Rapid Method To Determine 137Cs, 237Np, and Pu Isotopes in Seawater by SF-ICP-MS.

Neptunium-237, owing to its long half-life (t1/2 = 2.14 × 106 year) and similar conservatism to 137Cs, has the potential to replace 137Cs for water mass circulation studies on decades and even longer time scales. A new method for the determination of 137Cs, 237Np, and Pu isotopes in seawater samples was proposed to solve the difficulty of 237Np analysis in seawater. The developed method includes the separation technique of ammonium phosphomolybdate (AMP) adsorption for 137Cs and anion exchange chromatography for 237Np and Pu, a measurement technique of gamma spectrometry for 137Cs and SF-ICP-MS for 237Np and Pu isotopes. 242Pu as a pseudo isotope dilution tracer for Np, the negligible chemical fractionation between 237Np and 242Pu of 1.02 ± 0.06 (k = 2) was obtained by implementing sophisticated control of the redox system and chromatographic elution optimization. The analytical results for the International Atomic Energy Agency Certified Reference Materials (IAEA-443) agreed with the reference values, showing chemical yields of 65-88%, U decontamination factor above 106 level, and improved sample throughput (5 days for 12 samples). Meanwhile, the lower method detection limits (MDLs) of 237Np, 239Pu, and 240Pu were 1.3 × 10-3, 0.065, and 0.15 µBq L-1 for 15 L seawater, respectively. Results obtained by the developed method can be used to evaluate the impact on the marine ecological system of the planned marine discharge of Fukushima decontaminated wastewater. Working toward that purpose, we are the first to report the 237Np activity concentration in Pacific Ocean seawater sampled near the station site, and we obtained the value of 0.122-0.154 µBq L-1.

P-TransUNet: an improved parallel network for medical image segmentation.

Deep learning-based medical image segmentation has made great progress over the past decades. Scholars have proposed many novel transformer-based segmentation networks to solve the problems of building long-range dependencies and global context connections in convolutional neural networks (CNNs). However, these methods usually replace the CNN-based blocks with improved transformer-based structures, which leads to the lack of local feature extraction ability, and these structures require a huge number of data for training. Moreover, those methods did not pay attention to edge information, which is essential in medical image segmentation. To address these problems, we proposed a new network structure, called P-TransUNet. This network structure combines the designed efficient P-Transformer and the fusion module, which extract distance-related long-range dependencies and local information respectively and produce the fused features. Besides, we introduced edge loss into training to focus the attention of the network on the edge of the lesion area to improve segmentation performance. Extensive experiments across four tasks of medical image segmentation demonstrated the effectiveness of P-TransUNet, and showed that our network outperforms other state-of-the-art methods.

EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation.

Although various methods based on convolutional neural networks have improved the performance of biomedical image segmentation to meet the precision requirements of medical imaging segmentation task, medical image segmentation methods based on deep learning still need to solve the following problems: (1) Difficulty in extracting the discriminative feature of the lesion region in medical images during the encoding process due to variable sizes and shapes; (2) difficulty in fusing spatial and semantic information of the lesion region effectively during the decoding process due to redundant information and the semantic gap. In this paper, we used the attention-based Transformer during the encoder and decoder stages to improve feature discrimination at the level of spatial detail and semantic location by its multihead-based self-attention. In conclusion, we propose an architecture called EG-TransUNet, including three modules improved by a transformer: progressive enhancement module, channel spatial attention, and semantic guidance attention. The proposed EG-TransUNet architecture allowed us to capture object variabilities with improved results on different biomedical datasets. EG-TransUNet outperformed other methods on two popular colonoscopy datasets (Kvasir-SEG and CVC-ClinicDB) by achieving 93.44% and 95.26% on mDice. Extensive experiments and visualization results demonstrate that our method advances the performance on five medical segmentation datasets with better generalization ability.

Spatial-Spectral Unified Adaptive Probability Graph Convolutional Networks for Hyperspectral Image Classification.

