Analysis of the Application Effect of Family Collaborative Care Model on Elderly Patients with Type 2 Diabetes Mellitus and the Situation of Self-Care Ability

Objective: To study the application effect of the family collaborative care model on elderly patients with type 2 diabetes mellitus and its influence on self-care ability. Methods: The elderly type 2 diabetes mellitus patients (400 cases) treated in our hospital between March 2020 and July 2023 were divided into two groups by randomized grouping method;the control group received the conventional nursing program, while the observation group received the family collaborative nursing model. Blood glucose level, self-care ability, and quality of life were compared between the groups. Results: The blood glucose level of the observation group was lower than that of the control group (P < 0.05). The self- care ability and quality of life scores of the observation group were higher than those of the control group (P < 0.05). Conclusion: The family collaborative care model for elderly patients with type 2 diabetes mellitus can promote their self- care ability, improve the effect of glycemic control, and improve their quality of life, and is suitable for further promotion and application.

A Collaboration Network Model with Multiple Evolving Factors

To describe the empirical data of collaboration networks, several evolving mechanisms have been proposed, which usually introduce different dynamics factors controlling the network growth. These models can reasonably reproduce the empirical degree distributions for a number of we11-studied real-world collaboration networks. On the basis of the previous studies, in this work we propose a collaboration network model in which the network growth is simultaneously controlled by three factors, including partial preferential attachment, partial random attachment and network growth speed. By using a rate equation method, we obtain an analytical formula for the act degree distribution. We discuss the dependence of the act degree distribution on these different dynamics factors. By fitting to the empirical data of two typical collaboration networks, we can extract the respective contributions of these dynamics factors to the evolution of each networks.

Collaborative optimization model of renewable energy development considering peak shaving costs of various flexibility resources

China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of new energies is the limited flexibility of regulations on power system resources,resulting in insufficient consumption capacity.Thus,the flexible resource costs for peak shaving as well as the reasonable coordinated development and operation optimization of regional renewable energy need to be considered.In this study,a renewable energy development layout configuration analysis method was established by considering the composite cost of a power system,comprehensively analyzing the potential of various flexibility regulation resources for the power system and its composite peak shaving cost,and combining renewable energy output characteristics,load forecasting,grid development,and other factors.For the optimization of various flexible resource utilization methods,a peak shaving cost estimation method from the perspective of the entire power system was established by combining the on-grid electricity prices and operating costs of different power sources.A collaborative optimization model of power system operation that aims at the lowest peak shaving cost and satisfies the constraints of operation,safety,and environmental protection was proposed.Finally,a certain area of Gansu Province was used as an example to perform detailed analysis and calculation,which demonstrated that the model has an optimal effect.This model can provide an analysis method for regional renewable energy development layout configurations and system optimization operations.

Recommendation algorithm of cloud computing system based on random walk algorithm and collaborative filtering model

The traditional collaborative filtering recommendation technology has some shortcomings in the large data environment. To solve this problem, a personalized recommendation method based on cloud computing technology is proposed. The large data set and recommendation computation are decomposed into parallel processing on multiple computers. A parallel recommendation engine based on Hadoop open source framework is established, and the effectiveness of the system is validated by learning recommendation on an English training platform. The experimental results show that the scalability of the recommender system can be greatly improved by using cloud computing technology to handle massive data in the cluster. On the basis of the comparison of traditional recommendation algorithms, combined with the advantages of cloud computing, a personalized recommendation system based on cloud computing is proposed.

Assessing the host genetic background effects on type 2 diabetes and obesity development in response to mixed–oral bacteria and high-fat diet using the collaborative cross mouse model

Background: Host genetic background and sex, play central roles in defining the pathogenesis of type 2 diabetes(T2 D), obesity and infectious diseases. Our previous studies demonstrated the utilization of genetically highly diverse inbred mouse lines, namely collaborative cross(CC), for dissecting host susceptibility for the development of T2 D and obesity, showing significant variations following high-fat(42% fat) diet(HFD). Here, we aimed to assessing the host genetic background and sex effects on T2 D and obesity development in response to oral-mixed bacterial infection and HFD using the CC lines.Materials and Methods: Study cohort consists of 97 mice from 2 CC lines(both sexes), maintained on either HFD or Standard diet(CHD) for 12 weeks. At week 5 a group of mice from each diet were infected with Porphyromonas gingivalis(Pg) and Fusobacterium nucleatum(Fn) bacteria(control groups without infection). Body weight(BW) and glucose tolerance ability were assessed at the end time point of the experiment.Results: The CC lines varied(P <.05) at their BW gain and glucose tolerance ability(with sex effect) in response to diets and/or infection, showing opposite responses despite sharing the same environmental conditions. The combination of diet and infection enhances BW accumulation for IL1912, while restraints it for IL72. As for glucose tolerance ability, only females(both lines) were deteriorated in response to infection.Conclusions: This study emphasizes the power of the CC mouse population for the characterization of host genetic makeup for defining the susceptibility of the individual to development of obesity and/or impaired glucose tolerance.

