Impact of Dry Warming on Economic and Characteristic Crop and Coping Technology in Northwest of China

Based on the state of characteristics of dry warming of modern climate changing,the response of growth,output and quality of main economic crops such as cotton,flax and winter rape and characteristic crop such as vinifera and apple were discussed.The coping technology for climate changing and measurements for serving the agricultural were provided.

Cold/Warm Change Characteristics in Crop Growing Season in Heilongjiang Province During 1961-2009

[Objective] The aim of the study was to find out the cold/warm change characteristics in crop growing season and their relationship with food production in Heilongjiang Province.[Method] The temporal and spatial variation on the accumulated temperature steadily above 10 ℃ and its lasting days,the beginning date,the ending dates were investigated,and the relationship between food production and cold/warm climate in Heilongjiang Province during 1961-2009 was further analyzed.[Result] The results showed that the provincial average accumulated temperature steadily above 10 ℃ has increased by 355.4 ℃,the lasting days of accumulated temperature steadily above 10 ℃ has extended by 13d,and the beginning date has advanced by 8 d,while the ending date has delayed by 5 d in Heilongjiang Province during 49 years.Climate warming began from the 1980s,and the most significant period of climate warming was after the 1990s.The food production is closely related to cold/warm climate in Heilongjiang Province.[Conclusion] The climate warming was significant in crop growing season of Heilongjiang Province in the past 49 years,providing more favorable climatic conditions for the agricultural production.

The Variation Characteristics of the Cool and Warm Summer of the Northeast China

By analyzing the features of cold and warm summer of the northeast China during 1961-2002,the results showed the time from 1960s to late 1970s was the phase of cold summer took place,and the time from 1980s to early 1990s was the phase of cold and warm summer alternately took place.After the middle and late period of 1990s,it was the concentrated occurrence period of warm summer.The cool and warm summer had the continuity and cluster occurrence characteristics.The frequency of the cool summer was more than the warm summer,and the abnormal degree of warm summer was stronger than the cool summer,and the influence scope was wide.The cool summer had 4 frequent occurrence centers,and the warm summer had 2 frequent occurrence centers,located at the mountain zone and the hills zone.Not only the cool summer was easy to appear,but also the warm summer was easy to happen in the west and the east of Heilongjiang province.Comparatively speaking,the cool summer was easier to appear in the Changbai Mountain area.

Characteristics of Extreme Temperature Event and Its Response to Regional Warming in Northwest China in Past 45 Years

Using the daily maximum and minimum temperature dataset from 128 stations from 1960 to 2004 in Northwest China,daily extreme high temperature(EHT)and extreme low temperature(ELT)thresholds were deter-mined by centesimal method for different stations at first,then yearly EHT and ELT events were counted up in differ-ent stations,and the characteristics of their spatio-temporal distribution were diagnosed at last.The study drew follow-ing conclusions:1)The consistent anomaly distribution characteristic was the most important mode of the EHT and ELT events in Northwest China.2)The spatial distribution of the EHT and ELT events can be divided into five sub-regions,namely,the north of Qinghai and west of Gansu,the north of Xinjiang,the south of Xinjiang,the east of Northwest China and the south of Qinghai.3)The EHT events showed remarkable increasing trend in all of five sub-regions,but only in the north of Qinghai and west of Gansu area,sudden change phenomenon occurred;the ELT events showed decreasing trend in all of five sub-regions,and sudden change phenomenon occurred in Northwest China except for south of Qinghai.4)In all of five sub-regions the EHT events showed remarkable 12-14yr period os-cillation,and the ELT event showed significant 13-15yr and 7-8yr period oscillation.5)The EHT and ELT events displayed remarkable positive and negative responses to regional warming of Northwest China respectively.

Analysis on the Variation Characteristics of Temperature and Precipitation in Benxi Area under the Background of Climate Warming

[Objective] The research aimed to study the variation characteristics of temperature and precipitation in Benxi area under the background of climate warming.[Method] Based on the monthly mean temperature and precipitation data of four routine meteorological stations in Benxi area from 1953 to 2010,by using linear tendency rate,linear regression equation,wavelet analysis,Mann-Kendall detection and so on,the variation characteristics of temperature and precipitation under the background of climate warming in the area were analyzed.[Result] The annual average temperature during 1953-2010 in Benxi area presented rise trend,and the linear tendency rate was 0.28 ℃/10 a.It was temperature increase trend in four seasons.The temperature rise rate in winter was the maximum and was the minimum in summer.The annual rainfall presented decrease trend,and the linear tendency rate was-18.16 mm/10 a.Except in spring,it was decrease trend in other seasons.Mann-Kendall mutation detection showed that the mutation of annual average temperature in Benxi area in recent 58 years appeared in 1986.There was no mutation phenomenon in summer.Spring mutation appeared in 1974,and autumn mutation appeared in 1987.Winter mutation was in 1981.The annual and seasonal precipitation didn’t have the mutation phenomenon.The wavelet analysis found that the annual average temperature had the periodic variations of 12-14,5-6 and 2 years in Benxi area in recent 58 years.The annual rainfall had the periodic fluctuations of 8-12,5-6 and 2 years.[Conclusion] The research provided the scientific basis for exploration and sustainable development of the climate resources in the mountain area.

