Miracle-dz/UniFAR-FTUs huggingface dataset:
The chemical composition and in vitro digestibility evaluation of almond tree ( Prunus dulcis D

The current study aimed to evaluate the chemical composition and in vitro digestibility of almond tree (Prunus dulcis D. A. Webb syn. Prunus amygdalus; var. Shokoufeh) leaves versus hulls, and green versus dry leaves as feed for ruminants. The fresh green almond hulls (GAH) and leaves (GAL) were harvested and spread under a shade to dry. Dry almond leaves (DAL) were collected from under the trees where as dry almond hulls (DAH) were collected 4 weeks after harvesting the fresh samples. The chemical composition of substrates was determined using standard approaches and the metabolisable energy (ME), in vitro dry matter (DMD) and in vitro organic matter (OMD) digestibility were measured using the in vitro gas production (GP) technique. The GAL contained 81 g crude protein (CP) kg DM while DAH contained 103 g CP kg DM. The CP was higher (P = 0.0003) in dry (leaves and hulls) than in green (leaves and hulls) samples. The ash content ranged from 99.2 to 181.5 g kg DM in DAH and DAL, respectively, (P = 0.0041). The ether extract content ranged from 27 for DAH to 65 g kg for DAL (P = 0.0018). The acid detergent fibre and neutral detergent fibre content ranged from 185 to 304 and 444 to 620 g kg DM (P = 0.04), for GAL and DAH, respectively. The DAH had the highest (P = 0.0001) GP24 and GP96. The DAH had the highest (P = 0.0001) potential GP (i.e., b), while the GP rate was highest for GAL and GAH (P = 0.034), ME was highest for DAH (P = 0.0001), and in vitro OMDwas highest for DAH (P = 0.0001). The highest DMD (P = 0.0001) values were obtained with DAH followed by GAL, DAL and GAH, respectively. It can be concluded that almond hulls and leaves have a good nutritional potential to cover the maintenance nutrient requirements of small ruminants. Almond hulls and leaves can also be used as supplement to low quality mature pasture and/or crop residues. However, more studies are warranted to better characterize these feeds in in vivo animal feeding trials. M. Y. Elahi H. Kargar M. S. Dindarlou Department of Animal Science, Faculty of Agriculture, University of Zabol, P.O. Box 98615-538, Zabol, Iran A. E. Kholif Dairy Science Department, National Research Centre, 33 Bohouth St. Dokki, Giza, Egypt M. M. Y. Elghandour A. Z. M. Salem (&) Faculty of Veterinary Medicine and Livestock, Autonomous University of the Mexico State, Toluca, Mexico e-mail: asalem70@yahoo.com S. Rojas-Hernández Unidad Académica de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Guerrero, Chilpancingo, Mexico N. E. Odongo Department of Animal Sciences, School of Agriculture, Pwani University, Kilifi, Kenya 123 Agroforest Syst (2017) 91:773–780 DOI 10.1007/s10457-016-9964-5 Author's personal copy
Case study Gamra : Simple meshing for complex earthquakes

The static offsets caused by earthquakes are well described by elastostatic models with a discontinuity in the displacement along the fault. A traditional approach to model this discontinuity is to align the numerical mesh with the fault and solve the equations using finite elements. However, this distorted mesh can be difficult to generate and update. We present a new numerical method, inspired by the Immersed Interface Method (Leveque and Li, 1994), for solving the elastostatic equations with embedded discontinuities. This method has been carefully designed so that it can be used on parallel machines on an adapted finite difference grid. We have implemented this method in Gamra, a new code for earth modeling. We demonstrate the correctness of the method with analytic tests, and we demonstrate its practical performance by solving a realistic earthquake model to extremely high precision. & 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The influence of residential desegregation on property prices in South Africa : The Pietersburg case study

