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The aim of this study was to investigate the tissue perfusion status and circadian rhythm in moderately premature infants. As a prospective study, from July 2019 to October 2019, the haemodynamic stability of moderate to late preterm, including such indicators as perfusion index (PI), blood pressure (systolic/diastolic) (BP), heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and body temperature were monitored in the morning and at night within eight days after birth. There was no difference of statistical significance between PI values in the morning and at night (P>0.05). The HR from days six to eight after birth was higher than days one to three (P

Resveratrol (Resv) has antitumorigenic and antimetastatic activities; however, the molecular mechanisms underlying the inhibitory effects of Resv on the invasion and metastasis of breast cancer cells are still a subject of debate. In our study, we demonstrated that Resv inhibited tumor cell proliferation and tumor growth. It also suppressed invasion and pulmonary metastasis of breast cancer by reversing the transforming growth factor beta 1 (TGF-β1)-mediated EMT process. Meanwhile, the anticarcinogenic effects of Resv were abolished by the autophagy blocker 3-methyladenine (3-MA) or Beclin 1 small interfering RNA. Moreover, Resv upregulated autophagy-related genes and protein levels and induced the formation of autophagosomes in 4T1 breast cancer cells and xenograft mice, suggesting that autophagy was involved in the anticarcinogenic activities of Resv in both models. In addition, Resv-induced autophagy by increasing the expression of SIRT3 and phosphorylated AMPK. SIRT3 knockdown reduced AMPK phosphorylation and autophagy-related proteins levels, and suppressed the anticancer effects of Resv, demonstrating that the inhibitory effects of Resv on tumor progression were mediated via the SIRT3/AMPK/autophagy pathway. Taken together, our study provided novel insight into the anticancer effects of Resv and revealed that targeting the SIRT3/AMPK/autophagy pathway can serve as a new therapeutic target against breast cancer.

As a natural aerosol with the largest emissions on land, dust has important impacts on the atmospheric environment and climate systems. Both the emissions and transport of dust aerosols are tightly connected to meteorological conditions and as a result are confronted with strong modulations by the changing climate. Here, we project the changes in the global dust emissions and loading by the end of the 21st century, using an ensemble of model outputs from the Coupled Model Intercomparison Project version 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs). Based on the validations against site-level observations, we select 9 out of 14 models and estimate an ensemble global dust emissions of 2566 ± 1996 Tg a−1 (1 Tg = 1012 g) for the present day, in which 68 % is dry deposited and 31 % is wet deposited. Compared to 2005–2014, global dust emissions show varied responses, with a reduction of −5.6 ± 503 Tg a−1 under the SSP3–7.0 scenario but increased emissions up to 60.7 ± 542 Tg a−1 under the SSP5–8.5 scenario at 2090–2099. For all scenarios, the most significant increase in the dust emissions appears in North Africa (0.6 %–5.6 %) due to the combined effects of reduced precipitation but strengthened surface wind. In contrast, all scenarios show decreased emissions in the Taklimakan and Gobi deserts (−0.8 % to −11.9 %) because of the increased precipitation but decreased wind speed on a regional scale. The dust loading shows uniform increases over North Africa (1.6 %–13.5 %) and the downwind Atlantic, following the increased emissions but decreases over East Asia (−1.3 % to −10.5 %), and the downwind Pacific, partly due to enhanced local precipitation that promotes wet deposition. In total, global dust loading will increase by 2.0 %–12.5 % at the end of the 21st century under different climate scenarios, suggesting a likelihood of strengthened radiative and climatic perturbations by dust aerosols in a warmer climate.

High-temperature solid-solution is indispensable for bake-hardenable dilute Mg alloys, which generally induces grain coarsening. Herein, we report extraordinary thermal stability in a bake-hardenable dilute Mg-1.61Zn-0.57Mn-0.54Ca-0.46Al (wt. %, ZMXA2110) alloy, maintaining fine-grained structure at 450 °C. The thermal stability is stemmed from the Zener pinning effect of dense fine (∼15.0 nm) core–shell β-Mn particles and co-segregation of Zn and Ca at grain boundaries. The fine-grained (∼3.2 μm) dilute alloy exhibits high room-temperature formability in solid-solution condition with an Index Erichsen value of ∼6.0 mm, and impressive yield strength of ∼293 MPa with an evident increment of ∼60 MPa by bake-hardening treatment. By achieving extraordinary fine-grain thermal stability under high-temperature solid-solution treatment, appreciable bake-hardenability along with fine-grained structure are obtained simultaneously to ensure the development of dilute Mg alloys with high strength.

