Genome-wide association with transcriptomics reveals a shade-tolerance gene network in soybean

Shade tolerance is essential for soybeans in inter/relay cropping systems.A genome-wide association study(GWAS)integrated with transcriptome sequencing was performed to identify genes and construct a genetic network governing the trait in a set of recombinant inbred lines derived from two soybean parents with contrasting shade tolerance.An improved GWAS procedure,restricted two-stage multi-locus genome-wide association study based on gene/allele sequence markers(GASM-RTM-GWAS),identified 140 genes and their alleles associated with shade-tolerance index(STI),146 with relative pith cell length(RCL),and nine with both.Annotation of these genes by biological categories allowed the construction of a protein–protein interaction network by 187 genes,of which half were differentially expressed under shading and non-shading conditions as well as at different growth stages.From the identified genes,three ones jointly identified for both traits by both GWAS and transcriptome and two genes with maximum links were chosen as beginners for entrance into the network.Altogether,both STI and RCL gene systems worked for shade-tolerance with genes interacted each other,this confirmed that shadetolerance is regulated by more than single group of interacted genes,involving multiple biological functions as a gene network.

An In-depth Interpretation of the Universal Declaration of Human Rights With the Common Values of Humanity As the Research Paradigm

Interpreting the Universal Declaration of Human Rights from political,juridical and philosophical perspectives is es-sential for promoting the guiding principles of the Declaration,build-ing consensus on human rights,and advancing human rights practice in the new historical context.To conduct an academic,systematic in-terpretation of the Declaration that conforms to the trends of the times and answers the fundamental questions of the world,it is necessary to find a new research paradigm.The common values of humanity,namely peace,development,equity,justice,democracy and freedom,put forward by Xi Jinping,general secretary of the Communist Party of China(CPC)Central Committee,provide the most explanatory and penetrating scientific paradigm for reaching the issue.This paper an-alyzes and reflects on the views,value foundation and principled(con-tractual)consensus of human rights in the Declaration,and narrates and foresees the far-reaching significance of the three global initia-tives(namely,the Global Development Initiative,the Global Security Initiative,and the Global Civilization Initiative)with the common val-ues of humanity as the soul in advancing the modernization of global human rights governance and building a new form of human rights civilization.

Exploration of the Impact Mechanism of Government Credibility Based on Variable Screening Method

Government credibility is an important asset of contemporary national governance, an important criterion for evaluating government legitimacy, and a key factor in measuring the effectiveness of government governance. In recent years, researchers’ research on government credibility has mostly focused on exploring theories and mechanisms, with little empirical research on this topic. This article intends to apply variable selection models in the field of social statistics to the issue of government credibility, in order to achieve empirical research on government credibility and explore its core influencing factors from a statistical perspective. Specifically, this article intends to use four regression-analysis-based methods and three random-forest-based methods to study the influencing factors of government credibility in various provinces in China, and compare the performance of these seven variable selection methods in different dimensions. The research results show that there are certain differences in simplicity, accuracy, and variable importance ranking among different variable selection methods, which present different importance in the study of government credibility issues. This study provides a methodological reference for variable selection models in the field of social science research, and also offers a multidimensional comparative perspective for analyzing the influencing factors of government credibility.

A Survey on the Role of Complex Networks in IoT and Brain Communication

Complex networks on the Internet of Things(IoT)and brain communication are the main focus of this paper.The benefits of complex networks may be applicable in the future research directions of 6G,photonic,IoT,brain,etc.,communication technologies.Heavy data traffic,huge capacity,minimal level of dynamic latency,etc.are some of the future requirements in 5G+and 6G communication systems.In emerging communication,technologies such as 5G+/6G-based photonic sensor communication and complex networks play an important role in improving future requirements of IoT and brain communication.In this paper,the state of the complex system considered as a complex network(the connection between the brain cells,neurons,etc.)needs measurement for analyzing the functions of the neurons during brain communication.Here,we measure the state of the complex system through observability.Using 5G+/6G-based photonic sensor nodes,finding observability influenced by the concept of contraction provides the stability of neurons.When IoT or any sensors fail to measure the state of the connectivity in the 5G+or 6G communication due to external noise and attacks,some information about the sensor nodes during the communication will be lost.Similarly,neurons considered sing the complex networks concept neuron sensors in the brain lose communication and connections.Therefore,affected sensor nodes in a contraction are equivalent to compensate for maintaining stability conditions.In this compensation,loss of observability depends on the contraction size which is a key factor for employing a complex network.To analyze the observability recovery,we can use a contraction detection algorithm with complex network properties.Our survey paper shows that contraction size will allow us to improve the performance of brain communication,stability of neurons,etc.,through the clustering coefficient considered in the contraction detection algorithm.In addition,we discuss the scalability of IoT communication using 5G+/6G-based photonic technology.

