Unsupervised machine learning reveals slab hydration variations from deep earthquake distributions beneath the northwest Pacific

Although transformational faulting in the rim of the metastable olivine wedge is hypothesized as a triggering mechanism of deep-focus earthquakes, there is no direct evidence of such rim. Variations of the b value – slope of the Gutenberg-Richter distribution – have been used to decipher triggering and rupture mechanisms of deep earthquakes. However, detection limits prevent full understanding of these mechanisms. Using the Japan Meteorological Agency catalog, we estimate b values of deep earthquakes in the northwestern Pacific Plate, clustered in four regions with unsupervised machine learning. The b-value analysis of Honshu and Izu deep seismicity reveals a kink at magnitude 3.7–3.8, where the b value abruptly changes from 1.4–1.7 to 0.6–0.7. The anomalously high b values for small earthquakes highlight enhanced transformational faulting, likely catalyzed by deep hydrous defects coinciding with the unstable rim of the metastable olivine wedge, the thickness of which we estimate at ∼1 km

Gonadotropin-releasing hormone analogue and recombinant human growth hormone treatment for idiopathic central precocious puberty in girls

PurposeTo investigate the effectiveness and safety of gonadotropin-releasing hormone analogue (GnRHa) in combination with recombinant human growth hormone (rhGH) in girls with central precocious puberty (CPP).MethodsClinical data of 80 girls diagnosed with idiopathic central precocious puberty (ICPP) between January 2017 and June 2021 were retrospectively analyzed. Treatment strategy involved GnRHa alone (group A: n=34) and GnRHa+rhGH (group B: n=46). Children’s heights (Ht), weights (Wt) and sex hormone levels were measured every 3 months after treatment and bone age (BA) every six months. Heights, growth velocity (GV), predicted adult height (PAH), weights, body mass index (BMI), sex hormone levels and bone age were compared between the two groups.ResultsChildren in group B showed greater height gain at the 12th, 24th and 30th months after treatment (p<0.05) than those in group A, had faster growth rates in the first and second year following treatment (p<0.05) and better PAH (p<0.05). No statistical differences in weight or BMI were found between the two groups before treatment or at any time after treatment (p>0.05). Levels of LH and FSH were lower in both groups after treatment with no statistical differences between groups (p>0.05). The gap between bone age and chronological age gradually decreased in both groups and no abnormal progression of bone age or other adverse side effects occurred.ConclusionsThe combination of GnRHa with rhGH produced better height gains than GnRHa alone for patients with CPP. The gonadal axis was suppressed and progression of bone age delayed with good safety and efficacy

Deep Geophysical Anomalies Beneath the Changbaishan Volcano

Subsurface imaging is key to understanding the origin of intraplate volcanoes. The Changbaishan volcano, located about 2,000 km away from the western Pacific subduction zone, has several debated origins. To investigate this, we compared regional seismic tomography with the electrical resistivity results and obtained high-resolution 1D and quasi-2D velocity-depth profiles. We show that the upper mantle is characterized by two anomalies exhibiting distinct features which cannot be explained by the same mechanism. We document a localized low-velocity anomaly atop the 410-km discontinuity, where the P-wave velocity is reduced more than that of the S-wave (i.e., lower Vp/Vs). We propose that this anomaly is caused by the reduction of the effective moduli during the phase transformation of olivine. The other anomaly, located between 300 and 370 km depth, reveals a significant reduction of the S-wave velocity (i.e., higher Vp/Vs), associated with a reduction of the electrical resistivity, altogether consistent with partial melting

Combined effect of diabetes and frailty on mortality among Chinese older adults: A follow-up study

