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Abstract High performance imaging in parallel cameras is a worldwide challenge in computational optics studies. However, the existing solutions are suffering from a fundamental contradiction between the field of view (FOV), resolution and bandwidth, in which system speed and FOV decrease as system scale increases. Inspired by the compound eyes of mantis shrimp and zoom cameras, here we break these bottlenecks by proposing a deep learning-based parallel (DLBP) camera, with an 8-μrad instantaneous FOV and 4 × computational zoom at 30 frames per second. Using the DLBP camera, the snapshot of 30-MPs images is captured at 30 fps, leading to orders-of-magnitude reductions in system complexity and costs. Instead of directly capturing photography with large scale, our interactive-zoom platform operates to enhance resolution using deep learning. The proposed end-to-end model mainly consists of multiple convolution layers, attention layers and deconvolution layer, which preserves more detailed information that the image reconstructs in real time compared with the famous super-resolution methods, and it can be applied to any similar system without any modification. Benefiting from computational zoom without any additional drive and optical component, the DLBP camera provides unprecedented-competitive advantages in improving zoom response time (~ 100 ×) over the comparison systems. Herein, with the experimental system described in this work, the DLBP camera provides a novel strategy to solve the inherent contradiction among FOV, resolution and bandwidth.

Introduction. The interaction between diabetes, obesity, and bone metabolism was drawing increasing public attention. However, the osteometabolic changes in diabetes mellitus type 2 (T2DM) patients with abdominal obesity have not been fully revealed. This study is aimed at investigating the association between abdominal obesity indices and bone turnover markers among T2DM participants. Methods. 4351 subjects were involved in the METAL study. Abdominal obesity indices included neck, waist, and hip circumference, visceral adiposity index (VAI), lipid accumulation product (LAP), waist-to-hip ratio (WHR), and Chinese visceral adiposity index (CVAI). They were applied to elucidate the nexus between β-C-terminal telopeptide (β-CTX), osteocalcin (OC), and intact N-terminal propeptide of type I collagen (P1NP). Results. Abdominal obesity indices were strongly negatively associated with β-CTX and OC. Among males, five indices were negatively correlated with β-CTX (BMI, WC, LAP, WHR, and CVAI) and OC (BMI, NC, WC, WHR, and CVAI). There were no significant associations with P1NP. Among females, all eight indices were negatively associated with β-CTX. Seven indices were negatively related to OC (BMI, NC, WC, HC, LAP, WHR, and CVAI). The VAI was negatively correlated with P1NP. Conclusions. The present study demonstrated that in T2DM, abdominal obesity had an obviously negative correlation with bone metabolism. Abdominal obesity indices were significantly negatively associated with skeletal destruction (β-CTX) and formation (OC). In routine clinical practice, these easily obtained indices could be used as a preliminary screening method and relevant factors for osteodysfunction incidence risk at no additional cost and may be of particular value for postmenopausal women in T2DM populations.

Problem definition: We study stochastic periodic-review inventory systems with lost sales, where the decision maker has no access to the true demand distribution a priori and can only observe historical sales data (referred to as censored demand) and feature information about the demand. In an inventory system, excess demand is unobservable because of inventory constraints, and sales data alone cannot fully recover the true demand. Meanwhile, feature information about the demand is abundant to assist inventory decisions. We incorporate features for inventory systems with censored demand. Methodology/results: We propose two feature-based inventory algorithms called the feature-based adaptive inventory algorithm and the dynamic shrinkage algorithm. Both algorithms are based on the stochastic gradient descent method. We measure the performance of the proposed algorithms through the average expected regret in finite periods: that is, the difference between the cost of our algorithms and that of a clairvoyant optimal policy with access to information, which is acting optimally. We show that the average expected cost incurred under both algorithms converges to the clairvoyant optimal cost at the rate of O(log T/T) for the perishable inventory case and O(1/T) for the nonperishable inventory case. The feature-based adaptive inventory algorithm results in high volatility in the stochastic gradients, which hampers the initial performance of regret. The dynamic shrinkage algorithm uses a shrinkage parameter to adjust the gradients, which significantly improves the initial performance. Managerial implications: This paper considers feature information. The idea of dynamic shrinkage for the stochastic gradient descent method builds on a fundamental insight known as the bias-variance trade-off. Our research shows the importance of incorporating the bias-variance in a dynamic environment for inventory systems with feature information. Funding: W. T. Huh acknowledges support from the NSERC Discovery Grants [Grant RGPIN 2020-04213] and the Canada Research Chair Program. The work of Y. Rong was supported by the National Natural Science Foundation of China [Grants 72025201, 72331006, and 72221001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0135. [ABSTRACT FROM AUTHOR]

