Search results for: perceptual linear prediction (PLP’s)

Authors: Pouriya Darabiyan, Hadis Nazari, Kourosh Zarea, Saeed Ghanbari, Zeinab Raiesifar, Morteza Khafaie, Hanna Tuvesson

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Introduction Since the beginning of mobile phone addiction, alexithymia, depression, anxiety and stress have been stated as risk factors for Internet addiction, so this study was conducted with the aim of investigating the relationship between Alexithymia and Mobile phone addiction along with the mediating role of anxiety, stress and depression. Materials and methods In this descriptive-analytical and cross-sectional study in 2022, 412 students School of Nursing & Midwifery of Ahvaz Jundishapur University of Medical Sciences were included in the study using available sampling method. Data collection tools were: Demographic Information Questionnaire, Toronto Alexithymia Scale (TAS-20), Depression, Anxiety, Stress Scale (DASS-21) and Mobile Phone Addiction Index (MPAI). Frequency, Pearson correlation coefficient test and linear regression were used to describe and analyze the data. Also, structural equation models and path analysis method were used to investigate the direct and indirect effects as well as the total effect of each dimension of Alexithymia on Mobile phone addiction with the mediating role of stress, depression and anxiety. Statistical analysis was done by SPSS version 22 and Amos version 16 software. Results Alexithymia was a predictive factor for mobile phone addiction. Also, Alexithymia had a positive and significant effect on depression, anxiety and stress. Depression, anxiety and stress had a positive and significant effect on mobile phone addiction. Depression, anxiety and stress variables played the role of a relative mediating variable between Alexithymia and mobile phone addiction. Alexithymia through depression, anxiety and stress also has an indirect effect on Internet addiction. Conclusion Alexithymia is a predictive factor for mobile phone addiction; And the variables of depression, anxiety and stress play the role of a relative mediating variable between Alexithymia and mobile phone addiction.

Keywords: alexithymia, mobile phone, depression, anxiety, stress

Procedia PDF Downloads 99

Authors: Ravinder Kaur

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Introduction Global cerebrovascular reactivity (CVR) mapping is a promising clinical assessment for stress-testing the brain using physiological challenges, such as CO₂, to elicit changes in perfusion. It enables real-time assessment of cerebrovascular integrity and health. Conventional imaging approaches solely use steady-state parameters, like cerebral blood flow (CBF), to evaluate the integrity of the resting parenchyma and can erroneously show a healthy brain at rest, despite the underlying pathogenesis in the presence of cerebrovascular disease. Conversely, coupling CO₂ inhalation with phase-contrast MRI neuroimaging interrogates the capacity of the vasculature to respond to changes under stress. It shows promise in providing prognostic value as a novel health marker to measure neurovascular function in disease and to detect early brain vasculature dysfunction. Objective This exploratory study was established to:(a) quantify the CBF response to CO₂ in hypocapnia and hypercapnia,(b) evaluate disparities in CVR between internal carotid (ICA) and vertebral artery (VA), and (c) assess sex-specific variation in CVR. Methodology Phase-contrast MRI was employed to measure the cerebrovascular reactivity to CO₂ (±10 mmHg). The respiratory interventions were presented using the prospectively end-tidal targeting RespirActTM Gen3 system. Post-processing and statistical analysis were conducted. Results In 9 young, healthy subjects, the CBF increased from hypocapnia to hypercapnia in all vessels (4.21±0.76 to 7.20±1.83 mL/sec in ICA, 1.36±0.55 to 2.33±1.31 mL/sec in VA, p < 0.05). The CVR was quantitatively higher in ICA than VA (slope of linear regression: 0.23 vs. 0.07 mL/sec/mmHg, p < 0.05). No statistically significant effect was observed in CVR between male and female (0.25 vs 0.20 mL/sec/mmHg in ICA, 0.09 vs 0.11 mL/sec/mmHg in VA, p > 0.05). Conclusions The principal finding in this investigation validated the modulation of CBF by CO₂. Moreover, it has indicated that regional heterogeneity in hemodynamic response exists in the brain. This study provides scope to standardize the quantification of CVR prior to its clinical translation.

Keywords: cerebrovascular disease, neuroimaging, phase contrast MRI, cerebrovascular reactivity, carbon dioxide

Procedia PDF Downloads 149

Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

Procedia PDF Downloads 77

Authors: Jean De Dieu Ayabagabo, Paul A.Onjoro, Karubiu P. Migwi, Marie C. Dusingize

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This study investigated the effects of feed on milk yield and quality through feed monitoring and quality assessment, and the consequent enteric methane gas emissions from smallholder dairy farms in drier areas of Rwanda, using the Tier II approach for four seasons in three zones, namely; Mayaga and peripheral Bugesera (MPB), Eastern Savanna and Central Bugesera (ESCB), and Eastern plateau (EP). The study was carried out using 186 dairy cows with a mean live weight of 292 Kg in three communal cowsheds. The milk quality analysis was carried out on 418 samples. Methane emission was estimated using prediction equations. Data collected were subjected to ANOVA. The dry matter intake was lower (p<0.05) in the long dry season (7.24 Kg), with the ESCB zone having the highest value of 9.10 Kg, explained by the practice of crop-livestock integration agriculture in that zone. The Dry matter digestibility varied between seasons and zones, ranging from 52.5 to 56.4% for seasons and from 51.9 to 57.5% for zones. The daily protein supply was higher (p<0.05) in the long rain season with 969 g. The mean daily milk production of lactating cows was 5.6 L with a lower value (p<0.05) during the long dry season (4.76 L), and the MPB zone having the lowest value of 4.65 L. The yearly milk production per cow was 1179 L. The milk fat varied from 3.79 to 5.49% with a seasonal and zone variation. No variation was observed with milk protein. The seasonal daily methane emission varied from 150 g for the long dry season to 174 g for the long rain season (p<0.05). The rain season had the highest methane emission as it is associated with high forage intake. The mean emission factor was 59.4 Kg of methane/year. The present EFs were higher than the default IPPC value of 41 Kg from developing countries in African, the Middle East, and other tropical regions livestock EFs using Tier I approach due to the higher live weight in the current study. The methane emission per unit of milk production was lower in the EP zone (46.8 g/L) due to the feed efficiency observed in that zone. Farmers should use high-quality feeds to increase the milk yield and reduce the methane gas produced per unit of milk. For an accurate assessment of the methane produced from dairy farms, there is a need for the use of the Life Cycle Assessment approach that considers all the sources of emissions.

