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The psychosocial outcomes of adolescents and young adults (AYAs) diagnosed with cancer are poorer compared to their peers without cancer. However, AYAs with cancer from diverse racial and ethnic groups have been under-represented in research, which contributes to an incomplete understanding of the psychosocial outcomes of all AYAs with cancer. This paper evaluated the racial and ethnic representation in research on AYAs diagnosed with cancer using observational, cross-sectional data from the large Young Adults with Cancer in Their Prime (YACPRIME) study. The purpose was to better understand the psychosocial outcomes for those from diverse racial and ethnic groups. A total of 622 participants with a mean age of 34.15 years completed an online survey, including measures of post-traumatic growth, quality of life, psychological distress, and social support. Of this sample, 2% (n = 13) of the participants self-identified as Indigenous, 3% (n = 21) as Asian, 3% (n = 20) as “other,” 4% (n = 25) as multi-racial, and 87% (n = 543) as White. A one-way ANOVA indicated a statistically significant difference between racial and ethnic groups in relation to spiritual change, a subscale of post-traumatic growth, F(4,548) = 6.02, p < 0.001. Post hoc analyses showed that those under the “other” category endorsed greater levels of spiritual change than those who identified as multi-racial (p < 0.001, 95% CI = [2.49,7.09]) and those who identified as White (p < 0.001, 95% CI = [1.60,5.04]). Similarly, participants that identified as Indigenous endorsed greater levels of spiritual change than those that identified as White (p = 0.03, 95% CI = [1.16,4.08]) and those that identified as multi-racial (p = 0.005, 95% CI = [1.10,6.07]). We provided an extensive discussion on the challenges and limitations of interpreting these findings, given the unequal and small sample sizes across groups. We concluded by outlining key recommendations for researchers to move towards greater equity, inclusivity, and culturally responsiveness in future work.

The Hawkesbury-Nepean valley is one of the largest coastal basins in NSW. It supports the local agriculture industry and is an important environmental asset. Due to its narrow sandstone gorges, which create natural choke points, floodwaters from its major tributaries can rapidly back up, rise and spill out onto the flood plain. Thus, the valley is flood-prone, with a history of disastrous events, aggravated by a constrained road network for evacuation. Two flood events occurred in the Hawkesbury-Nepean valley in 2020 and 2021, however, the impact of each of those events was different in terms of lives lost (2 fatalities compared to none) and economic losses (more than AUD 2 billion compared to less than AUD 1 billion). In this study, reasons for the variation in impacts are explored by determining an inundation likelihood map, derived using a combination of the height above nearest drainage method and streamflow forecasts, and considering antecedent hydrological and climate conditions.

As an important control element in steam heating piping systems, the safety and stability of inverted bucket steam valves determine the reliable operation of the system. Therefore, it is necessary to investigate the acoustic mechanism of inverted bucket steam valves. Aiming at the difficulty of numerical simulation in accurately predicting the aerodynamic noise of inverted bucket steam valves, this paper proposes a new method for simulating the aerodynamic noise of inverted bucket steam valves based on multiband analysis (LES). The flow field of the inverted bucket steam valve is numerically simulated using the LES method to obtain wall pressure pulsation information and fluid velocity pulsation information, which are used as excitation sources for acoustic simulation. The characteristics of dipole and quadrupole sound sources were obtained by applying the FW-H method and experimentally verified. The results show that a new multifrequency band analysis method for inverted bucket steam valves is effective by comparing the numerical simulation results, in which the dipole source dominates in the low-frequency band, in the medium frequency range, the quadrupole source outperforms the dipole source, but in the high frequency range, the quadrupole source is dominant. The experimental results are in good agreement with the simulation results, and the correctness of the numerical simulation is confirmed by the fact that there is less than a 3% difference between the findings of the numerical simulation and the experimental data.

Understanding Holocene temperature changes is vital for resolving discrepancies between proxy reconstructions and climate models. The intricate temperature variations across the Tibetan Plateau (TP) add complexity to studying continental climate change during this period. Discrepancies between model-based and proxy-based reconstructions might stem from seasonal biases and environmental uncertainties in the proxies. Employing multiple proxies from a single sediment core for quantitative temperature reconstructions offers an effective method for cross-validation in terrestrial environments. Here, we present an ice-free-season temperature record for the past 15 kyr from a shallow, freshwater lake on the eastern TP, based on brGDGTs (branched glycerol dialkyl glycerol tetraethers). This record shows that the Holocene Thermal Maximum lags the pollen-based July temperature recorded in the same sediment core. We conclude that the mismatch between the brGDGT-based and pollen-based temperatures is primarily the result of seasonal variations in solar irradiance. The overall pattern of temperature changes is supported by other summer temperature records, and the Younger Dryas cold event and the Bølling–Allerød warm period are also detected. A generally warm period occurred during 8–3.5 ka, followed by a cooling trend in the late Holocene. Our findings have implications for understanding the seasonal signal of brGDGTs in shallow lakes and provide critical data for confirming the occurrence of seasonal biases in different proxies from high-elevation lakes. To further investigate the significance of the brGDGTs and temperature patterns on the TP, we examined existing brGDGT-based Holocene temperature records, which interpret these compounds as indicators of mean annual or growing season temperatures. The existing and available temperature records show complicated patterns of variation, some with general warming trends throughout the Holocene, some with cooling trends, and some with a warm middle Holocene. We analyzed the possible reasons for the diverse brGDGTs records on the TP and emphasize the importance of considering lake conditions and modern investigations of brGDGTs in lacustrine systems when using brGDGTs to reconstruct paleoenvironmental conditions.

A greater understanding of how young people cope with a cancer diagnosis is needed in order to inform age-appropriate supportive care. This paper describes the coping strategies used and explores relationships between coping strategies and personal, medical, and psychological variables among young adults (YAs) diagnosed with cancer. YAs (n = 547, mean age = 34.05 ± 6.00 years) completed an online survey, including the Brief COPE and measures of psychological functioning. Descriptive statistics and bivariate correlations were computed. Acceptance, self-distraction, positive reframing, and planning were the most used coping strategies by this sample. There were small (r = −0.09) to large (r = 0.51) significant relationships between personal, medical, and psychological variables and selected coping strategies. Coping with a cancer diagnosis early in life remains poorly understood. Identifying additional correlates and exploring inter- and intrapersonal variation in coping strategy use is required.

