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Graph-Level Anomaly Detection (GLAD) aims to distinguish anomalous graphs within a graph dataset. However, current methods are constrained by their receptive fields, struggling to learn global features within the graphs. Moreover, most contemporary methods are based on spatial domain and lack exploration of spectral characteristics. In this paper, we propose a multi-perspective hybrid graph-level anomaly detector namely GLADformer, consisting of two key modules. Specifically, we first design a Graph Transformer module with global spectrum enhancement, which ensures balanced and resilient parameter distributions by fusing global features and spectral distribution characteristics. Furthermore, to uncover local anomalous attributes, we customize a band-pass spectral GNN message passing module that further enhances the model's generalization capability. Through comprehensive experiments on ten real-world datasets from multiple domains, we validate the effectiveness and robustness of GLADformer. This demonstrates that GLADformer outperforms current state-of-the-art models in graph-level anomaly detection, particularly in effectively capturing global anomaly representations and spectral characteristics.

Nowadays, indoor localization has received extensive research interest due to more and more applications' needs for location information to provide a more precise and effective service [1], [2]. There are various wireless techniques and mechanisms that have been proposed; some of them have been studied in depth and come into use, such as Wi-Fi, RFID, and sensor networks. In comparison, the development of Bluetooth location technology is slow and there are not many papers and surveys in this field, although the performance and market value of Bluetooth are increasing steadily. In this paper, we aim to provide a detailed survey of various indoor localization systems with Bluetooth. In contrast with the existing surveys, we categorize the exciting localization techniques that have been proposed in the literature in order to sketch the development of Bluetooth location compared to other technologies. We also evaluate different systems from the perspective of availability, cost, scalability, and accuracy. We also discuss remaining problems and challenges to accurate Bluetooth localization., Comment: 8 pages, 2 figures

In this paper, we investigate an optimal control problem governed by parabolic equations with measure-valued controls over time. We establish the well-posedness of the optimal control problem and derive the first-order optimality condition using Clarke's subgradients, revealing a sparsity structure in time for the optimal control. Consequently, these optimal control problems represent a generalization of impulse control for evolution equations. To discretize the optimal control problem, we employ the space-time finite element method. Here, the state equation is approximated using piecewise linear and continuous finite elements in space, alongside a Petrov-Galerkin method utilizing piecewise constant trial functions and piecewise linear and continuous test functions in time. The control variable is discretized using the variational discretization concept. For error estimation, we initially derive a priori error estimates and stabilities for the finite element discretizations of the state and adjoint equations. Subsequently, we establish weak-* convergence for the control under the norm $\mathcal{M}(\bar I_c;L^2(\omega))$, with a convergence order of $O(h^\frac{1}{2}+\tau^\frac{1}{4})$ for the state.

Leaf functional traits are key indicators of plant functions useful for inferring complex plant processes, including their responses to environmental changes. Vegetation indices (VIs) composed of a few reflectance wavelengths hold the advantages of being relatively simple and effective and have been widely used within remote sensing to estimate leaf traits. However, the difference between the reflectance from the upper and lower part of the leaf suggests that leaf reflectance mainly provides one-sided information, constraining its ability to estimate leaf functional traits. Leaf transmittance, on the other hand, gives information about the whole leaf and has more potential to be sensitive to changes in leaf biochemistry. As transmittance-based VI is rare, this study aims to propose new transmittance-based VIs for accurate estimations of leaf traits. Three forms, i.e. the normalized difference VI, the simple ratio VI, and the difference VI were employed, and wavelength selection for transmittance-based and reflectance-based VIs were conducted, respectively. The applicability of these VIs for estimating four leaf functional traits (leaf chlorophyll (Cab), leaf carotenoids (Car), equivalent water thickness (EWT), and leaf mass per area (LMA)) were evaluated. Cross-validation using three datasets of field observations and sensitivity analysis showed that the VIs constructed using transmittance were relatively less affected by interferences from other leaf parameters, improving the estimation accuracy of Car, EWT, and LMA compared to their optimal reflectance counterparts (RMSE reduced by 2% to 15%, and MAE reduced by 7% to 20% for the pooled dataset). Our study revealed that the normalized difference VI based on transmittance showed considerable sensitivity to Car, EWT, and LMA, whereas the difference VI based on reflectance was effective in indicating Cab. The proposed transmittance-based VIs will aid remote mon

The gut microbiome is recognized as a key modulator of sepsis development. However, the contribution of the gut mycobiome to sepsis development is still not fully understood. Here, we demonstrated that the level of Candida albicans was markedly decreased in patients with bacterial sepsis, and the supernatant of Candida albicans culture significantly decreased the bacterial load and improved sepsis symptoms in both cecum ligation and puncture (CLP)-challenged mice and Escherichia coli-challenged pigs. Integrative metabolomics and the genetic engineering of fungi revealed that Candida albicans-derived phenylpyruvate (PPA) enhanced the bactericidal activity of macrophages and reduced organ damage during sepsis. Mechanistically, PPA directly binds to sirtuin 2 (SIRT2) and increases reactive oxygen species (ROS) production for eventual bacterial clearance. Importantly, PPA enhanced the bacterial clearance capacity of macrophages in sepsis patients and was inversely correlated with the severity of sepsis in patients. Our findings highlight the crucial contribution of commensal fungi to bacterial disease modulation and expand our understanding of the host-mycobiome interaction during sepsis development. © 2023, The Author(s), under exclusive licence to CSI and USTC., Funding: The National Natural Science Foundation of China (32271230 and 32071124) to PC; the NIH Grant (P30DK120515) to BS; the National Natural Science Foundation of China (82270581) to YC; the National Key R&D Project of China (2018YFC0115301), the National Natural Science Foundation of China (81974070), the Shenzhen Science and Technology Program (JCYJ20210324131010027) and the Research Foundation of Shenzhen Hospital of Southern Medical University (PT2018GZR10) to WG.

