Shifts In Trends Research Articles

Stability of the ecosystem gross primary productivity increasing in Chinese forestry ecological engineering area

Gross Primary Production (GPP) is an important component of global carbon cycle. In the context of ecosystem construction, ecosystem GPP is significantly increasing, however, the stability of the increasing remains unclear. In this study, the nonlinearity of GPP increasing and its stability were studied with Ensemble Empirical Mode Decomposition method in Chinese forestry ecological engineering (FEE) areas during 1982–2018. The results showed that (1) although linearly increasing trend of GPP occupied 50.83% of the area, it implied different nonlinear trends as monotonic increasing, decreasing to increasing, and increasing to decreasing, accounting for 25.30%, 9.03% and 7.76%, respectively. Meanwhile, for insignificantly linear changes of GPP (41.19%), among them, 5.99% and 5.41% showed trend reversal from increasing to decreasing and from decreasing to increasing, respectively. (2) the trends in all FEE areas were dominated by monotonic increasing, especially for shelterbelt programs of Middle Yellow River (YR). Meanwhile, the trend from decreasing to increasing also has high area percentage (15.75%), especially for YR and coast shelterbelt program (CS), indicating early degradation and later recovery. However, there are large areas (>10%) of the trend shifts from increasing to decreasing in most FEE areas, especially in the shelterbelt programs of Huaihe River and Taihu Lake (HT), Taihang Mountain(TH) and upper and middle reaches of Yangtze River (YZ), indicating high risk of future degradation. (3) Although GPP changes are mainly dominated by interannual variations except YR, contribution of trends to GPP changes are high in HT and TH; For monotonic increasing and decreasing to increasing, the trend contributions to whole GPP changes were > 33%, especially in YR and TH, indicating high stability of ecosystem improvement. For monotonic decreasing, increasing to decreasing and insignificant changes, the contributions were low, indicating low stability but high recovery potential or degradation risk;(4) Both agriculture reclamation and ecological engineering not only favored GPP increasing, but also enhanced its stability. Our results highlight the importance of the nonlinearity of trend and its stability, which provides scientific implications for evaluating the effectiveness of ecological engineering.

Longitudinal stream synoptic monitoring tracks chemicals along watershed continuums: a typology of trends.

There are challenges in monitoring and managing water quality due to spatial and temporal heterogeneity in contaminant sources, transport, and transformations. We demonstrate the importance of longitudinal stream synoptic (LSS) monitoring, which can track combinations of water quality parameters along flowpaths across space and time. Specifically, we analyze longitudinal patterns of chemical mixtures of carbon, nutrients, greenhouse gasses, salts, and metals concentrations along 10 flowpaths draining 1,765 km2 of the Chesapeake Bay region. These 10 longitudinal stream flowpaths are drained by watersheds experiencing either urban degradation, forest and wetland conservation, or stream and floodplain restoration. Along the 10 longitudinal stream flowpaths, we monitored over 300 total sampling sites along a combined stream length of 337 km. Synoptic monitoring along longitudinal flowpaths revealed: (1) increasing, decreasing, piecewise, or no trends and transitions in water quality with increasing distance downstream, which provide insights into water quality processes along flowpaths; (2) longitudinal trends and transitions in water quality along flowpaths can be quantified and compared using simple linear and non-linear statistical relationships with distance downstream and/or land use/land cover attributes, (3) attenuation and transformation of chemical cocktails along flowpaths depend on: spatial scales, pollution sources, and transitions in land use and management, hydrology, and restoration. We compared our LSS patterns with others from the global literature to synthesize a typology of longitudinal water quality trends and transitions in streams and rivers based on hydrological, biological, and geochemical processes. Applications of LSS monitoring along flowpaths from our results and the literature reveal: (1) if there are shifts in pollution sources, trends, and transitions along flowpaths, (2) which pollution sources can spread further downstream to sensitive receiving waters such as drinking water supplies and coastal zones, and (3) if transitions in land use, conservation, management, or restoration can attenuate downstream transport of pollution sources. Our typology of longitudinal water quality responses along flowpaths combines many observations across suites of chemicals that can follow predictable patterns based on watershed characteristics. Our typology of longitudinal water quality responses also provides a foundation for future studies, watershed assessments, evaluating watershed management and stream restoration, and comparing watershed responses to non-point and point pollution sources along streams and rivers. LSS monitoring, which integrates both spatial and temporal dimensions and considers multiple contaminants together (a chemical cocktail approach), can be a comprehensive strategy for tracking sources, fate, and transport of pollutants along stream flowpaths and making comparisons of water quality patterns across different watersheds and regions.

