Variation of soil physical-chemical characteristics in salt-affected soil in the Qarhan Salt Lake,Qaidam Basin

Soil salinization has adverse effects on the soil physical-chemical characteristics.However,little is known about the changes in soil salt ion concentrations and other soil physical-chemical characteristics within the Qarhan Salt Lake and at different soil depths in the surrounding areas.Here,we selected five sampling sites(S1,S2,S3,S4,and S5)alongside the Qarhan Salt Lake and in the Xidatan segment of the Kunlun Mountains to investigate the relationship among soil salt ion concentrations,soil physical-chemical characteristics,and environmental variables in April 2019.The results indicated that most sites had strongly saline and very strongly saline conditions.The main salt ions present in the soil were Na^(+),K^(+),and Cl^(-).Soil nutrients and soil microbial biomass(SMB)were significantly affected by the salinity(P<0.05).Moreover,soil salt ions(Na^(+),K^(+),Ca2+,Mg^(2+),Cl^(-),CO_(3)^(2-),SO_(4)^(2-),and HCO_(3)^(-))were positively correlated with electrical conductivity(EC)and soil water content(SWC),but negatively related to altitude and soil depth.Unlike soil salt ions,soil nutrients and SMB were positively correlated with altitude,but negatively related to EC and SWC.Moreover,soil nutrients and SMB were negatively correlated with soil salt ions.In conclusion,soil nutrients and SMB were mainly influenced by salinity,and were related to altitude,soil depth,and SWC in the areas from the Qarhan Salt Lake to the Xidatan segment.These results imply that the soil quality(mainly evaluated by soil physical-chemical characteristics)is mainly influenced by soil salt ions in the areas surrounding the Qarhan Salt Lake.Our results provide an accurate prediction of how the soil salt ions,soil nutrients,and SMB respond to the changes along a salt gradient.The underlying mechanisms controlling the soil salt ion distribution,soil nutrients,and SMB in an extremely arid desert climate playa should be studied in greater detail in the future.

Contribution to Comparative Study of Physical-Chemical Characteristics of Diack Basalt and Bandia Limestone for Use in Railway Engineering

This paper presents a comparative study of Physical-Chemical characteristics of Limestone and Basalt (from Senegalese quarries). First, chemical tests show that Basalt is richer in silica 51.59% versus 2.84% for Limestone. Basalt is made up of silica minerals and essentially carbonated minerals with a CaO percentage of 50.05%. Chemical results also show that Basalt is richer in iron 12.71% versus 0.44% for Limestone. Finally, they revealed a fire loss of 40.91% for Limestone and 2.44% for Basalt. Second, physical analysis results show that Diack Basalt has the best characteristics with a flattening coefficient of 5% between 5% and 20%;the percentage of pollutants is 0.36% less than 1%;the Los Angeles coefficient is 12.21% below 15, while Bandia Limestone gives a flattening coefficient of 3%;the Los Angeles coefficient of 40.17% and the percentage of pollutant (2.4%) well above 2%. It is noted that the percentage of Limestone pollutant is too high. These important results show the net advantage of Basalt compared to Limestone in terms of physical-chemical characteristics.

Optimised CNN Architectures for Handwritten Arabic Character Recognition

Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles.Arabic is morphologically rich,and its characters have a high similarity.The Arabic language includes 28 characters.Each character has up to four shapes according to its location in the word(at the beginning,middle,end,and isolated).This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters.The proposed architectures were derived from the popular CNN architectures,such as VGG,ResNet,and Inception,to make them applicable to recognizing character-size images.The experimental results on three well-known datasets showed that the proposed architectures significantly enhanced the recognition rate compared to the baseline models.The experiments showed that data augmentation improved the models’accuracies on all tested datasets.The proposed model outperformed most of the existing approaches.The best achieved results were 93.05%,98.30%,and 96.88%on the HIJJA,AHCD,and AIA9K datasets.

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating method.The variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared thermometer.The addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni alloys.The images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed camera.The solidification rate of Cu-Ni alloys,with the addition of Co elements,was explored.Finally,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 alloys.The experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification phase.In the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling degree.Furthermore,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

A Method for Detecting and Recognizing Yi Character Based on Deep Learning

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and recognition.In the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character detection.Then,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different scales.Further,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original map.These maps are then subjected to a differentiable binarization process,resulting in an approximate binarization map.This map helps to identify the boundaries of the text boxes.Finally,the text detection box is generated after the post-processing stage.In the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters recognition.Meanwhile,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text recognition.The experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,respectively.And also,we have compared the detection and recognition algorithms proposed in this paper with other typical algorithms.In these comparisons,the proposed model achieves better detection and recognition results with a certain reliability.

