementation of polyfloral honey and linden honey with dried apricots improves antioxidant activity of honey by enriching the phenolic composition.

Keywords: honey, dried apricot, HPLC, hydroxyl radical

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Authors: Layan Moussa, Darine Salam, Samir Mustapha

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Heavy metal contamination in agricultural soils in Lebanon poses serious environmental and health problems. Intensive efforts are employed to improve existing quantification methods of heavy metals in contaminated environments since conventional detection techniques have shown to be time-consuming, tedious, and costly. The implication of hyperspectral remote sensing in this field is possible and promising. However, factors impacting the efficiency of hyperspectral imaging in detecting and quantifying heavy metals in agricultural soils were not thoroughly studied. This study proposes to assess the use of hyperspectral imaging for the detection of Ni in agricultural clay soil collected from the Bekaa Valley, a major agricultural area in Lebanon, under different contamination levels and soil moisture content. Soil samples were contaminated with Ni, with concentrations ranging from 150 mg/kg to 4000 mg/kg. On the other hand, soil with background contamination was subjected to increased moisture levels varying from 5 to 75%. Hyperspectral imaging was used to detect and quantify Ni contamination in the soil at different contamination levels and moisture content. IBM SPSS statistical software was used to develop models that predict the concentration of Ni and moisture content in agricultural soil. The models were constructed using linear regression algorithms. The spectral curves obtained reflected an inverse correlation between both Ni concentration and moisture content with respect to reflectance. On the other hand, the models developed resulted in high values of predicted R2 of 0.763 for Ni concentration and 0.854 for moisture content. Those predictions stated that Ni presence was well expressed near 2200 nm and that of moisture was at 1900 nm. The results from this study would allow us to define the potential of using the hyperspectral imaging (HSI) technique as a reliable and cost-effective alternative for heavy metal pollution detection in contaminated soils and soil moisture prediction.

Keywords: heavy metals, hyperspectral imaging, moisture content, soil contamination

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Authors: Sylvia Huang

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Contemporary Buddhist music has been emerged at the new forms of large-scale public Buddhist ritual ceremonies that may involve up to 10,000 participants at a time. Since 2007, the Buddha’s Birthday ceremony (Sanskrit, Vesak) by the Buddhist Tzu Chi Foundation has being held at major cities in Taiwan and many affiliated Tzu Chi offices around the world. Analysis of this modern and technologically-dependent ceremony sheds new light on the significance of music in contemporary Buddhist ritual, and also on recently enhanced and increasingly intimate connections between music and Buddhism. Through extensive ethnographic research of ten years (2007-2017), the research explores how the form of contemporary Buddhist music relates to the role of music in participants’ experience of the ritual and the way in which they construct meaning. The theoretical approach draws on both ethnomusicology and Buddhist teachings, Dharma. As soundscape is defined as the entire sonic energy produced by a landscape, the concept of soundscape is utilised to examine the contemporary ritual music in the Tzu Chi Vesak ceremony. The analysis opens new territory in exploring how analysis of Buddhist music can benefit from incorporating Buddhist philosophy within the methodological approach. Main findings are: 1) music becomes a method for Buddhist understanding through a focus in particular on how the ceremonial program is followed by music, and 2) participants engage with each other and entrain with music in the Vesak ceremony. As Buddhist sounding, such as scripture reading, liturgical chanting, and ceremonial music singing, is a sonic epistemological knowing of the conditions in which Buddhism is practiced, experienced, and transmigrated, the research concludes by showing that studies of Buddhist music have the potential to reveal distinctively Buddhist concepts, meaning, and values. Certain principles of Buddhist philosophy are adopted within ethnomusicological analysis to further enhance understandings of the crucial function of music within such a ritual context. Finally, the contemporary Buddhist music performance in the ceremony is possessed as a means of direct access to the spiritual experience in Buddhism.

