Multi-scale Residual Transformer for VLF Lightning Transients Classification

The utilization of Very Low Frequency (VLF) electromagnetic signals in navigation systems is widespread. However, the non-stationary behavior of lightning signals can affect VLF electromagnetic signal transmission. Accurately classifying lightning signals is important for reducing interference and noise in VLF, thereby improving the reliability and overall performance of navigation systems. In recent years, the evolution of deep learning, specifically Convolutional Neural Network (CNNs), has sparked a transformation in lightning classification, surpassing traditional statistical methodologies. Existing CNN models have limitations as they overlook the diverse attributes of lightning signals across different scales and neglect the significance of temporal sequencing in sequential signals. This study introduces an innovative multi-scale residual transform (MRTransformer) that not only has the ability to discern intricate fine-grained patterns while also weighing the significance of different aspects within the input lightning signal sequence. This model performs the attributes of the lightning signal across different scales and the level of accuracy reached 90% in the classification. In future work, this model has the potential applied to a comprehensive understanding of the localization and waveform characteristics of lightning signals

AGI for Agriculture

Artificial General Intelligence (AGI) is poised to revolutionize a variety of sectors, including healthcare, finance, transportation, and education. Within healthcare, AGI is being utilized to analyze clinical medical notes, recognize patterns in patient data, and aid in patient management. Agriculture is another critical sector that impacts the lives of individuals worldwide. It serves as a foundation for providing food, fiber, and fuel, yet faces several challenges, such as climate change, soil degradation, water scarcity, and food security. AGI has the potential to tackle these issues by enhancing crop yields, reducing waste, and promoting sustainable farming practices. It can also help farmers make informed decisions by leveraging real-time data, leading to more efficient and effective farm management. This paper delves into the potential future applications of AGI in agriculture, such as agriculture image processing, natural language processing (NLP), robotics, knowledge graphs, and infrastructure, and their impact on precision livestock and precision crops. By leveraging the power of AGI, these emerging technologies can provide farmers with actionable insights, allowing for optimized decision-making and increased productivity. The transformative potential of AGI in agriculture is vast, and this paper aims to highlight its potential to revolutionize the industry

Impact of Brain Injury on Processing of Emotional Prosodies in Neonates

Being able to appropriately process different emotional prosodies is an important cognitive ability normally present at birth. In this study, we used event-related potential (ERP) to assess whether brain injury impacts the ability to process different emotional prosodies (happy, fear, and neutral) in neonates; whether the ERP measure has potential value for the evaluation of neurodevelopmental outcome in later childhood. A total of 42 full-term neonates were recruited from the neonatology department of Peking University First Hospital from June 2014 to January 2015. They were assigned to the brain injury group (n = 20) or control group (n = 22) according to their clinical manifestations, physical examinations, cranial images and routine EEG outcomes. Using an oddball paradigm, ERP data were recorded while subjects listened to happy (20%, deviation stimulus), fearful (20%, deviation stimulus) and neutral (80%, standard stimulus) prosodies to evaluate the potential prognostic value of ERP indexes for neurodevelopment at 30 months of age. Results showed that while the mismatch responses (MMRs) at the frontal lobe were larger for fearful than happy prosody in control neonates, this difference was not observed in neonates with brain injuries. This finding suggests that perinatal brain injury may influence the cognitive ability to process different emotional prosodies in neonatal brain; this deficit could be reflected by decreased MMR amplitudes in response to fearful prosody. Moreover, the decreased MMRs at the frontal lobe was associated with impaired neurodevelopment at 30 months old

Spin pinning effect to reconstructed oxyhydroxide layer on ferromagnetic oxides for enhanced water oxidation.