Supply chain management is aimed to keep going long-term performance of the supply chain and minimize the costs. Backscatter technology provides a more efficient way of being able to identify items and real-time monitoring. Among the backscatter systems, the ambient backscatter communication (AmBC) system provides a prospect of ultra-low energy consumption and does not require controlled excitation devices. In this paper, we introduce CRCScatter, a CRC reverse algorithm-based AmBC system using a single access point (AP). A CRC reverse decoder is applied to reverse the ambient data from CRC32 sequence in the backscatter packet and realize single-AP decoding. Based on the nature of DBPSK modulation in WiFi signal, the CRCScatter system obtains the tag data by XOR and Differential decoder. Our simulation results verify the effectiveness of our proposed system in the low SNR regime. The average decoding time of CRCScatter system is independent of the length of tag data. Furthermore, our system can append redundant bits in the tag data to improve the decoding accuracy while not increasing the decoding time.

BACKGROUND: The mortality following ST-segment elevation myocardial infarction (STEMI) remains substantial in the reperfusion era. Shenfu injection, as a traditional Chinese herbal formula, can alleviate ischemia-reperfusion injury through multiple pharmacologic effects. However, no robust data are available regarding the role of Shenfu injection in reducing infarct size for patients with STEMI undergoing primary percutaneous coronary intervention (PPCI). METHODS/DESIGN: This RESTORE trial is a multicenter, randomized, double-blind, parallel-group, placebo-controlled trial (NCT04493840). A total of 326 eligible patients with first-time anterior STEMI undergoing PPCI within 12 h of symptom onset will be enrolled from 10 centers in mainland China. Patients are randomized in a 1:1 fashion to receive either intravenous Shenfu injection (80mL Shenfu injection + 70mL 5% glucose injection) or placebo group (150mL 5% glucose injection) before reperfusion and followed by once a day until 5 days after PPCI. The primary end point is infarct size assessed by cardiac magnetic resonance (CMR) imaging 5±2 days after PPCI. The major secondary end points include enzymatic infarct size, microvascular obstruction, intramyocardial hemorrhage, left ventricular volume and ejection fraction assessed by CMR, as well as cardiovascular events at 30 days. CONCLUSIONS: The RESTORE trial is sufficiently powered to demonstrate the clinical effects of Shenfu injection on myocardial injury in STEMI patients undergoing PPCI in the contemporary era.

In this paper we propose a new finite element method for solving elliptic optimal control problems with pointwise state constraints, including the distributed controls and the Dirichlet or Neumann boundary controls. The main idea is to use energy space regularizations in the objective functional, while the equivalent representations of the energy space norms, i.e., the $H^{-1}(\Omega)$-norm for the distributed control, the $H^{1/2}(\Gamma)$-norm for the Dirichlet control and the $H^{-1/2}(\Gamma)$-norm for the Neumann control, enable us to transform the optimal control problem into an elliptic variational inequality involving only the state variable. The elliptic variational inequalities are second order for the three cases, and include additional equality constraints for Dirichlet or Neumann boundary control problems. Standard $C^0$ finite elements can be used to solve the resulted variational inequality. We provide preliminary a priori error estimates for the new algorithm for solving distributed control problems. Extensive numerical experiments are carried out to validate the accuracy of the new algorithm.

The boom of the Internet of Things has revolutionized people's lives, but it has also resulted in massive resource consumption and environmental pollution. Recently, Green IoT (GIoT) has become a worldwide consensus to address this issue. In this paper, we propose EEWScatter, an energy-efficient WiFi backscatter communication system to pursue the goal of GIoT. Unlike previous backscatter systems that solely focus on tags, our approach offers a comprehensive system-wide view on energy conservation. Specifically, we reuse ambient signals as carriers and utilize an ultra-low-power and battery-free design for tag nodes by backscatter. Further, we design a new CRC-based algorithm that enables the demodulation of both ambient and tag data by only a single receiver while using ambient carriers. Such a design eliminates system reliance on redundant transceivers with high power consumption. Results demonstrate that EEWScatter achieves the lowest overall system power consumption and saves at least half of the energy. What's more, the power consumption of our tag is only 1/1000 of that of active radio. We believe that EEWScatter is a critical step towards a sustainable future.

The aim of this paper is to study the shape optimization method for solving the Bernoulli free boundary problem, a well-known ill-posed problem that seeks the unknown free boundary through Cauchy data. Different formulations have been proposed in the literature that differ in the choice of the objective functional. Specifically, it was shown respectively in [14] and [16] that tracking Neumann data is well-posed but tracking Dirichlet data is not. In this paper we propose a new well-posed objective functional that tracks Dirichlet data at the free boundary. By calculating the Euler derivative and the shape Hessian of the objective functional we show that the new formulation is well-posed, i.e., the shape Hessian is coercive at the minimizers. The coercivity of the shape Hessian may ensure the existence of optimal solutions for the nonlinear Ritz-Galerkin approximation method and its convergence, thus is crucial for the formulation. As a summary, we conclude that tracking Dirichlet or Neumann data in its energy norm is not sufficient, but tracking it in a half an order higher norm will be well-posed. To support our theoretical results we carry out extensive numerical experiments., Comment: 27 pages, 6 figures, 4 tables, 27 references, will be resubmitted

Cloud-aided mobile edge networks (CAMENs) allow edge servers (ESs) to purchase resources from remote cloud servers (CSs), while overcoming resource shortage when handling computation-intensive tasks of mobile users (MUs). Conventional trading mechanisms (e.g., onsite trading) confront many challenges, including decision-making overhead (e.g., latency) and potential trading failures. This paper investigates a series of cross-layer matching mechanisms to achieve stable and cost-effective resource provisioning across different layers (i.e., MUs, ESs, CSs), seamlessly integrated into a novel hybrid paradigm that incorporates futures and spot trading. In futures trading, we explore an overbooking-driven aforehand cross-layer matching (OA-CLM) mechanism, facilitating two future contract types: contract between MUs and ESs, and contract between ESs and CSs, while assessing potential risks under historical statistical analysis. In spot trading, we design two backup plans respond to current network/market conditions: determination on contractual MUs that should switch to local processing from edge/cloud services; and an onsite cross-layer matching (OS-CLM) mechanism that engages participants in real-time practical transactions. We next show that our matching mechanisms theoretically satisfy stability, individual rationality, competitive equilibrium, and weak Pareto optimality. Comprehensive simulations in real-world and numerical network settings confirm the corresponding efficacy, while revealing remarkable improvements in time/energy efficiency and social welfare.