Keywords: footprint, forage, girinka, tier

Procedia PDF Downloads 205

Authors: Liliane Samara Ferreira Leite, Francys Kley Vieira Moreira, Luiz Henrique Capparelli Mattoso

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The increasing environmental concern regarding the plastic pollution worldwide has stimulated the development of low-cost biodegradable materials. Proteins are renewable feedstocks that could be used to produce biodegradable plastics. Gelatin, for example, is a cheap film-forming protein extracted from animal skin and connective tissues of Brazilian Livestock residues; thus it has a good potential in low-cost biodegradable plastic production. However, gelatin plastics are limited in terms of mechanical and barrier properties. Cellulose nanocrystals (CNC) are efficient nanofillers that have been used to extend physical properties of polymers. This work was aimed at evaluating the reinforcing efficiency of CNC on gelatin films. Specifically, we have employed the continuous casting as the processing method for obtaining the gelatin/CNC bionanocomposites. This required a first rheological study for assessing the effect of gelatin-CNC and CNC-CNC interactions on the colloidal state of the aqueous bionanocomposite formulations. CNC were isolated from eucalyptus pulp by sulfuric acid hydrolysis (65 wt%) at 55 °C for 30 min. Gelatin was solubilized in ultra-pure water at 85°C for 20 min and then mixed with glycerol at 20 wt.% and CNC at 0.5 wt%, 1.0 wt% and 2.5 wt%. Rotational measurements were performed to determine linear viscosity (η) of bionanocomposite solutions, which increased with increasing CNC content. At 2.5 wt% CNC, η increased by 118% regarding the neat gelatin solution, which was ascribed to percolation CNC network formation. Storage modulus (G’) and loss modulus (G″) further determined by oscillatory tests revealed that a gel-like behavior was dominant in the bionanocomposite solutions (G’ > G’’) over a broad range of temperature (20 – 85 °C), particularly at 2.5 wt% CNC. These results confirm effective interactions in the aqueous gelatin-CNC bionanocomposites that could substantially increase the physical properties of the gelatin plastics. Tensile tests are underway to confirm this hypothesis. The authors would like to thank the Fapesp (process n 2016/03080-3) for support.

Keywords: bionanocomposites, cellulose nanocrystals, gelatin, viscoelastic characterization

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Authors: Yen-Hui Chen, Terry Walker

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As the world experiences an energy crisis, investing in sustainable energy resources is a pressing mission for many countries. Microalgae-derived biodiesel has attracted intensive attention as an important biofuel, and microalgae Chlorella protothecoides lipid is recognized as a renewable source for microalgae-derived biodiesel production. Supercritical carbon dioxide (SC-CO₂) is a promising green solvent that may potentially substitute the use of organic solvents for lipid extraction; however, the efficiency of SC-CO₂ extraction may be affected by many variables, including temperature, pressure and extraction time individually or in combination. In this study, response surface methodology (RSM) was used to optimize the process parameters, including temperature, pressure and extraction time, on C. protothecoides lipid yield by SC-CO₂ extraction. A second order polynomial model provided a good fit (R-square value of 0.94) for the C. protothecoides lipid yield. The linear and quadratic terms of temperature, pressure and extraction time—as well as the interaction between temperature and pressure—showed significant effects on lipid yield during extraction. The optimal lipid yield from the model was predicted as the temperature of 59 °C, the pressure of 350.7 bar and the extraction time 2.8 hours. Under these conditions, the experimental lipid yield (25%) was close to the predicted value. The principal fatty acid methyl esters (FAME) of C. protothecoides lipid-derived biodiesel were oleic acid methyl ester (60.1%), linoleic acid methyl ester (18.6%) and palmitic acid methyl ester (11.4%), which made up more than 90% of the total FAMEs. In summary, this study indicated that RSM was useful to characterize the optimization the SC-CO₂ extraction process of C. protothecoides lipid yield, and the second-order polynomial model could be used for predicting and describing the lipid yield very well. In addition, C. protothecoides lipid, extracted by SC-CO₂, was suggested as a potential candidate for microalgae-derived biodiesel production.

