Multi-dimensional vibration sensing and simultaneous self-homodyne optical transmission of single wavelength net 5.36 Tb/s signal using telecom 7-core fiber

We present a high-capacity self-homodyne optical transmission system that enables simultaneously multidimensional vibration sensing based on a weakly-coupled 7-core fiber. To our knowledge, we demonstrate for the first-time detection of fiber vibration direction along with strength, frequency, and location of the vibration source, while transmitting in the meantime single-carrier 16 QAM signal reaching a net date rate of 5.36 Tb/s over 41.4 km of telecom 7-core fiber.Comment: 5 pages, 4 figure

Research on stress sensitivity of fractured carbonate reservoirs based on CT technology

Fracture aperture change under stress has long been considered as one of primary causes of stress sensitivity of fractured gas reservoirs. However, little is known about the evolution of the morphology of fracture apertures on flow property in loading and unloading cycles. This paper reports a stress sensitivity experiment on carbonate core plugs in which Computed Tomography (CT) technology is applied to visualize and quantitatively evaluate morphological changes to the fracture aperture with respect to confining pressure. Fracture models were obtained at selected confining pressures on which pore-scale flow simulations were performed to estimate the equivalent absolute permeability. The results showed that with the increase of confining pressure from 0 to 0.6 MPa, the fracture aperture and equivalent permeability decreased at a greater gradient than their counterparts after 0.6 MPa. This meant that the rock sample is more stress-sensitive at low effective stress than at high effective stress. On the loading path, an exponential fitting was found to fit well between the effective confining pressure and the calculated permeability. On the unloading path, the relationship is found partially reversible, which can evidently be attributed to plastic deformation of the fracture as observed in CT images

Alteration of Brain Structure With Long-Term Abstinence of Methamphetamine by Voxel-Based Morphometry

Background: A large portion of previous studies that have demonstrated brain gray matter reduction in individuals who use methamphetamine (MA) have focused on short-term abstinence, but few studies have focused on the effects of long-term abstinence of methamphetamine on brain structures.Materials and Methods: Our study includes 40 healthy controls and 44 abstinent methamphetamine-dependent (AMD) subjects who have abstained for at least 14 months. For every AMD subject, the age when they first used MA, the total time of MA use, the frequency of MA use in the last month before abstinence, the duration of abstinence and the craving score were recorded. Here we used magnetic resonance imaging (MRI) to measure the gray matter volume (GMV) of each subject with voxel-based morphometry method. Two-sample t-test (AlphaSim corrected) was performed to obtain brain regions with different gray matter volume (GMV) between groups. In addition, partial correlation coefficients adjusted for age, years of education, smoking, and drinking were calculated in the AMD group to assess associations between the mean GMV values in significant clusters and variables of MA use and abstinence.Results: Compared with the healthy control group, AMD group showed increased gray matter volumes in the bilateral cerebellum and decreased volumes in the right calcarine and right cuneus. Moreover, GMV of left cerebellum are positively correlated with the duration of abstinence in the AMD group (p = 0.040, r = 0.626).Conclusions: The present study showed that the gray matter volume in some brain regions is abnormal in the AMD subjects with long-term abstinence. Changes in gray matter volume of visual and cognitive function regions suggested that these areas play important roles in the progress of MA addiction and abstinence. In addition, positive correlation between GMV of the left cerebellum crus and duration of abstinence suggested that prolonged abstinence is beneficial to cognitive function recovery

Integrative transcriptome and metabolome analysis reveals the mechanism of fulvic acid alleviating drought stress in oat

Drought stress inhibits oat growth and yield. The application of fulvic acid (FA) can improve the drought resistance of oats, but the corresponding molecular mechanism of FA-mediated drought resistance remains unclear. Here, we studied the effects of FA on the drought tolerance of oat leaves through physiological, transcriptomic, and metabolomics analyses, and identified FA-induced genes and metabolites related to drought tolerance. Physiological analysis showed that under drought stress, FA increased the relative water and chlorophyll contents of oat leaves, enhanced the activity of antioxidant enzymes (SOD, POD, PAL, CAT and 4CL), inhibited the accumulation of malondialdehyde (MDA), hydrogen peroxide (H2O2) and dehydroascorbic acid (DHA), reduced the degree of oxidative damage in oat leaves, improved the drought resistance of oats, and promoted the growth of oat plants. Transcriptome and metabolite analyses revealed 652 differentially expressed genes (DEGs) and 571 differentially expressed metabolites (DEMs) in FA-treated oat leaves under drought stress. These DEGs and DEMs are involved in a variety of biological processes, such as phenylspropanoid biosynthesis and glutathione metabolism pathways. Additionally, FA may be involved in regulating the role of DEGs and DEMs in phenylpropanoid biosynthesis and glutathione metabolism under drought stress. In conclusion, our results suggest that FA promotes oat growth under drought stress by attenuating membrane lipid peroxidation and regulating the antioxidant system, phenylpropanoid biosynthesis, and glutathione metabolism pathways in oat leaves. This study provides new insights into the complex mechanisms by which FA improves drought tolerance in crops

