Transportation + Street Trees:: Effect of the Urban Design Industry's Roadside Landscape Improvement Standards on Driver and Pedestrian Performance

The purpose of the research is to examine the effect of industry standard urban design treatments for streetscaping of Main Streets on traffic accident rates and the pedestrian's perception of accessibility and safety. Existing research (Rosenblatt, Bahar) has indicated that the use of roadside landscaping is reducing vehicular traffic accident rates both in terms of frequency and severity. This paper identifies the next research steps being developed at Texas A&M University which will create better understanding of the impact of specific streetscape design treatment on pedestrian safety and accessibility. These standards will be evaluated for the effect on bicycle, pedestrian and wheelchair performance within the treated corridors

Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness

Adversarial training (AT) for robust representation learning and self-supervised learning (SSL) for unsupervised representation learning are two active research fields. Integrating AT into SSL, multiple prior works have accomplished a highly significant yet challenging task: learning robust representation without labels. A widely used framework is adversarial contrastive learning which couples AT and SSL, and thus constitute a very complex optimization problem. Inspired by the divide-and-conquer philosophy, we conjecture that it might be simplified as well as improved by solving two sub-problems: non-robust SSL and pseudo-supervised AT. This motivation shifts the focus of the task from seeking an optimal integrating strategy for a coupled problem to finding sub-solutions for sub-problems. With this said, this work discards prior practices of directly introducing AT to SSL frameworks and proposed a two-stage framework termed Decoupled Adversarial Contrastive Learning (DeACL). Extensive experimental results demonstrate that our DeACL achieves SOTA self-supervised adversarial robustness while significantly reducing the training time, which validates its effectiveness and efficiency. Moreover, our DeACL constitutes a more explainable solution, and its success also bridges the gap with semi-supervised AT for exploiting unlabeled samples for robust representation learning. The code is publicly accessible at https://github.com/pantheon5100/DeACL.Comment: Accepted by ECCV 2022 oral presentatio

Human brain anatomy reflects separable genetic and environmental components of socioeconomic status

Socioeconomic status (SES) correlates with brain structure, a relation of interest given the long-observed relations of SES to cognitive abilities and health. Yet, major questions remain open, in particular, the pattern of causality that underlies this relation. In an unprecedently large study, here, we assess genetic and environmental contributions to SES differences in neuroanatomy. We first establish robust SES–gray matter relations across a number of brain regions, cortical and subcortical. These regional correlates are parsed into predominantly genetic factors and those potentially due to the environment. We show that genetic effects are stronger in some areas (prefrontal cortex, insula) than others. In areas showing less genetic effect (cerebellum, lateral temporal), environmental factors are likely to be influential. Our results imply a complex interplay of genetic and environmental factors that influence the SES-brain relation and may eventually provide insights relevant to policy

The C-Fern (Ceratopteris richardii) Genome: Insights Into Plant Genome Evolution With the First Partial Homosporous Fern Genome Assembly

Ferns are notorious for possessing large genomes and numerous chromosomes. Despite decades of speculation, the processes underlying the expansive genomes of ferns are unclear, largely due to the absence of a sequenced homosporous fern genome. The lack of this crucial resource has not only hindered investigations of evolutionary processes responsible for the unusual genome characteristics of homosporous ferns, but also impeded synthesis of genome evolution across land plants. Here, we used the model fern species Ceratopteris richardii to address the processes (e.g., polyploidy, spread of repeat elements) by which the large genomes and high chromosome numbers typical of homosporous ferns may have evolved and have been maintained. We directly compared repeat compositions in species spanning the green plant tree of life and a diversity of genome sizes, as well as both short- and long-read-based assemblies of Ceratopteris. We found evidence consistent with a single ancient polyploidy event in the evolutionary history of Ceratopteris based on both genomic and cytogenetic data, and on repeat proportions similar to those found in large flowering plant genomes. This study provides a major stepping-stone in the understanding of land plant evolutionary genomics by providing the first homosporous fern reference genome, as well as insights into the processes underlying the formation of these massive genomes

DifAugGAN: A Practical Diffusion-style Data Augmentation for GAN-based Single Image Super-resolution

It is well known the adversarial optimization of GAN-based image super-resolution (SR) methods makes the preceding SR model generate unpleasant and undesirable artifacts, leading to large distortion. We attribute the cause of such distortions to the poor calibration of the discriminator, which hampers its ability to provide meaningful feedback to the generator for learning high-quality images. To address this problem, we propose a simple but non-travel diffusion-style data augmentation scheme for current GAN-based SR methods, known as DifAugGAN. It involves adapting the diffusion process in generative diffusion models for improving the calibration of the discriminator during training motivated by the successes of data augmentation schemes in the field to achieve good calibration. Our DifAugGAN can be a Plug-and-Play strategy for current GAN-based SISR methods to improve the calibration of the discriminator and thus improve SR performance. Extensive experimental evaluations demonstrate the superiority of DifAugGAN over state-of-the-art GAN-based SISR methods across both synthetic and real-world datasets, showcasing notable advancements in both qualitative and quantitative results

