Anisotropic characteristics of granular materials under simple shear

The discrete element method was used to investigate the microscopic characteristics of granular materials under simple shear loading conditions. A series of simple tests on photo-elastic materials were used as a benchmark. With respect to the original experimental observations, average micro-variables such as the shear stress, shear strain and the volumetric dilatancy were extracted to illustrate the performance of the DEM simulation. The change of anisotropic density distributions of contact normals and contact forces was demonstrated during the course of simple shear. On the basis of microscopic characteristics, an analytical approach was further used to explore the macroscopic behaviors involving anisotropic shear strength and anisotropic stress-dilatancy. This results show that under simple shear loading, anisotropic shear strength arises primarily due to the difference between principal directions of the stress and the fabric. In addition, non-coaxiality, referring to the difference between principal directions of the strain rate and the stress, generates less stress-dilatancy. In particular, the anisotropic hardening and anisotropic stress-dilatancy will reduce to the isotropic hardening and the classical Taylor’s stress-dilatancy under proportional loading.

The characterization of the time-dependent nonlinear viscoelastic of an LDPE melt using a simple thixotropy model

A new simple thixotropy model was proposed in the present paper to characterize the thixotropy-loop experiments and the start-up experiment of an LDPE （PE-FSB23D0221Q200） melt. The thixotropy model is a combination of a viscoelastic-component and a postulated kinetics process of structure change, which is constituted in terms of the indirect microstructural approach usually adopted in the characterization of thixotropy. The descriptions of the thixotropy model on both the thixotropy-loop tests and the startup test show good agreement with the experimental values, indicating the good capability of the model in characterizing the time-dependent nonlinear viscoelastic. The stress overshoot phenomenon and the stress relaxation after cessation of the thixotropy loop test can be described well by the model, whereas both of the typical viscoelastic phenomena could not be described in our previous work with a variant Huang model.

OD-CHARACTERIZATION OF ALMOST SIMPLE GROUPS RELATED TO U_6(2)

Let G be a finite group and π（G） = {pl,p2,…… ,pk} be the set of the primes dividing the order of G. We define its prime graph F（G） as follows. The vertex set of this graph is 7r（G）, and two distinct vertices p, q are joined by an edge if and only if pq ∈ πe（G）. In this case, we write p - q. For p ∈π（G）, put deg（p） ：= ｜{q ∈ π（G）｜p - q}｜, which is called the degree of p. We also define D（G） ：= （deg（p1）, deg（p2）,..., deg（pk））, where pl 〈 p2 〈 -……〈 pk, which is called the degree pattern of G. We say a group G is k-fold OD-characterizable if there exist exactly k non-isomorphic finite groups with the same order and degree pattern as G. Specially, a l-fold OD-characterizable group is simply called an OD-characterizable group. Let L ：= U6（2）. In this article, we classify all finite groups with the same order and degree pattern as an almost simple groups related to L. In fact, we prove that L and L.2 are OD-characterizable, L.3 is 3-fold OD-characterizable, and L.S3 is 5-fold OD-characterizable.

Regional disease characteristics and comorbidities of patients with schizophrenia in the Ziprasidone Observational Study of Cardiac Outcomes (ZODIAC): Findings from an international large simple trial

Background: Using baseline data from the Ziprasidone Observational Study of Cardiac Outcomes (ZODIAC), we assessed disease characteristics and prevalence of select comorbidities among subjects with schizophrenia in different clinical settings across 18 countries. ZODIAC was a randomized, open-label, one-year, large simple trial (LST) that enrolled 18,239 individuals with schizophrenia. Methods: Subjects were randomized to open-label treatment with ziprasidone (n = 9120) or olanzapine (n = 9119) in naturalistic (usual care) settings and followed for one year. Study sites (n = 749) applied minimal selection criteria in an attempt to make the study population as representative as possible of those receiving treatment in “real world” circumstances across the countries. Results: Mean patient age was 41 years, 55% were male, 34% were markedly ill or presented with more severe disease, and 66% of subjects had one or more select comorbid conditions [i.e. heart attack, stroke, hypertension, CAD/angina, high cholesterol/triglycerides, diabetes, or overweight (BMI ≥ 25)] at baseline. History of suicide attempt was greatest in the US (38%), compared with Sweden (34%), Brazil/South America (26%), Asia (23%), and Eastern Europe (20%). Overweight or obesity was the most prevalent comorbid risk factor, representing 60% of enrolled subjects, 70% of US subjects compared with 30% in Asia and 52% - 64% in the other regions studied. High cholesterol/triglycerides levels were found in 23% of US subjects compared with a relatively low prevalence in other countries (3% - 11%). History of cardiovascular or diabetes-related comorbidities was found in 31% of subjects. Current smoking (46.5%) and past smoking (11.8%) were common with men dominating the proportion of current smokers: US (61%);Asia (60%);Sweden (50%);Eastern Europe (49%);and Latin America (44%). Conclusions: Our findings indicate substantial baseline variations across countries in demographics, comorbid conditions, and psychiatric disease history. These data provide an international epidemiologic picture of schizophrenia and may help guide future research and treatment initiatives.

