Impact of a mobile health intervention based on multi-theory model of health behavior change on self-management in patients with differentiated thyroid cancer: protocol for a randomized controlled trial

IntroductionTheoretical models of health behavior are important guides for disease prevention and detection, treatment and rehabilitation, and promotion and maintenance of physical and mental health, but there are no intervention studies related to differentiated thyroid cancer (DTC) that use theoretical models of health as a guide. In this study, we used a microblogging platform as an intervention vehicle and mobile patient-doctor interactive health education as a means of intervention, with the aim of improving the health behaviors of DTC patients as well as the corresponding clinical outcomes.MethodsThis research project is a quantitative methodological study, and the trial will be a single-blind, single-center randomized controlled trial conducted at the Fourth Hospital of Harbin Medical University in Harbin, Heilongjiang Province. The study subjects are patients over 18 years of age with differentiated thyroid cancer who were given radioactive iodine-131 therapy as well as endocrine therapy after radical surgery for thyroid cancer. The intervention group will receive MTM-mhealth, and the realization of health education will rely on the smart terminal WeChat platform. Routine discharge education will be given to the control group at discharge. The primary outcome will be change in thyroid-stimulating hormone (TSH) from baseline and at 3 and 6 months of follow-up, and secondary outcomes will include change in self-management behavior, social cognitive and psychological, and metabolic control.DiscussionThis study will explore a feasible mHealth intervention program applied to a population of DTC patients using the Multi-theory model of health behavior change (MTM) as a guide, with the aim of evaluating the MTM-based intervention program for clinical outcome improvement in DTC patients, as well as determining the effectiveness of the MTM-based intervention program in improving self-management skills in DTC patients. The results of this study will indicate the feasibility as well as the effectiveness of the application of health theoretical modeling combined with mHealth applications in disease prognostic health management models, and provide policy recommendations and technological translations for the development of mobility-based health management applications in the field of health management

Therapy-induced tumour secretomes promote resistance and tumour progression.

Drug resistance invariably limits the clinical efficacy of targeted therapy with kinase inhibitors against cancer. Here we show that targeted therapy with BRAF, ALK or EGFR kinase inhibitors induces a complex network of secreted signals in drug-stressed human and mouse melanoma and human lung adenocarcinoma cells. This therapy-induced secretome stimulates the outgrowth, dissemination and metastasis of drug-resistant cancer cell clones and supports the survival of drug-sensitive cancer cells, contributing to incomplete tumour regression. The tumour-promoting secretome of melanoma cells treated with the kinase inhibitor vemurafenib is driven by downregulation of the transcription factor FRA1. In situ transcriptome analysis of drug-resistant melanoma cells responding to the regressing tumour microenvironment revealed hyperactivation of several signalling pathways, most prominently the AKT pathway. Dual inhibition of RAF and the PI(3)K/AKT/mTOR intracellular signalling pathways blunted the outgrowth of the drug-resistant cell population in BRAF mutant human melanoma, suggesting this combination therapy as a strategy against tumour relapse. Thus, therapeutic inhibition of oncogenic drivers induces vast secretome changes in drug-sensitive cancer cells, paradoxically establishing a tumour microenvironment that supports the expansion of drug-resistant clones, but is susceptible to combination therapy

Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction

Problems exist in power grid data management that have unclear relationships, weak security and low accuracy. By analysing the knowledge graph construction characteristics of smart grid data information and knowledge extraction, the grid data management platform is reshaped architecturally, and the knowledge graph construction technology is embedded in the grid data management framework. For the aforementioned problems, the knowledge graph construction and Internet of Things optimisation framework of power grid data knowledge extraction are proposed in this article. Firstly, the semantic search (KGSS) algorithm based on the knowledge graph is used. The KGSS algorithm extracts knowledge from structured, semi-structured and unstructured grid data through the massively parallel processing acquisition model and Hadoop database, and constructs knowledge entities, attributes and inter-entity relationships. Then, it optimises and predicts through the knowledge graph construction and Internet of Things optimisation framework extracted from power grid data knowledge. Finally, the experimental results show that the accuracy rate of the KGSS algorithm is 92%. The experimental results also show that it provides new ideas and research directions for power grid data under big data in the future

A Decision-Making Method for Landing Routes of Aircraft on the Carrier

The landing safety of aircraft is of great significance for the normal operation of an aircraft carrier. This paper presents an optimal method for landing routes of aircraft. Owing to the fuzziness of environmental information and human judgment, a decision-making method is introduced to reduce the workload of landing console operators (LCO). Specifically, a route option method for aircraft landing is proposed based on Fuzzy Multi-attribute Group Decision Making (FMAGDM). Firstly, the route option problem is described. Then the essential elements of route option are described. A group decision-making method is proposed, and the most reasonable landing route in current environment is obtained considering the knowledge composition and the weight of each decision maker. Finally, simulations under different environments are conducted. The results indicate that the decision-making method is able to adapt to the environment changes, and determine the most reasonable route for each validation case

