Investigation of Some Properties of Chemical Fertilizers Using Gamma-ray Spectrometry and Energy Dispersive X-ray Fluorescence Spectrometry

Instruments and Experimental Techniques - The purpose of this study is to investigate chemical fertilizers using gamma-ray spectrometry and energy dispersive X-ray fluorescence spectrometry...     

Development and validation of a liquid chromatographic-tandem mass spectrometric method for determination of eleven coccidiostats in milk

A reversed phase liquid chromatographic–tandem mass spectrometric method with simple solvent extraction and purification by solid phase extraction (SPE) has been developed for the determination of coccidiostats in milk. For sample preparation matrix solid phase dispersion, extraction by organic solvent and SPE with different cartridges were also tested. The compounds determined include lasalocid, narasin, salinomycin, monensin, semduramicin, maduramicin, robenidine, decoquinate, halofuginone, nicarbazin and diclazuril. Main steps of the method are addition of acetonitrile to the milk samples, centrifugation, removal of matrix by SPE, concentration by evaporation and LC–MS–MS determination. During a 15 min time segmented chromatographic run compounds are ionised either positively or negatively. Calculated recoveries range between 77.1% and 118.2%. Maximum levels are in the range of 1–20 μg/kg. The developed method was validated in line with the requirements of Commission Decision 2002/657/EC (2002). It is applicable for control of coccidiostat residues in milk as indicated in Regulation 124/2009/EC (2009).     

Pasting,Color, and Granular Properties of Starches From Local and Improved Cassava Varieties in High Rainfall Region of Nigeria

This study investigated the pasting, color, and granule properties of starches produced from 39 different cassava varieties (36 varieties resistant to cassava mosaic disease and three checks, TMS 30572, 4(2) 1425, and 82/00058) in two planting seasons at the experimental farm of the International Institute of Tropical Agriculture, Onne, Rivers State, Nigeria. Varieties screened showed significant seasonal differences (p?<?0.05) in all the properties over two harvesting seasons. The peak viscosity during heating ranged from 241.13 RVU to 485.21 RVU in year 1 and from 232.46RVU to 407.63RVU in year 2. Pasting time of the different starches ranged from 3.20–3.70 min in year 1 and from 3.6–4.2 min in year 2. Pasting temperature of the different starches ranged from 63.93–65.35 °C and from 73.15–77.15 °C in the years 1 and 2, respectively. Starch color intensity ranged from 85.05–94.49% in year 1 and from 90.27–92.96% in year 2. The structure of starches from cassava varieties was round in shape with granule size ranging from 12.50–22.50 μm in two years with varieties 97/0211 and 98/0510 as the smallest and variety 96/1632 as the largest. This study, therefore, showed that there were significant genotypic and seasonal variations in the pasting, color, and morphological properties of native starches from cassava.     

A comprehensive survey on optimizing deep learning models by metaheuristics

Deep neural networks (DNNs), which are extensions of artificial neural networks, can learn higher levels of feature hierarchy established by lower level features by transforming the raw feature space to another complex feature space. Although deep networks are successful in a wide range of problems in different fields, there are some issues affecting their overall performance such as selecting appropriate values for model parameters, deciding the optimal architecture and feature representation and determining optimal weight and bias values. Recently, metaheuristic algorithms have been proposed to automate these tasks. This survey gives brief information about common basic DNN architectures including convolutional neural networks, unsupervised pre-trained models, recurrent neural networks and recursive neural networks. We formulate the optimization problems in DNN design such as architecture optimization, hyper-parameter optimization, training and feature representation level optimization. The encoding schemes used in metaheuristics to represent the network architectures are categorized. The evolutionary and selection operators, and also speed-up methods are summarized, and the main approaches to validate the results of networks designed by metaheuristics are provided. Moreover, we group the studies on the metaheuristics for deep neural networks based on the problem type considered and present the datasets mostly used in the studies for the readers. We discuss about the pros and cons of utilizing metaheuristics in deep learning field and give some future directions for connecting the metaheuristics and deep learning. To the best of our knowledge, this is the most comprehensive survey about metaheuristics used in deep learning field.

     

Effect of Storage Conditions on the Quality Attributes of Shell (Table) Eggs

In tropical countries like Nigeria, egg preservation is a serious problem. The common practice is to store under ambient condition due to lack of refrigeration facilities and erratic power supply. Four crates of fresh table eggs were bought from the University of Agriculture, Makurdi farm and preliminary investigations of egg weights, Haugh unit, pH and yolk index were carried out before storage and found to be within standard. Thirty eggs were stored under ambient condition with and without application of oil respectively. The other group of thirty eggs was refrigerated. The initial weights were in the range of 60 – 69 g which reduced drastically. All other quality indices like the Haugh unit, the yolk index and pH declined drastically within the four weeks of the storage especially those that were stored under the ambient conditions. Those stored under refrigeration and those that were oiled and stored under ambient conditions (32 + 2 °C) maintained high quality standards in all the quality indices evaluated. The microbiological result also showed higher bacteria, yeast and mould count on those stored under ambient condition with the initial count of 5.0 × 10³ at first week and 2.8 × 10⁷ at the fourth week while the oiled and refrigerated eggs had values of 5.0 × 10³ at week zero and 7.2 × 10⁴ at week four of storage respectively. It is suggested that application of oil on eggs before storage can be practised to ensure retention of good quality eggs especially in the tropics and most developing nations of the world.     

Design and implementation of a low-cost multi-channel temperature measurement system for photovoltaic modules

An efficient and low-cost temperature logging system with a 16-channel input was developed for measurements of photovoltaic module temperature. This paper reports the principle of operation, design aspects, as well as the experimentation and performance of the simultaneous temperature measurement of 16 solar cells/modules. The system consists of a 16 channel multiplexer, a 12 bit A/D, a differential amplifier and NTC temperature sensors. The temperature range of the sensor is from −20 °C to 120 °C. The simplistic design requires no large internal memory to store data but incorporates a high degree of sensitivity and dynamic range (according to climate condition), thus the cost of the design remains low and makes it suitable for field applications. The system was successfully tested for the operating temperature of a 40-cell mono crystalline Si photovoltaic module under realistic outdoor conditions during a summer and a winter day. The temperature Instrumentation developed for avoidance of special interface card use enabled the successful collection of data from long distances with negligible level of noise.