Keywords: buddhist music, Taiwan, soundscape, Vesak ceremony

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Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: Sofia Ait Bouazza

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We consider the problem of finding a minimum identifying code in a graph. This problem was initially introduced in 1998 and has been since fundamentally connected to a wide range of applications (fault diagnosis, location detection …). Suppose we have a building into which we need to place fire alarms. Suppose each alarm is designed so that it can detect any fire that starts either in the room in which it is located or in any room that shares a doorway with the room. We want to detect any fire that may occur or use the alarms which are sounding to not only to not only detect any fire but be able to tell exactly where the fire is located in the building. For reasons of cost, we want to use as few alarms as necessary. The first problem involves finding a minimum domination set of a graph. If the alarms are three state alarms capable of distinguishing between a fire in the same room as the alarm and a fire in an adjacent room, we are trying to find a minimum locating domination set. If the alarms are two state alarms that can only sound if there is a fire somewhere nearby, we are looking for a differentiating domination set of a graph. These three areas are the subject of much active research; we primarily focus on the third problem. An identifying code of a graph G is a dominating set C such that every vertex x of G is distinguished from other vertices by the set of vertices in C that are at distance at most r≥1 from x. When only vertices out of the code are asked to be identified, we get the related concept of a locating dominating set. The problem of finding an identifying code (resp a locating dominating code) of minimum size is a NP-hard problem, even when the input graph belongs to a number of specific graph classes. Therefore, we study this problem in some restricted classes of undirected graphs like split graph, line graph and path in a directed graph. Then we present some results on the identifying code by giving an exact value of upper total locating domination and a total 2-identifying code in directed and undirected graph. Moreover we determine exact values of locating dominating code and edge identifying code of thin headless spider and locating dominating code of complete suns.

Keywords: identiying codes, locating dominating set, split graphs, thin headless spider

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Authors: Lemi Tolu

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Background: Postpartum family planning (PPFP) focuses on the prevention of unintended and closely spaced pregnancies through the first 12 months following childbirth. Objective: This study assesses the barriers to uptake of long-term and permanent family planning methods among immediate post-partum mothers at Saint Paul’s Hospital Millennium Medical College in Addis Ababa, Ethiopia. Methodology: An institution-based cross-sectional study was conducted from January 1 to June 30, 2017. The six months of study were used as strata, and systematic sampling used to select participants in each month. Post-partum mothers were interviewed using pretested structured questionnaires. Data entry and analysis were done using SPSS version 17. Bivariate and multivariable logistic regressions were fitted to identify determinants of post-partum family planning uptake. An OR with 95% CIs was calculated, and p values set at 005 were used to determine the statistical significance of associations. Results: Four hundred and twenty-two post-partum women were interviewed. Two hundred sixty-eight (63%) women received counselling on family planning, and 241 (66.8 %) got information about contraception. One hundred and fifty-two (45%) of the women accepted long-term and permanent contraception on their immediate postpartum period before discharge. Contraceptive counselling (OR = 2.13, 95% CI 1.004-3.331), getting information from the health facility (OR = 15.15, 95% CI 1.848-19.242), and partner support (OR = 1.367, 95% CI 1.175-2.771) were significantly associated with long-term and permanent contraception uptake. Conclusion: Postpartum counselling on family planning and provision of contraception information improve immediate postpartum FP acceptance, and, hence postpartum programs need to strengthen such services.

Keywords: contraception, immediate postpartum, long-term family planning, post-partum family planning

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Authors: Ya'u Muhammad, Umar Umar A. Mallammadori, Dahiru Mansur