Latent variable models have become instrumental in computational neuroscience for reasoning about neural computation. This has fostered the development of powerful offline algorithms for extracting latent neural trajectories from neural recordings. However, despite the potential of real time alternatives to give immediate feedback to experimentalists, and enhance experimental design, they have received markedly less attention. In this work, we introduce the exponential family variational Kalman filter (eVKF), an online recursive Bayesian method aimed at inferring latent trajectories while simultaneously learning the dynamical system generating them. eVKF works for arbitrary likelihoods and utilizes the constant base measure exponential family to model the latent state stochasticity. We derive a closed-form variational analogue to the predict step of the Kalman filter which leads to a provably tighter bound on the ELBO compared to another online variational method. We validate our method on synthetic and real-world data, and, notably, show that it achieves competitive performance, Published at ICLR 2023

Background Adalimumab induction and maintenance therapy have been applied to patients with Crohn's disease (CD). This study aimed to analyze the efficacy and safety of an optimized dose versus a standard dose of adalimumab in the treatment of CD.Methods It was a retrospective study involving 192 CD patients treated with adalimumab. According to the maintenance therapy following an induction therapy, CD patients were assigned to receive a standard dose (subcutaneously injected with 40mg of adalimumab every other week) and an optimized dose (subcutaneously injected with 80mg of adalimumab every other week). The clinical remission rate, inflammatory and nutritional indicators, mucosal healing rate, endoscopic response rate at 12th week, risk of treatment failure and safety were compared between groups.Results There were 139 patients in the standard dose group and 53 in the optimized dose group. At 12 weeks, no significant difference was detected in the clinical remission rate (79.1% vs. 81.1%; RR, 0.97; 95% CI, 0.81–1.24; P = 0.842). In infliximab-exposed CD patients, the optimized dose of adalimumab provided a significantly higher clinical remission rate (76.9% vs. 44.4%; RR, 0.58; 95% CI, 0.37–0.88; P = 0.018) and lower risk of treatment failure (HR, 0.36; 95% CI, 0.14–0.97; P = 0.042), but not in infliximab-naïve CD patients. The incidence of adverse events was comparable between groups (32.1% vs. 30.9%, P = 0.864).Conclusions An optimized adalimumab dose does not provide additionally clinical benefits to infliximab-naïve CD patients, compared with a standard dose, but can increase the clinical remission rate and lower the risk of treatment failure in infliximab-exposed CD patients at 12 weeks, without increasing the incidence of adverse events.

The formation of bulk metallic glass requires the constituent elements to have a negative heat of mixing but has no restrictions on its magnitude. An understanding of this issue is lacking due to the absence of a valid method for describing chemical ordering of metallic glasses. For example, the radial distribution function is ineffective in identifying the elemental preferences of packed atoms. Here, we show that using molecular-dynamics simulation, the chemical medium-range ordering of liquid alloys can be evaluated from persistent homology. This inherently arising chemical medium-range order in metallic glasses is exclusively regulated by the activation and inhibition of the constituent components, making the topology of metallic glasses a Turing pattern. The connecting schemes of atoms of the same species form three distinct regions, reflecting different correlations at the short and medium length scales, while the difference in the schemes corresponds to chemical ordering. By changing the elemental types, it is demonstrated that the chemical medium-range order strongly depends on the relative depth of the interatomic-potential wells. The study separates metallic glasses from crystals under the condition of negative heat of mixing by emphasizing their fundamental difference in interatomic potentials.