In this paper, we consider the finite element approximation to a parabolic Dirichlet boundary control problem and establish new a priori error estimates. In the temporal semi-discretization we apply the DG(0) method for the state and the variational discretization for the control, and obtain the convergence rates $O(k^{\frac{1}{4}})$ and $O(k^{\frac{3}{4}-\varepsilon})$ $(\varepsilon>0)$ for the control for problems posed on polytopes with $y_0\in L^2(\Omega)$, $y_d\in L^2(I;L^2(\Omega))$ and smooth domains with $y_0\in H^{\frac{1}{2}}(\Omega)$, $y_d\in L^2(I;H^1(\Omega))\cap H^{\frac{1}{2}}(I;L^2(\Omega))$, respectively. In the fully discretization of the optimal control problem posed on polytopal domains, we apply the DG(0)-CG(1) method for the state and the variational discretization approach for the control, and derive the convergence order $O(k^{\frac{1}{4}} +h^{\frac{1}{2}})$, which improves the known results by removing the mesh size condition $k=O(h^2)$ between the space mesh size $h$ and the time step $k$. As a byproduct, we obtain a priori error estimate $O(h+k^{1\over 2})$ for the fully discretization of parabolic equations with inhomogeneous Dirichlet data posed on polytopes, which also improves the known error estimate by removing the above mesh size condition.

The challenge of exchanging and processing of big data over mobile crowdsensing (MCS) networks calls for designing seamless data service provisioning mechanisms to enable utilization of resources of mobile devices/users for crowdsensing tasks. Although conventional onsite spot trading of resources based on real-time network conditions can facilitate data sharing, it often suffers from prohibitively long service provisioning delays and unavoidable trading failures due to requiring timely analysis of dynamic network environment. These limitations motivate us to investigate an integrated forward and spot trading mechanism (iFAST), which entails a novel hybrid data trading protocol with time efficiency, over uncertain MCS ecosystems. In iFAST, the sellers (i.e., mobile devices who can contribute data) can provide long-term or temporary sensing services to the buyers (i.e., sensing tasks). Specifically, it enables signing long-term contracts in advance of future transactions through a forward trading mode, via analyzing historical statistics of the network/market, for which the notion of overbooking is introduced and promoted. iFAST further encourages the buyers with unsatisfying service quality to recruit temporary sellers through a spot trading mode, considering the current network/market conditions. We analyze the fundamental blocks of iFAST and provide a case study to demonstrate its performance. Inspirations for future research directions of next-generation sensing and communication are summarized.

Leaf pigments are critical indicators of plant photosynthesis, stress, and physiological conditions. Inversion of radiative transfer models (RTMs) is a promising method for robustly retrieving leaf biochemical traits from canopy observations, and adding prior information has been effective in alleviating the "ill-posed" problem, a major challenge in model inversion. Canopy structure parameters, such as leaf area index (LAI) and average leaf inclination angle (ALA), can serve as prior information for leaf pigment retrieval. Using canopy spectra simulated from the PROSAIL model, we estimated the effects of uncertainty in LAI and ALA used as prior information for lookup table-based inversions of leaf chlorophyll (C-ab) and carotenoid (C-ar). The retrieval accuracies of the two pigments were increased by use of the priors of LAI (RMSE of C(ab )from 7.67 to 6.32 mu g cm(2) , C-ar from 2.41 to 2.28 mu g cm(2)) and ALA (RMSE of C-ab from 7.67 to 5.72 mu g cm(2) , C-ar from 2.41 to 2.23 mu g cm(2)). However, this improvement deteriorated with an increase of additive and multiplicative uncertainties, and when 40% and 20% noise was added to LAI and ALA respectively, these priors ceased to increase retrieval accuracy. Validation using an experimental winter wheat dataset also showed that compared with C-ar , the estimation accuracy of C-ab increased more or deteriorated less with uncertainty in prior canopy structure. This study demonstrates possible limitations of using prior information in RTM inversions for retrieval of leaf biochemistry, when large uncertainties are present. (C) 2022 Crop Science Society of China and Institute of Crop Science, CAAS. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd.

Kui Wu,* Hui-Hui Ke,* Wei Gong, Hua Hu, Li Chen Department of Obstetrics and Gynecology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, People’s Republic of China*These authors contributed equally to this workCorrespondence: Li Chen; Hua Hu, Department of Obstetrics and Gynecology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Shanghai, 201399, People’s Republic of China, Tel +86 21 5802 2995, Email chenli8369@163.com; Huhua20212022@163.comAim: To assess the impact of maternal pre-pregnancy body mass index (BMI) on gestational diabetes mellitus (GDM) based on different pre-pregnancy hemoglobin levels.Methods: This retrospective cohort study included 1289 pregnant women between June 2020 and January 2022. Clinical data were collected by reviewing their medical and antepartum screening records between 24 and 28 gestational weeks, including pre-pregnancy BMI and pre-pregnancy hemoglobin (Hb) levels. The diagnosis of GDM mainly depended on oral glucose tolerance test (OGTT) during 24– 28 weeks. Restricted cubic spline (RCS) was used to investigate the association between the pre-pregnancy Hb level and the risk of GDM. Univariate and multivariate logistic regression analyses were applied to evaluate the relative risk of GDM.Results: Of the 1289 included pregnant women, 187 (14.5%) women were diagnosed with GDM in this study. The pre-pregnancy Hb level was significantly associated with GDM risk, and the pre-pregnancy Hb level of 123 g/L was identified as the threshold to stratify and assess the association between the GDM risk and the pre-pregnancy BMI. For women with a pre-pregnancy Hb level ≥ 123 g/L, the pre-pregnancy BMI showed a significant association with GDM risk, and the estimated incidence rate of GDM was 7.7%, 14.8%, 36.3% and 44% for underweight, normal-weight, overweight and obese pregnant women, respectively. After adjusting for potential influencing f