Artemisia argyi H.Lév. & Vaniot essential oil (AAEO) has shown pharmacological effects such as anti‐inflammation, antioxidant, and anti‐tumor properties. However, the protective effect of AAEO on lipopolysaccharide (LPS)‐induced liver injury and its potential protective mechanism are still unclear. In this study, we used ultra‐performance liquid chromatography tandem mass spectrometry metabolomics techniques to investigate the changes in liver tissue metabolites in mice exposed to LPS with or without AAEO treatment for 14 days. The biochemical results showed that compared with the control group, AAEO significantly reduced the levels of liver functional enzymes, suggesting a significant improvement in liver injury. In addition, the 18 differential metabolites identified by metabolomics were mainly involved in the reprogramming of arachidonic acid metabolism, tryptophan metabolism, and purine metabolism. AAEO could significantly inhibit the expression of COX‐2, IDO1, and NF‐κB; enhance the body's anti‐inflammatory ability; and alleviate liver injury. In summary, our study identified the protective mechanism of AAEO on LPS‐induced liver injury at the level of small molecular metabolites, providing a potential liver protective agent for the treatment of LPS‐induced liver injury. [ABSTRACT FROM AUTHOR]

Environmental pollution and resource waste in Chinese cities have become important obstacles to sustainable economic development, and it is urgent to change the mode of economic development and improve the quality of economic development. In response to this challenge, this study proposes environmental regulation as a solution and empirically tests the impact of environmental regulation on green total factor productivity. The empirical results show that environmental regulation can significantly improve urban green total factor productivity, the public environmental concern and green finance strengthen the positive effect of environmental regulation on urban green total factor productivity. The mechanism test shows that environmental regulation can improve urban green total factor productivity through green technological innovation and industrial structure upgrading. Heterogeneity analysis reveals that, compared to the resource-based cities, the positive effect of environmental regulation on urban green total factor productivity is more significant in the non-resource-based cities with relatively developed traditional finance and high levels of industrial modernisation. Compared to the central and western as well as the northeast regions of China, the positive effect of environmental regulation on urban green total factor productivity is more significant in the eastern region due to capital accumulation and technological constraints. The results of the study remain reliable after a series of endogeneity and robustness tests. These studies provide an important research basis for providing more targeted environmental regulation programmes and better improving green total factor productivity. [ABSTRACT FROM AUTHOR]

Facial recognition payment technology (FR) has the potential to disrupt the offline retailing industry by automating the payment process. However, some firms that adopted FR payment technology have experienced only moderate success, and many customers have expressed frustration using FR payment technology. By utilizing data sets from three retail chains, we find that customers are less likely to use FR payment technology during self-checkouts when more customers are in line behind them, waiting and watching (the social presence effect), and when more preceding customers use the other payment technology (the herding effect). These findings imply that (1) the design of FR technology can be improved to alleviate the social presence effect (such as adding a privacy screen filter or beautify the appearance of the consumer's image), and (2) monetary incentives may be used to attract more users by leveraging the herding effect. Although facial recognition (FR) payment technology can be more convenient for customers, it is still not consistently used by many customers in retail. Using transaction data from three retail chains, we develop econometric models and an estimation strategy for examining the social presence and herding effects that affect FR payment technology use. Our key findings are as follows: (1) Customers are less likely to use FR payment technology when more customers are in line behind them, waiting and potentially watching—the social presence effect. (2) Customers are more likely to use FR payment technology when more preceding customers use FR payment technology—the herding effect. (3) Customers with more experience using FR payment technology are subject to a weaker social presence effect. The marginal social presence effect can result in a 4.75% reduction in the probability of the focal customer using FR payment technology, and the potential social presence effect can be as high as 48.42%. When the focal customer has one additional experience in using FR payment technology, the social presence effect is reduced by 7.79%. The herding effect can result in a 20.90% increase in the probability of the focal customer using FR payment technology. Theoretical and managerial implications are discussed. History: Rajiv Kohli served as the senior editor for this article. Funding: Y. Rong's work was supported by the National Natural Science Foundation of China [Grants 72025201 and 72221001]. X. Tian's work was supported by the National Natural Science Foundation of China [Grants 72172145 and 71932002], the Beijing Natural Science Foundation [Grant 9212020], and the Fundamental Research Funds for the Central Universities. J. Gao's work was supported by the National Natural Science Foundation of China [Grant 72232001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1205. [ABSTRACT FROM AUTHOR]

In view of the failure of GNSS signals, this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network (RNN). This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS, thereby obtaining a continuous, reliable and high-precision navigation solution. The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment. Subsequently, an experimental test on boat is also conducted to validate the performance of the method. The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal, as it outperforms extreme learning machine (ELM) and EKF by approximately 30% and 60%, respectively.