When people evaluate the engine NVH, they are not only mentioning whether the engine is loud or not, they say that is noisy or quiet. The difference between these two comments is the way they quantify the engine NVH, from the noise level or the sound quality. Lots of engineers used objective tools to quantify engine sound quality performance for years. In this paper, we would like to propose a novel sound quality matrix for the diesel engine which includes loudness, sharpness, mid-frequency, and high-frequency knocking parameters to perform the sound quality evaluation. In addition, an application case is described in this paper to demonstrate the usage of the new matrix.

Defect engineering is promising to tailor the physical properties of two-dimensional (2D) semiconductors for function-oriented electronics and optoelectronics. Compared with the extensively studied 2D binary materials, the origin of defects and their influence on physical properties of 2D ternary semiconductors have not been clarified. In this work, we thoroughly studied the effect of defects on the electronic structure and optical properties of few-layer hexagonal Znln2S4 via versatile spectroscopic tools in combination with theoretical calculations. It has been demonstrated that the Zn-In anti-structural defects induce the formation of a series of donor and acceptor levels inside the bandgap, leading to rich recombination paths for defect emission and extrinsic absorption. Impressively, the emission of donor-acceptor pair (DAP) in Znln2S4 can be significantly tailored by electrostatic gating due to efficient tunability of Fermi level (Ef). Furthermore, the layer-dependent dipole orientation of defect emission in Znln2S4 was directly revealed by back focal plane (BFP) imagining, where it presents obviously in-plane dipole orientation within a dozen layers thickness of Znln2S4. These unique features of defects in Znln2S4 including extrinsic absorption, rich recombination paths, gate tunability and in-plane dipole orientation will definitely benefit to the advanced orientation-functional optoelectronic applications.

supplemental Figure 1-12. Expression levels of 10 lncRNAs by qRT-PCR in 15 GBC tissues and paired non-tumor tissues (Figure 1). Expression levels of 8 mRNAs by qRT-PCR in 15 GBC tissues and paired non-tumor tissues (Figure 2). Molecular characteristics of GCASPC (Figure 3). Nucleotide sequence of the full-length human GCASPC gene (Figure 4). GCASPC has no coding capability (Figure 5). The expression level of GCASPC in gallbladder cancer cells (Figure 6). Manipulation of GCASPC expression level (Figure 7). Anti-proliferative activity of GCASPC (Figure 8). GCASPC acts in trans (Figure 9). The effect of GCASPC on the protein, activity and mRNA levels of PC (Figure 10). GCASPC destabilizes PC protein (Figure 11). GCASPC directly binds to miR-17-3p (Figure 12).

Long noncoding RNAs (lncRNA) are being implicated in the development of many cancers. Here, we report the discovery of a critical role for the lncRNA GCASPC in determining the progression of gallbladder cancer. Differentially expressed lncRNAs and mRNAs between gallbladder cancer specimens and paired adjacent nontumor tissues from five patients were identified and validated by an expression microarray analysis. Quantitative real-time PCR was used to measure GCASPC levels in tissues from 42 gallbladder cancer patients, and levels of GCASPC were confirmed further in a separate cohort of 89 gallbladder cancer patients. GCASPC was overexpressed or silenced in several gallbladder cancer cell lines where molecular and biological analyses were performed. GCASPC levels were significantly lower in gallbladder cancer than adjacent nontumor tissues and were associated with tumor size, American Joint Committee on Cancer tumor stage, and patient outcomes. GCASPC overexpression suppressed cell proliferation in vitro and in vivo, whereas GCASPC silencing had opposite effects. By RNA pull-down and mass spectrometry, we identified pyruvate carboxylase as an RNA-binding protein that associated with GCASPC. Because GCASPC is a target of miR-17-3p, we confirmed that both miR-17-3p and GCASPC downregulated pyruvate carboxylase level and activity by limiting protein stability. Taken together, our results defined a novel mechanism of lncRNA-regulated cell proliferation in gallbladder cancer, illuminating a new basis for understanding its pathogenicity. Cancer Res; 76(18); 5361–71. ©2016 AACR.

Supplementary Methods. Description of additional methods and procedures used in the study.