In [ESAIM: M2AN, 54(2020), 2229-2264], we proposed an HDG method to approximate the solution of a tangential boundary control problem for the Stokes equations and obtained an optimal convergence rate for the optimal control {that reflects its global regularity}. However, the error estimates depend on the pressure, and the velocity is not divergence free. The importance of pressure-robust numerical methods for fluids was addressed by John et al. [SIAM Review, 59(2017), 492-544]. In this work, we devise a new HDG method to approximate the solution of the Stokes tangential boundary control problem; the HDG method is also of independent interest for solving the Stokes equations. This scheme yields a $\mathbf{H}(\mathrm{div})$ conforming, globally divergence free, and pressure-robust solution. To the best of our knowledge, this is the first time such a numerical scheme has been obtained for an optimal boundary control problem for the Stokes equations. We also provide numerical experiments to show the performance of the new HDG method and the advantage over the non pressure-robust scheme.

In this paper we analyze the Schwarz alternating method for unconstrained elliptic optimal control problems. We discuss the convergence properties of the method in the continuous case first and then apply the arguments to the finite difference discretization case. In both cases, we prove that the Schwarz alternating method is convergent if its counterpart for an elliptic equation is convergent. Meanwhile, the convergence rate of the method for the elliptic equation under the maximum norm also gives a uniform upper bound (with respect to the regularization parameter $\alpha$) of the convergence rate of the method for the optimal control problem under the maximum norm of proper error merit functions in the continuous case or vectors in the discrete case. Our numerical results corroborate our theoretical results and show that with $\alpha$ decreasing to zero, the method will converge faster. We also give some exposition of this phenomenon.

Yong Li,1,* Sheng-Chun Fang,2,* Lan Zhou,1 Xue-Mei Mo,3 Hao-Dong Guo,3 Yan-Bo Deng,3 Hong-Hao Yu,1 Wei-Yi Gong3 1College of Biotechnology, Guilin Medical University, Guilin, Guangxi, 541100, People’s Republic of China; 2Department of Anesthesiology, Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, 430015, People’s Republic of China; 3Department of Pain Management, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, 541000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hong-Hao Yu, College of Biotechnology, Guilin Medical University, Guilin, Guangxi, 541100, People’s Republic of China, Email geneyhh@126.com Wei-Yi Gong, Department of Pain Management, Affiliated Hospital of Guilin Medical University, Guilin, 541000, Guangxi, People’s Republic of China, Email 942261597@qq.comBackground: Neuropathic pain (NP) after spinal cord injury (SCI-evoked NP) is clinically challenging; the underlying mechanisms are not fully understood, leading to a lack of promising treatment options. NP occurs in only a subset of patients with SCI. The injured spinal cord exhibits a series of histopathological changes, and the complement system has been shown to play an important role in these processes. In addition, NMDA receptor subunit 2B (NR2B) is involved in the development and maintenance of NP. This preliminary study was performed to investigate the correlations of the complement receptor 3/complement component 3 (CR3/C3) pathway and NR2B with SCI-evoked NP.Methods: A trauma-induced SCI animal model was established and SCI-evoked NP was evaluated by behavioural analysis. Transcriptome analysis was performed to identify genes in the CR3/C3 pathway related to synaptic modification, while the expression and distribution of NR2B in the injured spinal cord, and the relation to NP, were exam

Purpose: Free wall rupture (FWR) is a lethal complication after acute myocardial infarction; however, the un-derlying mechanisms of FWR are unclear. This study analyzes the relationship between neutrophil counts and FWR following ST-elevation myocardial infarction (STEMI). Methods: The case group was STEMI patients with FWR and the control group was STEMI patients without FWR (case-control ratio was 1:4). The demographic data, clinical manifestation and laboratory test results were retrospectively collected and analyzed. Results: Of a total of 6,712 consecutive STEMI patients, 78 patients (1.2%) had FWR. Compared with STEMI patients, patients with FWR were older and more likely to be female with an anterior infarct. White blood cell (WBC) counts were significantly higher in the FWR group. Moreover, we found that the elevated neutrophil counts mainly accounted for the elevated WBC counts. There was also a correlation between the age and neu-trophil counts (P=0.0109); as patient age increased, neutrophil counts decreased (P=0.0387). We also found no correlation between neutrophil counts and the time between myocardial infarction attack and FWR; however, when dividing these patients into FWR ≤48 h after admission to hospital for STEMI and FWR >48 h, there was a significant difference in neutrophil counts (P=0.0196). Furthermore, the results of logistic regression analy-sis showed that increased neutrophil was an independent risk factor for FWR (odds ratio: 2.404, confidence interval: 1.055-5.477). Conclusion: Elevated neutrophil counts were found to be the main cause of differences in WBC counts be-tween FWR and STEMI. Elevated neutrophil was an independent risk factor for FWR. This study provided clues for further research and development of therapeutics for the prevention of FWR.

