Time Period Research Articles

Конструирование образа прошлого в кино: кейс сериала «Слово пацана»

The article examines the problem of historical accuracy in cinema on the example of the popular Russian TV series “A hoodlum’s promise – blood on the asphalt”. In the context of the popularity of movies covering real historical events, the author gives a sociological interpretation of the artistic techniques used in the series aimed at constructing the image of the past. Based on their analysis, the authors identify the criteria that allow us to judge the plausibility and correspondence of the image of the past embodied in the film to the historical reality. These include: 1) the degree of authenticity of reconstruction of material culture of a particular time pe-riod; 2) authentic representation of mentality of a particular time period; and 3) filmmaker’s understanding and interpretation of historical processes, events, etc. It is emphasized that the modern trend is to move away from documentary authenticity in historical films, but it is also stressed that the key importance in this regard is the author’s intention, in some cases designed to convey to the viewer a certain social idea expressed by the skill of filmmakers.

Impact of Ginger Oleoresin on Leaf Tripe of Sapumhicha

The main objective of the study is to examine the impact of ginger on the leaf tripe of 'SapuMhicha'. SapuMhicha is a special dish consisting of buffalo leaf tripe stuffed with bone marrow; it is boiled and fried. This dish is popular in Kathmandu Valley, especially in Newar community. The use of ginger makes this dish tasty and hygienic. It is indigenous knowledge and practice; with this, it can be preserved for a certain time period. Ginger is valued in nutritional importance as it contains fiber. Ginger contributes to minimizing Microbial growth that helps to stimulate the digestive system. The use of ginger in a tripe recipe makes low microbial. This study focuses on this indigenous knowledge of how ginger enhances leaf tripe to use for a long time. The impact of ginger on leaf tripe is tested using the AOAC direct moisture determination method on different days from 1 to 16 at normal room temperature. The result was that the impact of ginger on tripe leaf was positive i.e. low microbial growth was noticed. The result showed that ginger enhances the shelf-life of tripe at room temperature as it can be stored for a certain period of time and remain suitable for use.

Deep learning assisted solar forecasting for battery swapping stations

ABSTRACT For the development of renewable energy generation as a viable alternative to fossil fuel-based generation, solar power has received widespread acceptance. An increase in solar power usage can mitigate the impact of climate change, energy demand, and cost-effective dispatch. To use solar power efficiently and ensure grid consistency, reliable and accurate forecasting of information becomes very crucial. Hence, the main purpose of this work is to get the best suitable solar irradiance forecasting model and to implement the forecasted solar power to the designed hybrid battery swapping stations. Each year, new techniques and approaches are used to improve the model accuracy with the critical aim of lowering the variability of predictions. This paper takes a close look at different deep-learning methods to predict solar irradiance for a certain period of time. The real-time time series data is used, and for analyzing the time series data, the statistical ARIMA model, LSTM-based RNN technique, and Dual Attention-based Recurrent Neural network have been used. These models are implemented using Jupyter Notebook with Python programming language. To analyze the efficiency and evaluate the performance of real-time data of the models, a comparative study has been done on the different error metrics. This paper reveals that the LSTM model is providing the best solar power forecasting with the least error metrics like MSE of .0091, MAE of .0525, RMSE of .0953, and MSLE of .0047.

Conditional survival analysis and dynamic survival prediction for intracranial solitary-fibrous tumor/hemangiopericytoma

BackgroundAs the form of World Health Organization Central Nervous System (WHO CNS) tumor classifications is updated, there is a lack of research on outcomes for intracranial combined solitary-fibrous tumor and hemangiopericytoma (SFT/HPC). This study aimed to explore conditional survival (CS) pattern and develop a survival prediction tool for intracranial SFT/HPC patients.MethodsData of intracranial SFT/HPC patients was gathered from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. The patients were split into training and validation groups at a 7:3 ratio for our analysis. CS is defined as the likelihood of surviving for a specified period of time (y years), given that the patient has survived x years after initial diagnosis. Then, we used this definition of CS to analyze the intracranial SFT/HPC patients. The least absolute shrinkage and selection operator (LASSO) regression and best subset regression (BSR) were employed to identify predictive factors. The Multivariate Cox regression analysis was applied to establish a novel CS-based nomogram, and a risk stratification system was developed using this model.ResultsFrom the SEER database, 401 patients who were diagnosed with intracranial SFT/HPC between 2000 and 2019 were identified. Among them, 280 were included in the training group and 121 were included in the internal validation group for analysis. Our study revealed that in intracranial SFT/HPC, 5-year survival rates saw significant improvement ranging from 78% at initial diagnosis to rates of 83%, 87%, 90%, and 95% with each successive year after surviving for 1–4 years. The LASSO regression and BSR identified patient age, tumor behavior, surgery and radiotherapy as predictors of CS-based nomogram development. A risk stratification system was also successfully constructed to facilitate the identification of high-risk patients.ConclusionThe CS pattern of intracranial SFT/HPC patients was outlined, revealing a notable improvement in 5-year survival rates after an added period of survival. Our newly-established CS-based nomogram and risk stratification system can provide a real-time dynamic survival estimation and facilitate the identification of high-risk patients, allowing clinicians to better guide treatment decision for these patients.