In hyperspectral image (HSI) classification task, semisupervised graph convolutional network (GCN)-based methods have received increasing attention. However, two problems still need to be addressed. The first is that the initial graph structure in the GCN-based methods is not sufficiently flexible to encode the homogenous structure similarity of HSI pixels when facing the complex scenarios induced by the spatial variability. Another problem is that the input (graph structure) and output (output features) of the GCN-based methods are separated with a "single pass" procedure, which is a suboptimal problem for HSI classification because it does not flexibly optimize the graph construction with a feedback method via output features. In this article, a novel spatial-spectral unified adaptive probability GCN (SSAPGCN) method is proposed for HSI classification. First, considering the homogeneous structural similarity of the pairwise relationships of HSI pixels, this article combines the inherent spectral information and spatial coordinates to obtain the spatial-spectral adaptive probability graph (SSAPG) structure, which can capture the probabilistic connectivity between each pair of the homogeneous HSI pixels. Second, the SSAPG structure and GCN model are combined into a unified framework to a daptively learn both the graph structure and the output features simultaneously with feedback. Finally, the proposed SSAPGCN method with two layers is evaluated on four public HSI datasets to demonstrate its superiority over different classification methods in terms of two evaluation metrics, the overall accuracy (OA) and kappa coefficient (KC), especially with small training sample sizes.

Spatial variation, sources, and potential ecological risk of metals in sediment in the northern South China Sea.

Heavy metals are of great concern to humans because of their persistence, bioaccumulation, and toxicity. A study on the spatial variation, sources, and potential ecological risk of heavy metals in the coastal sedimentary environment are helpful to clarify the pollution history of aquatic systems and effectively manage and control heavy metal pollution. However, most studies are limited to the Pearl River Estuary region. To investigate the spatial distribution characteristics, sources, and potential ecological risks of heavy metals (Cr, Cu, Pb, Ni, Sn, Zn, As, Cd), a total of 41 sediment samples from the northern South China Sea (NSCS) region were analyzed. The results show that Cu, Ni, Pb, and Zn have similar distribution patterns and their migration path in the coastal area is mainly controlled by the coastal current in western Guangdong. Meanwhile, these metals also have similar sources, i.e. natural weathering products. The distribution patterns of Cr, Sn, Cd, and As are not affected by the coastal current, and the sources of these metals are not only natural weathering products but also human inputs such as electroplating and electronic industries and runoff from agricultural sites. Agricultural activities, coal-burning activities, and aerosol precipitation may be another important source of human activities for As. More than half (65.9 %) of the sampling sites were categorized as having low potential ecological risk, 24.4 % for moderate risk, 7.3 % for considerable risk, and 2.4 % for high potential ecological risk, and the potential ecological risk metals of Cr, Cd, and As in NSCS should be more attention.

A deep learning network based on multi-scale and attention for the diagnosis of chronic atrophic gastritis.

BACKGROUND AND STUDY AIM: Chronic atrophic gastritis plays an important role in the process of gastric cancer. Deep learning is gradually introduced in the medical field, and how to better apply a convolutional neural network (CNN) to the diagnosis of chronic atrophic gastritis remains a research hotspot. This study was designed to improve the performance of CNN on diagnosing chronic atrophic gastritis by constructing and evaluating a network structure based on the characteristics of gastroscopic images. METHODS: Three endoscopists reviewed the endoscopic images of the gastric antrum from the Gastroscopy Image Database of Zhongnan Hospital and labelled available images according to pathological results. Two novel modules proposed recently were introduced to construct the Multi-scale with Attention net (MWA-net) considering the characters of similar medical images. After training the network using images of training sets, the diagnostic ability of the MWA-net was evaluated by comparing it with those of other deep learning models and endoscopists with varying degrees of expertise. RESULTS: As a result, 5,159 images of the gastric antrum from 2,240 patients were used to train and test the MWA-net. Compared with the direct application of famous networks, the MWA-net achieved the best performance (accuracy, 92.13%) with an increase of 1.80% compared to that of ResNet. The suspicious lesions indicated by the network are consistent with the conclusion of experts. The sensitivity and specificity of the convolutional network for gastric atrophy diagnosis are 90.19% and 94.51%, respectively, which are higher than those of experts. CONCLUSIONS: Highly similar images of chronic atrophic gastritis can be identified by the proposed MWA-net, which has a better performance than other well-known networks. This work can further reduce the workload of gastroscopists, simplify the diagnostic process and provide medical assistance to more residents.

Source and distribution characteristics of 239, 240, 241Pu, 237Np and 134, 137Cs in sediments in the Northwest and Central Equatorial Pacific after the Fukushima nuclear accident.

