Palmprint Recognition in Uncontrolled and Uncooperative Environment

Online palmprint recognition and latent palmprint identification are two branches of palmprint studies. The former uses middle-resolution images collected by a digital camera in a well-controlled or contact-based environment with user cooperation for commercial applications and the latter uses high-resolution latent palmprints collected in crime scenes for forensic investigation. However, these two branches do not cover some palmprint images which have the potential for forensic investigation. Due to the prevalence of smartphone and consumer camera, more evidence is in the form of digital images taken in uncontrolled and uncooperative environment, e.g., child pornographic images and terrorist images, where the criminals commonly hide or cover their face. However, their palms can be observable. To study palmprint identification on images collected in uncontrolled and uncooperative environment, a new palmprint database is established and an end-to-end deep learning algorithm is proposed. The new database named NTU Palmprints from the Internet (NTU-PI-v1) contains 7881 images from 2035 palms collected from the Internet. The proposed algorithm consists of an alignment network and a feature extraction network and is end-to-end trainable. The proposed algorithm is compared with the state-of-the-art online palmprint recognition methods and evaluated on three public contactless palmprint databases, IITD, CASIA, and PolyU and two new databases, NTU-PI-v1 and NTU contactless palmprint database. The experimental results showed that the proposed algorithm outperforms the existing palmprint recognition methods.Comment: Accepted in the IEEE Transactions on Information Forensics and Securit

Enlarging the Stokes Shift by Weakening the π-Conjugation of Cyanines for High Signal-To-Noise Ratiometric Imaging

The signal-to-noise ratio (SNR) is one of the key features of a fluorescent probe and one that often defines its potential utility for in vivo labeling and analyte detection applications. Here, it is reported that introducing a pyridine group into traditional cyanine-7 dyes in an asymmetric manner provides a series of tunable NIR fluorescent dyes (Cy-Mu-7) characterized by enhanced Stokes shifts (≈230 nm) compared to the parent cyanine 7 dye (nm). The observed Stokes shift increase is ascribed to symmetry breaking of the Cy-Mu-7 core and a reduction in the extent of conjugation. The fluorescence signals of the Cy-Mu-7 dyes are enhanced upon confinement within the hydrophobic cavity of albumin or via spontaneous encapsulation within micelles in aqueous media. Utilizing the Cy-Mu-7, ultra-fast in vivo kidney labeling in mice is realized, and it is found that the liver injury will aggravate the burden of kidney by monitoring the fluorescence intensity ratio of kidney to liver. In addition, Cy-Mu-7 could be used as efficient chemiluminescence resonance energy transfer acceptor for the reaction between H O and bisoxalate. The potential utility of Cy-Mu-7 is illustrated via direct monitoring fluctuations in endogenous H O levels in a mouse model to mimic emergency room trauma

Soil Abiotic Properties and Plant Functional Traits Mediate Associations Between Soil Microbial and Plant Communities During a Secondary Forest Succession on the Loess Plateau

In the context of secondary forest succession, aboveground-belowground interactions are known to affect the dynamics and functional structure of plant communities. However, the links between soil microbial communities, soil abiotic properties, plant functional traits in the case of semi-arid and arid ecosystems, are unclear. In this study, we investigated the changes in soil microbial species diversity and community composition, and the corresponding effects of soil abiotic properties and plant functional traits, during a ≥150-year secondary forest succession on the Loess Plateau, which represents a typical semi-arid ecosystem in China. Plant community fragments were assigned to six successional stages: 1–4, 4–8, 8–15, 15–50, 50–100, and 100–150 years after abandonment. Bacterial and fungal communities were analyzed by high-throughput sequencing of the V4 hypervariable region of the 16S rRNA gene and the internal transcribed spacer (ITS2) region of the rRNA operon, respectively. A multivariate variation-partitioning approach was used to estimate the contributions of soil properties and plant traits to the observed microbial community composition. We found considerable differences in bacterial and fungal community compositions between the early (S1–S3) and later (S4–S6) successional stages. In total, 18 and 12 unique families were, respectively, obtained for bacteria and fungi, as indicators of microbial community succession across the six stages. Bacterial alpha diversity was positively correlated with plant species alpha diversity, while fungal diversity was negatively correlated with plant species diversity. Certain fungal and bacterial taxa appeared to be associated with the occurrence of dominant plant species at different successional stages. Soil properties (pH, total N, total C, NH4-N, NO3-N, and PO4-P concentrations) and plant traits explained 63.80% and 56.68% of total variance in bacterial and fungal community compositions, respectively. These results indicate that soil microbial communities are coupled with plant communities via the mediation of microbial species diversity and community composition over a long-term secondary forest succession in the semi-arid ecosystem. The bacterial and fungal communities show distinct patterns in response to plant community succession, according to both soil abiotic properties and plant functional traits

