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15 pages, 1381 KiB

Open AccessArticle

Secure Sharing of Electronic Medical Records Based on Blockchain and Searchable Encryption

by Aomen Zhao and Hongliang Tian

Electronics 2025, 14(13), 2679; https://doi.org/10.3390/electronics14132679 - 2 Jul 2025

Viewed by 333

In recent years, Electronic Medical Record (EMR) sharing has played an indispensable role in optimizing clinical treatment plans, advancing medical research in biomedical science. However, existing EMR management schemes often face security risks and suffer from inefficient search performance. To address these issues, [...] Read more.

In recent years, Electronic Medical Record (EMR) sharing has played an indispensable role in optimizing clinical treatment plans, advancing medical research in biomedical science. However, existing EMR management schemes often face security risks and suffer from inefficient search performance. To address these issues, this paper proposes a secure EMR sharing scheme based on blockchain and searchable encryption. This scheme implements a decentralized management system with enhanced security and operational efficiency. Considering the scenario of EMRs requiring confirmation of multiple doctors to improve safety, the proposed solution leverages Shamir’s Secret Sharing to enable multi-party authorization, thereby enhancing privacy protection. Meanwhile, the scheme utilizes Bloom filter and vector operation to achieve efficient data search. The proposed method maintains rigorous EMR protection while improving the search efficiency of EMRs. Experimental results demonstrate that, compared to existing methodologies, the proposed scheme enhances security during EMR sharing processes. It achieves higher efficiency in index generation and trapdoor generation while reducing keyword search time. This scheme provides reliable technical support for the development of intelligent healthcare systems. Full article

(This article belongs to the Special Issue Blockchain Based Electronic Healthcare Solution and Security: 2nd Edition)

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20 pages, 6073 KiB

Open AccessArticle

A Unified Denoising Framework for Restoring the LiDAR Point Cloud Geometry of Reflective Targets

by Tianpeng Xie, Jingguo Zhu, Chunxiao Wang, Feng Li and Zhe Meng

Appl. Sci. 2025, 15(7), 3904; https://doi.org/10.3390/app15073904 - 2 Apr 2025

Cited by 1 | Viewed by 1097

Abstract

LiDAR point clouds of reflective targets often contain significant noise, which severely impacts the feature extraction accuracy and performance of object detection algorithms. These challenges present substantial obstacles to point cloud processing and its applications. In this paper, we propose a Unified Denoising [...] Read more.

LiDAR point clouds of reflective targets often contain significant noise, which severely impacts the feature extraction accuracy and performance of object detection algorithms. These challenges present substantial obstacles to point cloud processing and its applications. In this paper, we propose a Unified Denoising Framework (UDF) aimed at removing noise and restoring the geometry of reflective targets. The proposed method consists of three steps: veiling effect denoising using an improved pass-through filter, range anomalies correction through M-estimator Sample Consensus (MSAC) plane fitting and ray projection, and blooming effect denoising based on an adaptive error ellipse. The parameters of the error ellipse are automatically determined using the divergence angle of the laser beam, blooming factors, and the normal vector along the boundary of the point cloud. The proposed method was validated on a self-constructed traffic sign point cloud dataset. The experimental results showed that the method achieved a mean square error (MSE) of 0.15 cm², a mean city-block distance (MCD) of 0.05 cm, and relative height and width errors of 1.92% and 1.91%, respectively. Compared to five representative algorithms, the proposed method demonstrated superior performance in both denoising accuracy and the restoration of target geometric features. Full article

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19 pages, 2985 KiB

Open AccessArticle

Interactions between Filter-Feeding Bivalves and Toxic Diatoms: Influence on the Feeding Behavior of Crassostrea gigas and Pecten maximus and on Toxin Production by Pseudo-nitzschia

by Aurore Sauvey, Françoise Denis, Hélène Hégaret, Bertrand Le Roy, Christophe Lelong, Orianne Jolly, Marie Pavie and Juliette Fauchot

Toxins 2021, 13(8), 577; https://doi.org/10.3390/toxins13080577 - 19 Aug 2021

Cited by 9 | Viewed by 4094

Abstract

Among Pseudo-nitzschia species, some produce the neurotoxin domoic acid (DA), a source of serious health problems for marine organisms. Filter-feeding organisms—e.g., bivalves feeding on toxigenic Pseudo-nitzschia spp.—are the main vector of DA in humans. However, little is known about the interactions between bivalves [...] Read more.

