A Unified Hardware-based Threat Detector for AI Accelerators

The proliferation of AI technology gives rise to a variety of security threats, which significantly compromise the confidentiality and integrity of AI models and applications. Existing software-based solutions mainly target one specific attack, and require the implementation into the models, rendering them less practical. We design UniGuard, a novel unified and non-intrusive detection methodology to safeguard FPGA-based AI accelerators. The core idea of UniGuard is to harness power side-channel information generated during model inference to spot any anomaly. We employ a Time-to-Digital Converter to capture power fluctuations and train a supervised machine learning model to identify various types of threats. Evaluations demonstrate that UniGuard can achieve 94.0% attack detection accuracy, with high generalization over unknown or adaptive attacks and robustness against varied configurations (e.g., sensor frequency and location)

Mercury: An Automated Remote Side-channel Attack to Nvidia Deep Learning Accelerator

DNN accelerators have been widely deployed in many scenarios to speed up the inference process and reduce the energy consumption. One big concern about the usage of the accelerators is the confidentiality of the deployed models: model inference execution on the accelerators could leak side-channel information, which enables an adversary to preciously recover the model details. Such model extraction attacks can not only compromise the intellectual property of DNN models, but also facilitate some adversarial attacks. Although previous works have demonstrated a number of side-channel techniques to extract models from DNN accelerators, they are not practical for two reasons. (1) They only target simplified accelerator implementations, which have limited practicality in the real world. (2) They require heavy human analysis and domain knowledge. To overcome these limitations, this paper presents Mercury, the first automated remote side-channel attack against the off-the-shelf Nvidia DNN accelerator. The key insight of Mercury is to model the side-channel extraction process as a sequence-to-sequence problem. The adversary can leverage a time-to-digital converter (TDC) to remotely collect the power trace of the target model's inference. Then he uses a learning model to automatically recover the architecture details of the victim model from the power trace without any prior knowledge. The adversary can further use the attention mechanism to localize the leakage points that contribute most to the attack. Evaluation results indicate that Mercury can keep the error rate of model extraction below 1%

Excess Deaths of Gastrointestinal, Liver, and Pancreatic Diseases During the COVID-19 Pandemic in the United States

Objectives: To evaluate excess deaths of gastrointestinal, liver, and pancreatic diseases in the United States during the COVID-19 pandemic.Methods: We retrieved weekly death counts from National Vital Statistics System and fitted them with a quasi-Poisson regression model. Cause-specific excess deaths were calculated by the difference between observed and expected deaths with adjustment for temporal trend and seasonality. Demographic disparities and temporal-spatial patterns were evaluated for different diseases.Results: From March 2020 to September 2022, the increased mortality (measured by excess risks) for Clostridium difficile colitis, gastrointestinal hemorrhage, and acute pancreatitis were 35.9%; 24.8%; and 20.6% higher than the expected. For alcoholic liver disease, fibrosis/cirrhosis, and hepatic failure, the excess risks were 1.4–2.8 times higher among younger inhabitants than older inhabitants. The excess deaths of selected diseases were persistently observed across multiple epidemic waves with fluctuating trends for gastrointestinal hemorrhage and fibrosis/cirrhosis and an increasing trend for C. difficile colitis.Conclusion: The persistently observed excess deaths of digestive diseases highlights the importance for healthcare authorities to develop sustainable strategies in response to the long-term circulating of SARS-CoV-2 in the community

Distinct miRNAs associated with various clinical presentations of SARS-CoV-2 infection.

MicroRNAs (miRNAs) have been shown to play important roles in viral infections, but their associations with SARS-CoV-2 infection remain poorly understood. Here, we detected 85 differentially expressed miRNAs (DE-miRNAs) from 2,336 known and 361 novel miRNAs that were identified in 233 plasma samples from 61 healthy controls and 116 patients with COVID-19 using the high-throughput sequencing and computational analysis. These DE-miRNAs were associated with SASR-CoV-2 infection, disease severity, and viral persistence in the patients with COVID-19, respectively. Gene ontology and KEGG pathway analyses of the DE-miRNAs revealed their connections to viral infections, immune responses, and lung diseases. Finally, we established a machine learning model using the DE-miRNAs between various groups for classification of COVID-19 cases with different clinical presentations. Our findings may help understand the contribution of miRNAs to the pathogenesis of COVID-19 and identify potential biomarkers and molecular targets for diagnosis and treatment of SARS-CoV-2 infection

Improving Tomato Fruit Volatiles through Organic Instead of Inorganic Nutrient Solution by Precision Fertilization

This study investigated the effects of irrigation with a fully inorganic nutrient solution (control; NNNN) and an organic instead of an inorganic nutrient solution (OIINS) at the flowering–fruit setting (ONNN), fruit expanding (NONN), color turning (NNON), and harvest (NNNO) stages of the first spike on the type and content of tomato fruit volatiles to provide a theoretical basis for tomato aroma improvement and high-quality cultivation. Compared with the control (NNNN), the results showed that all OIINS-related treatments decreased the number of fruit volatiles and increased the relative content of common volatile compounds, characteristic effect compounds, aldehydes, and cis-3-hexenal. In particular, the relative order of performance of the OIINS-related treatments was NNNO > NNON > ONNN > NONN in terms of the relative content of characteristic compounds. For all treatments, the relative cis-3-hexenal and trans-2-hexenal percentages were 20.99–51.49% and 20.22–27.81%, respectively. Moreover, hexanal was only detected in tomato fruits under the NNNN and NNNO treatments. The effects of irrigation with OIINS on tomato fruit volatiles were related to the fruit developmental stage. At the mature stage, the organic nutrient solution was conducive to the accumulation of characteristic compounds and improved the fruit aroma quality

