Spatiotemporal Distribution Research Articles

Observation Definitions and Their Implications in Machine Learning–Based Predictions of Excessive Rainfall

Abstract The implications of definitions of excessive rainfall observations on machine learning model forecast skill are assessed using the Colorado State University Machine Learning Probabilities (CSU-MLP) forecast system. The CSU-MLP uses historical observations along with reforecasts from a global ensemble to train random forests to probabilistically predict excessive rainfall events. Here, random forest models are trained using two distinct rainfall datasets, one that is composed of fixed-frequency (FF) average recurrence intervals exceedances and flash flood reports and the other a compilation of flooding and rainfall proxies [Unified Flood Verification System (UFVS)]. Both models generate 1–3-day forecasts and are evaluated against a climatological baseline to characterize their overall skill as a function of lead time, season, and region. Model comparisons suggest that regional frequencies in excessive rainfall observations contribute to when and where the ML models issue forecasts and subsequently their skill and reliability. Additionally, the spatiotemporal distribution of observations has implications for ML model training requirements, notably, how long of an observational record is needed to obtain skillful forecasts. Experiments reveal that shorter-trained UFVS-based models can be as skillful as longer-trained FF-based models. In essence, the UFVS dataset exhibits a more robust characterization of excessive rainfall and impacts, and machine learning models trained on more representative datasets of meteorological hazards may not require as extensive training to generate skillful forecasts. Significance Statement Machine learning (ML) models have shown significant promise in recent years when used to predict high-impact weather hazards. Here, we explore two similarly trained ML models tasked with predicting excessive rainfall, but they use datasets that define excessive rainfall differently. We explore how definitions of excessive rainfall, for example, an amount of rainfall that would be expected to fall once per year, contribute to forecast skill through where these observations are reported. Generally, we find that the two models have substantial skill relative to climatology out to 3 days, but skill varies by geographical region and season in part because of the distribution of observations geographically. These results suggest that careful attention should be paid to how ML models are trained to predict meteorological hazards like excessive rainfall.

Spatial variability of hydraulic parameters of a cropped soil using horizontal crosshole ground penetrating radar

AbstractSoil hydraulic parameters (SHP) play a crucial role controlling the spatiotemporal distribution of water in the soil–plant continuum and thus affect water availability for crops. To provide reliable information on the SHP at different scales, measurement techniques with a good spatial resolution and low labor costs are required. In this study, we used crosshole ground penetrating radar (GPR)‐derived soil water contents (SWCs) measured along horizontal rhizotubes under a controlled experimental test site cropped with winter wheat to estimate the unimodal and dual‐porosity soil hydraulic characteristics with different soil layer setups. Therefore, sequential inversion of the GPR‐derived SWCs was performed using the hydrological model HYDRUS‐1D, whereby the SWC data were either averaged prior inversion or used in a spatially distributed way. To analyze if the time‐lapse gathered GPR data contain enough information to estimate the SHP, additional synthetic studies were performed increasing the data resolution to daily GPR measurements. The results showed that the time‐lapse data contained enough information to estimate the SHP accurately. Additionally, spatially distributed soil hydraulic characteristics differed from the one estimated based on averaged SWCs derived from spatially distributed GPR data. Finally, we derived spatially resolved SHP, which can be used for 3D process rhizosphere processes and root–soil interaction modeling.

Impact of Tonga volcanic eruption on the ionosphere based on ground-based GNSS and COSMIC occultation data

The eruption of large volcanoes may potentially disturb the upper atmosphere, causing disturbances in ionospheric plasma and triggering irregular changes in the Total Electron Content (TEC). The GNSS ionospheric inversion method has been used to analyze ionospheric anomalies caused by the volcano, while it was limited to the spatial distribution of ground-based GNSS. The joint observation with space-based GNSS can further improve the spatio-temporal distribution of ionospheric monitoring. The Tonga volcano erupted on January 15th, 2022, is the largest volcanic eruption since the beginning of the 21st century and generated intense acoustic, atmospheric gravity waves and ionospheric disturbance. In this paper, we used the GIM products, ground-based GNSS station data around the volcanic eruption point and COSMIC occultation data to analyze the short-term TEC change. The experiments showed that: the average TEC of GIM grid data on eruption day dropped by 7.5 TECu compared to the last day which was substantially larger than other three days. The TEC extracted from nearby tracking stations was smaller than GIM and the difference was inversely proportional to the distance between the station and the volcanic eruption site. The average daily ionospheric TEC obtained from the nearest TONG station was the biggest, as much as 3.44 TECu lower. The peak electron density of COSMIC occultation data gradually diminished and then recovered with TEC about 7.32 TECu lower than GIM products. The experments showed that there was a good consistency in the TEC obtained from space-based and ground-based GNSS, the Tonga volcano produced a huge TEC change over 10 TECu or even bigger. As a global grid product, GIM underestimated ionospheric changes due to its limited spatial resolution, which needs further improvement.

