Optimal Selling Prices for Small Sized Poultry Farmers

In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Choosing Local Organic Food: Consumer Motivations and Ethical Spaces

In recent years, the organic sector has increased significantly. However, with the ‘conventionalization’ of these products, it has been questioned whether these products have been losing their original vision. Accordingly, this research based on 31 phenomenological interviews with committed organic consumers in urban and rural areas of Portugal, aims to analyse how ethical motivations and ecological awareness are related to organic food consumption. The content thematic analysis highlights aspects related to society and environmental concerns. On an individual level, the importance of internal coherence, peace of mind and balance that these consumers find in the consumption of local organic products was stressed. For these consumers, local organic products consumption made for significant changes in their lives, aiding in the establishment of a green identity, and involves a certain philosophy of life. This vision of an organic lifestyle is grounded in a political and ecological perspective, beyond the usual organic definition, as a ‘post-organic era’. The paper contributes to better understand how an ideological environmental discourse allows highlighting the relationship between consumers’ environmental concerns and the politics of food, resulting in a possible transition to new sustainable consumption practices.

Resistance to Chloride Penetration of High Strength Self-Compacting Concretes: Pumice and Zeolite Effect

This paper aims to contribute to the characterization and the understanding of fresh state, compressive strength and chloride penetration tendency of high strength self-compacting concretes (HSSCCs) where Portland cement type II is partially substituted by 10% and 15% of natural pumice and zeolite. First, five concrete mixtures with a control mixture without any pozzolan are prepared and tested in both fresh and hardened states. Then, resistance to chloride penetration for all formulation is investigated in non-steady state and steady state by measurement of chloride penetration and diffusion coefficient. In non-steady state, the correlation between initial current and chloride penetration with diffusion coefficient is studied. Moreover, the relationship between diffusion coefficient in non-steady state and electrical resistivity is determined. The concentration of free chloride ions is also measured in steady state. Finally, chloride penetration for all formulation is studied in immersion and tidal condition. The result shows that, the resistance to chloride penetration for HSSCC in immersion and tidal condition increases by incorporating pumice and zeolite. However, concrete with zeolite displays a better resistance. This paper shows that the HSSCC with 15% pumice and 10% zeolite is suitable in fresh, hardened, and durability characteristics.

Resistance to Sulfuric Acid Attacks of Self-Consolidating Concrete: Effect Metakaolin and Various Cements Types

Due to their fluidity and simplicity of use, self-compacting concretes (SCCs) have undeniable advantages. In recent years, the role of metakaolin as a one of pozzolanic materials in concrete has been considered by researchers. It can modify various properties of concrete, due to high pozzolanic reactions and also makes a denser microstructure. The objective of this paper is to examine the influence of three type of Portland cement and metakaolin on fresh state, compressive strength and sulfuric acid attacks in self- consolidating concrete at early age up to 90 days of curing in lime water. Six concrete mixtures were prepared with three types of different cement as Portland cement type II, Portland Slag Cement (PSC), Pozzolanic Portland Cement (PPC) and 15% substitution of metakaolin by every cement. The results show that the metakaolin admixture increases the viscosity and the demand amount of superplasticizer. According to the compressive strength results, the highest value of compressive strength was achieved for PSC and without any metakaolin at age of 90 days. Conversely, the lowest level of compressive strength at all ages of conservation was obtained for PPC and containing 15% metakaolin. According to this study, the total substitution of PSC and PPC by Portland cement type II is beneficial to the increasing in the chemical resistance of the SCC with respect to the sulfuric acid attack. On the other hand, this increase is more noticeable by the use of 15% of metakaolin. Therefore, it can be concluded that metakaolin has a positive effect on the chemical resistance of SCC containing of Portland cement type II, PSC, and PPC.

Microstructure, Compressive Strength and Transport Properties of High Strength Self-Compacting Concretes Containing Natural Pumice and Zeolite

