Sternal Anomalies with Supernumerary and Subnumerary Vertebrae and Ribs – Case Reports

Background: Variations in the number of ribs and vertebrae have been noted in other wise normal looking people with some having supernumerary while others subnumerary. Sternal variations and anomalies though have not been as widely documented. These are two cases with one having a combination of sternal anomalies, supernumerary thoracic vertebrae and ribs and subnumerary lumbar vertebrae while the other had subnumerary thoracic vertebrae and ribs.Findings: Case 1: A 38year old female who had eleven thoracic vertebrae and corresponding pairs of ribs, nine pairs attached and two floating. The other skeletal components were normal. Case 2: Adult male had 13 thoracic vertebrae and thirteen corresponding pairs of ribs. Ten pairs of ribs attached to the cage and three floating. There were four lumber vertebrae. The manubrium of the sternum was much longer, ended at the third coastal cartilage attachment and there was an oval defect in the body of the sternum at the level of 5th costal cartilage. The rest of the skeleton was normal.Conclusions: Osteological variations in the rib cage and vertebrae are clinically important because they can mislead an unsuspecting clinician during diagnostic and therapeutic lumbar punctures, counting of ribs during heart examinations, drainage of the thorax and the 12th rib is important in citing of the incision for nephrectomy and other medical procedures. Radiological diagnosis, Forensic and medical legal pathological identifications need to put into consideration such variations

Sorghum [Sorghum bicolor (L.) Moench] Seed Quality as Affected by Variety, Harvesting Stage and Fertilizer Application in Bomet Country of Kenya

A set of laboratory experiments were conducted to evaluate the physiological quality of Sorghum bicolor (L.) Moench seeds subjected to different field cultural management practices. The main aim of this study was to contribute towards improved production of Sorghum bicolor (L.) Moench through better understanding of the crop’s agronomy. The experimental design was a three factorial split-split block design in the rain fed Sorghum bicolor (L.) Moench producing areas of Bomet County of Kenya. Treatments within the block were randomized. There were three factors which included variety at two levels (improved and local varieties); fertilizer application at two levels (with and without fertilizer); and seed selection at three levels (continuous, from booting stage and at harvest). Percentages of crop emergence and days to 50% physiological maturity were determined. The following seed quality tests were carried out: 1000-seed weight, standard germination, mean germination time and electrical conductivity. The improved variety had a field emergence of 100% while that of the local variety ranged from 60 - 97%. In regard to field emergence and maturity, there were significance differences (P≤ 0.001) between plots with fertilizer and those without regardless of the variety. Those plots with fertilizer outperformed those without. Germination and vigour tests indicated that seed selection time did not influence seed vigour, viability and yield (P ≤ 0.05). However, there were significant differences (P ≤ 0.001) between the improved variety (E1291) and local (Ochuti) variety. In relation to this, variety E1291 showed better seed vigour, viability and yield as compared to Ochuti. Similarly, there were significant differences (P ≤ 0.001) between plots to which fertilizer was applied and those without. Fertilizer application led to an increase in seed yield, seed weight, seed vigour and viability. It was therefore concluded that (i) E1291 was more adapted to the study area as compared to Ochuti and hence should be adopted by farmers; (ii) farmers should apply optimal phosphate and nitrogenous fertilizers to their soils so as to increase the quality and yield of their seed; and (iii) farmers could continue selecting their seed using their indigenous knowledge.Key words: Seed, Sorghum bicolor, viability, vigour, yiel

A novel online data-driven algorithm for detecting UAV navigation sensor faults

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate

Worldwide Contrast in Application of Bio-Fertilizers for Sustainable Agriculture: Lessons for Sub-Saharan Africa

The use of bio-fertilizers in sub-Saharan Africa (SSA) is low compared to selected developed and Asian countries. The later have perceived the products as useful and have invested in use of bio-fertilizers in their agricultural systems. Effective regulations in developed and selected Asian countries have enhanced the availability of high quality products. Conversely, lack of awareness, infrastructure, skill and absence of a supportive regulatory framework in SSA has negatively impacted the use of bio-fertilizers. This review aims at pointing out what SSA could learn from selected developed and Asian countries to improve the availability and adoption of high quality bio-fertilizers. The benefits in terms of biological nitrogen fixation, nutrient uptake, yield increases, cost saving, and utilization constraints are discussed to create awareness of stakeholders interested in the agricultural application of the technology in SSA. Keywords: bio-fertilizer, availability, adoption, profitability, sub-Saharan Afric