Evaluating Financial Risk in the Transition from EONIA to ESTER: A TimeGAN Approach with Enhanced VaR Estimations

This study investigates the evaluation of multivariate time series data using a Generative Adversarial Network (GAN). Calculating the Value at Risk (VaR) for the Euro Overnight Index Average (EONIA) over different time periods and evaluating the financial risk consequences of the EONIA to Euro Short-Term Rate (ESTER) transition are the main objectives. Through the use of a particular GAN called TimeGAN, which focuses on macro-finance temporal and latent representation, the study aims to predict short-rate risk for EONIA. When estimating lower VaR and the 1-day higher VaR for EONIA, the TimeGAN model performs poorly. However, it performs well when estimating upper VaR for 10-day and 20-day periods. The variation of TimeGAN with PLS+FM, which uses Positive Label Smoothing and Feature Matching shows the upper and lower VaR for EONIA over 10 and 20-day periods are excellently estimated by this enhanced model. Simulations for the 20-day EONIA show less variation between TimeGAN variations than a one-factor Vasicek model, even with the proper VaR estimations. This study evaluates the proposed transition mapping from ESTER to EONIA by the European Central Bank (ECB), calculating an ESTER+8.5bps shift with the TimeGAN with PLS+FM. The results do not refute the validity of the ECB's proposed EONIA-ESTER mapping. Additionally, the TimeGAN with PLS+FM accurately predicts VaR for 10 and 20-day periods for ESTER using the EONIA-ESTER mapping. Whereas the one-factor Vasicek model finds it difficult to estimate higher VaR for ESTER over the same time frames.

Enhancing multi-objective evolutionary algorithms with machine learning for scheduling problems: recent advances and survey

Multi-objective scheduling problems in workshops are commonly encountered challenges in the increasingly competitive market economy. These scheduling problems require a trade-off among multiple objectives such as time, energy consumption, and product quality. The importance of each optimization objective typically varies in different time periods or contexts, necessitating decision-makers to devise optimal scheduling plans accordingly. In actual production, decision-makers confront intricate multi-objective scheduling problems that demand balancing clients’ requirements and corporate interests while concurrently striving to reduce production cycles and costs. In solving various problems, multi-objective evolutionary algorithms have attracted the attention of researchers and gradually become one of the mainstream methods to solve these problems. In recent years, research combining multi-objective evolutionary algorithms with machine learning technology has shown great potential, opening up new prospects for improving the performance of multi-objective evolutionary methods. This article comprehensively reviews the latest application progress of machine learning in multi-objective evolutionary algorithms for scheduling problems. We review various machine learning techniques employed for enhancing multi-objective evolutionary algorithms, particularly focusing on different types of reinforcement learning methods. Different categories of scheduling problems addressed using these methods were also discussed, including flow-shop scheduling issues, job-shop scheduling challenges, and more. Finally, we highlighted the challenges faced by the field and outlined future research directions.

Long-term trends in incidence, mortality and burden of liver cancer due to specific etiologies in Hubei Province

Liver cancer, a chronic non-communicable disease, represents a serious public health problem. Long-term trends in the burden of liver cancer disease are heterogeneous across regions. Incidence and mortality of liver cancer, based on the Global Burden of Disease, were collected from the Chinese Centre for Disease Control and Prevention. Age–period–cohort model was utilized to reveal the secular trends and estimate the age, period and cohort effects on primary liver cancer due to specific etiologies. Both the age-standardized incidence and mortality rate of liver cancer in Hubei province were on the rise, although there were discrepancies between gender groups. From age–period–cohort analysis, both incidence and mortality of liver cancer due to Hepatitis B virus were the highest in all age groups. The incidence of all liver cancer groups increased with time period in males, while this upward trend was observed in females only in liver cancer due to alcohol use group. Cohort effects indicated the disease burden of liver cancer decreased with birth cohorts. Local drifts showed that the incidence of liver cancer due to specific etiologies was increasing in the age group of males between 40 and 75 years old. The impact of an aging population will continue in Hubei Province. the disease burden of liver cancer will continue to increase, and personalized prevention policies must be adopted to address these changes.

