Modeling Deep Learning Based Privacy Attacks on Physical Mail

Mail privacy protection aims to prevent unauthorized access to hidden content within an envelope since normal paper envelopes are not as safe as we think. In this paper, for the first time, we show that with a well designed deep learning model, the hidden content may be largely recovered without opening the envelope. We start by modeling deep learning-based privacy attacks on physical mail content as learning the mapping from the camera-captured envelope front face image to the hidden content, then we explicitly model the mapping as a combination of perspective transformation, image dehazing and denoising using a deep convolutional neural network, named Neural-STE (See-Through-Envelope). We show experimentally that hidden content details, such as texture and image structure, can be clearly recovered. Finally, our formulation and model allow us to design envelopes that can counter deep learning-based privacy attacks on physical mail.Comment: Source code: https://github.com/BingyaoHuang/Neural-ST

Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models

In this paper, we identify a cultural dominance issue within large language models (LLMs) due to the predominant use of English data in model training (e.g. ChatGPT). LLMs often provide inappropriate English-culture-related answers that are not relevant to the expected culture when users ask in non-English languages. To systematically evaluate the cultural dominance issue, we build a benchmark that consists of both concrete (e.g. holidays and songs) and abstract (e.g. values and opinions) cultural objects. Empirical results show that the representative GPT models suffer from the culture dominance problem, where GPT-4 is the most affected while text-davinci-003 suffers the least from this problem. Our study emphasizes the need for critical examination of cultural dominance and ethical consideration in their development and deployment. We show two straightforward methods in model development (i.e. pretraining on more diverse data) and deployment (e.g. culture-aware prompting) can significantly mitigate the cultural dominance issue in LLMs

A New Species of the Genus Sinomicrurus Slowinski, Boundy and Lawson, 2001 (Squamata: Elapidae) from Hainan Province, China

A new species of the coral snake genus Sinomicrurus is described based on four specimens from southern Hainan Island (three specimens from Tianchi, Jianfengling National Nature Reserve, one specimen from Diaoluoshan National Nature Reserve), Hainan Province, China. Morphologically, the new species is rather similar to Sinomicrurus kelloggi. However, it is distinct from S. kelloggi by the pattern on the head, the head length, head length/width, the number of infralabial scales, number of bands on dorsal body, and number of blotches on the belly

Analysis of the Association between Intestinal Microflora and Long-lived Elderly People

The intestinal microbiota is the cornerstone of the human intestinal microecosystem and plays an unnegligible role in the growth and health maintenance of the human body. In recent years, many studies have been committed to exploring the potential connection of gut flora and the elderly population. The changes of gut flora are affected by various factors such as age increase, disease, medication, living habits, nutritional structure, and the intestinal flora is expected to be applied to the comprehensive evaluation of elderly health and longevity in the future. Based on this, the research progress of the general elderly and its related influencing factors

Magnon-mediated interlayer coupling in an all-antiferromagnetic junction

The interlayer coupling mediated by fermions in ferromagnets brings about parallel and anti-parallel magnetization orientations of two magnetic layers, resulting in the giant magnetoresistance, which forms the foundation in spintronics and accelerates the development of information technology. However, the interlayer coupling mediated by another kind of quasi-particle, boson, is still lacking. Here we demonstrate such a static interlayer coupling at room temperature in an antiferromagnetic junction Fe2O3/Cr2O3/Fe2O3, where the two antiferromagnetic Fe2O3 layers are functional materials and the antiferromagnetic Cr2O3 layer serves as a spacer. The N\'eel vectors in the top and bottom Fe2O3 are strongly orthogonally coupled, which is bridged by a typical bosonic excitation (magnon) in the Cr2O3 spacer. Such an orthogonally coupling exceeds the category of traditional collinear interlayer coupling via fermions in ground state, reflecting the fluctuating nature of the magnons, as supported by our magnon quantum well model. Besides the fundamental significance on the quasi-particle-mediated interaction, the strong coupling in an antiferromagnetic magnon junction makes it a realistic candidate for practical antiferromagnetic spintronics and magnonics with ultrahigh-density integration.Comment: 19 pages, 4 figure

Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration

Motor deficits are observed in Alzheimer’s disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans

Formation of Complexes at Plasmodesmata for Potyvirus Intercellular Movement Is Mediated by the Viral Protein P3N-PIPO

Intercellular transport of viruses through cytoplasmic connections, termed plasmodesmata (PD), is essential for systemic infection in plants by viruses. Previous genetic and ultrastructural data revealed that the potyvirus cyclindrical inclusion (CI) protein is directly involved in cell-to-cell movement, likely through the formation of conical structures anchored to and extended through PD. In this study, we demonstrate that plasmodesmatal localization of CI in N. benthamiana leaf cells is modulated by the recently discovered potyviral protein, P3N-PIPO, in a CI:P3N-PIPO ratio-dependent manner. We show that P3N-PIPO is a PD-located protein that physically interacts with CI in planta. The early secretory pathway, rather than the actomyosin motility system, is required for the delivery of P3N-PIPO and CI to PD. Moreover, CI mutations that disrupt virus cell-to-cell movement compromise PD-localization capacity. These data suggest that the CI and P3N-PIPO complex coordinates the formation of PD-associated structures that facilitate the intercellular movement of potyviruses in infected plants