Supplemental Table 1-9. Clinical characteristics of 5 GBC patients used for lncRNA array (Table 1). Clinicopathological characterisitcs of 42 GBC patients (Cohort 1) (Table 2). Clinicopathological characterisitcs of 89 GBC patients (Cohort 2) (Table 3). Correlation between GCASPC expression and GBC clinicopathological characteristics in 42 patients (Cohort 1) (Table 4). Univariate and multivariate analyses of OS in 89 GBC patients by Cox regression analysis (Table 5). Proteins in the three bands specific to GCASPC identified by MALDI-TOF mass spectrometry (Table 6). miRNAs binding sites of GCASPC by MirTarget2 (Table 7). Information on antibodies used for correlation analysis (Table 8). Primer sequence used in this study (Table 9). supplemental Figure 1-12. Expression levels of 10 lncRNAs by qRT-PCR in 15 GBC tissues and paired non-tumor tissues (Figure 1). Expression levels of 8 mRNAs by qRT-PCR in 15 GBC tissues and paired non-tumor tissues (Figure 2). Molecular characteristics of GCASPC (Figure 3). Nucleotide sequence of the full-length human GCASPC gene (Figure 4). GCASPC has no coding capability (Figure 5). The expression level of GCASPC in gallbladder cancer cells (Figure 6). Manipulation of GCASPC expression level (Figure 7). Anti-proliferative activity of GCASPC (Figure 8). GCASPC acts in trans (Figure 9). The effect of GCASPC on the protein, activity and mRNA levels of PC (Figure 10). GCASPC destabilizes PC protein (Figure 11). GCASPC directly binds to miR-17-3p (Figure 12).

Background: Kidney renal clear cell carcinoma (KIRC) is a representative histologic subtype of renal cell carcinoma (RCC). RCC exhibits a strong immunogenicity with a prominent dysfunctional immune infiltration. Complement C1q C chain (C1QC) is a polypeptide in serum complement system and is involved in tumorigenesis and the modulation of tumor microenvironment (TME). However, researches have not explored the effect of C1QC expression on prognosis and tumor immunity of KIRC.Methods: The difference in a wide variety of tumor tissues and normal tissues in terms of the C1QC expression was detected using TIMER and TCGA portal databases, and further validation of protein expression of C1QC was conducted via Human Protein Atlas. Then, the associations of C1QC expression with clinicopathological data and other genes were studied with the use of UALCAN database. Subsequently, the association of C1QC expression with prognosis was predicted by searching the Kaplan-Meier plotter database. A protein-protein interaction (PPI) network with the Metascape database was built using STRING software, such that the mechanism underlying the C1QC function can be studied in depth. The TISCH database assisted in the evaluation of C1QC expression in different cell types in KIRC at the single-cell level. Moreover, the association of C1QC and the infiltration level of tumor immune cell was assessed using TIMER platform. The TISIDB website was selected to deeply investigate the Spearman correlation between C1QC and immune-modulator expression. Lastly, how C1QC affected the cell proliferation, migration, and invasion in vitro was assessed using knockdown strategies.Results: KIRC tissues had notably upregulated C1QC level in comparison with adjacent normal tissues, with showed a positive relevance to clinicopathological features including tumor stage, grade, and nodal metastasis, and a negative relevance to clinical prognosis in KIRC. C1QC knockdown inhibited KIRC cell proliferation, migration, and invasion, as indicated by the results of the in vitro experiment. Furthermore, functional and pathway enrichment analysis demonstrated that C1QC was involved in immune system-related biological processes. According to single-cell RNA analysis, C1QC exhibited a specific upregulation in macrophages cluster. Additionally, there was an obvious association of C1QC and a wide variety of tumor-infiltrating immune cells in KIRC. Also, high C1QC expression presented inconsistent prognosis in different enriched immune cells subgroups in KIRC. Immune factors might contribute to C1QC function in KIRC.Conclusion: C1QC is qualified to predict KIRC prognosis and immune infiltration biologically. Targeting C1QC may bring new hope for the treatment of KIRC.