Comparison of K-Means and FCM Algorithms to Optimize Spatiotemporal Pore Pressure Prediction of Earth Dams

To identify the behavior and health monitoring of dams, it is necessary to correctly interpret the results of instrumentation in different phases of construction, impounding, and operation. Therefore, the approach based on spatiotemporal prediction is presented to improve the interpretation of pore pressure behavior of Eyvashan Earth Dam. In this research, using the results of other existing healthy piezometers, a spatiotemporal distribution model is proposed using panel data, which can be effective for predicting and reconstructing missing data. The optimal spatiotemporal clustering of pore pressure changes monitoring with K-Means and Fuzzy C-means (FCM) algorithms will enable the monitoring of points of the dam where instrumentations are not designed and installed or defective instrumentations. In predicting the pore pressure of dams, the input data is classified based on the pore pressure monitoring data, but with the use of clustering algorithms, the classification after the cluster analysis steps will lead to the proper resolution of the pore pressure clustering. According to the validation results of each of the clustering algorithms, the FCM clustering algorithm has more suitable results than the K-Means algorithm in determining the pore pressure clusters. In general, FCM clustering and K-Means algorithms are suitable and efficient tools in the field of more accurate monitoring of earth dams, and by using the proposed method, the detection of unusual areas of pore pressure and the related safety diagnosis is facilitated.

A change in circulating chikungunya virus variant impacts Aedes aegypti vector competence and spatiotemporal distribution of disease in Malaysia.

In 2008-2010, Malaysia experienced a nationwide chikungunya virus (CHIKV) outbreak caused by the Indian Ocean lineage E1-226V (valine) variant, adapted to Aedes albopictus. In 2017-2022, transition to an E1-226A (alanine) variant occurred. Ae. albopictus prevails in rural areas, where most cases occurred during the E1-226V outbreak, while Ae. aegypti dominates urban areas. The shift in circulating CHIKV variants from E1-226V to E1-226A (2009-2022) was hypothesized to result in a transition from rural to urban CHIKV distribution, driven by differences in Ae. aegypti vector competence for the two variants. This study aimed to: (1) map the spatiotemporal spread of CHIKV cases in Malaysia between 2009-2022; and (2) compare replication of E1-226A and E1-226V variants in the midguts and head/thoraxes of Ae. aegypti. Spatiotemporal analysis of national notified CHIKV case addresses was performed. Between 2009-2022, 12,446 CHIKV cases were reported, with peaks in 2009 and 2020, and a significant shift from predominantly rural cases in 2009-2011 (85.1% rural), to urban areas in 2017-2022 (86.1% urban; p<0.0001). Two Ae. aegypti strains, field-collected MC1 and laboratory Kuala Lumpur (KL) strains, were fed infectious blood containing constructed CHIKV clones, pCMV-p2020A (E1-226A) and pCMV-p2020V (E1-226V) to measure CHIKV replication by real-time PCR and/or virus titration. The pCMV-p2020A clone replicated better in Ae. aegypti cell line Aag2 and showed higher replication, infection and dissemination efficiency in both Ae. aegypti strains, compared to pCMV-p2020V. This study revealed that a change in circulating CHIKV variants can be associated with changes in vector competence and outbreak epidemiology. Continued genomic surveillance of arboviruses is important.

Spatiotemporal Distribution of Human Rabies and Identification of Predominant Risk Factors in China from 2004 to 2020.

