Endocide-Induced Abnormal Growth Forms of Invasive Giant Salvinia (Salvinia molesta)

Giant salvinia (Salvinia molesta) is one of the most noxious invasive species in the world. The fern is known to have primary, secondary, and tertiary growth forms, which are also commonly hypothesized as growth stages. The identification of these forms is primarily based on the size and folding status of the floating leaves. However, we identified 12 forms in the greenhouse and the field. Our experiments showed that the folding of floating leaves is a reversible trait dependent on water access. The floating leaves quickly fold in response to water shortage, reducing water loss and needs, decreasing growth, and avoiding trichome damage. The leaves re-open to allow trichomes repel water and enhance growth when having adequate water supply. Larger secondary or tertiary forms do not produce small-leaf primary forms without high intensity stress. These results do not support the hypothesis that three growth forms represent sequential growth stages. The abnormal small-leaf forms are the result of endocide-induced autotoxicity and some of them never grow into other forms. The development of abnormal forms and reversible leaf folding strategy in response to high stress along with rapid asexual reproduction are major adaptive traits contributing to the invasiveness of S. molesta

Regulations to Respond to the Potential Benefits and Perils of SelfDriving Cars Analysis and Recommendations for Advancing Equity and Environmental Sustainability

The mobility system in the United States is unsafe, inequitable, and environmentally destructive. Most Americans rely on personally owned, individually occupied, and gas-powered cars—a status quo that leads to tens of thousands of people dying each year in collisions, creates barriers to employment and other opportunities for people of color and people with low incomes, and maintains a resource intensive transportation system that contributes to climate change and spurs sprawling land uses that destroy ecologies. Autonomous vehicles (AVs)—self-driving cars that can travel along publicly accessible streets some or all of the time without human involvement—could help mitigate these problems, if they are implemented in a thoughtful, well-regulated manner. However, if deployed haphazardly with inadequate oversight and regulation, they could produce even worse inequities than those caused by the current system.To evaluate the current landscape for AV deployment and use in the United States, we conducted a study focusing on automobile-sized AVs designed for passenger use as opposed to other types of AVs that could be used for public transit service or freight. Through a scholarship review, a scan of legislation nationwide, and interviews with stakeholders, we examine key potential benefits that AVs could generate, as well as the problems they could exacerbate. Carefully designed regulations could help ensure that these new technologies improve access to mobility and reduce pollution

Pentimento: Data Remanence in Cloud FPGAs

Cloud FPGAs strike an alluring balance between computational efficiency, energy efficiency, and cost. It is the flexibility of the FPGA architecture that enables these benefits, but that very same flexibility that exposes new security vulnerabilities. We show that a remote attacker can recover "FPGA pentimenti" - long-removed secret data belonging to a prior user of a cloud FPGA. The sensitive data constituting an FPGA pentimento is an analog imprint from bias temperature instability (BTI) effects on the underlying transistors. We demonstrate how this slight degradation can be measured using a time-to-digital (TDC) converter when an adversary programs one into the target cloud FPGA. This technique allows an attacker to ascertain previously safe information on cloud FPGAs, even after it is no longer explicitly present. Notably, it can allow an attacker who knows a non-secret "skeleton" (the physical structure, but not the contents) of the victim's design to (1) extract proprietary details from an encrypted FPGA design image available on the AWS marketplace and (2) recover data loaded at runtime by a previous user of a cloud FPGA using a known design. Our experiments show that BTI degradation (burn-in) and recovery are measurable and constitute a security threat to commercial cloud FPGAs.Comment: 17 Pages, 8 Figure

Appeal of tobacco quitline services among low-income smokers

INTRODUCTION: State tobacco quitlines are delivering cessation assistance through an increasingly diverse range of channels. However, offerings vary from state to state, many smokers are unaware of what is available, and it is not yet clear how much demand exists for different types of assistance. In particular, the demand for online and digital cessation interventions among low-income smokers, who bear a disproportionate burden of tobacco-related disease, is not well understood. METHODS: We examined interest in using 13 tobacco quitline services in a racially diverse sample of 1,605 low-income smokers in 9 states who had called a 2-1-1 helpline and participated in an ongoing intervention trial from June 2020 through September 2022. We classified services as standard (used by ≥90% of state quitlines [eg, calls from a quit coach, nicotine replacement therapy, printed cessation booklets]) or nonstandard (mobile app, personalized web, personalized text, online chat with quit coach). RESULTS: Interest in nonstandard services was high. Half or more of the sample reported being very or somewhat interested in a mobile app (65%), a personalized web program (59%), or chatting online with quit coaches (49%) to help them quit. In multivariable regression analyses, younger smokers were more interested than older smokers in digital and online cessation services, as were women and smokers with greater nicotine dependence. CONCLUSION: On average, participants were very interested in at least 3 different cessation services, suggesting that bundled or combination interventions might be designed to appeal to different groups of low-income smokers. Findings provide some initial hints about potential subgroups and the services they might use in a rapidly changing landscape of behavioral interventions for smoking cessation

Tailor: Altering Skip Connections for Resource-Efficient Inference

Deep neural networks use skip connections to improve training convergence. However, these skip connections are costly in hardware, requiring extra buffers and increasing on- and off-chip memory utilization and bandwidth requirements. In this paper, we show that skip connections can be optimized for hardware when tackled with a hardware-software codesign approach. We argue that while a network's skip connections are needed for the network to learn, they can later be removed or shortened to provide a more hardware efficient implementation with minimal to no accuracy loss. We introduce Tailor, a codesign tool whose hardware-aware training algorithm gradually removes or shortens a fully trained network's skip connections to lower their hardware cost. Tailor improves resource utilization by up to 34% for BRAMs, 13% for FFs, and 16% for LUTs for on-chip, dataflow-style architectures. Tailor increases performance by 30% and reduces memory bandwidth by 45% for a 2D processing element array architecture

The Public Repository of Xenografts enables discovery and randomized phase II-like trials in mice

More than 90% of drugs with preclinical activity fail in human trials, largely due to insufficient efficacy. We hypothesized that adequately powered trials of patient-derived xenografts (PDX) in mice could efficiently define therapeutic activity across heterogeneous tumors. To address this hypothesis, we established a large, publicly available repository of well-characterized leukemia and lymphoma PDXs that undergo orthotopic engraftment, called the Public Repository of Xenografts (PRoXe). PRoXe includes all de-identified information relevant to the primary specimens and the PDXs derived from them. Using this repository, we demonstrate that large studies of acute leukemia PDXs that mimic human randomized clinical trials can characterize drug efficacy and generate transcriptional, functional, and proteomic biomarkers in both treatment-naive and relapsed/refractory disease

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead