The Construction of Integrated Nursing Model Prevention of Oxaliplatin Chemotherapy-Induced Peripheral Nerve Injury

Objective: To investigate the effect of the integrated nursing model in the prevention of chemotherapy-induced peripheral injury. Methods: A total of 60 tumor patients receiving oxaliplatin for 1 - 6 cycles of chemotherapy from January to September 2023 were selected. 30 patients were selected from January to March and divided into the control group, and 30 patients were selected from July to 9 as the experimental group. The control group received conventional chemotherapy nursing, while the experimental group received integrated nursing. Anxiety, peripheral nerve toxicity stage and quality of life score were compared between the two groups before and after intervention. Results: After intervention, the scores of the self-rating Anxiety Scale (SAS) and the total scores of the oxaliplatin Levi specific sensory neurotoxicity scale in the experimental group were significantly lower than those in the control group, and the differences were statistically significant (P< 0.05);The Quality of Life Scale (FACT-G) score of cancer patients was higher than that of control group, and the difference was statistically significant (P< 0.05). Conclusion: The integrated nursing model can effectively reduce the anxiety of patients, reduce the incidence of peripheral nerve injury and improve the quality of life of patients.

Analysis of the Effect of Integrated Extended Care Model in Improving the Quality of Life of Elderly Patients with Type 2 Diabetes Mellitus

Objective: To analyze the impact of an integrated extended care model on improving the quality of life of elderly patients with Type 2 Diabetes Mellitus (T2DM). Methods: A total of 176 patients admitted to the hospital from March 2015 to February 2018 were selected and randomly assigned to an observation group and a control group, with 88 patients each. The control group implemented conventional nursing interventions, and the observation group carried out an integrated extended-care model. The level of glycemic control, quality of life, and daily medication adherence between both groups were compared. Results: The observation group showed significant improvement in the level of glycemic control, and their fasting blood glucose, 2-hour postprandial blood glucose, and glycated hemoglobin levels were significantly lower as compared with those in the study group (P < 0.05). The quality of life of the patients in the observation group was higher than that of the control group (P < 0.05). The observation group had a higher compliance score (95.48 ± 7.45) than the control group (81.31 ± 8.72) (t = 8.909, P < 0.05). Conclusion: The integrated extended care model allows patients to receive comprehensive and individualized nursing services after discharge, which improves the effect of drug therapy and the quality of life of patients.

The Model of“Post,Course,Competition,Certificate”Integrated Education for Electronic Information Engineering Technology Major in Higher Vocational Colleges

The core education function of higher vocational colleges is to train technical talents with high quality,so as to meet the needs of talents in the development stage of our society.Under the guidance of talent training,higher vocational colleges need to pay attention to establishing an all-round and three-dimensional education model,and promote innovation of higher vocational education on the basis of this.It is also a way to promote the innovation of higher vocational education to vigorously promote the construction of“post,course,competition,certificate”mode in the construction of education mode.Through the construction of“post,course,competition,certificate”mode,the education mode of higher vocational colleges is gradually improved,so as to strengthen the effectiveness of talent training in higher vocational colleges.Therefore,in this paper,the author puts forward some suggestions to promote the construction of the integrated education mode of the electronic information engineering technology major in higher vocational colleges,so as to help improve the talent training level of higher vocational colleges.

U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies

El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict it.In some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of research.This study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as ICM-UNet.The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific.In the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO events.These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies.Furthermore,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.

Integrated analysis of plasma rotation effect on HL-3 hybrid scenario

The hybrid scenario,which has good confinement and moderate MHD instabilities,is a proposed operation scenario for international thermonuclear experimental reactor(ITER).In this work,the effect of plasma rotation on the HL-3 hybrid scenario is analyzed with the integrated modeling framework OMFIT.The results show that toroidal rotation has no obvious effect on confinement with a high line averaged density of n_(bar)~(7)×10^(19)m^(-3).In this case,the ion temperature only changes from 4.7 keV to 4.4 keV with the rotation decreasing from 10^(5) rad/s to 10^(3) rad/s,which means that the turbulent heat transport is not dominant.While in the scenarios characterized by lower densities,such as n_(bar)~4×10^(19)m^(-3),turbulent transport becomes dominant in determining heat transport.The ion temperature rises from 3.8 keV to 6.1 keV in the core as the rotation velocity increases from 10^(3) rad/s to 10^(5) rad/s.Despite the ion temperature rising,the rotation velocity does not obviously affect electron temperature or density.Additionally,it is noteworthy that the variation in rotation velocity does not significantly affect the global confinement of plasma in scenarios with low density or with high density.