Human rabies is a prevalent issue in China, posing a significant public health concern in the country. This study fitted the Bayesian model of separable in spatial and temporal variation and inseparable spatiotemporal variation in disease risk respectively based on Integrated Nested Laplace Approximation (INLA) to investigate the spatiotemporal characteristics of human rabies across 31 provinces in China from 2004 to 2020. It also investigated the influence of natural and socio-environmental factors on the incidence of the disease. Within the study period, a total of 26,807 cases of human rabies were reported, with the highest risk of incidence occurring in 2007, followed by a steady annual decline to the lowest risk in 2020. Guangxi Province exhibited the highest risk, while Jilin Province had the lowest, with the southern, central, and eastern regions reporting higher risks than the northern and western areas. By 2020, most provinces such as Guangxi and Guizhou had significantly reduced their relative risk (RR) of human rabies from historical highs. However, some provinces like Hunan, Henan, and Jiangsu experienced an increase in RR compared to previous years. As the annual average temperature increases, the risk of human rabies incidence in China correspondingly rises. Conversely, with increases in the annual average daily sunshine duration, per capita disposable income of urban residents, and local government healthcare expenditures, the risk of human rabies incidence declines. We conclude that the risk of human rabies in China initially increased and then decreased annually from 2004 to 2020. Future efforts should continuously increase financial investments in rabies prevention and control, focusing particularly on Hunan, Henan, Jiangsu, and provinces characterized by higher temperatures, shorter sunshine durations, and lower economic levels.

Estimating wetland CH4 emissions on the Qinghai-Tibetan Plateau based on a processed model coupled with inundation dynamics between 1960 and 2100

Quantifying the impacts of climate change and wetland area dynamics on methane (CH4) emissions in the Qinghai-Tibetan Plateau (QTP) is crucial for enhancing our understanding of regional and global CH4 budgets. However, a major source of uncertainty in estimating wetland methane emissions stems from the limited delineation of wetland area dynamics. In this study, we integrated dynamic wetland inundation schemes into a process-based model to quantify the contributions of wetland area variations to natural wetland CH4 emissions on the QTP, both historically and in the future. The results revealed that climate change significantly influenced the spatiotemporal distribution of wetland CH4 emissions, with wetland inundation dynamics contributing between 21.84 % and 27.18 % of the increase in CH4 emissions from 1960 to 2020. Under future climate change scenarios, wetland CH4 emissions are projected to exhibit a more pronounced increasing trend, with wetland inundation dynamics projected to contribute 18.94 % to 21.80 % of the increase in CH4 emissions in the QTP under seven Shared Socioeconomic Pathways scenarios.

The spatiotemporal distribution and environmental suitability evaluation of Neolithic settlements in the Western Guanzhong Basin of China

Illustrating the relationship between past settlement changes and human-land could help us to understand the complex interactions among climate, human activities, and the environment. Based on archeological literature and fieldworks, this paper combines dating techniques and GIS analysis to explore the spatial and temporal distribution characteristics and human diffusion of Neolithic settlements in the Western Guanzhong Basin (WGB), and to quantitatively analyzes the relationship between human activities and natural geographic factors by index model. The results show that: (1) There was a continuity of Neolithic cultures in the WGB and the absolute chronological sequence of human activities ranges from 7500 to 3900 a BP; (2) The distribution of settlements tends to be on river terraces and Loess tableland, and with the evolution of Neolithic cultures, human activities shifted from near-water to far-water distributions and expanded to areas of high gradient. The center of activity of the settlement spreads from a single nucleus (the Wei River) to multiple nuclei (the Wei River, the Qian Rivers, and the Qishui River) and back to a single nucleus on the northern bank of the Wei River in the area of present Qishan-Fufeng, laying the foundation for the development and strength of the Western Zhou Dynasty Cultures in this area; (3) The suitability level of the natural geographic environment in the WGB gradually decreased from the Wei River to the north and south, and settlements were mainly distributed in the highly and moderately suitable zones; (4) It was found that as early as the Neolithic period, mankind had already grasped certain laws of nature, and the spatial distribution of settlements reflected mankind’s awareness of disaster avoidance and “compromise and reconciliation.”

