Numerical‐discrete‐scheme‐incorporated recurrent neural network for tasks in natural language processing

A variety of neural networks have been presented to deal with issues in deep learning in the last decades.Despite the prominent success achieved by the neural network,it still lacks theoretical guidance to design an efficient neural network model,and verifying the performance of a model needs excessive resources.Previous research studies have demonstrated that many existing models can be regarded as different numerical discretizations of differential equations.This connection sheds light on designing an effective recurrent neural network(RNN)by resorting to numerical analysis.Simple RNN is regarded as a discretisation of the forward Euler scheme.Considering the limited solution accuracy of the forward Euler methods,a Taylor‐type discrete scheme is presented with lower truncation error and a Taylor‐type RNN(T‐RNN)is designed with its guidance.Extensive experiments are conducted to evaluate its performance on statistical language models and emotion analysis tasks.The noticeable gains obtained by T‐RNN present its superiority and the feasibility of designing the neural network model using numerical methods.

A Range-Based Node Localization Scheme for UWASNs Considering Noises and Aided With Neurodynamics Model

Dear Editor,This letter focuses on the node localization problem in underwater acoustic sensor networks(UWASNs) with the time-dependent property and various noise disturbances. A range-based localization scheme aided with an integral-feedback-based neurodynamics(IND)model is proposed and referred to as IND-RS, which has the stability against the internal perturbations encountered during the solving process.

A zeroing neurodynamics‐based location method for nodes in underwater acoustic sensor network

Zeroing neurodynamics methodology,which dedicates to finding equilibrium points of equations,has been proven to be a powerful tool in the online solving of problems with considerable complexity.In this paper,a method for underwater acoustic sensor network(UASN)localisation is proposed based on zeroing neurodynamics methodology to preferably locate moving underwater nodes.A zeroing neurodynamics model specifically designed for UASN localisation is constructed with rigorous theoretical analyses of its effectiveness.The proposed zeroing neurodynamics model is compatible with some localisation algorithms,which can be utilised to eliminate error in non‐ideal situations,thus further improving its effectiveness.Finally,the effectiveness and compatibility of the proposed zeroing neurodynamics model are substantiated by examples and computer simulations.

Volatiles from <i>Prunus persica</i>Flowers and Their Correlation with Flower-Visiting Insect Community in Wanbailin Ecological Garden, China

Object: To investigate the VOCs from living Prunus persica flowers of different branches and their correlation with floral insects. Special, dominant and 20 VOCs were analysed from living Prunus persica flowers captured by closely and circularly headspace way in adsorbent tubes and ATD-GC/MS on 29 April in Wanbailin Ecological Garden, China. VOCs from high altitude tree are more than low altitude in sunny site, and floral volatile constituents from upslope branches are less than downslope of the same tree on high altitude. Special floral VOCs were alpha-dimethyl-benzenemethanol, isopropyl palmitate, ethylbenzene, p-xylene, acetophenone, 3-ethyl-2-methyl-Heptane on sunny slope, and propylene glycol, decanal, hexadecane on shady slope. Dominant VOCs founded during 8 temporal quanta were toluene, hexane, 2-ethyl-1-hexanol, dodecane, pentadecane. Floral VOCs’ number from sunny slope was significantly negative correlated with flower-visiting insect community richness, abundance, diversity on sunny or shady slope, which from shady slope was significantly positive correlated with flower-visiting insect community parameters on both slopes tried dividing insects visiting floral branches from Prunus persica in sunny site with n/2 + 1 or n/2 - 1, and shady site with n/2 before sampled volatiles day. On sampled volatiles day, 2-ethyl-1-hexanol from sunny slope was significantly positive correlated with flower-visiting insect community parameters on shady slope (P Prunus persica on sunny slope, and even floral branches kept on shady slope.

Encryption Algorithm Based NTRU in Underwater Acoustic Networks

Underwater acoustic networks (UANs) adopt acoustic communication. The opening and sharing features of underwater acoustic channel make communication in UANs vulnerable to eavesdropping and interfering. The applications of UANs such as underwater military, underwater warning and energy development are very demanding for the security level. Quantum computing poses a threat to security of the traditional public key cryptosystem such as large integer factorization and discrete logarithm. To solve these problems, a public key encryption algorithm is proposed based on number theory research unit (NTRU) for underwater acoustic networks. The traditional NTRU encryption scheme was improved and a new public key cryptosystem was provided. The algorithm combined the encryption algorithm with the identity of the node. Experimental results show that the key generation speed is very fast, and the speed of encryption and decryption is faster than RSA, ECC, ElGamal and other public key cryptosystems. It verifies that the encryption algorithm can resist quantum computing attacks.

SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice

Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.

Improved symptoms following bumetanide treatment in children aged 3-6 years with autism spectrum disorder:a randomized,double-blind,placebo-controlled trial

With the current limited drug therapy for the core symptoms of autism spectrum disorder(ASD),we herein report a randomized,double-blind,placebo-controlled trial to investigate the efficacy,safety,and potential neural mechanism of bumetanide in children with ASD aged 3-6 years old.A total of 120 children were enrolled into the study and randomly assigned to either 0.5 mg bumetanide or placebo.In the final sample,119 children received at least one dose of bumetanide(59 children) or placebo(60 children) were included in the final analysis.The primary outcome was a reduction in the Childhood Autism Rating Scale(CARS) score,and the secondary outcomes were the Clinical Global Impressions Scale(CGI)-Global Improvement(CGI-I) score at 3 months and the change from baseline to 3-month in the Autism Diagnostic Observation Schedule(ADOS).Magnetic resonance spectroscopy(MRS) was used to measure y-aminobutyric acid(GABA) and glutamate neurotransmitter concentrations in the insular cortex(IC) before and after the treatment.As compared with the placebo,bumetanide treatment was significantly better in reducing the severity.No patient withdrew from the trial due to adverse events.The superiority of bumetanide to placebo in reducing insular GABA,measured using MRS,was demonstrated.The clinical improvement was associated with a decrease in insular GABA in the bumetanide group.In conclusion,this trial in a large group of young children with predominantly moderate and severe ASD demonstrated that bumetanide is safe and effective in improving the core symptoms of ASD.However,the clinical significance remains uncertain,and future multi-center clinical trials are required to replicate these findings and confirm the clinical significance using a variety of outcome measures.

New Lattice-Based Digital Multi-signature Scheme

The traditional digital multi-signature schemes are mostly based on large integer factorization and the discrete logarithm,which cannot be secured in quantum environment.The paper presents a lattice-based multi-signature scheme that can resist the quantum attack using the hardness of average-case short integer solution problem(SIS).Multi-signature includes the simultaneous signature and sequential signature.The paper describes respectively the key generation,multi-signature generation and multi-signature verification of the two types of schemes.Moreover,experimental results prove that the digital multi-signature scheme based on lattice is especially efficient and secure to multi-signature generation.