Due to the difficult placement and vibration between reinforcements of reinforced concrete and the defects that it may cause, the use of self-compacting concrete (SCC) is becoming more widespread. Ordinary Portland Cement (OPC) is the most widely used binder in the construction industry. However, the manufacture of this cement results in a significant amount of CO2 being released, which is detrimental to the environment. Thus, an alternative to reduce the cost of SCC is the use of more economical and environmental mineral additives in partial or total substitution of Portland cement. Our study is in this context and aims to develop SCCs both economic and ecological. Two natural pozzolans such as pumice and zeolite are chosen in this research. This research tries to answer questions including the microstructure of the two types of natural pozzolan and their influence on the mechanical properties as well as on the transport property of SCC. Based on the findings of this study, the studied zeolite is a clinoptilolite that presents higher pozzolan activity compared to pumice. However, the use of zeolite decreases the compressive strength of SCC composites. On the contrary, the compressive strength in SCC containing of pumice increases at both early and long term ages with a remarkable increase at long term. A correlation is obtained between the compressive strength with permeable pore and capillary absorption. Also, the results concerning compressive strength and transport property are well justified by evaporable and non-evaporable water content measurement. This paper shows that the substitution of Portland cement by 15% of pumice or 10% of zeolite in HSSCC is suitable in all aspects. 

UK GAAP and IFRS Standards: Similarities and Differences

This paper aimed to help researchers and international companies to the differences and similarities between IFRS (International financial reporting standards) and UK GAAP or UK accounting principles, and to the accounting changes between standard setting of the International Accounting Standards Board and the Accounting Standards Board in United Kingdom. We will use in this study statistical methods to calculate similarities and difference frequencies between the UK standards and IFRS standards, according to the PricewaterhouseCoopers report in 2005. We will use the one simple test to confirm or refuse our hypothesis. In conclusion, we found that the gap between UK GAAP and IFRS is small.

Study on the Impact of Size and Position of the Shear Field in Determining the Shear Modulus of Glulam Beam Using Photogrammetry Approach

The shear modulus of a timber beam can be determined using torsion test or shear field test method. The shear field test method is based on shear distortion measurement of the beam at the zone with the constant transverse load in the standardized four-point bending test. The current code of practice advises using two metallic arms act as an instrument to measure the diagonal displacement of the constructing square. The size and the position of the constructing square might influence the shear modulus determination. This study aimed to investigate the size and the position effect of the square in the shear field test method. A binocular stereo vision system has been employed to determine the 3D displacement of a grid of target points. Six glue laminated beams were produced and tested. Analysis of Variance (ANOVA) was performed on the acquired data to evaluate the significance of the size effect and the position effect of the square. The results have shown that the size of the square has a noticeable influence on the value of shear modulus, while, the position of the square within the area with the constant shear force does not affect the measured mean shear modulus.

A Close Study on the Nitrate Fertilizer Use and Environmental Pollution for Human Health in Iran

Nitrogen accumulates in soils during the process of fertilizer addition to promote the plant growth. When the organic matter decomposes, the form of available nitrogen produced is in the form of nitrate, which is highly mobile. The most significant health effect of nitrate ingestion is methemoglobinemia in infants under six months of age (blue baby syndrome). The mobile nutrients, like nitrate nitrogen, are not stored in the soil as the available forms for the long periods and in large amounts. It depends on the needs for the crops such as vegetables. On the other hand, the vegetables will compete actively for nitrate nitrogen as a mobile nutrient and water. The mobile nutrients must be shared. The fewer the plants, the larger this share is for each plant. Also, this nitrate nitrogen is poisonous for the people who use these vegetables. Nitrate is converted to nitrite by the existing bacteria in the stomach and the Gastro-Intestinal (GI) tract. When nitrite is entered into the blood cells, it converts the hemoglobin to methemoglobin, which causes the anoxemia and cyanosis. The increasing use of pesticides and chemical fertilizers, especially the fertilizers with nitrates compounds, which have been common for the increased production of agricultural crops, has caused the nitrate pollution in the (soil, water, and environment). They have caused a lot of damage to humans and animals. In this research, the nitrate accumulation in different kind of vegetables such as; green pepper, tomatoes, egg plants, watermelon, cucumber, and red pepper were observed in the suburbs of Mashhad, Neisabour, and Sabzevar cities. In some of these cities, the information forms of agronomical practices collected were such as; different vegetable crops fertilizer recommendations, varieties, pesticides, irrigation schedules, etc., which were filled out by some of our colleagues in the research areas mentioned above. Analysis of the samples was sent to the soil and water laboratory in our department in Mashhad. The final results from the chemical analysis of samples showed that the mean levels of nitrates from the samples of the fruit crops in the mentioned cities above were all lower than the critical levels. These fruit crop samples were in the order of: 35.91, 8.47, 24.81, 6.03, 46.43, 2.06 mg/kg dry matter, for the following crops such as; tomato, cucumber, eggplant, watermelon, green pepper, and red pepper. Even though, this study was conducted with limited samples and by considering the mean levels, the use of these crops from the nutritional point of view will not cause the poisoning of humans.