Spatiotemporal distribution of toponymic cultural heritage in Jiangsu Province and its historical and geographical influencing factors

As a typical intangible cultural heritage, Toponymic Cultural Heritage (TCH) is rich in geographic information and semantic and physical connotations. In the context of the heritage conservation era, it is highly important to study the spatiotemporal distribution characteristics of toponymic cultural heritage and explore its historical and geographic influencing factors on the sustainable conservation and development of toponymic cultural heritage. However, most existing studies focus on the toponym cultural landscape, and less attention has been given to TCH. Therefore, on the basis of the data of 357 provincial TCH items in Jiangsu Province, this study investigated the spatiotemporal distribution characteristics and historical–geographical influencing factors of the TCH by using geospatial analysis methods, such as the average nearest neighbor, tyson polygon, kernel density estimation, standard deviational ellipse, and superposition coupling analysis, and proposed several strategies for adaptive reuse of TCH. The results show that (1) the TCHs of Jiangsu Province have a spatial distribution characteristic of "sparse in the north, scattered in the middle and dense in the south" and form a high-density agglomeration around the southern part of Jiangsu Province. In the distribution of cultural districts, the Jinling cultural district, the Wu cultural district, and the Huaiyang cultural district have the largest number of TCHs. (2) From the Pre-Qin period to the Ming and Qing Dynasties, TCHs, such as Nanjing, Yangzhou, Zhenjiang, Changzhou, and Suzhou, tended to merge in the southern part of Jiangsu. (3) In terms of type, the roads, streets and alleys of TCHs are the richest, and all types of TCHs are spatially clustered in the southern part of Jiangsu Province, which has a high level of urbanization, industrialization, and a superior geographic environment. (4) TCHs have spatial tendencies toward low altitudes and hydrophilicity, and relatively favorable natural geographical conditions provide a high-quality environment for TCHs in southern Jiangsu Province. Influenced by historical, humanistic, and geographical factors, TCH is unevenly developed spatially. As a historical population concentration area, an important political, economic, and cultural core area, and a center of gravity for cultural development, more TCH resources have survived in the southern part of Jiangsu Province. This study provides a new perspective for interpreting and recognizing TCH as a special intangible cultural heritage and can provide a reference for the sustainable conservation and development of TCH.

Sequential Release of Ibuprofen and the Gasotransmitter Hydrogen sulfide using Oxanorbornane-Based Synthetic Lipids as Carriers.

After understanding the biological signaling roles of hydrogen sulfide and its involvement in various physiological processes, there has been enormous interest in exploring its therapeutic utility in areas such as cancer, inflammation, cardiovascular diseases, etc. There is also growing interest in using suitable H2S donors in combination with other drugs to improve the treatment outcome through the modulation of multiple pathways. The premature release of H2S from small molecule donors and the difficulty in controlling its spatio-temporal distribution are the major challenges during these efforts. Hence the development of appropriate carriers that can release this gasotransmitter along with the therapeutic entity of interest in a controlled manner has high significance. In this regard, this report presents a novel drug delivery system from oxanorbornane-based synthetic lipids that carries a H2S-releasing 1,2-dithiole-3-thione moiety as part of the head group. Nanoaggregates of the resulting conjugate are not only capable of efficiently entrapping a non-steroidal anti-inflammatory drug such as ibuprofen, but also release this drug and H2S in a controlled and sequential manner.

Investigating uncertainties in air quality models used in GMAP/SIJAQ 2021 field campaign: General performance of different models and ensemble results

The international field campaign, GMAP/SIJAQ 2021, was conducted in Korea from October 18th to November 25th to enhance the performance and validation of the Geostationary Environment Monitoring Spectrometer (GEMS) products algorithm and obtain a better understanding of the current air pollution status of the Korean Peninsula. Five chemical transport models (CTMs), including CMAQ, CMAQ-GIST, CAMx, WRF-Chem, and WRF GEOS-Chem, were utilized during the campaign to assist in organizing the observation plan and identifying changes in pollutant concentrations and their spatiotemporal distribution in Korea following the Korea–United States Air Quality (KORUS-AQ) 2016. In this study, we evaluated the forecasting performance, strengths, and limitations of these five CTMs and their ensemble in simulating air quality. Intensive measurement data and intercomparisons were employed to explain discrepancies between observed and simulated results. A comparison of the CTM ensemble results for PM2.5 and various gaseous pollutants between the current GMAP/SIJAQ 2021 and previous KORUS-AQ 2016 campaigns showed the R-value for the total mass PM2.5 concentration increased from 0.88 to 0.94. This improvement is related to CTM updates, including the emission inventory and better reproductions of the concentrations of gaseous species. However, the models consistently underestimated carbon monoxide (CO) concentrations, similar to the results from KORUS-AQ. This finding still suggests a further challenge that requires consideration of missing anthropogenic sources. The results of the ensemble model agreed well with the chemical composition of PM2.5 observed at the intensive monitoring station. However, for NO3− and NH4+, discrepancies were primarily due to inaccuracies in the meteorological inputs, such as precipitation, relative humidity (RH), and nighttime planetary boundary layer height (PBLH) in the CTMs. Hence, all models overestimated the concentration of elemental carbon (EC), therefore, it is necessary to revise EC emissions in the SIJAQv2 inventory, as these apply to unusual levels recorded in Seoul during the reference year of 2018.