The gas-solid compatibility between environmentally friendly insulating gas and copper contacts is worth studying. In this paper, based on density functional theory, the adsorption calculation of CF3I, c-C4F8, five typical decomposition gases, and Cu (1 1 1) surface was carried out. The adsorption energies, transferred charges, charge densities, and densities of states were calculated for different adsorption configurations. Research indicates that there is no obvious charge transfer between the I atom and the Cu atom in the four adsorption sites of Cu (1 1 1) for the CF3I molecule. There is a charge transfer between the F atoms and the Cu top surface. The electrons lost by Cu are transferred to F atoms. In the configurations of different adsorption positions on CF3I and Cu (1 1 1) planes, the top and bridge adsorption energies are −0.835 eV and −0.993 eV, respectively, which are chemical adsorption. Therefore, CF3I is most likely to form adsorption at the top or bridge site of the Cu (1 1 1) surface. The adsorption energy of c-C4F8 gas on Cu (1 1 1) surface is similar to that of CF3I at fcc and hcp sites. The absolute values are all less than 0.8 eV, and the van der Waals force is the main force. The adsorption energies of C2F4 and C3F6 in the five decomposed gases are −1.315 eV and −1.204 eV, respectively. The charge transfer is −0.32 eV and −0.45 eV, respectively. Their values are larger than those of the other gases studied, which belong to chemical adsorption. The smaller values of the remaining three gases belong to physical adsorption. All molecular structures and Cu (1 1 1) planes were not significantly deformed. From a microscopic point of view, the gas can better exist on the copper surface.

By developing DPA-TPE-DCM with intense near-infrared fluorescence emission in the aggregation state, AIE materials were used for the first time in the early diagnosis of orthotopic TSCC and SLN mapping in an orthotopic TSCC-bearing mouse model.

Marine plankton have different biogeographical distribution patterns. However, it is not clear how the entire plankton assemblage is composed of these species with distinct biogeographical patterns. Tintinnina (tintinnids) is single-celled planktonic protozoa commonly used as model organisms in planktonic studies. In this research, we investigated the organization of Tintinnina assemblages along the Atlantic Meridional Transect (AMT) spanning over 90 degrees of latitude during the 29th AMT cruise (2019). Tintinnina with high frequency of occurrence was classified into four biogeographic distribution patterns (equatorial, gyre, frontal, and deep Chl a maximum) according to their vertical and horizontal distribution. All species falling within each distribution pattern formed a sub-assemblage. Equatorial sub-assemblage dominated in upper waters of the equatorial zone and gyre centres. Equatorial and frontal sub-assemblages co-dominated in upper waters of the frontal zones. Deep Chlorophyll a maximum Layer (DCM) sub-assemblage dominated in the DCM waters. Some Tintinnina species with high abundance could be used as indicator species of sub-assemblages. The Tintinnina assemblages in the northern and southern hemispheres exhibited asymmetry in terms of species composition. The latitudinal gradient of Tintinnina species richness was bimodal, which was shaped by the superposition of the species number of the four sub-assemblages with latitude. The result of this study contributes to the understanding of Tintinnina assemblage in the equatorial zone and subtropical gyres of the Pacific and Indian Ocean. It is also valuable for predicting the influence of global warming on changes in Tintinnina distribution and species richness.

In animal husbandry, feed efficiency is a crucial economic trait. In this study, the general linear model was used to perform association analysis for various genotypes and feed conversion ratio (FCR)-related traits. Reverse transcription-quantitative PCR (RT-qPCR) was used to detect the expression of SHISA3 and RFC3 mRNA levels in 10 tissues from 6 sheep. The results showed that SNPs in the NC_040257.1:c.625 T > C and NC_040261.1:g.9905 T > C were analyzed whether they were associated to feed efficiency parameters in Hu sheep (body weight, feed intake, average daily growth, and feed conversion ratio). NC_040257.1:c.625 T > C was shown to be significantly associated with body weight at 80, 100, and 120 days as well as feed conversion ratio (P < 0.05), whereas NC_040261.1:g.9905 T > C was found to be significantly associated with average daily weight gain from 80-140 days (ADG80-140) and FCR (P < 0.05). In Hu sheep, the CC genotypes of SHISA3 and RFC3 were the most common genotypes related to feed efficiency traits. Furthermore, the feed conversion ratio of the combined genotypes TTSHISA3-CCRFC3, TTSHISA3-CTRFC3, TTSHISA3-TTRFC3, CTSHISA3-CCRFC3 and CTSHISA3-CTRFC3 was significantly better than the FCR of CCSHISA3-TTRFC3. RT-qPCR results showed that the expression levels of SHISA3 were lower in the lung than in spleen, kidney, muscle and lymph (P < 0.05), and RFC3 was the lung had a highly significant higher expression level than the heart, liver, spleen, and muscle (P < 0.01). In conclusion, SHISA3 and RFC3 polymorphisms can be used as genetic markers for improving feed conversion efficiency in Hu sheep.

