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.

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.

Writing the Silenced Female Body, Scrutinizing the Grand Narrative of Colonization and Decolonization: The Body in Zoë Wicomb’s David’s Story

David’s Story by Zoë Wicomb addresses the complexities of representing female suffering and the limitations of traditional historical narratives in capturing the experiences of marginalized bodies.It challenges the grand narratives of national history by emphasizing the indispensable role of women’s experiences.Through characters like Dulcie and Rachael,Wicomb portrays the female body as a site of resistance and resilience,highlighting the need for more nuanced and inclusive ways of documenting history.Underscoring the inexpressibility of trauma and the limitations of language and representation,the novel self-reflexively acknowledges its own aporia of completing the narrative,embodying the ongoing struggle to capture the full breadth of human experience.

Host-induced gene silencing of the Verticillium dahliae thiamine transporter protein gene(VdThit)confers resistance to Verticillium wilt in cotton

Verticillium wilt(VW),induced by the soil-borne fungus Verticillium dahliae(Vd),poses a substantial threat to a diverse array of plant species.Employing molecular breeding technology for the development of cotton varieties with heightened resistance to VW stands out as one of the most efficacious protective measures.In this study,we successfully generated two stable transgenic lines of cotton(Gossypium hirsutum L.),VdThitRNAi-1 and VdThit-RNAi-2,using host-induced gene silencing(HIGS)technology to introduce double-stranded RNA(dsRNA)targeting the thiamine transporter protein gene(VdThit).Southern blot analysis confirmed the presence of a single-copy insertion in each line.Microscopic examination showed marked reductions in the colonization and spread of Vd-mCherry in the roots of VdThit-RNAi cotton compared to wild type(WT).The corresponding disease index and fungal biomass of VdThit-RNAi-1/2 also exhibited significant reductions.Real-time quantitative PCR(qRT-PCR)analysis demonstrated a substantial inhibition of VdThit expression following prolonged inoculation of VdThit-RNAi cotton.Small RNA sequencing(sRNA-Seq)analysis revealed the generation of a substantial number of VdThit-specific siRNAs in the VdThit-RNAi transgenic lines.Additionally,the silencing of VdThit by the siVdThit produced by VdThit-RNAi-1/2 resulted in the elevated expression of multiple genes involved in the thiamine biosynthesis pathway in Vd.Under field conditions,VdThit-RNAi transgenic cotton exhibited significantly enhanced disease resistance and yield compared with WT.In summary,our findings underscore the efficacy of HIGS targeting VdThit in restraining the infection and spread of Vd in cotton,thereby potentially enabling the development of cotton breeding as a promising strategy for managing VW.

Meta-silencer with designable timbre

Timbre,as one of the essential elements of sound,plays an important role in determining sound properties,whereas its manipulation has been remaining challenging for passive mechanical systems due to the intrinsic dispersion nature of resonances.Here,we present a meta-silencer supporting intensive mode density as well as highly tunable intrinsic loss and offering a fresh pathway for designable timbre in broadband.Strong global coupling is induced by intensive mode density and delicately modulated with the guidance of the theoretical model,which efficiently suppresses the resonance dispersion and provides desirable frequency-selective wave-manipulation capacity for timbre tuning.As proof-of-concept demonstrations for our design concepts,we propose three meta-silencers with the designing targets of high-efficiency broadband sound attenuation,efficiency-controlled sound attenuation and designable timbre,respectively.The proposed meta-silencers all operate in a broadband frequency range from 500 to 3200 Hz and feature deep-subwavelength sizes around 50 mm.Our work opens up a fundamental avenue to manipulate the timbre with passive resonances-controlled acoustic metamaterials and may inspire the development of novel multifunctional devices in noise-control engineering,impedance engineering,and architectural acoustics.

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.

“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.

Application of dual reciprocity boundary element method to predict acoustic attenuation characteristics of marine engine exhaust silencers

In marine engine exhaust silencing systems, the presence of exhaust gas flow influences the sound propagation inside the systems and the acoustic attenuation performance of silencers. In order to investigate the effects of three-dimensional gas flow and acoustic damping on the acoustic attenuation characteristics of marine engine exhaust silencers, a dual reciprocity boundary element method (DRBEM) was developed. The acoustic governing equation in three-dimensional potential flow was derived first, and then the DRBEM numerical procedure is given. Compared to the conventional boundary element method (CBEM), the DRBEM considers the second order terms of flow Mach number in the acoustic governing equation, so it is suitable for the cases with higher Mach number subsonic flow. For complex exhaust silencers, it is difficult to apply the single-domain boundary element method, so a substructure approach based on the dual reciprocity boundary element method is presented. The experiments for measuring transmission loss of silencers are conducted, and the experimental setup and measurements are explained. The transmission loss of a single expansion chamber silencer with extended inlet and outlet were predicted by DRBEM and compared with the measurements. The good agreements between predictions and measurements are observed, which demonstrated that the derived acoustic governing equation and the DRBEM numerical procedure in the present study are correct.