Disentangled Dynamic Graph Attention Network for Out-of-distribution Sequential Recommendation

Sequential recommendation, leveraging user-item interaction histories to provide personalized and timely suggestions, has drawn significant research interest recently. With the power of exploiting spatio-temporal dynamics, dynamic graph neural networks (DyGNNs) show great potential in sequential recommendation by modeling the dynamic relationship between users and items. However, spatio-temporal distribution shifts naturally exist in out-of-distribution sequential recommendation, where both user-item relationships and temporal sequences demonstrate pattern shifts. The out-of-distribution scenarios may lead to the failure of existing DyGNNs in handling spatio-temporal distribution shifts in sequential recommendation, given that the patterns they exploit tend to be variant w.r.t labels under distribution shifts. In this paper, we propose D isentangled I ntervention-based D ynamic graph A ttention networks with I nvariance Promotion ( I-DIDA ) to handle spatio-temporal distribution shifts in sequential recommendation by discovering and utilizing invariant patterns, ie , structures and features whose predictive abilities are stable across distribution shifts. Specifically, we first propose a disentangled spatio-temporal attention network to capture the variant and invariant patterns. By utilizing the disentangled patterns, we design a spatio-temporal intervention mechanism to create multiple interventional distributions and an environment inference module to infer the latent spatio-temporal environments, and minimize the invariance loss to leverage the invariant patterns with stable predictive abilities under distribution shifts. Extensive experiments demonstrate the superiority of our method over state-of-the-art sequential recommendation baselines under distribution shifts.

Spatiotemporal distribution of mass movements: insights into regional changes in climate and geological environments

Spatiotemporal distribution of mass movements: insights into regional changes in climate and geological environments

Spatio-temporal distribution of intensity and frequency of extreme temperature events over Nigeria

Spatio-temporal distribution of intensity and frequency of extreme temperature events over Nigeria

Reproductive Biology of the Invasive Blue Crab Callinectes sapidus in the Thermaikos Gulf (Northwest Aegean Sea, Eastern Mediterranean): Identifying Key Information for an Effective Population Management Policy

The reproductive biology of the invasive blue crab Callinectes sapidus was studied in the Thermaikos Gulf (Northwest Aegean Sea, Eastern Mediterranean). In the two-year survey, 5698 (2897♂/2801♀) crabs were caught with the use of fyke nets. Total sex ratio (♂/♀) reached equality (1.03:1). The female blue crab exhibited a protracted reproductive period. Mature and ovigerous females exhibit short migratory movements from estuarine and inshore waters, where the population mostly congregates (0–3 m), and move to slightly deeper waters (1–3 m) up to 9 m for spawning. A total of 340 ovigerous females were caught. Their number varied both spatially and temporally; they were observed for a 7-month period (April to October) with a clear peak in July–August and at a 3 m depth gradient corresponding to ≈60% of the total number of ovigerous females caught in both years. Size at first sexual maturity (CW50) was estimated at 113.1 mm CW. Average fecundity was ≈790,000 eggs. Experimental trawling showed that inshore waters (&lt;1 m) in the estuaries serve as nursery areas for juveniles. Defining the spatiotemporal and bathymetrical distribution of ovigerous females in any invaded coastal habitat could be considered key information for the implementation of a management policy for the species.

Organoids research progress in gynecological cancers: a bibliometric analysis.

