Long-term Trends Research Articles

The return of tall forests: Reconstructing the canopy resilience of an extensively harvested primary forest in Mediterranean mountains

Understanding recovery times and mechanisms of ecosystem dynamics towards the old-growth stage is crucial for forest restoration, but still poorly delineated in Mediterranean. Through tree-ring methods, we reconstructed the return of a tall canopy after severe human disturbance in a mixed beech (Fagus sylvatica) and silver fir (Abies alba) forest, located at a mountain site in the southern edge of both species' range (Gariglione, south Italy). The primary forest was extensively harvested between 1930 and 1950, removing up to 91 % of the biomass. Growth histories, climate-growth relationships and time-series of growth dominance in Gariglione were compared with a network of protected mature and old-growth beech forests distributed along a wide elevational gradient in the same region. We found that the renewed tall canopy of Gariglione is mainly composed of remnant trees, which include uncut trees and saplings, and the post-harvesting regeneration mostly represented by fir. Canopy beech trees reached maximum basal area increment (BAI) in the 1970s, 40–50 years after cutting. Then, beech BAI shifted towards negative trends in phase with drying climate (PDSI), while fir maintained a sustained growth until 2000. This growth asynchrony between the two species conferred community stability over the last decades. The network comparison highlighted the common negative impact of summer drought on high-frequency growth signals of beech in south Italy. However, analysis of long-term mean growth trends indicates decreasing BAI limited to Gariglione beech, revealing relevant differences due to site ecology and its interactions with legacy effects of past management in driving growth responses to climate change. Indeed, lowland mature beech forests showed increasing BAI in the last decades, while primary high-mountain forests displayed a remarkably stable low oscillating growth. In all the Mediterranean forests we studied, large and old trees showed a marked growth acclimation despite ongoing climate warming, demonstrating the effectiveness of landscape rewilding.

Response of alpine vegetation function to climate change in the Tibetan Plateau: A perspective from solar-induced chlorophyll fluorescence

Vegetation change in the Tibetan Plateau (TP) is a crucial indicator of climate change in alpine regions. Previous studies have reported an overall greening trend in the vegetation structure across the TP, especially in its northeastern part, in response to a warming climate. However, variations in the vegetation function and the possible drivers remain poorly understood. Considering the optimal temperature for plants in TP is usually higher than the current temperature, our hypothesis is the function and structure of alpine vegetation have changed synchronously over past few decades. To test this hypothesis, we analyzed satellite-observed solar-induced chlorophyll fluorescence (SIF) and leaf area index (LAI) in the Yellow River source (YRS) region in the northeastern TP to quantify the long-term trends in vegetation functional and structural states, respectively. The results suggest that from 1982 to 2018, SIF increased significantly in 77.71 % of the YRS area, resulting in a significant upward trend of 0.52 × 10−3 mW m−2 nm−1 sr−1 yr−1 (p < 0.001) for the regional-mean SIF. This represents a 16.1 % increase in SIF, which is close in magnitude to the increase in LAI over the same period. The synchronous changes between vegetation function and structure suggest that improved greenness corresponds to a similar level of change in carbon uptake across YRS. Additionally, we used a multiple regression approach to quantify the contribution of climatic factors to SIF changes in YRS. Our analyses show that the increases in SIF were primarily driven by rising temperatures. Spatially, temperature dominated SIF changes in most parts of YRS, except for certain dry parts in the northern and western YRS, where precipitation had a greater impact. Our results are crucial for a comprehensive understanding of climate regulations on vegetation structure and function in high-elevation regions.

Prevalence, Awareness, Treatment, and Control of Type 2 Diabetes in South Korea (1998 to 2022): Nationwide Cross-Sectional Study.

