Shoulder girdle recognition using electrophysiological and low frequency anatomical contraction signals for prosthesis control

Shoulder disarticulation amputees account for a small portion of upper-limb amputees,thus little emphasis has been devoted to developing functional prosthesis for this cohort of amputees.In this study,shoulder girdle recognition was investigated with acquired data from electrophysiological(electromyography[EMG])and low frequency contraction(accelerometer[Acc])signals from both amputee and non-amputee participants.The contribution of this study is based around the contrast of the classification accuracy(CA)for different sensor configurations using a unique set of signal features.It was seen that the fusion of the EMG-Acc produced an enhancement in the CA in the range of 10%-20%,depending on which windowing parameters were considered.From this,it was seen that the best combination of a windowing scheme and classifier would likely be for the 350 ms and spectral regression discriminant analysis,with a fusion of the EMG-Acc information.The results have thus provided evidence that the two sensors can be combined and used in practice for prosthesis control.Taking a holistic view on the study,the authors conclude by providing a framework on how the shoulder motion recognition could be combined with neuromuscular reprogramming to contribute towards easing the cognitive burden of amputees during the prosthesis control process.

Comparative study of natural chemical for enhanced oil recovery: Focus on extraction and adsorption at quartz sand surface

In chemical enhanced oil recovery(CEOR),it is very important to utilize the excessive usage of chemicals.A great opportunity lies in adopting natural surfactants,since it is cheaper,ecosystem friendly,and less toxic than their counterpart synthetic surfactants.Despite the availability of natural surfactant sources,it is yet very early to decide on their applicability.Therefore,this research focuses on natural-saponin extracted from different raw materials available in the Middle East and their interaction with quartz-sand.A special focus was given to the adsorption isotherm models to describe the interaction with the reservoir rocks.Three raw materials were investigated are fenugreek,sugar beet leaves and chickpeas.The main extraction method employed was the chemical extraction using the soxhelet.The study used Uv–vis spectrometer to investigate the micellization behaviour and the consequent adsorption on quartz-sand.The presence of triterpenoid saponin is found dominant in all the sample,the intensity and purity differed according to the raw material source.Tthe critical micelle concentration(CMC)was at a close range of 4–5.5 wt%in all the samples.The highest adsorption was obtained by sugar beet leaves which is 192 g/kg.It is 25%and 37%higher than the Fenugreek and chickpeas,respectively.Increasing the salinity resulted in adsorption reduction between 2%and 56%.For the adsorption isotherms,it showed good agreement with the Langmuir model fitting.The remarkable finding is that the sugar beet leaves heterogeneous model seems to be valid by Frendluich and Halsey isotherms.

Heat transfer enhancement from heat sources using optimal design of combined fins heat-sinks

The rapid movement of heat transferred goes to be the most important target for researchers to deals with the thermal problems of electronic systems.Especially,that has high packing densities in limited space.Consequently,vertical combination between two shapes of fins was considered to improve the thermal performance of heat sink.Here,many models(longitudinal-pin fins)were created as a new approach based on the stable both of material and size.In the analytical solution,Finite element techniques used to solve the mathematical modeling and signum-sinusoidal-signum function was modified to model both the variable heat transfer area and convection perimeter.While in the numerical procedure,ANSYS simulation used as the validation of temperature distribution.In addition,results from previous work were used as second method of validation process.The results show a high level of agreement by maximum difference does not exceed(3.52%).In the calculation process,natural convection,range of Ra number(105–107)were applied for all models of which each one is distinguished by the parameter of area ratio(A∗)between hybrid model and longitudinal model.The results show many advantages;a significant drop in temperature profile about(2.7%–8.8%).Also,decrease in thermal resistance by(23%–43%)and increases in heat transferred(29%–78%).Furthermore,all parameters have a significant improve for the models that have A∗<1.48.But this improvement was down to less level at A∗>1.48 as a result of overlapping between the effects of miscellaneous parameters.Irreversibility that associated with the entropy generation was considered.In this step,it becomes important to find the model that achieves maximize of the thermal performance and minimize of the entropy generation.For that,the optimization procedure using genetic algorithm was adopted.It's clearly the best model exist within a close range between 1.509 and 1.518 based on the behavior of the best fitness function.