Measuring the spatiotemporal dynamics of lake and reservoir water storage is fundamental for assessing the influence of climate variability and anthropogenic activities on water quantity and quality. Previous studies estimated relative water volume changes for lakes where both satellite-derived extent and radar altimetry data are available. This approach is limited to only a few hundred lakes worldwide and cannot estimate absolute (i.e. total volume) water storage. We increased the number of measured lakes by a factor of 300 by using high-resolution Landsat and Sentinel-2 optical remote sensing and ICESat-2 laser altimetry, in addition to radar altimetry from the Topex/Poseidon; Jason-1, Jason-2 and Jason-3; and Sentinel-3 and Sentinel-6 instruments. Historical time series (1984–2020) of water storage could be derived for more than 170 000 lakes globally with a surface area of at least 1 km2, representing 99 % of the total volume of all water stored in lakes and reservoirs globally. Specifically, absolute lake volumes are estimated based on topographic characteristics and lake properties that can be observed by remote sensing. In addition to that, we also generated relative lake volume changes solely based on satellite-derived heights and extents if both were available. Within this dataset, we investigated how many lakes can be measured in near real time (2020–current) in basins worldwide. We developed an automated workflow for near-real-time global lake monitoring of more than 27 000 lakes. The GloLakes historical and near-real-time lake storage dynamics data from 1984 to current are publicly available through https://doi.org/10.25914/K8ZF-6G46 (Hou et al., 2022c) and a web-based data explorer (http://www.globalwater.online, last access: 12 December 2023).

The aim of this study is to propose evaluation methodology for the quality assessment of depth cameras for indoor mapping applications. Specifically, we evaluate the RGBD sensor Intel Realsense D455 w.r.t. measurement accuracy and noise while investigating their dependence on two central parameters characterizing the measurement scenario simultaneously: measurement distance and inclination of observed surfaces. The evaluation results are presented two-dimensionally as a function of both parameters. To this aim, two evaluation studies are conducted. First, a checkerboard pattern is used as reference object in a controlled setting. Secondly, actual indoor mapping data resulting from the deployment of the evaluated sensor in the context of an RGBD-SLAM application is used to conduct a similar evaluation in representative conditions for the intended usage scenario of indoor mapping. In this case, a TLS scan of the respective indoor environment is used as reference for evaluation.

Abstract This study comprehensively investigates the oxidation kinetics of laser powder bed fusion (LPBF) processed GH3536 superalloy at 950 °C. The oxidation kinetics and oxide film microstructure characteristics are analyzed and the underlying mechanism is discussed, by comparing with the conventionally manufactured wrought GH3536 samples under the exactly same test condition. The oxidation rate of LPBF samples is faster at initial stage and then tends to flatten out with increase of heating duration time. The finer and equiaxed chromia crystals formed in LPBF GH3536 surface can effectively improve the oxidation resistance comparing to the columnar structure chromia in wrought GH3536. The oxide film with excellent protection in LPBF GH3536 provides an important contribution to the application of GH3536 at high temperature.

In this study, the diagnostic abilities of intensity parameters of optical coherence tomography angiography (OCTA) images in the early detection of diabetic retinopathy (DR) were determined. 78 normal healthy eyes, 10 diabetic eyes with mild non-proliferative diabetic retinopathy (NPDR), and 10 diabetic eyes with moderate NPDR were employed. Four retinal vascular plexuses were generated by using OCTA, which included the nerve fiber layer vascular plexus (NFLVP), superficial vascular plexus (SVP), intermediate capillary plexus (ICP) and deep capillary plexus (DCP). The parafoveal zone in each OCTA image was divided into four sectors which were the superior, temporal, inferior, and nasal sectors. Five intensity parameters including the mean, median, variance, skewness, and kurtosis of intensities were calculated for each sector. The factor of aging was evaluated among normal healthy subgroups. The diagnostic abilities of intensity parameters were evaluated between normal healthy subjects and diabetic patients with DR. Our results showed that the variance of intensities in superior sector in ICP achieved the highest AUROC value of 0.95 with the sensitivity of 0.87 and the specificity of 1.000 when comparing the diabetic patients with the mild NPDR to normal healthy subjects. The mean intensity in superior sector in ICP achieved the second highest AUROC value of 0.95 with the sensitivity of 0.90 and the specificity of 0.90 when comparing the diabetic patients with the moderate NPDR to normal healthy subjects. The proposed approach could offer a simple way to differentiate diabetic patients with early DR from normal healthy subjects without performing the relatively complicated image processing techniques.

Accurate snowpack simulations are critical for regional hydrological predictions, snow avalanche prevention, water resource management, and agricultural production, particularly during the snow ablation period. Data assimilation methodologies are increasingly being applied for operational purposes to reduce the uncertainty in snowpack simulations and to enhance their predictive capabilities. This study aims to investigate the feasibility of using a genetic particle filter (GPF) as a snow data assimilation scheme designed to assimilate ground-based snow depth (SD) measurements across different snow climates. We employed the default parameterization scheme combination within the Noah-MP (with multi-parameterization) model as the model operator in the snow data assimilation system to evolve snow variables and evaluated the assimilation performance of the GPF using observational data from sites with different snow climates. We also explored the impact of measurement frequency and particle number on the filter updating of the snowpack state at different sites and the results of generic resampling methods compared to the genetic algorithm used in the resampling process. Our results demonstrate that a GPF can be used as a snow data assimilation scheme to assimilate ground-based measurements and obtain satisfactory assimilation performance across different snow climates. We found that particle number is not crucial for the filter's performance, and 100 particles are sufficient to represent the high dimensionality of the point-scale system. The frequency of measurements can significantly affect the filter-updating performance, and dense ground-based snow observational data always dominate the accuracy of assimilation results. Compared to generic resampling methods, the genetic algorithm used to resample particles can significantly enhance the diversity of particles and prevent particle degeneration and impoverishment. Finally, we concluded that the GPF is a suitable candidate approach for snow data assimilation and is appropriate for different snow climates.