Type 2 diabetes poses an increasing disease burden in South Korea. The development and management of type 2 diabetes are closely related to lifestyle and socioeconomic factors, which have undergone substantial changes over the past few decades, including during the COVID-19 pandemic. This study aimed to investigate long-term trends in type 2 diabetes prevalence, awareness, treatment, and control. It also aimed to determine whether there were substantial alterations in the trends during the pandemic and whether these changes were more pronounced within specific demographic groups. This study examined the prevalence, awareness, treatment, and control of type 2 diabetes in a representative sample of 139,786 South Koreans aged >30 years, using data from the National Health and Nutrition Examination Survey and covering the period from 1998 to 2022. Weighted linear regression and binary logistic regression were performed to calculate weighted β coefficients or odds ratios. Stratified analyses were performed based on sex, age, region of residence, obesity status, educational background, household income, and smoking status. β (difference) was calculated to analyze the trend difference between the prepandemic period and the COVID-19 pandemic. To identify groups more susceptible to type 2 diabetes, we estimated interaction terms for each factor and calculated weighted odds ratios. From 1998 to 2022, a consistent increase in the prevalence of type 2 diabetes was observed among South Koreans, with a notable rise to 15.61% (95% CI 14.83-16.38) during the pandemic. Awareness followed a U-shaped curve, bottoming out at 64.37% (95% CI 61.79-66.96) from 2013 to 2015 before increasing to 72.56% (95% CI 70.39-74.72) during the pandemic. Treatment also increased over time, peaking at 68.33% (95% CI 65.95-70.71) during the pandemic. Control among participants with diabetes showed no substantial change, maintaining a rate of 29.14% (95% CI 26.82-31.47) from 2020 to 2022, while control among treated participants improved to 30.68% (95% CI 27.88-33.48). During the pandemic, there was a steepening of the curves for awareness and treatment. However, while the slope of control among participants being treated increased, the slope of control among participants with diabetes showed no substantial change during the pandemic. Older populations and individuals with lower educational level exhibited less improvement in awareness and control trends than younger populations and more educated individuals. People with lower income experienced a deceleration in prevalence during the pandemic. Over the recent decade, there has been an increase in type 2 diabetes prevalence, awareness, treatment, and control. During the pandemic, a steeper increase in awareness, treatment, and control among participants being treated was observed. However, there were heterogeneous changes across different population groups, underscoring the need for targeted interventions to address disparities and improve diabetes management for susceptible populations.

Cardiac Electrical and Structural Changes after Iodinated Contrast Media Administration: A Longitudinal Cohort Analysis.

Background: Iodinated contrast is commonly used for radiological procedures, with one dose delivering several hundred-fold the daily requirements needed for normal thyroid hormone production. Risks of excess iodine include incident thyroid dysfunction, which is associated with adverse cardiac outcomes, yet there are no prospective studies investigating the changes in cardiac physiology following iodine contrast administration. This study was conducted to investigate the longitudinal relationships between the amount of iodinated contrast administration and changes in cardiac electrophysiology and structure. Methods: A longitudinal cohort study was conducted with prospectively enrolled participants who received iodine contrast for elective computed tomography or coronary angiography. Serum thyroid function tests, electrocardiograms (EKG), and transthoracic echocardiograms were obtained serially until 36 months. Trends of electrical and structural cardiac changes following iodine contrast administration were assessed using mixed effect models. Results: The cohort was composed of 129 patients (median age, 70 [interquartile range: 63, 75] years; 98% male). Larger amounts of iodine exposure were associated with increases in QRS and QTc durations and decreased ejection fraction (EF), and these associations were still observed for follow-up EF after additionally adjusting for baseline values (the high-iodine contrast group vs. the low-iodine contrast group, -4.23% [confidence interval, -7.66% to -0.79%]). Dose-response analyses also showed lower EF with larger amounts of iodine received; these trends were not significant for the EKG parameters studied. Conclusions: Over a period of up to 36 months, a larger amount of administered iodine contrast was associated with lower EF among participants. Further investigation is needed to elucidate the long-term trends of electrical and structural cardiac function after iodine contrast administration.