Analysis of Young Girls’Eagerness to Spend for Disney Virtual Characters Based on Marketing Mix Theory

A virtual character is a design of a fictitious creature with distinctive characteristics created by people,and Disney virtual characters are those Intellectual Property(IP)images that appeared in Disneyland and Disney movies.This investigation aimed to explore why many younger females are keen to spend money on Disney virtual characters.This paper adopted the Marketing Mix Theory strategy(product,price,placement,and promotion(4P)),and the SWOT analysis method has been utilized.This paper investigated the relationship between the 4Ps and consumers’purchasing intentions,and it turned out that unique design and effective promotion in this Disney case would promote consumers’purchase intention,while the higher price and less accessible placements affected their purchase intentions.Thus,the high price and limited places somewhat inhibit customers’desire to buy;due to the attractiveness of the product itself and the promotion on the internet,the target consumers are still willing to consume.

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.

Being Human in a More-Than-Human World:Between a Silence Catalyst for(Re)Aestheticization and an Art Catalyst for Relationships

The contribution moves from highlighting how,in the context of Michel Serres’and posthumanism’s proposal of rethinking the human and the world in a perspective of inter-implication and universal co-belonging,silence(of the human word)assumes the function of a catalyst for the recognition/re-aestheticization of the human body in its sensory-aesthetic-cognitive-relational-hybrid dimensionality,and,with and for it,of the world in its agency(including artistic).Within the framework of this perspective,the investigation thus proposes a reading of art as a relation/catalyzer of relations,that is,as a(re)activation of positive relations of the human with and for a world that reveals itself to be increasingly hyper-complex,that is,more-than-human,in the continuity/inseparability of nature and culture.Taking Serresian ideas on artistic practices as non(only)human forms of expression and posthumanist“isomorphic”positions on non-human agency as tools,the research then highlights the“more-than-human”scope of art and the fact that artistic practices are responsive actions.So much so that,the human being emerges as co-agent and,of course,co-owner.

Host-Induced Gene Silencing of Effector AGLIP1 Enhanced Resistance of Rice to Rhizoctonia solani AG1-IA

Rice sheath blight, caused by Rhizoctonia solani AG1-IA, is a major disease in rice-growing areas worldwide. Effectors of phytopathogenic fungi play important roles during the infection process of fungal pathogens onto their host plants. However, the molecular mechanisms by which R. solani effectors regulate rice immunity are not well understood. Through prediction, 78 candidate effector molecules were identified. Using the tobacco rattle virus-host induced gene silencing(TRV-HIGS) system, 45 RNAi constructs of effector genes were infiltrated into Nicotiana benthamiana leaves. The results revealed that eight of these constructs resulted in a significant reduction in necrosis caused by infection with the AG1-IA strain GD-118. Additionally, stable rice transformants carrying the double-stranded RNA construct for one of the effector genes, AGLIP1, were generated to further verify the function of this gene. The suppression of the AGLIP1 gene increased the resistance of both N. benthamiana and rice against GD-118, and also affected the growth rate of GD-118, indicating that AGLIP1 is a key pathogenic factor. Small RNA sequencing showed that the HIGS vectors were processed into si RNAs within the plants and then translocated to the fungi, leading to the silencing of the target genes. As a result, AGLIP1 might be an excellent candidate for HIGS, thereby enhancing crop resistance against the pathogen and contributing to the control of R. solani infection.

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.

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.

A Comparative Analysis of the Origin and Formation Between Chinese Characters and English Alphabets

This research is based on the framework of social constructivism,utilizing the principle of Human Universals as a methodology to compare the similarities and differences between the ideation and formation methods of Chinese characters and English alphabets.Through comparative analysis of the ideation of English letters(pictogramme)and the origin of Chinese characters,known as the"Six Categories Theory,"we discover their alignment in terms of social,traditional,and cultural aspects.This suggests that different ethnic groups share common features in terms of life experience,learning cognitive development,and thinking habits.This study also finds that the origins of English letters and Chinese characters share similar linguistic features in their methods of constructing letters/characters,such as pictographic,ideographic,and semantic characteristics.Exploring these commonalities contributes to promoting learning and communication between Chinese and English characters.Additionally,by focusing on socio-cultural aspects,traditional customs,and cognitive learning,this study aims to break away from the traditional linguistic research approach that solely focuses on language differences.This provides a broader perspective and richer dimensions for Chinese and English language learning,facilitating the development of cross-linguistic and cross-cultural communication.

Stress response silencing by an E3 ligase mutated in neurodegeneration

Stress response pathways detect and alleviate adverse conditions to safeguard cell and tissue homeostasis,yet their prolonged activation induces apoptosis and disrupts organismal health1-3.How stress responses are turned off at the right time and place remains poorly understood.Here we report a ubiquitin-dependent mechanism that silences the cellular response to mitochondrial protein import stress.