Distillation Sequence Optimization Considering Extractive Distillation under Multiple Conditions: A Methanol to Propylene Case Study

This study provides insights into the distillation sequence optimization of refinery system in a methanol to propylene plant with extractive distillation under multiple conditions. The simulated annealing algorithm(SA) with relative cost function was used to solve a meaningful optimization problem. It was observed that different conditions had differed on the flowsheet. Case study shows the effectiveness of the proposed method.

The effectiveness of mI SMART:A nurse practitioner led technology intervention for multiple chronic conditions in primary care

Aims:Used as integrated tools,technology may improve access and outcomes of care.A new intervention that integrates multiple technologies called mI SMART has been developed,implemented,and evaluated by Nurse Practitioners.The aim of this paper is to present the initial effectiveness of a webbased,structure of sensors and mobile devices designed to overcome the known health determinant of access to care for rural,chronically ill patients by using technology.Methods:The study was conducted at a community primary-care clinic that provides free healthcare to impoverished adults.Adults with at least one chronic condition,a minimum of 3rd grade reading level,and without dementia/psychosis were recruited.Participants were given a Nexus7 tablet and Bluetooth self-monitoring devices.The intervention lasted for 12 weeks.Blood glucose,blood pressure,and weight were collected using the provided Bluetooth devices and means were evaluated with paired-samples ttests before and after the intervention.Results:Thirty participants were majority female,white,married,high-school educated or less,earning less than$20,000 per annum,and had multiple chronic conditions.Pre-intervention glucose,systolic blood pressure,diastolic blood pressure,weight and Body Mass Index were all reduced after the 12-week intervention.Conclusions:The mI SMART intervention is efficacious for use in improvised adults living in rural areas with multiple chronic conditions.As previously reported,the intervention was also shown to be feasible and acceptable to patients.The next step is a larger randomized controlled trial.

Dose of Telehealth to Improve Community-Based Care for Adults Living with Multiple Chronic Conditions: A Systematic Review

The purpose of this systematic review is to identify evidence of the appropriate dose of telehealth intervention services provided to community dwelling adults experiencing chronic illness or disability related to effectiveness, quality, safety, and cost. Academic Search Complete, CINAHL, MEDLINE, Cochrane, and JBI were searched using combinations of “telehealth or telemedicine or telemonitoring or telepractice or telenursing or telecare AND chronic illness or chronic disease”. Of the identified 449 articles, 47 articles met the inclusion criteria. Most study designs were quasi-experimental one group pre-test post-test (N = 16) with few Randomized Controlled Trials (N = 12). Twenty-three published articles studied the effect of telehealth for one chronic condition (49.9%) while 24 (51.1%) examined the effectiveness of telehealth for multiple chronic conditions. Measurement of telehealth outcomes varied and included efficacy, healthcare utilization, quality, adherence, cost, and safety. No standard measure of dose could be extrapolated. Length of intervention was measured and reported differently in each study. The dose of telehealth services that improve care effectiveness, quality, safety, and cost is still unknown for community dwelling adults experiencing chronic illness. The findings from this systematic review do indicate that longer duration of telehealth services (51 weeks), regardless of modality, produced positive outcomes as opposed to those with shorter durations (37 - 38 weeks) that produced neutral or mixed results. Collecting and reporting data related to clinical workflow such as dose of intervention specific to disease and type of modality is recommended. Rigorous study design including standard measurement at the RCT and Comparative Effectiveness level is still needed.

Part B: The Feasibility and Acceptability of mI SMART, a Nurse-Led Technology Intervention for Multiple Chronic Conditions

