OsNCED5 confers cold stress tolerance through regulating ROS homeostasis in rice.

Cold stress is one of the most serious abiotic stresses that affects the growth and yield in rice. However, the molecular mechanism by which abscisic acid (ABA) regulates plant cold stress tolerance is not yet clear. In this study, we identified a member of the OsNCED (9-cis-epoxycarotenoid dioxygenase) gene family, OsNCED5, which confers cold stress tolerance in rice.

A generative adversarial network for multiple reads reconstruction in DNA storage.

DNA storage is widely considered as a promising solution to the data explosion problem. However, the synthesis, PCR and sequencing processes usually result in erroneous reads involving base insertions, deletions, and substitutions. Specially this situation is even more serious in the 3rd generation of sequencing technologies.

Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T solar systems.

Optimization of thermophysical properties (TPPs) of MXene-based nanofluids is essential to increase the performance of hybrid solar photovoltaic and thermal (PV/T) systems. This study proposes a hybrid approach to optimize the TPPs of MXene-based Ionanofluids. The input variables are the MXene mass fraction (MF) and temperature.

CYP4BN4v7 regulates the population density dependent oocyte maturity rate in bean beetles.

The bean beetle (Callosobruchus maculatus) clearly exhibits population density-dependent polymorphism. Cytochrome P450 (CYP) is involved in many aspects of the physiological activities of insects. However, the role of CYP in population density-dependent polymorphisms remains unknown.

An ABA biosynthesis enzyme gene OsNCED4 regulates NaCl and cold stress tolerance in rice.

Rice (Oryza sativa L.) is susceptible to various abiotic stresses, such as salt, cold, and drought. Therefore, there is an urgent need to explore the relevant genes that enhance tolerance to these stresses.

Piezoelectric Ultrasonic Local Resonant Ultra-Precision Grinding for Hard-Brittle Materials.

Hard-brittle materials are widely used in the optics, electronics, and aviation industries, but their high hardness and brittleness make it challenging for traditional processing methods to achieve high efficiency and superior surface quality. This study aims to investigate the application of ultrasonic local resonant grinding to sapphire to improve the efficiency and meet the requirements for the optical window in the surface roughness of the material. The resonant frequency of a piezoelectric ultrasonic vibration system and the vibration amplitude of a grinding head's working face were simulated and tested, respectively.

A novel embedded kernel CNN-PCFF algorithm for breast cancer pathological image classification.

Early screening of breast cancer through image recognition technology can significantly increase the survival rate of patients. Therefore, breast cancer pathological image is of great significance for medical diagnosis and clinical research. In recent years, numerous deep learning models have been applied to breast cancer image classification, with deep CNN being a typical representative.

Assessing key parameters in simultaneous simulation of rapid kinetics of chlorophyll a fluorescence and trans-thylakoid electric potential difference.

Our study attempts to address the following questions: among numerous photosynthetic modules, which parameters notably influence the rapid chlorophyll fluorescence (ChlF) rise, the so-called O-J-I-P transient, in conjunction with the P515 signal, as these two records are easily obtained and widely used in photosynthesis research, and how are these parameters ranked in terms of their importance? These questions might be difficult to answer solely through experimental assays. Therefore, we employed an established photosynthesis model. Firstly, we utilized the model to simulate the measured rapid ChlF rise and P515 kinetics simultaneously.

Impact of urban-rural development and its industrial elements on regional economic growth: An analysis based on provincial panel data in China.

Urban-rural development is an important driving force for regional economic growth. The existing researches have studied this issue from various perspectives, but they ignore the impact of big data on the economy. In the post pandemic era, big data, as an emerging production factor, has a significant indicative effect in promoting urban-rural economic recovery and fostering new business forms.

Long-lasting anti-corrosion direct-to-metal polyurethane NP-GLIDE coatings based on the coordination effect and dual cross-linking of polyphenol.

Aluminum and its alloys have been widely used in our lives. However, Aluminum and its alloys is prone to corrosion, especially in harsh environment. In recent years, hydrophobic coatings were used in the corrosion protection of metal.

A Deniable Encryption Method for Modulation-Based DNA Storage.

Recent advancements in synthesis and sequencing techniques have made deoxyribonucleic acid (DNA) a promising alternative for next-generation digital storage. As it approaches practical application, ensuring the security of DNA-stored information has become a critical problem. Deniable encryption allows the decryption of different information from the same ciphertext, ensuring that the "plausible" fake information can be provided when users are coerced to reveal the real information.

Multimodal multi-objective optimization algorithm based on hierarchical environment selection strategy.

The article proposes an optimization algorithm using a hierarchical environment selection strategyto solve the deficiencies of current multimodal multi-objective optimization algorithms in obtaining the completeness and convergence of Pareto optimal Sets (PSs). Firstly, the algorithm in this article is framed by a differential evolutionary algorithm (DE) and uses a special crowding distance to design a neighborhood-based individual variation strategy, which also ensures the diversity, and then special crowding distance is used to help populations with non-dominated sorting. In the stage of environmental selection, a strategy of hierarchical selection of individuals was designed, which selects sorted non-dominant ranked individual layer by layer according to the ratio, which allows potential individuals tobe explored.