Effects of TCM Nursing Based on Syndrome Differentiation on Pulmonary Function and Quality of Life in Patients with Acute Exacerbation of COPD

[Objectives] To investigate the effects of TCM nursing based on syndrome differentiation on pulmonary function and quality of life in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). [Methods] A total of 92 patients with AECOPD who came to Nanchong Chinese Medicine Hospital from March 2022 to February 2023 were selected for the study, and the intervention group (TCM nursing based on syndrome differentiation, 46 cases) and the conventional group (basic nursing, 46 cases) were selected for the study, and the pulmonary function and quality of life of the two groups were compared. [Results] Before nursing, there was no significant difference in levels of forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and percentage of forced expiratory volume in one second to forced vital capacity (FEV1/FVC) between the intervention group and conventional group ( P >0.05). After 3 months of nursing, the levels of FVC, FEV1 and FEV1/FVC in the intervention group were higher than those in the conventional group ( P <0.05). Before nursing, there was no significant difference in the scores of health, emotion and social functions between the two groups ( P >0.05). At three months of nursing, the scores of health, emotion, and social functions in the intervention group were higher than those in the conventional group ( P <0.05). [Conclusions] The implementation of TCM nursing based on syndrome differentiation in patients with AECOPD can effectively improve the pulmonary function and quality of life of patients, and has significant clinical implementation value.

Some Problems of Warm Acupuncture in the Treatment of Knee Osteoarthritis

Knee osteoarthritis(KOA)is a chronic derivative joint issue that mainly damages the artistic cartilage and leads to pain,swelling,and stiffness around the joint,which is commomly worldwide.With the aging of society and the increment in obesity rate,the incidence of KOA increases sharply,which seriously effects the quality of human life.Before,how to take effective treatment methods is very important.Severe ways to treat the disease include non-steroidal drugs,local injections,surgery,and cell and gene therapies.However,each therapy has certain defections,such as gastrotestinal tract irritation,cardiovascular safety,or high medical costs for patients.Traditional Chinese medicine has a long history in treating KOA,reported by acupuncture,massage,internal administration of traditional Chinese medicine,and external use of traditional Chinese medicine.In clinical practice,patients can be treated from the root agreement to different etiology,and patients can be treated agreement to different syndrome types by syndrome difference to achieve effect.Studies have shown that warm acupuncture is effect in treating KOA.It has two kinds of treatment methods:acupuncture and moxibustion at the same time.It has fewer side effects and is more acceptable to patients.However,there are still some problems in the basic research and clinical application of warm acupuncture and moxibustion in treating KOA.This paper discussed the existing problems from the followingfive aspects:lack of unified synthesis difference and treatment system,problems in clinical research,weak basic research,problems in the study of moxibustion,and lack of the best treatment program recognized by the academic community.Meanwhile,the selection of acupoints,the relationship between acupuncture depth and anatomy should be further studied in order to offer research ideas for the healthy development of the treatment of KOA with warming acupuncture and moxibustion in the future.

Effect of Nursing Intervention Based on Caprini Risk Assessment Scale for Venous Thromboembolism in Perioperative Patients with Liver Cancer

Objective:To explore the effect of nursing intervention based on Caprini risk assessment scale for venous thromboembolism(VTE)in perioperative patients with liver cancer.Methods:A total of 128 hepatocellular cancer(HCC)patients who were hospitalized in our department from January 2021 to March 2022 and met the research criteria were selected.According to odd and even numbers in the order of inclusion,64 cases were divided into two groups:a control group and an observation group.The control group received routine nursing intervention during perioperative period,while the observation group received nursing intervention based on Caprini risk assessment scale for VTE.The incidence of VTE and complications were compared between the two groups.Results:The incidence of VTE and postoperative complications in the observation group were lower than those in the control group(P<0.05).Conclusion:Nursing intervention based on Caprini risk assessment scale for VTE can reduce the incidence of perioperative deep vein thrombosis and complications in patients with liver cancer;thus,it is worthy of clinical application.