Research on Dynamic Pricing and Long-Term Profit of Companies under Influence of Word of Mouth

Word of mouth (WOM) is crucial in customers’ purchasing decisions and affects companies’ long-term profits. This study examines the long-term trends in companies’ dynamic pricing and profits by using the Hamiltonian function method and dynamic simulation to construct a dynamic equation. It takes into account the intensity of word of mouth faced by companies and analyzes the level of publicity and consumers’ predictions of product quality. In this paper, we also discuss the interactive processes between WOM and advertising levels, the two most prominent market factors, and their ultimate impact on companies. The experimental results show that elevated levels of external advertising can potentially prompt companies to establish higher product pricing strategies, particularly in scenarios where the intensity of word of mouth is pronounced. In the initial phases of market development, the saturation level of consumers within the market exerts a negligible influence on companies’ long-term profit margins. Conversely, the rate of natural attrition from consumers’ upper threshold of product quality expectations distinctly impacts companies’ profitability.

Long-term meteorological characteristics and extreme climate indices over Tirupati: a rapidly developing tropical city

Tirupati’s climate has undergone significant changes in both temperature and precipitation patterns. While there has been a consistent increase in rainfall during the southwest monsoon, there is a concerning long-term trend of a decrease in total annual precipitation over the last 30 years. The city has experienced a rise in wet days during both the southwest and northeast monsoons, yet a recent decrease over the past three decades. Heavy precipitation events, particularly during the southwest monsoon, have shown a positive trend, whereas there have been no significant changes in heavy rainfall days during the northeast monsoon. Temperature trends reveal that there has been a warming scenario, with a significant positive trend in annual maximum temperatures and a consistent annual rise in mean minimum temperatures. A substantial decrease in cold and very cold days, especially during the last 30 years, suggests a broader warming trend impacting seasonal temperature variations in Tirupati. These findings highlight the complex interplay of monsoons, temperature variations, and changing precipitation patterns in Tirupati's climate over the years.

Long- and short-term coupling of sea surface temperature and atmospheric CO2 during the late Paleocene and early Eocene

The late Paleocene and early Eocene (LPEE) are characterized by long-term (million years, Myr) global warming and by transient, abrupt (kiloyears, kyr) warming events, termed hyperthermals. Although both have been attributed to greenhouse (CO2) forcing, the longer-term trend in climate was likely influenced by additional forcing factors (i.e., tectonics) and the extent to which warming was driven by atmospheric CO2 remains unclear. Here, we use a suite of new and existing observations from planktic foraminifera collected at Pacific Ocean Drilling Program Sites 1209 and 1210 and inversion of a multiproxy Bayesian hierarchical model to quantify sea surface temperature (SST) and atmospheric CO2 over a 6-Myr interval. Our reconstructions span the initiation of long-term LPEE warming (~58 Ma), and the two largest Paleogene hyperthermals, the Paleocene-Eocene Thermal Maximum (PETM, ~56 Ma) and Eocene Thermal Maximum 2 (ETM-2, ~54 Ma). Our results show strong coupling between CO2 and temperature over the long- (LPEE) and short-term (PETM and ETM-2) but differing Pacific climate sensitivities over the two timescales. Combined CO2 and carbon isotope trends imply the carbon source driving CO2 increase was likely methanogenic, organic, or mixed for the PETM and organic for ETM-2, whereas a source with higher δ13C values (e.g., volcanic degassing) is associated with the long-term LPEE. Reconstructed emissions for the PETM (5,800 Gt C) and ETM-2 (3,800 Gt C) are comparable in mass to future emission scenarios, reinforcing the value of these events as analogs of anthropogenic change.

Long-term trends in dissolved oxygen and environmental parameters in Jinhae Bay, Korea: A 25-year analysis (1997–2021)