3D indoor mapping is becoming increasingly critical for a variety of applications such as path planning and navigation for robots. In recent years, there is a growing interest in how low-cost sensors, such as monocular or depth cameras, can be used for 3D mapping. In our paper, we present an octree-based approach for real-time 3D indoor mapping using a handheld RGB depth camera. One benefit of the generated octree map is that it requires less storage and computational resources than point cloud models. Moreover, it explicitly represents free space and unmapped areas, which are essential for the robot's navigation tasks. In this work, on the basis of the ORB-SLAM3 system (Campos et al., 2021), we developed an octree mapping system, which directly calls the keyframes and estimated poses provided by ORB-SLAM3 algorithms. Furthermore, we used point cloud library (PCL) for the dense point cloud mapping and then OctoMap for the point cloud to octree map conversion. Finally, we implemented an efficient probabilistic 3D mapping in the robot operating system (ROS) environment. We used the TUM RGB-D dataset to evaluate the estimated trajectories of the camera. The evaluation shows an average translational RMSE of 5.9 cm on the TUM RGB-D dataset. Besides, we also compared the ground truth point clouds and our generated point clouds. The result shows the mean cloud-to-cloud distance in the corridor scene is about 6 cm. All the evaluation results show our proposed approach is a promising solution for advanced indoor voxel mapping and robotic navigation systems.

In order to reduce the temperature in the marine engine cabin, improve the working environment of the staff and meet the economy and emission requirements, the cooling system of the engine was experimentally investigated in the present study. In this regard, water cooling and air-cooling schemes were studied and the main indicators including engine torque, smoke-emission, and exhaust temperature were analyzed. The obtained results indicate that the highest torque can be obtained from the air-cooling turbine case and air-cooling exhaust pipe. As the applied torque decreases, the outlet smoke first decreases then increases and decreases finally. Moreover, it is found that the water-cooling turbine case and water-cooling exhaust pipe increase the smoke. When the turbocharger is equipped with a water-cooling turbine case and water-cooling exhaust pipe, the higher the engine torque, the higher the turbine exhaust temperature and oil tank temperature, and the greater the reduction of the exhaust temperature. The engine torque is in direct proportion to the fuel consumption. The greater the torque, the higher the engine speed and the greater the fuel consumption. The engine torque is inversely proportional to the fuel consumption rate. The greater the torque, the smaller the fuel consumption rate. In cases with water cooling exhaust devices at 110% loading speed, the temperature after the intercooler is higher than that with the air-cooling exhaust device. After the intercooler, the pressure increases as the applied torque increases, and a higher-pressure ratio can be obtained from the air-cooling exhaust device. The higher the engine torque, the higher the temperature of the turbine exhaust, the higher the outlet temperature of the circulating cooling water, and the higher the temperature in the cabin. It was concluded that the exhaust device of the air-cooling turbine case and water-cooling exhaust pipe can reduce the temperature in the engine parts by up to 2℃, thereby improving the working environment of the cabin staff, economic performance, and the emission index.

(1) Background: The COVID-19 global pandemic has impacted people worldwide with unique implications for vulnerable groups. In this cross-sectional study, we examined the impact of the early pandemic on children undergoing active cancer treatment and their parents. (2) Methods: In May 2020, 30 parents of children undergoing active cancer treatment completed an online survey regarding the impact of COVID-19 on their child’s cancer care, perceived utility of telemedicine, and child and parent mental health status. (3) Results: Most participants (87%) reported that they did not experience any changes to major cancer treatments. Among those who reported using telemedicine, 78% reported this to be beneficial. Over half of the participants reported that their child’s mental health status was worse now than prior to the COVID-19 global pandemic. Parent-reported child anxiety scores were significantly higher for those who reported changes to mental health care for their child compared to those who did not report the same, t(25.99) = −3.04, p = 0.005. (4) Conclusion: Child and parent mental health status were affected when compared to pre-pandemic. Telemedicine appears to be a promising complement to face-to-face meetings for some families and warrants further exploration.

We synthesized polycrystalline La_{3}Ni_{2}O_{7−δ} (δ≈0.07) samples by using the sol-gel method without postannealing under high oxygen pressure, and then measured temperature-dependent resistivity under various hydrostatic pressures up to 18 GPa by using the cubic anvil and two-stage multianvil apparatus. We find that the density-wave-like anomaly in resistivity is progressively suppressed with increasing pressure and the resistivity drop corresponding to the onset of superconductivity emerges at pressure as low as ∼6 GPa. Zero resistivity is achieved at 9 GPa below T_{c}^{zero}≈6.6 K, which increases quickly with pressure to 41 K at 18 GPa. However, the diamagnetic response was not detected in the ac magnetic susceptibility measurements up to 15 GPa, indicating a filamentary nature of the observed superconductivity in the studied pressure range. The constructed T-P phase diagram reveals an intimate relationship between superconductivity, density-wave-like order, and the strange-metal-like behaviors. The observation of zero-resistance state in the polycrystalline La_{3}Ni_{2}O_{7−δ} samples under high pressures not only corroborates the recent report of superconductivity in the pressurized La_{3}Ni_{2}O_{7} crystals but also facilitates further studies on this emerging family of nickelate high-T_{c} superconductors.

COVID-19 can be treated with monoclonal antibodies against SARS-CoV-2, but emerging new variants might show resistance towards existing therapy. Here authors show that anti-SARS-CoV-2 spike human single-chain antibody fragments could gain neutralizing activity against variants of concern upon engineering into a human bispecific antibody.

Carbon combustion rates can be altered with different particle sizes of solid fuel, which can directly affect the mineralization of iron ore sintering. A quantitative relationship between coke size and iron ore sintering indexes was studied using a mixture regression design method and simplex-lattice design. Also, the effects of optimal coke particle size on the cold intensity and productivity of the sinter were verified by sinter pot tests and analytical studying the sintering mineral structure. Results show that changing and optimizing the proportion of different coke sizes (5 mm) can satisfy the need for sintering production to indexes. It has important significance to reduce solid fuel consumption and improve the yield and quality of sinter.