Application of multidisciplinary team-based integrated traditional Chinese medicine and Western medicine in rotator cuff injury patients undergoing arthroscopic surgery

BACKGROUND Arthroscopic rotator cuff repair is a common surgical treatment for rotator cuff injuries(RCIs).Although this procedure has certain clinical advantages,it requires rehabilitation management interventions to ensure therapeutic efficacy.AIM To investigate the effect of integrated traditional Chinese medicine and Western medicine(TCM-WM)under the multidisciplinary team(MDT)model on the postoperative recovery of patients undergoing arthroscopic surgery for RCIs.METHODS This study enrolled 100 patients who underwent arthroscopic rotator cuff repair for RCIs at the Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine between June 2021 and May 2024.They were divided into a control group(n=48)that received routine rehabilitation treatment and an experimental group(n=52)that received TCM-WM under the MDT model(e.g.,acupuncture,TCM traumatology and orthopedics,and rehabilitation).The results of the Constant–Murley Shoulder Score(CMS),Visual Analogue Scale(VAS),Shoulder Pain and Disability Index(SPADI),muscular strength evaluation,and shoulder range of motion(ROM)assessments were analyzed.RESULTS After treatment,the experimental group showed significantly higher CMS scores in terms of pain,functional activity,shoulder joint mobility,and muscular strength than the baseline and those of the control group.The experimental group also exhibited significantly lower VAS and SPADI scores than the baseline and those of the control group.In addition,the experimental group showed significantly enhanced muscular strength(forward flexor and external and internal rotator muscles)and shoulder ROM(forward flexion,abduction,and lateral abduction)after treatment compared with the control group.CONCLUSION TCM-WM under the MDT model improved shoulder joint function,relieved postoperative pain,promoted postoperative functional recovery,and facilitated the recovery of muscular strength and shoulder ROM in patients with RCIs who underwent arthroscopic rotator cuff repair.

Exploration of the Construction and Path Selection of the Deep Integration Model of Industry-Education in Universities

Against the backdrop of continuous development in the field of education,universities are encouraged to innovate their talent cultivation systems and objectives.The deep integration of industry and education has emerged as an effective strategy,aligning with the basic requirements of the new engineering education initiative and exerting a positive impact on socioeconomic development.However,an analysis of the current state of industry-education integration in universities reveals several issues that require optimization,affecting the ultimate effectiveness of integration.To optimize this phenomenon and achieve high-quality development,universities need to further explore the construction of a deep integration model of industry and education,adhering to corresponding principles to form a comprehensive system.On this basis,pathways for deep industry-education integration can be summarized.

APPLICATION OF HYBRID AERO-ENGINE MODEL FOR INTEGRATED FLIGHT/PROPULSION OPTIMAL CONTROL

The real-time capability of integrated flight/propulsion optimal control （IFPOC） is studied. An appli- cation is proposed for IFPOC by combining the onboard hybrid aero-engine model with sequential quadratic pro- gramming （SQP）. Firstly, a steady-state hybrid aero-engine model is designed in the whole flight envelope with a dramatic enhancement of real-time capability. Secondly, the aero-engine performance seeking control including the maximum thrust mode and the minimum fuel-consumption mode is performed by SQP. Finally, digital simu- lations for cruise and accelerating flight are carried out. Results show that the proposed method improves real- time capability considerably with satisfactory effectiveness of optimization.

A Thermal-Conscious Integrated Circuit Power Model and Its Impact on Dynamic Voltage Scaling Techniques

We propose a novel thermal-conscious power model for integrated circuits that can accurately predict power and temperature under voltage scaling. Experimental results show that the leakage power consumption is underestimated by 52 % if thermal effects are omitted. Furthermore, an inconsistency arises when energy and temperature are simultaneously optimized by dynamic voltage scaling. Temperature is a limiting factor for future integrated circuits,and the thermal optimization approach can attain a temperature reduction of up to 12℃ with less than 1.8% energy penalty compared with the energy optimization one.

Dynamic stability analysis of porous functionally graded beams under hygro-thermal loading using nonlocal strain gradient integral model

We present a study on the dynamic stability of porous functionally graded(PFG)beams under hygro-thermal loading.The variations of the properties of the beams across the beam thicknesses are described by the power-law model.Unlike most studies on this topic,we consider both the bending deformation of the beams and the hygro-thermal load as size-dependent,simultaneously,by adopting the equivalent differential forms of the well-posed nonlocal strain gradient integral theory(NSGIT)which are strictly equipped with a set of constitutive boundary conditions(CBCs),and through which both the stiffness-hardening and stiffness-softening effects of the structures can be observed with the length-scale parameters changed.All the variables presented in the differential problem formulation are discretized.The numerical solution of the dynamic instability region(DIR)of various bounded beams is then developed via the generalized differential quadrature method(GDQM).After verifying the present formulation and results,we examine the effects of different parameters such as the nonlocal/gradient length-scale parameters,the static force factor,the functionally graded(FG)parameter,and the porosity parameter on the DIR.Furthermore,the influence of considering the size-dependent hygro-thermal load is also presented.