Effects of Supplemental Irrigation Based on Testing Soil Moisture and Nitrogen Fertilization Amount on the Yield and Nitrogen Uptake of Winter Wheat

[Objective] This study aimed to determine the effects of supplemental irrigation on yield and nitrogen uptake in winter wheat. [Method] Three supplemental irrigation levels were set based on the target soil contents of 60%, 70% and 80%） at jointing stage of wheat. Moreover, three nitrogen levels （0, 195 and 255 kg/hm^2） were designed. The experimental plots were arranged fol owing a split-plot design. Zhoumai 18 was selected as the experimental material. [Result] Supplemental irrigation and nitrogen application in combination had significant or extremely significant effects on yield, yield components and nitrogen uptake in winter wheat. The interaction between irrigation and nitrogen fertilization had significant or extremely significant influence on the number of ears, number of grains per ear, 1 000-grain weight, grain yield and nitrogen accumulation in winter wheat. Under different combinations of supplemental irrigation and nitrogen application, the maximum yield of winter wheat was obtained at W2 N195, while the minimum at W1 N255. [Conclusion] With the increase of irrigation, negative effect of nitrogen on number of ears, number of grains per ear, 1 000-grain weight, grain yield and nitrogen accumulation decrease under lower nitrogen application rate.

A Teaching Case of Subject Clause Based on Implicit Learning

The New English curriculum criteria suggest teaching English grammar based on the students’cognitive characteristics and emotional needs,helping them discover the rules and encouraging them to master the grammar by using it.But due to the limited time in a lesson,many English teachers adopt a simple approach to teach grammar,in which students are required to memorize the rules first and then practice a lot.This approach is effec-

Urban Construction Land Suitability Evaluation Based on Improved Multi-criteria Evaluation Based on GIS(MCE-GIS): Case of New Hefei City,China

Urban construction land suitability evaluation （UCLSE） is a complex system engineering and the basis for rational use of the limited urban land resources in China. It has an important practical value on urban construction land use planning and management from the angle of methodology. As a widely used technique, traditional multi-criteria evaluation based on GIS （MCE-GIS）, is not suitable for UCLSE. This study develops an improved MCE-GIS method which could be more suitable for UCLSE based on urban complex ecological system theory and the summary of the shortcomings of traditional MCE-GIS. The improvements include three aspects： a composite evaluation index system rather than natural indexes alone, an index weight calculated by using fuzzy Analytic Hierarchy Process （AHP） method rather than the common AHP method, and the integrated overlay rule, which includes selecting the minimum value, weighted linear combination （WLC） and simple summation. The main advantage of this improved technique is that it can make UCLSE more comprehensive, more operational and more reasonable. It can provide a scientific basis for decision making in the planning and management of urban construction land use. The improved MCE-GIS system has been adopted in the New Hefei City, Anhui Province, China. Based on the results of UCLSE in New Hefei, three functional areas including construction-appropriate areas, construction-restricted areas and construction-forbidden areas could be worked out, in which 36.90% of the total study area could be developed as urban construction land and the remaining 63.10% should be protected as reserves land or as ecological land. Furthermore, the results can orovide scientific decision suooort for spatial planning and eco-environment nrotection in New Hefei.

Application of a microseismic monitoring system in deep mining

A microseismic monitoring system was used in the Donggua Shan underground copper mine, and its application was introduced. The spacial distribution of the seismic event was monitored effectively during mining with this system. The distribution of the seismic intensity in different time periods and in the different mining districts was obtained via the clustering analysis of the monitored results, and the different intensity concentration districts of seismicity were compartmentalized. The various characteristics and waveforms of different vibrations in the underground mine were revealed with the help of the micro-seismic monitoring system. It was proved that the construction and application of the micro-seismic monitoring system in the mine not only realized the continuous monitoring of seismicity in the deep mine, but also settled an this system.