Keywords: Chlorella protothecoides, microalgal lipids, response surface methodology, supercritical carbon dioxide extraction

Procedia PDF Downloads 444

Authors: Syed Hadi Hasan, Devendra Kumar Singh, Viyaj Kumar

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Cr (VI) is a known toxic heavy metal and has been considered as a priority pollutant in water. The effluent of various industries including electroplating, anodizing baths, leather tanning, steel industries and chromium based catalyst are the major source of Cr (VI) contamination in the aquatic environment. Cr (VI) show high mobility in the environment and can easily penetrate cell membrane of the living tissues to exert noxious effects. The Cr (VI) contamination in drinking water causes various hazardous health effects to the human health such as cancer, skin and stomach irritation or ulceration, dermatitis, damage to liver, kidney circulation and nerve tissue damage. Herein, an attempt has been done to develop an efficient adsorbent for the removal of Cr (VI) from water. For this purpose nanosorbent composed of polyvinyl alcohol functionalized graphene oxide (GO/PVA) was prepared. Thus, obtained GO/PVA was characterized through FTIR, XRD, SEM, and Raman Spectroscopy. As prepared nanosorbent of GO/PVA was utilized for the removal Cr (VI) in batch mode experiment. The process variables such as contact time, initial Cr (VI) concentration, pH, and temperature were optimized. The maximum 99.8 % removal of Cr (VI) was achieved at initial Cr (VI) concentration 60 mg/L, pH 2, temperature 35 °C and equilibrium was achieved within 50 min. The two widely used isotherm models viz. Langmuir and Freundlich were analyzed using linear correlation coefficient (R2) and it was found that Langmuir model gives best fit with high value of R2 for the data of present adsorption system which indicate the monolayer adsorption of Cr (VI) on the GO/PVA. Kinetic studies were also conducted using pseudo-first order and pseudo-second order models and it was observed that chemosorptive pseudo-second order model described the kinetics of current adsorption system in better way with high value of correlation coefficient. Thermodynamic studies were also conducted and results showed that the adsorption was spontaneous and endothermic in nature.

Keywords: adsorption, GO/PVA, isotherm, kinetics, nanosorbent, thermodynamics

Procedia PDF Downloads 389

Authors: Ibrahim M. Mehedi, Uzair Ansari, Ubaid M. Al-Saggaf, Abdulrahman H. Bajodah

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This paper presents a methodology for balancing a rotary inverted pendulum system using Robust Generalized Dynamic Inversion (RGDI) under influence of parametric variations and external disturbances. In GDI control, dynamic constraints are formulated in the form of asymptotically stable differential equation which encapsulates the control objectives. The constraint differential equations are based on the deviation function of the angular position and its rates from their reference values. The constraint dynamics are inverted using Moore-Penrose Generalized Inverse (MPGI) to realize the control expression. The GDI singularity problem is addressed by augmenting a dynamic scale factor in the interpretation of MPGI which guarantee asymptotically stable position tracking. An additional term based on Sliding Mode Control is appended within GDI control to make it robust against parametric variations, disturbances and tracking performance deterioration due to generalized inversion scaling. The stability of the closed loop system is ensured by using positive definite Lyapunov energy function that guarantees semi-global practically stable position tracking. Numerical simulations are conducted on the dynamic model of rotary inverted pendulum system to analyze the efficiency of proposed RGDI control law. The comparative study is also presented, in which the performance of RGDI control is compared with Linear Quadratic Regulator (LQR) and is verified through experiments. Numerical simulations and real-time experiments demonstrate better tracking performance abilities and robustness features of RGDI control in the presence of parametric uncertainties and disturbances.

Keywords: generalized dynamic inversion, lyapunov stability, rotary inverted pendulum system, sliding mode control

Procedia PDF Downloads 172

Authors: Jubee Varghese, Pouria Hafiz

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Increased use of lightweight concrete in the construction industry is mainly due to its reduction in the weight of the structural elements, which in turn reduces the cost of production, transportation, and the overall project cost. However, the structural application of these lightweight concrete structures is limited due to its reduced density. Hence, further investigations are in progress to study the effect of fiber inclusion in improving the mechanical properties of lightweight concrete. Incorporating structural steel fibers, in general, enhances the performance of concrete and increases its durability by minimizing its potential to cracking and providing crack arresting mechanism. In this research, Geometric and Materially Non-linear Analysis (GMNA) was conducted for Finite Element Modelling using a software known as ABAQUS, to investigate the structural behavior of lightweight concrete with and without the addition of steel fibers and shear reinforcement. 21 finite element models of beams were created to study the effect of steel fibers based on three main parameters; fiber volume fraction (Vf = 0, 0.5 and 0.75%), shear span to depth ratio (a/d of 2, 3 and 4) and ratio of area of shear stirrups to spacing (As/s of 0.7, 1 and 1.6). The models created were validated with the previous experiment conducted by H.K. Kang et al. in 2011. It was seen that the lightweight fiber reinforcement can replace the use of fiber reinforced normal weight concrete as structural elements. The effect of an increase in steel fiber volume fraction is dominant for beams with higher shear span to depth ratio than for lower ratios. The effect of stirrups in the presence of fibers was very negligible; however; it provided extra confinement to the cracks by reducing the crack propagation and extra shear resistance than when compared to beams with no stirrups.

