Multi-branch Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation

In this paper, we present an automated approach for segmenting multiple sclerosis (MS) lesions from multi-modal brain magnetic resonance images. Our method is based on a deep end-to-end 2D convolutional neural network (CNN) for slice-based segmentation of 3D volumetric data. The proposed CNN includes a multi-branch downsampling path, which enables the network to encode information from multiple modalities separately. Multi-scale feature fusion blocks are proposed to combine feature maps from different modalities at different stages of the network. Then, multi-scale feature upsampling blocks are introduced to upsize combined feature maps to leverage information from lesion shape and location. We trained and tested the proposed model using orthogonal plane orientations of each 3D modality to exploit the contextual information in all directions. The proposed pipeline is evaluated on two different datasets: a private dataset including 37 MS patients and a publicly available dataset known as the ISBI 2015 longitudinal MS lesion segmentation challenge dataset, consisting of 14 MS patients. Considering the ISBI challenge, at the time of submission, our method was amongst the top performing solutions. On the private dataset, using the same array of performance metrics as in the ISBI challenge, the proposed approach shows high improvements in MS lesion segmentation compared with other publicly available tools.Comment: This paper has been accepted for publication in NeuroImag

CO2 Utilization via Integration of an Industrial Post-Combustion Capture Process with a Urea Plant: Process Modelling and Sensitivity Analysis

Carbon capture and utilization (CCU) may offer a response to climate change mitigation from major industrial emitters. CCU can turn waste CO(2)emissions into valuable products such as chemicals and fuels. Consequently, attention has been paid to petrochemical industries as one of the best options for CCU. The largest industrial CO(2)removal monoethanol amine-based plant in Iran has been simulated with the aid of a chemical process simulator, i.e., Aspen HYSYS(R)v.10. The thermodynamic properties are calculated with the acid gas property package models, which are available in Aspen HYSYS(R). The results of simulation are validated by the actual data provided by Kermanshah Petrochemical Industries Co. Results show that there is a good agreement between simulated results and real performance of the plant under different operational conditions. The main parameters such as capture efficiency in percent, the heat consumption in MJ/kg CO2 removed, and the working capacity of the plant are calculated as a function of inlet pressure and temperature of absorber column. The best case occurred at the approximate temperature of 40 to 42 degrees C and atmospheric pressure with CO2 removal of 80.8 to 81.2%; working capacity of 0.232 to 0.233; and heat consumption of 4.78 MJ/kg CO2

Visualising kinematics of an elastic Ossur ESR prosthetic foot using novel low-cost optical tracking systems

A novel method of measuring kinematics of elastic body is the subject of this investigation. Unlike kinematics of rigid body large elastic deformation tends to modify the dynamics of motion. In the case of amputee runner the change in kinematics of the foot depends on the stiffness, body mass and running beat frequency. Current measurement techniques, such as gait analysis assumes rigid elements. Currently there are inertia measurement unit (IMU) based systems that uses accelerometers and gyro to determine acceleration, velocities and orientations of the sensors. They are not capable of measuring changes in lengths or positions of the objects that they are attached to. For that reason predicting velocities and displacement by integrating acceleration is not always viable due to time step limits of the integrations that are necessary. Here a new optical device is developed and presented that is accurate and is practically error free to monitor Foot elastic deformation. In this paper the Dynamic elastic response of Ossur Running foot is being investigated using this device. The data generated show complete phase synchronisation with IMU but much better accuracy in terms of velocity and relative displacement of the feet due to flexure as a result of elastic response to Impulse

Kinematics study of the deltoid in Reverse Shoulder Arthroplasty using Standard Pre and Post-Operative X-Rays

© 15th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2018/MFPT 2018. All rights reserved. For patients with deficient rotator cuff Reverse Shoulder Arthroplasty, in which the centre of rotation of the glenohumeral joint is repositioned, is a popular treatment. However, for optimal restoration of motion after RSA, the correct implant selection and positioning within the bones is critical for a successful surgical outcome. This paper examines current practice of implant insertion and predicts what would be its mechanical advantage by using a developed graphical user interface importing pre and post-operative shoulder X-rays. Standardised X-rays of 8 shoulder griddle pre and post-operative were provided in the true anteroposterior (Grashey) view. Images were then calibrated and key geometrical parameters were identified in all images. A mathematical model for deltoid excursion and deltoid lever arm in full abduction was developed based on the mechanical model of the shoulder in order to investigate its performance (deltoid) in both native and reverse shoulders. Results showed that the deltoid lever arm was improved in reverse shoulders for lower abductions. In higher abductions a sudden drop in the lever arm's mechanical advantage was observed. It was also observed that more deltoid excursion occurred in full abduction of reverse shoulders compared to native shoulders

Techno-economic assessment and optimization of a solar-assisted industrial post-combustion CO2 capture and utilization plant

This paper studies the techno-economic feasibility of the solar-assisted regeneration process of the largest industrial CO2 removal monoethanolamine-based plant in Iran. The plant incorporating parabolic troughs is modelled using System Advisor Model software and the weather data are derived from the European Commission''s Photovoltaic Geographical Information System. Sensitivity analyses are realized to evaluate the effect of important parameters, i.e., the solar multiple and the hours of storage, and to reveal the optimum case. The studied impacts are linked to the overall net energy generation and the levelized cost of heat (LCOH). The optimum case is found to have a solar multiple of 3.1 and 18-hours of storage, resulting in a solar share of 0.7 and a LCOH of 3.85 (¢/kWh). When compared to the base case (solar multiple of 2 and 6 h of storage), the optimum solution results in a similar LCOH but it achieves the generation of an additional 16, 112 MWhth annually. The thermal energy supplied by the solar system leads to an annual reduction in the natural gas consumption of approximately 3.8 million m3 that results in a CO2 emission reduction of 7.1 kton. © 2021 The Author

Effect of mycorrhizal fungi on the absorption of phosphorus and zinc by two alfalfa varieties in cadmium contaminated soils

Some agricultural and industrial practices such as mining activities, waste materials of industrial factories, other pollutants and the application of wastewater on farmlands contaminate the agricultural soils. Cadmium is one of the most common heavy metals which accumulates in agricultural soils as a result of the application of phosphorus fertilizers and can easily be absorbed by plants even at very low concentrations with detrimental effects on the living systems. Alfalfa requires high rates of phosphorus fertilizer and therefore the soils under alfalfa are more prone to contamination of cadmium. Arbuscular Mycorrhizal fungi exist as obligate symbiotic organisms on roots of more than 80% of plant families and enhance the growth of the host plant by providing water and nutrients when the plant growth limited by environmental stresses. In order to evaluate the effect of Mycorrhiza symbiosis on nutrient absorption by alfalfa under the cadmium pollution, a factorial experiment base on completely randomized design conducted by using two alfalfa varieties (2122 and Hamadani cultivars); Glomus intraradices fungi; and four levels of cadmium (0, 5, 10 and 20 mg kg -1 soil) with four replications in green house on 2005. The plants cut at 50% bloom to determine root and shoot dry matter as well as mineral nutrient absorption by using standard laboratory procedures. The soil material rhyzosphere collected to determine colonization percent. Results showed that phosphorus and iron absorption of 2122 was superior under normal growing conditions. However, under cadmium stress Hamadani performed superior where it also proved none suitable as a host plant for symbiosis with Mycorrhiza. Fungi significantly (a = %1) increased the absorption of nitrogen, phosphorus and zinc by shoots and phosphorus even in the presence of cadmium adverse effects. Time of harvest also significantly improved the uptake of all the nutrients by the shoots as well as the dry matter production by shoots