To understand the possible influence of the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident on the deep sea, as well as the geochemical behavior and transport of radionuclides, 134Cs, 137Cs, 239, 240Pu, 241Pu, and 237Np were measured in the abyssal sediments of the Northwest Pacific (NWP) and Central Equatorial Pacific (CEP) Ocean. Data on the characteristics of these sediments obtained after the FDNPP accident are extremely rare, especially in the NWP subtropical gyre (NPSG) region. FDNPP-derived radio-Cs (134Cs, 137Cs) arrived at the open sea floor of the NWP before 2018 but was only found in the Kuroshio-Oyashio Extension (KOE) region. No FDNPP-derived Pu was detected in the abyssal sediments of the NWP or CEP. Pu in the NWP mainly originated from global fallout and the Pacific Proving Ground (PPG) close-in fallout, except for at station WP1 (39°N in the KOE region), where an abnormal but non-FDNPP-derived Pu signal was detected. Pu in the eastern CEP sediment was less affected by the PPG close-in fallout from the Marshall Islands and was mainly derived from global fallout, with some close-in fallout from the Johnston Atoll test. The KOE region was the area most affected by PPG close-in fallout Pu via Kuroshio transport, while the lowest inventories of 239+240Pu and 237Np were found in the NPSG region due to its oligotrophic environment. The 237Np originated from the same source as Pu, and the latitudinal pattern of 237Np was consistent with that of Pu. Station SS (in the marginal sea of the NWP) contained high 237Np/239Pu atom ratios in the deeper layers of sediment and had a 237Np depth profile opposite that of the 239+240Pu profile, compared to other stations; these differences are mainly attributed to differences in the behaviors of 237Np and 239Pu.

Distinctive distribution and migration of global fallout plutonium isotopes in an alpine lake and its implications for sediment dating.

This work investigated plutonium (Pu) isotopes in sediment cores collected from an alpine lake (Lake Heinongpo with 3779 m above sea level) in Southwestern China. 240Pu/239Pu atom ratios in all sediment samples showed the typical global fallout values of ∼0.18 without any influences from other Pu contaminant sources. 239+240Pu activities with surface and subsurface maximums followed by exponential decline with sediment depth were respectively observed in the two sediment cores. The distinctive depth distributions of 239,240Pu in the lake sediments was attributed to the very slow sediment deposition rate due to the lack of terrestrial sediment input, while the alpine snowmelt input was the primary source of Pu in the lake sediments in addition to the direct atmospheric deposition. The total Pu inventory was estimated to be 56.3 ± 1.4 and 63.9 ± 0.8 Bq/m2 respectively in the two sediment cores. The generally higher Pu inventory in the Lake Heinongpo compared with other reported lakes in similar latitude should be mainly attributed to their different Pu input passages. The advection-diffusion equation was further applied to evaluate the downward migration of Pu isotopes in the sediment cores and predict the future evolution of Pu distribution in the sediment cores. The fitted results indicated that the diffusion effect controlled the downward migration of Pu in the sediments, but this diffusive migration will not prevent the peak of global fallout Pu in undisturbed sediment cores from being a valuable time marker for sediment dating.

The 240Pu/239Pu atom ratio in Chinese soils.

The 240Pu/239Pu atom ratio is a very effective tool for the identification of the origin of plutonium (Pu) in the soil environment. We examine a dataset of 240Pu/239Pu atom ratios determined from surface and core soils at 240 sites across China. The data were compiled from 18 separate literature sources from the last 20 years. For the first time the spatial distribution (3 latitude bands and 7 natural regions) of the weighted average 240Pu/239Pu atom ratios in Chinese soils is investigated. An area to the West of Xining City, shows a weighted average 240Pu/239Pu atom ratio of 0.167 ±â€¯0.002, lower than that of average global fallout, which likely arises from the addition of local fallout radionuclides from the Chinese nuclear weapon tests at Lop Nor between 1964 and 1980. The Yumen and Jiuquan areas of Northwest China in particular show evidence of very low ratio material from the Chinese nuclear weapon tests. Excluding the impacted area around the test site the weighted average 240Pu/239Pu ratio of 0.182 ±â€¯0.002 suggests that global fallout is the main source of Pu in most Chinese soils.

137Cs and 239+240Pu in the Bohai Sea of China: Comparison in distribution and source identification between the inner bay and the tidal flat.