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Effect of kaempferol on haematological parameters in two weeks old broiler chickens with experimental Eimeria tenella infection was evaluated in this study. Sixty-day old broilers were randomly allotted into six groups (I-VI) of ten broilers each and brooded for two weeks with commercial broiler feed (vital feed®) and provided water ad libitum. At two weeks of age broilers in group 1 were neither infected nor treated. Broilers in groups II-VI were infected with Eimeria tenella sporulated oocyst (104/ml) via oral inoculation. After infection was established, broilers in groups II-IV were treated orally with 1 mg/kg, 1.5 mg/kg, and 2 mg/kg of kaempferol, respectively. Broilers in group V were treated for five days with amprolium, 1.25 g/L in drinking water. Broilers in group VI were administered normal saline, 5 ml/kg per os for five days. Five days post infection; all broilers were sacrificed by severing their jugular veins. Blood sample from each bird was collected in EDTA container for haematology. Caecal contents were harvested and used to determine the lesion score and caecal Oocyst count respectively. Data obtained was analyzed using pad prism version 5.0. Mean Packed Cell Volume (PCV), haemoglobin (Hb) concentration, and Red Blood Cell (RBC) count significantly (P < 0.05) increased in groups II, III, and IV in a dose dependent manner. Similarly, PCV, Hb concentration, and RBC count significantly (P < 0.05) increased in groups II, III, and IV when compared to VI. No significant (P > 0.05) difference in the mean values of PCV, Hb and RBC count were recorded between groups treated with kaempferol and group V. Caecal Oocyst counts and lesion scores reduced significantly (P < 0.05) in groups II, III, and IV in a dose dependent manner. It was therefore observed in this study that kaempferol improved haematological parameters and reduced Oocyst count as well as the lesion scores in broilers infected with Eimeria tenella.

Keywords: broilers, Eimeria tenella, kaempferol, lesion scores, oocyst count,

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Authors: M. N. Kadir, M. M. H. Oliver, T. Naher

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The study assesses the areal extent of riverine flood in the flood-prone area of Faridpur District of Bangladesh using hydrological model and Geographic Information System (GIS). In the context of preparing the inundation map, flood frequency analysis was carried out to assess flooding for different flood magnitudes. Flood inundation maps were prepared based on DEM, and discharge at the river using Delft-3D model. LANDSAT satellite images have been used to develop a land cover map in the study area. The land cover map was used for mapping of cropland area. By incorporating the inundation maps on the land cover map, agricultural damage was assessed. Present monetary values of crop damage were collected through field survey from actual flood of the study area. Two different inundation maps were produced from the model for the year 2000 and 2016. In the year 2000, the floods began in the month of July, whereas in the case of the year 2016 is started in August. Under both cases, most of the areas were found to have been flooded in the month of September followed by flood recession. In order to prepare the land cover maps, four categories of LCs were considered viz., cropland, water body, trees, and rivers. Among the 755791 acres area of Faridpur District, the croplands were categorized to be 334,589 acres, followed by water bodies (279900 acres), trees (101930 acres) and rivers 39372 (acres). Damage assessment data revealed that 40% of the total cropland area had been affected by the flood in the year 2000, whereas only 19% area was affected by the 2016 flood. The study concluded that September is the critical month for cropland protection since the highest flood is expected at this time of the year in Faridpur. The northwestern and the southwestern part of the district was categorized as most vulnerable to flooding.

Keywords: agricultural damage, Delft-3d, flood management, land cover map

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Authors: Mannar R. Maurya, Bhawna Uprety, Fernando Avecilla, Pedro Adão, J. Costa Pessoa