The Finnegan Score for Neonatal Opioid Withdrawal Revisited With Routine Electronic Data: Retrospective Study.

The severity of neonatal abstinence syndrome (NAS) may be assessed with the Finnegan score (FS). Since the FS is laborious and subjective, alternative ways of assessment may improve quality of care. In this pilot study, we examined associations between the FS and routine monitoring data obtained from the electronic health record system. The study included 205 neonates with NAS after intrauterine (n=23) or postnatal opioid exposure (n=182). Routine monitoring data were analyzed at 60±10 minutes (t-1) and 120±10 minutes (t-2) before each FS assessment. Within each time period, the mean for each variable was calculated. Readings were also normalized to individual baseline data for each patient and parameter. Mixed effects models were used to assess the effect of different variables. Plots of vital parameters against the FS showed heavily scattered data. When controlling for several variables, the best-performing mixed effects model displayed significant effects of individual baseline-controlled mean heart rate (estimate 0.04, 95% CI 0.02-0.07) and arterial blood pressure (estimate 0.05, 95% CI 0.01-0.08) at t-1 with a goodness of fit (R2m) of 0.11. Routine electronic data can be extracted and analyzed for their correlation with FS data. Mixed effects models show small but significant effects after normalizing vital parameters to individual baselines.

Modern trends in the development of plant production under agrarian crises

Modern trends in the development of plant production under agrarian crises

Changes in Pore Structure and Fractal Characteristics of Solvents Pretreated High-Rank Coal under Supercritical CO2

CO2 injection in coal seams, which is a significant initiative to mitigate environmental problems caused by greenhouse gases, often leads a sequence of changes in the physical properties of coal reservoirs. To look into how the pore structure changes in the process of CO2 sequestration, we selected fresh coal from Huoerxinhe coal mine in China as the object. Then, acid treatment and SC-CO2 extraction were used to dissolve Organic and inorganic components in coal. Thus, by using SEM, LTGA-N2 apparatus and XRD, the characteristics of pore parameter and fractal dimension variation were discussed. The research results show that, the APS of samples THF, HCL-HF and Y-C increase, while the total PV decreases and the pore connectivity deteriorates. The pore connectivity of Samples THF and HCL-HF is improved (THF-C, HCL-HF-C), but the total pore volume continuously reduces. In addition, solvents treatment and SC-CO2 extraction mainly act on the microporous fraction. After solvents pretreatment, the changes in the pore size distribution curves are mainly manifested in the reduction of number of micropores, especially in the micropores around 3–4 nm. There is a small increase in micropores for samples Y-C and HCL-HF-C, with the pore size mainly concentrated around 4 nm, while the pores of the sample THF-C mainly show an increase within the scope of 3–16 nm. Generally, solvent pretreatment and SC-CO2 extraction help to simplify pore structure. However, the sample HCL-HF-C shows opposite change characteristics. In a short period of time, the larger pore fractal dimension, the less beneficial it is to the flow of CO2, while pore fractal dimension becomes progressively less useful in assessing pore connectivity with increasing time.

A review of emerging trends in Laves phase research: Bibliometric analysis and visualization

Abstract The rapid development of modern aerospace and energy industries requires increasingly high service performance of metallic materials. Laves phase intermetallic compounds with the chemical formula AB2-type have attracted much attention due to their high melting point, excellent high-temperature strength, and oxidation resistance, and are regarded as one of the promising candidates for a new generation of high-temperature structural applications. Although it can be identified that Laves phase alloy research has been an active research field in the last 20 years in terms of the trend of literature volume growth, there is still a lack of systematic descriptions and comprehensive overviews of the latest frontiers and hotspots in the field. In this article, a quantitative and visual knowledge mapping of the articles published in the field of Laves phase research in the last 20 years has been carried out based on the bibliometric analysis methodology of Cite Space software. Quantitative analysis of high-frequency keywords to understand the basic development of Laves phase and the evolution of the main research hotspots in each period of time identified the hotspots of common concern seven themes: Laves phase, electronic structure, precipitation, Inconel 718 alloy, phase diagram, high-entropy alloys, and TiAl-based alloys. The analysis of the emergent keywords shows that electronic structure, high-entropy alloys, total energy calculations, and laser cladding can represent the research frontiers of Laves phases. This study provides systematic and valuable reference information to gain insight into the current state of Laves phase research and the evolution of the theme, which will be useful for further research.