Gynecological cancers (GC) pose a severe threat to the health and safety of women's lives, and organoids, as in-vitro research models, have demonstrated significant advantages in simulating tissue characteristics and drug screening. In recent years, there has been a rapid increase in research outcomes related to organoids in GC. However, there has been no bibliometric study concerning. Publications related to GC and organoids from 2010-2023 were retrieved from the Web of Science Core Collection (WoSCC). We conducted a bibliometric analysis and visualization using CiteSpace, VOSviewer, and the Bibliometrix R Package. This analysis included the spatiotemporal distribution, author, sources, references, and keywords. A total of 333 publications were included. The number of annual publications indicated an explosive phase of development since 2019. The USA was the most important country in terms of cooperation, publication output, citation and centrality. University of California system ranked first in productivity among institutions, and HIPPO Y is the most relevant author in the research field. CANCERS published the most documents, and NATURE is the most cited sources. Analysis of Keywords and References, it is possible to establish the trend, and find the hotspots in the research field. This bibliometric analysis delineated global landscapes and progress trends in GC organoids research. This study emphasized that organoids can effectively replicate the original tissue or tumors, providing a good in-vitro model for research on tumor-related mechanisms and showing significant advantages in drug screening and efficacy clinical prediction. Additionally, as preclinical models, they provide compelling evidence for personalized therapy and prediction of patient drug responses.

Spatiotemporal distribution of sedimentary chloropigments and organic carbon in a shelf sea ecosystem, with a focus on the cold water mass

The Yellow Sea is one of the most thoroughly studied shelf seas in the northwestern Pacific. However, many aspects of the northern Yellow Sea sediments remain poorly understood. Sedimentary chloropigments and total organic carbon (TOC) are crucial components that indicate benthic primary productivity and ecosystem functioning in the marginal sea system. The present study investigated the temporal and spatial variations of sediment chloroplastic pigments (Chl-a and Pha-a) and TOC contents in relation to seasons and the northern Yellow Sea Cold Water Mass (NYSCWM). Decadal trends were also examined using linear regression on time-series data from 12 cruises conducted over a nine-year period (2006–2014). The correlations between sedimentary Chorophy-a (Chl-a), Pheophorbide-a (Pha-a), TOC, and their ratios with other abiotic and biotic factors were analyzed to detect any effects of the NYSCWM on the spatiotemporal distribution of sediment Chl-a, Pha-a, TOC contents, as well as the ecological relevance of their ratios as indicators of food quality (freshness) in the benthic system. The NYSCWM substantially influences the spatial and seasonal distribution of sedimentary Chl-a, Pha-a, and TOC contents. High values of Pha-a, TOC, and the ratios of Pha-a/(Chl-a + Pha-a) and TOC/Chl-a were often observed in the central region of the NYSCWM, where Chl-a showed clear seasonal fluctuations while Pha-a and TOC remained relatively constant. While sedimentary TOC appears to negatively mirror the spatial pattern of primary productivity in the water column, the spatial pattern of sedimentary Chl-a in relation to NYSCWM is less evident. However, the contents of Pha-a and TOC in the central NYSCWM sediments were higher than those at surrounding NYSCWM stations. Surface sediment Pha-a/(Chl-a + Pha-a) ratio was negatively correlated with meiofauna abundance and biomass and positively correlated with nematode/copepod ratio. This finding indicates that the quality of sediment organic matter is important to meiofauna. Conversely, the lower organic degradation rate at the lower bottom temperature of the NYSCWM may explain the observed higher Pha-a and TOC contents in its central area. Time-series data collected over nine years at the NYSCWM stations showed a decreasing trend for Chl-a, while TOC and the ratio of Pha-a/(Chl-a + Pha-a) exhibited increasing tendencies. This trend may imply a reduced quality of food supply to the benthic food web in the shelf sea system, along with degraded ecosystem functioning and service under the impacts of global change and anthropogenic disturbances.

Imaging PD-L1 in the brain-Journey from the lab to the clinic.