A Platform for Collaborative Modeling

A collaborative virtual modeling environment based on VRML is presented as a sugarcane harvester modeling framework, and is illustrated with the implemented software that can using I;EAS, Smarteam, and Conceptual Innovation Design System （CIDS） as the supporting platform, which is powerful enough to meet the demands of different real life applications. It is possible to perform collaborative interactive modifications with concurrent synchronous visualization at each client computer with any required level of detail. The platform provides a product modeling and assembling environment, and the product data among I;EAS, Smarteam and CIDS can be exchanged.

The Effectiveness of a Multidisciplinary Collaborative Model for the Diagnosis and Treatment of Vertigo

Objective:To investigate the effectiveness of applying a multidisciplinary collaborative model for the diagnosis and treatment of patients with vertigo.Methods:The study was carried out in Xianyang Hospital of Yan’an University,in which 100 patients with vertigo were selected from April 2021 to April 2022 and were divided into two groups:the control group was under the single diagnosis and treatment model,whereas the experimental group was under the multidisciplinary collaborative diagnosis and treatment model,with 50 cases in each group.The diagnostic effects of the two groups were compared.Results:The diagnostic and therapeutic efficiency of the patients in the experimental group were 94%and 98%,respectively,while those of the patients in the control group were 78%and 82%,respectively,with a significant difference between the two groups(p<0.05).The balance scores of the patients in both groups were low before the treatment,in which the difference was not significant(p>0.05);after the treatment,the scores improved,with those of the patients in the experimental group being significantly higher than those in the control group(p<0.05).Moreover,the satisfaction rate of patients in the experimental group(98%)was significantly higher than that of the control group(80%)(p<0.05).Conclusion:The application of the multidisciplinary collaborative diagnosis and treatment model in the diagnosis of patients with vertigo is effective.The multidisciplinary model can improve clinical diagnosis,enhance the treatment effect,improve the clinical symptoms of patients,and increase the satisfaction of patient care.Hence,it is of high clinical application value.

Lowering fasting blood glucose with non-dialyzable material of cranberry extract is dependent on host genetic background,sex and diet

Background:Type 2 diabetes(T2D)is a polygenic metabolic disease,character-ized by high fasting blood glucose(FBG).The ability of cranberry(CRN)fruit to regulate glycemia in T2D patients is well known.Here,a cohort of 13 lines of the genetically diverse Collaborative Cross(CC)mouse model was assessed for the effect of non-dialyzable material(NDM)of cranberry extract in lowering fasting blood glucose.Methods:Eight-week-old mice were maintained on either a standard chow diet(con-trol group)or a high-fat diet(HFD)for 12 weeks,followed by injections of intraperi-toneal(IP)NDM(50 mg/kg)per mouse,three times a week for the next 6 weeks.Absolute FBG(mg/dl)was measured bi-weekly and percentage changes in FBG(%FBG)between weeks 0 and 12 were calculated.Results:Statistical analysis showed a significant decrease in FBG between weeks 0 and 12 in male and female mice maintained on CHD.However,a non-significant in-crease in FBG values was observed in male and female mice maintained on HFD dur-ing the same period.Following administration of NDM during the following 6 weeks,the results show a variation in significant levels of FBG lowering between lines,male and female mice and under the different diets.Conclusion:The results suggest that the efficacy of NDM treatment in lowering FGB depends on host genetic background(pharmacogenetics),sex of the mouse(phar-macosex),and diet(pharmacodiet).All these results support the need for follow-up research to better understand and implement a personalized medicine approach/uti-lization of NDM for reducing FBG.

Enhancing Collaborative Talent Development:A Two-Tutor System Model for Chinese Universities and Enterprises

This paper explores the collaboration between P University in Guangzhou and Guangdong enterprises for talent development,utilizing a phenomenological research approach.The study includes participants from students,teachers,and enterprise employees.It uncovers challenges such as differing talent development philosophies,a gap between university education and practical teaching,and an imbalance between theoretical knowledge and practical skills.The paper proposes solutions,emphasizing the need for urgent action to drive educational reform.It also highlights the benefits for students,school administrators,and enterprises.The research methodology,data collection,and analysis process are detailed.The aim is to provide theoretical support for enhancing cooperation between education and industry.