BackgroundFrailty and diabetes are two important health problems associated with aging in older individuals. This paper seeks to analyze the frailty in older adults suffering from diabetes and the combined effect of diabetes and frailty on mortality risk.MethodsThe frailty index (FI) model was employed when evaluating frailty among the older adults based on the baseline data conducted in 2009; and death as outcome variables collected in 2020 were analyzed. The influence of diabetes on age-related changes in frailty in the older adults and resulting mortality rates was analyzed. Cox regression and Kaplan-Meier curves were applied to evaluate the influence on the risk of death and the 11-year survival of the older adults with varying diabetes and frailty statuses.ResultsUltimately, 1,213 older people aged between 60 and 101, with an average age of (74.79 ± 8.58) at baseline, were included in the analysis. By 2020, there had been 447 deaths with mortality at 36.9% (447/1,213); there were 271 cases of diabetes, with a prevalence of 22.3% (271/1,213). The mean FI value for older adults with diabetes was higher than that of those without regardless of age, and the average annual relative growth rate of the FI value for older adults with diabetes was higher than that of those without diabetes (β = 0.039 vs. β = 0.035, t = 8.367, P < 0.001). For all FI value levels, the mortality rate among older adults with diabetes was higher than that of those without. The Cox Regression analysis showed that, compared with those suffering from neither diabetes nor frailty, older adults with both had the higher mortality risk (HR = 1.760. P < 0.001), followed by older adults suffering from frailty alone (HR = 1.594, P = 0.006), and then by older adults suffering from only diabetes (HR = 1.475, P = 0.033). The survival analysis showed that the median survival of those suffering from diabetes and frailty to be the shortest at just 57.23 (95% CI: 54.05 to 60.41) months, lower than the 83.78 (95% CI: 79.33 to 88.23) months in those suffering from frailty alone, and 119.93 (95% CI: 113.84 to 126.02) months in those with only diabetes, and 124.39 (95% CI: 119.76 to 129.02) months in older adults with neither diabetes nor frailty (P < 0.001).ConclusionFrailty is common among older adults suffering from diabetes, and there is an increased risk of poor health outcomes, such as death, among older adults suffering from diabetes and frailty. When diagnosing, treating, and dealing with older adults with diabetes, attention should be paid to screening and assessing frailty in hopes of identifying it early so that appropriate measures of intervention can be taken to avoid or delay the resulting adverse effects

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Dual Stream Computer-Generated Image Detection Network Based On Channel Joint And Softpool

With the development of computer graphics technology, the images synthesized by computer software become more and more closer to the photographs. While computer graphics technology brings us a grand visual feast in the field of games and movies, it may also be utilized by someone with bad intentions to guide public opinions and cause political crisis or social unrest. Therefore, how to distinguish the computer-generated graphics (CG) from the photographs (PG) has become an important topic in the field of digital image forensics. This paper proposes a dual stream convolutional neural network based on channel joint and softpool. The proposed network architecture includes a residual module for extracting image noise information and a joint channel information extraction module for capturing the shallow semantic information of image. In addition, we also design a residual structure to enhance feature extraction and reduce the loss of information in residual flow. The joint channel information extraction module can obtain the shallow semantic information of the input image which can be used as the information supplement block of the residual module. The whole network uses SoftPool to reduce the information loss of down-sampling for image. Finally, we fuse the two flows to get the classification results. Experiments on SPL2018 and DsTok show that the proposed method outperforms existing methods, especially on the DsTok dataset. For example, the performance of our model surpasses the state-of-the-art by a large margin of 3%.Comment: 7 pages, 4 figure

Multiple-Gene Regulation for Enhanced Antitumor Efficacy with Branch-PCR-Assembled TP53 and MYC Gene Nanovector

Multiple proteins are involved in network regulation through the crosstalk of different signaling pathways in cancers. Here, we propose a novel strategy of genome therapy with branch-PCR-assembled gene nanovectors to perform network-based gene regulation at multiple levels for cancer therapy. To validate network-based multiplex-gene regulation for genome therapy, we chose to simultaneously target one tumor suppressor gene (TP53) and one oncogene (MYC) in two different signaling pathways. The results showed that, compared to gene nanovectors targeting single genes (NP-TP53 and NP-shMYC), branch-PCR-assembled gene nanovectors simultaneously expressing p53 proteins and MYC shRNA arrays (NP-TP53-shMYC) showed enhanced antitumor efficacy in both MDA-MB-231 cancer cells and an MDA-MB-231-tumor-bearing mouse model. These findings indicate the feasibility and effectiveness of genome therapy in cancer therapy

Digital transformation, productive services agglomeration and innovation performance

Innovation is a necessary guarantee for sustainable development. Stepping into the digital age, digital transformation has triggered the innovation revolution. This paper takes 30 provinces in China from 2012 to 2022 as the research sample, we verify whether digital transformation has improved innovation performance. Based on the Solow growth model and agglomeration economics theory, we also explore the moderating role and threshold effect of agglomeration in productive service industry between digital transformation and innovation performance. To achieve this, we apply the methods of machine learning and text analysis to construct an evaluation index of regional digital transformation and measure it. The paper finds that China's digital transformation index is increasing, but there is a digital divide between regions. We also determine that digital transformation significantly and positively contributes to the level of innovation performance. Considering the threshold effect of agglomeration in productive service industry, the impact of digital transformation on innovation performance exhibits non-linear characteristics, As the level of agglomeration continues to exceed the threshold, the innovation-driven effect of digital transformation increases. The research results help clarify the relationship between digital transformation and innovation performance, and provide favorable policy directions for regional governments to identify digital divides and make reasonable industrial layouts. Thus, it can promote the construction of digital China and innovation power, injecting strong innovation force into the realization of SDGs