Audio2AB:Audio-driven collaborative generation of virtual character animation

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of success.However,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient attention.Methods Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body animations.This parameterization method can be used to drive full-body animations of virtual characters and improve their portability.In the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial data.The Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio features.Finally,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss function.Results By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape weights.Therefore,different 3D virtual character animations could be created through parameterization.Conclusions The experimental results showed that the proposed method could generate significant gestures and facial animations.

A Novel 6G Scalable Blockchain Clustering-Based Computer Vision Character Detection for Mobile Images

6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques.

Frontier Progress of Landscape Character Assessment in China

The role of Landscape Character Assessment(LCA)at the level of territorial landscape governance spans both natural and social sciences.By analyzing the development history,research distribution,methods and applications of cutting-edge cases of LCA in China,the following conclusions are drawn:①the LCA research in China originated earlier than that in Europe,but has not yet been systematically applied to the implementation of urban and rural planning at all levels;②the fundamental theory of LCA in China has been well constructed,with three main research directions:technologyled,assessment-led,and assessment combined with other theories;③the development of LCA in rural areas is more mature than in urban areas,but the progress of research is uneven across regions;④the current research presents significant“bottom-up”academic characteristics,and there is an urgent need for government decision-making authorities and academia to jointly promote a“top-down”standardized governance mechanism to comprehensively promote the modernization of territorial landscape governance.

Leguminosae plants play a key role in affecting soil physical-chemical and biological properties during grassland succession after farmland abandonment in the Loess Plateau,China

Leguminosae are an important part of terrestrial ecosystems and play a key role in promoting soil nutrient cycling and improving soil properties.However,plant composition and species diversity change rapidly during the process of succession,the effect of leguminosae on soil physical-chemical and biological properties is still unclear.This study investigated the changes in the composition of plant community,vegetation characteristics,soil physical-chemical properties,and soil biological properties on five former farmlands in China,which had been abandoned for 0,5,10,18,and 30 a.Results showed that,with successional time,plant community developed from annual plants to perennial plants,the importance of Leguminosae and Asteraceae significantly increased and decreased,respectively,and the importance of grass increased and then decreased,having a maximum value after 5 a of abandonment.Plant diversity indices increased with successional time,and vegetation coverage and above-and below-ground biomass increased significantly with successional time after 5 a of abandonment.Compared with farmland,30 a of abandonment significantly increased soil nutrient content,but total and available phosphorus decreased with successional time.Changes in plant community composition and vegetation characteristics not only change soil properties and improve soil physical-chemical properties,but also regulate soil biological activity,thus affecting soil nutrient cycling.Among these,Leguminosae have the greatest influence on soil properties,and their importance values and community composition are significantly correlated with soil properties.Therefore,this research provides more scientific guidance for selecting plant species to stabilize soil ecosystem of farmland to grassland in the Loess Plateau,China.

Discussion of Online Teaching Strategies for Teaching Elementary Chinese Characters to Foreigners Based on Error Analyses

The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Chinese language learners.Since online teaching is not limited by time and space,its application is widespread.For beginners in the Chinese language,the Chinese characters are both a priority and a challenge.The“Chinese Character Classification,”also known as the“Six Writings,”is the earliest systematic theory of Chinese character structures,and teaching Chinese characters in categories based on the“Chinese Character Classification”is a method that fits the cognition of beginners.In order to teach Chinese characters in a targeted approach,based on the collection and analysis of the common errors of Chinese characters among beginners,(1)this paper proposes that(a)the intuitive method can be applied to teach pictographic characters,indicative characters,and associative compound characters in online teaching;(b)the inductive-deductive method of“basic characters to new characters”can be applied for the teaching of pictophonetic characters and associative compound characters;(c)the learning of character patterns should be approached in a whole-part-whole process,while importance should be attached to the suggestion of the frequency effect with a view to facilitating the online learning of Chinese characters for beginners.The aim of this paper is to provide some practical implications for the online teaching of Chinese characters to foreigners.