Abstract Background Excessive reactive oxygen species from endothelial mitochondria in type 2 diabetes individuals (T2DM) may occur through multiple related mechanisms, including production of mitochondrial reactive oxygen species (mtROS), inner mitochondrial membrane (Δψm) hyperpolarization, changes in mitochondrial mass and membrane composition, and fission of the mitochondrial networks. Inner mitochondrial membrane proteins uncoupling protein-2 (UCP2) and prohibitin (PHB) can favorably impact mtROS and mitochondrial membrane potential (Δψm). Circulating levels of UCP2 and PHB could potentially serve as biomarker surrogates for vascular health in patients with and without T2DM. Methods Plasma samples and data from a total of 107 individuals with (N = 52) and without T2DM (N = 55) were included in this study. Brachial artery flow mediated dilation (FMD) was measured by ultrasound. ELISA was performed to measure serum concentrations of PHB1 and UCP2. Mitochondrial membrane potential was measured from isolated leukocytes using JC-1 dye. Results Serum UCP2 levels were significantly lower in T2DM subjects compared to control subjects (3.01 ± 0.34 vs. 4.11 ± 0.41 ng/mL, P = 0.04). There were no significant differences in levels of serum PHB. UCP2 levels significantly and positively correlated with FMDmm (r = 0.30, P = 0.03) in T2DM subjects only and remained significant after multivariable adjustment. Within T2DM subjects, serum PHB levels were significantly and negatively correlated with UCP2 levels (ρ = − 0.35, P = 0.03). Conclusion Circulating UCP2 levels are lower in T2DM patients and correlate with endothelium-dependent vasodilation in conduit vessels. UCP2 could be biomarker surrogate for overall vascular health in patients with T2DM and merits additional investigation.

Abstract Background The accurate evaluation of BRAFV600E mutation in preoperative fine‐needle aspiration cytology (FNAC) specimens is important for making management decisions in thyroid nodules (TNs). The aim of this study was to assess the false‐positive and false‐negative BRAFV600E mutations in thyroid FNAC specimens and their influence on diagnosis of TN. Methods This prospective study enrolled 292 nodules in 269 patients who underwent BRAFV600E mutation analysis using amplification refractory mutation system‐quantitative real‐time polymerase chain reaction (ARMS‐qPCR) both in FNAC specimens and formalin‐fixed, paraffin‐embedded (FFPE) tissue samples after surgery. The false‐positive and false‐negative mutations for BRAFV600E analysis using ARMS‐qPCR in FNAC specimens were recorded, with reference to the results of BRAFV600E mutation analysis using ARMS‐qPCR in FFPE tissue sample. Diagnostic performances of FNAC, BRAFV600E mutation analysis in FNAC specimens, BRAFV600E mutation analysis in FFPE tissue sample, and the combination of FNAC and BRAFV600E mutation analysis for predicting thyroid malignancy were assessed. Results The false‐positive and false‐negative mutations for BRAFV600E analysis using ARMS‐qPCR in FNAC specimens were 10.1% (19/189) and 7.1% (7/98), respectively. FNAC combined with preoperative BRAFV600E mutation analysis significantly increased the diagnostic sensitivity from 75.7% to 92.3%, and accuracy from 78.7% to 90.6% in comparison with FNAC alone (both P .05). Conclusions FNAC combined with preoperative BRAFV600E mutation analysis can significantly increase the diagnostic performance in comparison with FNAC alone. False‐positive and false‐negative BRAFV600E mutation results are found in preoperative FNAC specimens, whereas it does not affect the overall auxiliary diagnosis of TNs.

BackgroundThe interrelation between glucose and bone metabolism is complex and has not been fully revealed. This study aimed to investigate the association between insulin resistance, β-cell function and bone turnover biomarker levels among participants with abnormal glycometabolism.MethodsA total of 5277 subjects were involved through a cross-sectional study (METAL study, http://www.chictr.org.cn, ChiCTR1800017573) in Shanghai, China. Homeostasis model assessment of insulin resistance (HOMA-IR) and β-cell dysfunction (HOMA-%β) were applied to elucidate the nexus between β-C-terminal telopeptide (β-CTX), intact N-terminal propeptide of type I collagen (P1NP) and osteocalcin (OC). β-CTX, OC and P1NP were detected by chemiluminescence.ResultsHOMA-IR was negatively associated with β-CTX, P1NP and OC (regression coefficient (β) -0.044 (-0.053, -0.035), Q4vsQ1; β -7.340 (-9.130, -5.550), Q4vsQ1 and β -2.885 (-3.357, -2.412), Q4vsQ1, respectively, all P for trend