Changing Trends in Conscious Sedation at Pediatric Dental Offices: A Bibliometric Analysis

The uncooperative behavior of children in the dental office has increased the demand for pharmacological behavior management techniques. Moderate sedation is more effective by providing analgesia and anxiolysis, thereby aiding in carrying out the most comfortable, efficient, and high-quality dental services. There is a need to understand the various aspects such as the choice of drug, method of drug administration, safety, and efficacy. Bibliometrics can reveal significant shifts in research and publication trends. Therefore, this study aimed to perform a bibliometric analysis of the literature on evolving trends in conscious sedation at pediatric dental offices. The bibliometric research used RStudio 2021.09.0+351 for Windows (RStudio, Boston, MA), package "bibliometrix," and VOS viewer software (Centre for Science and Technology Studies, Leiden University, The Netherlands. https://www.vosviewer.com). Elsevier's Scopus database (www.scopus.com) provided the literary data for this study, which were exported in BibTex format. The articles were independently categorized according to the following aspects: (a) annual scholarly output; (b) leading countries or regions; (c) leading journals; (d) productive authors; (e) citations; (f) study design; and (g) distribution of topics. The findings considered 1996 through 2022 and used journals, books, articles, and other sources, totaling 1064 papers, with an average of 10.7 per year. According to the findings, the United States, the United Kingdom, and India were principally leading the field of conscious sedation research. In total, 2433 authors were found through the search. The study identified the nations that are currently researching the topics such as midazolam and nitrous-oxide; this paves the way for future partnerships to strengthen the evidence generated in other topic areas using novel sedatives and exploring the different routes of drug administration, thereby benefiting the scientific community by identifying knowledge gaps and experts in this area of research.

Effect of Demographic Variable on Consumer Buying Behaviour of Branded Apparels In Himachal Pradesh

Clothing is as essential to a person as food and shelter. Consumers are the individuals who buy goods and services for personal consumption. To dress up an elegant and adorable manner has always a prime concern of every human being. The textile industry is India's second largest industry. Customers are paying close attention to clothing, which has become a tool for people to express their individuality. The Consumer behaviour has been changing rapidly over the past many years and now a major trend shift of the buying behaviour of the consumers behaviour towards products of variable brands specially the branded luxury garments has been witnessed. To be effective in today's competitive industry, it is essential to comprehend what buyers desire and want. This study aims to determine how buyers purchase branded readymade apparel and which variables influence their purchases in Himachal Pradesh, India. This paper also determines how much customers know about available brands, which factors influencing the consumer buying behaviour. The consumer’s internal and external factors determines their purchasing behaviour.

Short and long-term temperature variations drive recruitment variability in marine and estuarine juvenile fishes

Understanding the long-term effects of climatic factors on key species' recruitment is crucial to species management and conservation. Here, we analysed the recruitment variability of key species (Dicentrarchus labrax, Platichthys flesus, Solea solea, Pomatoschistus microps and Pomatoschistus minutus) in an estuary between 2003 and 2019, and related it with the prevailing local and large-scale environmental factors. Using a dynamic factor analysis (DFA), juvenile abundance data were grouped into three common trends linked to different habitat uses and life cycle characteristics, with significant effect of temperature-related variables on fish recruitment: Sea surface temperature and the Atlantic Multidecadal Oscillation. In 2010, a regime shift in the North Atlantic coincided with a shift in the common trends, particularly a decline in P. flesus and S. solea trend. This work highlights the thermophilic character of fish recruitment and the necessity to investigate key biological processes in the context of species-specific responses to climate change.

Apple's Financial Outlook: A Comprehensive Analysis of its Stock Performance

As traders, investors, and analysts try to decide whether to buy, sell, or hold Apple Inc. shares, Apple Stock Prediction is a crucial component of the financial market. It is difficult to forecast the future value of Apple's stock due to market volatility and a variety of unknown events, including shifts in customer tastes, political unpredictability, and global economic trends. Therefore, it is essential to use a variety of techniques to find the most effective strategy for forecasting Apple's stock price. To ascertain the intrinsic value of a stock, fundamental analysis examines financial statements, market patterns, and economic conditions. This method looks at the sales, profit margins, and cash flow of Apple Inc. as well as its overall financial performance. On the other hand, technical analysis examines past market data, such as price and volume, to spot patterns and trends that can predict future price movements. Charts, graphs, and other visual aids are used in this strategy to pinpoint potential entry and exit positions for trading Apple's stock. Multi-Layer Perceptron is a kind of artificial neural network that mimics the actions of the human brain and has been successfully used to analyze large amounts of complex data. In contrast, XGBoost is a machine learning algorithm that makes predictions using previous data, making it perfect for predicting the future movement of Apple's stock.

