Physiology and health assessment,risk balance,and model for endstage liver disease scores:Postoperative outcome of liver transplantation

BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.

The effect of dehydration on plant regeneration and some physiology characters in rice calli

The plant regeneration frequencies of ealli fromplant tissue and cell culture,especially that of thecalli from rice tissue culture and rice anther cul-ture,and that of the foreign-DNA-transfor-mation-derived rice calli is very low(usually 10-15%).It is therefor very important to improve theplant regeneration frequency of rice calli.A1-

Boxing Practitioners Physiology Review: 3. Dietary Supplementation, Weight Control, Recovery and Altitude

The preceding parts of the review concerned kinanthropometric parameters, skeletal muscle recruitment, ergometry, systemic responses and adaptations. Main teachings of this third part of the whole review follow. At the 1996 Atlanta Olympic Game, most vitamin users (91 percent) were boxers. After 18 days of endurance training at the altitude of 1800 m, in boxers, 1) erythropoietin and reticulocytes values increased, 2) remained unchanged parameters of iron metabolism and maximal oxygen uptake values, 3) iron supplementation decreased total body hemoglobin values. Zinc supplementation and/or regularity while boxing influenced plasma levels of calcium, copper, iron, magnesium, phosphorus and zinc in boxers. Sodium bicarbonate ingestion increased punches frequency and time to fatigue in boxers. Boxing-induced thermal dehydration yielded 1) body and muscle masses decrease compensated by increased neural input to muscle, to maintain muscle strength, but 2) a 26.8 percent performance fall. In boxers, fluid and food intake restriction 1) changed neither blood vitamin status nor plasma glutathione levels, 2) yielded a) a negative mood profile and a performance decrease, when resulted in body mass fall by 5.16 percent but b) no performance decrease when fall was by three percent. Diet protein or protein and caloric components decrease increased, in boxers, protein catabolism and, for the same submaximal workload, heart rate and oxygen intake. In food-restricted boxers, myoprotein catabolism increased with decreasing meal intake frequency. Competition and no-competition boxers utilize massage. Massage increased perceptions of recovery after a whole boxing performance. High level of cardiorespiratory fitness accelerates recovery process between boxing rounds.

Corrigendum:Disentangling brain PrPC proteoforms and their roles in physiology and disease

In the article titled“Disentangling brain PrPC proteoforms and their roles in physiology and disease”,published on pages 963-965,Issue 5,Volume 19 of Neural Regeneration Research(Vanni and Romolo,2024;doi:10.4103/1673-5374.385302),the name of the second author appears incorrectly.The correct name is Romolo Nonno.

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.

Physiology of medicinal and aromatic plants under drought stress

Drought poses a significant challenge,restricting the productivity of medicinal and aromatic plants.The strain induced by drought can impede vital processes like respiration and photosynthesis,affecting various aspects of plants’growth and metabolism.In response to this adversity,medicinal plants employ mechanisms such as morphological and structural adjustments,modulation of drought-resistant genes,and augmented synthesis of secondary metabolites and osmotic regulatory substances to alleviate the stress.Extreme water scarcity can lead to leaf wilting and may ultimately result in plant death.The cultivation and management of medicinal plants under stress conditions often differ from those of other crops.This is because the main goal with medicinal plants is not only to increase the yield of the above-ground parts but also to enhance the production of active ingredients such as essential oils.To elucidate these mechanisms of drought resistance in medicinal and aromatic plants,the current review provides a summary of recent literature encompassing studies on the morphology,physiology,and biochemistry of medicinal and aromatic plants under drought conditions.

Artificial intelligence in physiological characteristics recognition for internet of things authentication

Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)systems.However,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral characteristics.Behavioral characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in practice.However,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate authentication.Thus,we review the literature on the use of AI in physiological characteristics recognition pub-lished after 2015.We use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their limitations.We also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.

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.

Effects of Light Quality on Growth and Physiological Characteristics of Neopyropia yezoensis Free Living Conchocelis

[Objectives]To study the differences of growth rate,morphology,ultrastructure,pigment content and antioxidant enzyme activity of free-living conchocelis of cultivated type of Neopyropia yezoensis under different light qualities(white,red,blue,and green light).[Methods]The study was carried out through light quality design and culture,growth rate determination,microstructure and ultrastructure observation,chlorophyll a content and carotenoid content determination,phycobiliprotein content determination,malondialdehyde(MDA)content determination,superoxide dismutase(SOD)activity determination.[Results]After 21 d of culture,the specific growth rate(SGR)and chlorophyll a content of free-living conchocelis of N.yezoensis were significantly increased by white light(WL),followed by red light(RL)and green light(GL),and they were the lowest under blue light(BL).Compared with the WL group,the BL group had the highest content of phycoerythrin(PE),and the RL and GL groups had the highest content of phycocyanin(PC).The algal body of WL group was normal black brown,and the cell wall was the thickest.In RL and GL groups,the algal bodies were green,and their diameters and cell wall thicknesses were similar to those in WL group.In BL group,the algal body was bright red,the diameter was the smallest,the cell wall was the thinnest,and the ultrastructure showed that the number of plastoglobulus on the thylakoid was the largest.After BL irradiation,the highest MDA content and the lowest SOD activity were observed.The results revealed that WL is the most beneficial to the growth of free-living conchocelis,followed by RL and GL,while BL has adverse effects.[Conclusions]This study explored the most suitable light quality conditions for the propagation of free-living conchocelis.It is expected to provide germplasm guarantee for the production and seedling of N.yezoensis.