Background: An opportunity to improve care of multiple chronic conditions for those living in rural areas of the country may exist through the use of technology. Integrating technology interventions into existing rural health systems allows for increased access to healthcare services and augments self-management ability for patients. However, questions remain about acceptability and feasibility of technology use in rural populations. The purpose of this paper is to present the feasibility of mI-SMART, a HIPAA compliant, web-based, structure of mHealth sensors and mobile devices designed to overcome the known health determinant of access to care for rural, chronically ill patients by using technology. Methods: The study was conducted at a primary-care clinic that provided healthcare at no or low cost to low income adults. Inclusion criteria encompassed adults, with at least one chronic condition, having at least 3rd grade reading level, without having dementia/psychosis. Each participant was given a Nexus7 tablet and Bluetooth self-monitoring devices. Feasibility was evaluated in four ways and acceptability was evaluated with post-intervention questionnaires. Results: Thirty participants [mean age: 52 years (SD: 10.0, range: 29 - 74)] were majority female (70%), white (70%), married (60%), high-school educated or less (56.7%), impoverished (less than $20,000 per annum (56.7%), with multiple chronic conditions (96.7%)). During the trial, all participants were able to transmit data. No error messages were due to the mI-SMART system. Errors were user related and solved with technical support. Mean number of self-monitor transmissions was 219.7 [(SD: 197.4), range: 1 - 733]. Participants logged into the system an average of 163. 1 [(SD: 169.7), range: 2 - 568] times and viewed an average of 1092.1 [(SD: 1205.6), range: 8 - 3851] intervention components. Over eighty-six percent of participants sent data for 12 weeks and 43.1% used the intervention for longer. Conclusions: The mI-SMART system is a feasible option for impoverished persons living in rural areas.

Part A: The Development of mI SMART, a Nurse-Led Technology Intervention for Multiple Chronic Conditions

Background: The treatment of Multiple Chronic Conditions (MCC) is complex for both patients and providers. Used as integrated tools, technology may decrease complexity, remove the barrier of distance to obtain care, and improve outcomes of care. A new platform that integrates multiple technologies for primary health care called mI SMART (Mobile Improvement of Self-Management Ability through Rural Technology) has been developed. The purpose of this paper is to present to development of mI SMART, a nurse-led technology intervention for treating for MCC in primary care. Methods: The creation of mI SMART was guided by the model for developing complex nursing interventions. The model suggests a process for building and informing interventions with the intention of effectiveness, sustainability, and scalability. Each step in the model builds from and informs the previous step. Results: The process resulted in the integrated technologies of mI SMART. The system combines a HIPAA compliant, web-based, structure of mHealth sensors and mobile devices to treat and monitor multiple chronic conditions within an existing free primary care clinic. The mI SMART system allows patients to track diagnoses, medications, lab results, receive reminders for self-management, perform self-monitoring, obtain feedback in real time, engage in education, and attend visits through video conferencing. The system displays a record database to patients and providers that will be integrated into existing Electronic Health Records. Conclusion: By using the model for developing complex nursing interventions, a multifaceted solution to clinical problems was identified. Through modeling and seeking expert review, we have established a sustainable and scalable integrated nurse-led intervention that may increase access and improve outcomes for patients living in rural and underserved areas. The first trial of mI SMART has been completed and evaluated for feasibility, acceptability, and effectiveness in persons in rural areas living with multiple chronic conditions.

Attention mechanism based multi-scale feature extraction of bearing fault diagnosis

Effective bearing fault diagnosis is vital for the safe and reliable operation of rotating machinery.In practical applications,bearings often work at various rotational speeds as well as load conditions.Yet,the bearing fault diagnosis under multiple conditions is a new subject,which needs to be further explored.Therefore,a multi-scale deep belief network(DBN)method integrated with attention mechanism is proposed for the purpose of extracting the multi-scale core features from vibration signals,containing four primary steps:preprocessing of multi-scale data,feature extraction,feature fusion,and fault classification.The key novelties include multi-scale feature extraction using multi-scale DBN algorithm,and feature fusion using attention mecha-nism.The benchmark dataset from University of Ottawa is applied to validate the effectiveness as well as advantages of this method.Furthermore,the aforementioned method is compared with four classical fault diagnosis methods reported in the literature,and the comparison results show that our pro-posed method has higher diagnostic accuracy and better robustness.

