Utilisation of fish silage by ruminants

1. The literature in the following areas is reviewed: ruminant protein rationing systems and methods of measurement of dietary protein degradability; rate of passage through the ruminant digestive tract; protein supplementation of diets for growing cattle; production and utilisation of fish silage and protection of dietary protein by formaldehyde treatment. 2. Eleven acidified fish silages were prepared using a range of formalin levels (0-40 cm3kg-1 fish waste). White fish filleting scrap was minced and well mixed with formic acid (1.5-2.0% v/w) before the addition of the appropriate level of formalin. The silages were stored before analysis in closed plastic containers at a temperature of 23 +/-

Consumption Rates of Invasive Freshwater Gastropod Pomacea Canaliculata on Aquatic Plants from Shatt Al-Arab River, Basra, Iraq

Pomacea canaliculata (Gastropoda: Ampullariidae) is a common species in many parts of the world and an important consumer of aquatic macrophytes. We conducted laboratory tests to quantify the rates of consumption of aquatic plants in Shatt Al-Arab River, Basra, Iraq. six freshwater plant species were presented to an invasive P. canaliculata in laboratory tests. This study was carried out during January to December 2017 to evaluate the consumption rates to specific aquatic plants than others by freshwater snails Pomacea canaliculata. Specimens of Snails were collected from ponds in intertidal zones at banks of Shatt al-Arab River near Al- Salhyaa canal in Shatt Al- Arab city  from aquatic plants; Typha domingensis, Phragmites australis, Bacopa monniera, Ceratophyllum demersum and Potamogeton crispus. The presence of these Specimens aquatic plants was affected by the water temperature and   salinity, they almost disappear in winter leading to low snail numbers at that season. Statistical analysis shows a significant differences (P<0.05) between numbers of snails on five aquatic plants in the field that were these are collected. Bacopa monniera , Lemna minor, C. demersum and P. crispus were the higher preferred to snails in this study, while T. domingensis, P. australis recorded lower preferred by snails. In this study we use snail Pomacea canaliculata as a biological control agent of common macrophyte weeds species. Results indicated that P. canaliculata reared on Lemna, Bacopa, Ceratophyllum and Potamogeton had the highest food preference and consumption rates, but all individuals fed with Phragmites showed lowest feeding consumption rates and little the food preference. significantly differing from the others. However, in the absence of Bacopa , Lemna, Ceratophyllum and Potamogeton were consumed. Keywords: Consumption rate, aquatic plants, Pomacea canaliculata, Snail . DOI: 10.7176/JAAS/52-0

Cytotoxic Effect of Vincarosea Aqueous Crude Extraction Human Brain Carcinoma Cell Line (AMGM) In Vitro

The present study investigated the cytotoxic effects of aqueous crude extracts of Vincarosea leaves, flowers and seeds on Human brain carcinoma cell line (AMGA, Ahmed Majeed Glioblastoma Multiform ) in vitro, by using serial double dilution (concentration between 1.95-1000 µg/ml). The results showed that the cytotoxic effect of extracts was depended on type of parts of plant extracted, concentration and exposure time. The concentration 1000 µg/ml gave inhibition rate (IR), were (34, 49 and 64) % of leaves, flowers and seeds extracts respectively compared with control 100% after 24 hours from exposure time. However, low concentrations of aqueous extracts were found to induce the AMGA cells growth and proliferation (PR), it was 115% by treatment with aqueous extract offlowers extract in 1.95 µg/ml after 24 hours of exposed

Smart Door Lock : A first prototype of a networked power lock controller with an NFC interface

