Umami taste components in chicken-spices blends and potential effect of aroma on umami taste intensity

In this study,umami taste intensity(UTI)and umami taste components in chicken breast(CB)and chickenspices blends were characterized using sensory and instrumental analysis.Our main objective was to assess the aroma-umami taste interactions in different food matrices and reconcile the aroma-taste perception to assist future product development.The impact of key aroma,including vegetable-note"2-pentylfuran",meaty"methional",green"hexanal",and spicy-note-estragole and caryophyllene"on UTI was evaluated in monosodium glutamate and chicken extract.We found that spices significantly decreased UTI and umami taste components in CB.Interestingly,the perceptually similar odorants and tastants exhibited the potential to enhance UTI in food matrices.Methional was able to increase the UTI,whereas spicy and green-note components could reduce the UTI significantly.This information would be valuable to food engineers and formulators in aroma selection to control the UTI perceived by consumers,thus,improving the quality and acceptability of the chicken products.

Mesh representation matters:investigating the influence of different mesh features on perceptual and spatial fidelity of deep 3D morphable models

Background Deep 3D morphable models(deep 3DMMs)play an essential role in computer vision.They are used in facial synthesis,compression,reconstruction and animation,avatar creation,virtual try-on,facial recognition systems and medical imaging.These applications require high spatial and perceptual quality of synthesised meshes.Despite their significance,these models have not been compared with different mesh representations and evaluated jointly with point-wise distance and perceptual metrics.Methods We compare the influence of different mesh representation features to various deep 3DMMs on spatial and perceptual fidelity of the reconstructed meshes.This paper proves the hypothesis that building deep 3DMMs from meshes represented with global representations leads to lower spatial reconstruction error measured with L_(1) and L_(2) norm metrics and underperforms on perceptual metrics.In contrast,using differential mesh representations which describe differential surface properties yields lower perceptual FMPD and DAME and higher spatial fidelity error.The influence of mesh feature normalisation and standardisation is also compared and analysed from perceptual and spatial fidelity perspectives.Results The results presented in this paper provide guidance in selecting mesh representations to build deep 3DMMs accordingly to spatial and perceptual quality objectives and propose combinations of mesh representations and deep 3DMMs which improve either perceptual or spatial fidelity of existing methods.

Effectiveness of anti-psychiatric treatment on visual and haptic perceptual disorder for a patient with Alzheimer’s disease: A case report

BACKGROUND Perception is frequently impaired in patients with Alzheimer’s disease(AD).Several patients exhibit visual or haptic hallucinations.CASE SUMMARY A 71-year-old Chinese man presented with visual and haptic hallucinations he had been experiencing for 2 weeks.The clinical manifestations were the feeling of insects crawling and biting the limbs and geison.He looked for the insects while itching and scratching,which led to skin breakage on the limbs.He was treated with topical and anti-allergic drugs in several dermatology departments without any significant improvement.After admission,the patient was administered risperidone(0.5 mg)and duloxetine(2 mg/day).One week later,the dose of risperidone was increased to 2 mg/day,and that of duloxetine was increased to 60 mg/day.After 2 weeks of treatment,the patient’s sensation of insects crawling and biting disappeared,and his mood stabilized.CONCLUSION This patient manifested psychiatric behavioral symptoms caused by AD brain atrophy.It was important to re-evaluate the patient’s cognitive-psychological status when the patient repeatedly went to the hospital for treatment.Follow-up attention to cognitive function and the consideration of perceptual deficits as early manifestations of AD should be considered.

FMHADP:Design of an Efficient Pre-Forensic Layer for Mitigating Hybrid Attacks via Deep Learning Pattern Analysis

Network attack detection and mitigation require packet collection,pre-processing,feature analysis,classification,and post-processing.Models for these tasks sometimes become complex or inefficient when applied to real-time data samples.To mitigate hybrid assaults,this study designs an efficient forensic layer employing deep learning pattern analysis and multidomain feature extraction.In this paper,we provide a novel multidomain feature extraction method using Fourier,Z,Laplace,Discrete Cosine Transform(DCT),1D Haar Wavelet,Gabor,and Convolutional Operations.Evolutionary method dragon fly optimisation reduces feature dimensionality and improves feature selection accuracy.The selected features are fed into VGGNet and GoogLeNet models using binary cascaded neural networks to analyse network traffic patterns,detect anomalies,and warn network administrators.The suggested model tackles the inadequacies of existing approaches to hybrid threats,which are growing more common and challenge conventional security measures.Our model integrates multidomain feature extraction,deep learning pattern analysis,and the forensic layer to improve intrusion detection and prevention systems.In diverse attack scenarios,our technique has 3.5% higher accuracy,4.3% higher precision,8.5% higher recall,and 2.9% lower delay than previous models.

Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-II

A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation(DNSGA-II)strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product.First,the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users;then,the product multidimensional scale analysis is applied to classify the research objects,and again the reference samples are screened by the semantic differentialmethod,and the samples are parametrized in two dimensions by using elliptic Fourier analysis;finally,the fuzzy dynamic evaluation function is used as the objective function of the algorithm,and the coordinates of key points of product contours Finally,with the fuzzy dynamic evaluation function as the objective function of the algorithm and the coordinates of key points of the product profile as the decision variables,the optimal product profile solution set is solved by DNSGA-II.The validity of the model is verified by taking the optimization of the shape scheme of the hospital connection site as an example.For comparison with DNSGA-II,other multi-objective optimization algorithms are also presented.To evaluate the performance of each algorithm,the performance evaluation index values of the five multi-objective optimization algorithms are calculated in this paper.The results show that DNSGA-II is superior in improving individual diversity and has better overall performance.

Robust Watermarking Algorithm for Medical Images Based on Non-Subsampled Shearlet Transform and Schur Decomposition

With the development of digitalization in healthcare,more and more information is delivered and stored in digital form,facilitating people’s lives significantly.In the meanwhile,privacy leakage and security issues come along with it.Zero watermarking can solve this problem well.To protect the security of medical information and improve the algorithm’s robustness,this paper proposes a robust watermarking algorithm for medical images based on Non-Subsampled Shearlet Transform(NSST)and Schur decomposition.Firstly,the low-frequency subband image of the original medical image is obtained by NSST and chunked.Secondly,the Schur decomposition of low-frequency blocks to get stable values,extracting the maximum absolute value of the diagonal elements of the upper triangle matrix after the Schur decom-position of each low-frequency block and constructing the transition matrix from it.Then,the mean of the matrix is compared to each element’s value,creating a feature matrix by combining perceptual hashing,and selecting 32 bits as the feature sequence.Finally,the feature vector is exclusive OR(XOR)operated with the encrypted watermark information to get the zero watermark and complete registration with a third-party copyright certification center.Experimental data show that the Normalized Correlation(NC)values of watermarks extracted in random carrier medical images are above 0.5,with higher robustness than traditional algorithms,especially against geometric attacks and achieve watermark information invisibility without altering the carrier medical image.

Perceptual Optimization for Point-Based Point Cloud Rendering

Point-based rendering is a common method widely used in point cloud rendering.It realizes rendering by turning the points into the base geometry.The critical step in point-based rendering is to set an appropriate rendering radius for the base geometry,usually calculated using the average Euclidean distance of the N nearest neighboring points to the rendered point.This method effectively reduces the appearance of empty spaces between points in rendering.However,it also causes the problem that the rendering radius of outlier points far away from the central region of the point cloud sequence could be large,which impacts the perceptual quality.To solve the above problem,we propose an algorithm for point-based point cloud rendering through outlier detection to optimize the perceptual quality of rendering.The algorithm determines whether the detected points are outliers using a combination of local and global geometric features.For the detected outliers,the minimum radius is used for rendering.We examine the performance of the proposed method in terms of both objective quality and perceptual quality.The experimental results show that the peak signal-to-noise ratio(PSNR)of the point cloud sequences is improved under all geometric quantization,and the PSNR improvement ratio is more evident in dense point clouds.Specifically,the PSNR of the point cloud sequences is improved by 3.6%on average compared with the original algorithm.The proposed method significantly improves the perceptual quality of the rendered point clouds and the results of ablation studies prove the feasibility and effectiveness of the proposed method.

Perceptual Learning of Grate Orientation Discrimination in Cats

Perceptual learning of orientation discrimination was investigated using cats. Two adult cats （Cat 1 and 2） were trained to monocularly discriminate between two static striped sinusoidal grates with 30° orientation difference. After greater than 80% correct performance was reached, cats were then required to monocularly perform a discrimination between two grates with consecutively shifting orientation difference（2°, 4°, 6°, 8°, 10°, 12°, 16°, 20°, 24°, 30°） . The staircase method （two correct-down and one error-up） was applied throughout the training to track the threshold of orientation difference that cats could detect. The performance of detecting grates with varied orientation difference was measured respectively for beth trained and untrained eyes before and after training. Our results showed that the learning effect of discrimination for grates with a fixed orientation difference transferred completely from the trained eye to the untrained eye, whereas the inter-eye transfer for detecting °ates with gradually reducing orientation difference was almost nonegrates. The two opposite learning effects in the same subject strongly suggest that different information processing mechanisms might mediate the learning processes.