Research on the Path of Integrating Ideological and Political Courses into College Physical Education Courses Under the Background of Cultivating Moral Character and Cultivating People

The national education department clearly pointed out in the“Guidelines for the Construction of Ideological and Political Curriculum in Colleges and Universities”that colleges and universities need to take on the fundamental task of cultivating moral character and cultivating people in the process of education,and reasonably integrate ideological and political courses into the curriculum to promote the overall improvement of students’ideological and political quality.This article outlines the connotation of ideological and political courses in the context of cultivating moral character and cultivating people,analyzes and summarizes the significance of integrating ideological and political courses into college physical education courses,summarizes existing problems in the construction of ideological and political courses in college physical education,and explores the path of integrating ideological and political courses into college physical education courses under the background of cultivating moral character and cultivating people,with a view to providing guidelines for teachers.

Sailfish Optimizer with Deep Transfer Learning-Enabled Arabic Handwriting Character Recognition

The recognition of the Arabic characters is a crucial task incomputer vision and Natural Language Processing fields. Some major complicationsin recognizing handwritten texts include distortion and patternvariabilities. So, the feature extraction process is a significant task in NLPmodels. If the features are automatically selected, it might result in theunavailability of adequate data for accurately forecasting the character classes.But, many features usually create difficulties due to high dimensionality issues.Against this background, the current study develops a Sailfish Optimizer withDeep Transfer Learning-Enabled Arabic Handwriting Character Recognition(SFODTL-AHCR) model. The projected SFODTL-AHCR model primarilyfocuses on identifying the handwritten Arabic characters in the inputimage. The proposed SFODTL-AHCR model pre-processes the input imageby following the Histogram Equalization approach to attain this objective.The Inception with ResNet-v2 model examines the pre-processed image toproduce the feature vectors. The Deep Wavelet Neural Network (DWNN)model is utilized to recognize the handwritten Arabic characters. At last,the SFO algorithm is utilized for fine-tuning the parameters involved in theDWNNmodel to attain better performance. The performance of the proposedSFODTL-AHCR model was validated using a series of images. Extensivecomparative analyses were conducted. The proposed method achieved a maximum accuracy of 99.73%. The outcomes inferred the supremacy of theproposed SFODTL-AHCR model over other approaches.

“Cartoon Characters Can Touch Your Soul and Set Trends”——Interview with Lina JU,Chief Designer of GENMEC

Recently,HUGY has become quite popular in the Chinese market.The character can been seen everywhere,from its emojis,memes,cartoon stories,and art toys,to T-shirts,candies,garments.HUGY is a cartoon of a cute puppy,who is always smiling widely and reaching out his arms,ready to hug you.We invited the character’s creator,Lina Ju for an interview.Lina Ju comes from South Korea but has been working in China for 10 years.She is the chief designer of GENMEC,a trendy brand belonging to Sums Model,a company based in the south of China.

Effects of Microelement Fertilizers on Main Economic Characters and Yield of Peanut

The main purpose of this study was to explore and master the optimal types and application methods of microelement fertilizers suitable for peanut cultivation in Linyi City.The results showed that the application of zinc,magnesium,sulfur,calcium and other microelement fertilizers to peanut plants had a certain yield-increasing effect,and zinc had the most significant yield-increasing effect.Compared with the control check(CK),the yield per unit area increased by 1431 kg/hm^(2),equivalent to an increase of 38.4%.Meanwhile,according to field investigation and observation,the treatment of increasing zinc fertilizer had a certain promotion effect on peanut emergence rate,seedling growth potential,and yield components.

Typos Correction in Overseas Chinese Learning Based on Chinese Character Semantic Knowledge Graph

In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunciation, but do not master the semantics of Chinese characters. If they can understand the meaning of Chinese characters and form knowledge groups of the characters with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph (CCSKG). In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104,187 associated edges were finally established for 6752 Chinese characters. Thanks to the development of deep learning, OpenHowNet releases the core data of HowNet and provides useful APIs for calculating the similarity between two words based on sememes. Therefore our method combines the advantages of data-driven and knowledge-driven. The proposed method treats Chinese sentences as subgraphs of the CCSKG and uses graph algorithms to correct Chinese typos and achieve good results. The experimental results show that compared with keras-bert and pycorrector + ernie, our method reduces the false acceptance rate by 38.28% and improves the recall rate by 40.91% in the field of learning Chinese as a foreign language. The CCSKG can help to promote Chinese overseas communication and international education.

