Life Cycle-Based Analysis of Meat Production: Ecosystem Impacts

Recently, meat production ecosystem impacts initiated many hot discussions and researchers, and it is a difficult implementation to reduce such impacts due to the demand of meat products. It calls for better management and control of ecosystem impacts from every aspects of meat production. This article analyzes the ecosystem impacts of meat production based on meat products life cycle. The analysis shows that considerable ecosystem impacts are caused by different meat production steps: initial establishment phase, animal raising, slaughterhouse processing, meat consumption, and wastes management. Based on this analysis, the impacts are summarized as: leading factor for biodiversity loss; water waste, land use waste and land degradation; greenhouse gases emissions; pollution to air, water, and soil; related major diseases. The article also provides a discussion on a solution-sustainable food system, which could help in reducing ecosystem impacts. The analysis method is based on the life cycle level, it provides a concept of the whole meat industry ecosystem impacts, and the analysis result could be useful to manage or control meat production ecosystem impacts from investor, producer and consumer sides.

A Semi-Implicit Phase Field Model for Droplet Evolution

A semi-implicit phase field method for droplet evolution is proposed. Using the phase field Cahn-Hilliard equation, we are able to track the interface in multiphase flow. The idea of a semi-implicit finite difference scheme is reviewed and employed to solve two nonlinear equations, including the Navier-Stokes and the Cahn-Hilliard equations. The use of a semi-implicit method allows us to have larger time steps compared to explicit schemes. The governing equations are coupled and then solved by a GMRES solver (generalized minimal residual method) using modified Gram-Schmidt orthogonalization. To show the validity of the method, we apply the method to the simulation of a rising droplet, a leaky dielectric drop and the coalescence of drops. The numerical solutions to the phase field model match well with existing solutions over a defined range of variables.

Comparing Test Equating by Item Response Theory and Raw Score Methods with Small Sample Sizes on a Study of the ARTé: Mecenas Learning Game

The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Technology Roadmapping in Defense Industry

The rapid progress of technology in today's competitive conditions has also accelerated companies' technology development activities. As a result, companies are paying more attention to R&D studies and are beginning to allocate a larger share to R&D projects. A more systematic, comprehensive, target-oriented implementation of R&D studies is crucial for the company to achieve successful results. As a consequence, Technology Roadmap (TRM) is gaining importance as a management tool. It has critical prospects for achieving medium and long term success as it contains decisions about past business, future plans, technological infrastructure. When studies on TRM are examined, projects to be placed on the roadmap are selected by many different methods. Generally preferred methods are based on multi-criteria decision making methods. Management of selected projects becomes an important point after the selection phase of the projects. At this stage, TRM are used. TRM can be created in many different ways so that each institution can prepare its own Technology Roadmap according to their strategic plan. Depending on the intended use, there can be TRM with different layers at different sizes. In the evaluation phase of the R&D projects and in the creation of the TRM, HAVELSAN, Turkey's largest defense company in the software field, carries out this process with great care and diligence. At the beginning, suggested R&D projects are evaluated by the Technology Management Board (TMB) of HAVELSAN in accordance with the company's resources, objectives, and targets. These projects are presented to the TMB periodically for evaluation within the framework of certain criteria by board members. After the necessary steps have been passed, the approved projects are added to the time-based TRM, which is composed of four layers as market, product, project and technology. The use of a four-layered roadmap provides a clearer understanding and visualization of company strategy and objectives. This study demonstrates the benefits of using TRM, four-layered Technology Roadmapping and the possibilities for the institutions in the defense industry.

Influences of Juice Extraction and Drying Methods on the Chemical Analysis of Lemon Peels

This study aimed to determine the influence of some different juice extraction methods (screw type hand operated juice extractor and pressed squeeze juice extractor) as well as drying methods (microwave, solar and oven drying) on the chemical properties of lemon peels. It could be concluded that extraction of juice by screw type and drying of peel using the microwave drying method were the best preparative processing steps methods for lemon peel utilization as food additives.