Most major cell phone manufacturers have been releasing cell phones equipped with Near Field Communication (NFC). At the same time there is also increasing use of mobile payments and user verification with the use of the NFC technology. These trends indicate both the increasing popularity and great potential for increased use of NFC in today’s society. As a result NFC has a huge potential to simplify our everyday tasks, ranging from paying for items to accessing our office or home. In this context we will focus on using NFC together with a Power over Ethernet (PoE) powered circuit board and NFC reader to realize a simple system for granting access to open a locked door. One of the purposes of this realization is to explore what services can be realized when such a system is connected to the home/building network and connected to the Internet. A second purpose is to learn how to use network attached devices, as the concept of the Internet of Things is considered by many to be a driving force in the next generation Internet. This project uses very in expensive and low power hardware, as the number of devices is potentially very large and thus in order to minimize the technology’s impact on the environment we must consider how to minimize the power used – while maintaining the desired user functionality. This bachelor’s thesis project made it possible for a PoE powered circuit board containing a MSP430 microcontroller to work along with a NFC reader, which was connected through the Serial Peripheral Interface (SPI). We hope that the end result of this project will lead to a simpler life by exploiting this increasingly ubiquitous technology. For example, a homeowner could send a one-time key to a repair person who is coming to fix their sink. Similarly a homeowner could send a key to their neighbor which is valid for two weeks so that their neighbor could come into their home to water the plants while they are away on vacation. Another example is lending your apartment key to a friend while you are out of town.Det blir allt vanligare med närfältskommunikation (NFC) i dagens samhälle, mobiltelefons-tillverkarna börjar utveckla nya telefoner med NFC teknik inbyggd, samtidigt som användningen av NFC ökat. Det sker även en utveckling inom mobila betalningar och användar-verifiering med användning av NFC, då NFC förenklar detta. Med detta sagt kommer vi att arbeta med detta i detta kandidatexamens-arbete där vi fokuserar på NFC samt Power over Ethernet som använder MSP430 chippet som kärna. Med dessa enheter kombinerade kommer en enkel rörelse med ett NFC kort över en NFC läsare som sedan skall ge åtkomst till en låst dörr. Detta i större kombination med en Internetuppkoppling kunna ge ägaren möjligheten att kunna skicka ut dörrnycklar till andra användare. I detta kandidatexamensarbete gjorde vi det möjligt för ett PoE kretskort bestående av ett MPS430 mikroprocessor att samarbeta med en NFC läsare genom SPI protokollet. Genom att utveckla detta projekt hoppas vi att vårt slutresultat leder till en enklare delning av nycklar med hjälp av denna teknologi

Control of Salmonella Spp isolated from Garmat Ali sewage by superoxide radicals produced in vitro.

A modified method was used in the present study to generate superoxide radicals (O2.-) in vitro, the method involves exposing of riboflavin to lighting and generate O2.-. Salmonella Spp was isolated from sewage of  Garmat Ali region in Basrah city, Iraq. This study aimed to reduced Salmonella Spp by submitted it  to superoxide radicals. A significant reduction in the number of bacteria was revealed after exposed to superoxide radicals at (10, 20, 30, 40 and 50) µg/mL of riboflavin for 10 min of lighting with fluorescent  lamp ( 40 watt ), as well as the reduction in bacteria number was observed when the bacteria was exposed to superoxide radicals at 30µg/mL of riboflavin for intervals (5, 10, 15, 20, 25 and 30) min of lighting with fluorescent  lamp. This study  suggesting that reduction in bacteria number was increased as increased riboflavin concentration or increased lighting time

Automated Detection of Broncho-Arterial Pairs Using CT Scans Employing Different Approaches to Classify Lung Diseases

Current research indicates that for the identification of lung disorders, comprising pneumonia and COVID-19, structural distortions of bronchi and arteries (BA) should be taken into account. CT scans are an effective modality to detect lung anomalies. However, anomalies in bronchi and arteries can be difficult to detect. Therefore, in this study, alterations of bronchi and arteries are considered in the classification of lung diseases. Four approaches to highlight these are introduced: (a) a Hessian-based approach, (b) a region-growing algorithm, (c) a clustering-based approach, and (d) a color-coding-based approach. Prior to this, the lungs are segmented, employing several image preprocessing algorithms. The utilized COVID-19 Lung CT scan dataset contains three classes named Non-COVID, COVID, and community-acquired pneumonia, having 6983, 7593, and 2618 samples, respectively. To classify the CT scans into three classes, two deep learning architectures, (a) a convolutional neural network (CNN) and (b) a CNN with long short-term memory (LSTM) and an attention mechanism, are considered. Both these models are trained with the four datasets achieved from the four approaches. Results show that the CNN model achieved test accuracies of 88.52%, 87.14%, 92.36%, and 95.84% for the Hessian, the region-growing, the color-coding, and the clustering-based approaches, respectively. The CNN with LSTM and an attention mechanism model results in an increase in overall accuracy for all approaches with an 89.61%, 88.28%, 94.61%, and 97.12% test accuracy for the Hessian, region-growing, color-coding, and clustering-based approaches, respectively. To assess overfitting, the accuracy and loss curves and k-fold cross-validation technique are employed. The Hessian-based and region-growing algorithm-based approaches produced nearly equivalent outcomes. Our proposed method outperforms state-of-the-art studies, indicating that it may be worthwhile to pay more attention to BA features in lung disease classification based on CT images

An Effective Ensemble Machine Learning Approach to Classify Breast Cancer Based on Feature Selection and Lesion Segmentation Using Preprocessed Mammograms