Image quality assessment based on perceptual grouping

To further explore the human visual system（ HVS）,the perceptual grouping（ PG）, which has been proven to play an important role in the HVS, is adopted to design an effective image quality assessment（ IQA） model. Compared with the existing fixed-window-based models, the proposed one is an adaptive window-like model that introduces the perceptual grouping strategy into the IQA model. It works as follows： first,it preprocesses the images by clustering similar pixels into a group to the greatest extent; then the structural similarity is used to compute the similarity of the superpixels between reference and distorted images; finally, it integrates all the similarity of superpixels of an image to yield a quality score. Experimental results on three databases（ LIVE, IVC and MICT） showthat the proposed method yields good performance in terms of correlation with human judgments of visual quality.

Analysis of the Image Space of Rural Landscape of the Pearl River Delta

Through questionnaires and perceptual maps,we made a variation analysis of landscape spatial image to the people in the Pearl River Delta from the viewpoint of the subjective perception.It is found that the people of different ages and different education levels from different areas hold diversified perceptions towards rural landscape space,and they have different ideal rural landscapes.However,there is a common point that the development of rural landscape should retain its excellent local landscape features and the local spirit,which will provide references for building the ideal rural landscape model.

遗传性听力损失基因组学研究现状与挑战

在21世纪生命科学飞速发展的今天，医学已经进入一个基因组医学时代，人们对健康和疾病的认识在前所未有的分子水平上得到详尽的分析和理解。此时，不寻常的机遇和挑战摆在了我们这些维护生命健康和从事临床实践的医师面前。纵观十余年遗传性听力损失的发展历史，毋庸置疑的是，由于基因组学的快速发展和伟大成就才使得我们在一个研究手段有限、研究范围极为狭窄的专业领域中产生了快速的突破。同时，也使我们不得不思考，我们如何面对这样的机遇和挑战？

Perceptual video coding method based on JND and AR model

In order to achieve better perceptual coding quality while using fewer bits, a novel perceptual video coding method based on the just-noticeable-distortion （JND） model and the auto-regressive （AR） model is explored. First, a new texture segmentation method exploiting the JND profile is devised to detect and classify texture regions in video scenes. In this step, a spatial-temporal JND model is proposed and the JND energy of every micro-block unit is computed and compared with the threshold. Secondly, in order to effectively remove temporal redundancies while preserving high visual quality, an AR model is applied to synthesize the texture regions. All the parameters of the AR model are obtained by the least-squares method and each pixel in the texture region is generated as a linear combination of pixels taken from the closest forward and backward reference frames. Finally, the proposed method is compared with the H.264/AVC video coding system to demonstrate the performance. Various sequences with different types of texture regions are used in the experiment and the results show that the proposed method can reduce the bit-rate by 15% to 58% while maintaining good perceptual quality.

近距离3D人机交互技术研究实现

3D人机交互技术是计算机图形学、虚拟现实和模式识别的交叉融合领域,可分为虚拟环境的显示和三维物体识别。该研究将虚拟环境显示和三维物体识别整合成一个完整的解决方案并应用到1:1模拟虚拟场景的近距离交互。研究了虚拟现实之间的坐标转换;分析了影响虚拟物体立体显示的三个主要因素:Open GL中摄像机的张角,摄像机间距和立体图像对的产生;并实现了基于Intel Perceptual Computing的三维物体识别。实验结果显示:该方案在1:1模拟虚拟场景方面具有良好的3D显示效果,同时在手势识别方面有较高的识别率。

基于改进的VGG16模型的副热带高压相似识别及应用评估

台风预报除常规方法外,查找历史相似作为预报和决策的参考依据是常用手段,但从海量历史台风中检索相似费时费力。提出了一种基于改进的视觉几何组模型VGG16的副热带高压(以下简称副高)相似检索方法,进行基于副高相似的历史相似台风查询。通过对1979—2020年台风季19736个对应时次的副高图像提取、数据增强、模型学习和优化,并以学习感知图像块相似度(learned perceptual image patch similarity,LPIPS)作为副高相似的度量指标,最终建立了改进的VGG16模型。试验结果表明,使用该模型可以找出较为相似的历史台风,模型检索得到的排名第一的历史相似台风与目标台风相似度高达92.55%,该方法可为台风预报业务人员提供了积极参考。同时,该模型相较于传统的人工识别,识别时间较短、检索效率高,可在业务及科研中推广应用。