We investigated artificial radionuclides (239+240Pu and 137Cs) in surface sediments and sediment cores collected from the Bohai Bay and the tidal flat of the Liaodong Bay, China. Increasing trends for 239+240Pu activities and 240Pu/239Pu atom ratios (˃0.18) were observed from land to sea and from north to south in the Bohai Bay. This spatial pattern implied that the scavenging process between riverine sediments and Pacific Proving Ground (PPG) source Pu transported by the currents such as Yellow Sea Warm Current had occurred in the Bohai Bay. In contrast, relatively lower 240Pu/239Pu atom ratios in the tidal flat of Liaodong Bay were due to the mixing process between more global out and less PPG source Pu. The riverine Pu contributions to the total global fallout Pu in the Haihe River (32.8%) were much lower than those in the Yangtze River estuary (77%-80%), indicating better soil conservation in the Haihe River Catchment.

Sources of plutonium isotopes and 137Cs in coastal seawaters of Liaodong Bay and Bohai Strait, China and its environmental implications.

In order to investigate the sources of plutonium in seawaters of Liaodong Bay and Bohai Strait, China, surface seawater samples were collected and analyzed for 239+240Pu and 137Cs by radiochemical separation combined with ICP-MS and γ-spectrometry, respectively. A large variation of 239+240Pu activities was observed, ranging from 1.993 to 29.677 mBq/m3 in the Liaodong Bay and from 0.932 to 10.183 mBq/m3 in the Bohai Strait. 137Cs activities showed little variation between the investigated locations, which was attributed to the different behavior characteristics of 239+240Pu and 137Cs in seawaters. The 240Pu/239Pu atom ratios showed a significant variation between the Liaodong Bay (0.185) and Bohai Strait (0.225), indicating that Pu derived from the Pacific Proving Grounds might have been transported to the Bohai Strait but not yet to the Liaodong Bay, which could further provide valuable reference for evaluating the seawater exchange cycle between the Bohai Sea and Yellow Sea.

Sedimentary record of plutonium in the North Yellow Sea and the response to catchment environmental changes of inflow rivers.

Plutonium (Pu) isotopes were first determined in surface and core sediment samples collected from the northern North Yellow Sea (NYS) to elucidate their source terms and deposition process as well as the response to catchment environmental changes of inflow rivers. 240Pu/239Pu atom ratios in all sediments showed the typical global fallout value of ∼0.18 without any influences from the nuclear weapons tests conducted recently in the North Korea or early in the Pacific Proving Ground. The large variation of 239+240Pu activities (0.022-0.515 mBq/g) observed in surface sediments should be mainly attributed to the re-suspension and transportation of fine sediments influenced by the Liaonan Costal Current. Based on the two 239+249Pu depth profiles with easily observed onset fallout levels (1952) and global fallout peaks (1963), 239+240Pu served as a valid time mark in the coastal sedimentary system. Riverine input Pu contributed only 15-27% to the total global fallout inventory (92.5-108.8 Bq/m2) in the northern NYS, much lower than that in the Yangtze River estuary (77-80%), indicating a better soil conservation in the northeast China due to higher forest coverage compared to the Yangtze River's drainage basin. The increase of riverine input Pu after 1980s reflected the more intense soil erosion degree caused by the land use and cover change due to the increment of human activities in the northeast China at the same period. Our results demonstrated that plutonium is a good indicator for studying sedimentary process and its response to the environment in the coastal area.

Vertical distributions and source identification of the radionuclides 239Pu and 240Pu in the sediments of the Liao River estuary, China.

Activity concentration of plutonium (Pu) and its isotopic compositions are extensively used for measuring transport processes of Pu and identifying its source. We investigated the spatial distribution characteristics of 239+240Pu activity concentrations and 240Pu/239Pu atom ratio in several sediment cores collected from the Liao River coastal zone. Additionally, we calculated the 239+240Pu inventories and based on the 240Pu/239Pu atom ratio to trace Pu source. The activity concentrations of 239+240Pu in surface sediments of the Liao River estuary ranged between 0.103 ± 0.008 and 0.978 ± 0.035 mBq/g, with an average of 0.294 ± 0.024 mBq/g. The 240Pu/239Pu atom ratios, ranging from 0.173 ± 0.047 to 0.215 ± 0.061 (mean: 0.188 ± 0.049 (1σ)), were consistent with global fallout value, which indicates the global atmospheric fallout is the main source of Pu in sediment cores from the both sides of Liao River estuary. As for the tidal flat core LT-2, the mean 240Pu/239Pu atom ratio, slightly higher than that of the global fallout value, was 0.217 ± 0.050. Such pattern of Pu isotopic compositions indicated that Pu on the tidal flat in the Liao River estuary is sourced from a combination of global fallout and close-in fallout from the PPG by ocean currents transporting. And by using a two end-member mixing model, the results indicate the relative contribution of the PPG close-in fallout to core LT-2 is round 27% and 73% can be attributed to global fallout and river input. Therefore, these results clearly indicate that the direct global fallout is the main source of Pu in the Liao River estuary.