Soil Moisture Control System: A Product Development Approach

In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.

Mix Proportioning and Strength Prediction of High Performance Concrete Including Waste Using Artificial Neural Network

There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Sustainability Impact Assessment of Construction Ecology to Engineering Systems and Climate Change

Construction industry, as one of the main contributor in depletion of natural resources, influences climate change. This paper discusses incremental and evolutionary development of the proposed models for optimization of a life-cycle analysis to explicit strategy for evaluation systems. The main categories are virtually irresistible for introducing uncertainties, uptake composite structure model (CSM) as environmental management systems (EMSs) in a practice science of evaluation small and medium-sized enterprises (SMEs). The model simplified complex systems to reflect nature systems’ input, output and outcomes mode influence “framework measures” and give a maximum likelihood estimation of how elements are simulated over the composite structure. The traditional knowledge of modeling is based on physical dynamic and static patterns regarding parameters influence environment. It unified methods to demonstrate how construction systems ecology interrelated from management prospective in procedure reflects the effect of the effects of engineering systems to ecology as ultimately unified technologies in extensive range beyond constructions impact so as, - energy systems. Sustainability broadens socioeconomic parameters to practice science that meets recovery performance, engineering reflects the generic control of protective systems. When the environmental model employed properly, management decision process in governments or corporations could address policy for accomplishment strategic plans precisely. The management and engineering limitation focuses on autocatalytic control as a close cellular system to naturally balance anthropogenic insertions or aggregation structure systems to pound equilibrium as steady stable conditions. Thereby, construction systems ecology incorporates engineering and management scheme, as a midpoint stage between biotic and abiotic components to predict constructions impact. The later outcomes’ theory of environmental obligation suggests either a procedures of method or technique that is achieved in sustainability impact of construction system ecology (SICSE), as a relative mitigation measure of deviation control, ultimately.

Spin-Dependent Transport Signatures of Bound States: From Finger to Top Gates

Spin-orbit gap feature in energy dispersion of one-dimensional devices is revealed via strong spin-orbit interaction (SOI) effects under Zeeman field. We describe the utilization of a finger-gate or a top-gate to control the spin-dependent transport characteristics in the SOI-Zeeman influenced split-gate devices by means of a generalized spin-mixed propagation matrix method. For the finger-gate system, we find a bound state in continuum for incident electrons within the ultra-low energy regime. For the top-gate system, we observe more bound-state features in conductance associated with the formation of spin-associated hole-like or electron-like quasi-bound states around band thresholds, as well as hole bound states around the reverse point of the energy dispersion. We demonstrate that the spin-dependent transport behavior of a top-gate system is similar to that of a finger-gate system only if the top-gate length is less than the effective Fermi wavelength.

Improved Processing Speed for Text Watermarking Algorithm in Color Images

Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Prediction on Housing Price Based on Deep Learning

In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Voyage Analysis of a Marine Gas Turbine Engine Installed to Power and Propel an Ocean-Going Cruise Ship

A gas turbine-powered cruise Liner is scheduled to transport pilgrim passengers from Lagos-Nigeria to the Islamic port city of Jeddah in Saudi Arabia. Since the gas turbine is an air breathing machine, changes in the density and/or mass flow at the compressor inlet due to an encounter with variations in weather conditions induce negative effects on the performance of the power plant during the voyage. In practice, all deviations from the reference atmospheric conditions of 15 oC and 1.103 bar tend to affect the power output and other thermodynamic parameters of the gas turbine cycle. Therefore, this paper seeks to evaluate how a simple cycle marine gas turbine power plant would react under a variety of scenarios that may be encountered during a voyage as the ship sails across the Atlantic Ocean and the Mediterranean Sea before arriving at its designated port of discharge. It is also an assessment that focuses on the effect of varying aerodynamic and hydrodynamic conditions which deteriorate the efficient operation of the propulsion system due to an increase in resistance that results from some projected levels of the ship hull fouling. The investigated passenger ship is designed to run at a service speed of 22 knots and cover a distance of 5787 nautical miles. The performance evaluation consists of three separate voyages that cover a variety of weather conditions in winter, spring and summer seasons. Real-time daily temperatures and the sea states for the selected transit route were obtained and used to simulate the voyage under the aforementioned operating conditions. Changes in engine firing temperature, power output as well as the total fuel consumed per voyage including other performance variables were separately predicted under both calm and adverse weather conditions. The collated data were obtained online from the UK Meteorological Office as well as the UK Hydrographic Office websites, while adopting the Beaufort scale for determining the magnitude of sea waves resulting from rough weather situations. The simulation of the gas turbine performance and voyage analysis was effected through the use of an integrated Cranfield-University-developed computer code known as ‘Turbomatch’ and ‘Poseidon’. It is a project that is aimed at developing a method for predicting the off design behavior of the marine gas turbine when installed and operated as the main prime mover for both propulsion and powering of all other auxiliary services onboard a passenger cruise liner. Furthermore, it is a techno-economic and environmental assessment that seeks to enable the forecast of the marine gas turbine part and full load performance as it relates to the fuel requirement for a complete voyage.