Among Pseudo-nitzschia species, some produce the neurotoxin domoic acid (DA), a source of serious health problems for marine organisms. Filter-feeding organisms—e.g., bivalves feeding on toxigenic Pseudo-nitzschia spp.—are the main vector of DA in humans. However, little is known about the interactions between bivalves and Pseudo-nitzschia. In this study, we examined the interactions between two juvenile bivalve species—oyster (Crassostrea gigas) and scallop (Pecten maximus)—and two toxic Pseudo-nitzschia species—P. australis and P. fraudulenta. We characterized the influence of (1) diet composition and the Pseudo-nitzschia DA content on the feeding rates of oysters and scallops, and (2) the presence of bivalves on Pseudo-nitzschia toxin production. Both bivalve species fed on P. australis and P. fraudulenta. However, they preferentially filtered the non-toxic Isochrysis galbana compared to Pseudo-nitzschia. The presence of the most toxic P. australis species resulted in a decreased clearance rate in C. gigas. The two bivalve species accumulated DA in their tissues (up to 0.35 × 10⁻³ and 5.1 × 10⁻³ µg g⁻¹ for C. gigas and P. maximus, respectively). Most importantly, the presence of bivalves induced an increase in the cellular DA contents of both Pseudo-nitzschia species (up to 58-fold in P. fraudulenta in the presence of C. gigas). This is the first evidence of DA production by Pseudo-nitzschia species stimulated in the presence of filter-feeding bivalves. The results of this study highlight complex interactions that can influence toxin production by Pseudo-nitzschia and accumulation in bivalves. These results will help to better understand the biotic factors that drive DA production by Pseudo-nitzschia and bivalve contamination during Pseudo-nitzschia blooms. Full article

(This article belongs to the Special Issue Phycotoxins: From Producers to Transfer in the Food Chain)

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19 pages, 1887 KiB

Open AccessArticle

Vectored-Bloom Filter for IP Address Lookup: Algorithm and Hardware Architectures

by Hayoung Byun, Qingling Li and Hyesook Lim

Appl. Sci. 2019, 9(21), 4621; https://doi.org/10.3390/app9214621 - 30 Oct 2019

Cited by 12 | Viewed by 5579

Abstract

The Internet Protocol (IP) address lookup is one of the most challenging tasks for Internet routers, since it requires to perform packet forwarding at wire-speed for tens of millions of incomming packets per second. Efficient IP address lookup algorithms have been widely studied [...] Read more.

The Internet Protocol (IP) address lookup is one of the most challenging tasks for Internet routers, since it requires to perform packet forwarding at wire-speed for tens of millions of incomming packets per second. Efficient IP address lookup algorithms have been widely studied to satisfy this requirement. Among them, Bloom filter-based approach is attractive in providing high performance. This paper proposes a high-speed and flexible architecture based on a vectored-Bloom filter (VBF), which is a space-efficient data structure that can be stored in a fast on-chip memory. An off-chip hash table is infrequently accessed, only when the VBF fails to provide address lookup results. The proposed architecture has been evaluated through both a behavior simulation with C language and a timing simulation with Verilog. The hardware implementation result shows that the proposed architecture can achieve the throughput of 5 million packets per second in a field programmable gate array (FPGA) operated at 100 MHz. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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2 pages, 171 KiB

Open AccessEditorial

Advances and Current Challenges in Marine Biotoxins Monitoring

by Pedro Reis Costa

J. Mar. Sci. Eng. 2019, 7(9), 302; https://doi.org/10.3390/jmse7090302 - 2 Sep 2019

Cited by 2 | Viewed by 2323

Abstract

Shellfish are filter-feeding organisms that may accumulate high levels of naturally-occurring toxins, produced by harmful algal blooms, and act as marine toxin vectors to whomever consumes them [...] Full article

(This article belongs to the Special Issue Advances and Current Challenges in Marine Biotoxins Monitoring)

12 pages, 2295 KiB

Open AccessArticle

A Bloom Filter for High Dimensional Vectors

by Chunyan Shuai, Hengcheng Yang, Xin Ouyang and Zeweiyi Gong

Information 2018, 9(7), 159; https://doi.org/10.3390/info9070159 - 2 Jul 2018

Cited by 1 | Viewed by 5059

Abstract

Regardless of the type of data, traditional Bloom filters treat each element of a set as a string, and by iterating every character of the string, they discretize all data randomly and uniformly. However, with the data size and dimension increases, these variants [...] Read more.