The air void content is one of the most important volumetric properties of asphalt matrixes, such as asphalt mixtures or mortars, because it can greatly affect the performance of the matrix. At the mixture level, there are standardized methods for measuring the air void content, which is an important design parameter of a mixture. However, at the mortar scale, no unified method has been proposed to determine the air void content corresponding to the asphalt mixture. Therefore, this research aims to, first, characterize the air void distribution within the mortar of an asphalt mixture and then develop an updated theoretical method for calculating the air void content of asphalt mortar. The internal structures of air voids from three commonly used asphalt mixtures with different gradations were captured using an industrial CT scanning technique and then morphologically characterized using the image analysis method. Three-dimensional models of the air voids were reconstructed, and the air void content calculated from the CT images was also verified by density tests. The scanning results show that the air void content and air void size fit the cumulative Weibull curve. The results show that the nominal maximum particle size (NMPS) of mortar and the mixture air void content were the main parameters that affected the mortar’s air voids. The mortar air void content had linear relationships with both the mixture air void content and the mixture asphalt aggregate ratio. The mortar air void content was more sensitive to the NMPS of the asphalt mixture compared with the air void content or asphalt aggregate ratio of the mixture. This research provides a quantitative method to calculate the air void content of asphalt mortar within a mixture, which may help in the matrix design of mortar.

The recent trend for multi-camera 3D object detection is through the unified bird's-eye view (BEV) representation. However, directly transforming features extracted from the image-plane view to BEV inevitably results in feature distortion, especially around the objects of interest, making the objects blur into the background. To this end, we propose OA-BEV, a network that can be plugged into the BEV-based 3D object detection framework to bring out the objects by incorporating object-aware pseudo-3D features and depth features. Such features contain information about the object's position and 3D structures. First, we explicitly guide the network to learn the depth distribution by object-level supervision from each 3D object's center. Then, we select the foreground pixels by a 2D object detector and project them into 3D space for pseudo-voxel feature encoding. Finally, the object-aware depth features and pseudo-voxel features are incorporated into the BEV representation with a deformable attention mechanism. We conduct extensive experiments on the nuScenes dataset to validate the merits of our proposed OA-BEV. Our method achieves consistent improvements over the BEV-based baselines in terms of both average precision and nuScenes detection score. Our codes will be published.

