Electron detachment in negative ion-molecule collisions

Absolute total cross sections for electron detachment, reactive scattering, charge transfer and dissociative charge transfer have been measured for collisions of hydrogen and halogen negative ions with various molecular targets. The reactants investigated involve H(\u27-), D(\u27-), F(\u27-), Cl(\u27-), Br(\u27-) and I(\u27-) ions as projectiles and H(,2), D(,2), HD, N(,2), CO, O(,2), CO(,2), CH(,4) and Cl(,2) molecules as targets. The energy range of these experiments extended from about 1 eV to about 300 eV in the lab.;The threshold behavior of the detachment cross sections for the reactants H(\u27-)(D(\u27-)) + H(,2),D(,2) and HD has been determined. The thresholds for detachment for both H(\u27-) and D(\u27-) ions are found to be larger than the electron affinity of hydrogen and isotopic substitution reveals that the detachment cross sections scale with relative collision energy at low collision energies and with relative collision velocity at high collision energies. Upper and lower bounds on detachment-rate constants which are based upon the measurements are presented.;Studies of the reactants H(\u27-)(D(\u27-)) and B(,2), CO, O(,2), CO(,2) and CH(,4) reveal that electron detachment is the dominant process for all the molecular targets except O(,2) for which charge transfer dominates. Isotope effects are observed in all the cross sections. The general features of the charge-transfer cross section for the O(,2) target are in agreement with the ideas of a simple two-state collision model. The cross sections for charge transfer (or dissociative charge transfer) are found to be small for all targets except O(,2).;In the case of the collisions of F(\u27-) and Cl(\u27-) with H(,2), D(,2) and HD, reactive scattering is found to be the dominant inelastic channel for F(\u27-) projectile. Electron detachment of F(\u27-) is found to occur by two distinct mechanisms. A striking difference in the detachment and reactive cross sections is observed when Cl(\u27-) is substituted for F(\u27-) in that the electron detachment cross section is generally larger than that for reactive scattering. Isotope effects are observed in all the cross sections for both F(\u27-) and Cl(\u27-).;Charge transfer and dissociative charge transfer cross sections are found to be the dominant channels for collisions of Cl(\u27-), Br(\u27-) and I(\u27-) with Cl(,2). The electron detachment cross section for I(\u27-) + Cl(,2) is found to be anomalously low. Some energy loss spectra are reported for I(\u27-) + Cl(,2). They exhibit substantial inelastic scattering which is consistent with the calculated potentials of Cl(,2)

Should Younger Siblings of Peanut-Allergic Children Be Assessed by an Allergist before Being Fed Peanut?

<p/> <p>The objective of this study was to determine the risk of peanut allergy in siblings of peanut-allergic children. In 2005-2006, 560 households of children born in 1995 in the province of Manitoba, Canada, were surveyed. The index children (8-to 10-year-olds) were assessed by a pediatric allergist and had skin-prick testing and/or capRAST for peanut allergy. Surveys were completed by parents for siblings to determine the presence of peanut allergy. Of 560 surveys, 514 (92%) were completed. Twenty-nine (5.6%) index children were peanut allergic. Fifteen of 900 (1.7%) siblings had peanut allergy. Four of 47 (8.5%) were siblings of peanut-allergic children and 11 of 853 (1.3%) were siblings of non-peanut-allergic children. The risk of peanut allergy was markedly increased in siblings of a peanut-allergic child (odds ratio 6.72, 95% confidence interval 2.04-22.12). Siblings of peanut-allergic children are much more likely to be allergic to peanut. An allergy assessment by a qualified allergist should be routinely recommended before feeding peanut to these children.</p

Rehabilitation system for paraplegic patients using mind machine interface; a conceptual framework

Mind-Machine Interface (MMI) is a newly surfaced term in the field of control engineering and rehabilitation systems. This technique, coupled with the existing functional electrical stimulation (FES) systems, can be very beneficial for effective rehabilitation of disabled patients. This paper presents a conceptual framework for the development of MMI based FES systems for therapeutic aid and function restoration in spinal cord injured (SCI) paraplegic patients. It is intended to acquire thought modulated signals from human brain and then use these signals to command and control FES as desired by the patient. The proposed setup can significantly assist the rehabilitation and recovery of paraplegic patients due to the ease of control for the user