In recent decades, global oceanic dissolved oxygen (DO) levels have been consistently declining, leading to a notable increase in hypoxic zones. However, comprehensive information on the current trends of DO in Jinhae Bay remains scarce. This study investigated the long-term variations in bottom dissolved oxygen (DO) in Jinhae Bay, specifically focusing on recurring occurrences of oxygen-deficient water (ODW) in August, coinciding with the lowest average DO levels with the most stratified water. ODW events predominantly manifested in the inner bay, while the outer bay exhibited fewer instances due to robust water exchange processes. Analysis of the Low DO group revealed higher surface temperature and salinity, indicating diminished oxygen solubility compared to the High DO group. Lower Chemical oxygen demand (COD) and chlorophyll-a (Chl-a) values in the Low DO group suggested enhanced bacterial decomposition and subdued photosynthesis, in contrast to the High DO group. Over the last 25 years, Jinhae Bay has experienced a discernible decline in bottom DO concentrations. Contrastingly, surface temperature has exhibited a consistent upward trend, notably accelerating in the last 12 years, indicating reduced oxygen solubility. Notably, a substantial reduction in bottom DO levels was observed in the outer bay, previously considered less susceptible to hypoxic conditions. Furthermore, a concurrent decrease in pH highlights the urgency for a comprehensive investigation encompassing both summer hypoxia and seawater acidification, crucial for protecting Jinhae Bay's ecosystem from further deterioration.

Potential Impacts of Future Climate Change on Super-Typhoons in the Western North Pacific: Cloud-Resolving Case Studies Using Pseudo-Global Warming Experiments

Potential impacts of projected long-term climate change toward the end of the 21st century on rainfall and peak intensity of six super-typhoons in the western North Pacific (WNP) are assessed using a cloud-resolving model (CRM) and the pseudo-global warming (PGW) method, under two representative concentration pathway (RCP) emission scenarios of RCP4.5 and RCP8.5. Linear long-term trends in June–October are calculated from 38 Coupled Model Intercomparison Project phase 5 (CMIP5) models from 1981–2000 to 2081–2100, with warmings of about 3 °C in sea surface temperature, 4 °C in air temperature in the lower troposphere, and increases of 20% in moisture in RCP8.5. The changes in RCP4.5 are about half the amounts. For each typhoon, three experiments are carried out: a control run (CTL) using analysis data as initial and boundary conditions (IC/BCs), and two future runs with the trend added to the IC/BCs, one for RCP4.5 and the other for RCP8.5, respectively. Their results are compared for potential impacts of climate change. In future scenarios, all six typhoons produce more rain rather consistently, by around 10% in RCP4.5 and 20% in RCP8.5 inside 200–250 km from the center, with increased variability toward larger radii. Such increases are tested to be highly significant and can be largely explained by the increased moisture and water vapor convergence in future scenarios. However, using this method, the results on peak intensity are mixed and inconsistent, with the majority of cases becoming somewhat weaker in future runs. It is believed that in the procedure to determine the best initial time for CTL, which yielded the strongest TC, often within a few hPa in minimum central sea-level pressure to the best track data, an advantage was introduced to the CTL unintentionally. Once the long-term trends were added in future runs, the environment of the storm was altered and became not as favorable for subsequent intensification. Thus, the PGW approach may have some bias in assessing the peak intensity of such super-typhoon cases, and caution should be practiced.

Economic activities, dry bulk freight, and economic policy uncertainties as drivers of oil prices: A tail-behaviour time-varying causality perspective

This paper examines the dynamic impact of economic activity, Baltic dry bulk and economic policy uncertainty on oil prices. Drawing on demand-side economic theory, we focus on how economic activity and economic policy uncertainty drive oil prices and subsequently contribute to the formation of market equilibrium. In this context, we first introduce a unidirectional quantile and time-varying Granger-causality mechanism for the drivers of oil prices. Our novel rolling window quantile Granger causality approach reveals that economic activity drives crude oil price fluctuations and highlights their important role in market imbalances. In particular, economic activity and the Baltic exchange rate index emerge as essential drivers of oil prices, confirming our hypothesis of a demand-side effect. Moreover, our robustness wavelet quantile correlation (WQC) analyses reveal that economic activity promotes oil price fluctuations along both long-term equilibrium trends and short-term dynamics. In contrast, economic policy uncertainty has a dampening effect on oil prices. More broadly, economic activity is positively correlated with the Baltic exchange dry index, highlighting its broader impact on global trade indicators. Moreover, we use a bivariate Quantile on Quantile regression method to identify the equilibrium searches of different thresholds and estimate the robustness of the validity of the WQC findings. Analyzing the quantile and frequency connectedness spillovers, we observe that shocks from economic activity are particularly pronounced in the tail quantiles, reinforcing the demand-side narrative. Overall, the increased risk in extreme tails underscores the increased interaction between economic activity, oil prices and economic policy uncertainties. Our findings have important implications for policymakers and highlight the need for adaptive strategies to manage potential oil price shocks. Thus, by adopting a demand-side perspective, policymakers can better anticipate and respond to oil price fluctuations, promoting more resilient economic policies.