The prevalence of hypertension (HTN) is higher in patients with non-alcoholic fatty liver disease (NAFLD). Inflammation is the key link between HTN and NAFLD. Systemic inflammation can be dramatically increased by inflammatory diet intake. However, whether controlling the inflammatory diet intake in NAFLD patients could affect the occurrence of HTN still remains unknown. Our aim here is to evaluate the effect of the dietary inflammatory index (DII) on blood pressure in patients with different grades of hepatic steatosis. The data were collected from the National Health and Nutrition Examination Survey (NHANES) (2017-2018). DII was calculated based on the data of 24-h dietary recall interviews. The severity of liver steatosis was assessed by a controlled attenuation parameter. Multivariable logistic regression, multivariable linear regression and subgroup analyses were conducted to determine the association between DII and blood pressure in patients with different degrees of hepatic steatosis. A total of 5449 participants were included in this analysis. In male participants with severe liver steatosis (S3), the highest DII tertile group was more likely to have higher systolic blood pressure (SBP) compared with the lowest tertile group (Tertile1: 128.31(125.31,131.31), Tertile3: 133.12(129.40,136.85), P for trend =0.03551). DII was positively correlated with SBP and the prevalence of HTN in males with hepatic steatosis grade S3 (≥ 67% steatosis) (SBP: P for trend = 0.011, HTN: P for trend = 0.039). Regarding the association of DII with SBP and HTN, the tests for interaction were significant for hepatic steatosis (SBP: interaction for p = 0.0015, HTN: interaction for p = 0.0202). In the present study, we demonstrated that DII was a risk factor for increased SBP and the prevalence of HTN in males with severe hepatic steatosis S3, indicating that anti-inflammatory dietary management should be considered in these individuals to reduce the risk of developing HTN. Patients in the highest DII tertiles group had a higher SBP and higher rates of HTN compared with patients in the lowest DII tertiles group in male participants with severe hepatic steatosis S3.DII was positively associated with SBP and the prevalence of HTN in males with hepatic steatosis grade S3.The effect of DII on SBP and prevalence of HTN was significantly dependent on the severity of hepatic steatosis. Patients in the highest DII tertiles group had a higher SBP and higher rates of HTN compared with patients in the lowest DII tertiles group in male participants with severe hepatic steatosis S3. DII was positively associated with SBP and the prevalence of HTN in males with hepatic steatosis grade S3. The effect of DII on SBP and prevalence of HTN was significantly dependent on the severity of hepatic steatosis.

Additional file 1.

Supplementary Material

Image deep steganography (IDS) is a technique that utilizes deep learning to embed a secret image invisibly into a cover image to generate a container image. However, the container images generated by convolutional neural networks (CNNs) are vulnerable to attacks that distort their high-frequency components. To address this problem, we propose a novel method called Low-frequency Image Deep Steganography (LIDS) that allows frequency distribution manipulation in the embedding process. LIDS extracts a feature map from the secret image and adds it to the cover image to yield the container image. The container image is not directly output by the CNNs, and thus, it does not contain high-frequency artifacts. The extracted feature map is regulated by a frequency loss to ensure that its frequency distribution mainly concentrates on the low-frequency domain. To further enhance robustness, an attack layer is inserted to damage the container image. The retrieval network then retrieves a recovered secret image from a damaged container image. Our experiments demonstrate that LIDS outperforms state-of-the-art methods in terms of robustness, while maintaining high fidelity and specificity. By avoiding high-frequency artifacts and manipulating the frequency distribution of the embedded feature map, LIDS achieves improved robustness against attacks that distort the high-frequency components of container images.

Transformers have been shown to work well for the task of English euphemism disambiguation, in which a potentially euphemistic term (PET) is classified as euphemistic or non-euphemistic in a particular context. In this study, we expand on the task in two ways. First, we annotate PETs for vagueness, a linguistic property associated with euphemisms, and find that transformers are generally better at classifying vague PETs, suggesting linguistic differences in the data that impact performance. Second, we present novel euphemism corpora in three different languages: Yoruba, Spanish, and Mandarin Chinese. We perform euphemism disambiguation experiments in each language using multilingual transformer models mBERT and XLM-RoBERTa, establishing preliminary results from which to launch future work.

System resolution

Latent Gaussian process (GP) models are widely used in neuroscience to uncover hidden state evolutions from sequential observations, mainly in neural activity recordings. While latent GP models provide a principled and powerful solution in theory, the intractable posterior in non-conjugate settings necessitates approximate inference schemes, which may lack scalability. In this work, we propose cvHM, a general inference framework for latent GP models leveraging Hida-Mat\'ern kernels and conjugate computation variational inference (CVI). With cvHM, we are able to perform variational inference of latent neural trajectories with linear time complexity for arbitrary likelihoods. The reparameterization of stationary kernels using Hida-Mat\'ern GPs helps us connect the latent variable models that encode prior assumptions through dynamical systems to those that encode trajectory assumptions through GPs. In contrast to previous work, we use bidirectional information filtering, leading to a more concise implementation. Furthermore, we employ the Whittle approximate likelihood to achieve highly efficient hyperparameter learning., Comment: Published at ICML 2023

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