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The reaction of the tripodal tetradentate dibasic ligand 6,6'–(2–(pyridin–2–yl)ethylazanediyl)bis(methylene)bis(2,4–di–tert–butylphenol), H2L1 I, with [VIVO(acac)2] in CH3CN gives the VVO–complex, [VVO(acac)(L1)] 1. Crystallization of 1 in CH3CN at ~0 ºC, gives dark blue crystals of 1, while at room temperature it affords dark green crystals of [{VVO(L1)}2µ–O] 3. Upon prolonged treatment of 1 in MeOH [VVO(OMe)(MeOH)(L1)] 2 is obtained. All three complexes are analyzed by single–crystal X–ray diffraction, depicting distorted octahedral geometry around vanadium. In the reaction of H2L1 with VIVOSO4 partial hydrolysis of the tripodal ligand results in elimination of the pyridyl fragment of L1 and the formation of H[VVO2(L2)] 4, containing the ONO tridentate ligand 6,6'–azanediylbis(methylene)bis(2,4–di–tert–butylphenol), H2L2 II. Compound 4, which was not fully characterized, undergoes dimerization in acetone yielding the hydroxido–bridged [{VVO(L2)}2µ–(HO)2] 5, having distorted octahedral geometry around each vanadium. In contrast, from a solution of 4 in acetonitrile, the dinuclear compound [{VVO(L2)}2µ–O] 6 is obtained, with trigonal bipyramidal geometry around each vanadium. The methoxido complex 2 is successfully employed as a functional catechol–oxidase mimic in the oxidation of catechol to o–quinone under air. The process is confirmed to follow a Michaelis–Menten type kinetics with respect to catechol, the Vmax and KM values obtained being 7.66×10–6 M min -1 and 0.0557 M, respectively, and the turnover frequency is 0.0541 min–1. Complex 2 is also used as a catalyst precursor for the oxidative bromination of thymol in aqueous medium. The selectivity shows quite interesting trends, namely when not using excess of primary oxidizing agent, H2O2 the para mono–brominated product corresponds to ~93 % of the products and no dibromo derivative is formed.

Keywords: oxidovanadium (V) complexes, tripodal ligand, crystal structure, catechol oxidase mimetic activity

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Authors: Saâd Oukkass, Abderrahim Bouftou, Rachid Ouchn, L. Lebrun, Miloudi Hlaibi

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We invariably exist in a world steeped in colors, whether in our clothing, food, cosmetics, or even medications. However, most of the dyes we use pose significant problems, being both harmful to the environment and resistant to degradation. Among these dyes, methylene blue and acid yellow 61 stand out, commonly used to dye various materials such as cotton, wood, and silk. Fortunately, various methods have been developed to treat and remove these polluting dyes, among which membrane processes play a prominent role. These methods are praised for their low energy consumption, ease of operation, and their ability to achieve effective separation of components. Adsorption on activated carbon is also a widely employed technique, complementing the basic processes. It proves particularly effective in capturing and removing organic compounds from water due to its substantial specific surface area while retaining its properties unchanged. In the context of our study, we examined two crucial aspects. Firstly, we explored the possibility of selectively extracting methylene blue from a mixture containing another dye, acid yellow 61, using a polymer inclusion membrane (PIM) made of PVA. After characterizing the morphology and porosity of the membrane, we applied kinetic and thermodynamic models to determine the values of permeability (P), initial flux (J0), association constant (Kass), and apparent diffusion coefficient (D*). Subsequently, we measured activation parameters (activation energy (Ea), enthalpy (ΔH#ass), entropy (ΔS#)). Finally, we studied the effect of activated carbon on the processes carried out through the membrane, demonstrating a clear improvement. These results make the membrane developed in this study a potentially pivotal player in the field of membrane separation.

Keywords: dyes, methylene blue, membrane, activated carbon

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Authors: Laura Florez

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The construction industry is labour intensive, and the behaviour and management of workers have a direct impact on the performance of construction projects. One of the issues it currently faces is how to recruit and maintain its workers. Construction is known as an industry where workers face the problem of short employment durations, frequent layoffs, and periods of unemployment between jobs. These challenges not only creates pressures on the workers but also project managers have to constantly train new workers, face skills shortage, and uncertainty on the quality of the workers it will attract. To consider worker’s needs and project managers expectations, one practice that can be implemented is to schedule construction projects to maintain a stable workforce. This paper proposes a mixed integer programming (MIP) model to schedule projects with the objective of maximising social sustainability of construction projects, that is, maximise labour stability. Aside from the social objective, the model accounts for equipment and financial resources required by the projects during the construction phase. To illustrate how the solution strategy works, a construction programme comprised of ten projects is considered. The projects are scheduled to maximise labour stability while simultaneously minimising time and minimising cost. The tradeoff between the values in terms of time, cost, and labour stability allows project managers to consider their preferences and identify which solution best suits their needs. Additionally, the model determines the optimal starting times for each of the projects, working patterns for the workers, and labour costs. This model shows that construction projects can be scheduled to not only benefit the project manager, but also benefit current workers and help attract new workers to the industry. Due to its practicality, it can be a valuable tool to support decision making and assist construction stakeholders when developing schedules that include social sustainability factors.