Spatiotemporal evolution characteristics and driving forces of vegetation cover variations in the Chengdu-Chongqing region of China under the background of rapid urbanization.

The research on the spatiotemporal changes and driving factors of ecosystems in rapidly urbanizing regions has always been a topic of widespread concern. As the fourth pole of China's economic development, the research on the Chengdu-Chongqing region has reference significance for the urbanization process of developing countries such as India, Brazil, and South Africa.The normalized difference vegetation index (NDVI) has been widely applied in studies of plant and ecosystem changes. Based on MODIS NDVI data from 2001 to 2020 and meteorological data of the same period, this study reveals the evolution of NDVI in the Chengdu-Chongqing region from three aspects: the spatiotemporal variation characteristics of NDVI, the prediction of future trends in vegetation coverage, and the response of vegetation to climate change and human activities. During the period of plant growth, the mean NDVI achieved a value of 0.78, and the vegetation coverage rate is increasing year by year. According to the Hurst index, the future NDVI in Chengdu-Chongqing region will tend to decrease, and its trend is opposite to that of the past period of time. The Chengdu-Chongqing region vegetation positively affected by human activities is greater than those negatively affected, and in terms of vegetation degradation, the impact of human activities is greater than climate change.

The Role of New Era Exporters on the Financial Growth in India

The present study aims to investigate the relationships among India's financial development, international trade, and the evolution of economic growth. The study's primary focal areas have been the real GDP, which has replaced economic growth, export and import services, international commerce, gross capital creation, and exchange rate as independent variables. More frequent traders are often found to have excellent advancement rates and to have a positive influence on the growth of the financial industry and the economy. The research will also examine if there is a sustained correlation between various macroeconomic factors in India from 2000 to 2018, such as trade growth, financial development, and other macroeconomic variables. Regarding the previous sentence, the study employed the Johansen co-integration approach, KPSS, ADF, and PP to ascertain if financial development, economic growth, and trade variables continue to be associated over an extended period of time. These techniques were also applied to investigate the long-term relationships between particular variables. The direction of causation between variables can be ascertained using the Granger causality test. All of the variables have been shown to be non-stationar, and the study demonstrates that there is a long-term correlation between financial development, economic growth, and international trade. The study's conclusions show the interdependence of trade, financial development, and economic development; yet, while macroeconomic policy is stable, negative macroeconomic variables, such increasing inflation, might impede economic progress.

영상분석을 활용한 충청북도의 유튜브 홍보 전략에 관한 연구

The purpose of this study is to present a developmental model by analyzing the promotion and production strategies of local governments' YouTube channels. When the 8th popular election was launched, Chungcheongbuk-do, which recorded the ‘number of subscribers’ in the lowest ranks in the country, increased the number of subscribers to 3.5 in about a year, winning the grand prize in the ‘SNS of the Year Award’ part of the local government. The promotion and production strategy for YouTube in Chungcheongbuk-do can provide strategies for operating SNS channels of other local governments. The research method examined the causal relationship between the ‘title outlet and video concept’ of the video, and conducted content analysis to derive promotion and production strategies. As a result of analyzing the title concept (emphasis on the place, highlighting the concept) and the video concept (core person, core place, core concept), it was found that there is a causal relationship of the mutual organic narrative structure. The promotion strategies of YouTube in Chungcheongbuk-do were ① policy promotion, ② tourism promotion, ③ agricultural information, and ④ regional image and channel promotion, and the production strategy was ① familiar characters and ② experience highlights, ③ interest increases, and ④ show platform production. This study is meaningful as a study on YouTube channels of a very few local governments, where the number of subscriptions has increased rapidly in a short period of time, and it is worth using it for future local government YouTube research. However, there is a limit to the inability to conduct research on various factors such as production and editing subjects, content indicators (comments, etc.), and subtitles, so I hope that three-dimensional research will be conducted in subsequent studies.