Removal of nickel from wastewater using an agricultural adsorbent

Chemical wastewater streams may contain toxic compounds which are non-biodegradable, and therefore require advanced treatment techniques such as adsorption. However, application of adsorption processes is often limited by the cost of adsorbents. In this study, the adsorption capacity of a low-cost adsorbent (pine sawdust) was investigated by treating wastewater containing nickel (II) and other heavy metal ions. Results were analysed using response surface methodology and a factorial design was employed to determine the interactive effects of the various factors on the adsorption capacity. Furthermore, Langmuir and Freundlich adsorption isotherms were fitted to experimental data to characterise the adsorption of the nickel ions by the pine sawdust. As a result, the highest adsorption capacity was attained at the combined effect of low adsorbent dose, high pH and high initial concentration. On the other hand, the Freundlich isotherm fitted the experimental data better than the Langmuir isotherm. Results of this study indicate that the use of pine sawdust could be a promising solution to the elimination of nickel ions from multi-component aqueous solutions.Keywords: sawdust, adsorption, nickel ions, wastewater, isother

Phylogenetic relationships within and among Brassica species from RAPD loci associated with blackleg resistance

The genus Brassica comprises economically important oilseed and vegetable crops. Their susceptibility to fungal diseases such as blackleg causes yield loss. In this study, thirty accessionsfrom USDA germplasm collection representing two diploid Brassica species (Brassica rapa and Brassica oleracea var. virids) and fifteen tetraploid cultivars (Brassica napus) from the national wintercanola variety trials (NWCVT) were evaluated using 13 sets of random amplified polymorphic DNA (RAPD) associated with blackleg resistance in Brassica nigra. 126 highly polymorphic bands with an average of 10 per primer were detected. A UPGMA dendrogram showed B. rapa as highly diverse and was supported from three different basal branches, while B. napus accessions were generally monophyletic. Similarly, all of B. oleraceae accessions were supported from the same basal node.Generally, the three species were reciprocally paraphyletic, suggesting that the RAPD markers showed both functional relationships as well as homology, possibly due to selection at the RAPD loci associated with blackleg resistance. Consequently, two potentially susceptible B. napus accessions were identified. The high polymorphic information content (PIC) and number of phylogenetically informative bands established RAPD as a useful tool for phylogenetic reconstruction, quantification ofgenetic diversity for conservation, cultivar classification and molecular breeding in Brassica

Integrated solution for anomalous driving detection based on BeiDou/GPS/IMU measurements

© 2016 Elsevier Ltd.There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks

An integrated solution for lane level irregular driving detection on highways

Global Navigation Satellite Systems (GNSS) has been widely used in the provision of Intelligent Transportation System (ITS) services. Current meter level system availability can fulfill the road level applications, such as route guide, fleet management and traffic control. However, meter level of system performance is not sufficient for the advanced safety applications. These lane level safety applications requires centimeter/decimeter positioning accuracy, with high integrity, continuity and availability include lane control, collision avoidance and intelligent speed assistance, etc. Detecting lane level irregular driving behavior is the basic requirement for these safety related ITS applications. The two major issues involved in the lane level irregular driving identification are accessing to high accuracy positioning and vehicle dynamic parameters and extraction of erratic driving behaviour from this and other related information. This paper proposes an integrated solution for the lane level irregular driving detection. Access to high accuracy positioning is enabled by GNSS and Inertial Navigation System (INS) integration using filtering with precise vehicle motion models and lane information. The detection of different types of irregular driving behaviour is based on the application of a Fuzzy Inference System (FIS). The evaluation of the designed integrated systems in the field test shows that 0.5 m accuracy positioning source is required for lane level irregular driving detection algorithm and the designed system can detect irregular driving styles