Regardless of the type of data, traditional Bloom filters treat each element of a set as a string, and by iterating every character of the string, they discretize all data randomly and uniformly. However, with the data size and dimension increases, these variants are inefficient. To better discretize vectors with high numerical dimensions, this paper improves the string hashes to integer hashes. Based on the integer hashes and a counter array, we propose a new variant—high-dimensional bloom filter (HDBF)—to extend the Bloom filter into high-dimensional spaces, which can represent and query numerical vectors of a big set with a low false positive probability. This paper theoretically analyzes the feasibility of the integer hashes on discretizing data and discusses the relationship of parameters of the HDBF. The experiments illustrate that, in high-dimensional numerical spaces, the HDBF shows better randomness on distribution and entropy than that of the counting Bloom filter. Compared with the parallel Bloom filters, for a fixed false positive probability, the HDBF displays time-space overheads, and is more suitable to deal with the numerical vectors with high dimensions. Full article

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22 pages, 904 KiB

Open AccessTechnical Note

Learning-Based Algal Bloom Event Recognition for Oceanographic Decision Support System Using Remote Sensing Data

by Weilong Song, John M. Dolan, Danelle Cline and Guangming Xiong

Remote Sens. 2015, 7(10), 13564-13585; https://doi.org/10.3390/rs71013564 - 19 Oct 2015

Cited by 27 | Viewed by 7242

Abstract

This paper describes the use of machine learning methods to build a decision support system for predicting the distribution of coastal ocean algal blooms based on remote sensing data in Monterey Bay. This system can help scientists obtain prior information in a large [...] Read more.

This paper describes the use of machine learning methods to build a decision support system for predicting the distribution of coastal ocean algal blooms based on remote sensing data in Monterey Bay. This system can help scientists obtain prior information in a large ocean region and formulate strategies for deploying robots in the coastal ocean for more detailed in situ exploration. The difficulty is that there are insufficient in situ data to create a direct statistical machine learning model with satellite data inputs. To solve this problem, we built a Random Forest model using MODIS and MERIS satellite data and applied a threshold filter to balance the training inputs and labels. To build this model, several features of remote sensing satellites were tested to obtain the most suitable features for the system. After building the model, we compared our random forest model with previous trials based on a Support Vector Machine (SVM) using satellite data from 221 days, and our approach performed significantly better. Finally, we used the latest in situ data from a September 2014 field experiment to validate our model. Full article

(This article belongs to the Special Issue Remote Sensing of Water Resources)

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Graphical abstract

41 pages, 984 KiB

Open AccessReview

Non-Traditional Vectors for Paralytic Shellfish Poisoning

by Jonathan R. Deeds, Jan H. Landsberg, Stacey M. Etheridge, Grant C. Pitcher and Sara Watt Longan

Mar. Drugs 2008, 6(2), 308-348; https://doi.org/10.3390/md6020308 - 10 Jun 2008

Cited by 241 | Viewed by 30026

Abstract

Paralytic shellfish poisoning (PSP), due to saxitoxin and related compounds, typically results from the consumption of filter-feeding molluscan shellfish that concentrate toxins from marine dinoflagellates. In addition to these microalgal sources, saxitoxin and related compounds, referred to in this review as STXs, are [...] Read more.

Paralytic shellfish poisoning (PSP), due to saxitoxin and related compounds, typically results from the consumption of filter-feeding molluscan shellfish that concentrate toxins from marine dinoflagellates. In addition to these microalgal sources, saxitoxin and related compounds, referred to in this review as STXs, are also produced in freshwater cyanobacteria and have been associated with calcareous red macroalgae. STXs are transferred and bioaccumulate throughout aquatic food webs, and can be vectored to terrestrial biota, including humans. Fisheries closures and human intoxications due to STXs have been documented in several non-traditional (i.e. non-filter-feeding) vectors. These include, but are not limited to, marine gastropods, both carnivorous and grazing, crustacea, and fish that acquire STXs through toxin transfer. Often due to spatial, temporal, or a species disconnection from the primary source of STXs (bloom forming dinoflagellates), monitoring and management of such non-traditional PSP vectors has been challenging. A brief literature review is provided for filter feeding (traditional) and nonfilter feeding (non-traditional) vectors of STXs with specific reference to human effects. We include several case studies pertaining to management actions to prevent PSP, as well as food poisoning incidents from STX(s) accumulation in non-traditional PSP vectors. Full article

(This article belongs to the Special Issue Marine Toxins)

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