The extension of variability properties in gamma-ray bursts to blazars

Both gamma-ray bursts (GRBs) and blazars have relativistic jets pointing at a small angle from our line of sight. Several recent studies suggested that these two kinds of sources may share similar jet physics. In this work, we explore the variability properties for GRBs and blazars as a whole. We find that the correlation between minimum variability timescale (MTS) and Lorentz factor, $\Gamma$, as found only in GRBs by Sonbas et al. can be extended to blazars with a joint correlation of $\rm MTS\propto\Gamma^{-4.7\pm0.3}$. The same applies to the $\rm MTS\propto \it L_{\gamma}^{\rm -1.0\pm0.1}$ correlation as found in GRBs, which can be well extended into blazars as well. These results provide further evidence that the jets in these two kinds of sources are similar despite of the very different mass scale of their central engines. Further investigations of the physical origin of these correlations are needed, which can shed light on the nature of the jet physics.Comment: 6 pages, 2 figures, accepted for publication in MNRA

Developing a real-time monitoring traceability system for cold chain of Tricholoma matsutake

Tricholoma matsutake (T. matsutake) is a special type of fungus known as "the king of bacteria", and has the very high economic value. However, it is also very difficult to transport due to its corruptibility. Therefore, tracing and tracking the quality and safety of T. matsutake in the cold chain is very important and necessary. Based on changes in the cold chain environmental parameters determine the safety of T. matsutake is a viable option. This paper developed and tested a real-time monitoring traceability system (RM-TM) using emerging Internet of Things (IoT) technologies for monitoring the cold chain logistics environmental parameters of T. matsutake. Finally, system testing and evaluation have shown that RM-TM can track and monitor temperature, humidity, oxygen and carbon dioxide fluctuations in the cold chain in real-time. In addition, the collected data can be used to increase the transparency of cold chain logistics and to more effectively control quality, safety, and traceability. In general, the system evaluation results show that it is reliable and meets the requirements of users

Eco-physiological adaptation of dominant tree species at two contrasting karst habitats in southwestern China

The purpose of this study was to investigate the eco-physiological adaptation of indigenous woody species to their habitats in karst areas of southwestern China. Two contrasting forest habitats were studied: a degraded habitat in Daxiagu and a well-developed habitat in Tianlongshan, and the eco-physiological characteristics of the trees were measured for three growth seasons. Photosynthetic rate (Pn), stomatal conductance (gs), and transpiration rate (Tr) of the tree species in Daxiagu were 2-3 times higher than those in Tianlongshan under ambient conditions. However, this habitat effect was not significant when measurements were taken under controlled conditions. Under controlled conditions, Pn, gs, and Tr of the deciduous species were markedly higher than those for the evergreen species. Habitat had no significant effect on water use efficiency (WUE) or photochemical characteristics of PSII. The stomatal sensitivity of woody species in the degraded habitat was much higher than that in the well-developed habitat. Similarly, the leaf total nitrogen (N) and phosphorus (P) contents expressed on the basis of either dry mass or leaf area were also much higher in Daxiagu than they were in Tianlongshan. The mass-based leaf total N content of deciduous species was much higher than that of evergreen species, while leaf area-based total N and P contents of evergreens were significantly higher than those of deciduous species. The photosynthetic nitrogen- and phosphorus-use efficiencies (PNUE and PPUE) of deciduous species were much higher than those of evergreens. Further, the PPUE of the woody species in Tianlongshan was much higher than that  of the woody species in Daxiagu. The results from three growth seasons imply that the tree species were able to adapt well to their growth habitats. Furthermore, it seems that so-called “temporary drought stress” may not occur, or may not be severe for most woody plants in karst areas of southwestern China

Mining Users’ Preference Similarities in E-commerce Systems Based on Webpage Navigation Logs