Double helical conformation of polymer chains is widely observed in biomacromolecules and plays an essential role in exerting their biological functions, such as molecular recognition and information storage. It has remained challenging, however, to prepare synthetic helical polymers, and those that exist have mainly been limited to single-stranded polymers or short oligomeric double helices. Here, we report the synthesis of covalent helical polymers, with a high molecular weight, from the achiral monomer hexahydroxytriphenylene through to spiroborate formation. Polymerization and crystallization occurred simultaneously under solvothermal conditions to form single crystals of the resulting helical covalent polymers. Characterization by single-crystal X-ray diffraction showed that each crystal consisted of pairs of mechanically entwined polymers. No strong non-covalent interactions were observed between the two helical polymers that formed a pair; instead, each strand interacted with neighbouring pairs through hydrogen bonding. Each individual crystal was made up of helical polymers of the same handedness, but the crystallization process produced a racemic conglomerate, with equal amounts of right-handed and left-handed crystals.

Objective: Major bleeding is a common complication following treatment for an acute coronary syndrome (ACS) and is associated with increased mortality. We aimed to explore the temporal trend of bleeding events in relation to changes of therapeutic strategies among patients hospitalized for ACS in China. Methods: The CCC-ACS project (Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome) is a collaborative initiative of the American Heart Association and the Chinese Society of Cardiology. We analyzed 113,567 ACS patients from 241 hospitals in China from 2015 to 2019. Major bleeding was defined as intracranial bleeding, retroperitoneal bleeding, a decline in hemoglobin levels ≥3 g/dL, transfusion with overt bleeding, bleeding requiring surgical intervention, and fatal bleeding. Kruskal-Wallis test was used to examine the trend of major bleeding over time. Results: The rate of in-hospital major bleeding decreased from 6.3% in 2015 to 4.7% in 2019 (unadjusted OR = 0.74, 95% CI: 0.68-0.80, and P < 0.001). The relative changes were consistent across almost all subgroups including patients with NSTE-ACS and STEMI, although the trend was more pronounced in NSTE-ACS patients. The decrease in bleeding was accompanied by a decrease in use of GP IIb/IIIa inhibitors and parenteral anticoagulation therapy during hospitalization. The annual reduced risk of bleeding (OR = 0.91, 95% CI: 0.89-0.93) was attenuated after stepwise adjusting for baseline characteristics and antithrombotic treatments (OR = 0.95, 95% CI: 0.93-0.97), but did not change after adjusting for invasive treatment (OR = 0.95, 95% CI: 0.93-0.97). Conclusions: There was a temporal reduction in in-hospital bleeding among Chinese ACS patients during the last 5 years, which was associated with more evidence-based use of antithrombotic therapies. Clinical Trial Registration: https://www.clinicaltrials.gov, identifier: NCT02306616.

Recent advances in backscatter open a promising direction for ultra-low power communication. However, the state-of-art ZigBee backscatter system, Interscatter, has several drawbacks to deploy. Its backscatter tag and exciting source, Bluetooth, can hardly decode packets from other ZigBee nodes, which left Interscatter one-way communication. Besides, it adopts instantaneous phase change to modulate information, producing obvious sidelobes and interfering devices working on neighboring channels severely. To address the problems mentioned above, we introduce Homoscatter, a novel ZigBee backscatter system that adopts specific ZigBee devices to generate a single tone and leverages continuous phase change to modulate information, which eliminates spectral leakage. It also does codeword translation on the packet header of exciting packets, improving the utilization of ambient signal. The prototype of Homoscatter consists of a microchip radio, a backscatter tag, and a commodity receiver. The evaluations show that the occupied bandwidth of Homoscatter achieves 3x smaller than Interscatter. When the channel capacity is 17.5 kbps, the continuous phase change modulation achieves 13 kbps with the codeword translation on the excitation header. Based on the widely spread IoT devices, Homoscatter is a practical way to build an efficient connection between IoT devices., Comment: This article has very many grammatical errors, plus its logic needs to be reorganized to avoid creating a reading barrier for the reader. We withdraw this article and intend to reorganize the work

The seven basic facial expression classifications are a basic way to express complex human emotions and are an important part of artificial intelligence research. Based on the traditional Bayesian neural network framework, the ResNet18_BNN network constructed in this paper has been improved in the following three aspects: (1) A new objective function is proposed, which is composed of the KL loss of uncertain parameters and the intersection of specific parameters. Entropy loss composition. (2) Aiming at a special objective function, a training scheme for alternately updating these two parameters is proposed. (3) Only model the parameters of the last convolution group. Through testing on the FER2013 test set, we achieved 71.5% and 73.1% accuracy in PublicTestSet and PrivateTestSet, respectively. Compared with traditional Bayesian neural networks, our method brings the highest classification accuracy gain.

Machine learning is completely changing the trends in the fashion industry. From big to small every brand is using machine learning techniques in order to improve their revenue, increase customers and stay ahead of the trend. People are into fashion and they want to know what looks best and how they can improve their style and elevate their personality. Using Deep learning technology and infusing it with Computer Vision techniques one can do so by utilizing Brain-inspired Deep Networks, and engaging into Neuroaesthetics, working with GANs and Training them, playing around with Unstructured Data,and infusing the transformer architecture are just some highlights which can be touched with the Fashion domain. Its all about designing a system that can tell us information regarding the fashion aspect that can come in handy with the ever growing demand. Personalization is a big factor that impacts the spending choices of customers.The survey also shows remarkable approaches that encroach the subject of achieving that by divulging deep into how visual data can be interpreted and leveraged into different models and approaches. Aesthetics play a vital role in clothing recommendation as users' decision depends largely on whether the clothing is in line with their aesthetics, however the conventional image features cannot portray this directly. For that the survey also highlights remarkable models like tensor factorization model, conditional random field model among others to cater the need to acknowledge aesthetics as an important factor in Apparel recommendation.These AI inspired deep models can pinpoint exactly which certain style resonates best with their customers and they can have an understanding of how the new designs will set in with the community. With AI and machine learning your businesses can stay ahead of the fashion trends.