Fast-armored target detection based on multi-scale representation and guided anchor

Focused on the task of fast and accurate armored target detection in ground battlefield,a detection method based on multi-scale representation network(MS-RN) and shape-fixed Guided Anchor(SF-GA)scheme is proposed.Firstly,considering the large-scale variation and camouflage of armored target,a new MS-RN integrating contextual information in battlefield environment is designed.The MS-RN extracts deep features from templates with different scales and strengthens the detection ability of small targets.Armored targets of different sizes are detected on different representation features.Secondly,aiming at the accuracy and real-time detection requirements,improved shape-fixed Guided Anchor is used on feature maps of different scales to recommend regions of interests(ROIs).Different from sliding or random anchor,the SF-GA can filter out 80% of the regions while still improving the recall.A special detection dataset for armored target,named Armored Target Dataset(ARTD),is constructed,based on which the comparable experiments with state-of-art detection methods are conducted.Experimental results show that the proposed method achieves outstanding performance in detection accuracy and efficiency,especially when small armored targets are involved.

Archimedean copula estimation of distribution algorithm based on artificial bee colony algorithm

The artificial bee colony （ABC） algorithm is a com- petitive stochastic population-based optimization algorithm. How- ever, the ABC algorithm does not use the social information and lacks the knowledge of the problem structure, which leads to in- sufficiency in both convergent speed and searching precision. Archimedean copula estimation of distribution algorithm （ACEDA） is a relatively simple, time-economic and multivariate correlated EDA. This paper proposes a novel hybrid algorithm based on the ABC algorithm and ACEDA called Archimedean copula estima- tion of distribution based on the artificial bee colony （ACABC） algorithm. The hybrid algorithm utilizes ACEDA to estimate the distribution model and then uses the information to help artificial bees to search more efficiently in the search space. Six bench- mark functions are introduced to assess the performance of the ACABC algorithm on numerical function optimization. Experimen- tal results show that the ACABC algorithm converges much faster with greater precision compared with the ABC algorithm, ACEDA and the global best （gbest）-guided ABC （GABC） algorithm in most of the experiments.

QIM digital watermarkingbased on LDPC code and messagepassingunder scalingattacks

Watermarking system based on quantization index modulation （QIM） is increasingly popular in high payload applications,but it is inherently fragile against amplitude scaling attacks.In order to resist desynchronization attacks of QIM digital watermarking,a low density parity check （LDPC） code-aided QIM watermarking algorithm is proposed,and the performance of QIM watermarking system can be improved by incorporating LDPC code with message passing estimation/detection framework.Using the theory of iterative estimation and decoding,the watermark signal is decoded by the proposed algorithm through iterative estimation of amplitude scaling parameters and decoding of watermark.The performance of the proposed algorithm is closer to the dirty paper Shannon limit than that of repetition code aided algorithm when the algorithm is attacked by the additive white Gaussian noise.For constant amplitude scaling attacks,the proposed algorithm can obtain the accurate estimation of amplitude scaling parameters.The simulation result shows that the algorithm can obtain similar performance compared to the algorithm without desynchronization.

Post-processing Free Quantum Random Number Generator Based on Avalanche Photodiode Array

Quantum random number generators adopting single negligible dead time of avalanche photodiodes （APDs） photon detection have been restricted due to the non- We propose a new approach based on an APD array to improve the generation rate of random numbers significantly. This method compares the detectors＇ responses to consecutive optical pulses and generates the random sequence. We implement a demonstration experiment to show its simplicity, compactness and scalability. The generated numbers are proved to be unbiased, post-processing free, ready to use, and their randomness is verified by using the national institute of standard technology statistical test suite. The random bit generation efficiency is as high as 32.8% and the potential generation rate adopting the 32× 32 APD array is up to tens of Gbits/s.