The shift of decadal trend in Middle East dust activities attributed to North Tropical Atlantic variability

The Middle East, as the world’s second-largest dust source region, has dust emissions that significantly impact numerous populated areas, extending from North America to South Asia. Over the past two decades, dust activity in the Middle East has exhibited pronounced variability, with a notable trend shift from positive to negative around 2010. The underlying cause of this trend shift remains elusive. In this study, we employ multi-source datasets and global climate model simulations to demonstrate that the variability of Middle East dust activities is closely tied to changes in North Tropical Atlantic (NTA) sea surface temperature (SST). Specifically, a warm NTA SST anomaly generates an anomalous regional zonal cell characterized by ascending air motion above the NTA and descending air surrounding the Middle East. The associated surface high pressures around the Middle East subsequently induce hot and dry conditions accompanied by intensified Shamal winds in the north, which are favorable for dust emission and transport. The shift in SST trends from positive to negative in the NTA around 2010 is therefore responsible for the observed dust trend shift in the Middle East. This mechanism holds vital implications for predicting decadal dust variability over the Middle East region and further the project of global environment.

Sustainable application of nanoparticles in wastewater treatment: Fate, current trend & paradigm shift

Existing water and wastewater treatment techniques are becoming increasingly difficult to employ due to the discovery of new toxins, the rapid development of population and industrial activities, and the limited quantity of water resources. Treatment of wastewater is a critical need in modern civilization due to a scarcity of water resources and rising industrial activity. Some of the techniques utilized include adsorption, flocculation, filtration, and others, although they are only used for primary wastewater treatment. However, the development and deployment of modern wastewater management with high efficiency and low capitalization are critical in terms of mitigating the environmental consequences of waste. The employment of different nanomaterials in the treatment of wastewater has opened up a world of possibilities for heavy metal and pesticide removal, as well as the treatment of microbes and organic contaminants in wastewater. Nanotechnology is a rapidly evolving technology because of certain nanoparticle's outstanding physiochemical and biological capabilities as contrasted to bulk counterparts. Secondly, it has been established that this is a cost-effective treatment strategy with significant potential in wastewater management, transcending the limitations imposed by currently existing technology. Advances in nanotechnology to reduce water contamination have been presented in this review, including the use of various nanomaterials such as nanocatalysts, nanoadsorbents, and nanomembranes in the treatment of wastewater containing organic contaminants, hazardous metals, and virulent pathogens.

Reassessment of the declines in the largest freshwater lake in China (Poyang Lake): uneven trends, risks and underlying causes

Water level decline in the largest freshwater lake in China (Poyang Lake) has raised grave concerns and continuous debates regarding the proposal of a water control project. Previous hydrologic investigations on the water level decline in Poyang Lake were conducted mostly during recession season and typical dry years and hence lacked the comprehensive view of associated risks and possible spatial heterogeneity of trend during low water level periods. The present study reassessed the long-term trend and regime shift of low water level variations and their associated risks based on hydrological data across multiple stations in Poyang Lake during 1952–2021. The underlying causes of the trends of water level decline were further investigated. Results showed uneven trends and risks of water level variations in different seasons and across different lake regions. The water level of all five hydrological stations in Poyang Lake significantly dropped in the recession season, and the risks of water level decline evidently increased since 2003, which could be largely attributed to the water level drop in the Yangtze River. In terms of the dry season, clear spatial differences of long-term trend of water level were found, with water level in the central and southern lake regions significantly dropping, which was probably caused by dramatic bathymetry undercutting in the central and northern lake regions. In addition, the impacts of topographic changes became significant when water level of Hukou fell below 13.8 and 11.8m for the northern and southern lake regions, respectively. By contrast, water level in the northern lake region showed increasing trends in the dry season. In addition, only the occurrence time of water level under moderate risk significantly advanced for all stations except for Hukou. The present study could provide a full picture of low water level trends, associated risks across different lake regions and underlying causes in Poyang Lake, thus providing insights into adaptive water resources management.

Provisional Mortality Data - United States, 2022.