Transient Characteristics of Residual Meridional Circulation during Stratospheric Sudden Warming

The residual meridional circulation derived from the transformed Eulerian-mean thermodynamic equation and continuity equation can be separated into two parts,the slowly varying diabatic circulation and the transient circulation,as demonstrated by others.We calculated and composite-analyzed the transient and diabatic circulation for 14 stratospheric sudden warming(SSW) events from 1979-2002 by using the daily ECMWF reanalysis data.Specifically,the transient residual meridional circulation was calculated both with and without inclusion of the eddy heat transport term in the transformed Eulerian-mean thermodynamic equation to investigate the importance of the eddy heat transport term.The results showed that calculations of transient residual meridional circulation present rapid variations during SSWs,with or without inclusion of the eddy heat transport term.Although the patterns of transient residual meridional circulation with the eddy heat transport term were similar to that without the eddy heat transport term during SSW,the magnitudes in the upper stratosphere and high-latitude regions differed.As for the diabatic circulation,its daily variations were small during SSW events,and its patterns were in agreement with its monthly average.

Characteristics of Temperature Change in China over the Last 2000 years and Spatial Patterns of Dryness/Wetness during Cold and Warm Periods

This paper presents new high-resolution proxies and paleoclimatic reconstructions for studying climate changes in China for the past 2000 years. Multi-proxy synthesized reconstructions show that temperature variation in China has exhibited significant 50–70-yr, 100–120-yr, and 200–250-yr cycles. Results also show that the amplitudes of decadal and centennial temperature variation were 1.3℃ and 0.7℃, respectively, with the latter significantly correlated with long-term changes in solar radiation, especially cold periods, which correspond approximately to sunspot minima. The most rapid warming in China occurred over AD 1870–2000, at a rate of 0.56°± 0.42℃（100 yr）^（-1）; however, temperatures recorded in the 20 th century may not be unprecedented for the last 2000 years, as data show records for the periods AD 981–1100 and AD1201–70 are comparable to the present. The ensemble means of dryness/wetness spatial patterns in eastern China across all centennial warm periods illustrate a tripole pattern： dry south of 25°N, wet from 25°–30°N, and dry to the north of 30°N. However, for all centennial cold periods, this spatial pattern also exhibits a meridional distribution. The increase in precipitation over the monsoonal regions of China associated with the 20 th century warming can primarily be attributed to a mega El Nino–Southern Oscillation and the Atlantic Multidecadal Oscillation. In addition, a significant association between increasing numbers of locusts and dry/cold conditions is found in eastern China. Plague intensity also generally increases in concert with wetness in northern China, while more precipitation is likely to have a negative effect in southern China.

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.

THE FREQUENCY CHARACTERISTICS OF WARM AND COLD EPISODES IN THE NIO REGIONS

On the basis of NOAA/CPC data of sea surface temperature anomaly in the Nifio regions during Jan. 1950 - Dec. 2003, the wavelet power spectrum of SST were studied with significance and confidence testing at different scales in this paper. It shows that the SST are provided with multi-time scales structure nested one another, and vary on scales of 2 - 7 years, 8 - 20 years and 〉30 years. The most significant variation of the warm and cold episodes is in the 4-year band of period. The power, frequency structure and confidence of the same episode are different in different Nino regions. The intensity of oscillations is increasing at low frequency bands and decreasing at high frequency bands from east to west in the Nino regions, especially after 1970.

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.

Nocturnal-to-morning rains during the warm season in South China:characteristics and predictability

The characteristics of nocturnal-to-morning rainfall(NMR)during the warm season in South China are examined using hourly surface observations from 2015–2019.Results show that strong NMR is mainly located in coastal regions and mountainous areas.NMR mainly occurs during 0200–0800 LST.The distribution of NMR can be divided into two types.The first pattern is a coastal type where NMR is mainly located at windward sites,such as southern coastal mountain areas in Guangdong(GD)and in Guangxi(GX).The second type is an inland type where NMR is mainly located at windward sites,such as the northern mountainous areas in GX and the Pearl River Delta regions in GD.The strong convergence between the northerly wind over the mountainous regions and southerly wind,as well as the strong downhill winds strengthened by the narrow pipe effect over the valleys in mountainous areas,together contribute to the high frequency of inland NMR.The strong southeasterly onshore wind and the cyclonic circulations strengthened by the northeasterly wind over the northern mountainous areas contribute to the high frequency of coastal NMR.Though the GRAPES(Global/Regional Assimilation and Prediction System)model can capture the intensity and distribution of large-scale NMR,it exhibits low predictability of small-scale NMR,especially that in the warm sector.