DATA MODEL AND VISUALIZATION OF 3D CITY LANDSCAPE BASED ON INTEGRATED DATABASES

Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since the data volume of raster are very huge, special strategies(for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.

An Introduction to the Integrated Climate Model of the Center for Monsoon System Research and Its Simulated Influence of El Ni?no on East Asian–Western North Pacific Climate

This study introduces a new global climate model--the Integrated Climate Model （ICM）--developed for the seasonal prediction of East Asian-western North Pacific （EA-WNP） climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics （CMSR, IAP）, Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of E1 Nifio as one of the most important factors on EA-WNP climate. ICM successfully reproduces the distribution of sea surface temperature （SST） and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA-WNP climate E1 Nifio and the East Asia-Pacific Pattern--are also well simulated in ICM, with realistic spatial pattern and period. The simulated E1 Nifio has significant impact on EA-WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA-WNP climate.

Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed,Gansu Province,China

Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups,(i) training dataset and(ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages,distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.

An integrated modeling method for prediction of sulfur content in agglomerate

Based on the idea of fusing modeling, an integrated prediction model for sintering process was proposed. A framework for sulfur content prediction was established, which integrated multi modeling ways together, including mathematical model combined with neural network(NN), rule model based on empirical knowledge and model-choosing coordinator. Via metallurgic mechanism analysis and material balance computation, a mathematical model calculated the sulfur content in agglomerate by the material balance equation with some parameters predicted by NN method. In the other model, the relationship between sulfur content and key factors was described in the form of expert rules. The model-choosing coordinator based on fuzzy logic was introduced to decide the weight of result of each model according to process conditions. The model was tested by industrial application data and produced a relatively satisfactory prediction error. The model also preferably reflected the varying tendency of sulfur content in agglomerate as the evidence of its prediction performance.

Multi-modal Gesture Recognition using Integrated Model of Motion, Audio and Video

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Discretization Approach in Integrated Hydrologic Model for Surface and Groundwater Interaction

The commonly used discretization approaches for distributed hydrological models can be broadly categorized into four types,based on the nature of the discrete components:Regular Mesh,Triangular Irregular Networks(TINs),Representative Elementary Watershed(REWs) and Hydrologic Response Units(HRUs).In this paper,a new discretization approach for landforms that have similar hydrologic properties is developed and discussed here for the Integrated Hydrologic Model(IHM),a combining simulation of surface and groundwater processes,accounting for the interaction between the systems.The approach used in the IHM is to disaggregate basin parameters into discrete landforms that have similar hydrologic properties.These landforms may be impervious areas,related areas,areas with high or low clay or organic fractions,areas with significantly different depths-to-water-table,and areas with different types of land cover or different land uses.Incorporating discrete landforms within basins allows significant distributed parameter analysis,but requires an efficient computational structure.The IHM integration represents a new approach interpreting fluxes across the model interface and storages near the interface for transfer to the appropriate model component,accounting for the disparate discretization while rigidly maintaining mass conservation.The discretization approaches employed in IHM will provide some ideas and insights which are helpful to those researchers who have been working on the integrated models for surface-groundwater interaction.

A unified model for diagnosing energy usage abnormalities in regional integrated energy service systems

An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling. To reduce energy wastage and increase energy utilization, it is necessary to perform efficiency analyses and diagnoses on integrated energy systems(IESs). However, the integrated energy data necessary for energy efficiency analyses and diagnoses come from a wide variety of instruments, each of which uses different transmission protocols and data formats. This makes it challenging to handle energy-flow data in a unified manner. Thus, we have constructed a unified model for diagnosing energy usage abnormalities in IESs. Using this model, the data are divided into working days and non-working days, and benchmark values are calculated after the data have been weighted to enable unified analysis of several types of energy data. The energy-flow data may then be observed, managed, and compared in all aspects to monitor sudden changes in energy usage and energy wastage. The abnormal data identified and selected by the unified model are then subjected to big-data analysis using technical management tools, enabling the detection of user problems such as abnormalities pertaining to acquisition device, metering, and energy usage. This model facilitates accurate metering of energy data and improves energy efficiency. The study has significant implications in terms of fulfilling the energy saving.