Hangqi Shen,1– 6,* Hui Zhang,7,8,* Wei Gong,1– 6 Tianwei Qian,1– 6 Tianyu Cheng,1– 6 Li Jin,7,8 Xiaofeng Wang,7– 10 Dawei Luo,1– 6 Xun Xu1– 6 1Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, People’s Republic of China; 3Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai, People’s Republic of China; 4Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai, People’s Republic of China; 5National Clinical Research Center for Eye Diseases, Shanghai, People’s Republic of China; 6Key Laboratory of Arrhythmias of the Ministry of Education of China, Tongji University School of Medicine, Shanghai, People’s Republic of China; 7Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, People’s Republic of China; 8Human Phenome Institute, Fudan University, Shanghai, People’s Republic of China; 9Shanghai Key Laboratory of Clinical Geriatric Medicine and Huadong Hospital Clinical Research Center for Geriatric Medicine, Shanghai, People’s Republic of China; 10National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Dawei Luo; Xun XuDepartment of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of ChinaEmail dr-davie@yeah.net; drxuxun@sjtu.edu.cnPurpose: This study aimed to explore the current prevalence, causes, and factors associated with visual impairment in a Chinese elderly population.Methods: A random sample of 2164 candidat

FRMD6, a member of the group of FERM-domain proteins, is involved both in communication between cells, interactions with extracellular matrix, cellular apoptotic and regenerative mechanisms. FRMD6 was first discovered in the rodent sciatic nerve, and in the present immunohistochemical study we investigated the distribution of FRMD6 in the dorsal root ganglia (DRGs), sciatic nerve and spinal cord following sciatic nerve injury. FRMD6-immunoreactivity was found in the cytoplasm, nucleus or both, and in a majority of DRG neurons. FRMD6-immunoreactivity co-existed with several well-known neuronal markers, including calcitonin gene-related peptide, isolectin B4 and neurofilament 200 in mouse DRGs. After peripheral nerve injury, the FRMD6 mRNA levels and the overall percentage of FRMD6-positive neuron profiles (NPs) were decreased in ipsilateral lumbar DRGs, the latter mainly affecting small size neurons with cytoplasmic localization. Conversely, the proportion of NPs with nuclear FRMD6-immunoreactivity was significantly increased. In the sciatic nerve, FRMD6-immunoreactivity was observed in non-neuronal cells and in axons, and accumulated proximally to a ligation of the nerve. In the spinal cord FRMD6-immunoreactivity was detected in neurons in both dorsal and ventral horns, and was upregulated in ipsilateral dorsal horn after peripheral nerve axotomy. Our results demonstrate that FRMD6 is strictly regulated by peripheral nerve injury at the spinal level., QC 20200324

Zi-You Wu,1,2 Wei Shen,3 Juan-Qing Yue,4 Wen-Yan Yao,1,2 Shi-Lei Liu,1,2 Yun-Peng Jin,1,2 Ping Dong,1,2 Fei Ma,1,2 Xiang-Song Wu,1,2,* Wei Gong1,2,* 1Department of General Surgery, Xinhua Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Shanghai Key Laboratory of Biliary Tract Disease Research, Shanghai, People’s Republic of China; 3Shanghai Colorectal Cancer Research Center, Shanghai, People’s Republic of China; 4Department of Pathology, Xinhua Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiang-Song Wu; Wei GongDepartment of General Surgery, Xinhua Hospital, Affiliated to Shanghai Jiao Tong University School of Medicine, No. 1665 Kongjiang Road, Shanghai 200092, People’s Republic of ChinaTel +86 13651683182Email wuxiangsong@xinhuamed.com.cn gongwei@xinhuamed.com.cnPurpose: The aim of this study was to determine the Immunoscore as an independent prognostic factor for cholangiocarcinoma and establish a useful prognostic model for postoperative patients.Methods: This retrospective study was performed to assess the correlation between the clinicopathological features, tumor immune microenvironment, and prognosis of 76 patients with cholangiocarcinoma. Multivariate analysis was used to identify independent factors significantly associated with local recurrence-free survival (LRFS) and overall survival (OS). Finally, we constructed a nomogram combining the Immunoscore with clinicopathologic features to predict postoperative recurrence and OS.Results: The present study showed that immune cell infiltration was negatively correlated with tumor size, peripheral vascular invasion, lymph node metastasis, and tumor staging. Kaplan–Meier curves indicated that a decreased Immunoscore was associated with poor prognosis. Multivariate

Ping Wu,1 Haolin Hu,2 Jinwen Li,1 Wei Gong1 1Department of Oncology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, 441021, People’s Republic of China; 2Department of Surgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, 441021, People’s Republic of ChinaCorrespondence: Haolin HuDepartment of Surgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Jingzhou St 39, Xiangyang 441021, People’s Republic of ChinaTel +86 138 7168 9148Email hh1910sc@gmail.comAim: Cullin 4B (CUL4B) is a member of the cullin ubiquitin-ligase family, which participates in proteolysis. Aberrant CUL4B expression has been shown in many malignancies. This study aimed to elucidate oncogenic role of CUL4B in gastric cancer (GC).Methods: CUL4B expression in GC tissues was examined by RT-PCR and immunohistochemistry. The proliferation, invasion and tumorigenicity of GC cells with CUL4B overexpression or knockdown were evaluated.Results: CUL4B expression significantly increased in GC tissues, and was correlated to UICC stage and differentiation of GC, as well as poor overall survival and disease-free survival. Both univariate and multivariate analysis identified CUL4B as an independent predictor for GC patient prognosis. In addition, CUL4B promoted GC cell proliferation and invasion in vitro and tumor formation in vivo.Conclusion: CUL4B is overexpressed to promote GC development and progression. CUL4B is a promising prognostic marker and therapeutic target for GC.Keywords: CUL4B, gastric cancer, biomarker, prognosis