Longer-term impacts of the COVID-19 pandemic on obstructive sleep apnoea (OSA)-related healthcare: a province-based study

RationaleFollowing marked reductions in sleep medicine care early in the COVID-19 pandemic, there is limited information about the recovery of these services. We explored long-term trends in obstructive sleep apnoea...

Long-Term Variation Patterns of Precipitations Driven by Climate Change in China from 1901 to 2022

Studying long-term precipitation trends is crucial for sustainable development, as the proper utilization of water resources is essential for maintaining a sustainable water supply. The objective and novelty of this paper was to reveal the gradual mutation process of precipitation in China over a century. This study utilized monthly precipitation data from 1901 to 2022 (at a century scale) to analyze and explore the spatiotemporal variability in precipitation across different time scales and regions with a trend analysis, an abrupt change analysis, and gravity center models. The findings indicate that (1) from 1901 to 2022, the precipitation in China generally decreased from the southeast coastal areas toward the northwest inland regions. (2) There were significant differences in the migration of precipitation gravity centers among the different study regions, with the least dispersion being observed in the Liao River basin, while the Hai River basin, various river basins in the northwest, and the Pearl River basin exhibited certain regularities in gravity center movement, and other regions showed periodic variations. (3) Over the period from 1901 to 2022, there was a trend of transitioning from lower to higher precipitation levels. (4) According to continuous long-term abrupt change tests, the timing of precipitation shifts varied across different basins. Precipitation, as a crucial component of natural resources, directly impacts various aspects of socio-economic life. Research findings provide decision support for regional flood control and disaster reduction and offer scientific decisions for ecological security.

Expert-based prior uncertainty analysis of gridded water balance components: Application to the irrigated Hindon River Basin, India

Study regionHindon River Basin, North India. Study focusAccurate estimation of water balance components is crucial for water management applications yet challenging due to errors in monthly gridded water balance data products. Error and uncertainty quantification is especially important in the absence of extensive in-situ data. This paper presents a prior uncertainty analysis for such situations consisting of two components: (i) quantification of prior uncertainties using metrics that quantify errors in individual products and variability and consistency between products, and (ii) reduction of prior uncertainties by eliminating unrealistic water balance estimates. New hydrological insights for the regionGrid-scale inter-product uncertainty or variability, computed as the coefficient of variation (CV, %) at various temporal scales, reveals discrepancies between water balance products due to a combination of factors, including methodological differences, inherent spatial variability, data sources, and resolution disparities. At the mean annual scale, P fluxes display a lower grid-scale inter-product uncertainty (5–9 %) than ET (20–55 %), while the ∆TWS from GRACE solutions show a moderate mean annual grid-scale inter-product uncertainty (15–19 %). Grid-scale inter-product uncertainties of ∆SMS for July – representing the onset of the monsoon season – are high (CV = 54–122 %), indicating that the uncertainty in estimates of this component may have a large impact on water balance analyses. P fluxes exhibited fewer spatio-temporal uncertainties (R2 above 0.8) than ET fluxes (R2 less than 0.75). The exclusion of the unreliable data sets resulted in (a) reducing uncertainties in input water balance components with triple collocation range shifting from 15–38 to 17–23 mm/month for ET and from 16–52 to 11–23 mm/month for P, (b) obtaining updated prior estimates of seasonal water balance. The updated priors of water balance variables per season suggest a net basin outflow (from −318 to −57 mm/season) during the monsoon (rainy) season and net basin inflow (from −38 to 330 mm/season) during the non-monsoon (dry) season, the latter related to surface-water imports from outside the basin. All GRACE data sets exhibit a regional long-term decreasing trend in total water storage (ranging from −31 to −61 mm/year), qualitatively confirming previously documented unsustainable groundwater depletion in the basin. Prior ranges and uncertainties for all water balance variables reported here can be used as input into a posterior analysis that uses in-situ data for locally calibrating (bias-correcting, noise-filtering) and further updating the prior estimates.