Air/CO2 cooling garment: Description and benefits of use for subjects exposed to a hot and humid climate during physical activities

The severity of the hot and humid conditions to which miners are exposed increases as the depth of the work site increases.This can cause heat stress that can greatly affect the health and safety of workers.To resolve this,a cooling garment has been developed that uses an atmospheric discharge of liquid CO2 to create a cool microclimate with an average temperature of 12.5(±0.4)℃ beneath the garment.To evaluate the garment's cooling efficiency,19 male subjects participated in an experimental procedure.The two modes,cooling on and off,were compared.Significant physiological differences were found between the two modes after minute 27(p<0.05)until the end of the recovery phase for the heart rate(maximum difference of 10 beats per minute)and the internal body temperature(maximum difference of 0.33℃).It was found that the modes also affected the subjects'perceptions.The ON-mode was associated with better well-being and thermal comfort,and reduced humidity sensation.Perceptions of exertion were lower in the ON-mode condition from minute 2.The findings provide strong evidence of the ability of this cooling garment to reduce heat stress in hot and humid conditions similar to those encountered in deep mines.

Perceptual learning for treating amblyopia in children based on activation of visual signal pathway Relationship of curative effects and time

BACKGROUND： Conventional methods （such as occlusion therapy, fine manipulation, complementary, and alternative medicine） take effects slowly, are time and labor consuming, and have uncertain curative effects in the treatment of amblyopia. Perceptual learning, a new method for treating amblyopia, improves the ability to process signals from the cerebral optic nerve system by specific visual stimulation and visual learning, as well as activation of the visual signal pathway utilizing brain nervous system plasticity. OBJECTIVE： This study investigated and evaluated the curative effects of perceptual learning, which can directionally increase brain plasticity, on the treatment of amblyopia in children. The relationship between curative effect and time was also analyzed. DESIGN： A self-control experiment. SETTING： Visual Science and Optometry Center, People＇s Hospital of Guangxi Zhuang Autonomous Region. PARTICIPANTS： A total of 125 amblyopic children （250 amblyopic eyes）, 73 males, 52 females, averaging （6±2） years of age, received treatment at the Visual Science and Optometry Center, People＇s Hospital of Guangxi Zhuang Autonomous Region between September 2006 and February 2007 and were recruited for this study. All children presented with no structural disease of the eyeballs. Written informed consent for therapeutic regiments was obtained from each child＇s parent. The protocol received approval from the Hospital＇s Ethics Committee. METHODS： Visual function was tested with a perceptual learning system （Research Center for Human Health and Development of Sun Yat-sen University, National Engineering Technique Research Center for Medical Care Implement） for visual noise, position noise, contour discrimination, contrast sensitivity, grating stereogram, and random-dot fusion. These tests helped to evaluate the efficiency of visual information processing of these children, and to determine the degree of defects of the optic nerve cells and the connections of visual cortical neurons. According to results of visual function tests, individualized treatment was adopted for each amblyopia patient using perceptual learning system. One course of treatment lasted one month, and treatment was performed twice every day with two training procedures （each training procedure lasted for ten minutes）. There was a ten-minute time interval between the two training procedures. The training treatment was performed in a quiet and dark environment. Visual acuity and recovery of visual function were tested every month. Original training procedure was continued or adjusted according to the results of visual function. MAIN OUTCOME MEASURES： Visual function change; relationship of curative effects and curative time. RESULTS： A total of 125 amblyopia children were included in the final analysis. The total efficiency of perceptual learning for treating amblyopia in children was 75.2%. Visual acuity began to greatly increase 3 months after treatment （P 〈 0.05）. Visual acuity was best corrected from 0.60 ± 0.23 before treatment to 0.86 ± 0.26 after treatment （P 〈 0.05）. The mean time to reach improved levels with curative effects was （2.82 ± 1.30） months, and to reach a basically cured level was （2.87 ±1.40） months. Percentage of improved visual acuity was the highest [98% （39/40）] in children that received 3 months of treatment and the lowest [55% （31/56）] in children that received 1 month of treatment （P 〈 0.05）. The percentage of basically cured levels with curative effects increased with length of learning time and was the greatest in children that received 4 months of treatment [67% （31/46）, P 〈 0.05]. CONCLUSION： Perceptual learning rapidly and remarkably improves visual function of amblyopia children; however, the curative effects are first apparent two and three months after intervention.