Die opheffing van die Groepsgebiedewet in 1991 het gedurende die afgelope agt jaar 'n aansienlike verandering in die voormalige apartheidstede in Suid-Afrika help teweegbring. Die geskiedenis van Pietersburg, die hoofstad van die Noordelike Provinsie, het definitief die segregasieproses in daardie stad beïnvloed. Hierdie opname handel oor residensiële veranderinge in hierdie stad tussen Junie 1991 en Desember 1996. Die residensiële plasing van swart mense in die voorheen wit, kleurlingen Indiërgebiede in Pietersburg is gekarteer. Die opname toon dat die waarde van eiendomme in die middel en hoër ekonomiese status-buurte aanvanklik stabiel gebly het, maar na 1995, toe die persentasie swart huiseienaars in sommige gebiede tot 20% en selfs hoër gestyg het, het die pryse van eiendomme in hierdie buurte begin daal. 'n Resegregasieproses (sosiale hergroepering in hierdie woonbuurte) is ook besig om in hierdie stad na vore te tree.
Analysis of epidemiological models for disease control in single and multiple populations under resource constraints

Efficient management of epidemics is one of the primary motivations for computational modelling of disease dynamics. Examples range from reactive control measures, where the resources used to manage the epidemic in real time may be limited to prophylactic control measures such as deployment of genetically resistant plant varieties, which may lead to economic trade-offs. In such situations the question is how should resources for disease control be deployed to ensure the efficient management of the epidemic. Mathematical models are a powerful tool to investigate such questions since experiments are usually infeasible and the primary aim of this thesis is to study selected mathematical models of disease control to improve the current understanding of their behaviour. We initially analyse the dynamical behaviour that arises from incorporating an economic constraint into two simple, but widely used epidemic models with reactive control. Despite the selection of simple models, the addition of constrained control leads to mathematically rich dynamics, including the coexistence of multiple stable equilibria and stable limit cycles arising from global bifurcations. We use the analytical understanding obtained from the simple model to explore how to allocate a limited resource optimally between a number of separate populations that are exposed to an epidemic. Initially, we assume that the allocation is done at the beginning and cannot be changed later. We seek to answer the question of how the resource should be allocated efficiently to minimise the long-term number of infections. We show that the optimal allocation strategy can be approximated by a solution to a knapsack-type problem, that is the problem of how to select items of varying values and weights to maximise combined value without going over certain combined weight. The weights and values are given as functions of the population sizes, initial conditions, and the disease parameters. Later, we relax the assumptions to allow for reallocation and use the understanding of the dynamics gained from the simple models in the
Record linkage to enhance consented cohort and routinely collected health data from a UK birth cohort

Abstract Background In longitudinal health research, combining the richness of cohort data to the extensiveness of routine data opens up new possibilities, providing information not available from one data source alone. In this study, we set out to extend information from a longitudinal birth cohort study by linking to the cohort child’s routine primary and secondary health care data. The resulting linked datasets will be used to examine health outcomes and patterns of health service utilisation for a set of common childhood health problems. We describe the experiences and challenges of acquiring and linking electronic health records for participants in a national longitudinal study, the UK Millennium Cohort Study (MCS). Method Written parental consent to link routine health data to survey responses of the MCS cohort member, mother and her partner was obtained for 90.7% of respondents when interviews took place at age seven years in the MCS. Probabilistic and deterministic linkage was used to link MCS cohort members to multiple routinely-collected health data sources in Wales and Scotland. Results Overall linkage rates for the consented population using country-specific health service data sources were 97.6% for Scotland and 99.9% for Wales. Linkage rates between different health data sources ranged from 65.3% to 99.6%. Issues relating to acquisition and linkage of data sources are discussed. Conclusions Linking longitudinal cohort participants with routine data sources is becoming increasingly popular in population data research. Our results suggest that this is a valid method to enhance information held in both sources of data.
Difference Spectroscopic Method for the Estimation of Acebutolol Hydrochloride in Bulk and In its Formulation

A simple, precise and accurate difference spectroscopic method has been developed for the estimation of Acebutolol Hydrochloride in bulk drug form by difference spectrophotometric method. Acebutolol Hydrochloride has exhibited maximum absorbance at about 233nm and 234nm in acidic and basic solution respectively. Beer’s law was obeyed in the concentration range of 2-10 μg/ml in both the cases. The regression of coefficient was found to be r=0.9992. The LOD and LOQ value were found to be 0.2670ppm and 0.8091ppm respectively. The proposed method was successfully applied for the determination of Acebutolol Hydrochloride in bulk drug. As per ICH guidelines the result of the analysis were validated statistically and were found to be satisfactory.
Adaptive edge-based prediction for lossless image compression