Keywords: ABAQUS, beams, fiber-reinforced concrete, finite element, light weight, shear span-depth ratio, steel fibers, steel-fiber volume fraction

Procedia PDF Downloads 107

Authors: Gloria Patricia Manurung

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Jakarta Bus Rapid Transit (BRT) system which was established in 2009 to reduce private vehicle usage and ease the rush hour gridlock throughout the Jakarta Greater area, has failed to achieve its purpose. With gradually increasing the number of private vehicles ownership and reduced road space by the BRT lane construction, private vehicle users intuitively invade the exclusive lane of BRT, creating local traffic along the BRT network. Invaded BRT lanes costs become the same with the road network, making BRT which is supposed to be the main public transportation in the city becoming unreliable. Efforts to guard critical lanes with preventing the invasion by allocating traffic agents at several intersections have been expended, lead to the improving congestion level along the lane. Given a set of number of traffic agents, this study uses an analytical approach to finding the best deployment strategy of traffic agent on a simplified Jakarta road network in minimizing the BRT link cost which is expected to lead to the improvement of BRT system time reliability. User-equilibrium model of traffic assignment is used to reproduce the origin-destination demand flow on the network and the optimum solution conventionally can be obtained with brute force algorithm. This method’s main constraint is that traffic assignment simulation time escalates exponentially with the increase of set of agent’s number and network size. Our proposed metaheuristic and heuristic algorithms perform linear simulation time increase and result in minimized BRT cost approaching to brute force algorithm optimization. Further analysis of the overall network link cost should be performed to see the impact of traffic agent deployment to the network system.

Keywords: traffic assignment, user equilibrium, greedy algorithm, optimization

Procedia PDF Downloads 229

Authors: Alina Fedossova, Jose Jorge Sierra Molina

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SIP problems are part of non-classical optimization. There are problems in which the number of variables is finite, and the number of constraints is infinite. These are semi-infinite programming problems. Most algorithms for semi-infinite programming problems reduce the semi-infinite problem to a finite one and solve it by classical methods of linear or nonlinear programming. Typically, any of the constraints or the objective function is nonlinear, so the problem often involves nonlinear programming. An investment portfolio is a set of instruments used to reach the specific purposes of investors. The risk of the entire portfolio may be less than the risks of individual investment of portfolio. For example, we could make an investment of M euros in N shares for a specified period. Let yi> 0, the return on money invested in stock i for each dollar since the end of the period (i = 1, ..., N). The logical goal here is to determine the amount xi to be invested in stock i, i = 1, ..., N, such that we maximize the period at the end of ytx value, where x = (x1, ..., xn) and y = (y1, ..., yn). For us the optimal portfolio means the best portfolio in the ratio "risk-return" to the investor portfolio that meets your goals and risk ways. Therefore, investment goals and risk appetite are the factors that influence the choice of appropriate portfolio of assets. The investment returns are uncertain. Thus we have a semi-infinite programming problem. We solve a semi-infinite optimization problem of portfolio selection using the outer approximations methods. This approach can be considered as a developed Eaves-Zangwill method applying the multi-start technique in all of the iterations for the search of relevant constraints' parameters. The stochastic outer approximations method, successfully applied previously for robotics problems, Chebyshev approximation problems, air pollution and others, is based on the optimal criteria of quasi-optimal functions. As a result we obtain mathematical model and the optimal investment portfolio when yields are not clear from the beginning. Finally, we apply this algorithm to a specific case of a Colombian bank.

Keywords: outer approximation methods, portfolio problem, semi-infinite programming, numerial solution

Procedia PDF Downloads 309

Authors: Japinder Wadhawan, Pradeep Rajan, Alok K. Saran, Navdeep S. Sidhu, Daanvir K. Dhir

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Currently, research focus in the development of agricultural equipment and tractor parts in India is innovation and use of alternate materials like austempered ductile iron (ADI). Three-point linkage mechanism of the tractor is susceptible to unpredictable load conditions in the field, and one of the critical components vulnerable to failure is lift arm. Conventionally, lift arm is manufactured either by forging or casting (SG Iron) and main objective of the present work is to reduce the failure occurrences in the lift arm, which is achieved by changing the manufacturing material, i.e ADI, without changing existing design. Effect of four pertinent variables of manufacturing ADI, viz. austenitizing temperature, austenitizing time, austempering temperature, austempering time, was investigated using Taguchi method for design of experiments. To analyze the effect of parameters on the mechanical properties, mean average and signal-to-noise (S/N) ratio was calculated based on the design of experiments with L9 orthogonal array and the linear graph. The best combination for achieving the desired mechanical properties of lift arm is austenitization at 860°C for 90 minutes and austempering at 350°C for 60 minutes. Results showed that the developed component is having 925 MPA tensile strength, 7.8 per cent elongation and 120 joules toughness making it more suitable material for lift arm manufacturing. The confirmatory experiment has been performed and found a good agreement between predicted and experimental value. Also, the CAD model of the existing design was developed in computer aided design software, and structural loading calculations were performed by a commercial finite element analysis package. An optimized shape of the lift arm has also been proposed resulting in light weight and cheaper product than the existing design, which can withstand the same loading conditions effectively.

Keywords: austempered ductile iron, design of experiment, finite element analysis, lift arm

