Timing theory integrated nursing combined behavior change integrated theory of nursing on primiparous influence

BACKGROUND The comprehension and utilization of timing theory and behavior change can offer a more extensive and individualized provision of support and treatment alternatives for primipara.This has the potential to enhance the psychological well-being and overall quality of life for primipara,while also furnishing healthcare providers with efficacious interventions to tackle the psychological and physiological obstacles encountered during the stages of pregnancy and postpartum.AIM To explore the effect of timing theory combined with behavior change on selfefficacy,negative emotions and quality of life in patients with primipara.METHODS A total of 80 primipara cases were selected and admitted to our hospital between August 2020 and May 2022.These cases were divided into two groups,namely the observation group and the control group,with 40 cases in each group.The nursing interventions differed between the two groups,with the control group receiving routine nursing and the observation group receiving integrated nursing based on the timing theory and behavior change.The study aimed to compare the pre-and post-nursing scores of Chinese Perceived Stress Scale(CPSS),Edinburgh Postpartum Depression Scale(EPDS),Self-rating Anxiety Scale(SAS),breast milk knowledge,self-efficacy,and SF-36 quality of life in both groups.RESULTS After nursing,the CPSS,EPDS,and SAS scores of the two groups was significantly lower than that before nursing,and the CPSS,EPDS,and SAS scores of the observation group was significantly lower than that of the control group(P=0.002,P=0.011,and P=0.001 respectively).After nursing,the breastfeeding knowledge mastery,selfefficacy,and SF-36 quality of life scores was significantly higher than that before nursing,and the breastfeeding knowledge mastery(P=0.013),self-efficacy(P=0.008),and SF-36 quality of life(P=0.011)scores of the observation group was significantly higher than that of the control group.CONCLUSION The integration of timing theory and behavior change integrated theory has been found to be an effective approach in alleviating negative mood and stress experienced by primipara individuals,while also enhancing their selfefficacy and overall quality of life.This study focuses on the key concepts of timing theory,behavior change,primipara individuals,negative mood,and quality of life.

Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains complex.To this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to 2021.Then,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation phenology.Additionally,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly defined.The SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other vegetation.The EOS in MDW and GSD were concentrated between late August and April and early September and early January,respectively.Vegetation phenology exhibits distinct responses to seasonal temperature and precipitation patterns.The advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,respectively.The advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,respectively.On the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect effects.The indirect effect of winter precipitation is the main factor affecting the advance or delay of SOS,and the area proportions were 16.29%and 23.42%,respectively.The indirect effects of fall temperatures and precipitation were the main factors affecting the delay and advancement of EOS,respectively,with an area share of 15.80%and 21.60%.This study provides valuable insight into the relationship between vegetation phenology and climate change,which can be of great practical value for the ecological protection of the Qinghai-Tibetan Plateau as well as for the development of GSD ecological animal husbandry in the QM alpine pastoral area.

Study on Ecological Change Remote Sensing Monitoring Method Based on Elman Dynamic Recurrent Neural Network

In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.

Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Time-lapse geophysical technology-based study on overburden strata changes induced by modern coal mining

To study the impact of modern coal mining on overlying strata and its water bearing conditions,integrated time-lapse geophysical prospecting integrating 3D seismic,electrical and ground penetrating radar method were used.Through observing and analyzing the geophysical data variations of all stages of pre-mining,mining and post-mining as well as post-mining deposition stable period,impacts of coal mining on stratigraphic structure and its water bearing were studied and modern coal mining induced stratigraphic change pattern was summarized.The research result shows that the stratigraphic structure and the water bearing of surface layer during modern coal mining have self-healing pattern with mining time;the self-healing capability of near-surface strata is relatively strong while the roof weak;water bearing selfhealing of near-surface strata is relatively high while the roof strata adjacent to mined coal beds low.Due to integrated time-lapse geophysical prospecting technology has extra time dimension which makes up the deficiency of static analysis of conventional geophysical methods,it can better highlight the dynamic changes of modern coal mining induced overburden strata and its water bearing conditions.