Application of Seasonal Auto-regressive Integrated Moving Average Model in Forecasting the Incidence of Hand-foot-mouth Disease in Wuhan,China

Outbreaks of hand-foot-mouth disease（HFMD） have occurred many times and caused serious health burden in China since 2008. Application of modern information technology to prediction and early response can be helpful for efficient HFMD prevention and control. A seasonal auto-regressive integrated moving average（ARIMA） model for time series analysis was designed in this study. Eighty-four-month（from January 2009 to December 2015） retrospective data obtained from the Chinese Information System for Disease Prevention and Control were subjected to ARIMA modeling. The coefficient of determination（R^2）, normalized Bayesian Information Criterion（BIC） and Q-test P value were used to evaluate the goodness-of-fit of constructed models. Subsequently, the best-fitted ARIMA model was applied to predict the expected incidence of HFMD from January 2016 to December 2016. The best-fitted seasonal ARIMA model was identified as（1,0,1）（0,1,1）12, with the largest coefficient of determination（R^2=0.743） and lowest normalized BIC（BIC=3.645） value. The residuals of the model also showed non-significant autocorrelations（P_（Box-Ljung（Q））=0.299）. The predictions by the optimum ARIMA model adequately captured the pattern in the data and exhibited two peaks of activity over the forecast interval, including a major peak during April to June, and again a light peak for September to November. The ARIMA model proposed in this study can forecast HFMD incidence trend effectively, which could provide useful support for future HFMD prevention and control in the study area. Besides, further observations should be added continually into the modeling data set, and parameters of the models should be adjusted accordingly.

A new method to evaluate integrated production system capacity in oil fields

To improve the design and management of an integrated production system(IPS),a set of mathematical models and workflows are developed for evaluating the capacity of an IPS at steady-state conditions.Combining the conservation laws with applicable multiphase fluid and choke models,these mathematical models are solved to characterize the hydraulics of an integrated system of reservoir,wells,chokes,flowlines,and separator at steady state.The controllable variables such as well count,choke size and separator pressure are adjusted to optimize the performance of the IPs at a specific time.It is found that increasing the well count can increase the bulk flow rate of the production network,but too many wells may increase the manifold pressure,leading to decline of single-well production.Increasing the choke size can improve the capacity of the IPs.The production of the IPs is negatively correlated with the separator pressure.With increasing separator pressure and decreasing choke size,the increment of total fluid production(the capacity of IPS)induced by increasing well count decreases.Validation tests with field examples show a maximum absolute deviation is 1.5%,demonstrating the robustness and validity of the proposed mathematical models and workflows.

Retrospective analysis of hepatitis C infected patients treated through an integrated care model

AIM To determine if our health system's integrated model reflects sustained virologic response(SVR) outcomes similar to those in clinical trial data, maximizes adherence, and averts drug interactions.METHODS Subjects with chronic hepatitis C had their medical records reviewed from November 1st, 2014 through March 1st, 2016. Patients eligible for treatment were entered into an integrated care model therapy algorithm. The primary outcome was SVR12 based on intention to treat(ITT) analysis. Inclusion criteria consisted of both treatment na?ve and experienced patients over the age of 18 who were at least twelve weeks post-therapy completion with any genotype(GT) or METAVIR score. Secondary outcomes included adherence, adverse events, and number of drug interaction interventions.RESULTS At the time of analysis, 133 patients had reached twelve weeks post therapy with ITT. In the ITT analysis 70 patients were GT 1a, 26 GT 1b, 23 could not be differentiated between GT 1a or 1b, 8 GT 2, 4 GT 3, and 2 patients with multiple genotypes. The ITT treatment regimens consisted of 97 sofosbuvir(SOF)/ledipasvir(LDV), 8 SOF/LDV and ribavirin(RBV), 7 SOFand Simeprevir(SMV), 6 3D and RBV, 1 3D, 11 SOF and RBV, and 1 SOF, peg interferon alpha, and RBV. The overall SVR12 rate was 93% in the ITT analysis with a total of 6 patients relapsing. In patients with cirrhosis, 89% obtained SVR12. All 33 patients who were previous treatment failures achieved SVR12. Drug-drug interactions were identified in 56.4% of our patient population, 69 of which required interventions made by the pharmacist. The most common side effects were fatigue(41.4%), headache(28.6%), nausea(18.1%), and diarrhea(8.3%). No serious adverse effects were reported.CONCLUSION Dean Health System's integrated care model successfully managed patients being treated for hepatitis C virus(HCV). The integrated care model demonstrates high SVR rates amongst patients with different levels of fibrosis, genotypes, and HCV treatment history.