A Decision-Making Method for Landing Routes of Aircraft on the Carrier

The landing safety of aircraft is of great significance for the normal operation of an aircraft carrier. This paper presents an optimal method for landing routes of aircraft. Owing to the fuzziness of environmental information and human judgment, a decision-making method is introduced to reduce the workload of landing console operators (LCO). Specifically, a route option method for aircraft landing is proposed based on Fuzzy Multi-attribute Group Decision Making (FMAGDM). Firstly, the route option problem is described. Then the essential elements of route option are described. A group decision-making method is proposed, and the most reasonable landing route in current environment is obtained considering the knowledge composition and the weight of each decision maker. Finally, simulations under different environments are conducted. The results indicate that the decision-making method is able to adapt to the environment changes, and determine the most reasonable route for each validation case

Computational Simulations of Fabrication of Aluminum-Based Josephson Junctions: Topological Aspects of the Barrier Structure

Although the performance of qubits has been improved in recent years, the differences in the microscopic atomic structure of the Josephson junctions, the core devices prepared under different preparation conditions, are still underexplored. In this paper, the effects of the oxygen temperature and upper aluminum deposition rate on the topology of the barrier layer in the aluminum-based Josephson junctions have been presented by classical molecular dynamics simulations. We apply a Voronoi tessellation method to characterize the topology of the interface and central regions of the barrier layers. We find that when the oxygen temperature is 573 K and the upper aluminum deposition rate is 4 Å/ps, the barrier has the fewest atomic voids and the most closely arranged atoms. However, if only the atomic arrangement of the central region is considered, the optimal rate of the aluminum deposition is 8 Å/ps. This work provides microscopic guidance for the experimental preparation of Josephson junctions, which helps to improve the performance of qubits and accelerate the practical application of quantum computers

Aeration strength analysis of overflow weir in siphon well based on numerical simulation of water–air two‐phase flow

Abstract The phenomenon of water aeration is serious after the overflow weir in the siphon well at the cooling water circulation system of coastal power plants. At present, designing special hydraulic structures is an effective way to reduce the intensity of aeration. In this paper, three engineering structure schemes were designed, and the three‐dimensional Realizable k–ε turbulence model was used. The volume of fluid method was introduced to capture the free water surface, and the unstructured grid was used to construct the two‐phase turbulent flow field. The aeration concentration and pressure distribution, obtained by numerical simulation, were basically consistent with the physical model test results. The results showed that the flow field at the orifice plates of cases 1 and 2 changed drastically, and the turbulent kinetic energy downstream of the orifice plate decreased with the increase of the number of holes. As for case 3, it showed that the high‐speed water flow fell into the water cushion pool, tumbling and sucking up a lot of air, and the turbulent kinetic energy and Reynolds stress were significantly greater than the other two cases. The hydraulic structure changed the cavitation characteristics of the downflow water, and the sequence of aeration concentration of the horizontal section was case 3 > case 1 > case 2. The aeration concentration was only 9.18%–17.86% in case 2. The aeration concentration at stable time is expressed as a function of the relative water depth y/y90 and the turbulent diffusion coefficient D. The distribution formula of aeration concentration was established, and its validity was verified by literatures. The results of this study will provide a certain reference for in‐depth analysis of water–air mixing motion characteristics, and simultaneously, it will have a guiding significance for the design of siphon well defoaming engineering

Computational Simulations of Fabrication of Aluminum-Based Josephson Junctions: Topological Aspects of the Barrier Structure

Although the performance of qubits has been improved in recent years, the differences in the microscopic atomic structure of the Josephson junctions, the core devices prepared under different preparation conditions, are still underexplored. In this paper, the effects of the oxygen temperature and upper aluminum deposition rate on the topology of the barrier layer in the aluminum-based Josephson junctions have been presented by classical molecular dynamics simulations. We apply a Voronoi tessellation method to characterize the topology of the interface and central regions of the barrier layers. We find that when the oxygen temperature is 573 K and the upper aluminum deposition rate is 4 Å/ps, the barrier has the fewest atomic voids and the most closely arranged atoms. However, if only the atomic arrangement of the central region is considered, the optimal rate of the aluminum deposition is 8 Å/ps. This work provides microscopic guidance for the experimental preparation of Josephson junctions, which helps to improve the performance of qubits and accelerate the practical application of quantum computers