Keywords: labour stability, mixed-integer programming (MIP), scheduling, workforce management

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Authors: Kgabo Pofu, Hintsa Araya, Dean Oelofse, Sonja Venter, Christian Du Plooy, Phatu Mashela

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Nematode resistance to the tropical root-knot (Meloidogyne species) nematodes is one of the most preferred nematode management strategies in development of smallholder resource-poor farming systems. Due to its pharmacological and ethnomedicinal applications, Artemisia annua is one of the underutilised crops that have attracted attention of policy-makers in rural agrarian development in South Africa. However, the successful introduction of this crop in smallholder resource-poor farming systems could be upset by the widespread aggressive Meloidogyne species, which have limited management options. The objective of this study therefore was to determine the degree of nematode resistance to the South African M. incognita and M. javanica population densities on A. annua seedlings. Uniform three-week-old seedlings in pots containing pasteurised growing medium under greenhouse conditions were inoculated using a series of eggs and second-stage juveniles of two Meloidogyne species in separate trials. At 56 days after inoculation, treatments were highly significant on reproductive factor (RF) for M. incognita and M. javanica on A. annua, contributing 87 and 89% in total treatment variation of the variables, respectively. At all levels of inoculation, RF values for M. incognita (0.17-0.79) and M. javanica (0.02-0.29) were below unity, without any noticeable root galls. Infection of A. annua by both Meloidogyne species had no significant effects on growth variables. In conclusion, A. annua seedlings are resistant to the South African M. incognita and M. javanica population densities and could therefore be explored further for use in smallholder resource-poor farming systems.

Keywords: ethnomedicial plants, medicinal plants, underutilised crops, plant parasitic nematodes

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Hasika Mith, Hassany Ly, Hengsim Phoung, Rathana Sovann, Pichmony Ek, Sokuntheary Theng

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Rice is one of the most important crops used in the production of ready-to-cook (RTC) products such as rice vermicelli, noodles, rice paper, Banh Kanh, wine, snacks, and desserts. Meanwhile, extrusion is the most creative food processing method used for developing products with improved nutritional, functional, and sensory properties. This method authorizes process control such as mixing, cooking, and product shaping. Therefore, the objectives of this study were to produce rice vermicelli using a twin screw extruder, and the cooking properties of extruded rice vermicelli were investigated. Response Surface Methodology (RSM) with Box-Behnken design was applied to optimize extrusion conditions in order to achieve the most desirable product characteristics. The feed moisture rate (30–35%), the barrel temperature (90–110°C), and the screw speed (200–400 rpm) all play a big role and have a significant impact on the water absorption index (WAI), cooking yield (CY), and cooking loss (CL) of extrudate rice vermicelli. Results showed that the WAI of the final extruded rice vermicelli ranged between 216.97% and 571.90%. The CY ranged from 147.94 to 203.19%, while the CL ranged from 8.55 to 25.54%. The findings indicated that at a low screw speed or low temperature, there are likely to be more unbroken polymer chains and more hydrophilic groups, which can bind more water and make WAI values higher. The extruded rice vermicelli's cooking yield value had altered considerably after processing under various conditions, proving that the screw speed had little effect on each extruded rice vermicelli's CY. The increase in barrel temperature tended to increase cooking yield and reduce cooking loss. In conclusion, the extrusion processing by a twin-screw extruder had a significant effect on the cooking quality of the rice vermicelli extrudate.

