Dynamics, Mechanistic and Equilibrium Studies for the Biosorption of Nickel on Palm Tree Leaves

Adsorption of heavy metals on biological sorbents, activated carbon and synthetic resin particles is a common separation technique. In this study, the biosorption of nickel ions from aqueous solution by palm tree leaves was investigated as a function of shaking time, nickel ions concentration and equilibrium pH. Competitive adsorption of nickel on palm tree leaves with EDTA and citric acid was also investigated. Batch adsorption experiments revealed that the biosorption of nickel on palm tree leaves was strongly pH dependent, and maximum nickel sorption was found to occur at equilibrium pH of 6.0. Dynamics studies showed that: the initial uptake of nickel on palm tree leaves was rapid, equilibrium was established within 30 minutes, and the data followed the pseudo-second order reaction. The equilibrium sorption data of nickel on palm tree leaves at solution pH 6.0 were described by two-parameter isotherm models such as the Langmuir, Freundlich, and D-R models and three-parameter models such as Redlich-Peterson and Sips isotherm models. Ion-exchange, adsorption-complexation and intraparticle diffusion mechanisms were found to be involved in the biosorption process. The Effect of ions interference on the biosorption of nickel on palm tree leaves showed that the sorption of nickel on palm tree leaves was adversely affected by the presence of chelating agents such as EDTA and citric acid

Simple speed sensorless DTC-SVM scheme for induction motor drives

The paper focuses on the development of a novel DSP based high performance speed sensorless control scheme for PWM voltage source inverter fed induction motor drives. Firstly, two generic torque and flux control methods the Field Oriented Control (FOC) and Direct Torque Control (DTC), are briefly described. For implementation the sensorless scheme DTC with Space Vector Modulation (DTCSVM) has been selected because it eliminates the disadvantages associated with the DTC while keeping the advantages of both FOC and DTC. Secondly, the simple flux vector observer allowing speed sensor elimination is given. The novelty of the presented system lays in combining the DTC-SVM structure with a simple observer for both torque/flux and speed sensorless control. Furthermore, the DTC-SVM structure which operates in speed sensorless and torque control mode is presented. Finally, the description of a 50 kW laboratory drive and experimental results illustrating properties of the system are given

Model Systems to Define Remyelination Therapies

Demyelinating diseases of the central nervous system (CNS), such as multiple sclerosis (MS), are characterized by multiple focal demyelinating lesions, resulting in various functional deficits. The pathology of MS is defined by local loss of myelin sheaths in the brain and spinal cord associated with infiltration of peripheral immune cells. Classically, MS starts with a series of relapses and remissions, followed several years later by a more progressive form of the disease and a steady functional decline. Although the mechanism of disease initiation is poorly understood, disease progression is associated with immune system activation toward CNS antigens including myelin proteins. Animal models of MS have been critical in the development of MS therapies, with experimental allergic encephalitis (EAE) being the most common. This model has been instrumental in defining the role of T cells in disease progression and in the development of targeted therapies. Understanding the biology of myelin repair has, however, largely come from other model systems including local targeted demyelination in vivo, slice preparations, and in vitro. This has led to the identification of a diverse array of potential new targets to modulate disease progression. Development of these new avenues is the target of intensive ongoing research

Single vesicle imaging indicates distinct modes of rapid membrane retrieval during nerve growth

<p>Abstract</p> <p>Background</p> <p>During nerve growth, cytoplasmic vesicles add new membrane preferentially to the growth cone located at the distal tip of extending axons. Growth cone membrane is also retrieved locally, and asymmetric retrieval facilitates membrane remodeling during growth cone repulsion by a chemorepellent gradient. Moreover, growth inhibitory factors can stimulate bulk membrane retrieval and induce growth cone collapse. Despite these functional insights, the processes mediating local membrane remodeling during axon extension remain poorly defined.</p> <p>Results</p> <p>To investigate the spatial and temporal dynamics of membrane retrieval in actively extending growth cones, we have used a transient labeling and optical recording method that can resolve single vesicle events. Live-cell confocal imaging revealed rapid membrane retrieval by distinct endocytic modes based on spatial distribution in <it>Xenopus </it>spinal neuron growth cones. These modes include endocytic "hot-spots" triggered at the base of filopodia, at the lateral margins of lamellipodia, and along dorsal ridges of the growth cone. Additionally, waves of endocytosis were induced when individual filopodia detached from the substrate and fused with the growth cone dorsal surface or with other filopodia. Vesicle formation at sites of membrane remodeling by self-contact required F-actin polymerization. Moreover, bulk membrane retrieval by macroendocytosis correlated positively with the substrate-dependent rate of axon extension and required the function of Rho-family GTPases.</p> <p>Conclusions</p> <p>This study provides insight into the dynamic membrane remodeling processes essential for nerve growth by identifying several distinct modes of rapid membrane retrieval in the growth cone during axon extension. We found that endocytic membrane retrieval is intensified at specific subdomains and may drive the dynamic membrane ruffling and re-absorption of filopodia and lamellipodia in actively extending growth cones. The findings offer a platform for determining the molecular mechanisms of distinct endocytic processes that may remodel the surface distribution of receptors, ion channels and other membrane-associated proteins locally to drive growth cone extension and chemotactic guidance.</p

Space vector pulse-width modulation technique for an eleven-phase voltage source inverter with sinusoidal output voltage generation

This paper discusses the space vector pulse width modulation (SVPWM) scheme for an eleven-phase two-level voltage source inverter (VSI), aimed at producing a sinusoidal output voltage waveform. Generalised space vector theory is used to realise the SVPWM. As per the general inverter switching theory, there are 211 = 2048 switching states that yield 2046 active voltage space vectors and one zero voltage vector, which results with two switching states. Out of the total of 2046 active voltage vectors, the most suitable set comprising 110 active voltage vectors is identified and is utilised in the implementation of the SVPWM. The sinusoidal voltage is obtained by controlling the duty cycles of the applied voltage space vectors in such a way that the non-zero reference voltage in the first (d-q) plane is achieved, while simultaneously zeroing the average voltage in the other four (x-y) planes in accordance with the zero references. The theoretical results are verified by experimentation using a passive resistive-inductive load. Finally, experimentally obtained THD values of the phase voltage and current for the eleven-phase SVPWM are compared with the corresponding values obtained using SVPWM for other odd phase numbers. Keywords: Eleven-phase system, Multi-phase drives, Space vector PWM, Voltage source inverte

An Open Natural Language Processing (NLP) Framework for Ehr-Based Clinical Research: A Case Demonstration Using the National COVID Cohort Collaborative (N3c)

Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both symbolic and statistical methods, as well as highlight the need for federated annotation and evaluation to resolve several pitfalls encountered in the course of these efforts