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Anne E. Watkins, Eli P. Fenichel, Daniel M. Weinberger, Chantal B.F. Vogels, Doug E. Brackney, Arnau Casanovas-Massana, Melissa Campbell, John Fournier, Santos Bermejo, Rupak Datta, Charles S. Dela Cruz, Shelli F. Farhadian, Akiko Iwasaki, Akiko Iwasaki, Albert I. Ko, Nathan D. Grubaugh, Anne L. Wyllie | As saliva collection is non-invasive, extending this strategy to test pooled saliva samples from multiple individuals could thus provide a simple method to expand testing capacity. |
48 Citations | The composition of saliva in post- and perimenopausal women was found to be estrogen-dependent. |
63 Citations | Therefore, an in vivo test design for estrogenicity should include an analysis of several estrogen sensitive parameters in different estrogen sensitive tissues. |
26 Citations | The method was found to be suitable for the detection of mixtures of saliva and semen in conjunction with the Brentamine test for the detection of acid phosphatase. |
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How does transfer learning improve the efficiency of edge computing for face recognition?
10 answers
Transfer learning significantly enhances the efficiency of edge computing for face recognition by leveraging pre-trained models to achieve high accuracy with less computational resource requirement and quicker adaptation to new, specific tasks. This approach is particularly beneficial in edge computing environments where computational resources are limited, and latency is a critical factor.
The EdgeFace network, inspired by the hybrid architecture of EdgeNeXt, demonstrates how a lightweight model can achieve state-of-the-art face recognition results on edge devices, benefiting from a combination of CNN and Transformer models optimized through transfer learning techniques. Similarly, the use of transfer learning in facial expression recognition (FER) systems, as shown with the EfficientNet architectures, allows for high accuracy in recognizing facial expressions from small datasets, showcasing the method's power in enhancing model performance without the need for extensive data.
In the context of smart UAV delivery systems, a multi-UAV-edge collaborative framework utilizes feature extraction and storage on edge devices, showcasing how transfer learning can streamline the identification process in real-world applications by efficiently handling face recognition tasks at the edge. Moreover, the application of transfer learning in optimizing models for specific small and medium-sized datasets, as seen in the comparison of VGG16 and MobileNet's performance, further illustrates its role in improving the efficiency and accuracy of face recognition systems in edge computing scenarios.
Additionally, the integration of transfer learning with novel architectures, such as the combination of attention modules and lightweight backbone networks in an edge-cloud joint inference architecture, demonstrates a balanced approach to achieving high classification accuracy while maintaining low-latency inference, crucial for edge computing applications.
In summary, transfer learning enhances the efficiency of edge computing for face recognition by enabling the use of compact, yet powerful models that require less computational power and can be quickly adapted to new tasks, thereby improving both the speed and accuracy of face recognition on edge devices.What percent of blood plasma contains lead?5 answers
Lead concentration in blood plasma is a crucial aspect of assessing human exposure to lead. Studies have shown that lead plasma concentration is generally less than 5% of total blood lead, representing the biologically active fraction capable of crossing cell membranes. The bioavailability of lead in blood plasma has been predicted to range from 78-93%, indicating its suitability as a biomarker for lead exposure even at low levels. Methodological aspects, such as sample collection techniques and processing, significantly influence plasma lead levels, with variations observed based on different collection methods and anticoagulants used. Analytical difficulties in measuring lead levels in plasma, especially in samples with low lead concentrations, can introduce biases and confound assessments of toxicological relevance.How does the presence of Porphyromonas gingivalis in the oral microbiome contribute to the development of rheumatoid arthritis?4 answers
The presence of Porphyromonas gingivalis (Pg) in the oral microbiome is linked to the development of rheumatoid arthritis (RA) through various mechanisms. Pg produces enzymes that promote citrullination, leading to the synthesis of anti-citrullinated peptide antibodies associated with RA onset and severity. Additionally, Pg-specific antibodies in saliva are elevated in RA patients, potentially indicating local immune responses in the salivary glands. Furthermore, the enzyme PPAD produced by Porphyromonas gulae, a related bacterium, is implicated in citrullination associated with RA pathophysiology. Other bacteria like Aggregatibacter actinomycetemcomitans, which causes periodontitis, also contribute to RA development through virulence factors like leukotoxin A. These findings highlight the intricate relationship between oral bacteria, citrullination, and RA pathogenesis.What are the effects of running in menopause symptoms?5 answers
Running during menopause can have significant effects on menopausal symptoms. Aerobic training has been shown to decrease typical menopausal symptoms, especially night sweats, mood swings, and irritability. Regular exercise, including running, may alleviate menopausal symptoms, impacting psychological, somatic, vasomotor, and sexual aspects. Additionally, exercise can counteract changes due to menopause, such as protecting against bone loss, impacting lipoprotein metabolism, and decreasing vasomotor symptoms. Female runners approaching menopause should be aware of the physiological changes that come with age and menopause, and integrating lifestyle behaviors like sleep, recovery, and nutrition with aerobic and strength training can help maintain participation and performance in sports.What is the molecular mechanism behind the influence of salinity on polyketide production in dinoflagellates?5 answers