Computational Study of Blood Flow Analysis for Coronary Artery Disease

The aim of this study is to estimate the effect of blood flow through the coronary artery in human heart so as to assess the coronary artery disease.Velocity, wall shear stress (WSS), strain rate and wall pressure distribution are some of the important hemodynamic parameters that are non-invasively assessed with computational fluid dynamics (CFD). These parameters are used to identify the mechanical factors responsible for the plaque progression and/or rupture in left coronary arteries (LCA) in coronary arteries.The initial step for CFD simulations was the construction of a geometrical model of the LCA. Patient specific artery model is constructed using computed tomography (CT) scan data with the help of MIMICS Research 19.0. For CFD analysis ANSYS FLUENT-14.5 is used.Hemodynamic parameters were quantified and flow patterns were visualized both in the absence and presence of coronary plaques. The wall pressure continuously decreased towards distal segments and showed pressure drops in stenotic segments. Areas of high WSS and high flow velocities were found adjacent to plaques deposition.

A Numerical Description of a Fibre Reinforced Concrete Using a Genetic Algorithm

This work reports about an approach for an automatic adaptation of concrete formulations based on genetic algorithms (GA) to optimize a wide range of different fit-functions. In order to achieve the goal, a method was developed which provides a numerical description of a fibre reinforced concrete (FRC) mixture regarding the production technology and the property spectrum of the concrete. In a first step, the FRC mixture with seven fixed components was characterized by varying amounts of the components. For that purpose, ten concrete mixtures were prepared and tested. The testing procedure comprised flow spread, compressive and bending tensile strength. The analysis and approximation of the determined data was carried out by GAs. The aim was to obtain a closed mathematical expression which best describes the given seven-point cloud of FRC by applying a Gene Expression Programming with Free Coefficients (GEP-FC) strategy. The seven-parametric FRC-mixtures model which is generated according to this method correlated well with the measured data. The developed procedure can be used for concrete mixtures finding closed mathematical expressions, which are based on the measured data.

Evaluation of Negative Air Ions in Bioaerosol Removal: Indoor Concentration of Airborne Bacterial and Fungal in Residential Building in Qom City, Iran

The present investigation was conducted to detect the type and concentrations of bacterial and fungal bioaerosols in one room (bedroom) of each selected residential building located in different regions of Qom during February 2015 (n=9) to July 2016 (n=11). Moreover, we evaluated the efficiency of negative air ions (NAIs) in bioaerosol reduction in indoor air in residential buildings. In the first step, the mean concentrations of bacterial and fungal in nine sampling sites evaluated in winter were 744 and 579 colony forming units (CFU)/m3, while these values were 1628.6 and 231 CFU/m3 in the 11 sampling sites evaluated in summer, respectively. The most predominant genera between bacterial and fungal in all sampling sites were detected as Micrococcus spp. and Staphylococcus spp. and also, Aspergillus spp. and Penicillium spp., respectively. The 95% and 45% of sampling sites have bacterial and fungal concentrations over the recommended levels, respectively. In the removal step, we achieved a reduction with a range of 38% to 93% for bacterial genera and 25% to 100% for fungal genera by using NAIs. The results suggested that NAI is a highly effective, simple and efficient technique in reducing the bacterial and fungal concentration in the indoor air of residential buildings.

Synthesis, Physicochemical Characterization and Study of the Antimicrobial Activity of Chlorobutanol