Chuang Lyu,1 Gong-Wei Lyu,2 Jan Mulder,3,4 Aurora Martinez,5 Tie-Jun Sten Shi5 1State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute of Chinese Academy of Agricultural Sciences, Harbin 150069, People’s Republic of China; 2Department of Neurology, 1st Hospital of Harbin Medical University, Harbin 150001, People’s Republic of China; 3Department of Neuroscience, Karolinska Institutet, Stockholm SE-171 77, Sweden; 4Science for Life Laboratory, Karolinska Institutet, Stockholm SE-171 65, Sweden; 5Department of Biomedicine, University of Bergen, Bergen 5009, NorwayCorrespondence: Chuang Lyu Tel +86 13304503501Email htylv123@126.comTie-Jun Sten Shi Tel +47 45392855Email tiejun.shi@uib.noBackground: G protein-gated inwardly rectifying potassium (GIRK) channels are involved in the regulation of neuronal excitability. Four GIRK subunits (GIRK1-4) are expressed in rat dorsal root ganglia (DRGs). Recently, we have characterized the expression of GIRK1 and − 2, and both are downregulated in rat DRGs and spinal cord after a complete sciatic nerve transection (axotomy). Here, we aimed to study the neurochemical characteristics of GIRK3, and its regulation in rat DRGs and spinal cord induced by nerve injury.Methods: A sciatic nerve axotomy was performed to study the influences of injury on GIRK3 expression in DRGs and spinal cord. A dorsal root rhizotomy and a sciatic nerve crush were employed to study the axonal transport of GIRK3 protein, respectively. Immunohistochemistry analysis was employed for investigating the neurochemical characteristics of GIRK3.Results: In control DRGs, ∼ 18% of neuron profiles (NPs) were GIRK3-positive (+), and ∼ 41%, ∼ 48% and ∼ 45% of GIRK3+ NPs were CGRP+, IB4+ and NF200+, respectively. GIRK3-like immunoreactivity was observed in glabrous skin of hind paws and axons originating from DRG neurons. Fourteen days after axotomy, more than one-third of DRG NPs

Zhang F, Li M, Wu X, et al. Drug Des Devel Ther. 2015;9:3969–3987. On page 3976, Figure 3B should be presented as follows: Following a review of the data post-publication, the authors found two identical cell cycle images in two different groups were placed for 200μM and 400μM. We have replaced the image for 400μM in this corrigendum. The authors confirmed that this error does not affect any statistical results or any relevant conclusions about Figure 3B. The authors apologize for this oversight.   Read the original article here &nbsp

Selfish mining, which is an attack on the integrity of the Bitcoin network, was first proposed by Cornell researchers Emin Gun Sirer and Ittay Eyal in 2013. Selfish mining attack also exists in most Nakamoto consensus protocols. Generally speaking, selfish mining strategy can comprise a Nakamoto consensus system with less than 25% mining power of the whole system. We have discussed how the Bicomp can resist selfish mining in our former paper "Bicomp: A Bilayer Scalable Nakamoto Consensus Protocol". In this technical report, we give a detailed derivation on the conditions a selfish attacker should meet to earn more revenues through selfish mining. And we also get a conclusion that through adjusting macroblock difficulties together with tenure lengths, the Bicomp protocol has high resistant towards selfish mining.

Radio Frequency Identification (RFID) is an emerging technology for electronic labeling of objects for the purpose of automatically identifying, categorizing, locating, and tracking the objects. But in their current form RFID systems are susceptible to cloning attacks that seriously threaten RFID applications but are hard to prevent. Existing protocols aimed at detecting whether there are cloning attacks in single-reader RFID systems. In this paper, we investigate the cloning attacks identification in the multireader scenario and first propose a time-efficient protocol, called the time-efficient Cloning Attacks Identification Protocol (CAIP) to identify all cloned tags in multireaders RFID systems. We evaluate the performance of CAIP through extensive simulations. The results show that CAIP can identify all the cloned tags in large-scale RFID systems fairly fast with required accuracy.

Nitrogen-doped porous activated carbon monoliths (NDP-ACMs) have long been the most desirable materials for supercapacitors. Unique to the conventional template based Lewis acid/base activation methods, herein, we report on a simple yet practicable novel approach to production of the three-dimensional NDP-ACMs (3D-NDP-ACMs). Polyacrylonitrile (PAN) contained carbon nanotubes (CNTs), being pre-dispersed into a tubular level of dispersions, were used as the starting material and the 3D-NDP-ACMs were obtained via a template-free process. First, a continuous mesoporous PAN/CNT based 3D monolith was established by using a template-free temperature-induced phase separation (TTPS). Second, a nitrogen-doped 3D-ACM with a surface area of 613.8 m²/g and a pore volume 0.366 cm³/g was obtained. A typical supercapacitor with our 3D-NDP-ACMs as the functioning electrodes gave a specific capacitance stabilized at 216 F/g even after 3000 cycles, demonstrating the advantageous performance of the PAN/CNT based 3D-NDP-ACMs., National Science Foundation (U.S.) (DMR-1507806)