Procedia PDF Downloads 233

Authors: Oluwaseun A. Oyetade, Roelof J. Kriek

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The development of effective catalysts for the oxygen evolution reaction (OER) is of great importance to combat energy-related concerns in the environment. Herein, we report a one-step solvothermal method employed for the fabrication of nickel selenide hybrids (NiSe-Ni₃Se₂) and a series of nickel selenide hybrid/multiwalled carbon nanotube composites (NiSe-Ni₃Se₂/MWCNT) as electrocatalysts for OER in alkaline media. The catalytic activities of these catalysts were investigated via several electrochemical characterization techniques, such as linear sweep voltammetry, chronoamperometric studies at constant potential, electrochemical surface area determination, and Tafel slope calculation, under alkaline conditions. Morphological observations demonstrated the agglomeration of non-uniform NiSe-Ni₃Se₂ microspheres around carbon nanotubes (CNTs), demonstrating the successful synthesis of NiSe-Ni₃Se₂/MWCNT nanocomposites. Among the tested electrocatalysts, the 20% NiSe-Ni₃Se₂/MWCNT nanocomposite demonstrated the highest activity, exhibiting an overpotential of 325 mV to achieve a current density of 10 mA.cm⁻² in 0.1 mol.dm⁻³ KOH solution. The NiSe-Ni₃Se₂/MWCNT nanocomposites showed improved activity toward OER compared to bare NiSe-Ni₃Se₂ hybrids and MWCNTs, exhibiting an overpotential of 528, 392 and 434 mV for 10%, 30% and 50% NiSe-Ni₃Se₂/MWCNT nanocomposites, respectively. These results compare favourably to the overpotential of noble catalysts, such as RuO₂ and IrO₂. Our results imply that the addition of MWCNTs increased the activity of NiSe-Ni₃Se₂ hybrids due to an increased number of catalytic sites, dispersion of NiSe-Ni₃Se₂ hybrid nanoparticles, and electronic conductivity of the nanocomposites. These nanocomposites also demonstrated better long-term stability compared to NiSe-Ni₃Se₂ hybrids and MWCNTs. Hence, NiSe-Ni₃Se₂/MWCNT nanocomposites possess the potential as effective electrocatalysts for OER in alkaline media.

Keywords: carbon nanotubes, electrocatalysts, nanocomposites, nickel selenide hybrids, oxygen evolution reaction

Procedia PDF Downloads 129

Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

Procedia PDF Downloads 122

Authors: Attef Kouadria, Yehya Bouteghrine, Amar Manaa, Tarek Mouats, Djalel Eddine Tria, Hamid Abdelhafid Ghouti

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Personal protection systems have been used in several forms for centuries. The need for light-weight composite structures has been in great demand due to their weight and high mechanical properties ratios in comparison to heavy and cumbersome steel plates. In this regard, lighter ceramic plates with a backing plate made of high strength polymeric fibers, mostly aramids, are widely used for protection against ballistic threats. This study aims to improve the ballistic performance of ceramic/composite plates subjected to ballistic impact by reducing the back face deformation (BFD) measured after each test. A new hybridization technique was developed in this investigation to increase the energy absorption capabilities of the backing plates. The hybridization consists of combining different types of aramid fabrics with different linear densities of aramid fibers (Dtex) and areal densities with an epoxy resin to form the backing plate. Therefore, several composite structures architectures were prepared and tested. For better understanding the effect of the hybridization, a serial of tensile, compression, and shear tests were conducted to determine the mechanical properties of the homogeneous composite materials prepared from different fabrics. It was found that the hybridization allows the backing plate to combine between the mechanical properties of the used fabrics. Aramid fabrics with higher Dtex were found to increase the mechanical strength of the backing plate, while those with lower Dtex found to enhance the lateral wave dispersion ratio due to their lower areal density. Therefore, the back face deformation was significantly reduced in comparison to a homogeneous composite plate.

Keywords: aramid fabric, ballistic impact, back face deformation, body armor, composite, mechanical testing

Procedia PDF Downloads 151

Authors: Amar F. Siddique

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The Guwahati city is one of the fastest growing cities of the north-eastern region of India, situated on the South Bank of the Brahmaputra River falls in the highest seismic zone level V. The city has witnessed many high magnitude earthquakes in the past decades. The Assam earthquake occurred on August 15, 1950, of moment magnitude 8.7 epicentered near Rima, Tibet was one of the major earthquakes which caused a serious structural damage and widespread soil liquefaction in and around the region. Hence the study of ground motion characteristics of Guwahati city is very essential. In this present work 1D equivalent linear ground response analysis (GRA) has been adopted using Deep soil software. The analysis has been done for two typical sites namely, Panbazar and Azara comprising total four boreholes location in Guwahati city of India. GRA of the sites is carried out by using an input motion recorded at Nongpoh station (recorded PGA 0.048g) and Nongstoin station (recorded PGA 0.047g) of 1997 Indo-Burma earthquake. In comparison to motion recorded at Nongpoh, different amplifications of bedrock peak ground acceleration (PGA) are obtained for all the boreholes by the motion recorded at Nongstoin station; although, the Fourier amplitude ratios (FAR) and fundamental frequencies remain almost same. The difference in recorded duration and frequency content of the two motions mainly influence the amplification of motions thus getting different surface PGA and amplification factor keeping a constant bedrock PGA. From the results of response spectra, it is found that at the period of less than 0.2 sec the ground motion recorded at Nongpoh station will give a high spectral acceleration (SA) on the structures than at Nongstoin station. Again for a period greater than 0.2 sec the ground motion recorded at Nongstoin station will give a high SA on the structures than at Nongpoh station.

