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Private set intersection (PSI) is a hot topic in cryptography and has a wide range of applications such as privacy preserving personal properties matching and data mining. Many PSI protocols have been presented, which discussed the efficiency and formal security. However, there are few PSI protocols for the cloud computing environments, where the cloud server offers effective computations and storage capabilities to clients and performs the PSI computations for clients. In this paper, we propose an efficient PSI protocol for the cloud computing environments, which is based on homomorphic encryption, pseudorandom function, set polynomial representation, and point-value form of polynomials. Our PSI protocol enjoys the following advantages: (a) our protocol gives a natural secure data storage; (b) normal channels are suitable to our protocol; (c) the communication and computation complexity are linear to the dataset size; (d) our protocol provides a formal detailed simulated-based security proof; (e) our protocol is a scalable protocol that could be extended to multiple clients conveniently, and a formal simulated-based security proof is provided in details.

Introduction: Alzheimer’s disease (AD), which is characterized by abnormal deposition of amyloid-β (Aβ) plaques and impaired neurogenesis and cognition, still lacks an optimally effective therapeutic agent for its management, and mounting evidence has shown that inflammatory processes are implicated in AD. Sophocarpine has been reported to exert inflammation-regulating effects in various diseases. However, whether sophocarpine can exert anti-neuroinflammatory and neuroprotective effects in AD remains unclear. This study investigated whether sophocarpine could ameliorate the pathological features and potential mechanisms in a mouse AD model. Methods: APP/PS1 mice were treated with sophocarpine for 8 weeks. We quantified the effects of sophocarpine treatment on cognitive performance using a behavioral test. Brain Aβ deposits and neurogenesis were evaluated using immunofluorescence staining. We also assessed the morphology and inflammatory changes induced by sophocarpine administration and its expression in the hippocampus. Results: Administration of sophocarpine significantly alleviated cognitive impairment and reduced neural loss. APP/PS1 mice treated with sophocarpine showed reduced Aβ plaque deposits and enhanced neurogenesis. Sophocarpine markedly decreased the expression of inflammation markers and inhibited microglial activation. Conclusions: Sophocarpine could potentially alleviate cognitive impairment and brain damage in APP/PS1 mice with its neuroprotective effects via modulation of the inflammatory pathway.

The low-voltage distribution network field wiring is very complicated and there are many changes in the relationship between households and changes, which brings great difficulties to the topology identification and line loss management of the transformer area. This paper proposed an intelligence low-voltage power system based on edge computing in order to improve the automation level of low-voltage distribution area, and to solve problems such as identification inaccuracy of topological relations in the low-voltage distribution area at present and singleness of condition monitoring parameters in station area, etc. The terminal is implanted with two edge calculation models based on artificial intelligence technology, which can realize topology identification and state parameters monitoring. The multistate parameter monitoring and decision analysis provides functions of event monitoring and early warning of abnormal state for the low voltage distribution system. In the topology identification analysis, the Markov random field was applied to establish the mathematical model of non-oriented graph and the joint probability distribution to describe the correlation between the nodes in the distribution network, thus realizing topology-relation identification of nodes in respective layers of the distribution area. On this basis, taking a low-voltage station as an example, a case analysis was undertaken. It was verified via the effectiveness and accuracy of the intelligence low-voltage station, which lays a foundation for research of the intelligent and fine management of the low voltage station system.

Alzheimer's disease (AD) is the most common neurodegenerative disorder causing dementia worldwide, and is mainly characterized by aggregated β-amyloid (Aβ). Increasing evidence has shown that plant extracts have the potential to delay AD development. The plant sterol β-Sitosterol has a potential role in inhibiting the production of platelet Aβ, suggesting that it may be useful for AD prevention. In the present study, we aimed to investigate the effect and mechanism of β-Sitosterol on deficits in learning and memory in amyloid protein precursor/presenilin 1 (APP/PS1) double transgenic mice. APP/PS1 mice were treated with β-Sitosterol for four weeks, from the age of seven months. Brain Aβ metabolism was evaluated using ELISA and Western blotting. We found that β-Sitosterol treatment can improve spatial learning and recognition memory ability, and reduce plaque load in APP/PS1 mice. β-Sitosterol treatment helped reverse dendritic spine loss in APP/PS1 mice and reversed the decreased hippocampal neuron miniature excitatory postsynaptic current frequency. Our research helps to explain and support the neuroprotective effect of β-Sitosterol, which may offer a novel pharmaceutical agent for the treatment of AD. Taken together, these findings suggest that β-Sitosterol ameliorates memory and learning impairment in APP/PS1 mice and possibly decreases Aβ deposition.

Antibiotics are commonly used in swine feed to treat and prevent disease, as well as to promote growth. Antibiotics released into the environment via wastewater could accelerate the emergence of antibiotic-resistant bacteria and resistance genes in the surrounding environment. In this study, we quantified the occurrence of sulfonamides, sulfonamide-resistant microorganisms and resistance genes in the wastewater from a swine farm in northern Taiwan and its surrounding natural water bodies and soils. Sulfonamide levels were similar in the receiving downstream and upstream river water. However, the prevalence of sulfonamide-resistant bacteria and resistance genes, as analyzed by cultivation-dependent and -independent molecular approaches, was significantly greater in the downstream compared to the upstream river water samples. Barcoded-pyrosequencing revealed a highly diverse bacterial community structure in each sample. However, the sequence identity of the sulfonamide resistance gene sul1 in the wastewater and downstream environment samples was nearly identical (99–100%). The sul1 gene, which is genetically linked to class 1 integrons, was dominant in the downstream water bodies and soils. In conclusion, the increased prevalence of sulfonamide resistance genes in the wastewater from a swine farm, independent of the persistent presence of sulfonamides, could be a potential source of resistant gene pools in the surrounding environment.