Producing hydrogen by water electrolysis suffers from the kinetic barriers in the oxygen evolution reaction (OER) that limits the overall efficiency. With spin-dependent kinetics in OER, to manipulate the spin ordering of ferromagnetic OER catalysts (e.g., by magnetization) can reduce the kinetic barrier. However, most active OER catalysts are not ferromagnetic, which makes the spin manipulation challenging. In this work, we report a strategy with spin pinning effect to make the spins in paramagnetic oxyhydroxides more aligned for higher intrinsic OER activity. The spin pinning effect is established in oxideFM/oxyhydroxide interface which is realized by a controlled surface reconstruction of ferromagnetic oxides. Under spin pinning, simple magnetization further increases the spin alignment and thus the OER activity, which validates the spin effect in rate-limiting OER step. The spin polarization in OER highly relies on oxyl radicals (O∙) created by 1st dehydrogenation to reduce the barrier for subsequent O-O coupling

Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas. This fascination extends particularly to the Internet of Things (IoT), a landscape characterized by the interconnection of countless devices, sensors, and systems, collectively gathering and sharing data to enable intelligent decision-making and automation. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the IoT. Specifically, it starts by outlining the fundamental principles of IoT and the critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it delves into AGI fundamentals, culminating in the formulation of a conceptual framework for AGI's seamless integration within IoT. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education. However, adapting AGI to resource-constrained IoT settings necessitates dedicated research efforts. Furthermore, the paper addresses constraints imposed by limited computing resources, intricacies associated with large-scale IoT communication, as well as the critical concerns pertaining to security and privacy

Responses of carbon exchange characteristics to meteorological factors, phenology, and extreme events in a rubber plantation of Danzhou, Hainan: evidence based on multi-year data

IntroductionOn Hainan Island, a rubber plantation that occupies a large swath of land plays an important role in the regional carbon budget. However, the carbon exchange of the rubber plantation is poorly understood.MethodsIn this study, using the eddy covariance methods we measured carbon metrics in the rubber plantation for 13 years from 2010 to 2022.ResultsWe clarified that the rubber plantation is a carbon sink and the annual net ecosystem exchange (NEE), ecosystem respiration, and gross primary production were −911.89 ± 135.37, 1,528.04 ± 253.50, and 2,439.93 ± 259.63 gC·m−2·a−1, respectively. Carbon fluxes differed between interannual years; specifically, rainy season fluxes were nearly double dry season fluxes. Radiation explained 46% of the variation for NEE in rainy season, and temperature explained 36% of the variation for NEE in the dry season. LAI explained the highest proportion of the monthly variation in NEE (R2 = 0.72, p < 0.001), indicating that when hydrothermal conditions are sufficient phenology may be the primary factor controlling carbon sequestration of rubber plantation. Due to climate change, there is an increasing probability of extreme climate events, such as typhoons, heat waves, and drought. Thus, we compared NEE before and after such events and results show extreme climate events reduce carbon uptake in the rubber plantation. We found that typhoons reduced NEE to varying degrees on different timescales. Heat waves generally decreased NEE during the day but recovered quickly and increased carbon uptake if there was sufficient precipitation. Drought reduced carbon uptake and continued to decrease even after precipitation.DiscussionEstimating the carbon sink capacity of the rubber plantation and studying the response to regional environmental changes are important for both applied research (carbon sink research and market trading, sink enhancement, and emission reduction, etc.) and basic research (land use change, phenology change, etc.)

Interleukin-35 Expression in Non-Small Cell Lung Cancer is Associated with Tumor Progression

Background/Aims: Lung cancer continues to be the leading cause of cancer related deaths worldwide due to its high incidence, malignant behavior and lack of major advancements in treatment strategy. The occurrence and development of lung cancer is closely related to inflammation. Thus, we conducted the present study to investigate the effects of IL-35 (Interleukin 35), a newly identified anti-inflammatory factor, on non-small cell lung cancer (NSCLC), which accounts for about 85% of all lung cancers. Methods: We first evaluated the IL-35 expression in 384 pairs of NSCLC samples and their adjacent normal mucosa by realtime PCR, ELISA (Enzyme-linked immunoassay) and tissue microarrays. Then the role of IL-35 on patient survival rates, cancer progression and their sensitivity to chemotherapy drugs were assessed. Results: IL-35 was barely expressed in the NSCLC tissues but highly expressed in the adjacent normal tissues. The down-regulation of IL-35 was significantly correlated with the results of American Joint Committee on Cancer stage, differentiation and it was also shown to be an independent prognostic indicator of disease-free survival and overall survival for patients with NSCLC. Overexpression of IL-35 in NSCLC cells suppressed cell migration, invasion, proliferation, colony formation through suppressing β-catenin. IL-35 inhibited NSCLC formation in the mice model and sensitize the cancer cells to chemotherapy drugs. Conclusion: Our results showed that IL-35 plays an inhibitory role in NSCLC development and function as a novel prognostic indicator and a potential therapeutic target