Analysis of Change Point in Surface Temperature Time Series Using Cumulative Sum Chart and Bootstrapping for Asansol Weather Observation Station, West Bengal, India

This paper aims to detect the short-term as well as long-term change point in the surface air temperature time series for Asansol weather observation station, West Bengal, India. Temperature data for the period from 1941 to 2010 of the said weather observatory have been collected from Indian Meteorological Department, Kolkata. Variations and trends of annual mean temperature, annual mean maximum temperature and annual minimum temperature time series were examined. The cumulative sum charts (CUSUM) and bootstrapping were used for the detection of abrupt changes in the time series data set. Statistically significant abrupt changes and trends have been detected. The major change point in the annual mean temperatures occurred around 1986 (0.57°C) at the period of 25 years in the long-term regional scale. On the other side, the annual mean maximum and annual mean minimum temperatures have distinct change points at level 1. There are abrupt changes in the year 1961 (Confidence interval 1961, 1963) for the annual mean maximum and 1994 (Confidence interval 1993, 1996) for the annual mean minimum temperatures at a confidence level of 100% and 98%, respectively. Before the change, the annual mean maximum and annual mean minimum temperatures were 30.90°C and 23.99°C, respectively, while after the change, the temperatures became 33.93°C and 24.84°C, respectively. Over the entire period of consideration (1941-2010), 11 forward and backward changes were found in total. Out of 11, there are 3 changes (1961, 1986 and 2001) in annual mean temperatures, 4 changes (1957, 1961, 1980 and 1994) in annual mean maximum temperatures, and rest 4 changes (1968, 1981, 1994 and 2001) are associated with annual mean minimum temperature data set.

On-line outlier and change point detection for time series

The detection of outliers and change points from time series has become research focus in the area of time series data mining since it can be used for fraud detection, rare event discovery, event/trend change detection, etc. In most previous works, outlier detection and change point detection have not been related explicitly and the change point detections did not consider the influence of outliers, in this work, a unified detection framework was presented to deal with both of them. The framework is based on ALARCON-AQUINO and BARRIA's change points detection method and adopts two-stage detection to divide the outliers and change points. The advantages of it lie in that: firstly, unified structure for change detection and outlier detection further reduces the computational complexity and make the detective procedure simple; Secondly, the detection strategy of outlier detection before change point detection avoids the influence of outliers to the change point detection, and thus improves the accuracy of the change point detection. The simulation experiments of the proposed method for both model data and actual application data have been made and gotten 100% detection accuracy. The comparisons between traditional detection method and the proposed method further demonstrate that the unified detection structure is more accurate when the time series are contaminated by outliers.

Modeling and Investigation of the Wall Thickness Changes and Process Time in Thermo-Mechanical Tube Spinning Process Using Design of Experiments

Tube spinning technology is one of the effective methods of manufacturing large diameter thin-walled shapes. In this research, effects of major parameters of thermo mechanical tube spinning process such as preform's thickness, percentage of thickness reduction, mandrel rotational speed, feed rate, solution treatment time and aging treatment time on the wall thickness changes and process time in thermo-mechanical tube spinning process for fabrication of 2024 aluminum spun tubes using design of experiments (DOE), are studied. The statistical results are verified through some experiments. Results of experimental evaluation are analyzed by variance analysis and mathematic models are obtained. Finally using these models, input parameters for optimum production are achieved.

Unsupervised Time Series Segmentation: A Survey on Recent Advances

Time series segmentation has attracted more interests in recent years,which aims to segment time series into different segments,each reflects a state of the monitored objects.Although there have been many surveys on time series segmentation,most of them focus more on change point detection(CPD)methods and overlook the advances in boundary detection(BD)and state detection(SD)methods.In this paper,we categorize time series segmentation methods into CPD,BD,and SD methods,with a specific focus on recent advances in BD and SD methods.Within the scope of BD and SD,we subdivide the methods based on their underlying models/techniques and focus on the milestones that have shaped the development trajectory of each category.As a conclusion,we found that:(1)Existing methods failed to provide sufficient support for online working,with only a few methods supporting online deployment;(2)Most existing methods require the specification of parameters,which hinders their ability to work adaptively;(3)Existing SD methods do not attach importance to accurate detection of boundary points in evaluation,which may lead to limitations in boundary point detection.We highlight the ability to working online and adaptively as important attributes of segmentation methods,the boundary detection accuracy as a neglected metrics for SD methods.

RESIDENCE TIME DISTRIBUTION STUDIES WITH TRACER EXPERIMENTS:IMPULSE INJECTION VERSUS STEP CHANGE OF FEED

1 INTRODUCTIONThe popularly used axial dispersion model is mathematically expressed by aone-dimensional partial differential

Time Sequence Change-Point Model of Electrostatic State Parameters of Aircraft Engine

Electrostatic monitoring technology of particle charging information can facilitate online monitoring of aero-engine,which effectively enhances engine fault diagnosis and health managements.Unlike traditional engine state monitoring technologies,aircraft engine monitoring by gas path electrostatic monitoring not only covers the predicted information source itself,but also detects the information that can provide an early warnings for initial fault states through gas path charging levels.This paper establishes a non-stationary time sequence change-point model for anomaly recognition of electrostatic signals based on change-point theory combined with difference method of non-stationary time series.Finally,electrostatic induction data were utilized by the engine life test for a particular aircraft to validate the proposed algorithm.The results indicate that the activity level and the event rate were0.5—0.8(nc)and 50%,respectively,which were far greater than 4—12(pc)and 0—4% under normal working conditions of the engine.

