Effect of feeding Lupin (Lupinusangustifolius) on carcass composition of Boer goat

This study was undertaken to measure the effects of different dietary treatments on carcass composition of Boer goats. The main protein source in the diet was Lupinusangustifolius and other ingredients were palm kernel expeller (PKE), soya bean meal, fish meal, wheat pollard, corn, molasses, crude palm oil, broken rice, and Brachariahumidicola hay. The protein level and energy level in all treatment diet was isocaloric and isonitrogenous (Crude Protein ~ 16.3% and Metabolizable Energy ~ 10.3MJ/kg). The Lupin composition in three treatment diets was 0%, 10% and 30%, respectively. Twenty four Boer goats, age 8-9 months old were used in this study which was divided into three equal groups. The adaptability period was 14 days and the feeding trial goes for 103 days. All goats were slaughtered according to Malaysian Halal Protocol 2009. The results revealed no significant differences (P<0.05) in the initial weight, final weight, weight gain, hot carcass weight, cold carcass weight and dressing percentage among the groups. There was also no significant difference on carcass composition: production of lean meat, and bone to fat ratio among the groups. Thus, this study showed that Lupin can be used as an alternative for protein source in goats reared in tropical condition and its performance in term of weight gain and carcass composition is as good as soybean meal

Structural, optical and magnetic properties of nanostructured Cr-substituted Ni-Zn spinel ferrites synthesized by a microwave combustion method

Nanoparticles of Cr3+-substituted Ni-Zn ferrites with a general formula Ni0.4Zn0.6-xCrxFe2O4 (x = 0.0 - 0.6) have been synthesized via a facile microwave combustion route. The crystalline phase has been characterized by XRD, TEM, FT-I and XPS revealing the spinel ferrite structure without extra phases. Crystallite sizes of 23 - 32 nm as estimated by XRD analyses, after corrections for crystal stains by Williamson-Hall method, are comparable to the average particle sizes observed by TEM which indicates successfully synthesized nanocrystals. Rietveld refinement analyses of the XRD patterns have inferred a monotonic decrease behavior of the lattice parameter with Cr doping in agreement with Vegard's law of solid solution series. Furthermore, cations distribution with an increased inversion factor indicate the B-site preference of Cr3+ ions. The oxidation states and cations distribution indicated by XPS results imply the Cr3+ doping on the account of Zn2+ ions and a partial reduction of Fe3+ to Fe2+ to keep the charge balance in a composition series of (Ni2+)0.4(Zn2+, Cr3+)0.6(Fe2+, Fe3+)2(O2-)4. The optical properties were explored by optical UV-Vis spectroscopy indicating allowed direct transitions with band gap energy that decreases from 3.9 eV to 3.7 eV with Cr doping. Furthermore, the photocatalytic activity for the degradation of methyl orange (MO) dye was investigated showing largely enhanced photodecomposition up to 30% of MO dye over Ni0.4Cr0.6Fe2O4 for 6 hours. A vibrating sample magnetometry (VSM) measurements at room temperature show further enhancement in the saturation magnetization of Ni0.4Zn0.6Fe2O4 , the highest in Ni-Zn ferrites, from about 60 to 70 emu/g with the increase of Cr concentration up to x = 0.1, while the coercivity shows a general increase in the whole range of Cr doping.Comment: 21 page, 9 figure

Characterization of Artificial Magnetic Conductor, Electromagnetic Band Gap and Frequency Selective Surface

This paper investigates the characteristics of Artificial Magnetic Conductor (AMC), Electromagnetic Band Gap (EBG) and Frequency Selective Surface (FSS) at 5.8 GHz. Reflection magnitude and phase are characterized both AMC and EBG meanwhile, the band gap is specially characterized by the EBG structure. Besides that, transmission and reflection coefficients are used to characterize the FSS structure. Three different flexible substrates are considered which are Fast Film, Arlon AD350 and Rogers RO3010. Then, angular stability is analyzed for each structure. In order to design AMC, EBG and FSS by using thin substrate, the highest dielectric constant is needed to develop a compact structure with the highest bandwidth. Later, AMC, EBG and FSS structures can be used to improve the radiation pattern apart from enhancing the realized gain of a low profile antenna such as dipole antenna

Pathological test type and chemical detection using deep neural networks:a case study using ELISA and LFA assays

Purpose: The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals have created a demand for intelligent systems with the least error-prone diagnosis results to be used by less medically trained persons and save clinical time. This paper aims at investigating the development of image-based colourimetric analysis. The purpose of recognising such tests is to support wider users to begin a colourimetric test to be used at homecare settings, telepathology and so on. Design/methodology/approach: The concept of an automatic colourimetric assay detection is delivered by utilising two cases. Training deep learning (DL) models on thousands of images of these tests using transfer learning, this paper (1) classifies the type of the assay and (2) classifies the colourimetric results. Findings: This paper demonstrated that the assay type can be recognised using DL techniques with 100% accuracy within a fraction of a second. Some of the advantages of the pre-trained model over the calibration-based approach are robustness, readiness and suitability to deploy for similar applications within a shorter period of time. Originality/value: To the best of the authors’ knowledge, this is the first attempt to provide colourimetric assay type classification (CATC) using DL. Humans are capable to learn thousands of visual classifications in their life. Object recognition may be a trivial task for humans, due to photometric and geometric variabilities along with the high degree of intra-class variabilities, it can be a challenging task for machines. However, transforming visual knowledge into machines, as proposed, can support non-experts to better manage their health and reduce some of the burdens on experts.</p