The influence of salinity on polyketide production in dinoflagellates involves complex molecular mechanisms. Salinity levels impact the biosynthesis of polyketides through the regulation of specific biosynthetic pathways. Dinoflagellates, known for producing polyketide toxins, utilize Type I modular polyketide synthases (PKSs) for biosynthesis. Salinity variations affect gene expression levels in dinoflagellates, such as sxtA4 and sxtG, involved in toxin biosynthesis. Additionally, the ability of dinoflagellates to tolerate different salinities involves genes related to osmolyte production, salinity stress response, and ion transport. These findings suggest that salinity plays a crucial role in modulating the molecular pathways responsible for polyketide production in dinoflagellates, highlighting the intricate interplay between environmental factors and toxin biosynthesis.What is malting?5 answers
Malting is a crucial process involving the controlled germination of cereal grains like barley, wheat, rye, oats, and rice, with the aim of converting them into malt. This process is essential in industries like brewing and distilling, where the enzymes formed during germination modify the grain's cellular structure and composition. Malting enhances the nutritional quality of grains by reducing anti-nutrient compounds, improving protein content bioavailability, and increasing enzyme activity, such as proteases that aid in starch breakdown. Additionally, malting can be used to produce complementary composite foods rich in essential nutrients like iron and zinc, crucial for infant health and development, by reducing phytic acid content through the production of phytase enzyme.What is the traditional method for preparing beer using sweet potato in different cultures?4 answers
The traditional method for preparing beer using sweet potato in different cultures involves several common steps. Initially, the sweet potato material is processed by cleaning, cutting into shreds, cooking, and mixing with water. Subsequently, enzymes like amylase are added to convert starch into sugar, followed by processes such as filtration, boiling, addition of hops, fermentation, and storage to obtain the final beer product. Additionally, the use of purple sweet potato in beer production has been explored, resulting in anthocyanin-rich beer with unique characteristics like antioxidative properties, a purple color, and lower alcohol content, which was well-received by sensory panelists. This innovative approach not only enhances the nutritional value of the beer but also offers a cost-effective and simpler technology for large-scale production, potentially benefiting tribal communities dependent on sweet potato cultivation for their livelihoods.How does computer vision technology aid in the detection of diseases in cotton crops?5 answers
Computer vision technology, particularly through deep learning methods like convolutional neural networks (CNNs), plays a crucial role in detecting diseases in cotton crops. By utilizing CNN models such as ResNet50, SSD with MobileNet-V2, and Faster R-CNN with Inception-V2, researchers have been able to achieve high accuracy rates ranging from 65% to 97.66% in identifying various cotton diseases. These models analyze visual symptoms in images of cotton plants to classify diseases like boll rot, anthracnose, and crown gall caused by bacteria and fungi. The integration of machine learning and artificial intelligence technologies enables quick, accurate, and automated disease identification, facilitating early detection, effective management, and ultimately leading to increased crop yield and economic benefits for cotton farmers.What are the levels of endogenous estrogen in men and women?5 answers
Endogenous estrogen levels vary between men and women. In men, total estradiol levels were found to increase with age. Conversely, in women, higher levels of total estradiol were associated with a higher risk of dementia, including Alzheimer's disease and vascular dementia. Additionally, high endogenous estrogen levels, particularly estrone and estradiol, were linked to a more unhealthy artery wall, indicating a potential association with atherosclerosis in both sexes. Furthermore, in women undergoing in vitro fertilization, increased endogenous estrogen levels led to reductions in cholesterol levels in VLDL and LDL, along with decreased levels of Apolipoprotein B and PCSK9, suggesting a role in modulating cholesterol and lipoprotein metabolism.Is using one cigarette enough to make changes at the brain level with a consequence of addiction?4 answers
Using one cigarette can indeed lead to changes at the brain level with potential consequences of addiction. Nicotine, the primary addictive component in cigarettes, induces neuroadaptive changes associated with addiction. Even a single exposure to nicotine can impact brain plasticity, as seen in studies where nicotine self-administration decreased plasticity-related processes in the hippocampal formation. Furthermore, cigarette smoke exposure, whether active or passive, can cause significant pathological and neurological changes in the brain, which can be mitigated by neuroactive agents like bacoside A. Nicotine addiction, particularly in women, can inhibit estrogen signaling in the brain, making it more vulnerable to ischemic damage. Therefore, even minimal exposure to cigarette smoke can initiate brain alterations that contribute to addiction and related health risks.Which food has low glycemic index?4 answers
Sago, wheat, barley, herbs, and taro are examples of foods with low glycemic index (GI). Sago-based traditional foods like Saguk and Linut have moderate to low GI values, attributed to their resistant starch content. Wheat, barley, and wheat + barley products exhibit low GI values compared to white bread, making them suitable for managing diabetes. Taro, known for its low GI content, is highlighted as a beneficial food for diabetics due to its ability to help control blood sugar levels. Additionally, the study identifies young corn, kepok banana, cassava, Havermuth, and sweet potato as foods with low GI values, aiding in the selection of low-GI ingredients for diabetes prevention. These foods can be valuable additions to a diabetic-friendly diet due to their low impact on blood sugar levels.