Introduction and objectives: Chlorobutanol is a raw material, mainly used as an antiseptic and antimicrobial preservative in injectable and ophthalmic preparations. The main objective of our study was the synthesis and evaluation of the antimicrobial activity of chlorobutanol hemihydrates. Material and methods: Chlorobutanol was synthesized according to the nucleophilic addition reaction of chloroform to acetone, identified by an infrared absorption using Spectrum One FTIR spectrometer, melting point, Scanning electron microscopy and colorimetric reactions. The dosage of Carvedilol active substance was carried out by assaying the degradation products of chlorobutanol in a basic solution. The chlorobutanol obtained was subjected to bacteriological tests in order to study its antimicrobial activity. The antibacterial activity was evaluated against strains such as Escherichia coli (ATCC 25 922), Staphylococcus aureus (ATCC 25 923) and Pseudomonas aeroginosa (ATCC = American type culture collection). The antifungal activity was evaluated against human pathogenic fungal strains, such as Candida albicans and Aspergillus niger provided by the parasitology laboratory of the Hospital of Tizi-Ouzou, Algeria. Results and discussion: Chlorobutanol was obtained in an acceptable yield. The characterization tests of the product obtained showed a white and crystalline appearance (confirmed by scanning electron microscopy), solubilities (in water, ethanol and glycerol), and a melting temperature in accordance with the requirements of the European pharmacopoeia. The colorimetric reactions were directed towards the presence of a trihalogenated carbon and an alcohol function. The spectral identification (IR) showed the presence of characteristic chlorobutanol peaks and confirmed the structure of the latter. The microbiological study revealed an antimicrobial effect on all strains tested (Sataphylococcus aureus (MIC = 1250 µg/ml), E. coli (MIC = 1250 µg/ml), Pseudomonas aeroginosa (MIC = 1250 µg/ml), Candida albicans (MIC =2500 µg/ml), Aspergillus niger (MIC =2500 µg/ml)) with MIC values close to literature data. Conclusion: Thus, on the whole, the synthesized chlorobutanol satisfied the requirements of the European Pharmacopoeia, and possesses antibacterial and antifungal activity; nevertheless it is necessary to insist on the purification step of the product in order to eliminate the maximum impurities.

A Study on How Newlyweds Handle the Difference with Parents on Wedding Arrangements and Its Implication for Services in Hong Kong

This research examined the literature review of wedding preparation’s challenges and its developmental tasks of family transition under family life cycle. Five interviewees were invited to share their experiences on the differences with their parents in regard to wedding preparations and coping strategies. Some coping strategies and processes were highlighted for facilitating the family to achieve the developmental tasks during the wedding preparation. However, those coping strategies and processes may only act as the step and the behavior, while “concern towards parents” was found to be the essential element behind these behaviors. In addition to pre-marital counseling, a developmental group was suggested to develop under the framework of family life cycle and its related coping strategies on working with the newlyweds who encountered intergenerational differences in regard to their wedding preparations.

Analytical Comparison of Conventional Algorithms with Vedic Algorithm for Digital Multiplier

In today’s scenario, the complexity of digital signal processing (DSP) applications and various microcontroller architectures have been increasing to such an extent that the traditional approaches to multiplier design in most processors are becoming outdated for being comparatively slow. Modern processing applications require suitable pipelined approaches, and therefore, algorithms that are friendlier with pipelined architectures. Traditional algorithms like Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda architectures have been proven to be comparatively slow for pipelined architectures. These architectures, therefore, need to be optimized or combined with other architectures amongst them to enhance its performances and to be made suitable for pipelined hardware/architectures. Recently, Vedic algorithm mathematically has proven to be efficient by appearing to be less complex and with fewer steps for its output establishment and have assumed renewed importance. This paper describes and shows how the Vedic algorithm can be better suited for pipelined architectures and also can be combined with traditional architectures and algorithms for enhancing its ability even further. In this paper, we also established that for complex applications on DSP and other microcontroller architectures, using Vedic approach for multiplication proves to be the best available and efficient option.

Image Segmentation and Contour Recognition Based on Mathematical Morphology

In image segmentation contour detection is one of the important pre-processing steps in recent days. Contours characterize boundaries and contour detection is one of the most difficult tasks in image processing. Hence it is a problem of fundamental importance in image processing. Contour detection of an image decreases the volume of data considerably and useless information is removed, but the structural properties of the image remain same. In this research, a robust and effective contour detection technique has been proposed using mathematical morphology. Three different contour detection results are obtained by using morphological dilation and erosion. The comparative analyses of three different results also have been done.