Many thousands of large dam reservoirs have been constructed worldwide during the last 70 years to increase reliable water supplies and support economic growth. Because reservoir storage measurements are generally not publicly available, so far there has been no global assessment of long-term dynamic changes in reservoir water volumes. We overcame this by using optical (Landsat) and altimetry remote sensing to reconstruct monthly water storage for 6695 reservoirs worldwide between 1984 and 2015. We relate reservoir storage to resilience and vulnerability and investigate interactions between precipitation, streamflow, evaporation, and reservoir water storage. This is based on a comprehensive analysis of streamflow from a multi-model ensemble and as observed at ca. 8000 gauging stations, precipitation from a combination of station, satellite and forecast data, and open water evaporation estimates. We find reservoir storage has diminished substantially for 23 % of reservoirs over the three decades, but increased for 21 %. The greatest declines were for dry basins in southeastern Australia (−29 %), southwestern USA (−10 %), and eastern Brazil (−9 %). The greatest gains occurred in the Nile Basin (+67 %), Mediterranean basins (+31 %) and southern Africa (+22 %). Many of the observed reservoir changes could be explained by changes in precipitation and river inflows, emphasizing the importance of multi-decadal precipitation changes for reservoir water storage. Uncertainty in the analysis can come from, among others, the relatively low Landsat imaging frequency for parts of the Earth and the simple geo-statistical bathymetry model used. Our results also show that there is generally little impact from changes in net evaporation on storage trends. Based on the reservoir water balance, we deduce it is unlikely that water release trends dominate global trends in reservoir storage dynamics. This inference is further supported by different spatial patterns in water withdrawal and storage trends globally. A more definitive conclusion about the impact of changes in water releases at the global or local scale would require data that unfortunately are not publicly available for the vast majority of reservoirs globally.

Objective Native plants can be used as additives to replace antibiotics to improve ruminant feed utilization and animal health. An experiment was conducted to evaluate the effects of Gentiana straminea (GS) on nutrient digestibility, methane emissions, and energy metabolism of Simmental calves. Methods Thirty-two (5-week-old) male Simmental clves, with initial body weight (BW) of 155±12 kg were fed the same basal diet of concentrates (26%), alfalfa hay (37%), and oat hay (37%) and were randomly separated into four treatment groups according to the amount of GS that was added to their basal diet. The four different groups received different amounts of GS as a supplement to their basal diet during whole experiment: (0 GS) 0 mg/kg BW, the control; (100 GS) 100 mg/kg BW; (200 GS) 200 mg/kg BW; and (300 GS) 300 mg/kg BW. Results For calves in the 200 GS and 300 GS treatment groups, there was a significant increase in dry matter (DM) intake (p

The use of multi-branch architectures in off-the-shelf light-weight residual series neural networks can significantly improve their performance in remote sensing scene classification tasks. However, such architectures come at the expense of an increased number of parameters and calculations. In this paper, we propose the Decoupling Multi-branch Pointwise Convolutions (DMPConv), which works without a corresponding increase in parameters and calculations during inferencing, and at the same time, can maintain the same performance improvement ability as the multi-branch architectures. DMPConv can be decoupled into two states, the training-time DMPConv and the inferencing-time DMPConv. The training-time DMPConv enhances the expressivity of the network by using weighted multi-branch 1×1 convolutions. After training, we use structural reconstruction to convert the training-time DMPConv to the inferencing-time DMPConv, which has the same form as vanilla 1×1 convolution, so as to realize the inferencing-free. Extensive experiments were conducted on multiple remote sensing scene classification benchmarks, including Aerial Image data set and NWPU-RESISC45 data set to demonstrate the superiority of DMPConv.

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg ^2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg ^2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg ^2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

Water clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984–2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red / blue band ratio algorithm was applied to map SDD for lakes (>0.01 km2) based on the first SDD dataset, where R2=0.79 and relative RMSE (rRMSE) =61.9 %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984–2018, lakes in the Tibetan–Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32±0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60±0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia–Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01–1 km2, whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.271571, Tao et al., 2021).

The fate of hematopoietic stem cells can be controlled by factors such as calcium ion concentration. Here the authors report an intravital ratiometric analysis method to measure extracellular calcium ion concentrations and absolute pH in mouse bone marrow.

Summary: Background: The COVID-19 pandemic continues to cause morbidity and mortality worldwide. Most approved COVID-19 vaccines generate a neutralizing antibody response that primarily targets the highly variable receptor-binding domain (RBD) of the SARS-CoV-2 spike (S) protein. SARS-CoV-2 “variants of concern” have acquired mutations in this domain allowing them to evade vaccine-induced humoral immunity. Recent approaches to improve the breadth of protection beyond SARS-CoV-2 have required the use of mixtures of RBD antigens from different sarbecoviruses. It may therefore be beneficial to develop a vaccine in which the protective immune response targets a more conserved region of the S protein. Methods: Here we have developed a vaccine based on the conserved S2 subunit of the S protein and optimized the adjuvant and immunization regimen in Syrian hamsters and BALB/c mice. We have characterized the efficacy of the vaccine against SARS-CoV-2 variants and other coronaviruses. Findings: Immunization with S2-based constructs elicited a broadly cross-reactive IgG antibody response that recognized the spike proteins of not only SARS-CoV-2 variants, but also SARS-CoV-1, and the four endemic human coronaviruses. Importantly, immunization reduced virus titers in respiratory tissues in vaccinated animals challenged with SARS-CoV-2 variants B.1.351 (beta), B.1.617.2 (delta), and BA.1 (omicron) as well as a pangolin coronavirus. Interpretation: These results suggest that S2-based constructs can elicit a broadly cross-reactive antibody response resulting in limited virus replication, thus providing a framework for designing vaccines that elicit broad protection against coronaviruses. Funding: NIH, Japan Agency for Medical Research and Development, Garry Betty/ V Foundation Chair Fund, and NSF.