Very Long-periodic Pulsations Detected Simultaneously in a White-light Flare and Sunspot Penumbra

We investigate the origin of very long-periodic pulsations in the white-light emission of an X6.4 flare on 2024 February 22 (SOL2024-02-22T22:08), which occurred at the edge of a sunspot group. The flare white-light fluxes reveal four successive and repetitive pulsations, which are simultaneously measured by the Helioseismic and Magnetic Imager and the White-light Solar Telescope. A quasi-period of 8.6−1.9+1.5 minutes, determined by the Morlet wavelet transform, is detected in the visible continuum channel. The modulation depth, which is defined as the ratio between the oscillatory amplitude and its long-term trend, is smaller than 0.1%, implying that the quasi-periodic pulsation (QPP) feature is a weak wave process. Imaging observations show that the X6.4 flare occurs near a sunspot group. Moreover, the white-light brightening is located in sunspot penumbra, and a similar quasi-period of about 8.5 −1.8+1.6 minutes is identified in one penumbral location of the nearest sunspot. The map of Fourier power distribution suggests that a similar periodicity is universally existing in most parts of the penumbra that is close to the penumbral–photospheric boundary. Our observations support the scenario that the white-light QPP is probably modulated by the slow-mode magnetoacoustic gravity wave leaking from the sunspot penumbra.

Long-term trends in human-induced water storage changes for China detected from GRACE data

Terrestrial Water Storage (TWS) plays a pivotal role in water resource management by providing a comprehensive measure of both surface water and groundwater availability. This study investigates changes in TWS driven by human activities from 2003 to 2023, and forecasts future TWS trends under various climate change and development scenarios. Our findings reveal a continuous decline in China's TWS since 2003, with an average annual decrease of approximately 1.36 mm. This reduction is primarily attributed to the combined effects of climate change and human activities, including irrigation, industrial water use, and domestic water consumption. Notably, TWS exhibits significant seasonal and annual fluctuations, with variations ranging ±10 mm. For the future period (2024–2030), we project greater disparities between water resource supply and demand in specific years for the Songliao, Southwest, and Yangtze basins. Consequently, future water resource management must prioritize water conservation during wet seasons, particularly in years when supply-demand conflicts for limited water resources intensify. This study is valuable for effective planning and sustainable utilization of water resources.

Learning the feature distribution similarities for online time series anomaly detection

Identifying anomalies in multi-dimensional sequential data is crucial for ensuring optimal performance across various domains and in large-scale systems. Traditional contrastive methods utilize feature similarity between different features extracted from multidimensional raw inputs as an indicator of anomaly severity. However, the complex objective functions and meticulously designed modules of these methods often lead to efficiency issues and a lack of interpretability. Our study introduces a structural framework called SimDetector, which is a Local–Global Multi-Scale Similarity Contrast network. Specifically, the restructured and enhanced GRU module extracts more generalized local features, including long-term cyclical trends. The multi-scale sparse attention module efficiently extracts multi-scale global features with pattern information. Additionally, we modified the KL divergence to suit the characteristics of time series anomaly detection, proposing a symmetric absolute KL divergence that focuses more on overall distribution differences. The proposed method achieves results that surpass or approach the State-of-the-Art (SOTA) on multiple real-world datasets and synthetic datasets, while also significantly reducing Multiply-Accumulate Operations (MACs) and memory usage.