构建“合作主义”社会保障模式的途径探讨——以非营利组织发展为视角

试图探讨在我国社会保障制度的转型时期 ,面临社会保障需求的多元化转变 ,非营利组织作为一股新兴力量构建“合作主义”的社会保障模式的必要性 ,并且分析了现行的制度环境需做出的相应转变的可行途径。

Erectile dysfunction: on the efficacy of a phosphodiesterase inhibitor with concurrent sex therapy

1 Introduction Erectile dysfunction (ED) is a condition that affects perhaps 25 to 30 million men in the U.S.A. constituting

Multi-Dimension Support Vector Machine Based Crowd Detection and Localisation Framework for Varying Video Sequences

In this paper, we propose a novel method for anomalous crowd behaviour detection and localization with divergent centers in intelligent video sequence through multiple SVM (support vector machines) based appearance model. In multi-dimension SVM crowd detection, many features are available to track the object robustly with three main features which include 1) identification of an object by gray scale value, 2) histogram of oriented gradients (HOG) and 3) local binary pattern (LBP). We propose two more powerful features namely gray level co-occurrence matrix (GLCM) and Gaber feature for more accurate and authenticate tracking result. To combine and process the corresponding SVMs obtained from each features, a new collaborative strategy is developed on the basis of the confidence distribution of the video samples which are weighted by entropy method. We have adopted subspace evolution strategy for reconstructing the image of the object by constructing an update model. Also, we determine reconstruction error from the samples and again automatically build an update model for the target which is tracked in the video sequences. Considering the movement of the targeted object, occlusion problem is considered and overcome by constructing a collaborative model from that of appearance model and update model. Also if update model is of discriminative model type, binary classification problem is taken into account and overcome by collaborative model. We run the multi-view SVM tracking method in real time with subspace evolution strategy to track and detect the moving objects in the crowded scene accurately. As shown in the result part, our method also overcomes the occlusion problem that occurs frequently while objects under rotation and illumination change due to different environmental conditions.

Multi-view collaborative modeling method for complex system

It is hard to model a complex system by simply combining its partial characteristics.This paper presents a multi-view collaborative modeling method for complex system.Multi users,multi subjects,multi granularities and multi models in complex system modeling are unified to multi views.The principles and schemes for the decomposition of complex systems are introduced.According to the principle of separation of concerns,a complex system can be decomposed to a variety of model views.Collaborative modeling means that the views can be associated and integrated to form complete system model through their semantic.According to the form of representation,the models are generalizes to three kinds,i.e.,view models,semantic models and storage models,which provides a unified framework for conversion and mapping between the models.Under the guidance of the method,a tool for the modeling of warship C2 system is developed.Applications show that the tool can support collaborative modeling and design for C2 system outstandingly.

Preference transfer model in collaborative filtering for implicit data

Generally, predicting whether an item will be liked or disliked by active users, and how much an item will be liked, is a main task of collaborative filtering systems or recommender systems. Recently, predicting most likely bought items for a target user, which is a subproblem of the rank problem of collaborative filtering, became an important task in collaborative filtering. Traditionally, the prediction uses the user item co-occurrence data based on users' buying behaviors. However, it is challenging to achieve good prediction performance using traditional methods based on single domain information due to the extreme sparsity of the buying matrix. In this paper, we propose a novel method called the preference transfer model for effective cross-domain collaborative filtering. Based on the preference transfer model, a common basis item-factor matrix and different user-factor matrices are factorized.Each user-factor matrix can be viewed as user preference in terms of browsing behavior or buying behavior. Then,two factor-user matrices can be used to construct a so-called ‘preference dictionary' that can discover in advance the consistent preference of users, from their browsing behaviors to their buying behaviors. Experimental results demonstrate that the proposed preference transfer model outperforms the other methods on the Alibaba Tmall data set provided by the Alibaba Group.

A virtual learning environment of the Chinese University of Hong Kong

This paper introduces a scalable virtual learning environment of the ChineseUniversity of Hong Kong;an explicitly geographical, immersive, and sharable 3Dlearning space with comprehensive social elements. It is characterized by multiuser collaborative modeling, group learning approaches of geo-collaboration,social space-oriented hierarchical avatars, and knowledge exchanging and sharingbased on virtual geographic experiments. Applications for the purpose of publiceducation and virtual geographic experiment, and indicated future works provethe possibility to offer a greater opportunity to foster interdisciplinary collaborations, revitalize teaching patterns and learning contents, improve learners’cognitive abilities to solve problems, and enhance their understanding of scientificconcepts and processes.

Reality-Virtuality Fusional Campus Environment:An Online 3D Platform Based on OpenSimulator

This paper presents a reality-virtual fusional campus environment.It is an online 3D platform with some aspects of real information merged together.The whole platform is based on OpenSimulator with detailed geo-models to represent the university campus.Some preliminary experiments were done to integrate the realistic information with the virtual campus for making the geo-environment not only with detailed indoor and outdoor models,but also with the real representations of the physical world.The overall motivation is to provide a framework with strong support for reality-virtuality fusional modeling in a collaborative 3D online platform for research purposes.