Introduction Paediatric cancer affects children and families from diverse backgrounds. However, there is a limited understanding of how diversity/cultural factors play a role, especially in survivorship. This protocol outlines a systematic review on the cultural influences in survivors of childhood cancer.Methods and analysis This protocol is reported based on the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) guidelines checklist and is registered with PROSPERO. EMBASE, MEDLINE and PsycINFO are searched. Eligibility criteria include original research studies published in English, and an assessment of culture on survivors of childhood cancer. Search terms are developed with a medical librarian. Primary objective will be to describe culture (ethnic and population groups, migration status, acculturation, cultural characteristics) in survivors of paediatric cancer and study characteristics and methods. Secondary objective will be to identify the role of culture in outcomes of survivors of paediatric cancer. Data extraction will include participant characteristics such as the number of participants and/or controls, sex, age at diagnosis. Extraction will also include analytical approaches, type of cultural variables (predictor, moderator, mediator, outcome) and effect measures.Ethics and dissemination Ethical approval was not required for this systematic review. Results from this systematic review will be disseminated in line with PRISMA guidelines through peer-reviewed publications and conference presentations. Findings will also be shared with our target communities, including survivors of childhood cancer and their families, through the creation of lay summaries and/or educational workshops in the community. Knowledge gathered from this review may help to identify gaps in knowledge and directions for future research. They may also inform the development of clinical recommendations for healthcare providers of survivors of childhood cancer.PROSPERO registration number CRD42021234101.

ABSTRACT COVID-19 convalescent plasma (CCP) was an early and widely adopted putative therapy for severe COVID-19. Results from randomized control trials and observational studies have failed to demonstrate a clear therapeutic role for CCP for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Underlying these inconclusive findings is a broad heterogeneity in the concentrations of neutralizing antibodies (nAbs) between different CCP donors. We conducted this study to evaluate the effectiveness and safety of nAb titer-defined CCP in adults admitted to an academic referral hospital. Patients positive by a SARS-CoV-2 nucleic acid amplification test and with symptoms for 1:640 (high-titer group) or ≥1:160 to 1:640 (standard-titer group) in addition to standard of care treatments. The primary clinical outcome was time to hospital discharge, with mortality and respiratory support evaluated as secondary outcomes. Adverse events were contrasted by CCP titer. Between 28 August and 4 December 2020, 316 participants were screened, and 55 received CCP, with 14 and 41 receiving high- versus standard-titer CCP, respectively. Time to hospital discharge was shorter among participants receiving high- versus standard-titer CCP, accounting for death as a competing event (hazard ratio, 1.94; 95% confidence interval [CI], 1.05 to 3.58; Gray’s P = 0.02). Severe adverse events (SAEs) (≥grade 3) occurred in 4 (29%) and 23 (56%) of participants receiving the high versus standard titer, respectively, by day 28 (risk ratio, 0.51; 95% CI, 0.21 to 1.22; Fisher’s P = 0.12). There were no observed treatment-related AEs. (This study has been registered at ClinicalTrials.gov under registration no. NCT04524507). IMPORTANCE In this study, in a high-risk population of patients admitted for COVID-19, we found an earlier time to hospital discharge among participants receiving CCP with nAb titers of >1:640 compared with participants receiving CCP with a lower nAb titer and no CCP-related AEs. The significance of our research is in identifying a dose response of CCP and clinical outcomes based on nAb titer. Although limited by a small study size, these findings support further study of high-nAb-titer CCP defined as >1:640 in the treatment of COVID-19.

Abstract Background Coronavirus (CoV) nonstructural protein 14 (nsp14) has exoribonuclease (ExoN) activity, responsible for proofreading and contributing to replication fidelity. It has been reported that CoVs exhibit variable sensitivity to nsp14-ExoN deficiency. Betacoronavirus murine hepatitis virus (MHV) and severe acute respiratory syndrome (SARS)-CoV were viable upon nsp14-ExoN deficiency. While betacoronavirus Middle East respiratory syndrome (MERS)-CoV and SARS-CoV-2 were non-viable with disabled nsp14-ExoN. In this study, we investigated the nsp14-ExoN deficiency of alphacoronavirus porcine epidemic diarrhea virus (PEDV) in viral pathogenesis using reverse genetics. Results Eight nsp14-ExoN deficient mutants, targeting the predicted active sites and the Zinc finger or mental-coordinating sites, of PEDV were designed. Only one mutant E191A with a mutation in the Mg2+-binding site was rescued using the infectious clone of PEDV PC22A strain (icPC22A). The passage no.1–3 (P1-3) of E191A grew to very low titers in Vero cells. To evaluate the pathogenesis of the E191A, 4 or 5-day-old gnotobiotic pigs were inoculated orally with 100 TCID50/pig of the E191A-P1, icPC22A, or mock. All mock pigs did not shed virus in feces or show clinical signs. All pigs inoculated with icPC22A shed high viral RNA levels, had severe diarrhea, and died by 6 days post-inoculation (dpi). In contrast, only 3 pigs (3/4, 75%) in the E191A-P1 group shed low levels of viral RNA and 2 pigs had moderate diarrhea at acute infection phase. At 22 dpi, each pig was challenged orally with 106 plaque forming unit of virulent icPC22A. All pigs in the mock group developed severe diarrhea and 2 of the 5 pigs died. Pigs in the E191A-P1 group had less severe diarrhea and no pigs died. Sanger sequencing analysis revealed that the viral genome in the fecal sample of one E191A-P1-inoculated pig and the P4 virus passaged in vitro lost the E191A mutation, suggesting the genetic instability of the E191A mutant. Conclusion The recombinant PEDV variants carrying mutations at the essential functional sites within nsp14-ExoN were either lethal or genetically unstable. Our finding further confirmed the critical role of nsp14-ExoN in CoV life cycle, suggesting that it may be a target for the design of universal anti-CoV drugs.