Experimental Determination of Shear Strength Properties of Lightweight Expanded Clay Aggregates Using Direct Shear and Triaxial Tests

Artificial lightweight aggregates have a wide range of applications in industry and engineering. Nowadays, the usage of this material in geotechnical activities, especially as backfill in retaining walls has been growing due to the specific characteristics which make it a competent alternative to the conventional geotechnical materials. In practice, a material with lower weight but higher shear strength parameters would be ideal as backfill behind retaining walls because of the important roles that these parameters play in decreasing the overall active lateral earth pressure. In this study, two types of Light Expanded Clay Aggregates (LECA) produced in the Leca factory are investigated. LECA is made in a rotary kiln by heating natural clay at different temperatures up to 1200 °C making quasi-spherical aggregates with different sizes ranged from 0 to 25 mm. The loose bulk density of these aggregates is between 300 and 700 kN/m3. The purpose of this research is to determine the stress-strain behavior, shear strength parameters, and the energy absorption of LECA materials. Direct shear tests were conducted at five normal stresses of 25, 50, 75, 100, and 200 kPa. In addition, conventional triaxial compression tests were operated at confining pressures of 50, 100, and 200 kPa to examine stress-strain behavior. The experimental results show a high internal angle of friction and even a considerable amount of nominal cohesion despite the granular structure of LECA. These desirable properties along with the intrinsic low density of these aggregates make LECA as a very proper material in geotechnical applications. Furthermore, the results demonstrate that lightweight aggregates may have high energy absorption that is excellent alternative material in seismic isolations.

Application of ANN for Estimation of Power Demand of Villages in Sulaymaniyah Governorate

Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

The Supply Chain Management and Supply Chain Responsiveness in the Competitiveness of the Agrofood Sector: An Econometric Analysis

The purpose of this article is to conduct a theoretical and empirical study in order to analyze how the Supply Chain Management (SCM) and Supply Chain Responsiveness (SCR) affects the competitive advantage of the agrofood sector in 2017, in particular, the exporting companies of berries in Mexico. This work is presented in two parts, as a first part is developed a theoretical analysis of the main studies to measure the variables subject to the study. Subsequently an empirical study is carried out through field work and to process the data a logical econometric model is performed to be able to evaluate the effect of the SCM and SCR on the competitive advantage in the companies exporting berries. The results suggest that the SCM has a positive effect on the competitive advantage of the companies under study, so it is necessary to implement greater practices oriented towards a suitable SCM for the companies to achieve a competitive performance. In the case of SCR, it was found that this variable does not have effect on competitive advantage.

Analysis of Fertilizer Effect in the Tilapia Growth of Mozambique (Oreochromis mossambicus)

This paper analyses the effect of fertilizer (organic and inorganic) in the growth of tilapia. An experiment was implemented in the Aquapesca Company of Mozambique; there were considered four different treatments. Each type of fertilizer was applied in two of these treatments; a feed was supplied to the third treatment, and the fourth was taken as control. The weight and length of the tilapia were used as the growth parameters, and to measure the water quality, the physical-chemical parameters were registered. The results show that the weight and length were different for tilapias cultivated in different treatments. These differences were evidenced mainly by organic and feed treatments, where there was the largest and smallest value of these parameters, respectively. In order to prove that these differences were caused only by applied treatment without interference for the aquatic environment, a Fisher discriminant analysis was applied, which confirmed that the treatments were exposed to the same environment condition.

A Ground Structure Method to Minimize the Total Installed Cost of Steel Frame Structures

This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.