A Numerical Simulation Study of Temperature and Pressure Effects on the Breakthrough Pressure of CO_(2)in Unsaturated Low-permeability Rock Core

Gas breakthrough pressure is a key parameter to evaluate the sealing capacity of caprock,and it also plays important roles in safety and capacity of CO_(2)geological storage.Based on the published experimental results,we present numerical simulations on CO_(2)breakthrough pressure in unsaturated low-permeability rock under 9 multiple P-T conditions(which can keep CO_(2)in gaseous,liquid and supercritical states)and thus,a numerical method which can be used to accurately predict CO_(2)breakthrough pressure on rock-core scale is proposed.The simulation results show that CO_(2)breakthrough pressure and breakthrough time are exponential correlated with P-T conditions.Meanwhile,pressure has stronger effects on experimental results than that of temperature.Moreover,we performed sensitivity studies on the pore distribution indexλ(0.6,0.7,0.8,and 0.9)in van Genuchten-Muale model.Results show that with the increase ofλ,CO_(2)breakthrough pressure and breakthrough time both show decreasing trends.In other words,the larger the value ofλis,the better the permeability of the caprock is,and the worse the CO_(2)sealing capacity is.The numerical method established in this study can provide an important reference for the prediction of gas breakthrough pressure on rock-core scale and for related numerical studies.

Qualitative Algebra and Graph Theory Methods for Dynamic Trend Analysis of Continuous System

Qualitative algebraic equations are the basis of qualitative simulation,which are used to express the dynamic behavior of steady-state continuous processes.When the values and operation of qualitative variables are redefined,qualitative algebraic equations can be transformed into signed direct graphs,which are frequently used to predict the trend of dynamic changes.However,it is difficult to use traditional qualitative algebra methods based on artificial trial and error to solve a complex problem for dynamic trends.An important aspect of modern qualitative algebra is to model and characterize complex systems with the corresponding computer-aided automatic reasoning.In this study,a qualitative affection equation based on multiple conditions is proposed,which enables the signed di-rect graphs to describe complex systems better and improves the fault diagnosis resolution.The application to an industrial case shows that the method performs well.

Compressor geometric uncertainty quantification under conditions from near choke to near stall

Geometric and working condition uncertainties are inevitable in a compressor,deviating the compressor performance from the design value.It’s necessary to explore the influence of geometric uncertainty on performance deviation under different working conditions.In this paper,the geometric uncertainty influences at near stall,peak efficiency,and near choke conditions under design speed and low speed are investigated.Firstly,manufacturing geometric uncertainties are analyzed.Next,correlation models between geometry and performance under different working conditions are constructed based on a neural network.Then the Shapley additive explanations(SHAP)method is introduced to explain the output of the neural network.Results show that under real manufacturing uncertainty,the efficiency deviation range is small under the near stall and peak efficiency conditions.However,under the near choke conditions,efficiency is highly sensitive to flow capacity changes caused by geometric uncertainty,leading to a significant increase in the efficiency deviation amplitude,up to a magnitude of-3.6%.Moreover,the tip leading-edge radius and tip thickness are two main factors affecting efficiency deviation.Therefore,to reduce efficiency uncertainty,a compressor should be avoided working near the choke condition,and the tolerances of the tip leading-edge radius and tip thickness should be strictly controlled.

Development of a region-partitioning method for debris flow susceptibility mapping

Debris flow susceptibility mapping(DFSM)has been reported in many studies,however,the irrational use of the same conditioning factor system for DFSM in regional-scale has not been thoroughly resolved.In this paper,a region-partitioning method that is based on the topographic characteristics of watershed units was developed with the objective of establishing multiple conditioning factor systems for regional-scale DFSM.First,watershed units were selected as the mapping units and created throughout the entire research area.Four topographical factors,namely,elevation,slope,aspect and relative height difference,were selected as the basis for clustering watershed units.The k-means clustering analysis was used to cluster the watershed units according to their topographic characteristics to partition the study area into several parts.Then,the information gain ratio method was used to filter out superfluous factors to establish conditioning factor systems in each region for the subsequent debris flow susceptibility modeling.Last,a debris flow susceptibility map of the whole study area was acquired by merging the maps from all parts.DFSM of Yongji County in Jilin Province,China was selected as a case study,and the analytical hierarchy process method was used to conduct a comparative analysis to evaluate the performance of the region-partitioning method.The area under curve(AUC)values showed that the partitioning of the study area into two parts improved the prediction rate from 0.812 to 0.916.The results demonstrate that the region-partitioning method on the basis of topographic characteristics of watershed units can realize more reasonable regional-scale DFSM.Hence,the developed region-partitioning method can be used as a guide for regional-scale DFSM to mitigate the imminent debris flow risk.