Assessment of Drug Delivery Systems from Molecular Dynamic Perspective

In this study, we developed and simulated nano-drug delivery systems efficacy in compare to free drug prescription. Computational models can be utilized to accelerate experimental steps and control the experiments high cost. Molecular dynamics simulation (MDS), in particular NAMD was utilized to better understand the anti-cancer drug interaction with cell membrane model. Paclitaxel (PTX) and dipalmitoylphosphatidylcholine (DPPC) were selected for the drug molecule and as a natural phospholipid nanocarrier, respectively. This work focused on two important interaction parameters between molecules in terms of center of mass (COM) and van der Waals interaction energy. Furthermore, we compared the simulation results of the PTX interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane. The molecular dynamic analysis resulted in low energy between the nanocarrier and the cell membrane as well as significant decrease of COM amount in the nanocarrier and the cell membrane system during the interaction. Thus, the drug vehicle showed notably better interaction with the cell membrane in compared to free drug interaction with the cell membrane.

Effect of Assumptions of Normal Shock Location on the Design of Supersonic Ejectors for Refrigeration

The complex oblique shock phenomenon can be simply assumed as a normal shock at the constant area section to simulate a sharp pressure increase and velocity decrease in 1-D thermodynamic models. The assumed normal shock location is one of the greatest sources of error in ejector thermodynamic models. Most researchers consider an arbitrary location without justifying it. Our study compares the effect of normal shock place on ejector dimensions in 1-D models. To this aim, two different ejector experimental test benches, a constant area-mixing ejector (CAM) and a constant pressure-mixing (CPM) are considered, with different known geometries, operating conditions and working fluids (R245fa, R141b). In the first step, in order to evaluate the real value of the efficiencies in the different ejector parts and critical back pressure, a CFD model was built and validated by experimental data for two types of ejectors. These reference data are then used as input to the 1D model to calculate the lengths and the diameters of the ejectors. Afterwards, the design output geometry calculated by the 1D model is compared directly with the corresponding experimental geometry. It was found that there is a good agreement between the ejector dimensions obtained by the 1D model, for both CAM and CPM, with experimental ejector data. Furthermore, it is shown that normal shock place affects only the constant area length as it is proven that the inlet normal shock assumption results in more accurate length. Taking into account previous 1D models, the results suggest the use of the assumed normal shock location at the inlet of the constant area duct to design the supersonic ejectors.

Contribution to the Success of the Energy Audit in the Industrial Environment: A Case Study about Audit of Interior Lighting for an Industrial Site in Morocco

The energy audit is the essential initial step to ensure a good definition of energy control actions. The in-depth study of the various energy-consuming equipments makes it possible to determine the actions and investments with best cost for the company. The analysis focuses on the energy consumption of production equipment and utilities (lighting, heating, air conditioning, ventilation, transport). Successful implementation of this approach requires, however, to take into account a number of prerequisites. This paper proposes a number of useful recommendations concerning the energy audit in order to achieve better results, and a case study concerning the lighting audit of a Moroccan company by showing the gains that can be made through this audit.

Optimized Preprocessing for Accurate and Efficient Bioassay Prediction with Machine Learning Algorithms

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Coastal Resources Spatial Planning and Potential Oil Risk Analysis: Case Study of Misratah’s Coastal Resources, Libya