NanoSIMS analysis of water content in bridgmanite at the micron scale: An experimental approach to probe water in Earth’s deep mantle

Water, in trace amounts, can greatly alter chemical and physical properties of mantle minerals and exert primary control on Earth’s dynamics. Quantifying how water is retained and distributed in Earth’s deep interior is essential to our understanding of Earth’s origin and evolution. While directly sampling Earth’s deep interior remains challenging, the experimental technique using laser-heated diamond anvil cell (LH-DAC) is likely the only method available to synthesize and recover analog specimens throughout Earth’s lower mantle conditions. The recovered samples, however, are typically of micron sizes and require high spatial resolution to analyze their water abundance. Here we use nano-scale secondary ion mass spectrometry (NanoSIMS) to characterize water content in bridgmanite, the most abundant mineral in Earth’s lower mantle. We have established two working standards of natural orthopyroxene that are likely suitable for calibrating water concentration in bridgmanite, i.e., A119(H2O) = 99 ± 13 μg/g (1SD) and A158(H2O) = 293 ± 23 μg/g (1SD). We find that matrix effect among orthopyroxene, olivine, and glass is less than 10%, while that between orthopyroxene and clinopyroxene can be up to 20%. Using our calibration, a bridgmanite synthesized by LH-DAC at 33 ± 1 GPa and 3,690 ± 120 K is measured to contain 1,099 ± 14 μg/g water, with partition coefficient of water between bridgmanite and silicate melt ∼0.025, providing the first measurement at such condition. Applying the unique analytical capability of NanoSIMS to minute samples recovered from LH-DAC opens a new window to probe water and other volatiles in Earth’s deep mantle

ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data

Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and diverse radiology reports with cross-source heterogeneity pose a huge generalizability challenge to the current methods under massive data volume, mainly because the style and normativity of radiology reports are obviously distinctive among institutions, body regions inspected and radiologists. Recently, the advent of large language models (LLM) offers great potential for recognizing signs of health conditions. To resolve the above problem, we collaborate with the Second Xiangya Hospital in China and propose ChatRadio-Valuer based on the LLM, a tailored model for automatic radiology report generation that learns generalizable representations and provides a basis pattern for model adaptation in sophisticated analysts' cases. Specifically, ChatRadio-Valuer is trained based on the radiology reports from a single institution by means of supervised fine-tuning, and then adapted to disease diagnosis tasks for human multi-system evaluation (i.e., chest, abdomen, muscle-skeleton, head, and maxillofacial $\&$ neck) from six different institutions in clinical-level events. The clinical dataset utilized in this study encompasses a remarkable total of \textbf{332,673} observations. From the comprehensive results on engineering indicators, clinical efficacy and deployment cost metrics, it can be shown that ChatRadio-Valuer consistently outperforms state-of-the-art models, especially ChatGPT (GPT-3.5-Turbo) and GPT-4 et al., in terms of the diseases diagnosis from radiology reports. ChatRadio-Valuer provides an effective avenue to boost model generalization performance and alleviate the annotation workload of experts to enable the promotion of clinical AI applications in radiology reports

A Meta-Analysis Reveals Opposite Effects of Biotic and Abiotic Stresses on Transcript Levels of Arabidopsis Intracellular Immune Receptor Genes

Plant intracellular immune receptor NLR (nucleotide-binding leucine-rich repeat) proteins sense the presence of pathogens and trigger strong and robust immune responses. NLR genes are known to be tightly controlled at the protein level, but little is known about their dynamics at the transcript level. In this study, we presented a meta-analysis of transcript dynamics of all 207 NLR genes in the Col-0 accession of Arabidopsis thaliana under various biotic and abiotic stresses based on 88 publicly available RNA sequencing datasets from 27 independent studies. We find that about two thirds of the NLR genes are generally induced by pathogens, immune elicitors, or salicylic acid (SA), suggesting that transcriptional induction of NLR genes might be an important mechanism in plant immunity regulation. By contrast, NLR genes induced by biotic stresses are often repressed by abscisic acid, high temperature and drought, suggesting that transcriptional regulation of NLR genes might be important for interaction between abiotic and biotic stress responses. In addition, pathogen-induced expression of some NLR genes are dependent on SA induction. Interestingly, a small group of NLR genes are repressed under certain biotic stress treatments, suggesting an unconventional function of this group of NLRs. This meta-analysis thus reveals the transcript dynamics of NLR genes under biotic and abiotic stress conditions and suggests a contribution of NLR transcript regulation to plant immunity as well as interactions between abiotic and biotic stress responses.</jats:p