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.

Effects of Climate Warming on Phenological Characteristics of Urban Forest in Shenyang City,China

Change in plant phenology is one of the most sensitive ecological responses to climate warming. Little information is known about the effects of climate warming on phenology of urban tree species in the northern forest of China. In this study, we investigated the phenological characteristics of the main tree species in the urban forest of Shengyang City in China and the correlation between phenology and atmospheric temperature from the discontinuous data during past 42 years over three time periods(from 1962 to 1965, 1977 to 1978, and 2000 to 2005). The results showed that the annual average temperature in Shenyang City showed an increasing trend and increased by 0.96℃ from 1962 to 2005 due to climate warming. The germination phenology of the urban trees was negatively correlated with the temperature in winter and early spring. The leafing phenology was mainly influenced by the temperature in spring before leafing. Influenced by climate warming, the germination, leafing, and flowering phenologies of this urban forest in 2005 were 14, 13, and 10 days earlier than those in 1962, respectively. We inferred that further warming in winter might prolong the growing season of urban trees in the northern forest of China.

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.

Fireworks Optimization with Deep Learning-Based Arabic Handwritten Characters Recognition Model

Handwritten character recognition becomes one of the challenging research matters.More studies were presented for recognizing letters of various languages.The availability of Arabic handwritten characters databases was confined.Almost a quarter of a billion people worldwide write and speak Arabic.More historical books and files indicate a vital data set for many Arab nationswritten in Arabic.Recently,Arabic handwritten character recognition(AHCR)has grabbed the attention and has become a difficult topic for pattern recognition and computer vision(CV).Therefore,this study develops fireworks optimizationwith the deep learning-based AHCR(FWODL-AHCR)technique.Themajor intention of the FWODL-AHCR technique is to recognize the distinct handwritten characters in the Arabic language.It initially pre-processes the handwritten images to improve their quality of them.Then,the RetinaNet-based deep convolutional neural network is applied as a feature extractor to produce feature vectors.Next,the deep echo state network(DESN)model is utilized to classify handwritten characters.Finally,the FWO algorithm is exploited as a hyperparameter tuning strategy to boost recognition performance.Various simulations in series were performed to exhibit the enhanced performance of the FWODL-AHCR technique.The comparison study portrayed the supremacy of the FWODL-AHCR technique over other approaches,with 99.91%and 98.94%on Hijja and AHCD datasets,respectively.

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.

CHARACTERISTICS OF CLIMATE WARMING AND IMPACT ON CLIMATE ZONES CHANGE IN GUANGDONG

Based on temperature data in Guangdong in the past 50years, statistical methods are used to analyze the characteristics of temperature in spatial and temporal variation. The results show that land surface temperature warms by 0.16℃/1 0a in Guangdong. The range of warming was lower than the average of nationwide and global land surface. Furthermore, the temperature has a larger increase tendency in winter and spring and coastal areas than in summer and autumn and inland areas. Climate zones move towards the north obviously. North tropical zone is expanding, south subtropical zone is reducing and central subtropical zone is relatively stable. Under the global climate warming, characteristics of climate warming in Guangdong were influenced by atmosphere general circulation, sea surface temperature and human activities etc.

Characteristics of zooplankton community in North Yellow Sea unveiled an indicator species for the Yellow Sea Warm Current in winter: Euchaeta plana

Zooplankton distributions are largely influenced by both biotic and abiotic factors in the surrounding environment.Some zooplankton species can be used as bio-indicators for particular currents and water masses to help discover the dynamics of water current in the ocean.In this study,we investigated the distribution of zooplankton in North Yellow Sea(NYS)during winter when the Yellow Sea Warm Current(YSWC)influenced that area.Zooplankton communities in the NYS were dominated by temperate and warm-temperate species,such as Calanus sinicus,Paracalanus parvus,Acartia bifilosa,and Sagitta crassa.Two warm-water species,Eucheata plana and Sagitta enflata were also present.Cluster analysis grouped NYS zooplankton into three communities,the Shandong Coastal Community(SCC)in the Shandong neritic area,the Yellow Sea Central Community(YSCC)in the central waters of the NYS,and the Liaoning Coastal Community(LCC)in the Liaoning neritic area.Abundances varied significantly among these communities,with an average of 102.2 ind./m^3 in SCC,179.8 ind./m^3 in YSCC,and 1244.2 ind./m^3 in LCC.Depth and the bottom(3 m from the sea floor)temperature were likely the primary abiotic factors influencing zooplankton distributions.The appearance of E.plana,an indicator species for the YSWC path,indicated a significant northwestward trend for the YSWC in 2007.

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.