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths around the world within the past 2 years. Transmission within the United States has been heterogeneously distributed by geography and social factors with little data from North Carolina. Here, we describe results from a weekly cross-sectional study of 12,471 unique hospital remnant samples from 19 April to 26 December 2020 collected by four clinical sites within the University of North Carolina Health system, with a majority of samples from urban, outpatient populations in central North Carolina. We employed a Bayesian inference model to calculate SARS-CoV-2 spike protein immunoglobulin prevalence estimates and conditional odds ratios for seropositivity. Furthermore, we analyzed a subset of these seropositive samples for neutralizing antibodies. We observed an increase in seroprevalence from 2.9 (95% confidence interval [CI], 1.8 to 4.5) to 12.8 (95% CI, 10.6 to 15.2) over the course of the study. Latinx individuals had the highest odds ratio of SARS-CoV-2 exposure at 6.56 (95% CI, 4.66 to 9.44). Our findings aid in quantifying the degree of asymmetric SARS-CoV-2 exposure by ethnoracial grouping. We also find that 49% of a subset of seropositive individuals had detectable neutralizing antibodies, which was skewed toward those with recent respiratory infection symptoms. IMPORTANCE PCR-confirmed SARS-CoV-2 cases underestimate true prevalence. Few robust community-level SARS-CoV-2 ethnoracial and overall prevalence estimates have been published for North Carolina in 2020. Mortality has been concentrated among ethnoracial minorities and may result from a high likelihood of SARS-CoV-2 exposure, which we observe was particularly high among Latinx individuals in North Carolina. Additionally, neutralizing antibody titers are a known correlate of protection. Our observation that development of SARS-CoV-2 neutralizing antibodies may be inconsistent and dependent on severity of symptoms makes vaccination a high priority despite prior exposure.

BackgroundAdolescent and young adult (AYA; 13 to 39 years) survivors of childhood cancer may be especially vulnerable to physical health and mental health concerns during the pandemic. We investigated the impact of COVID-19 on the mental health status of AYA survivors (Aim 1) and shared tailored, evidence-based health-related information on COVID-19 (Aim 2).MethodsBetween May and June 2020, participants completed a cross-sectional online survey assessing their cancer history, current mental health status, and their COVID-19 information needs.ResultsNinety-four participants (78 females, 13 males, 2 non-binary) with a mean age of 26.9 years (SD = 6.2) were included in the final sample. Participants reported residing from 10 countries and 94% identified as White. Nearly half of the participants (49%) described their mental health status as worse now than before the pandemic. Thirty-nine participants (41%) that indicated their current mental health status was tied to fears/worries about their past cancer and treatment experienced a higher level of anxiety and PTSS than those who did not report the same. Most participants (77%) had not received any information related to the potential risks of COVID-19 and expressed an interest in receiving this information. In response, an infographic detailing recommended strategies for coping with mental health problems in the pandemic, along with preliminary study findings, was developed.DiscussionAYA survivors reporting their mental health status was linked to their past cancer experienced poorer mental health. There is a value to educating survivors on their potential health risks, but accounting for their perceived mental health vulnerabilities should be considered when disseminating knowledge. The use of an infographic is a unique contribution towards the development of innovative and personalized means of sharing health education to this vulnerable yet resilient group. This research on the mental health status of AYA survivors very early in the pandemic informs continued initiatives investigating the rapidly changing nature of how COVID-19 may impact AYA survivors today and in the future.

Interface engineering is a significant strategy to develop structural materials with good properties. In this study, bulk V/Cu nano-multilayers with different layer thicknesses were fabricated by cross accumulative roll bonding (CARB). Interface stability of V/Cu nano-multilayers with different layer thicknesses and their effects on thermal conductivity and helium irradiation have been explored. The microstructure analysis, tensile and hardness tests result show that V/Cu nano-multilayers maintain high mechanical properties and good thermal stability after annealing at 500 °C for 1 h. However, the strength drastically degrades after higher-temperature annealing because of microstructure instability, which is closely related to the aspect ratio of grains. Furthermore, spheroidization occurring in multilayer during the annealing process promotes efficient electron transportation and weakens electron scattering, which benefits the increase of thermal conductivity. The irradiation response of V/Cu nano-multilayers was explored by helium bombardment with a fluence of 1 × 1017 ions/cm2 at room temperature and 500 °C, respectively. Helium bubbles transform to gas cavities with increasing irradiated temperature, and different morphology of cavities at heterointerface, newly formed grain boundaries and triple junctions is attributed to the defect diffusion preference combined with thermal-induced interfaces migration.

Detection of circulating tumor cells (CTCs), at the single-cell level, can be of great value for subsequent treatment of tumors but remains a significant challenge. Herein, we report a phage-based detection strategy for the identification of single CTC. The key assay component is the flexible recombinant M13@anti-CEA-scFv probe (M13, CEA, and scFv stand for M13 phage, carcinoembryonic antigen, and single-chain variable region fragment, respectively), which has a high, monoclonal antibody-like binding affinity for tumor cell-expressed CEA antigen, as confirmed by enzyme-linked immunosorbent assay (ELISA). Cell immunofluorescence experiments by confocal microscopy also demonstrate that the M13@anti-CEA-scFv could specifically bind to CEA-positive colon cancer cells such as Caco-2 and HT29, instead of CEA-negative HEK293T cells even when in great excess. Quantitative polymerase chain reaction (qPCR) further proves the ability to pin down single Caco-2 cell in 1 mL of spiked samples by 1,000 copies of M13@anti-CEA-scFv probe, after merely 15 min incubation. Another probe, the rigid magnetic microparticle (MMP), loaded with anti-CEA antibody, is used for the initial screening of the single CTC, which is mixed with numerous lymphocytes. The CEA on the resultant MMPs/CTC complex is subsequently recognized by numerous copies of M13@anti-CEA-scFv to form an MMP/CTC/M13@anti-CEA-scFv sandwich complex. Probing the phage DNA in this complex by qPCR leads to the unambiguous identification of the single Caco-2 cell in 1 mL of spiked blood samples. The phage-based detection strategy holds promise for the single-cell detection of any CTCs since the scFv displayed at the end of phage can be customized to the unique antigen of a specific CTC.