ADAPTIVE EDGE-BASED PREDICTION FOR LOSSLESS IMAGE COMPRESSION by Rahul G. Parthe The increasing use of images in a variety of applications has heightened the need for methods to compress an image. Image compression is needed in efficient management of the two main resources in computing systems; space and communication time. Computer based data compression has been practiced for decades and image compression has been studied since the 70’s. Thus compression algorithms are slowly approaching their theoretical limit. Image data modeling in particular, is very difficult due to the higher order correlations that exist in natural continuous images. Though the established compression results are hard to surpass, there are some aspects that can be considered to achieve better performance. The gain might appear small, but still significant, especially when considered from the viewpoint of increasing image size of available images. In this work, we study two aspects of lossless compression where these improvements can be made. The research is focused on lossless image compression technique based on the traditional two-phase (prediction and encoding) method. Each module is studied separately and new techniques are suggested which lead to a better performance compared to other state-of-the-art technologies. In the prediction module, we propose two different edge-based prediction schemes. Edge Based Predictor (EBP) and Least-Squares Edge Based Predictor (LS-EBP) place emphasis on edges in the image and make predictions accordingly. EBP is a gradient based nonlinear adaptive predictor. It switches between different prediction-rules based on few threshold parameters determined by a pre-analysis procedure. The pre-analysis procedure makes a first pass on the image and automatically determines a set of parameters that are further used by the prediction scheme to improve their decision-making. The LS-EBP predictor also works in conjunction with the pre-analysis method, but optimizes the prediction for each pre-analysis assigned edge location. Unlike in traditional LS based methods, LS-EBP applies the least-square approach only at the edge points in the image. The result is an adaptive scheme with improved compression and a significant reduction in the overall computation. For the encoding module, a novel method is proposed for image residual error encoding. The Burrows Wheeler Transform (BWT) inspires this method. This method performs better than applying the BWT directly on the images. We also present a context based adaptive error modeling and encoding scheme. When coupled with the above-mentioned prediction schemes, the result is the best-known compression performance in the genre of compression schemes with same time and space complexity. Dedication I dedicate my thesis to my parents Ganpat Parthe Shakuntala Parthe
IS THE ROUTINE USE OF INTRAVENOUS UROGRAPHY STILL JUSTIFIED ? FINDINGS FROM A CROSS-SECTIONAL STUDY IN A REFERRAL HOSPITAL IN ADDIS ABABA

Introduction: Intravenous urography has been the imaging modality of choice for long due to its good spatial resolution and excellent anatomic details of the collecting system of the kidney. The introduction of cross-sectional imaging has challenged the use of intravenous urography as the modality to look for diseases of the collecting system of the kidney. Despite developments in imaging, intravenous urography is still useful in the work-up of some diseases of the collecting system, but ordered by physicians for lots of obsolete indications. Objective: This study was conducted to review the current use of Intravenous Urography by referring physicians. Methods: The study was a cross-sectional study with prospective data collection conducted at the Radiology Department of Tikur Anbessa Specialized Hospital. Data was collected for consecutive six years from 2009-2015 by using a structured questionnaire developed for the purposes of the study. All patients who were sent to the department for intravenous urography examination during the study period were included in the study. Results: The study involved 253 patients who were sent to the department of radiology for intravenous urographic study. Among these, 163 (64.6%) males and 90 (35.4%) female. The mean age for the study population was 31 (SD -17.1) years. The commonest indications for intravenous urography were renal stones (36.8%) and hydronephrosis (30.4%). Hematuria was an indication in five (2.0%) of the patients. Nearly a quarter of them (23.7%) had normal intravenous urography finding. Conclusion: Most of the indications for intravenous urography at Tikur Anbessa Specialized Hospital were unjustified and would have been avoided as they were particularly obsolete for pediatric patients. The indications for intravenous urography should adhere to international current standards.
Lysozyme – Alginate Nanocomplex : The Role of Alginate Composition