Comparative Study on Biological and Commercial Characteristics of Multiple Varieties of Broccoli(Brassica oleracea L.var.italica Plenck)and Vegetable Soybean(Glycine max(L.)Merr.)

[Objectives]This study was conducted to select vegetable soybean varieties(Glycine max(L.)Merr.)that are suitable for local cultivation and meet export requirements.[Methods]Through continuous years of comparative experiments on broccoli and vegetable soybean varieties,detailed biological characteristic and economic quality data of multiple varieties were obtained.[Results]Vegetable soybean variety Taiwan 75-3 had very prominent early-maturing trait,the highest quality(qualification rate),and higher yield than the control check(CK);and the early-maturing trait of vegetable soybean variety Kaohsiung 9 was also prominent,and its yield was higher than that of the CK.They could be promoted as the main vegetable soybean varieties for spring open field cultivation in this region.Among the tested broccoli varieties,Lake had a higher yield,and was relatively tolerant to cold.It had an early harvest period,and was planted as an early autumn variety in this region.Naihan Youxiu showed the highest yield,good quality,cold resistance,and strong adaptability,making it suitable for planting as a late autumn variety in this region.[Conclusions]This study provides technical guidance for the cultivation of local broccoli and vegetable soybean.

Associations between Mental Health Outcomes and Adverse Childhood Experiences and Character Strengths among University Students in Southern China

Adverse childhood experiences(ACEs)can negatively affect mental health,whereas character strengths seem to be positively correlated with mental health.Detailed information on the history of ACEs among university students in China and the extent which mental health is associated with ACEs and character strengths can contribute to the needed empirical evidence for relevant stakeholders.Objectives of this study are 1)to estimate the prevalence of ACEs among undergraduate students in Southern China;and 2)to assess the extent which mental health outcomes(positive growth,well-being,and depression)are associated with ACEs and character strengths among undergraduate students in Southern China.We conducted a self-administered survey amongfirst and second-year students at a university in Southern China and analyzed data using descriptive statistics and linear regression analyses.Among the 779 students who completed the questionnaire,283 were males,439 were females,and 57 did not indicate their gender.The prevalence of ACEs among the participants was 32.1%.History of ACEs was associated with lower positive growth score(Adjusted Beta=-0.20;95%CI=-0.37,-0.02;p=0.030)and lower well-being score(Adjusted Beta=-1.13;95%CI=-2.04,-0.23;p=0.014).Vitality domain of character strength was associated with all three mental health outcomes after adjusting for covariables(all p-values<0.001).Our studyfindings provide empirical evidence for stakeholders in university mental health.However,caveats regarding lack of temporality,selection bias,social desirability bias,and lack of generalizability should be considered in the interpretation of the studyfindings.

On the Mean Value of High-Powers of a Special Character Sum Modulo a Prime

In this paper,we use the elementary methods,the properties of Dirichlet character sums and the classical Gauss sums to study the estimation of the mean value of high-powers for a special character sum modulo a prime,and derive an exact computational formula.It can be conveniently programmed by the“Mathematica”software,by which we can get the exact results easily.

Arabic Optical Character Recognition:A Review

This study aims to review the latest contributions in Arabic Optical Character Recognition(OCR)during the last decade,which helps interested researchers know the existing techniques and extend or adapt them accordingly.The study describes the characteristics of the Arabic language,different types of OCR systems,different stages of the Arabic OCR system,the researcher’s contributions in each step,and the evaluationmetrics for OCR.The study reviews the existing datasets for the Arabic OCR and their characteristics.Additionally,this study implemented some preprocessing and segmentation stages of Arabic OCR.The study compares the performance of the existing methods in terms of recognition accuracy.In addition to researchers’OCRmethods,commercial and open-source systems are used in the comparison.The Arabic language is morphologically rich and written cursive with dots and diacritics above and under the characters.Most of the existing approaches in the literature were evaluated on isolated characters or isolated words under a controlled environment,and few approaches were tested on pagelevel scripts.Some comparative studies show that the accuracy of the existing Arabic OCR commercial systems is low,under 75%for printed text,and further improvement is needed.Moreover,most of the current approaches are offline OCR systems,and there is no remarkable contribution to online OCR systems.