The goal of the Libyan Environmental General Authority (EGA) and National Oil Corporation (Department of Health, Safety & Environment) during the last 5 years has been to adopt a common approach to coastal and marine spatial planning. Protection and planning of the coastal zone is a significant for Libya, due to the length of coast and, the high rate of oil export, and spills’ potential negative impacts on coastal and marine habitats. Coastal resource scenarios constitute an important tool for exploring the long-term and short-term consequences of oil spill impact and available response options that would provide an integrated perspective on mitigation. To investigate that, this paper reviews the Misratah coastal parameters to present the physical and human controls and attributes of coastal habitats as the first step in understanding how they may be damaged by an oil spill. This paper also investigates costal resources, providing a better understanding of the resources and factors that impact the integrity of the ecosystem. Therefore, the study described the potential spatial distribution of oil spill risk and the coastal resources value, and also created spatial maps of coastal resources and their vulnerability to oil spills along the coast. This study proposes an analysis of coastal resources condition at a local level in the Misratah region of the Mediterranean Sea, considering the implementation of coastal and marine spatial planning over time as an indication of the will to manage urban development. Oil spill contamination analysis and their impact on the coastal resources depend on (1) oil spill sequence, (2) oil spill location, (3) oil spill movement near the coastal area. The resulting maps show natural, socio-economic activity, environmental resources along of the coast, and oil spill location. Moreover, the study provides significant geodatabase information which is required for coastal sensitivity index mapping and coastal management studies. The outcome of study provides the information necessary to set an Environmental Sensitivity Index (ESI) for the Misratah shoreline, which can be used for management of coastal resources and setting boundaries for each coastal sensitivity sectors, as well as to help planners measure the impact of oil spills on coastal resources. Geographic Information System (GIS) tools were used in order to store and illustrate the spatial convergence of existing socio-economic activities such as fishing, tourism, and the salt industry, and ecosystem components such as sea turtle nesting area, Sabkha habitats, and migratory birds feeding sites. These geodatabases help planners investigate the vulnerability of coastal resources to an oil spill.

Modeling of Microelectromechanical Systems Diaphragm Based Acoustic Sensor

Acoustic sensors are extensively used in recent days not only for sensing and condition monitoring applications but also for small scale energy harvesting applications to power wireless sensor networks (WSN) due to their inherent advantages. The natural frequency of the structure plays a major role in energy harvesting applications since the sensor key element has to operate at resonant frequency. In this paper, circular diaphragm based MEMS acoustic sensor is modelled by Lumped Element Model (LEM) and the natural frequency is compared with the simulated model using Finite Element Method (FEM) tool COMSOL Multiphysics. The sensor has the circular diaphragm of 3000 µm radius and thickness of 30 µm to withstand the high SPL (Sound Pressure Level) and also to withstand the various fabrication steps. A Piezoelectric ZnO layer of thickness of 1 µm sandwiched between two aluminium electrodes of thickness 0.5 µm and is coated on the diaphragm. Further, a channel with radius 3000 µm radius and length 270 µm is connected at the bottom of the diaphragm. The natural frequency of the structure by LEM method is approximately 16.6 kHz which is closely matching with that of simulated structure with suitable approximations.

Investigation on Mesh Sensitivity of a Transient Model for Nozzle Clogging

A transient model for nozzle clogging has been developed and successfully validated against a laboratory experiment. Key steps of clogging are considered: transport of particles by turbulent flow towards the nozzle wall; interactions between fluid flow and nozzle wall, and the adhesion of the particle on the wall; the growth of the clog layer and its interaction with the flow. The current paper is to investigate the mesh (size and type) sensitivity of the model in both two and three dimensions. It is found that the algorithm for clog growth alone excluding the flow effect is insensitive to the mesh type and size, but the calculation including flow becomes sensitive to the mesh quality. The use of 2D meshes leads to overestimation of the clog growth because the 3D nature of flow in the boundary layer cannot be properly solved by 2D calculation. 3D simulation with tetrahedron mesh can also lead to an error estimation of the clog growth. A mesh-independent result can be achieved with hexahedral mesh, or at least with triangular prism (inflation layer) for near-wall regions.

Fuzzy Logic and Control Strategies on a Sump

Sump can be defined as a reservoir which contains slurry; a mixture of solid and liquid or water, in it. Sump system is an unsteady process owing to the level response. Sump level shall be monitored carefully by using a good controller to avoid overflow. The current conventional controllers would not be able to solve problems with large time delay and nonlinearities, Fuzzy Logic controller is tested to prove its ability in solving the listed problems of slurry sump. Therefore, in order to justify the effectiveness and reliability of these controllers, simulation of the sump system was created by using MATLAB and the results were compared. According to the result obtained, instead of Proportional-Integral (PI) and Proportional-Integral and Derivative (PID), Fuzzy Logic controller showed the best result by offering quick response of 0.32 s for step input and 5 s for pulse generator, by producing small Integral Absolute Error (IAE) values that are 0.66 and 0.36 respectively.