A New Characterization of Simple K_3-groups

In this paper, We show that the simple K\-3-groups can be characterized by the orders of their maximal abelian subgroups. That is, we have Theorem Let G be a finite group and M a simple K \-3-group. Then G is isomorphic to M if and only if the set of the orders of the maximal abelian subgoups of G is the same as that of M .

Identification and Characterization of Simple Sequence Repeats (SSR) Markers Associated with Downy Mildew Resistance Locus “<i>RPV1</i>” in Grapes

The cultivation of grapes is severely impacted by the emergence of downy mildew (DM) disease which negatively affects quality and yield possibly resulting in heavy losses. Due to certain shortcomings in the usage of fungicides and the development of new cultivars by plant breeding, marker assisted selection (MAS) will be an efficient alternative method to introduce desired genes into the cultivated varieties in a short time period. The Simple sequence repeats (SSR) markers seem to be the most popular genetic marker of choice for MAS. In the present study, we identified 14 new SSR markers in RPV1 locus that are associated with downy mildew resistance in grapes. The characterization of the identified markers was carried out on the basis of various parameters such as types of repeat motifs, number of repeats, different classes and structure of microsatellites. Additionally, SSR genotyping in 56 different grape accessions was done to determine the susceptibility or resistance of these accessions to DM.

Molecular characterization of sweet potato(Ipomoea batatas[L.]Lam)germplasms for desirable traits by using simple sequence repeats markers

Every breeding program that aims to create new and improved cultivars with desired traits mostly relies on information related to genetic diversity.Therefore,molecular characterization of germplasms is important to obtain target cultivars with desirable traits.Sweet potato[Ipomoea batatas(L.)Lam]is widely considered the world’s most important crop,with great diversity in morphological and phenotypic traits.The genetic diversity of 20 sweet potato germplasms originating from Bangladesh,CIP,Philippines,Taiwan,and Malaysia were compared,which was accomplished by genetic diversity analysis by exploring 20 microsatellite DNA markers for germplasm characterization and utilization.This information was effective in differentiating or clustering the sweet potato genotypes.A total of 64 alleles were generated using the 20 primers throughout the 20 germplasm samples,with locus IBS97 having the highest number of alleles(5),whereas locus IbU33 had the fewest alleles(2).The alleles varied in size from 105(IbU31)to 213 base pairs(IBS34).The Polymorphism Information Content(PIC)values for the loci IbL46 and IBS97 varied from 0.445 to 0.730.IBS97 has the highest number of effective alleles(3.704),compared to an average of 2.520.The average Shannon’s diversity index(H)was 1.003,ranging from 0.673 in IbU3 to 1.432 in IBS97.The value of gene flow(Nm)varied between 0.000 and 0.005,with an average of 0.003,whereas genetic differentiation(FST-values)ranged between 0.901 and 1.000.The sweet potato germplasm included in this study had a broad genetic base.SP1 vs.SP9 and SP12 vs.SP18 germplasm pairings had the greatest genetic distance(GD=0.965),while SP1 vs.SP2 germplasm couples had the least genetic diversity(GD=0.093).Twenty genotypes were classified into two groups in the UPGMA dendrogram,with 16 genotypes classified as group“A”and the remaining four genotypes,SP10,SP18,SP19,and SP20,classified as group“B.”According to cluster analysis,the anticipated heterozygosity(gene diversity)of Nei(1973)was 0.591 on average.In summary,SSR markers successfully evaluated the genetic relationships among the sweet potato accessions used and generated a high level of polymorphism.The results of the present study will be useful for the management of germplasm,improvement of the current breeding strategies,and the release of new cultivars as varieties.

