Hybrid electric vehicle fuel minimization by DC-DC converter dual-phase-shift control

The paper introduces an advanced DC-link variable voltage control methodology that improves significantly the fuel economy of series Hybrid Electric Vehicles (HEVs). The DC-link connects a rectifier, a Dual Active Bridge (DAB) DC-DC converter and an inverter, interfacing respectively the two sources and the load in a series HEV powertrain. The introduced Dual Phase Shift (DPS) proportional voltage conversion ratio control scheme is realized by manipulating the phase shifts of the gating signals in the DAB converter, to regulate the amount of DAB converter power flow in and out of the DC-link. Dynamic converter efficiency models are utilized to account for switching, conduction, copper and core losses. The control methodology is proposed on the basis of improving the individual efficiency of the DAB converter but with its parameters tuned to minimize the powertrain fuel consumption. Since DPS control has one additional degree of freedom as compared to Single Phase Shift (SPS) voltage control schemes, a Lagrange Multiplier optimization method is applied to minimize the leakage inductance peak current, the main cause for switching and conduction losses. The DPS control scheme is tested in simulations with a full HEV model and two associated conventional supervisory control algorithms, together with a tuned SPS proportional voltage conversion ratio control scheme, against a conventional PI control in which the DC-link voltage follows a constant reference. Nonlinear coupling difficulties associated with the integration of varying DC-link voltage in the powertrain are also exposed and addressed

Non-cascaded short-term pumped-storage hydro-thermal scheduling using accelerated particle swarm optimization

© 2018 IEEE. This paper presents the implementation of a variant of the famous particle swarm optimization, known as Accelerated Particle Swarm Optimization (APSO), on a non-cascaded or a two-unit hydro-thermal system with consideration of hydal pumping in light loading intervals of hydro-thermal scheduling period. APSO is an easy to program and easy to implement variant of Particle Swarm Optimization (PSO) that has the ability to converge to a good approximate to global optimum within a few iterations. A standard pumped-storage hydrothermal scheduling problem, discussed in existing literature, is considered for the implementation of APSO. A comparison of this implementation is also given with the previously existing implementations of other algorithms

Influence of nitrogen sources on production of &#946b-galactosidase by Aspergillus niger

The study was undertaken to enhance the production of b-galactosidase using five organic nitrogen sources with wheat bran as a substrate under solid state fermentation. The microbial source Aspergillus niger and its DG-resistant mutant that were grown in medium with initial pH of 5.5 in 250 ml flasks at 30°C for 144 h and sample was harvested after every 24 h and analysed for substrate consumption, cell mass formation and enzyme production. All the nitrogen sources, ammonium sulphate, corn steep liquor, diammonium phosphate, fish meal and urea showed significant results. However, higher values of enzyme activity of 168.0 and 371.15 IU/l/h, parent and mutant, respectively, was obtained from sample in which corn steep liquor was used as a nitrogen source as compared tocontrol (73.1 and 176.3 IU/l/h in parent and mutant, respectively). The effect of nitrogen sources was also found significant in both the organisms but higher in mutant organism (2.2 fold). It is concluded that enzyme production enhanced 2.7 fold by use of suitable production medium under optimum cultural conditions and that the mutant derivative of A. niger can be exploited for hyper production of this enzyme

Barriers to green supply chain management: An emerging economy context

© 2019 Elsevier Ltd Green supply chain management is attracting increasing attention as a way to decrease the adverse environmental effects of industries worldwide. However, considering the context of an emerging economy like Bangladesh, green supply chain management is still in its inception and has not been widely embraced in the textile industry, and therefore barriers hindering its adoption in emerging economy context demand a comprehensive investigation. This research reviews the viewpoints and hurdles in adopting green supply chain management practices in the context of the Bangladeshi textile industry. A questionnaire survey of Bangladeshi textile practitioners of operations and supply chain management division, having a sample size of thirty, was undertaken to identify the barriers, and a hierarchical cluster analysis technique was used in the detailed analysis of this data. Opinions were sought from experts on the significance of the resulting clusters, considering the relative importance of the barriers. Fifteen barriers to the adoption of green supply chain management were identified in the review of the literature, with these barriers then analyzed by using the data collected from Bangladeshi textile industry practitioners. The research indicates that the most important barrier is that there is low demand from customers and financial constraint resulting from short term little financial benefit to businesses, with lack of government regulations also a commonly faced barrier in adopting green supply chain initiatives. This study will provide valuables insights to practitioners and relevant policy makers about the barriers prevailing in the emerging economies towards the adoption of green supply chain management practices, which, in turn, can guide to undertake appropriate steps for alleviating those barriers

A biochemical and histopathologic study showing protection and treatment of gentamicin-induced nephrotoxicity in rabbits using vitamin c

Gentamicin and vitamin C have been proposed as nephrotoxic and antioxidant, respectively. This study involved biochemical and histopathologic investigation showing protection and treatment of gentamicin-induced nephrotoxicity in rabbits using vitamin C for 26 days hypothesizing that whether vitamin C would inhibit or decrease the raised serum urea and creatinine levels. This study was conducted on 25 healthy male albino rabbits (average weight 1.5±0.2 kg), classified into 5groups: group A, B, C, D and E for nephrocurative (study-I) and  nephroprotective (study-II) studies. Control group of rabbits (group A) received only the vehicle of gentamicin ampoule. In study-I, gentamicin sulphate (GS 80 mg/kg, i.m.) was administered to group B and C rabbits for ten days, then group C rabbits received vitamin C 250 mg/Kg for remaining 16 days. Group D and E received GS 80 mg/kg and GS 80 mg/kg i.m.-vitamin C 250 mg/kg orally, respectively during whole period (26 days) of study-II. After 26 days, various biochemical parameters, i.e. serum creatinine, blood urea nitrogen (BUN), and serum antioxidant activity, and histopathologic investigations were made. Nephrotoxicity was observed in rabbit groups B, C and D as evident from significant (p<0.05) high levels of serum creatinine and BUN and low serum antioxidantlevels as compared to the levels of control group. Decrease in the levels of serum creatinine and BUN along with the increase in serum antioxidant activity was observed after vitamin C treatment in group C. While, renal-protective role of vitamin C was seen in group E as compared to the control. In conclusion, Gentamicin induced nephrotoxicity can be  attenuated or treated using vitamin C

