Query with Assumptions for Probabilistic Relational Databases

Users may have prior knowledge about a probabilistic database. They prefer to query over a probabilistic database on their prior knowledge which cannot be written as component clauses of conventional SQL queries. A naive approach is to query over a new database version, which is generated by transforming the original probabilistic database to satisfy users\u27 prior knowledge; however, it is impractical to generate a different probabilistic database version for each prior knowledge. In this paper, we propose the concept of the query with assumptions which allow users to describe their prior knowledge with a newly introduced ASSUMPTION clause of SQL. We also propose an approach to obtain the result of a query based on assumption clauses. The experimental studies show our approach has better performance compared to the naive approach

Enabling Access Control for Encrypted Multi-Dimensional Data in Cloud Computing through Range Search

With the growing popularity of cloud computing, data owners are increasingly opting to outsource their data to cloud servers due to the numerous benefits it offers. However, this outsourcing raises concerns about data privacy since the data stored on remote cloud servers is not directly controlled by the owners. Encryption of the data is an effective approach to mitigate these privacy concerns. However, encrypted data lacks distinguishability, leading to limitations in supporting common operations such as range search and access control. In this research paper, we propose a method called RSAC (Range Search Supporting Access Control) for encrypted multi-dimensional data in cloud computing. Our method leverages policy design, bucket embedding, algorithm design, and Ciphertext Policy-Attribute Based Encryption (CPABE) to achieve its objectives. We present extensive experimental results that demonstrate the efficiency of our method and conduct a thorough security analysis to ensure its robustness. Our proposed RSAC method addresses the challenges of range search and access control over encrypted multi-dimensional data, thus contributing to enhancing privacy and security in cloud computing environments

Formation and Characterization of Lactoferrin-Hyaluronic Acid Conjugates and Their Effects on the Storage Stability of Sesamol Emulsions

The purpose of this study was to fabricate biopolymer conjugates from lactoferrin (LF) and hyaluronic acid (HA) and then to investigate their potential as emulsifiers for forming sesamol-loaded emulsions. Initially, LF-HA covalent conjugates were formed using the carbodiimide coupling method in aqueous solutions at pH = 4.5, and then the nature of the conjugates was investigated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, and fluorescence spectroscopy. The results demonstrated the formation of an amide link between the amine groups of LF and the carboxyl groups of HA. Sesamol emulsions were prepared using the LF-HA conjugates as emulsifiers and their stability was determined. The conjugates improved both the physical and chemical stability of the emulsions during storage. Optimum stability of the emulsion was obtained at a LF-to-HA molar ratio of 2:1. Our results suggest that LF-HA conjugates may be effective emulsifiers for use in food stuffs and other applications

Predicting the Extreme Loads in Power Production of Large Wind Turbines Using an Improved PSO Algorithm

Predicting the extreme loads in power production for the preliminary-design of large-scale wind turbine blade is both important and time consuming. In this paper, a simplified method, called Particle Swarm Optimization-Extreme Load Prediction Model (PSO-ELPM), is developed to quickly assess the extreme loads. This method considers the extreme loads solution as an optimal problem. The rotor speed, wind speed, pitch angle, yaw angle, and azimuth angle are selected as design variables. The constraint conditions are obtained by considering the influence of the aeroelastic property and control system of the wind turbine. An improved PSO algorithm is applied. A 1.5 MW and a 2.0 MW wind turbine are chosen to validate the method. The results show that the extreme root load errors between PSO-ELPM and FOCUS are less than 10%, while PSO-ELPM needs much less computational cost than FOCUS. The distribution of flapwise bending moments are close to the results of FOCUS. By analyzing the loads, we find that the extreme flapwise bending moment of the blade root in chord coordinate (CMF_ROOT) is largely reduced because of the control system, with the extreme edgewise bending moment of the blade root in chord coordinate (CME_ROOT) almost unchanged. Furthermore, higher rotor speed and smaller pitch angle will generate larger extreme bending moments at the blade root

Privacy-Guarding Optimal Route Finding with Support for Semantic Search on Encrypted Graph in Cloud Computing Scenario

The arrival of cloud computing age makes data outsourcing an important and convenient application. More and more individuals and organizations outsource large amounts of graph data to the cloud computing platform (CCP) for the sake of saving cost. As the server on CCP is not completely honest and trustworthy, the outsourcing graph data are usually encrypted before they are sent to CCP. The optimal route finding on graph data is a popular operation which is frequently used in many fields. The optimal route finding with support for semantic search has stronger query capabilities, and a consumer can use similar words of graph vertices as query terms to implement optimal route finding. Due to encrypting the outsourcing graph data before they are sent to CCP, it is not easy for data customers to manipulate and further use the encrypted graph data. In this paper, we present a solution to execute privacy-guarding optimal route finding with support for semantic search on the encrypted graph in the cloud computing scenario (PORF). We designed a scheme by building secure query index to implement optimal route finding with support for semantic search based on searchable encryption idea and stemmer mechanism. We give formal security analysis for our scheme. We also analyze the efficiency of our scheme through the experimental evaluation

Preservation of Cichoric Acid Antioxidant Properties Loaded in Heat Treated Lactoferrin Nanoparticles

In the current research, a new cichoric acid (CA) encapsulation system was investigated. The optimal condition for the formation of lactoferrin-cichoric acid nanoparticles (LF-CA NPs) was determined by controlling the solution pH, the thermal treatment conditions, and the concentration of CA. Fluorescence indicated that the electrostatic force and the hydrophobic force were the main forces in the formation of LF-CA NPs. LF-CA NPs prepared under different conditions were spherical in shape with smaller particle sizes and good zeta potential demonstrating good colloidal stability. Especially, the prepared particle size of the LF-CA NPs at pH 7 and 95 °C was about 67.20 ± 1.86 nm. The circular dichroism (CD) and the Fourier transform infrared spectroscopy (FTIR) results showed that the combination of LF (lactoferrin) and CA affected the secondary structure of the LF. The differential scanning calorimetry (DSC) results indicated that the addition of CA increased the thermal stability of LF. In vitro antioxidant experiments confirmed the antioxidant capacity of LF-CA NPs was better than CA. CA was successfully encapsulated into LF NPs with high encapsulated efficiency (97.87–99.87%) by high performance liquid chromatography (HPLC). These results showed that LF could be used as the wall material of CA with excellent nature

Magnetic Fabric of Freshly Consolidated Lacustrine Mudstones Constrains the "Present-Day" Strain Field

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Chemoenzymatic synthesis of α-dystroglycan core M1 O-mannose glycans

The diversity-oriented chemoenzymatic synthesis of α-dystroglycan (α-DG) core M1 O-mannose glycans has been achieved via a three-step sequential one-pot multienzyme (OPME) glycosylation of a chemically prepared disaccharyl serine intermediate. The high flexibility and efficiency of this chemoenzymatic strategy was demonstrated for the synthesis of three more complex core M1 O-mannose glycans for the first time along with three previously reported core M1 structures