The National Center for Health Statistics' (NCHS) National Vital Statistics System (NVSS) collects and reports annual mortality statistics using U.S. death certificate data. Because of the time needed to investigate certain causes of death and to process and review death data, final annual mortality data for a given year are typically released 11 months after the end of the calendar year. Provisional data, which are based on the current flow of death certificate data to NCHS, provide an early estimate of deaths, before the release of final data. NVSS routinely releases provisional mortality data for all causes of death and for deaths associated with COVID-19.* This report is an overview of provisional U.S. mortality data for 2022, including a comparison with 2021 death rates. In 2022, approximately 3,273,705 deaths† occurred in the United States. The estimated 2022 age-adjusted death rate decreased by 5.3%, from 879.7 per 100,000 persons in 2021 to 832.8. COVID-19 was reported as the underlying cause or a contributing cause in an estimated 244,986 (7.5%) of those deaths (61.3 deaths per 100,000). The highest overall death rates by age, race and ethnicity, and sex occurred among persons who were aged ≥85 years, non-Hispanic American Indian or Alaska Native (AI/AN), non-Hispanic Black or African American (Black), and male. In 2022, the four leading causes of death were heart disease, cancer, unintentional injuries, and COVID-19. Provisional death estimates provide an early indication of shifts in mortality trends and can guide public health policies and interventions aimed at reducing mortality, including deaths directly or indirectly associated with the COVID-19 pandemic.

COVID-19 Mortality Update — United States, 2022

The National Center for Health Statistics' (NCHS) National Vital Statistics System (NVSS) collects and reports annual mortality statistics using U.S. death certificate data. Provisional data, which are based on the current flow of death certificate data to NCHS, provide an early estimate of deaths before the release of final data.* This report summarizes provisional U.S. COVID-19 death data for 2022. In 2022, COVID-19 was the underlying (primary) or contributing cause in the chain of events leading to 244,986 deaths† that occurred in the United States. During 2021-2022, the estimated age-adjusted COVID-19-associated death rate decreased 47%, from 115.6 to 61.3 per 100,000 persons. COVID-19 death rates were highest among persons aged ≥85 years, non-Hispanic American Indian or Alaska Native (AI/AN) populations, and males. In 76% of deaths with COVID-19 listed on the death certificate, COVID-19 was listed as the underlying cause of death. In the remaining 24% of COVID-19 deaths, COVID-19 was a contributing cause. As in 2020 and 2021, during 2022, the most common location of COVID-19 deaths was a hospital inpatient setting (59%). However, an increasing percentage occurred in the decedent's home (15%), or a nursing home or long-term care facility (14%).§ Provisional COVID-19 death estimates provide an early indication of shifts in mortality trends and can help guide public health policies and interventions aimed at reducing COVID-19-associated mortality.

Review of artificial intelligence and internet of things technologies in land and water management research during 1991–2021: A bibliometric analysis

The challenges of urbanization, land degradation, water scarcity, and climate change are threatening agricultural systems and food security. Therefore, it is essential to manage land and water resources sustainably to improve productivity and address these challenges. Digital agriculture, which involves the use of smart systems and advanced farming practices incorporating Artificial Intelligence (AI) and Internet of Things (IoT) technologies, can provide solutions for sustainable agriculture and climate change adaptation. This study aims to fill the research gap by understanding the recent pulse and current trends of significant works published on AI and IoT-assisted land and water management (LWM) research. A bibliometric analysis of 436 English language articles published over the last three decades (1991–2021) was conducted. The study revealed a significant shift in research trends in 2010, with over 60 AI techniques utilized under different AI and IoT frameworks for LWM. The highly adopted AI techniques include Artificial Neural Networks (ANN—9.85%), Adaptive Neuro-Fuzzy Inference System (ANFIS —5.98%), Support Vector Regression (SVR—3.87%), Random Forest (RF—3.16%),​ and Multilayer Perceptron-ANN (MLP-ANN—2.81%). China, India, Iran, Australia, and the USA were identified as pioneers in the field, while Italy, Spain, and Saudi Arabia showed potential as emerging countries but with low collaboration links. The study also discussed the current limitations and challenges of AI and IoT technologies. Future research focus areas for AI and IoT were identified, and it was recommended to conduct comparative evaluations of AI techniques to determine the most effective approach for specific LWM domains.