In the present work we investigated the electrostatic self-assembly of nanocomplexes (NCXs) made of lysozyme (Lyz) and different alginates (Alg A Mw ~4kD and M/G ~1.42 or Alg B Mw ~7kD and M/G~5.00) to establish a relationship between the alginate structure and both the physical (size and zeta potential, optical density) and the thermodynamic properties of the systems. It was found that the alginate rich in mannuronic unit (Alg B) had a greater binding stoichiometry and lower affinity than Alg A, a fact that correlated with a more extended structure that in turn affected the capacity to form hydrogen bonds associated with the differences in charge distribution. Both alginates show higher affinity and temperature stability than poly-acrylic acid (PAA), showing the importance of the polyasaccharide structure in the NCXs formation. For the first time we showed that the M/G ratio plays a role on the affinity of interaction of alginate and lysozyme. Finally, these NCXs seem promising systems for biomedical application due to their in vitro biocompatibility and macromolecules retention capacity.
Model Size Selection for Prototype-Based Classifiers using Large Geometric Margin Minimum Classification Error Training

where is a training sample, is a functional margin misclassification measure, and is a class model. Maximizing the geometric margin is shown to be effective in avoiding the over-training [2]. Utilizing this effect, the LGM-MCE training conducts the concurrent optimization, i.e., the minimization of classification error counts and the maximization of geometric margin values, aiming at the accurate classification of future samples.
Rewriting of Plain SO Tgds into Nested Tgds

Schema mappings express the relationships between sources in data interoperability scenarios and can be expressed in various formalisms. Source-to-target tuple-generating dependencies (s-t tgds) can be easily used for data transformation or query rewriting tasks. Second-order tgds (SO tgds) are more expressive as they can also represent the composition and inversion of s-t tgds. Yet, the expressive power of SO tgds comes with the problem of undecidability for some reasoning tasks. Nested tgds and plain SO tgds are mapping languages that are between s-t tgds and SO tgds in terms of expressivity, and their properties have been studied in the recent years. Nested tgds are less expressive than plain SO tgds, but the logical equivalence problem for nested tgds is decidable. However, a detailed characterization of plain SO tgds that have an equivalent nested tgd is missing. In this paper, we present an algorithmic solution for translating plain SO tgds into nested tgds. The algorithm computes one or more nested tgds, if a given plain SO tgd is rewritable. Furthermore, we are able to give a detailed characterization of those plain SO tgds for which an equivalent nested tgd exists, based on the structural properties of the source predicates and Skolem functions in the plain SO tgd. In the evaluation, we show that our algorithm covers a larger subset of plain SO tgds than previous approaches and that a rewriting can be computed efficiently although the algorithm has the exponential complexity.
Editing and Imputation in the context of data integration from multiple sources and mixed modes Editing and Imputing VAT Data for the Purpose of Producing Mixed-Source Turnover Estimates

1. Recently there has been a push for National Statistics Institutes to make greater use of administrative data in the production of business statistics. This should reduce burden on businesses and could lead to increased efficiency. In many cases, it is not possible to completely replace surveys with administrative data, so a mixed-source approach is required instead. The Office for National Statistics (ONS) is developing a method for producing mixed-source estimates for the Monthly Business Survey (MBS), based on a combination of Value Added Tax (VAT) Turnover data and a reduced survey.
Development of Electronic Learning Tools to Improve the Quality of Elementary Linear Algebra Course

The focus of the research is to develop a constructivist electronic teaching aids for Elementary Linear Algebra. The teaching aid is useful for learning using ACE cycle that consists of three components: activities, classroom discussion, and exercises. Developmental research design is choose for developing electronic teaching aids and for implementing the teaching aid, the experimental research design is selected. The research is conducted in two years focussing on producing valid, practical, and effective electronic teaching aids. The research activities are divided into two phases. Phase one aim at producing a valid prototype of teaching aids. For this purpose, need assessment, curriculum analysis, review of related literature, and designing the prototype of the teaching aids where done. The designed prototype was validated by two qualified Elementary Linear Algebra reviewers. The finding showed that the designed prototype fulfilled the criteria of content and construct validity. Phase two of the research was conducted at Mathematics Department of Universitas Negeri Padang. The aim of the second phase is to see the effectiveness of the designed prototype. Keywords—APOS theory, ACE cycle, constructivist
MapReduce based parallel data processing for drug-drug interaction prediction