A new classification system for bacterial Rieske non-heme iron aromatic ring-hydroxylating oxygenases

<p>Abstract</p> <p>Background</p> <p>Rieske non-heme iron aromatic ring-hydroxylating oxygenases (RHOs) are multi-component enzyme systems that are remarkably diverse in bacteria isolated from diverse habitats. Since the first classification in 1990, there has been a need to devise a new classification scheme for these enzymes because many RHOs have been discovered, which do not belong to any group in the previous classification. Here, we present a scheme for classification of RHOs reflecting new sequence information and interactions between RHO enzyme components.</p> <p>Result</p> <p>We have analyzed a total of 130 RHO enzymes in which 25 well-characterized RHO enzymes were used as standards to test our hypothesis for the proposed classification system. From the sequence analysis of electron transport chain (ETC) components of the standard RHOs, we extracted classification keys that reflect not only the phylogenetic affiliation within each component but also relationship among components. Oxygenase components of standard RHOs were phylogenetically classified into 10 groups with the classification keys derived from ETC components. This phylogenetic classification scheme was converted to a new systematic classification consisting of 5 distinct types. The new classification system was statistically examined to justify its stability. Type I represents two-component RHO systems that consist of an oxygenase and an FNR_C-type reductase. Type II contains other two-component RHO systems that consist of an oxygenase and an FNR_N-type reductase. Type III represents a group of three-component RHO systems that consist of an oxygenase, a [2Fe-2S]-type ferredoxin and an FNR_N-type reductase. Type IV represents another three-component systems that consist of oxygenase, [2Fe-2S]-type ferredoxin and GR-type reductase. Type V represents another different three-component systems that consist of an oxygenase, a [3Fe-4S]-type ferredoxin and a GR-type reductase.</p> <p>Conclusion</p> <p>The new classification system provides the following features. First, the new classification system analyzes RHO enzymes as a whole. RwithSecond, the new classification system is not static but responds dynamically to the growing pool of RHO enzymes. Third, our classification can be applied reliably to the classification of incomplete RHOs. Fourth, the classification has direct applicability to experimental work. Fifth, the system provides new insights into the evolution of RHO systems based on enzyme interaction.</p

Antipsychotic Use in Pregnancy: Patient Mental Health Challenges, Teratogenicity, Pregnancy Complications, and Postnatal Risks

Pregnant women constitute a vulnerable population, with 25.3% of pregnant women classified as suffering from a psychiatric disorder. Since childbearing age typically aligns with the onset of mental health disorders, it is of utmost importance to consider the effects that antipsychotic drugs have on pregnant women and their developing fetus. However, the induction of pharmacological treatment during pregnancy may pose significant risks to the developing fetus. Antipsychotics are typically introduced when the nonpharmacologic approaches fail to produce desired effects or when the risks outweigh the benefits from continuing without treatment or the risks from exposing the fetus to medication. Early studies of pregnant women with schizophrenia showed an increase in perinatal malformations and deaths among their newborns. Similar to schizophrenia, women with bipolar disorder have an increased risk of relapse in antepartum and postpartum periods. It is known that antipsychotic medications can readily cross the placenta, and exposure to antipsychotic medication during pregnancy is associated with potential teratogenicity. Potential risks associated with antipsychotic use in pregnant women include congenital abnormalities, preterm birth, and metabolic disturbance, which could potentially lead to abnormal fetal growth. The complex decision-making process for treating psychosis in pregnant women must evaluate the risks and benefits of antipsychotic drugs

Multipole interaction between atoms and their photonic environment

Macroscopic field quantization is presented for a nondispersive photonic dielectric environment, both in the absence and presence of guest atoms. Starting with a minimal-coupling Lagrangian, a careful look at functional derivatives shows how to obtain Maxwell's equations before and after choosing a suitable gauge. A Hamiltonian is derived with a multipolar interaction between the guest atoms and the electromagnetic field. Canonical variables and fields are determined and in particular the field canonically conjugate to the vector potential is identified by functional differentiation as minus the full displacement field. An important result is that inside the dielectric a dipole couples to a field that is neither the (transverse) electric nor the macroscopic displacement field. The dielectric function is different from the bulk dielectric function at the position of the dipole, so that local-field effects must be taken into account.Comment: 17 pages, to be published in Physical Review