Response of Bacterial Metabolic Activity to the River Discharge in the Pearl River Estuary: Implication for CO2 Degassing Fluxes

Bacterial production (BP), respiration (BR) and growth efficiency (BGE) were simultaneously determined along an environmental gradient in the Pearl River Estuary (PRE) in the wet season (May 2015) and the dry season (January 2016), in order to examine bacterial responses to the riverine dissolved organic carbon (DOC) in the PRE. The Pearl River discharge delivered labile dissolved organic matters (DOM) with low DOC:DON ratio, resulting in a clear gradient in DOC concentrations and DOC:DON ratios. BP (3.93–144 μg C L−1 d−1) was more variable than BR (64.6–567 μg C L−1 d−1) in terms of the percentage, along an environmental gradient in the PRE. In response to riverine DOC input, BP and the cell-specific BP increased; in contrast, the cell-specific bacterial respiration declined, likely because labile riverine DOC mitigated energetic cost for cell maintenance. Consequently, an increase in bacterial respiration was less than expected. Our findings implied that the input of highly bioavailable riverine DOC altered the carbon portioning between anabolic and catabolic pathways, consequently decreasing the fraction of DOC that bacterioplankton utilized for bacterial respiration. This might be one of the underlying mechanisms for the low CO2 degassing in the PRE receiving large amounts of sewage DOC

Beyond Volume Pattern: Storage-Efficient Boolean Searchable Symmetric Encryption with Suppressed Leakage

Boolean Searchable Symmetric Encryption (BSSE) enables users to perform retrieval operations on the encrypted data while sup- porting complex query capabilities. This paper focuses on addressing the storage overhead and privacy concerns associated with existing BSSE schemes. While Patel et al. (ASIACRYPT’21) and Bag et al. (PETS’23) introduced BSSE schemes that conceal the number of single keyword re- sults, both of them suffer from quadratic storage overhead and neglect the privacy of search and access patterns. Consequently, an open ques- tion arises: Can we design a storage-efficient Boolean query scheme that effectively suppresses leakage, covering not only the volume pattern for singleton keywords, but also search and access patterns? In light of the limitations of existing schemes in terms of storage over- head and privacy protection, this work presents a novel solution called SESAME. It realizes efficient storage and privacy preserving based on Bloom filter and functional encryption. Moreover, we propose an en- hanced version, SESAME+, which offers improved search performance. By rigorous security analysis on the leakage functions of our schemes, we provide a formal security proof. Finally, we implement our schemes and demonstrate that SESAME+ achieves superior search efficiency and reduced storage overhead

Audiovisual n-Back Training Alters the Neural Processes of Working Memory and Audiovisual Integration: Evidence of Changes in ERPs

(1) Background: This study investigates whether audiovisual n-back training leads to training effects on working memory and transfer effects on perceptual processing. (2) Methods: Before and after training, the participants were tested using the audiovisual n-back task (1-, 2-, or 3-back), to detect training effects, and the audiovisual discrimination task, to detect transfer effects. (3) Results: For the training effect, the behavioral results show that training leads to greater accuracy and faster response times. Stronger training gains in accuracy and response time using 3- and 2-back tasks, compared to 1-back, were observed in the training group. Event-related potentials (ERPs) data revealed an enhancement of P300 in the frontal and central regions across all working memory levels after training. Training also led to the enhancement of N200 in the central region in the 3-back condition. For the transfer effect, greater audiovisual integration in the frontal and central regions during the post-test rather than pre-test was observed at an early stage (80-120 ms) in the training group. (4) Conclusion: Our findings provide evidence that audiovisual n-back training enhances neural processes underlying a working memory and demonstrate a positive influence of higher cognitive functions on lower cognitive functions

Dynamic model for piezotronic and piezo-phototronic devices under low and high frequency external compressive stresses (Featured)