Analyzing abnormal pattern of hotelling [formula omitted] control chart for compositional data using artificial neural networks

Compositional data (CoDa) has been monitored in statistical process monitoring, where multivariate control charts (CCs) such as Hotelling TC2, MEWMA-CoDa, and MCUSUM-CoDa are commonly used to determine if a process is in-control. However, these charts can encounter problems when there is an out-of-control (OOC) process due to various factors such as shifts in variables, outliers, or trends. To address this issue, a pattern recognition (PR) tool using multilayer feed-forward neural networks (MLFFNN) is proposed to accurately recognize CoDa patterns. In the simulation study, six different models in simplex sample space are used to induce trends and shifts in CoDa, and sufficient samples are generated to evaluate the proposed PR model’s performance. The isometric log-ratio (ilr) transformation is applied to CoDa to convert the data from simplex sample space to real space. The Hotelling TC2 statistic is obtained from the generated values after applying the ilr transformation. TC2 statistic is then standardized for MLFFNN, and a back-propagation learning algorithm is used to accurately fit the PR model. Results show the proposed model accurately identifies the CCs pattern, even during OOC processes. A time budget CoDa is analyzed to demonstrate the proposed model’s effectiveness in recognizing patterns.

The shift in research trends related to artificial intelligence in library repositories during the coronavirus pandemic

PurposeThis study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two topics during the coronavirus pandemic.Design/methodology/approachThe study gathered secondary data from the Scopus website using the keywords “AI,” “library” and “repository,” from 1993 to 2022. Data were re-analyzed using the bibliometric software VOSviewer to examine the trending country's keyword relations and appearance and Biblioshiny to study the publication metadata.FindingsIndex keywords, such as “human,” “deep learning,” “machine learning,” “surveys” and “open-source software,” became popular during 2020, being closely related to digital libraries. Additionally, the annual scientific production of papers increased significantly in 2021. Words related to data mining also had the most significant growth from 2019 to 2022 because of the importance of data mining for library services during the pandemic.Practical implicationsThis study provides insight for librarians for the implementation of AI to support repositories during the pandemic. Librarians can learn how to maximize the AI-based repository services in academic libraries during the pandemic. Furthermore, academic libraries can create policies for repository services using AI.Social implicationsThis study can lead researchers, academicians and practitioners in conducting research on AI in library repositories.Originality/valueAs research on AI and digital repositories remains limited, the study identifies themes and highlights the knowledge gap existing in the field.

ISLAMIC INVESTMENT IN INDONESIA BEFORE AND DURING PANDEMIC OF COVID-19: A BIBLIOMETRIC STUDY

Indonesia had a potential for Islamic investment development because of its biggest number of Muslims in the world. Islamic investment through the sharia capital market was positive even during the pandemic of COVID-19. This study has a purpose to observe the correlation between topic-related Islamic investment in Indonesia along with the shift of trend of topics before and during COVID-19. There were 1072 samples gathered from Scopus website with keyword “Islamic”, “investment”, and “Indonesia”. The data were analyzed using bibliometric method. This study used Vosviewer and R Studio to analyzed the data. The result showed that there were correlation between

Regime Shift of the Sea Level Trend in the South China Sea Modulated by the Tropical Pacific Decadal Variability

AbstractDuring the altimeter era, the sea level in the South China Sea (SCS) and western tropical Pacific (WTP) experienced significant decadal variability. The sea level rose during 1993–2009 and fell during 2010–2019. The decadal variability of Walker Circulation associated with the Pacific Decadal Oscillation can explain the sea level variability in the WTP to a great extent. The wind forced westward propagating Rossby waves increased (decreased) the sea level in the WTP during 1993–2009 (2010–2019). However, the interior wind forcing has a negligible contribution to the decadal variability of the sea level in the SCS. The remote forcing from WTP through the oceanic bridge was supposed to play a dominant role. The sensitive experiments of a 1½‐layer model and Regional Oceanic Modeling System suggested that the sea level signals via the Sibutu Passage and Mindoro Strait accounted for the decadal variability of sea level in the central basin of SCS.

Interdecadal Shift in Dipole Pattern Precipitation Trends Over the Tibetan Plateau: Roles of Local Vortices

AbstractTrends of precipitation over the Tibetan Plateau (TP) are characterized by a north‐south dipole pattern, and the role of local mesoscale systems, TP vortices (TPVs), remains ambiguous. This work reports that the north‐south dipole pattern trends in the TPVs‐associated precipitation have experienced an interdecadal shift in the last two decades, that is, increases in northern TP and decreases in southern TP first and then varies opposite trends, which greatly contributes to the similar interdecadal shift in TP precipitation trends. Furthermore, the causes of changes in TPV frequency are explored from the perspective of lower troposphere conditions. We find that the lower‐level winds, that is, zonal winds over the TP and meridional winds across the northwestern TP boundary, are responsible for the regionally different variations in TPV frequency. The variations in Indian Ocean Dipole are suggested to contribute to the changes in lower‐level winds over the TP.