An optimization algorithm for maximum quasi-clique problem based on information feedback model.

The maximum clique problem in graph theory is a well-known challenge that involves identifying the complete subgraph with the highest number of nodes in a given graph, which is a problem that is hard for nondeterministic polynomial time (NP-hard problem). While finding the exact application of the maximum clique problem in the real world is difficult, the relaxed clique model quasi-clique has emerged and is widely applied in fields such as bioinformatics and social network analysis. This study focuses on the maximum quasi-clique problem and introduces two algorithms, NF1 and NR1.

Two-stage multi-objective evolutionary algorithm for overlapping community discovery.

As one of the essential topological structures in complex networks, community structure has significant theoretical and application value and has attracted the attention of researchers in many fields. In a social network, individuals may belong to different communities simultaneously, such as a workgroup and a hobby group. Therefore, overlapping community discovery can help us understand and model the network structure of these multiple relationships more accurately.

Structural Characteristics of the Yunnan Deashed Lignite and Construction of the Macromolecular Structure Model.

The structural characteristics and macromolecular model of lignite are important for its effective utilization. In this paper, Yunnan (YN) lignite was taken as the study object, and deashing pretreatment was carried out to remove the influence of minerals in lignite before spectroscopic analysis. Fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and C nuclear magnetic resonance (NMR) spectroscopy of deashed lignite and gas chromatography and mass spectrometry (GC/MS) of methanol lignite extract were subsequently performed.

Physical activity and mental health trends in Korean adolescents: Analyzing the impact of the COVID-19 pandemic from 2018 to 2022.

Objective: Mental health significantly affects the physical and emotional development of adolescents. The aim of the current study was to examine how physical activity (PA) and mental health among Korean adolescents changed before and after the start of the COVID-19 pandemic.

Methods: We used comparative cross-sectional methods, gathering information from the Korea Disease Control and Prevention Agency databases and conducting Chi-square testing and correlation analysis for evaluation.

Screening rate constants in the simulation of rapid kinetics of chlorophyll fluorescence using the Morris method.

Chlorophyll fluorescence, a sensitive and cost-effective probe, is widely used in photosynthetic research. Its rapid phase, occurring within 1 second under intense illumination, displays complex O-J-I-P transients, providing valuable insights into various aspects of photosynthesis. In addition to employing experimental approaches to measure the rapid Fluorescence Induction (FI) kinetics, mathematical modeling serves as a crucial tool for understanding the underlying mechanisms that drive FI dynamics.

Hypothalamic transcriptome profile from laying period to incubation period of Changshun green-shell laying hens.

Incubation behavior in chickens is closely associated with hypothalamus. Here, RNA sequencing of hypothalamus from Changshun green-shell laying hens, an indigenous chicken breed from China, in egg-laying period (LP) and incubation period (BP) was conducted to identify critical pathways and candidate genes involved in controlling the incubation behavior in hypothalamus. A total of 637 up-regulated and 305 down-regulated differently expressed genes (DEGs) were identified in chicken hypothalamus between LP and BP groups.

Enhanced full-seawater splitting with a CoNiP@N,P-C core-shell electrocatalyst.

This study investigated a novel electrocatalyst with a core-shell structure of CoNiP@N,P-C. The unique carbon shell of this catalyst serves a dual purpose: exposing numerous active sites and safeguarding CoNiP nanoparticles from dissolution caused by the electrolyte. As a result, the CoNiP@N,P-C nanoparticles exhibit exceptional electrochemical properties.

Optimizing low-power task scheduling for multiple users and servers in mobile edge computing by the MUMS framework.

In today's increasingly popular Internet of Things (IoT) technology, its energy consumption issue is also becoming increasingly prominent. Currently, the application of Mobile Edge Computing (MEC) in IoT is becoming increasingly important, and scheduling its tasks to save energy is imperative. To address the aforementioned issues, we propose a Multi-User Multi-Server (MUMS) scheduling framework aimed at reducing the energy consumption in MEC.

Partial Alleviation of Homologous Superinfection Exclusion of SeMNPV Latently Infected Cells by G1 Phase Infection and G2/M Phase Arrest.

Viral infection can regulate the cell cycle, thereby promoting viral replication. Hijacking and altering the cell cycle are important for the virus to establish and maintain a latent infection. Previously, Spodoptera exigua multiple nucleopolyhedrovirus (SeMNPV)-latently infected P8-Se301-C1 cells, which grew more slowly than Se301 cells and interfered with homologous SeMNNPV superinfection, were established.

A framework of evolutionary optimized convolutional neural network for classification of shang and chow dynasties bronze decorative patterns.

As a UNESCO World Cultural Heritage, the aesthetic value of bronze artifacts from the Shang and Chow Dynasties has had a profound influence on Chinese traditional culture and art. To facilitate the digital preservation and protection of these Shang and Chow bronze artifacts (SCB), it becomes imperative to categorize their decorative patterns. Therefore, a SCB pattern classification method of differential evolution called Shang and Chow Bronze Convolutional Neural Network (SCB-CNN) is proposed.