Numerical Simulation of Reiner–Rivlin Nanofluid Flow under the Influence of Thermal Radiation and Activation Energy over a Rotating Disk

In current study,the numerical computations of Reiner–Rivlin nanofluid flow through a rotational disk under the influence of thermal radiation and Arrhenius activation energy is considered.For innovative physical situations,the motile microorganisms are incorporated too.The multiple slip effects are considered in the boundary conditions.The bioconvection of motile microorganism is utilized alongside nanofluids to provide stability to enhanced thermal transportation.The Bioconvection pattern in various nanoparticles accredits novel applications of biotechnology like the synthesis of biological polymers,biosensors,fuel cells,petroleum engineering,and the natural environment.By deploying some suitable similarity transformation functions,the governing partial differential equations(PDEs)of the flow problem are rehabilitated into dimensionless forms.The accomplished ordinary differential equations(ODEs)are solved numerically through the bvp4c scheme via a built-in function in computational MATLAB software.The upshots of some prominent physical and bioconvection parameters including wall slip parameters,thermophoresis parameter,Brownian motion parameter,Reiner–Revlin nanofluid parameter,Prandtl number,Peclet number,Lewis number,bioconvection Lewis number,and the mixed convection parameter against velocity,temperature,nanoparticles concentration,and density of motile microorganism profiles are dichotomized and pondered through graphs and tables.The presented computations show that the velocity profiles are de-escalated by the wall slip parameters while the thermal and solutal fields are upgraded with augmentation in thermophoresis number and wall slip parameters.The presence of thermal radiation enhances the temperature profile of nanofluid.The concentration profile of nanoparticles is boosted by intensification in activation energy.Furthermore,the increasing values of bioconvection Lewis number and Peclet number decay the motile microorganisms’field.

Improved deep residual shrinkage network for a multi-cylinder heavy-duty engine fault detection with single channel surface vibration

The health monitoring and fault diagnosis of heavy-duty engines are increasingly important for energy storage ecosystem. During operation, vibration characters corresponding to the specific fault need to be extracted from the overall system vibration. Faulty characteristics emanating from one single cylinder are also mixed with those from other cylinders. Besides, the change of working condition brings strong nonlinearities in surface vibration. To solve these problems, an improved deep residual shrinkage network (IDRSN) is developed for detecting diverse engine faults at various degrees using single channel surface vibration signal. Within IDRSN, a wide convolution kernel is utilized in first convolution layer to capture the long-term fault-related impacts and eliminate the short-time random impact. The residual network module is adopted to enhance the focus the relevant components of vibration signals. Mini-batch training strategy is used to improve the model stability. Meanwhile, Gradient-weighted class activation map is adopted to assess the consistency between the learned knowledge and the fault-related information. The IDRSN is implemented to diagnosing a diesel engine under various faults, faulty degrees and operating speeds. Comparisons with existing models are analyzed in terms of hyper-parameters, training samples, noise resistance, and visualization. Results demonstrate the proposed IDRSN's superior performance on fault diagnosis accuracy, stability, anti-noise performance, and anti-interference performance. An average accuracy rate of 98.38 % was achieved by the proposed IDRSN, in comparison to 96.64 % and 93.56 % achieved by the DRSN and the wide-kernel deep convolutional neural network respectively. These results highlight the proposed IDRSN's superiority in diagnosing multiple faults under various working conditions, offering a low-cost, highly effective, and applicable approach for complex fault diagnosis tasks.

Necessary and sufficient conditions of the rendezvous between a single spacecraft and three non-coplanar Walker constellation satellites

The probability of the rendezvous between a single spacecraft and three non-coplanar constellation satellites is studied,and the necessary and sufficient conditions of the rendezvous without orbital maneuver are deduced.The rendezvous orbit design can be transformed into the patching of two spacecraft orbits,either of which can achieve the rendezvous with two satellites.Firstly,due to the precious quality of spherical geometry,the unique existence of the rendezvous orbit for two constellation satellites is proved.Then,according to the difference between equispaced and non-equispaced orbital planes of three satellites,the necessary and sufficient conditions are given respectively,and the calculating method of the spacecraft orbit is proposed.At last,the constraint conditions between two different rendezvous orbits is derived,while the relative position of two groups of objects are under specific distribution.The results can be applied to the rendezvous between a single spacecraft and multiple constellation satellites without orbital maneuver.