We study the broadband emission of Mrk 501 using multiwavelength observations from 2017 to 2020 performed with a multitude of instruments, involving, among others, MAGIC, Fermi's Large Area Telescope (LAT), NuSTAR, Swift, GASP-WEBT, and the Owens Valley Radio Observatory. Mrk 501 showed an extremely low broadband activity, which may help to unravel its baseline emission. Nonetheless, significant flux variations are detected at all wave bands, with the highest occurring at X-rays and very-high-energy (VHE) γ -rays. A significant correlation (>3 σ ) between X-rays and VHE γ -rays is measured, supporting leptonic scenarios to explain the variable parts of the emission, also during low activity. This is further supported when we extend our data from 2008 to 2020, and identify, for the first time, significant correlations between the Swift X-Ray Telescope and Fermi-LAT. We additionally find correlations between high-energy γ -rays and radio, with the radio lagging by more than 100 days, placing the γ -ray emission zone upstream of the radio-bright regions in the jet. Furthermore, Mrk 501 showed a historically low activity in X-rays and VHE γ -rays from mid-2017 to mid-2019 with a stable VHE flux (>0.2 TeV) of 5% the emission of the Crab Nebula. The broadband spectral energy distribution (SED) of this 2 yr long low state, the potential baseline emission of Mrk 501, can be characterized with one-zone leptonic models, and with (lepto)-hadronic models fulfilling neutrino flux constraints from IceCube. We explore the time evolution of the SED toward the low state, revealing that the stable baseline emission may be ascribed to a standing shock, and the variable emission to an additional expanding or traveling shock.

In this study, we found that neutralizing antibody responses in COVID-19-convalescent individuals vary in magnitude but are durable and correlate well with receptor binding domain (RBD) Ig binding antibody levels compared to other SARS-CoV-2 antigen responses. In our cohort, higher neutralizing antibody titers are independently and significantly associated with male sex compared to female sex.

Hydromorphological attributes such as flow width, water extent, and gradient play an important role in river hydrological, biogeochemical, and ecological processes and can help to predict river conveyance capacity, discharge, and flow routing. While there are some river width datasets at global or regional scales, they do not consider temporal variation in river width and do not cover all Australian rivers. We combined detailed mapping of 1.4 million river reaches across the Australian continent with inundation frequency mapping from 27 years of Landsat observations. From these, the average flow width at different recurrence frequencies was calculated for all reaches, having a combined length of 3.3 million km. A parameter γ was proposed to describe the shape of the frequency–width relationship and can be used to classify reaches by the degree to which flow regime tends towards permanent, frequent, intermittent, or ephemeral. Conventional scaling rules relating river width to gradient and contributing catchment area and discharge were investigated, demonstrating that such rules capture relatively little of the real-world variability. Uncertainties mainly occur in multi-channel reaches and reaches with unconnected water bodies. The calculated reach attributes are easily combined with the river vector data in a GIS, which should be useful for research and practical applications such as water resource management, aquatic habitat enhancement, and river engineering and management. The dataset is available at https://doi.org/10.25914/5c637a7449353 (Hou et al., 2019).

Abstract Background Palliative pemetrexed-based chemotherapy remains a standard of care treatment for the majority of patients with advanced non-squamous non-small-cell lung cancer (NSCLC). Currently, no predictive markers for pemetrexed treatment are available. Methods Resected tumour samples from pemetrexed-naïve NSCLC patients were collected. Gene expression profiling with respect to predicted sensitivity to pemetrexed classified predicted responders (60%) and non-responders (40%) based on differentially expressed genes encoding for pemetrexed target enzymes. Genes showing a strong correlation with these target genes were selected for measurement of corresponding protein expressions by immunohistochemical (IHC) staining. A semi-quantitative IHC scoring method was applied to construct a prediction model for response to pemetrexed. A retrospective cohort of patients with advanced NSCLC treated with first-line pemetrexed-based chemotherapy was used for external validation. Results From ninety-one patients resected tumour samples were collected. The majority of patients had early or locally advanced NSCLC (96.3%). Gene expression profiling revealed five markers, which mRNA levels strongly correlated to pemetrexed target genes mRNA levels: TPX2, CPA3, EZH2, MCM2 and TOP2A. Of 63 (69%) patients IHC staining scores of these markers were obtained, which significantly differed between predicted non-responders and responders (P

SARS-CoV-2 (the causative agent of COVID-19) is a major public health threat and one of two related coronaviruses that have caused epidemics in modern history. A method of screening potential infectible hosts for preemergent and future emergent coronaviruses would aid in mounting rapid response and intervention strategies during future emergence events.

Chimeric antigen receptor (CAR) T cells use re-engineered cell surface receptors to specifically bind to and lyse oncogenic cells. Two clinically approved CAR-T–cell therapies have significant clinical efficacy in treating CD19-positive B cell cancers. With widespread interest to deploy this immunotherapy to other cancers, there has been great research activity to design new CAR structures to increase the range of targeted cancers and anti-tumor efficacy. However, several obstacles must be addressed before CAR-T–cell therapies can be more widely deployed. These include limiting the frequency of lethal cytokine storms, enhancing T-cell persistence and signaling, and improving target antigen specificity. We provide a comprehensive review of recent research on CAR design and systematically evaluate design aspects of the four major modules of CAR structure: the ligand-binding, spacer, transmembrane, and cytoplasmic domains, elucidating design strategies and principles to guide future immunotherapeutic discovery.