In this work, we aim to establish a theoretical method for modelling the dynamic characteristics of piezotronics and piezo-phototronic devices. By taking the simplest piezotronic device, PN junction as an example, we combine the small signal model and the unified approach to investigate its diffusion capacitance and conductance when it is under both low and high frequency external compressive stresses. This approach is different from the traditional considerations that treat the piezopotential as a static value. Furthermore, we expand the theory into piezo-phototronic devices, e.g., a light emitting diode. The dynamic recombination rate and light emitting intensity are quantitatively calculated under different frequencies of external compressive stresses

PyPose v0.6: The Imperative Programming Interface for Robotics

PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has been used in many tasks due to its meticulously designed application programming interface (API) and efficient implementation. From its initial launch in early 2022, PyPose has experienced significant enhancements, incorporating a wide variety of new features into its platform. To satisfy the growing demand for understanding and utilizing the library and reduce the learning curve of new users, we present the fundamental design principle of the imperative programming interface, and showcase the flexible usage of diverse functionalities and modules using an extremely simple Dubins car example. We also demonstrate that the PyPose can be easily used to navigate a real quadruped robot with a few lines of code

Safety and Immunogenicity of H5N1 Influenza Vaccine Based on Baculovirus Surface Display System of Bombyx mori

Avian influenza virus (H5N1) has caused serious infections in human beings. This virus has the potential to emerge as a pandemic threat in humans. Effective vaccines against H5N1 virus are needed. A recombinant Bombyx mori baculovirus, Bmg64HA, was constructed for the expression of HA protein of H5N1 influenza virus displaying on the viral envelope surface. The HA protein accounted for approximately 3% of the total viral proteins in silkworm pupae infected with the recombinant virus. Using a series of separation and purification methods, pure Bmgp64HA virus was isolated from these silkworm pupae bioreactors. Aluminum hydroxide adjuvant was used for an H5N1 influenza vaccine. Immunization with this vaccine at doses of 2 mg/kg and 0.67 mg/kg was carried out to induce the production of neutralizing antibodies, which protected monkeys against influenza virus infection. At these doses, the vaccine induced 1:40 antibody titers in 50% and 67% of the monkeys, respectively. The results of safety evaluation indicated that the vaccine did not cause any toxicity at the dosage as large as 3.2 mg/kg in cynomolgus monkeys and 1.6 mg/kg in mice. The results of dose safety evaluation of vaccine indicated that the safe dose of the vaccine were higher than 0.375 mg/kg in rats and 3.2 mg/kg in cynomolgus monkeys. Our work showed the vaccine may be a candidate for a highly effective, cheap, and safe influenza vaccine for use in humans

Decidability of the Equivalence of Multi-Letter Quantum Finite Automata

Multi-letter quantum finite automata (QFAs) were a new one-way QFA model proposed recently by Belovs, Rosmanis, and Smotrovs (LNCS, Vol. 4588, Springer, Berlin, 2007, pp. 60-71), and they showed that multi-letter QFAs can accept with no error some regular languages ((a + b) ∗ b) that are unacceptable by the one-way QFAs. In this paper, we study the decidability of the equivalence of multi-letter QFAs, and the main technical contributions are as follows: (1) We show that any two k1-letter QFA A1 and k2-letter QFA A2 over the same input alphabet Σ are equivalent if and only if they are (n 2 m k−1 − m k−1 + k)-equivalent, where m = |Σ | is the cardinality of Σ, k = max(k1, k2), and n = n1 + n2, with n1 and n2 being the numbers of states of A1 and A2, respectively. When k = 1, we obtain the decidability of equivalence of measure-once QFAs in the literature. (2) However, if we determine the equivalence of multi-letter QFAs by checking all strings of length not more than n 2 m k−1 − m k−1 + k, then the worst time complexity is exponential, i.e., O(n 4 m n2 m k−1 −m k−1 +k). Therefore, we design a polynomial-time O(m 2k n 8 + km k n 6) algorithm for determining the equivalence of any two multi-letter QFAs. Here, the time complexity is concerning the number of states in the multi-letter QFAs, and k is thought of as a constant