Keywords: fourier amplitude ratio, ground response analysis, peak ground acceleration, spectral acceleration

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: ZhenlinJu, Christopher P. Vellano, RehanAkbani, Yiling Lu, Gordon B. Mills

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The epithelial–mesenchymal transition (EMT) is a process by which epithelial cells acquire mesenchymal characteristics, such as profound disruption of cell-cell junctions, loss of apical-basolateral polarity, and extensive reorganization of the actin cytoskeleton to induce cell motility and invasion. A hallmark of EMT is its capacity to promote metastasis, which is due in part to activation of several transcription factors and subsequent downregulation of E-cadherin. Unfortunately, current approaches have yet to uncover robust protein marker sets that can classify tumors as possessing strong EMT signatures. In this study, we utilize reverse phase protein array (RPPA) data and consensus clustering methods to successfully classify a subset of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tumors into an EMT protein signaling group (EMT group). The overall survival (OS) of patients in the EMT group is significantly worse than those in the other Hormone and PI3K/AKT signaling groups. In addition to a shrinkage and selection method for linear regression (LASSO), we applied training/test set and Monte Carlo resampling approaches to identify a set of protein markers that predicts the EMT status of CESC tumors. We fit a logistic model to these protein markers and developed a classifier, which was fixed in the training set and validated in the testing set. The classifier robustly predicted the EMT status of the testing set with an area under the curve (AUC) of 0.975 by Receiver Operating Characteristic (ROC) analysis. This method not only identifies a core set of proteins underlying an EMT signature in cervical cancer patients, but also provides a tool to examine protein predictors that drive molecular subtypes in other diseases.

Keywords: consensus clustering, TCGA CESC, Silhouette, Monte Carlo LASSO

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Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

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Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

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Authors: Anca Maria Cimpean, Serban Comsa

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Chick embryo chorioallantoic membrane (CAM) is a well vascularised in vivo experimental model used as a platform for testing the behavior of different implants inserted on it from tumor fragments to therapeutic agents or various biomaterials. Five types of collagen-based biomaterials with 2D and 3D structure (MotifMesh, Optimaix2D, Optimaix3D, Dual Layer Collagen and Xenoderm) were implanted on CAM and continuously evaluated by stereomicroscope for up to 5 days post-implant with an emphasis of their ability to requisite and develop new blood vessels (BVs) followed by microscopic analysis. MotifMEsh did not induce any angiogenic response lacking to be invaded by BVs from the CAM, but it induced intense inflammatory response necrosis and fibroblastic reaction around the implant. Optimaix2D has good adherence. CAM with minimal or no inflammatory reaction, a good integration of the CAM between the collagen mesh’s fibers, consistent adhesion of the cells to the collagen fibers,and a good ability to form pseudo-vascular channels filled with cells. Optimaix3D induced the highest angiogenic effects on CAM. The material shows good integration on CAM. The collagen fibers of the material show the ability to organize themselves into linear and tubular structures. It is possible to see blood elements, especially at the periphery of the implant. Dual-layer collagen behaves similar to Optimaix 3D, while Xenoderm induced a moderate angiogenic effect on CAM. Based on these data, we may conclude that collagen-based materials have variable ability to requisite and develop new blood vessels. A proper selection of collagen-based biomaterial scaffolds may crucially influence the acquisition and development of blood vessels during angiogenesis assays.

Keywords: chick embryo chorioallantoic membrane, collagen scaffolds, blood vessels, vascular microenvironment

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Authors: Kushaal Selvarajah, Geetha Annavi, Mohd Noor Hisham Mohd Nadzir

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Sambar deer (Rusa unicolor) was uplisted from Least Concern to Vulnerable by the International Union for Conservation of Nature Red list in 2015 due to drastic population decline in the wild throughout its geographical range. Sambar deer is a valued prey for the highly endangered species such as the Malayan tiger. Ex-situ conservation efforts, i.e., captive breeding, initiated by local government to boost sambar deer numbers in captivity and to reintroduce into the wild to support a higher number of tigers, consistent with the goal of our National Tiger Conservation Action Plan. The reproductive success of sambar deer and their welfare management practices in captivity are important components for effective captive breeding programs. However, there is a lack of study carried out on sambar deer in recent years and their behavior in captivity. Three captive sites (Zoo Negara, Zoo Taiping, and Sungkai Conservation Centre) were selected and observed for an average of 40 days each site (6 hours/day). A Generalized Linear Model (GLM) was used to determine the correlation between social behavior and extrinsic parameters. A comparison between all three captive sites showed the strongest correlation in behavioral variability, followed by a time of observation. This proves that there is a difference between in behavioral consistency and frequency between herds across captive sites rising to the possibility of external factors that are influential. Time of day of observation also had significant influence on certain extrinsic parameters being skewed to morning observations and this could be due to an adaptive behavior to the feeding time in the captive sites being in the morning which caused the deer to be resting towards the afternoon. Extensive study need to be done on sambar deer to pinpoint the specifics and better understanding of these possible influential factors in their behavior.

Keywords: behaviour ecology, captivity, ex-situ conservation, husbandry

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Authors: A. Sainvil, J. Mallela, L. M. Pereira

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Adolescents and young adults (AYA) diagnosed with cancer are tasked with managing their health through treatment, a time when reliance on and independence from parents may change in unexpected ways. Resilience allows patients to cope and manage their own health through treatment, promoting motivation and a healthier lifestyle. The film acts as a source of reflection through the cancer journey, which may have an impact on how patients cope. The current research investigated relationships between resilient linguistic qualities of the video narratives and attitudes toward personal health management. N=24 patients diagnosed between ages 11-18 were recruited. First, participants provided demographic information, then made a video testimonial about their cancer experience. After filming, participants then completed a questionnaire on the perceived benefits for themselves and others for making the video. Videos were transcribed and analyzed for thematic content via codebook and for linguistic qualities, indicating resilience with the use of the Linguistic Inquiry and Word Count Analysis Program (LIWC). Linear regressions were then calculated to explore relationships between resilient qualities, thematic content, and participants’ perceptions of their medical team and willingness to care for themselves. Participants who spoke with greater narrator connectedness were more likely to change their view of their medical team (β=.628 p=.034). When a participant believed that providers were likely to view their video, they were marginally more likely to want to take better care of themselves (β=.367, p=.078). Participants who spoke in depth about their health reported higher intention to take better care of themselves (β=.785, p=.033). AYAs with cancer who showcased certain resilient qualities within their narrative were more likely to consider taking better care of themselves. Additionally, the more patients reflected on their health, the more they wanted to take better care of themselves. These relationships were stronger when a patient believed that a provider would watch their video. Study findings highlight the utility of film in uncovering aspects of resilience and coping that may lead to healthier behaviors in AYAs with cancer.