River discharge measurements have proven invaluable to monitor the global water cycle, assess flood risk, and guide water resource management. However, there is a delay, and ongoing decline, in the availability of gauging data and stations are highly unevenly distributed globally. While not a substitute for river discharge measurement, remote sensing is a cost-effective technology to acquire information on river dynamics in situations where ground-based measurements are unavailable. The general approach has been to relate satellite observation to discharge measured in situ, which prevents its use for ungauged rivers. Alternatively, hydrological models are now available that can be used to estimate river discharge globally. While subject to greater errors and biases than measurements, model estimates of river discharge do expand the options for applying satellite-based discharge monitoring in ungauged rivers. Our aim was to test whether satellite gauging reaches (SGRs), similar to virtual stations in satellite altimetry, can be constructed based on Moderate Resolution Imaging Spectroradiometer (MODIS) optical or Global Flood Detection System (GFDS) passive microwave-derived surface water extent fraction and simulated discharge from the World-Wide Water (W3) model version 2. We designed and tested two methods to develop SGRs across the Amazon Basin and found that the optimal grid cell selection method performed best for relating MODIS and GFDS water extent to simulated discharge. The number of potential river reaches to develop SGRs increases from upstream to downstream reaches as rivers widen. MODIS SGRs are feasible for more river reaches than GFDS SGRs due to its higher spatial resolution. However, where they could be constructed, GFDS SGRs predicted discharge more accurately as observations were less affected by cloud and vegetation. We conclude that SGRs are suitable for automated large-scale application and offer a possibility to predict river discharge variations from satellite observations alone, for both gauged and ungauged rivers.

Carbon dioxide release during soil organic carbon (SOC) turnover is a pivotal component of atmospheric CO2 concentrations and global climate change. However, reliably measuring SOC turnover rates on large spatial and temporal scales remains challenging. Here we use a natural carbon isotope approach, defined as beta (β), which was quantified from the δ13C of vegetation and soil reported in the literature (176 separate soil profiles), to examine large-scale controls of climate, soil physical properties and nutrients over patterns of SOC turnover across terrestrial biomes worldwide. We report a significant relationship between β and calculated soil C turnover rates (k), which were estimated by dividing soil heterotrophic respiration rates by SOC pools. ln( − β) exhibits a significant linear relationship with mean annual temperature, but a more complex polynomial relationship with mean annual precipitation, implying strong-feedbacks of SOC turnover to climate changes. Soil nitrogen (N) and clay content correlate strongly and positively with ln( − β), revealing the additional influence of nutrients and physical soil properties on SOC decomposition rates. Furthermore, a strong (R2 = 0.76; p β) and estimates of litter and root decomposition rates suggests similar controls over rates of organic matter decay among the generalized soil C stocks. Overall, these findings demonstrate the utility of soil δ13C for independently benchmarking global models of soil C turnover and thereby improving predictions of multiple global change influences over terrestrial C-climate feedback.

Improved electrical characteristics of CMOS inverters composed of Ge n- and p-finFETs were demonstrated by utilizing newly introduced Ge surface treatments. In-situ digital O3 treatment in ALD chamber was adopted on the surface of Ge fin sidewall in order to reduce the roughness and etching damages through the GeO desorption mechanism. The treatment effects were checked by AFM and C-V measurements. By combining this treatment with optimized microwave annealing, sub-threshold slope and the $\text{I}_{\mathrm{ ON}}/\text{I}_{\mathrm{ OFF}}$ ratio were remarkably improved in both n-finFET and p-finFET, and Ge CMOS inverters with high voltage gain of 50.3 V/V at low ${V}_{D}= 0.6$ V was realized. Finally, simulations on an ideal Ge CMOS inverter were presented.

Time series data in practical applications always contain missing values due to sensor malfunction, network failure, outliers etc. In order to handle missing values in time series, as well as the lack of considering temporal properties in machine learning models, we propose a spatiotemporal prediction framework based on missing value processing algorithms and deep recurrent neural network (DRNN). By using missing tag and missing interval to represent time series patterns, we implement three different missing value fixing algorithms, which are further incorporated into deep neural network that consists of LSTM (Long Short-term Memory) layers and fully connected layers. Real-world air quality and meteorological datasets (Jingjinji area, China) are used for model training and testing. Deep feed forward neural networks (DFNN) and gradient boosting decision trees (GBDT) are trained as baseline models against the proposed DRNN. Performances of three missing value fixing algorithms, as well as different machine learning models are evaluated and analysed. Experiments show that the proposed DRNN framework outperforms both DFNN and GBDT, therefore validating the capacity of the proposed framework. Our results also provides useful insights for better understanding of different strategies that handle missing values.

Estimating exposure to fine Particulate Matter (PM2.5) requires surface with high spatial resolution. Aerosol optical depth (AOD) is one of MODIS products, being used to monitor PM2.5 concentration on ground level indirectly. In this research, AOD was derived in fine spatial resolution of 1×1 Km by utilizing an algorithm developed in which local aerosol models and conditions were took into account. Afterwards, due to spatial varying the relation between AOD-PM2.5, a regional scale geographically weighted regression model (GWR) was developed to derive daily seamless surface concentration of PM2.5 over Beijing, Tianjin and Hebei. For this purpose , various combinations of explanatory variables were investigated in the base of data availability, among which the best one includes AOD, PBL height, mean value of RH in boundary layer, mean value of temperature in boundary layer, wind speed and pressure was selected for the proposed GWR model over study area. The results show that, our model produces surface concentration of PM2.5 with annual RMSE of 18.6μg/m3. Besides, the feasibility of our model in estimating air pollution level was also assessed and high compatibility between model and ground monitoring was observed, which demonstrates the capability of the MODIS AOD and proposed model to estimate ground level PM2.5.

Major tsunami disasters often cause great damage in the first few hours following an earthquake. The possible severity of such events requires preparations to prevent tsunami disasters or mitigate them. This paper is an attempt to develop a decision support system for rapid tsunami evacuation for local decision makers. Based on the numerical results database of tsunami disasters, this system can quickly obtain the tsunami inundation and travel time. Because numerical models are calculated in advance, this system can reduce decision-making time. Population distribution, as a vulnerability factor, was analyzed to identify areas of high risk for tsunami disasters. Combined with spatial data, this system can comprehensively analyze the dynamic and static evacuation process and identify problems that negatively impact evacuation, thus supporting the decision-making for tsunami evacuation in high-risk areas. When an earthquake and tsunami occur, this system can rapidly obtain the tsunami inundation and travel time and provide information to assist with tsunami evacuation operations.