Modelling of human thermal comfort in armored military vehicles: An experimental study of removing heat with spot cooling

Military combat vehicles differ in many ways from civil automotive vehicles because of their aim of usage and structure. One of these differences is using spot cooling technic for the air conditioning system in the vehicle. However, the A/C system in these vehicles is driven by the engine of the vehicle, like in civil automotive vehicles. When the engine of the vehicle is off, the A/C system does not work as well. But in some conditions, the military personnel in a military vehicle may need to work on some duties for some period of time without running the engine of the vehicle. So, military personnel need a secondary system that creates A/C effect for that period of time. In this study, an analytical model is prepared to determine the total amount of heat transfer value that should be removed from the personnel by spot cooling with different properties of blowing air to help in designing this required A/C effective system. This analytical model is validated with an experimental setup that simulates the conditions of a sample military combat vehicle. This validated analytical model has been carried out with respect to different blowing air properties and the range of distances between the louver and the personnel. The values that provide the minimum required amount of heat transfer to be removed from the personnel are determined and used to create thermal balance curves. These curves can be used to design a new A/C system to make military personnel comfortable in the vehicle.

Inference of highly time-resolved melt pool visual characteristics and spatially-dependent lack-of-fusion defects in laser powder bed fusion using acoustic and thermal emission data

With a growing demand for high-quality fabrication, the interest in real-time process and defect monitoring of laser powder bed fusion (LPBF) has increased, leading manufacturers to incorporate a variety of online sensing methods including acoustic sensing, photodiode sensing, and high-speed imaging. However, real-time acquisition of high-resolution melt pool images in particular remains computationally demanding in practice due to the high variability of melt pool morphologies and the limitation of data caching and transfer, making it challenging to detect the local lack-of-fusion (LOF) defect occurrences. In this work, we propose a new acoustic and thermal information-based monitoring method that can robustly infer critical LPBF melt pool morphological features in image forms and detect spatially-dependent LOF defects within a short time period. We utilize wavelet scalogram matrices of acoustic and photodiode clip data to identify and predict highly time-resolved (within a 1.0 ms window) visual melt pool characteristics via a well-trained data-driven pipeline. With merely the acoustic and photodiode-collected thermal emission data as the input, the proposed pipeline enables data-driven inference and tracking of highly variable melt pool visual characteristics with R2≥0.8. We subsequently validate our proposed approach to infer local LOF defects between two adjacent scanlines, showing that our proposed approach can outperform our selected baseline theoretical model based on previous literature. Revealing the physical correlation between airborne acoustic emission, thermal emission, and melt pool morphology, our work demonstrates the feasibility of creating an efficient and cost-effective acoustic- and thermal-based approach to facilitate online visual melt pool characterization and LOF defect detection. We believe that our work can further contribute to the advances in quality control for LPBF.

Examining Barriers to Early Hearing Diagnosis.

Many factors create barriers for early hearing detection and intervention (EHDI), especially those related to unfavorable social determinants of health (SDOH). The primary aim of this study was to evaluate diagnostic timing of infants at risk for congenital hearing loss in consideration of known barriers. Understanding the specific barriers to early diagnosis can inform interventions to improve timeliness of diagnosis and subsequent habilitation. A retrospective chart review was completed for infants referred for diagnostic audiologic testing at a tertiary urban-setting Children's Hospital from 2018 to 2021. After exclusion criteria were applied, 1,488 infants were included in the analysis. Various factors were recorded from electronic medical records including those specific to SDOH. Time to diagnosis was derived and compared across five factors of interest that have previously been shown to impact diagnostic timeline, including (a) insurance type, (b) race/ethnicity, (c) presence of middle ear dysfunction at first auditory brainstem response (ABR), (d) proximity to diagnostic center, and (e) diagnostic timing before and during/after the COVID-19 pandemic. Across the study time period, 77% of infants referred for diagnostic testing had confirmed diagnosis by the EHDI benchmark of 3 months. Analysis of time to diagnosis across factors of interest revealed no clinically significant differences for insurance type, race/ethnicity, proximity to diagnostic center, or timing in reference to the COVID-19 pandemic. Presence of middle ear dysfunction on first ABR was found to significantly protract final diagnostic timing. Although some known barriers for EHDI can be universal, other factors may have a differential impact on an infant's timeline to diagnosis based on their specific location, which can interact differently with additional known barriers. Understanding local challenges will serve to better guide programs in implementing facilitators that will address their specific needs for improved outcomes.