Recent development of perceptual image hashing

The easy generation, storage, transmission and reproduction of digital images have caused serious abuse and security problems. Assurance of the rightful ownership, integrity, and authenticity is a major concern to the academia as well as the industry. On the other hand, efficient search of the huge amount of images has become a great challenge. Image hashing is a technique suitable for use in image authentication and content based image retrieval （CBIR）. In this article, we review some representative image hashing techniques proposed in the recent years, with emphases on how to meet the conflicting requirements of perceptual robustness and security. Following a brief introduction to some earlier methods, we focus on a typical two-stage structure and some geometric-distortion resilient techniques. We then introduce two image hashing approaches developed in our own research, and reveal security problems in some existing methods due to the absence of secret keys in certain stage of the image feature extraction, or availability of a large quantity of images, keys, or the hash function to the adversary. More research efforts are needed in developing truly robust and secure image hashing techniques.

Influence of brittleness and confining stress on rock cuttability based on rock indentation tests

In order to understand the influence of brittleness and confining stress on rock cuttability,the indentation tests were carried out by a conical pick on the four types of rocks.Then,the experimental results were utilized to take regression analysis.The eight sets of normalized regression models were established for reflecting the relationships of peak indentation force(PIF)and specific energy(SE)with brittleness index and uniaxial confining stress.The regression analyses present that these regression models have good prediction performance.The regressive results indicate that brittleness indices and uniaxial confining stress conditions have non-linear effects on the rock cuttability that is determined by PIF and SE.Finally,the multilayer perceptual neural network was used to measure the importance weights of brittleness index and uniaxial confining stress upon the influence for rock cuttability.The results indicate that the uniaxial confining stress is more significant than brittleness index for influencing the rock cuttability.

A Novel Robust Watermarking Algorithm for Encrypted Medical Image Based on DTCWT-DCT and Chaotic Map

In order to solve the problem of patient information security protection in medical images,whilst also taking into consideration the unchangeable particularity of medical images to the lesion area and the need for medical images themselves to be protected,a novel robust watermarking algorithm for encrypted medical images based on dual-tree complex wavelet transform and discrete cosine transform(DTCWT-DCT)and chaotic map is proposed in this paper.First,DTCWT-DCT transformation was performed on medical images,and dot product was per-formed in relation to the transformation matrix and logistic map.Inverse transformation was undertaken to obtain encrypted medical images.Then,in the low-frequency part of the DTCWT-DCT transformation coefficient of the encrypted medical image,a set of 32 bits visual feature vectors that can effectively resist geometric attacks are found to be the feature vector of the encrypted medical image by using perceptual hashing.After that,different logistic initial values and growth parameters were set to encrypt the watermark,and zero-watermark technology was used to embed and extract the encrypted medical images by combining cryptography and third-party concepts.The proposed watermarking algorithm does not change the region of interest of medical images thus it does not affect the judgment of doctors.Additionally,the security of the algorithm is enhanced by using chaotic mapping,which is sensitive to the initial value in order to encrypt the medical image and the watermark.The simulation results show that the pro-posed algorithm has good homomorphism,which can not only protect the original medical image and the watermark information,but can also embed and extract the watermark directly in the encrypted image,eliminating the potential risk of decrypting the embedded watermark and extracting watermark.Compared with the recent related research,the proposed algorithm solves the contradiction between robustness and invisibility of the watermarking algorithm for encrypted medical images,and it has good results against both conventional attacks and geometric attacks.Under geometric attacks in particular,the proposed algorithm performs much better than existing algorithms.

ICC色彩管理中颜色转换的再现意图分析

ICC色彩管理中颜色转换的再现意图,有时也被学者们称之为转换目的或者是再现目的,它是颜色在进行色貌变换和色域映射时的选择依据,选择不同的再现意图,所得到的特性连接色空间值（PCS）不同,进而最后得到的颜色复制的效果也是不同的。因此,再现意图在色彩管理中是一个非常关键的概念,选择合适的再现意图才能得到用户所希望的颜色复制效果。国际色彩联盟ICC规定了四种再现意图：感知意图（perceptual intent）、