Forestry under Climate Change. Is Time a Tool for Sustainable Forest Management?

Changing climate conditions are known to influence forest tree growth response and the CO2 cycle. Dendroclimatological research has shown that the climate signal, species composition, and growth trends have changed in different types of forest ecosystems during the last century. Under current and demonstrated changes in climate variability at the geographic, regional, and local levels tree growth shows also variability and trends that can be non-stationary during time even at relatively short distance between sites. In forest planning and management, yield tables, site quality indices, age class, rate of growth, and spatial distribution are some of the most used tools and parameters. However, these methods do not involve climate variability during time although climate is the main driver in trends of forest and tree growth. Previous research warns about the risk that forest management under changing climatic conditions could amplify their negative effects. For example, changing climate conditions may impact on temperature and/or precipitation thresholds critical to forest tree growth. Forest biomass, resilience, and CO2 storage may be damaged unless forest planning and management implement the relationships between climate variability and trends of tree growth. A positive aspect is that, periods of favorable climate conditions may allow harvesting higher amount of wood mass and storing more CO2 than traditional planning methods. And, the average length of both favorable and adverse periods appears to occur within the validity period of a forest management plan. Here, we show a conceptual development to implement climate variability in forest management in the view of continuing the research.

Spatio-temporal changes of underground coal fires during 2008-2016 in Khanh Hoa coal field(North-east of Viet Nam) using Landsat time-series data

Underground coal fires are one of the most common and serious geohazards in most coal producing countries in the world. Monitoring their spatio-temporal changes plays an important role in controlling and preventing the effects of coal fires, and their environmental impact. In this study, the spatio-temporal changes of underground coal fires in Khanh Hoa coal field(North-East of Viet Nam) were analyzed using Landsat time-series data during the 2008-2016 period. Based on land surface temperatures retrieved from Landsat thermal data, underground coal fires related to thermal anomalies were identified using the MEDIAN+1.5×IQR(IQR: Interquartile range) threshold technique. The locations of underground coal fires were validated using a coal fire map produced by the field survey data and cross-validated using the daytime ASTER thermal infrared imagery. Based on the fires extracted from seven Landsat thermal imageries, the spatiotemporal changes of underground coal fire areas were analyzed. The results showed that the thermalanomalous zones have been correlated with known coal fires. Cross-validation of coal fires using ASTER TIR data showed a high consistency of 79.3%. The largest coal fire area of 184.6 hectares was detected in 2010, followed by 2014(181.1 hectares) and 2016(178.5 hectares). The smaller coal fire areas were extracted with areas of 133.6 and 152.5 hectares in 2011 and 2009 respectively. Underground coal fires were mainly detected in the northern and southern part, and tend to spread to north-west of the coal field.

Change Point Detection and Trend Analysis for Time Series

Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whereas trend can be defined as estimation of gradual departure from past norms.We analyze the time series data in the presence of trend,using Cox-Stuart methods together with the change point algorithms.We applied the methods to the nearsurface wind speed time series for Australia as an example.The trends in near-surface wind speeds for Australia have been investigated based upon our newly developed wind speed datasets,which were constructed by blending observational data collected at various heights using local surface roughness information.The trend in wind speed at 10 m is generally increasing while at 2 m it tends to be decreasing.Significance testing,change point analysis and manual inspection of records indicate several factors may be contributing to the discrepancy,such as systematic biases accompanying instrument changes,random data errors(e.g.accumulation day error)and data sampling issues.Homogenization technique and multiple-period trend analysis based upon change point detections have thus been employed to clarify the source of the inconsistencies in wind speed trends.

Difference in Surface Roughness of Ethylene-Vinyl-Acetate Sheet before and after Application of Finishing Liquid: Part 2 Changes over Time in Surface Roughness