Keywords: adolescents, cancer, resilience, health management

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Authors: Ka Ho Yau, Jan Frederick Engels, Kwok Kei Lai, Reinhard Renneberg

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Lateral flow test is a prevalent technology in various sectors such as food, pharmacology and biomedical sciences. Colloidal gold (CG) is widely used as the signalling molecule because of the ease of synthesis, bimolecular conjugation and its red colour due to intrinsic SPRE. However, the production of colloidal gold is costly and requires vigorous conditions. The stability of colloidal gold are easily affected by environmental factors such as pH, high salt content etc. Silica nanoparticles are well known for its ease of production and stability over a wide range of solvents. Using reverse micro-emulsion (w/o), silica nanoparticles with different sizes can be produced precisely by controlling the amount of water. By incorporating different water-soluble dyes, a rainbow colour of the silica nanoparticles could be produced. Conjugation with biomolecules such as antibodies can be achieved after surface modification of the silica nanoparticles with organosilane. The optimum amount of the antibodies to be labelled was determined by Bradford Assay. In this work, we have demonstrated the ability of the dye-doped silica nanoparticles as a signalling molecule in lateral flow test, which showed a semi-quantitative measurement of the analyte. The image was further analysed for the LOD=10 ng of the analyte. The working range and the linear range of the test were from 0 to 2.15μg/mL and from 0 to 1.07 μg/mL (R2=0.988) respectively. The performance of the tests was comparable to those using colloidal gold with the advantages of lower cost, enhanced stability and having a wide spectrum of colours. The positives lines can be imaged by naked eye or by using a mobile phone camera for a better quantification. Further research has been carried out in multicolour detection of different biomarkers simultaneously. The preliminary results were promising as there was little cross-reactivity being observed for an optimized system. This approach provides a platform for multicolour detection for a set of biomarkers that enhances the accuracy of diseases diagnostics.

Keywords: colorimetric detection, immunosensor, paper-based biosensor, silica

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Authors: Farah Naja, Nahla Hwalla, Leila Itani, Shirine Baalbaki, Abla Sibai, Lara Nasreddine

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Purpose: To propose an index for assessing adherence to a Middle-Eastern version of the Mediterranean diet as represented by the traditional Lebanese Mediterranean diet (LMD), to evaluate the association between the LMD and selected European Mediterranean diets (EMD); to examine socio-demographic and lifestyle correlates of adherence to Mediterranean diet (MD) among Lebanese adults. Methods: Using nationally representative dietary intake data of Lebanese adults, an index to measure adherence to the LMD was derived. The choice of food groups used for calculating the LMD score was based on results of previous factor analyses conducted on the same dataset. These food groups included fruits, vegetables, legumes, olive oil, burghol, dairy products, starchy vegetables, dried fruits, and eggs. Using Pearson’s correlation and scores tertiles distributions agreement, the derived LMD index was compared to previously published EMD indexes from Greece, Spain, Italy, France, and EPIC. Results: Fruits, vegetables and olive oil were common denominators to all MD scores. Food groups, specific to the LMD, included burghol and dried fruits. The LMD score significantly correlated with the EMD scores, while being closest to the Italian (r=0.57) and farthest from the French (r=0.21). Percent agreement between scores’ tertile distributions and Kappa statistics confirmed these findings. Multivariate linear regression showed that older age, higher educational, female gender, and healthy lifestyle characteristics were associated with increased adherence to all MD studied. Conclusion: A novel LMD index was proposed to characterize Mediterranean diet in Lebanon, complementing international efforts to characterize the MD and its association with disease risk.

Keywords: mediterranean diet, adherence, Middle-East, Lebanon, Europe

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Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

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This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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Authors: Arvan Prakash Ankitha, Madasamy Arockiasamy

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The increasing demand for adopting pile foundations in bridgeshas pointed towardsthe need to constantly improve the existing analytical techniques for better understanding of the behavior of such foundation systems. This study presents a simplistic approach using the energy-based method to assess the displacement responses of piles subjected to general loading conditions: Axial Load, Lateral Load, and a Bending Moment. The governing differential equations and the boundary conditions for a bridge pile embedded in multi-layered soil strata subjected to the general loading conditions are obtained using the Hamilton’s principle employing variational principles and minimization of energies. The soil non-linearity has been incorporated through simple constitutive relationships that account for degradation of soil moduli with increasing strain values.A simple power law based on published literature is used where the soil is assumed to be nonlinear-elastic and perfectly plastic. A Tresca yield surface is assumed to develop the soil stiffness variation with different strain levels that defines the non-linearity of the soil strata. This numerical technique has been applied to a pile foundation in a two - layered soil strata for a pier supporting the bridge and solved using the software MATLAB R2019a. The analysis yields the bridge pile displacements at any depth along the length of the pile. The results of the analysis are in good agreement with the published field data and the three-dimensional finite element analysis results performed using the software ANSYS 2019R3. The methodology can be extended to study the response of the multi-strata soil supporting group piles underneath the bridge piers.