Enhanced Anti-diabetic Effect of Berberine Combined With Timosaponin B2 in Goto-Kakizaki Rats, Associated With Increased Variety and Exposure of Effective Substances Through Intestinal Absorption

Objective: Inspired by the traditionally clinical application of herb pair Zhimu-Huangbo to treat diabetes, a combination of plant ingredients, timosaponin B2 (TB-2) and berberine (BBR), was evaluated for their anti-diabetic efficacy and cooperative mechanisms.Methods: The efficacy and pharmacokinetics of orally administered TB-2 (33.3 mg/kg/day), BBR (66.7 mg/kg/day), and TB-2+BBR (100 mg/kg/day) were evaluated in spontaneously non-obese diabetic Goto-Kakizaki (GK) rats, and metformin (200 mg/kg/day) was used as a positive control. The comparative exposure of the parent drugs, timosaponin A3 (TB-2 metabolite), and M1–M5 (BBR metabolites) was quantified in the portal vein plasma (before hepatic disposition), liver, and systemic plasma (after hepatic disposition) of normal rats on single and combination treatments. Cooperative mechanism of TB-2 and BBR on intestinal absorption and hepatic metabolism was investigated in Caco-2 cells and primary hepatocytes, respectively.Results: After a 6-week experiment, non-fasting and fasting blood glucose levels and oral glucose tolerance test results showed that TB-2+BBR treatments (100 mg/kg/day) displayed significantly anti-diabetic efficacy in GK rats, comparable to that on metformin treatments. However, no significant improvement was observed on TB-2 or BBR treatments alone. Compared to single treatments, combination treatments led to the increased circulating levels of BBR by 107% in GK rats. In normal rats, the hepatic exposure of BBR, timosaponin A3, and M1–M5 was several hundred folds higher than their circulating levels. Co-administration also improved the levels in the plasma and liver by 41–114% for BBR, 141–230% for TB-2, and 12–282% for M1–M5. In vitro, the interaction between TB-2 and BBR was mediated by intestinal absorption, rather than hepatic metabolism.Conclusion: Combining TB-2 and BBR enhanced the anti-diabetic efficacy by increasing the in vivo variety of effective substances, including the parent compounds and active metabolites, and improving the levels of those substances through intestinal absorption. This study is a new attempt to assess the effects of combined plant ingredients on diabetes by scientifically utilizing clinical experience of an herb pair

Amyloid and SCD jointly predict cognitive decline across Chinese and German cohorts.

INTRODUCTION Subjective cognitive decline (SCD) in amyloid-positive (Aβ+) individuals was proposed as a clinical indicator of Stage 2 in the Alzheimer's disease (AD) continuum, but this requires further validation across cultures, measures, and recruitment strategies. METHODS Eight hundred twenty-one participants from SILCODE and DELCODE cohorts, including normal controls (NC) and individuals with SCD recruited from the community or from memory clinics, underwent neuropsychological assessments over up to 6 years. Amyloid positivity was derived from positron emission tomography or plasma biomarkers. Global cognitive change was analyzed using linear mixed-effects models. RESULTS In the combined and stratified cohorts, Aβ+ participants with SCD showed steeper cognitive decline or diminished practice effects compared with NC or Aβ- participants with SCD. These findings were confirmed using different operationalizations of SCD and amyloid positivity, and across different SCD recruitment settings. DISCUSSION Aβ+ individuals with SCD in German and Chinese populations showed greater global cognitive decline and could be targeted for interventional trials. HIGHLIGHTS SCD in amyloid-positive (Aβ+) participants predicts a steeper cognitive decline. This finding does not rely on specific SCD or amyloid operationalization. This finding is not specific to SCD patients recruited from memory clinics. This finding is valid in both German and Chinese populations. Aβ+ older adults with SCD could be a target population for interventional trials