A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems.

A web geographical information system is a typical service-intensive application. Tile prefetching and cache replacement can improve cache hit ratios by proactively fetching tiles from storage and replacing the appropriate tiles from the high-speed cache buffer without waiting for a client's requests, which reduces disk latency and improves system access performance. Most popular prefetching strategies consider only the relative tile popularities to predict which tile should be prefetched or consider only a single individual user's access behavior to determine which neighbor tiles need to be prefetched. Some studies show that comprehensively considering all users' access behaviors and all tiles' relationships in the prediction process can achieve more significant improvements. Thus, this work proposes a new global user-driven model for tile prefetching and cache replacement. First, based on all users' access behaviors, a type of expression method for tile correlation is designed and implemented. Then, a conditional prefetching probability can be computed based on the proposed correlation expression mode. Thus, some tiles to be prefetched can be found by computing and comparing the conditional prefetching probability from the uncached tiles set and, similarly, some replacement tiles can be found in the cache buffer according to multi-step prefetching. Finally, some experiments are provided comparing the proposed model with other global user-driven models, other single user-driven models, and other client-side prefetching strategies. The results show that the proposed model can achieve a prefetching hit rate in approximately 10.6% ~ 110.5% higher than the compared methods.

Association of Plutonium isotopes with natural soil particles of different size and comparison with 137Cs.

Information on how plutonium (Pu) isotopes associate with natural soil particles of different size is very important for the interpretation involved in the application of Pu isotopes as soil erosion tracers. This work investigated the association of Pu isotopes with different particle size fractions of natural soils and compared it with that of 137Cs. Ten bulk soils collected from two different areas were separated into different particle size fractions by a combination of wet sieving and centrifugation techniques and the sub-samples were analyzed for 137Cs, 239Pu and 240Pu. Results showed that the concentrations of both 239+240Pu and 137Cs increase with decreased particle sizes and are closely related to the specific surface areas of soil particles, which demonstrated a similar preferential association of Pu with finer soil particles as 137Cs. The activity ratios of 239+240Pu/137Cs in soil fractions increasing with increased particle size further indicated a less preferential transport of Pu with fine particles compared to 137Cs. These results not only highlight the suitability of Pu isotopes as soil erosion tracers, but also provide useful information for assessing the migration behavior of Pu in contaminated environments.

Simultaneous determination of radiocesium ((135)Cs, (137)Cs) and plutonium ((239)Pu, (240)Pu) isotopes in river suspended particles by ICP-MS/MS and SF-ICP-MS.

Due to radioisotope releases in the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident, long-term monitoring of radiocesium ((135)Cs and (137)Cs) and Pu isotopes ((239)Pu and (240)Pu) in river suspended particles is necessary to study the transport and fate of these long-lived radioisotopes in the land-ocean system. However, it is expensive and technically difficult to collect samples of suspended particles from river and ocean. Thus, simultaneous determination of multi-radionuclides remains as a challenging topic. In this study, for the first time, we report an analytical method for simultaneous determination of radiocesium and Pu isotopes in suspended particles with small sample size (1-2g). Radiocesium and Pu were sequentially pre-concentrated using ammonium molybdophosphate and ferric hydroxide co-precipitation, respectively. After the two-stage ion-exchange chromatography separation from the matrix elements, radiocesium and Pu isotopes were finally determined by ICP-MS/MS and SF-ICP-MS, respectively. The interfering elements of U ((238)U(1)H(+) and (238)U(2)H(+) for (239)Pu and (240)Pu, respectively) and Ba ((135)Ba(+) and (137)Ba(+) for (135)Cs and (137)Cs, respectively) were sufficiently removed with the decontamination factors of 1-8×10(6) and 1×10(4), respectively, with the developed method. Soil reference materials were utilized for method validation, and the obtained (135)Cs/(137)Cs and (240)Pu/(239)Pu atom ratios, and (239+240)Pu activities showed a good agreement with the certified/information values. In addition, the developed method was applied to analyze radiocesium and Pu in the suspended particles of land water samples collected from Fukushima Prefecture after the FDNPP accident. The (135)Cs/(137)Cs atom ratios (0.329-0.391) and (137)Cs activities (23.4-152Bq/g) suggested radiocesium contamination of the suspended particles mainly originated from the accident-released radioactive contaminates, while similar Pu contamination of suspended particles caused by the accident could be neglected as the (240)Pu/(239)Pu atom ratios (0.182-0.208) were within the range of global fallout.