Keywords: pile foundations, deep foundations, multilayer soil strata, energy based method

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Tarali Kalita, Karabi Dutta

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The North Eastern Region of India, with diverse climatic conditions and a wide range of ecological habitats, makes an ideal natural abode for a good number of silk-producing insects. Cocoon is the economically important life stage from where silk of economic importance is obtained. In recent years, silk-based biomaterials have gained considerable attention, which is dependent on the structure and properties of the silkworm cocoons as well as silk yarn. The present investigation deals with the morphological study of cocoons, including cocoon color, cocoon size, shell weight and shell ratio of eleven different species of silk insects collected from different regions of North East India. The Scanning Electron Microscopic study and X-ray photoelectron spectroscopy were performed to know the arrangement of silk threads in cocoons and the atomic elemental analysis, respectively. Further, collected cocoons were degummed and reeled/spun on a reeling machine or spinning wheel to know the filament length, linear density and tensile strength by using Universal Testing Machine. The study showed significant variation in terms of cocoon color, cocoon shape, cocoon weight and filament packaging. XPS analysis revealed the presence of elements (Mass %) C, N, O, Si and Ca in varying amounts. The wild cocoons showed the presence of Calcium oxalate crystals which makes the cocoons hard and needs further treatment to reel. In the present investigation, the highest percentage of strain (%) and toughness (g/den) were observed in Antheraea assamensis, which implies that the muga silk is a more compact packing of molecules. It is expected that this study will be the basis for further biomimetic studies to design and manufacture artificial fiber composites with novel morphologies and associated material properties.

Keywords: cocoon characterization, north-east India, prospects, silk characterization

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Authors: Sellidj Abdelaziz, Lebaili Soltane

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A cobalt-based alloy type Co-Cr-Ni-WC was deposited by plasma transferred arc projection (PTA) on a stainless steel valve. The alloy is characterized at the equilibrium by a solid solution Co (γ) mainly dendritic, and eutectic carbides M₇C₃ and ηM₆C. At the deposit/substrate interface, this microstructure is modified by the fast cooling mode of the alloy when applied in the liquid state on the relatively cold steel substrate. The structure formed in this case is heterogeneous and metastable phases can occur and evolve over temperature service. Coating properties and reliability are directly related to microstructures formed during deposition. We were interested more particularly in this microstructure formed during the solidification of the deposit in the region of the interface joining the soldered couple and its evolution during cyclic heat treatments at temperatures similar to those of the thermal environment of the valve. The characterization was carried out by SEM-EDS microprobe CAMECA, XRD, and micro hardness profiles. The deposit obtained has a linear and regular appearance that is free of cracks and with little porosity. The morphology of the microstructure represents solidification stages that are relatively fast with a temperature gradient high at the beginning of the interface by forming a plane front solid solution Co (γ). It gradually changes with the decreasing temperature gradient by getting farther from the junction towards the outer limit of the deposit. The matrix takes the forms: cellular, mixed (cells and dendrites) and dendritic. Dendritic growth is done according to primary ramifications in the direction of the heat removal which takes place in the direction perpendicular to the interface, towards the external surface of the deposit, following secondary and tertiary undeveloped arms. The eutectic carbides M₇C₃ and ηM₆C formed are very thin and are located in the intercellular and interdendritic spaces of the solid solution Co (γ).

Keywords: Co-Ni-Cr-W-C alloy, solid deposit, microstructure, carbides, cyclic heat treatment

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Authors: Emmanuel Abayomi Rotimi

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Context: Rabbits production plays important role in increasing animal protein supply in Nigeria. Rabbit production provides a cheap, affordable, and healthy source of meat. The growth of animals involves an increase in body weight, which can change the conformation of various parts of the body. Live weight and linear measurements are indicators of growth rate in rabbits and other farm animals. Aims: This study aimed to define the body dimensions of New Zealand rabbits and also to investigate the morphometric traits variables that contribute to body conformation by the use of principal component analysis (PCA). Methods: Data were obtained from 80 New Zealand rabbits (40 bucks and 40 does) raised in Livestock Teaching and Research Farm, Federal University Dutsinma. Data were taken on body weight (BWT), body length (BL), ear length (EL), tail length (TL), heart girth (HG) and abdominal circumference (AC). Data collected were subjected to multivariate analysis using SPSS 20.0 statistical package. Key results: The descriptive statistics showed that the mean BWT, BL, EL, TL, HG, and AC were 0.91kg, 27.34cm, 10.24cm, 8.35cm, 19.55cm and 21.30cm respectively. Sex showed significant (P<0.05) effect on all the variables examined, with higher values recorded for does. The phenotypic correlation coefficient values (r) between the morphometric traits were all positive and ranged from r = 0.406 (between EL and BL) to r = 0.909 (between AC and HG). HG is the most correlated with BWT (r = 0.786). The principal component analysis with variance maximizing orthogonal rotation was used to extract the components. Two principal components (PCs) from the factor analysis of morphometric traits explained about 80.42% of the total variance. PC1 accounted for 64.46% while PC2 accounted for 15.97% of the total variances. Three variables, representing body conformation, loaded highest in PC1. PC1 had the highest contribution (64.46%) to the total variance, and it is regarded as body conformation traits. Conclusions: This component could be used as selection criteria for improving body weight of rabbits.

Keywords: conformation, multicollinearity, multivariate, rabbits and principal component analysis

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