A SIMPLE ANALYSIS OF THE GEOTECTONICEVOLUTIONAL CHARACTERS OF TONGLINAREA,ANHUI

Tonglin area is one ofthe areaswherethere existmany copperore deposits.The geotec- tonic property has many titles.Mostof geological scholarscall itthe lower Yangtze platform depression and divide the geotectonic stages into formation of basement,sedimentaion of coverand intreplate deformation.According to the diwa theory,this paperclassifies itas the Jiangsu- Hubei geodepressional system ofthe Central China geodepressional region.Accord- ing to the analysis of the features ofstructural layers,the geotectonic evolution of the region is divided into four stages:pre- geosyncline,geosyncline,platform and

Investigation on characteristics of liquid self-diffusion in slit nanopores using simple quasicrystal model of liquid

Dynamical properties of liquid in nano-channels attract much interest because of their applications in engineering and biological systems. The transfer behavior of liquid confined within nanopores differs significantly from that in the bulk. Based on the simple quasicrystal model of liquid, analytical expressions of self-diffusion coefficient both in bulk and in slit nanopore are derived from the Stokes–Einstein equation and the modified Eyring's equation for viscosity. The local self-diffusion coefficient in different layers of liquid and the global self-diffusion coefficient in the slit nanopore are deduced from these expressions. The influences of confinement by pore walls,pore widths, liquid density, and temperature on the self-diffusion coefficient are investigated. The results indicate that the self-diffusion coefficient in nanopore increases with the pore width and approaches the bulk value as the pore width is sufficiently large. Similar to that in bulk state, the self-diffusion coefficient in nanopore decreases with the increase of density and the decrease of temperature, but these dependences are weaker than that in bulk state and become even weaker as the pore width decreases. This work provides a simple method to capture the physical behavior and to investigate the dynamic properties of liquid in nanopores.

The Comparative Study of Two Translated Texts on Huangdirent Translating Styles o'n s Internal Classics——Simple Analysis on the Diffe Culture-Specific Lexicon, Figure of Speech and Four-Chinese-Character Structures

Huangdi's Internal Classics(Neijin) is one of the most important ancient medical classics, which plays far-reaching influence in medical field. More and more domestic and overseas scholars published their translated texts on Neijing. Due to the diversity of editions and different understanding, the translating styles and contents are widely different. This study will focus on the different translating styles on culture-specific lexicon、figure of speech and four-Chinese-character structures in Neijin.

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.

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.

An Affordable and Easily Accessible Approach for Acrylonitrile Monomer Purification through a Simple Column Technique

This manuscript presents a dataset detailing a method for purifying monomers. Purification plays a crucial role in every chemical process, as it leads to an improvement in product quality through the removal of impurities. The primary method for monomer purification, like acrylonitrile (AN), is the distillation technique. However, this technique is unsafe and hard to set up or handle. A straightforward, risk-free, low-cost method like the column technique resolves these issues. A simple column technique demonstrated the successful execution of purifying AN. Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) analyses confirmed that AN was successfully purified, with purity reaching 99.8%. FTIR spectra revealed changes in the position and intensity of the stretching vibration peaks after purification. Also, the functional groups of the inhibitor monomethyl ether of hydroquinone (MeHQ) were undetected after purification. Furthermore, after purification, NMR spectra revealed the absence of aromatic protons and carbons associated with MeHQ. In conclusion, the column technique is a successful and inexpensive way to purify AN monomers. This makes it useful for a wide range of applications, especially in polymerization reactions where MeHQ needs to be removed to prevent self-polymerization during the initiation process.

Simple and effective method for treating severe adult skeletal class II malocclusion: A case report

BACKGROUND Severe skeletal class II malocclusion is the indication for combined orthodontic and orthognathic treatment.CASE SUMMARY A woman with a chief complaint of a protruding chin and an inability to close her lips requested orthodontic camouflage.The treatment plan consisted of extracting the right upper third molar,right lower third molar,left lower second molar,and left upper third molar and moving the maxillary dentition distally using a convenient method involving microimplant nail anchors,push springs,long arm traction hooks,and elastic traction chains.After 52 months of treatment,her overbite and overjet were normal,and her facial profile was favorable.CONCLUSION This method can be used for distal movement of the maxillary dentition and to correct severe skeletal class II malocclusion in adults.

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.