A Quarter Car ARX Model Identification Based on Real Car Test Data

This paper presents a system identification of a quarter car passive suspension system dynamic model based on real-time running test car data. The input-output data of a car were recorded by test-driving the car on a road surface. The input variable is the vertical acceleration of the car shaft, while the output variable is the vertical acceleration of the body of the car. Two acceleration sensors were installed on the front right corner of the car: One on top of the suspension and another on the car shaft at the bottom of the suspension. The acquired data were used to identify the mathematical model of a quarter car passive suspension system dynamics. A quarter car passive suspension system was assumed to have an ARX model structure, hence qualifies to be a candidate model for system identification. The system identification algorithm used in this work was based on linear least-square estimation. The results showed that the best ARX model of the car passive suspension system model is produced with the best fit of 90.65%, Akaike’s FPE is 5.315x10-6. The output order of the model was found to be four, the input order is two and the time delay was one. The fit rate greater than 90% and along with a very small value for the FPE means that the system identification requirements are fulfilled and the identified model is acceptable

Heterosis analysis in strain-crossed hybrid Rohu (Labeo Rohita) through mMicrosatellite DNA variability assay

Labeo rohita is an important commercial aquaculture species in Bangladesh, but it needs improved growth performance to meet the increasing demand for fish. Genetic improvement through inter-strain crossing, generating heterosis, is quicker than a selection strategy. Therefore, crosses were made between two strains of rohu: Padma River strain and a hatchery strain. Growth performance analyis showed the highest growth rate in the Padma × Padma cross followed by one of the reciprocal crosses Hatchery♂ × Padma♀ (hybrid). The lowest growth rate was observed in Hatchery × Hatchery cross. DNA variability study using three microsatellite markers showed polymorphism (P95) in these crosses. Variations were observed in number and frequencies of alleles and mean heterozygosity in different loci; the mean number of alleles varied from 4.667±0.882, 3.333±1.333 and 2.667±1.202 in Padma, hybrid and Hatchery strains respectively. Relatively high levels of gene flow and low Strain differentiation (FST) values were found between the Padma and hybrid strains. The UPGMA dendrogram based on genetic distance placed the Padma population in one cluster and the hybrid and Hatchery populations in another. The results revealed that there was relatively low level of genetic variability in the riverine and hatchery reared populations of L. rohita in Bangladesh

The quadriceps muscle of knee joint modelling using neural network approach: Part 2

— Artificial neural network has been implemented in many filed, and one of the most famous estimators. Neural network has long been known for its ability to handle a complex nonlinear system without a mathematical model and has the ability to learn sophisticated nonlinear relationships provides. Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the mean square error (MSE). Subsequently, this paper displays the change of quadriceps muscle model by using fake savvy strategy named backpropagation neural system nonlinear autoregressive (BPNN-NAR) model in perspective of utilitarian electrical affectation (FES). A movement of tests using FES was driven. The data that is gotten is used to develop the quadriceps muscle model. 934 planning data, 200 testing and 200 endorsement data set are used as a part of the change of muscle model. It was found that BPNNNARMA is suitable and efficient to model this type of data. A neural network model is the best approach for modelling nonlinear models such as active properties of the quadriceps muscle with one input, namely output namely muscle force

Gas chromatography mass spectrometry couple with quadrupole time-of-flight (GC-QTOF MS) as a powerful tool for profiling of oxygenated sesquiterpenes in agarwood oil

Agarwood (Aquilaria malaccensis) is very well known as the most expensive wood in the world due to its wide applications in perfumery, cosmetic traditional medicine, and religious ceremonies. The study aimed to give an in-depth characterisation focusing on marker compounds in A. malaccensis from different places in Malaysia. The establishment of an oxygenated sesquiterpenes chemical profile of the fungus-infected agarwood oil was achieved by gas chromatography mass spectrometry (GC–MS) coupled with quadrupole time (QTOF) technique. Aroma compounds were identified as sesquiterpenes and oxygenated sesquiterpenes where agarospirol was found in samples of all locations (3.12%, 3.54%, 3.36% and 2.26% from Melaka, Pahang, Kelantan A and Kelantan B respectively) and also N-hexadecanoic acid as one of the major compounds. Both compounds were further isolated by Prep-GC and confirmed by NMR. This study provides a reference for agarwood oil analysis from different origins in Malaysia

Smart Home Control for Disabled Using Brain Computer Interface

Electroencephalography (EEG) based smart home control system is one of the major applications of Brain Computer Interface (BCI) that allows disabled people to maximize their capabilities at home. A Brain Computer Interface (BCI) is a device that enables severely disabled people to communicate and interact with their environments using their brain waves. In this project, the scope includes Graphical User Interface (GUI) acts as a control and monitoring system for home appliances which using BCI as an input. Hence, NeuroSky MindWave headset is used to detect EEG signal from brain. Furthermore, a prototype model is developed using Raspberry Pi 3 Model B+, 4 channels 5V relay module, light bulb and fan. The raw data signal from brain wave is being extracted to operate the home appliances. Besides, the results agree well with the command signal used during the experiment. Lastly, the developed system can be easily implemented in smart homes and has high potential to be used in smart automation