3D visual simulation of individual and crowd behavior in earthquake evacuation

Simulation of behaviors in emergencies is an interesting subject that helps to understand evacuation processes and to give out warnings for contingency plans. Individual and crowd behaviors in the earthquake are different from those under normal circumstances. Panic will spread in the crowd and cause chaos. Without considering emotion, most existing behavioral simulation methods analyze the movement of people from the point of view of mechanics. After summarizing existing studies, a new simulation method is discussed in this paper. First, 3D virtual scenes are constructed with the proposed platform. Second, an individual cognitive architecture, which integrates perception, motivation, behavior, emotion, and personality, is proposed. Typical behaviors are analyzed and individual evacuation animations are realized with data captured by motion capture devices. Quantitative descriptions are presented to describe emotional changes in individual evacuation. Facial expression animation is used to represent individuals’ emotions. Finally, a crowd behavior model is designed on the basis of a social force model. Experiments are carried out to validate the proposed method. Results showed that individuals’ behavior, emotional changes, and crowd aggregation can be well simulated. Users can learn evacuation processes from many angles. The method can be an intuitional approach to safety education and crowd management

Both low and high levels of low-density lipoprotein cholesterol are risk factors for diabetes diagnosis in Chinese adults

Aims: This study aimed to investigate whether both high and low levels of low-density lipoprotein cholesterol (LDL-C), i.e., hypercholesterolemia and hypocholesterolemia, were associated with diabetes in Chinese adults. Methods: This cross-sectional study included 22,557 Chinese adults. The LDL-C reference interval was determined from a healthy sub-cohort. Associations between hypocholesterolemia or hypercholesterolemia with diabetes were analyzed using binary logistic regression. Results: The LDL-C reference interval was 1.48–3.77 mmol/L (57.23–145.78 mg/dL). Therefore, hypocholesterolemia, normocholesterolemia, and hypercholesterolemia were defined as an LDL-C concentration of 3.77 mmol/L, respectively. Prevalence of diabetes was higher in people with hypocholesterolemia or hypercholesterolemia than that in people with normocholesterolemia. Hypocholesterolemia was associated with an increased multivariable-adjusted risk for diabetes diagnosis (odds ratio, 1.57; 95% confidence interval, 1.18–2.08), and so was hypercholesterolemia (odds ratio, 1.29; 95% confidence interval, 1.10–1.51). The results remained significant after exclusion of those who took lipid-lowering drugs from the analysis. Conclusions: This study demonstrated that both low and high levels of LDL-C were associated with a higher risk of diabetes diagnosis. Patients with either high or low LDL-C may need to be closely monitored for the risk of diabetes

A perception-based emotion contagion model in crowd emergent evacuation simulation

With the increasing number of emergencies, the crowd simulation technology has attracted wide attention in recent years. Existing emergencies have shown that individuals are easy to be influenced by other’s emotion during the evacuation. This will make it easier for people to aggregate together and increase security risks. Some of the existing evacuation models without considering emotion are therefore not suitable for describing crowd behaviors in emergencies. We propose a perception-based emotion contagion model and use multi-agent technology to simulate the crowd behaviors. Navigation points are introduced to guide the movement of the agents. Based on the proposed model, a prototype simulation system for crowd emotion contagion is developed. The comparative simulation experiments verify that the model can effectively deduct the evacuation time and crowd emotion contagion. The proposed model could be an assistant analysis method for crowd management in emergencies