Cell and gene therapy investment: evolution and future outlook on investor perspectives

Background aimsTo better understand the attitudes and behaviors of investors involved in funding cell and gene therapy (CGT) businesses, the Business Development and Finance) subcommittee of International Society for Cell and Gene Therapy, in collaboration with Truist Securities, conducted a broad survey of the investment community in late 2021. MethodsThis survey follows a similar study that this group executed in 2018, and the longitudinal comparisons between the two time periods provide insights into how investor behavior in the CGT field has evolved. ResultsThe vast majority of investor respondents are specialist biotech investors who are primarily active in deploying capital in North America and Europe. There was a notable increase in the proportion of investors actively deploying capital in China and Japan between 2018 and 2021. The percentage of respondents’ portfolios dedicated to CGT companies has also increased in this period, reflecting a noteworthy trend in the therapeutic landscape. ConclusionsClinically significant data remain the dominant force behind investment decisions, whereas competition from other drug modalities has now emerged as the most-cited barrier to making a CGT investment, eclipsing safety concerns as the most significant barrier to investment in 2018. Concerns around manufacturing and scale-up have also increased in prominence amongst the investment community. Gene-editing technologies are attracting investors as the most compelling new CGT technology. This survey also revealed that most investors expect to increase their level of investment in allogeneic technologies relative to autologous products in the coming years.

Reducing Unnecessary Transfusions of RBCs in Inpatients Admitted Across Niagara Health Community Hospitals.

Blood products are scarce resources. Audits on the use of red blood cells (RBCs) in tertiary centers have repeatedly highlighted inappropriate use. Earlier retrospective audit at our local community hospitals has demonstrated that only 85% and 54% of all requests met Choosing Wisely Canada guidelines for pre-transfusion hemoglobin (Hb) of 80 g/L or less and single unit, respectively.We sought to improve RBC utilization by 15% over a period of 12 months (meeting Choosing Wisely Canada criteria of pre-transfusion Hb ≤80g/L by >80% and single-unit transfusion by >65%). Following repeated PDSA (Plan-Do-Study-Act) cycles, we implemented educational strategies, prospective transfusion medicine (TM) technologist-led screening of orders, and an RBC order set. The 3-month median percentages of appropriate RBC use for pre-transfusion Hb and single unit (September-November 2021) across all 3 hospitals were 90% and 71%, respectively. Overall, the rate of appropriate RBCs based on pre-transfusion Hb remained above target (>80%), with minimal improvement across all hospitals (median percentage at pre- and post-technologist screening periods of 87% and 90%, respectively). The median percentage of appropriate RBCs based on single-unit transfusion orders has improved across all Niagara Health hospitals with sustained targets (3-month median percentage at pre- and post-technologist screening and most recent time periods of 54%, 56%, and 71%, respectively). We have taken a collaborative, multifaceted approach to optimizing utilization of RBCs across the Niagara Health hospitals. The rates of appropriate RBC use were comparable with the provincial and national accreditation benchmark standards. In particular, the TM technologist-led screening was effective in producing sustained improvement with respect to single-unit transfusion. One of the balancing outcomes was increasing workload on technologists. Local and provincial efforts are needed to facilitate recruitment and retention of laboratory technologists, especially in community hospitals.

The impact of tropical cyclones and water conservancy projects on island's flash floods.

The analysis of the influencing factors of flash floods, one of the most destructive natural disasters, is the basis of scientific disaster prevention and mitigation. There is little research considering the influence of tropical cyclones (TCs) and water conservancy projects on flash floods, which cannot be ignored in the island areas where flash floods often occur due to the complex influence of various factors. In this study, under the pressure-state-response framework (PSR framework), the factors affecting the distribution of flash floods on Hainan Island, China, from 1970 to 2010 were quantitatively analyzed by using the geographical detector method. By dividing the time period, give full play to the advantages of the PSR framework and show the evolution process of various factors. Different from inland areas, extreme precipitation and tropical cyclones play a major role in the spatial distribution of flash floods on Hainan Island, China, and the driving force of tropical cyclones is 1.1 times that of extreme precipitation on average. Medium-sized reservoirs play the greatest role in the prevention of flash floods on Hainan Island, and their driving forces reach 0.38 times of extreme precipitation on average, followed by large-sized reservoirs and small-sized reservoirs. Large-sized reservoirs are limited in quantity and have limited effectiveness in preventing flash floods on Hainan Island. Therefore, in the forecasting and risk management of flash flood in the island area, more attention should be paid to the impact of extreme precipitation and TCs, and the role of medium-sized reservoir should be fully exerted.