Keywords: cooking loss, cooking quality, cooking yield, extruded rice vermicelli, twin-screw extruder, water absorption index

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Authors: Newton Muhury, Armando A. Apan, Tek N. Marasani, Gebiaw T. Ayele

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The changing climate has degraded freshwater availability in Australia that influencing vegetation growth to a great extent. This study assessed the vegetation responses to groundwater using Terra’s moderate resolution imaging spectroradiometer (MODIS), Normalised Difference Vegetation Index (NDVI), and soil water content (SWC). A hydrological model, SWAT, has been set up in a southeast Australian river catchment for groundwater analysis. The model was calibrated and validated against monthly streamflow from 2001 to 2006 and 2007 to 2010, respectively. The SWAT simulated soil water content for 43 sub-basins and monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) were applied in the machine learning tool, Waikato Environment for Knowledge Analysis (WEKA), using two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The assessment shows that different types of vegetation response and soil water content vary in the dry and wet seasons. The WEKA model generated high positive relationships (r = 0.76, 0.73, and 0.81) between NDVI values of all vegetation in the sub-basins against soil water content (SWC), the groundwater flow (GW), and the combination of these two variables, respectively, during the dry season. However, these responses were reduced by 36.8% (r = 0.48) and 13.6% (r = 0.63) against GW and SWC, respectively, in the wet season. Although the rainfall pattern is highly variable in the study area, the summer rainfall is very effective for the growth of the grass vegetation type. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Abdul Salam Turkmani

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Clay of the northern Palmyra region is one of the most important raw materials used in the Syrian ceramics industry. This study is focused on the evaluation of various laboratory analyses such as chemical analysis (XRF), mineral X-ray diffraction analysis (XRD), differential thermal analysis (DTA), and semi-industrial tests carried out on samples collected on two representative locations of the upper Oligocene in AlMkamen valley (MK) and lower Miocene in AlZukara valley (ZR) of the northern part of Palmyra, Syria. Chemical results classify the (MK) and (ZR) clays as semi-plastic red clay slightly carbonate and (eliminate probable) illite-chlorite clays with a very fine particle size distribution. Content of SiO₂ between 46.28-57.66%, Al2O3 13.81-25.2%, Fe₂O₃ 3.47-11.58%, CaO 1.15-7.19%, Na₂O+K₂O varied between 3.34-3.71%. Based on clay chemical composition and iron and carbonate content, these deposits can be considered as red firing clays. Their mineralogical composition is mainly represented by illite, kaolinite and quartz, and accessories minerals such as calcite, feldspar, phillipsite, and goethite. The results of the DTA test confirm the presence of gypsum and quartz phases in (MK) clay. Ceramic testing shows good green and dry bending strength values, which varied between 9-14 kg/cm², at 1160°C to 1180°C. Water absorption moves from 14.6 % at 1120°C to 2.2% at 1180°C to 1.6% at 1200°C. Breaking load after firing changes from 400 to 590 kg/cm². At 1200°C (MK), clay reaches perfect vitrification. After firing, the color of the clay changes from orange-hazel to red-brown at 1180°C. Technological results confirmed the suitability of the studied clays to produce floor and wall ceramic tiles. Using one of the two types of clay into the ceramic body or both types together gave satisfactory industrial results.

Keywords: ceramic, clay, industry , Palmyra

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Authors: Anila Xhahysa, Migena Ceyhan, Neki Kuka, Klajdi Qoshi, Damiano Koxhaj