Plutonium determination in seawater by inductively coupled plasma mass spectrometry: A review.

Knowing the concentration and isotopic ratio of Pu in seawater is of critical importance for assessing Pu contamination and investigating oceanic processes. In recent decades, the concentration of (239+240)Pu in seawater, particularly for surface seawater, has presented an exponential decreasing trend with time; thus determination of Pu in seawater has become a challenge nowadays. Here, we have summarized and critically discussed a variety of reported analytical methods for Pu determination in seawater sample based on inductively coupled plasma mass spectrometry (ICP-MS) analytical technique for rapid ultra-trace detection of Pu. Generally, pretreatments for seawater sample include co-precipitation, valence adjustment and chemical separation and purification procedures, all of which are comprehensively reviewed. Overall, the selected anion-exchange, extraction resins and operation condition are important for decontamination of interference from matrix elements and achieving satisfactory chemical yields. In addition, other mass spectrometric and radiometric detections are briefly addressed and compared with the focus on assessing ICP-MS. Finally, we discuss some issues and prospects in determination and application of Pu isotopes in seawater samples for future research.

Feature Selection and Pedestrian Detection Based on Sparse Representation.

Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. Based on the theoretical analysis of six frequently-used features, SIFT, SURF, Haar, HOG, LBP and LSS, and their comparison with experimental results, this paper screens out the sparse feature subsets via sparse representation to investigate whether the sparse subsets have the same description abilities and the most stable features. When any two of the six features are fused, the fusion feature is sparsely represented to obtain its important components. Sparse subsets of the fusion features can be rapidly generated by avoiding calculation of the corresponding index of dimension numbers of these feature descriptors; thus, the calculation speed of the feature dimension reduction is improved and the pedestrian detection time is reduced. Experimental results show that sparse feature subsets are capable of keeping the important components of these six feature descriptors. The sparse features of HOG and LSS possess the same description ability and consume less time compared with their full features. The ratios of the sparse feature subsets of HOG and LSS to their full sets are the highest among the six, and thus these two features can be used to best describe the characteristics of the pedestrian and the sparse feature subsets of the combination of HOG-LSS show better distinguishing ability and parsimony.

Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns.

Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further split for distributed storage. In this paper, we propose a complete theoretical system for the distributed storage of small geospatial image data files based on mining the access patterns of geospatial image data using their historical access log information. First, an algorithm is developed to construct an access correlation matrix based on the analysis of the log information, which reveals the patterns of access to the geospatial image data. Then, a practical heuristic algorithm is developed to determine a reasonable solution based on the access correlation matrix. Finally, a number of comparative experiments are presented, demonstrating that our algorithm displays a higher total parallel access probability than those of other algorithms by approximately 10-15% and that the performance can be further improved by more than 20% by simultaneously applying a copy storage strategy. These experiments show that the algorithm can be applied in distributed environments to help realize parallel I/O and thereby improve system performance.

Heavy metal spatial variability and historical changes in the Yangtze River estuary and North Jiangsu tidal flat.

This research focuses on the spatial and temporal patterns of heavy metals from the Yangtze River estuary and the tidal flat of north Jiangsu. Most heavy metals in the surficial sediments after normalization to Ti decreased seaward at the Yangtze River estuary. The core records showed that the heavy metal variations in the last 50years were primarily linked to natural weathering input of trace elements. However, significant heavy metal pollution (mainly Ni, Pb, Cd, Cu and As) were in the two study areas, with anthropogenic inventories accounting for 23-40% percent of the total pollution. Sequential extraction showed that Pb, Cu and Ni were present largely in the non-residual fraction, which indicated the potential bioavailability in the study areas. The SEM/EDS together with sequential extraction facilitated the easy tracing of the origin/sources of heavy metals in a simple way in the estuary and the tidal flat.