New Dynamic Algorithm for IRFPA Bad Pixel Detection and Compensation Based on Statistics

Based on the analysis to the behavior of bad pixels, a statistics-based auto-detecting and compensation algorithm for bad pixels is proposed. The correcting process is divided into two stages： bad pixel detection and bad pixel compensation. The proposed detection algorithm is a combination of median filtering and statistic method. Single frame median filtering is used to locate approximate map, then statistic method and threshold value is used to get the accurate location map of bad pixels. When the bad pixel detection is done, neighboring pixel replacement algorithm is used to compensate them in real-time. The effectiveness of this approach is test- ed by applying it to I-IgCATe infrared video. Experiments on real infrared imaging sequences demonstrate that the proposed algorithm requires only a few frames to obtain high quality corrections. It is easy to combine with traditional static methods, update the pre-defined location map in real-time.

Improved MOEA/D for Dynamic Weapon-Target Assignment Problem

Conducting reasonable weapon-target assignment( WTA) with near real time can bring the maximum awards with minimum costs which are especially significant in the modern war. A framework of dynamic WTA( DWTA) model based on a series of staged static WTA( SWTA) models is established where dynamic factors including time window of target and time window of weapon are considered in the staged SWTA model. Then,a hybrid algorithm for the staged SWTA named Decomposition-Based Dynamic Weapon-target Assignment( DDWTA) is proposed which is based on the framework of multi-objective evolutionary algorithm based on decomposition( MOEA / D) with two major improvements: one is the coding based on constraint of resource to generate the feasible solutions, and the other is the tabu search strategy to speed up the convergence.Comparative experiments prove that the proposed algorithm is capable of obtaining a well-converged and well diversified set of solutions on a problem instance and meets the time demand in the battlefield environment.

MICROSTRUCTURES AND MECHANICAL PROPERTIES OF β-NiA1CONTAINING α-Fe PRECIPITATES

The microstructures of B2-ordered NiA1 containing α-Fe precipitates have been investigated in terms of transmission electron microscopy. Fine precipitation of α-Fe (bcc structure) occurs in NiA1 by aging around 973K. The aging behavior was investigated by microhandness measurements and the temperature dependence of the yield strength of precipitate- comaining B2- ordered NiA1 was investigated by compression tests over the temperature range of 673-1273K. The fine precipitation of α-Fe was found to enhance greatly the low and intermediate temperature yield strength. When the deformation temperature is over 1073K, the strength of precipitate- containing NiA1 was comparable to ternary solid solution hardening NiA1-Fe. Dislocations bypass the particles during deformation and typical Orowan loops were observed surrounding the or-Fe particles after deformation.

Specific Emitter Identification Based on Visibility Graph Entropy

The specific emitter identification （SEI） technique some external feature measurements of the signal. determines the unique emitter of a given signal by using It has recently attracted a great deal of attention because many applications can benefit from it. This work addresses the SEI problem using two methods, namely, the normalized visibility graph entropy （NVGE） and the normalized horizontal visibility graph entropy （NHVGE） based on treating emitters as nonlinear dynamical systems. Firstly, the visibility graph （VG） and the horizontal visibility graph （HVG） are used to convert the instantaneous amplitude, phase and frequency of received signals into graphs. Then, based on the information captured by the VG and the HVG, the normalized Shannon entropy （NSE） calculated from the corresponding degree distributions are utilized as the rf fingerprint. Finally, four emitters from the same manufacturer are utilized to evaluate the performance of the two methods. Experimental results demonstrate that both the NHVGE-based method and NVGE-based method are quite effective and they perform much better than the method based on the normalized permutation entropy （NPE） in the case of a small amount of data. The NVGE-based method performs better than the NHVGE-based method since the VG can extract more information than the HVG does. Moreover, our methods do not distinguish between the transient signal and the steady-state signal, making it practical.

Design and Strategy of Series-Parallel Hybrid System Based on BSFC

In this paper,a drive control strategy is developed based on the characteristics of series-parallel plug-in hybrid system.Energy management strategies in various modes are established with the basis on the minimum brake specific fuel consumption(BSFC)curve of engine.The control strategy,which is based on rules and system efficiency,is adopted to determine the entry/exit mechanisms of various modes according to battery state of charge(SOC),required power and required speed.The vehicle test results verify that the proposed control strategy can improve vehicle economy efficiently and makes a good effect on engine control.