Making a Case for Entrepreneurial Skill Development in Schools

Today’s youth is faced with new risks emerging from fast advancing technology such as AI and increased individual responsibilities. With these trend shifts, foundational knowledge alone, without an understanding of the interconnected nature of the applications in real life is not going to effectively prepare the youth for future success. It is therefore imperative to introduce students to the essentials of entrepreneurial mindset early in their middle and high school education.
 Although this is a critical challenge faced by youth today, there is very little advocacy for incorporating entrepreneurial skill development in school curriculum.
 The intent of this research project is to outlay the foundational skills that are essential to building an entrepreneurial mindset and to recommend a curriculum that will advance entrepreneurial skill development in middle and high school students.
 The roadmap of this paper begins with making the case for introducing entrepreneurial skill curriculum, proceeding to the cultural factors that influence skill development, Recommendation, purpose of Case Studies, and concluding summary.

RETROSPECTIVE ANALYSIS OF CLINICAL TRENDS OF SEXUALLY TRANSMITTED INFECTIONS IN PRE-COVID AND POST-COVID ERA AMONG ATTENDEES OF STI CLINIC IN TERTIARY CARE CENTRE IN SOUTH INDIA

Background The global COVID-19 pandemic was not only directly responsible for immeasurable COVID-related morbidity and mortality but also had an indirect impact on incidence and transmission prole of various Sexually Transmitted Infections (STIs) due to sexual distancing and service interruption. Long-term implications of these conicting factors on the STI epidemic have not yet been fully gauged. Aim of study To evaluate the prevalence and pattern of STIs in an earmarked population before, during and after the COVID pandemic. Methods A retrospective analysis of patients who reported to STI OPD of a tertiary care centre in South India over 5 years from 2018 to 2022 was performed and the varying clinical trends, prevalence and transmission dynamics of sexually transmitted infections were analyzed. Results The prevalence of STI in patients reported has been recorded at 12.83% (2018), 12.30% (2019), 13.01% (2020), 7.80% (2021) and 7.45 % (2022). The increased prevalence of STIs in 2020 may be due to the reduced overall census in STI Clinic. True to service interruption, HIV cases in year 2020 was recorded at an all-time low of 32 followed by an increase to 103 and 101 in 2021 and 2022 respectively. Bacterial STIs, especially Syphilis, have displayed a rising trend as evident by the prevalence of 11.05% in 2022. as opposed to the prevalence of 3.24% in 2018 Conclusion The shift in STI clinical trends could be partly attributed to the restrictive measures enforced by the Government during COVID and partly by psychosocial behavioural changes brought about by the post-COVID pandemic situation. The increasing trend of bacterial STIs in the post COVID years has to be curtailed with targeted interventions. Preventive and early treatment strategies among high-risk behaviour groups need to be strengthened to keep the STIs under control in post covid era

Shifting incidence and survival of epithelial ovarian cancer (1995-2014): A SurvMark-2 study.

The aim of the study is to provide a comprehensive assessment of incidence and survival trends of epithelial ovarian cancer (EOC) by histological subtype across seven high income countries (Australia, Canada, Denmark, Ireland, New Zealand, Norway and the United Kingdom). Data on invasive EOC diagnosed in women aged 15 to 99 years during 1995 to 2014 were obtained from 20 cancer registries. Age standardized incidence rates and average annual percentage change were calculated by subtype for all ages and age groups (15-64 and 65-99 years). Net survival (NS) was estimated by subtype, age group and 5-year period using Pohar-Perme estimator. Our findings showed marked increase in serous carcinoma incidence was observed between 1995 and 2014 among women aged 65 to 99 years with average annual increase ranging between 2.2% and 5.8%. We documented a marked decrease in the incidence of adenocarcinoma "not otherwise specified" with estimates ranging between 4.4% and 7.4% in women aged 15 to 64 years and between 2.0% and 3.7% among the older age group. Improved survival, combining all EOC subtypes, was observed for all ages combined over the 20-year study period in all countries with 5-year NS absolute percent change ranging between 5.0 in Canada and 12.6 in Denmark. Several factors such as changes in guidelines and advancement in diagnostic tools may potentially influence the observed shift in histological subtypes and temporal trends. Progress in clinical management and treatment over the past decades potentially plays a role in the observed improvements in EOC survival.