Mining users’ preference patterns in e-commerce systems is a fertile area for a great many application directions, such as shopping intention analysis, prediction and personalized recommendation. The web page navigation logs contain much potentially useful information, and provide opportunities for understanding the correlation between users’ browsing patterns and what they want to buy. In this article, we propose a web browsing history mining based user preference discovery method for e-commerce systems. First of all, a user-browsing-history-hierarchical-presentationgraph to established to model the web browsing histories of an individual in common e-commerce systems, and secondly an interested web page detection algorithm is designed to extract users’ preference. Finally, a new method called UPSAWBH (User Preference Similarity Calculation Algorithm Based on Web Browsing History), which measure the level of users’ preference similarity on the basis of their web page click patterns, is put forward. In the proposed UPSAWBH, we take two factors into account: 1) the number of shared web page click sequence, and 2) the property of the clicked web page that reflects users’ shopping preference in e-commerce systems. We conduct experiments on real dataset, which is extracted from the server of our self-developed e-commerce system. The results indicate a good effectiveness of the proposed approach

Ball Mill Fault Prediction Based on Deep Convolutional Auto-Encoding Network

Ball mills play a critical role in modern mining operations, making their bearing failures a significant concern due to the potential loss of production efficiency and economic consequences. This paper presents an anomaly detection method based on Deep Convolutional Auto-encoding Neural Networks (DCAN) for addressing the issue of ball mill bearing fault detection. The proposed approach leverages vibration data collected during normal operation for training, overcoming challenges such as labeling issues and data imbalance often encountered in supervised learning methods. DCAN includes the modules of convolutional feature extraction and transposed convolutional feature reconstruction, demonstrating exceptional capabilities in signal processing and feature extraction. Additionally, the paper describes the practical deployment of the DCAN-based anomaly detection model for bearing fault detection, utilizing data from the ball mill bearings of Wuhan Iron & Steel Resources Group and fault data from NASA's bearing vibration dataset. Experimental results validate the DCAN model's reliability in recognizing fault vibration patterns. This method holds promise for enhancing bearing fault detection efficiency, reducing production interruptions, and lowering maintenance costs.Comment: 9 pages, 11 figure

Associations between gut microbiota and sleep: a two-sample, bidirectional Mendelian randomization study

IntroductionPrevious research has reported that the gut microbiota performs an essential role in sleep through the microbiome–gut–brain axis. However, the causal association between gut microbiota and sleep remains undetermined.MethodsWe performed a two-sample, bidirectional Mendelian randomization (MR) analysis using genome-wide association study summary data of gut microbiota and self-reported sleep traits from the MiBioGen consortium and UK Biobank to investigate causal relationships between 119 bacterial genera and seven sleep-associated traits. We calculated effect estimates by using the inverse-variance weighted (as the main method), maximum likelihood, simple model, weighted model, weighted median, and MR-Egger methods, whereas heterogeneity and pleiotropy were detected and measured by the MR pleiotropy residual sum and outlier method, Cochran’s Q statistics, and MR-Egger regression.ResultsIn forward MR analysis, inverse-variance weighted estimates concluded that the genetic forecasts of relative abundance of 42 bacterial genera had causal effects on sleep-associated traits. In the reverse MR analysis, sleep-associated traits had a causal effect on 39 bacterial genera, 13 of which overlapped with the bacterial genera in the forward MR analysis.DiscussionIn conclusion, our research indicates that gut microbiota may be involved in the regulation of sleep, and conversely, changes in sleep-associated traits may also alter the abundance of gut microbiota. These findings suggest an underlying reciprocal causal association between gut microbiota and sleep

The home language environment in rural China: variations across family characteristics