Prediction of drug-drug interactions (DDIs) can prevent unexpected adverse drug events (ADEs). ADEs can damage people’s health and bring about economic losses to the society. Existing methods usually adopt the dataset of the adverse drug reports (ADRs) to build the DDI prediction statistical model; however, the ADRs dataset contains billions of records and the U. S. government releases new ADRs quarterly so that the data volume keeps growing. It is time consuming to clean these data and extract useful features from ADRs, which delay the development of effective DDIs prediction models. In this paper, a parallel processing framework based on MapReduce model is proposed. The MapReduce model is utilized to extract names and adverse reactions of drugs and count their frequencies based on ADRs, which can improve the efficiency of data cleaning and feature extraction of the Food and Drug Administration (FDA)'s adverse drug reports. The parallelization of the statistical screening and processing method of ADRs are implemented on the Hadoop cluster. Experimental results show the processing of FDA’s adverse drug reports can be achieved accurately by this method and the speed of processing can be improved effectively by using the proposed parallel computing framework.
Design and Analysis of Ku/K-band Circular SIW Patch Antenna using 3D EM-based Artificial Neural Networks

Substrate Integrated Waveguide (SIW) antennas are considered as main radiators for RF and microwave wireless systems due to their low profile, low cost and soft integration with the other devices. The gain of a SIW patch antenna may be enhanced using different techniques such as Artificial Neural Networks (ANN) by modifying the antenna’s geometry with high efficiency comparing to electromagnetic techniques that take more time. This paper describes a novel structure of a circular SIW patch antenna design using a tree-dimensional electromagnetic (3D-EM) simulation based on ANN model which is developed as an accurate tool for synthesizing the forward side and then analyzing the reverse side of the problem. In this work, ANN algorithms are used for training the samples to provide precise geometrical dimensions of the SIW patch antenna with high accuracy for the target requirements. The antenna is designed to operate in Ku and K frequency bands, resonate at 16.10 GHz and 19.81 GHz respectively and show good performance resulting in low return losses of less than -10dB to -29dB for the selective frequency bands.
A Logistic Regression Model of Customer Satisfaction for Online Food Delivery Services

Customer satisfaction is very important in today's competitive scenario. Without customer satisfaction, companies cannot imagine their survival. This paper used logistic regression to develop a customer satisfaction model for online food delivery services. Eight dimensions or variables have been considered: Better Discounts, Better Choice of Restaurants, Food quality, Packing of food, on time doorstep delivery, Customer service, Mode of payment and Pricing. From the study it is found that online food delivery service providers are lacking in the packing of food, on time door step delivery, customer service, and pricing.
Pardirallus sanguinolentus ( Aves : Rallidae ) do Chile central

With the aim to identify the parasite fauna of plumbeous rail, Pardirallus sanguinolentus (Aves: Rallidae) in Chile, 26 carcasses were parasitologically necropsied. The present study revealed the presence of 14 species of parasites (inverse Simpson index = 4.64; evenness = 0.332), including ectoparasites: feather mites: Analloptes megnini, Grallobia sp. , Grallolichus sp. , Megniniella sp. , and Metanalges sp. ; the feather lice Pseudomenopon meinertzhageni, Rallicola andinus, and Fulicoffula sp. ; and six species of gastrointestinal helminths: Heterakis psophiae, Porrocaecum ardeae, Tetrameres sp. , Capillaria sp. , Diorchis sp. , and Plagiorhynchus sp. The relatively high parasite richness that was found could be attributed to the highly favorable conditions of wetlands for parasite development. All parasites found, except feather lice, are new records for plumbeous rail. A checklist of parasites for plumbeous rail is presented.