The Assessment of Precipitation and Droughts in the Aegean Region Using Stochastic Time Series and Standardized Precipitation Index

This study analyzes drought conditions in the Aegean region using monthly precipitation data from nine stations between 1972 and 2020. The Standardized Precipitation Index (SPI) was calculated for 1-, 3-, 6-, 9-, and 12-month periods to evaluate drought conditions at different timescales and station-specific conditions. The results indicate that short-term droughts are more frequent but shorter in duration, while longer periods exhibit fewer but more prolonged droughts. The relative frequency of drought across all periods ranges between 9% and 27%. The İzmir and Denizli stations were highlighted due to their representation of coastal and inner regions, respectively. The findings show that coastal stations, like İzmir, experience more frequent wet years compared to inner stations like Denizli, which have more dry years. Time series linear autoregressive (AR) models, using SPI-12 data, were developed to represent long-term drought trends and forecasts. The best-fitting models were determined using AIC, AICC, FPE, and Var(e) criteria, with AR(2) generally being the most suitable, except for Denizli. This integrated analysis of SPI and AR models provides a robust basis for understanding regional precipitation regimes and predicting future droughts, aiding in the development of effective drought mitigation strategies and water resource management. Future research is anticipated to extend this analysis to encompass all of Turkey and explore various time series models’ applicability.

The Effect of the RMAT Designation on Biotechnology Stock Prices, Drug Development Timelines and Outcomes: An Empirical Analysis

This research examines the impact of the U.S. FDA's Regenerative Medicine Advanced Therapy (RMAT) designation on biotechnology and small pharmaceutical companies, focusing on both stock price reactions and drug development timelines. The research employs an event-study methodology to analyze share price movements following RMAT announcements and evaluates the long-term product development outcomes for these companies. Findings reveal that while RMAT designation leads to an initial short-term stock price increase of approximately 8.11% within five days, this optimism diminishes over time, with long-term trends showing a decline in stock value. Furthermore, products under RMAT designation exhibited longer development timelines compared to non-RMAT therapies, raising questions about the designation's effectiveness in accelerating product availability. The study underscores the complex implications of RMAT for stakeholders, emphasizing the need for strategic planning and further regulatory refinement to better align short-term investor expectations with long-term product development realities.

When wavelet decomposition meets external attention: a lightweight cloud server load prediction model

Load prediction tasks aim to predict the dynamic trend of future load based on historical performance sequences, which are crucial for cloud platforms to make timely and reasonable task scheduling. However, existing prediction models are limited while capturing complicated temporal patterns from the load sequences. Besides, the frequently adopted global weighting strategy (e.g., the self-attention mechanism) in temporal modeling schemes has quadratic computational complexity, hindering the immediate response of cloud servers in complex real-time scenarios. To address the above limitations, we propose a Wavelet decomposition-enhanced External Transformer (WETformer) to provide accurate yet efficient load prediction for cloud servers. Specifically, we first incorporate discrete wavelet transform to progressively extract long-term trends, highlighting the intrinsic attributes of temporal sequences. Then, we propose a lightweight multi-head External Attention (EA) mechanism to simultaneously consider the inter-element relationships within load sequences and the correlations across different sequences. Such an external component has linear computational complexity, mitigating the encoding redundancy prevalent and enhancing prediction efficiency. Extensive experiments conducted on Alibaba Cloud’s cluster tracking dataset demonstrate that WETformer achieves superior prediction accuracy and the shortest inference time compared to several state-of-the-art baseline methods.

Modelling an urban wastewater system via a space–time multivariate calibration to understand and improve water bodies quality

ABSTRACT The European Water Framework Directive requires good quality status for water bodies remaining solely attainable through a global approach. Urban wastewater integrated modelling is a promising tool for this purpose. However, certain barriers still hinder its application, such as the significant amount of data required and specifically in the sewer system, the issues with data quality or the monitoring and maintenance costs. This study develops an integrated model for Dijon Metropole in France using multiple hydraulic and quality data sources (e.g. sensors, analysers, laboratory measurements) and calibration criteria. The results show that long-term trends can be predicted for hydraulic and quality variables. The scenarios demonstrate that combined sewer overflows are responsible for most of the anoxic and ammonium high concentration periods in the rivers during rain events compared to the Water Resources Recovery Facility (WRRF). Therefore, adding storm tanks in the wastewater system will reduce stress on aquatic organisms during rainfall events. Reducing WRRF discharge during wet weather can also reduce the average and percentile of ammonium in the river. These results indicate that strategies should be adapted depending on the water quality objective (biological and/or physico-chemical) and the sensitivity of the organisms present in the river.