Immune checkpoint inhibitors (ICPIs) have proven to restore adaptive anti-tumor immunity in many cancers; however, no noteworthy therapeutic schedule has been established for patients with glioblastoma (GBM). High programmed death-ligand 1 (PD-L1) expression is associated with immunosuppressive and aggressive phenotypes in GBM. Presently, there is no standardized protocol for assessing PD-L1 expression levels to select patients and monitor their response to ICPI therapy. The aim of this study was to investigate the use of 89Zr-DFO-Atezolizumab to image the spatio-temporal distribution of PD-L1 in preclinical mouse models and in patients with newly diagnosed GBM treated with/without neoadjuvant Pembrolizumab. The immunoreactivity, binding affinity, and specificity of 89Zr-DFO-Atezolizumab were confirmed in vitro. Mice-bearing orthotopic GBM tumors or patients with newly diagnosed GBM treated with/without Pembrolizumab were intravenously injected with 89Zr-DFO-Atezolizumab, and PET/CT images were acquired 24, 48, and 72 hours in mice and at 48 and 72 post-injection in patients. Radioconjugate uptake was quantified in the tumor and healthy tissues. Ex vivo immunohistochemistry (IHC) and immunophenotyping were performed on mouse tumor samples or resected human tumors. 89Zr-DFO-Atezolizumab was prepared with high radiochemical purity (RCP > 99%). In vitro cell-associated radioactivity of 89Zr-DFO-Atezolizumab corroborated cell line PD-L1 expression. PD-L1 in mouse GBM tumors was detected with high specificity using 89Zr-DFO-Atezolizumab and radioconjugate uptake correlated with IHC. Patients experienced no 89Zr-DFO-Atezolizumab-related side effects. High 89Zr-DFO-Atezolizumab uptake was observed in patient tumors at 48 hours post-injection, however, the uptake varied between patients treated with/without Pembrolizumab. 89Zr-DFO-Atezolizumab can visualize distinct PD-L1 expression levels with high specificity in preclinical mouse models and in patients with GBM, whilst complementing ex vivo analysis.

Spatiotemporal Distribution of Mercury in Tree Rings and Soils Within Forests Surrounding Coal-Fired Power Plants

The release of mercury (Hg) from coal-fired power plants (CPPs) into local ecosystems poses substantial environmental and health hazards. This study was conducted in Chungcheong-nam-do, South Korea, a region featuring over half of the country’s coal power facilities, to estimate the impacts of CPPs on Hg distribution in forest ecosystems. By analyzing Hg concentrations in pine tree rings and soil at 21 locations around CPPs and comparing them to control sites and industrial zones, we present a nuanced understanding of the effects of CPPs on Hg concentration. The analysis of Hg concentrations in tree rings showed a significant decrease in Hg levels as the distance from the power plants increased, suggesting that CPPs primarily influence Hg distribution in trees within a 25 km radius. In contrast, soil Hg concentrations did not exhibit a clear trend. This may reflect the limitations of this study in accounting for the physicochemical properties of the soil at each sampling site. Nevertheless, the Potential Ecological Risk Index for soil Hg contamination indicated a higher risk rating within a 1 km radius of the CPPs compared to other locations. Hg concentrations in tree rings have shown a steady decline since the 1970s, suggesting the positive effects of air pollution regulations. This also highlights the value of tree core samples as effective tools for monitoring historical Hg pollution. Furthermore, the higher historical concentrations of Hg in tree rings imply that trees may have acted as sinks for atmospheric Hg in the past.

MNCATM: A Multi-Layer Non-Uniform Coding-Based Adaptive Transmission Method for 360° Video

With the rapid development of multimedia services and smart devices, 360-degree video has enhanced the user viewing experience, ushering in a new era of immersive human–computer interaction. These technologies are increasingly integrating everyday life, including gaming, education, and healthcare. However, the uneven spatiotemporal distribution of wireless resources presents significant challenges for the transmission of ultra-high-definition 360-degree video streaming. To address this issue, this paper proposes a multi-layer non-uniform coding-based adaptive transmission method for 360° video (MNCATM). This method optimizes video caching and transmission by dividing non-uniform tiles and leveraging users’ dynamic field of view (FoV) information and the multi-bitrate characteristics of video content. First, the video transmission process is formalized and modeled, and an adaptive transmission optimization framework for a non-uniform video is proposed. Based on this, the optimization problem required by the paper is summarized, and an algorithm is proposed to solve the problem. Simulation experiments demonstrate that the proposed method, MNCATM, outperforms existing transmission schemes in terms of bandwidth utilization and user quality of experience (QoE). MNCATM can effectively utilize network bandwidth, reduce latency, improve transmission efficiency, and maximize user experience quality.