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.

Effects of Inoculation with Phosphate Solubilizing Bacteria on the Physiology,Biochemistry,and Expression of Genes Related to the Protective Enzyme System of Fritillaria taipaiensis P.Y.Li

Fritillaria taipaiensis P.Y.Li is a widely used medicinal herb in treating pulmonary diseases.In recent years,its wild resources have become scarce,and the demand for efficient artificial cultivation has significantly increased.This article is the first to apply phosphate solubilizing bacteria isolated from the rhizosphere soil of F.taipaiensis P.Y.Li to the cultivation process of F.taipaiensis P.Y.Li.The aim is to identify suitable reference strains for the artificial cultivation and industrial development of F.taipaiensis P.Y.Li by examining the effects of various phosphate solubilizing bacteria and their combinations on photosynthesis,physiological and biochemical properties,and gene expression related to the protective enzyme system in F.taipaiensis P.Y.Li.The experiment,conducted in pots at room temperature,included a control group(CK)and groups inoculated with inorganic phosphorussolubilizing bacteria:W1(Bacillus cereus),W2(Serratia plymuthica),W12(Bacillus cereus and Serratia plymuthica),and groups inoculated with organophosphorus-solubilizing bacteria:Y1(Bacillus cereus),Y2(Bacillus cereus),Y12(Bacillus cereus and Bacillus cereus),totaling seven groups.Compared to CK,most growth indices in the bacterial addition groups showed significant differences,with W12 achieving the highest values in all indices except the leaf area index.The content of photosynthetic pigments,photosynthetic parameters,and osmoregulatory substances increased variably in each bacterial treatment group.W12 exhibited the highest content of chlorophyll a and soluble protein,while W1 had the highest free proline content.The activities of peroxidase(POD),superoxide dismutase(SOD),and catalase(CAT)in all inoculated groups were higher than in CK,with significant changes in SOD and CAT activities.The malondialdehyde(MDA)content in all inoculated groups was lower than in CK,with Y12 being the lowest,at approximately 30%of CK.Gene expression corresponding to these three enzymes also increased variably,with POD expression in Y2 being the highest at 2.73 times that of CK.SOD and CAT expression in Y12 were the highest,at 1.84 and 4.39 times that of CK,respectively.These results indicate that inoculating phosphate solubilizing bacteria can enhance the growth of F.taipaiensis P.Y.Li,with the mixed inoculation groups W12 and Y12 demonstrating superior effects.This lays a theoretical foundation for selecting bacterial fertilizers in the cultivation process of F.taipaiensis P.Y.Li.

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.

From Society to Solitude:An In-depth Analysis of Thoreau’s Characters in Walden

With the deterioration of the environment and the unbalanced relationship between man and nature,people are plagued by varieties of social problems and rising spiritual crises.This paper aims to analyze Thoreau’s characters in Walden and attempts to provide the implications for our contemporary life.Combined with Thoreau’s life experience and the background of Walden,the paper starts with the analysis of Thoreau’s characters from three aspects concerning his pursuit of inner serenity,search for true essence of life and abiding passion for life,which constitute his unique and independent characters and provide the enlightenment for contemporary life.We concluded that unique thoughts,attitudes,and spirit embedded in Thoreau’s characters are inextricably connected with our contemporary life.His personal experience and practice of solitary life at Walden Pond is a testimony to the necessity of closing to nature actively and confronting life passionately.

Progress in the evaluation tool of Character Strengths and its application in nursing staff

Character Strengths is a group of positive personality traits reflected through cognition,behavior,and emotion,which play a positive role in improving happiness,alleviating negative emotions,and maintaining physical and mental health.This article reviews the concept,content,methods,evaluation tools,and application progress of Character Strengths in nurses,so as to provide a reference for clinical managers and improve the quality of life,mental health,and professional satisfaction of n urses.

Chip Surface Character Recognition Based on OpenCV

Chip surface character recognition is an important part of quality inspection in the field of microelectronics manufacturing.By recognizing the character information on the chip,automated production,quality control,and data collection and analysis can be achieved.This article studies a chip surface character recognition method based on the OpenCV vision library.Firstly,the obtained chip images are preprocessed.Secondly,the template matching method is used to locate the chip position.In addition,the surface characters on the chip are individually segmented,and each character image is extracted separately.Finally,a Support Vector Machine(SVM)is used to classify and recognize characters.The results show that this method can accurately recognize the surface characters of chips and meet the requirements of chip quality inspection.

A Review of Research on Handwritten Chinese Character Recognition with Multi-Feature Fusion

This paper analyzes the progress of handwritten Chinese character recognition technology,from two perspectives:traditional recognition methods and deep learning-based recognition methods.Firstly,the complexity of Chinese character recognition is pointed out,including its numerous categories,complex structure,and the problem of similar characters,especially the variability of handwritten Chinese characters.Subsequently,recognition methods based on feature optimization,model optimization,and fusion techniques are highlighted.The fusion studies between feature optimization and model improvement are further explored,and these studies further enhance the recognition effect through complementary advantages.Finally,the article summarizes the current challenges of Chinese character recognition technology,including accuracy improvement,model complexity,and real-time problems,and looks forward to future research directions.