Multi-Span Greenhouse Energy Saving by External Insulation: System Design and Implementation

To address the issues of excessive heat loss from the roofs of multi-span greenhouses and high energy consumption for heating during winter production, we propose an approach for the external insulation of the roof of multi-span glass greenhouses and have developed an external insulation system (EIS) to practice this approach. The system achieved full coverage of the greenhouse roof through mechanized unfurling and furling of external thermal blankets, thereby achieving energy-saving insulation. This paper describes the overall design and working method of the EIS, providing detailed design and structural parameters for critical components such as the traction rope transmission mechanism and the rail-type sealing structure. Through a system verification experiment, the specifications of the traction rope were determined and the rationality of the EIS’s thermal blanket unfurling and furling time was confirmed. An insulation performance experiment indicated that the average heat flux of the greenhouse roof covered with the external thermal blanket over 14 continuous nights was 54.2 W/m2, compared with 198.6 W/m2 for a single-layer glass roof. Covering the roof with the external thermal blanket reduced heat loss from the glass roof by 72.7%. The average heat flux of the roof of the Venlo-type multi-span greenhouse with double-layer internal insulation was 99.9 W/m2 during the same period, indicating that the heat loss from the roof using external insulation was only 50.3%. This study provides a novel thermal insulation approach and an energy-saving system for multi-span greenhouses

Maternal low thyroxin levels are associated with adverse pregnancy outcomes in a Chinese population

<div><p>Although thyroid dysfunction in early pregnancy may have adverse effects on pregnancy outcomes, few studies have examined the relationship between maternal low free thyroxin (FT4) levels in both first and third trimesters of pregnancy and the incidence of adverse pregnancy outcomes. We hypothesized that low FT4 levels in either first or third trimesters of pregnancy may have different effects on pregnancy outcomes. The study included 6,031 mothers who provided both first and third pregnancy serum samples for analyses of thyroid function. Adverse pregnancy outcomes, such as gestational diabetes mellitus (GDM), pregnancy-induced hypertension and preeclampsia, were diagnosed using the oral glucose tolerance test, blood pressure and urine protein test. Serum metabolites like adenosine and its analogues were identified using hydrophilic interaction liquid chromatography (HILIC)-tandem mass spectrometry (MS/MS). The incidence of hypothyroidism in pregnant women tended to increase with age and pre-pregnancy body mass index (BMI). The incidence of GDM was negatively correlated with maternal FT4 levels during early pregnancy while the incidence of preeclampsia was negatively correlated with maternal FT4 levels during late pregnancy. The incidence of pregnancy-induced hypertension was not significantly correlated with maternal FT4 levels. The women who had isolated maternal hypothyroxemia (IMH) in the third trimester of pregnancy had an increased risk of developing preeclampsia. Some metabolites like adenosine and its analogues in the serum were significantly changed in pregnant mothers with IMH. In conclusion, low FT4 levels during pregnancy are a risk factor for GDM and preeclampsia. Adenosine and its analogues may be important bridges between IMH and preeclampsia.</p></div

Dysregulation of miR-6868-5p/FOXM1 circuit contributes to colorectal cancer angiogenesis

Abstract Background Transcription factor forkhead box M1 (FOXM1) is a crucial regulator in colorectal cancer (CRC) progression. However, the regulatory mechanisms causing dysregulation of FOXM1 in CRC remain unclear. Methods Dual-luciferase reporter assay was conducted to determine FOXM1 as miR-6868-5p target. The function of miR-6868-5p and FOXM1 in CRC angiogenesis was verified in vitro. Intratumoral injection model was constructed to explore the effect of miR-6868-5p on angiogenesis in vivo. Chromatin immunoprecipitation assays were used to assess direct binding of H3K27me3 to the miR-6868 promoter. Results Through integrated analysis, we identified miR-6868-5p as the potent regulator of FOXM1. Overexpression of miR-6868-5p in CRC cells inhibited the angiogenic properties of co-cultured endothelial cells, whereas silencing of miR-6868-5p had opposite effects. In vivo delivery of miR-6868-5p blocked tumor angiogenesis in nude mice, resulting in tumor growth inhibition. Rescue of FOXM1 reversed the effect of miR-6868-5p on tumor angiogenesis. Further mechanistic study revealed that FOXM1 promoted the production of IL-8, which was responsible for the miR-6868-5p/FOXM1 axis-regulated angiogenesis. Reciprocally, FOXM1 inhibited miR-6868-5p expression through EZH2-mediated H3K27me3 on miR-6868-5p promoter, thus forming a feedback circuit. Clinically, the level of miR-6868-5p was downregulated in CRC tissues and inversely correlated with microvessel density as well as levels of FOXM1 and IL-8 in tumor specimens. Conclusions Together, these data identify miR-6868-5p as a novel determinant of FOXM1 expression and establish a miR-6868-5p/FOXM1 regulatory circuit for CRC angiogenesis, providing potential target for CRC treatment

Specific reference ranges of FT4 during first and third trimester of pregnancy.

<p>Specific reference ranges of FT4 during first and third trimester of pregnancy.</p