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The seismic event catalog has been updated in the framework of a bilateral project supported by the Central European Investment Fund and with the extensive support of Global Earthquake Model Foundation to update Albania's national seismic hazard model. The earthquake catalogue prepared within this project covers the Western Balkan area limited by 38.0° - 48°N, 12.5° - 24.5°E and includes 41,806 earthquakes that occurred in the region between 510 BC and 2022. Since the moment magnitude characterizes the earthquake size accurately and the selected ground motion prediction equations for the seismic hazard assessment employ this scale, it was chosen as the uniform magnitude scale for the catalogue. Therefore, proxy values of moment magnitude had to be obtained by using new magnitude conversion equations between the local and other magnitude types to this unified scale. The Global Centroid Moment Tensor Catalogue was considered the most authoritative for moderate to large earthquakes for moment magnitude reports; hence it was used as a reference for calibrating other sources. The best fit was observed when compared to some regional agencies, whereas, with reports of moment magnitudes from Italy, Greece and Turkey, differences were observed in all magnitude ranges. For teleseismic magnitudes, to account for the non-linearity of the relationships, we used the exponential model for the derivation of the regression equations. The obtained regressions for the surface wave magnitude and short-period body-wave magnitude show considerable differences with Global Earthquake Model regression curves, especially for low magnitude ranges. Moreover, a conversion relation was obtained between the local magnitude of Albania and the corresponding moment magnitude as reported by the global and regional agencies. As errors were present in both variables, the Deming regression was used.

Keywords: regression, seismic catalogue, local magnitude, tele-seismic magnitude, moment magnitude

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Authors: Mohammed Belalia Douma

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Interactive learning is considered as the most effective strategy of learning, it is an educational philosophy based on the learner's contribution and involvement mainly in classroom and how he interacts toward his small society “classroom”, and the level of his collaboration into challenge, discovering, games, participation, all these can be provided through the interactive learning, which aims to activate the learner's role in the operation of learning, which focuses on research and experimentation, and the learner's self-reliance in obtaining information, acquiring skills, and forming values and attitudes. Whereas not based on memorization only, but rather on developing thinking and the ability to solve problems, on teamwork and collaborative learning. With the exchange or roles - teacher to student- , when the student will be more active and performing operations more than the student under the interactive learning method; we might face a several issues dealing with class controlling management, noise, and stability of learning… etc. This research paper is observing the application of the interactive learning on reality “classroom” and answers several assumptions and analyzes the issues coming up of these strategies mainly: noise, class control…etc The research sample was about 150 student of the 3rd year primary school in “Chlef” district, Algeria, level: beginners in the range of age 08 to 10 years old . We provided a questionnaire of confidential fifteen questions and also analyzing the attitudes of learners during three months. it have witnessed as teachers a variety of strategies dealing with applying the interactive learning but with a different issues; time management, noise, uncontrolled classes, overcrowded classes. Finally, it summed up that although the active education is an inevitably effective method of teaching, however, there are drawbacks to this, in addition to the fact that not all theoretical strategies can be applied and we conclude with solutions of this case study.

Keywords: interactive learning, student, learners, strategies.

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Authors: Aicha Assal, El Mostapha Lotfi

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Rapid industrialization and population growth are currently the main causes of energy and environmental problems associated with wastewater treatment. Wastewater treatment plants (WWTPs) aim to treat wastewater before discharging it into the environment, but they are not yet capable of treating non-biodegradable contaminants such as heavy metals. Toxic heavy metals can disrupt biological processes in WWTPs. Consequently, it is crucial to combine additional physico-chemical treatments with WWTPs to ensure effective wastewater treatment. In this study, the authors examined the pretreatment process for urban wastewater generated by the El Jadida WWTP in order to assess its treatment efficiency. Various physicochemical and spatiotemporal parameters of the WWTP's raw and treated water were studied, including temperature, pH, conductivity, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), suspended solids (SS), total nitrogen, and total phosphorus. The results showed an improvement in treatment yields, with measured performance values of 77% for BOD5, 63% for COD, and 66% for TSS. However, spectroscopic analyses revealed persistent coloration in wastewater samples leaving the WWTP, as well as the presence of heavy metals such as Zn, cadmium, chromium, and cobalt, detected by inductively coupled plasma optical emission spectroscopy (ICP-OES). To remedy these staining problems and reduce the presence of heavy metals, a new low-cost, environmentally-friendly eggshell-based solution was proposed. This method eliminated most heavy metals such as cobalt, beryllium, silver, and copper and significantly reduced the amount of cadmium, lead, chromium, manganese, aluminium, and Zn. In addition, the bioadsorbent was able to decolorize wastewater by up to 84%. This adsorption process is, therefore, of great interest for ensuring the quality of wastewater and promoting its reuse in irrigation.

Keywords: WWTP, wastewater, heavy metals, decoloration, depollution, COD, BOD5

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Authors: Pabasara H. Gamage, Sisira K. Weliwegamage, Sameera R. Gunatilake, Hondamuni I. C De Silva, Parakrama Karunaratne

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Green diesel is an upcoming category of biofuels, which has more practical advantages than biodiesel. Production of green diesel involves production of hydrocarbons from various fatty acid sources. Though green diesel is chemically similar to fossil fuel hydrocarbons, it is more environmentally friendly. Decarboxylation of fatty acid sources is one of green diesel production methods and is less expensive and more energy efficient compared to hydrodeoxygenation. Free fatty acids (FFA), undergo decarboxylation readily than triglycerides. Waste coconut oil, which is a rich source of FFA, can be easily decarboxylated than other oils which have lower FFA contents. These free fatty acids can be converted to hydrocarbons by decarboxylation. Experiments were conducted to carry out decarboxylation of waste coconut oil in a high pressure hastealloy reactor (Toption Goup LTD), in the presence of soda lime and mixtures of soda lime and alumina. Acid value (AV) correlates to the amount of FFA available in a sample of oil. It can be shown that with the decreasing of AV, FFAs have converted to hydrocarbons. First, waste coconut oil was reacted with soda lime alone, at 150 °C, 200 °C, and 250 °C and 1.2 MPa pressure for 2 hours. AVs of products at different temperatures were compared. AV of products decreased with increasing temperature. Thereafter, different mixtures of soda lime and alumina (100% Soda lime, 1:1 soda lime and alumina and 100% alumina) were employed at temperatures 150 °C, 200 °C, and 250 °C and 1.2 MPa pressure. The lowest AV of 2.99±0.03 was obtained when 1:1 soda lime and alumina were employed at 250 °C. It can be concluded with respect to the AV that the amount of FFA decreased when decarboxylation temperature was increased. Soda lime:alumina 1:1 mixture showed the lowest AV among the compositions studied. These findings lead to formulate a method to successfully synthesize hydrocarbons by decarboxylating waste coconut oil in the presence of soda lime and alumina (1:1) at elevated tempertaures such as 250 °C.

Keywords: acid value, free fatty acids, green diesel, high pressure reactor, waste coconut oil

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Authors: Rozi Laskaraki, Argyris Karapetsas, Aikaterini Karapetsa

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This paper is focused on the efficacy of a rehabilitation program based on musical activities, implied to a group of school-aged dyslexic children. Objective: The purpose of this study was to investigate the efficacy of auditory training including musical exercises in children with developmental dyslexia (DD). Participants and Methods: 45 third-, and fourth-grade students with DD and a matched control group (n=45) were involved in this study. In the beginning, students participated in a clinical assessment, including both electrophysiological (i.e., event related potentials (ERPs) esp.P300 waveform) and neuropsychological tests, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Initial assessment’s results confirmed statistically significant lower performance for children with DD, compared to that of the typical readers. After clinical assessment, a subgroup of children with dyslexia was submitted to a music auditory training program, conducted in 45-minute training sessions, once a week, for twenty weeks. The program included structured and digitized musical activities involving pitch, rhythm, melody and tempo perception and discrimination as well as auditory sequencing. After the intervention period, children underwent a new recording of ERPs. Results: The electrophysiological results revealed that children had similar P300 latency values to that of the controls, after the remediation program; thus children overcame their deficits. Conclusion: The outcomes of the current study suggest that ERPs is a valid clinical tool in neuropsychological assessment settings and dyslexia can be ameliorated through music auditory training.

Keywords: dyslexia, event related potentials, learning disabilities, music, rehabilitation

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