Entropy generation in magnetohydrodynamic radiative non-Newtonian dissipative convection flow from an inclined plane : numerical study

A theoretical model is developed to study entropy generation in non-Newtonian magnetohydrodynamic thermal convection from an inclined plate as a simulation of electroconductive polymer materials processing of relevance to automotive coating applications. High temperature invokes radiative effects which are analysed with the Rosseland diffusion flux approximation. The Jeffery’s viscoelastic model is deployed to describe the non-Newtonian characteristics of the fluid and provides a good approximation for magnetic polymers, which constitutes a novelty of the present work. The normalized nonlinear boundary value problem is solved computationally with the Keller-Box implicit finite-difference technique. Extensive solutions for velocity, surface temperature, skin friction and heat transfer rate are visualized graphically for various thermophysical parameters. Validation is conducted with earlier published work for the case of a vertical plate in the absence of magnetic field, radiative flux and non-Newtonian effects. The dimensionless entropy generation is obtained via the reduced momentum and energy equations. Bejan number is generally decreased with greater values of Deborah number. Increasing magnetic field reduces entropy generation number whereas it enhances the Bejan number. Increasing Brinkman number (dissipation parameter) is found to enhance the entropy generation number whereas it suppresses the Bejan number

Recent Developments in Detection of Central Serous Retinopathy through Imaging and Artificial Intelligence Techniques – A Review

Central Serous Retinopathy (CSR) or Central Serous Chorioretinopathy (CSC) is a significant disease that causes blindness and vision loss among millions of people worldwide. It transpires as a result of accumulation of watery fluids behind the retina. Therefore, detection of CSR at early stages allows preventive measures to avert any impairment to the human eye. Traditionally, several manual methods for detecting CSR have been developed in the past; however, they have shown to be imprecise and unreliable. Consequently, Artificial Intelligence (AI) services in the medical field, including automated CSR detection, are now possible to detect and cure this disease. This review assessed a variety of innovative technologies and researches that contribute to the automatic detection of CSR. In this review, various CSR disease detection techniques, broadly classified into two categories: a) CSR detection based on classical imaging technologies, and b) CSR detection based on Machine/Deep Learning methods, have been reviewed after an elaborated evaluation of 29 different relevant articles. Additionally, it also goes over the advantages, drawbacks and limitations of a variety of traditional imaging techniques, such as Optical Coherence Tomography Angiography (OCTA), Fundus Imaging and more recent approaches that utilize Artificial Intelligence techniques. Finally, it is concluded that the most recent Deep Learning (DL) classifiers deliver accurate, fast, and reliable CSR detection. However, more research needs to be conducted on publicly available datasets to improve computation complexity for the reliable detection and diagnosis of CSR disease

Design and development of autonomous robotic fish for object detection and tracking

In this article, an autonomous robotic fish is designed for underwater operations like object detection and tracking along with collision avoidance. The computer-aided design model for prototype robotic fish is designed using the Solid Works® software to export an stereolithography (STL) file to MakerBot, a 3D printer, to manufacture the parts of robotic fish using polylactic acid thermoplastic polymer. The precise maneuverability of the robotic fish is achieved by the propulsion of a caudal fin. The oscillation of the caudal fin is controlled by a servomotor. A combination of visual and ultrasonic sensors is used to track the position and distance of the desired object with respect to the fish and also to avoid the obstacles. The robotic fish has the ability to detect an object up to a distance of 90 cm at normal exposure conditions. A computational fluid dynamics analysis is conducted to analyze the fluid hydrodynamics (flow rate of water and pressure) around the hull of a robotic fish and the drag force acting on it. A series of experimental results have shown the effectiveness of the designed underwater robotic fish. </jats:p

Single molecule light field microscopy

We introduce single molecule light field microscopy (SMLFM), a new class of three-dimensional (3D) single molecule localization microscopy. By segmenting the back focal plane of a microscope objective with an array of microlenses to generate multiple 2D perspective views, the same single fluorophore can be imaged from different angles. These views, in combination with a bespoke fitting algorithm, enable the 3D positions of single fluorophores to be determined from parallax. SMLFM achieves up to 20 nm localization precision throughout an extended 6 µ m depth of field. The capabilities of SMLFM are showcased by imaging membranes of fixed eukaryotic cells and DNA nanostructures below the optical diffraction limit.</jats:p

Proceedings of the Salford Postgraduate Annual Research Conference (SPARC) 2011

These proceedings bring together a selection of papers from the 2011 Salford Postgraduate Annual Research Conference(SPARC). It includes papers from PhD students in the arts and social sciences, business, computing, science and engineering, education, environment, built environment and health sciences. Contributions from Salford researchers are published here alongside papers from students at the Universities of Anglia Ruskin, Birmingham City, Chester,De Montfort, Exeter, Leeds, Liverpool, Liverpool John Moores and Manchester