Background: Breast cancer, behind skin cancer, is the second most frequent malignancy among women, initiated by an unregulated cell division in breast tissues. Although early mammogram screening and treatment result in decreased mortality, differentiating cancer cells from surrounding tissues are often fallible, resulting in fallacious diagnosis. Method: The mammography dataset is used to categorize breast cancer into four classes with low computational complexity, introducing a feature extraction-based approach with machine learning (ML) algorithms. After artefact removal and the preprocessing of the mammograms, the dataset is augmented with seven augmentation techniques. The region of interest (ROI) is extracted by employing several algorithms including a dynamic thresholding method. Sixteen geometrical features are extracted from the ROI while eleven ML algorithms are investigated with these features. Three ensemble models are generated from these ML models employing the stacking method where the first ensemble model is built by stacking ML models with an accuracy of over 90% and the accuracy thresholds for generating the rest of the ensemble models are >95% and >96. Five feature selection methods with fourteen configurations are applied to notch up the performance. Results: The Random Forest Importance algorithm, with a threshold of 0.045, produces 10 features that acquired the highest performance with 98.05% test accuracy by stacking Random Forest and XGB classifier, having a higher than >96% accuracy. Furthermore, with K-fold cross-validation, consistent performance is observed across all K values ranging from 3–30. Moreover, the proposed strategy combining image processing, feature extraction and ML has a proven high accuracy in classifying breast cancer

Pixel-level image analysis to derive the broncho-artery (BA) ratio employing HRCT scans: A computer-aided approach

Bronchiectasis in children is a major health issue which can be life-threatening if not diagnosed and effectively treated. In the diagnosis of bronchiectasis, an increased broncho-arterial (BA) ratio is considered a significant marker. The BA ratio is measured by evaluating BA pairs, using high-resolution computed tomography (HRCT) scans. Detecting BA pairs automatically is challenging due to the complex characteristics of BA pairs and the ambiguous appearance of the bronchi. This study proposes an effective computerized approach to detect BA pairs and assess BA ratio using HRCT scans of children and employing computer-aided techniques and novel custom-build algorithms. Attention is given to reconstructing broken bronchial walls and identifying discrete BA pairs using custom-built kernel based and patch-based algorithms for pixel-level image analysis. To detect BA pairs, the lung region is segmented in the HRCT slices and image preprocessing techniques, including noise reduction, binarizing, largest contour detection and a hole-filling algorithm, are applied. A histogram analysis method is introduced to clean the images. A kernel-based algorithm is proposed to reconstruct the pixel distribution if the bronchial wall is so that the bronchi can be detected precisely. Potential arteries are detected using balanced histogram thresholding, morphological opening and an approach based on four conditions related to the object area circularity, rectangular boundary box ratio and enclosing circle area ratio. Potential bronchi are detected through matching of object coordinates with potential arteries, hole-filling and four condition based approaches. The potential BA pairs are detected by matching the coordinates of potential bronchi with those of potential arteries as the artery and bronchus are adjacent to each other in BA pairs. Finally, from the potential BA pairs, actual BA pairs are identified using a custom-built patch algorithm. The study is conducted using 2471 HRCT slices of seven children, obtained from the Royal Darwin Hospital, Australia. The BA ratio is derived based on the ratio of diameters, major axis lengths, minor axis lengths, area, convex hull and equivalent diameter where the BA ratios are respectively 0.51–0.65, 0.49–0.59, 0.59–0.77, 0.25–0.42, 0.29–0.47, 1.5–2 and 0.50–0.65

Mortality in hospital patients with and without mental disorders: a data-linkage cohort study

Objective: In the general population, people with mental disorders have increased mortality. This association, however, has not been explored in a population who at some time were inpatients of a public hospital. Methods: The sampling frame was patients admitted to an Australian regional public hospital 1996–2010. Those with known mental disorder were compared with an equal number of randomly selected patients without known mental disorder, matched for age, sex, and year of admission. Mortality outcomes were determined by linkage of hospital data and the National Death Index. Results: We identified 15,356 patients with mental disorder and 15,356 without known mental disorder, 25.2% of the former and 17.3% of the latter died during the study period. The odds ratio (OR) for death in those with mental disorder was 2.20 (95% confidence interval: 2.01–2.41) after adjusting for confounders, and their mean age at death was 4.6 years younger (p < 0.001). Other independent risk factors for mortality were being Indigenous (OR 1.72, 1.32–2.24), not partnered (OR 1.55, 1.36–1.76) or having multiple comorbidities (OR 1.65, 1.43–1.90). In the model that included multiple interactions, the ORs for death in Indigenous patients with mental disorder were markedly higher (6.6–9.5), regardless of other risk factors. Discussion: Among patients with a history of public hospital admission, those with mental disorders have higher mortality than those without mental disorders. This gap in life expectancy mandates increased attention, by clinicians and health services alike, to preventable causes of death in people with mental illness