Background A rich language environment is an important element of a nurturing home environment. Despite their proven importance, vocabulary and conversation have been shown to vary widely across households—even within the same socio-economic class. One significant gap in the existing literature is its nearly exclusive geographic focus on Western and developed settings, with little attention given to poorer communities in lower/middle income countries. The purpose of this study was to empirically illustrate the characteristics of the home language environment in the low SES, non-Western cultural setting of rural China. Methods Using Language Environment Analysis (LENA) automated language-analysis system, this study measured the home language environment of 38 children aged 20-27 months in Northwest rural China. Our primary measures of the home language environment were Adult Word Count (AWC), Conversational Turn Count (CTC) and Child Vocalization Count (CVC). Multivariate linear regression models were used to examine the association between home language environment and family/child characteristics, and language skills (Measured by MacArthur-Bates Communicative Developmental Inventory score). Results In this paper, by comparison, we found that the home language environment of our rural sample fell far behind that of urban households. We also identify significant, positive correlations between language skills and both AWC and CTC. Our analysis finds no significant correlations between home language environment and family/child characteristics. Conclusion In this paper, we present the first ever findings using the LENA system to measure the home language environment of young children from poor rural communities in China. We found that the home language environment of lower-SES household was significantly worse than high-SES households, and demonstrated the importance of the home language environment to language skills, pointing to a need for more high-quality studies of the home language environment in rural China to better understand possible mechanisms behind low levels of parent-child language engagement and ways to improve the home language environment

Novel Experience Induces Persistent Sleep-Dependent Plasticity in the Cortex but not in the Hippocampus

Episodic and spatial memories engage the hippocampus during acquisition but migrate to the cerebral cortex over time. We have recently proposed that the interplay between slow-wave (SWS) and rapid eye movement (REM) sleep propagates recent synaptic changes from the hippocampus to the cortex. To test this theory, we jointly assessed extracellular neuronal activity, local field potentials (LFP), and expression levels of plasticity-related immediate-early genes (IEG) arc and zif-268 in rats exposed to novel spatio-tactile experience. Post-experience firing rate increases were strongest in SWS and lasted much longer in the cortex (hours) than in the hippocampus (minutes). During REM sleep, firing rates showed strong temporal dependence across brain areas: cortical activation during experience predicted hippocampal activity in the first post-experience hour, while hippocampal activation during experience predicted cortical activity in the third post-experience hour. Four hours after experience, IEG expression was specifically upregulated during REM sleep in the cortex, but not in the hippocampus. Arc gene expression in the cortex was proportional to LFP amplitude in the spindle-range (10–14 Hz) but not to firing rates, as expected from signals more related to dendritic input than to somatic output. The results indicate that hippocampo-cortical activation during waking is followed by multiple waves of cortical plasticity as full sleep cycles recur. The absence of equivalent changes in the hippocampus may explain its mnemonic disengagement over time

A test on external Compton models for γ\gamma-ray active galactic nuclei

There is clear evidence that the $\gamma$-ray emission from active galactic nuclei (AGNs) is attributed to the inverse Compton scatterings in the relativistic blobs near the massive black holes. If the soft seed photons are from the regions outside the blobs, a linear relation between $(\nu F_{\nu,\gamma}/\nu F_{\nu, \rm syn} u^{*})^{1/(1+\alpha)}$ and Doppler factor $\delta$ is expected, where $\nu F_{\nu,\gamma}$ and $\nu F_{\nu, \rm syn}$ are monochromatic $\gamma$-ray and synchrotron fluxes, respectively, and $u^{*}$ is the energy density of soft seed photons \citep{D97}. We estimate the soft photon energy density in the relativistic blobs contributed by the broad line region (BLRs) in these $\gamma$-ray AGNs using their broad-line emission data. The Doppler factors $\delta$ are derived from their radio core and X-ray emission data, based on the assumption that the X-ray emission is produced through synchrotron self-Compton (SSC) scatterings. We find two nearly linear correlations: $(\nu F_{\nu,\gamma}/\nu F_{\rm opt} u^{*})^{1/(1+\alpha)} \propto \delta^{1.09}$, and $(\nu F_{\nu,\gamma}/\nu F_{\rm IR} u^{*})^{1/(1+\alpha)} \propto \delta^{1.20}$, which are roughly consistent with the linear correlation predicted by the theoretical model for external Compton scatterings. Our results imply that the soft seed photons are dominantly from the BLRs in these $\gamma$-ray AGNs.Comment: 18 pages, accepted by Ap