Surface texture of the mouthguard affects the sense of adaptation in the athlete and further affects hygiene. The aim of this study was to investigate the changes over time in surface roughness after finish polishing of ethylene vinyl acetate (EVA) sheets and before and after finishing liquid application, and to evaluate its effectiveness. Total of 160 specimens of EVA (3 × 3 mm) were divided into 4 groups according to polishing condition (control = unpolished;RB = Robinson-brush;LF = Lisko-Fine, and MW = Mouthguard-wheel). Polishing was performed at low speed by using a straight headpiece. The rotation speed was 5000, 4000 and 6000 rpm for RB, LF, and MW, respectively. Next, a finishing liquid was applied to each specimen. Changes over time in surface roughness before and after application of the finishing liquid were compared by a non-contact surface shape measuring machine. The arithmetic average height (Sa) was measured. The measurement time points were before application, immediately after application, and at 5, 10, and 15 min after application. The changes over time of the surface roughness of the sheet before and after application of the finishing liquid were analyzed by two-way analysis of variance and Bonferroni’s multiple comparison tests. Surface roughness of the specimen before application became coarse in the order of control;MW, LF and RB, and Sa were about 0.21 μm, 2.03 μm, 2.94 μm, and 4.72 μm, respectively. That showed the same order after finishing liquid application. Significant decrease in Sa for RB and LF were seen at 10 min after application and at 5 min after application, respectively. Sa of MW was not significantly different before and after application. The results of this study showed that a lubricity of about 1.0 μm increases within 5 - 10 min of application of finishing liquid, but in cases where polishing was performed to about 2.0 μm;the application of finishing liquid has no ef-fect.

Economic Analysis of CO2 Emission Abatement Applying a Dynamic CGE Model with Endogenous Technological Change： Impacts of the Time Horizon

We evaluate economic and environmental impacts of climate change mitigation in a country scale considering various time horizons in the analysis applying a single-country dynamic computable general equilibrium model with endogenous technological change. Although there is a possibility that Gross Domestic Product （GDP） becomes larger for the abatement cases than the baseline case in the earlier years, it tends to be lower than that in the later years. The longer the time horizon and/or the more severe the abatement, the larger the negative impacts will be. When subsidizing R＆D investment, increase in GDP compared to the baseline case is realized in the middle of the time horizon, and the larger increase tends to be observed for the longer-term cases. These results would be due to technological change induced by the subsidies and emission abatement. Environmental indicators are also improved. We showed that the results were influenced by the target time horizon when using an intertemporal dynamic model.

Real-time observation of integrin bending/unbending conformational changes on living cells

Introduction Integrins are a large family of adhesion molecules broadly expressed on the surface of a wide variety of cells as heterodimers. Binding of integrins to ligands provides not only mechanical anchorage for the cell to another cell or

Local and Time Changes over a 66-Year Period and Annual Relocation of Saudi Arabian Subtropical High Pressure

Saudi Arabian subtropical high pressure is a major system affecting general circulation of the atmosphere of west Asia. Its annual relocation affects the relocation of other systems in the area, such as Mediterranean cyclones, Sudanese low pressure areas, and west wind waves. This system is known to relocate to the south and north in response to outward solar relocation, but the reasons behind its eastern and western relocation have not been studied thoroughly. The present study examined 1000 and 850 HPa levels over the course of 66 years (1948-2015) to determine a pattern of latitudinal and longitudinal relocation of the system using synoptic maps. The research showed that, after 2008, high pressure latitudinal and longitudinal swings were larger than in previous years and the annual high pressure relocation was not in concord with the apparent motion of the sun. At the onset of autumnal moderation, the high pressure core was positioned to the north of Saudi Arabia (22° - 30° north latitude and 42° - 50° south longitude). Southern movement continued until the end of March, when the core again relocated to the north. These relocations first occurred slowly, but the northern relocation occurred very quickly from May to June, such that the core moved northward 22° to 30°. After June, the core did not relocate much until the end of September. After September, it relocated strongly south in all time periods. It was noted that high pressure over Saudi Arabia had two cores from June to September in some years;in others the high pressure core was in southwestern Iran and Iraq. In still others, a southwest to northeast high pressure tab entered Iran from the southwest (Khuzestan) and continued northward with a core forming in the northern Caspian Sea.

Climate Change Crunch Time

From November 28 to December 9,the 17th Conference of the Parties(COP17) to the United Nations Framework Convention on Climate Change takes place in Durban,South Africa.Discussions will center on what the international community can do to cope with the increasingly serious climate change.In an article for China Today,Xie Zhenhua, Vice Chairman of National Development and Reform Commission,explained China’s efforts in carbon emission reduction and its stance at the upcoming conference.His edited views follow:

Analysis of Season Change in Jiyang from Meteorological Standpoint

[Objective] The aim was to analyze changing characters of four seasons in Jiyang, providing references for farming and disaster prevention in the area. [Methed] Changing characters of initial time and lasting periods of four seasons in Jiyang for 30 years were analyzed from meteorological standpoint with weather information from 1981 to 2010 observed in surface meteorological observation in Jiyang. [Result] Recent 30 years, initial time of spring and winter in Jiyang were earlier than before, especially for spring. In contrast, initial time of summer and autumn were later, especially for autumn. In addition, periods of spring and winter declined and the latter changed more significantly. Meanwhile, periods of summer and autumn extended and rate of linear trend for summer period was 0.042 hou/year. [Conclusion] The research indicated that lasting days of summer extended significantly and of spring and winter shortened under the background of global warming.