Chuang Lyu,1,2 Gong-Wei Lyu,3 Aurora Martinez,4 Tie-Jun Sten Shi4 1State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute of Chinese Academy of Agricultural Sciences, Harbin, People’s Republic of China; 2Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden; 3Department of Neurology, 1st Hospital of Harbin Medical University, Harbin, People’s Republic of China; 4Department of Biomedicine, University of Bergen, Bergen, Norway Background: The proapoptotic molecule BAX, plays an important role in mitochondrial apoptotic pathway. Dorsal root ganglion (DRG) neurons depend on neurotrophic factors for survival at early developmental stages. Withdrawal of neurotrophic factors will induce apoptosis in DRG neurons, but this type of cell death can be delayed or prevented in neonatal Bax knockout (KO) mice. In adult animals, evidence also shows that DRG neurons are less dependent upon neurotrophic factors for survival. However, little is known about the effect of Bax deletion on the survival of normal and denervated DRG neurons in adult mice. Methods: A unilateral sciatic nerve transection was performed in adult Bax KO mice and wild-type (WT) littermates. Stereological method was employed to quantify the number of lumbar-5 DRG neurons 1 month post-surgery. Nerve injury-induced autotomy behavior was also examined on days 1, 3, and 7 post-surgery. Results: There were significantly more neurons in contralateral DRGs of KO mice as compared with WT mice. The number of neurons was reduced in ipsilateral DRGs in both KO and WT mice. No changes in size distributions of DRG neuron profiles were detected before or after nerve injury. Injury-induced autotomy behavior developed much earlier and was more serious in KO mice. Conclusion: Although postnatal death or loss of DRG neurons is partially prevented by Bax deletion, this effect cannot interfere with long-term nerve injury-induced neuronal loss. The exaggerated self-amp

Fayong Ke,1,2,* Zheng Wang,1,2,* Xiaoling Song,1,2 Qiang Ma,1,2 Yunping Hu,2 Lin Jiang,2 Yijian Zhang,2 Yingbin Liu,1,2 Yong Zhang,1 Wei Gong1,2 1Department of General Surgery, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 2Institute of Biliary Disease Research, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China *These authors contributed equally to this work Background: Cholangiocarcinoma (CCA) is the most common biliary tract malignancy in the world with high resistance to current chemotherapies and extremely poor prognosis. The main objective of this study was to investigate the inhibitory effects of cryptotanshinone (CTS), a natural compound isolated from Salvia miltiorrhiza Bunge, on CCA both in vitro and in vivo and to explore the underlying mechanisms of CTS-induced apoptosis and cell cycle arrest. Methods: The anti-tumor activity of CTS on HCCC-9810 and RBE cells was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) assay and colony forming assays. Cell cycle changes were detected by flow cytometric analysis. Apoptosis was detected by annexin V/propidium iodide double staining and Hoechst 33342 staining assays. The efficacy of CTS in vivo was evaluated using a HCCC-9810 xenograft model in athymic nude mice. The expression of key proteins involved in cell apoptosis and signaling pathway in vitro was analyzed by Western blot analysis. Results: CTS induced potent growth inhibition, S-phase arrest, apoptosis, and colony-forming inhibition in HCCC-9810 and RBE cells in a dose-dependent manner. Intraperitoneal injection of CTS (0, 10, or 25 mg/kg) for 4 weeks significantly inhibited the growth of HCCC-9810 xenografts in athymic nude mice. CTS treatment induced S-phase arrest with a decrease of cyclin A1 and an increase of cyclin D1 protein level. Bcl-2 expression was downregulated remarkably, while Bax expressi

Cheng Gong,1 Zongyuan Yang,1 Lingyun Zhang,2 Yuehua Wang,2 Wei Gong,2 Yi Liu3 1Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 2Department of Oncology, XiangYang Central Hospital, Hubei University of Arts and Science, XiangYang, 3Department of Medicinal Chemistry, School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China Abstract: Quercetin is proven to have anticancer effects for many cancers. However, the role of tumor suppressor p53 on quercetin’s radiosensitization and regulation of endoplasmic reticulum (ER) stress response in this process remains obscure. Here, quercetin exposure resulted in ER stress, prolonged DNA repair, and the expression of p53 protein; phosphorylation on serine 15 and 20 increased in combination with X-irradiation. Quercetin pretreatment could potentiate radiation-induced cell death. The combination of irradiation and quercetin treatment aggravated DNA damages and caused typical apoptotic cell death; as well the expression of Bax and p21 elevated and the expression of Bcl-2 decreased. Knocking down of p53 could reverse all the above effects under quercetin in combination with radiation. In addition, quercetin-induced radiosensitization was through stimulation of ATM phosphorylation. In human ovarian cancer xenograft model, combined treatment of quercetin and radiation significantly restrained the growth of tumors, accompanied with the activation of p53, CCAAT/enhancer-binding protein homologous protein, and γ-H2AX. Overall, these results indicated that quercetin acted as a promising radiosensitizer through p53-dependent ER stress signals. Keywords: quercetin, p53, endoplasmic reticulum stress, DNA double-strand breaks, eIF-2α (eukaryotic initiation factor 2α), ATM kinase

Radio Frequency Identification (RFID) technology plays an important role in supply chain logistics and inventory control. In these applications, a series of scanning operations at different locations are often needed to cover the entire inventory (tags). In such continuous scanning scenario, adjacent scans inevitably read overlapping tags multiple times. Most existing methods suffer from low scanning efficiency when the overlap is small, since they do not distinguish the size of overlap which is an important factor of scanning performance. In this paper, we analytically unveil the fundamental relationship between the performance of continuous scanning and the size of overlap, deriving a critical threshold for the selection of scanning strategy. Further, we design an accurate estimator to approximate the overlap. Combining the estimate and a compact data structure, an adaptive scanning scheme is introduced to achieve low communication time. Through detailed analysis and extensive simulations, we demonstrate that the proposed scheme significantly outperforms previous approach in total scanning time. © 1993-2012 IEEE.

Sensor networks are widely used in various domains like the intelligent transportation systems. Users issue queries to sensors and collect sensing data. Due to the low quality sensing devices or random link failures, sensor data are often noisy. In order to increase the reliability of the query results, continuous queries are often employed. In this work we focus on continuous holistic queries like Median. Existing approaches are mainly designed for non-holistic queries like Average. However, it is not trivial to answer holistic ones due to their non-decomposable property. We first propose two schemes based on the data correlation between different rounds, with one for getting the exact answers and the other one for deriving the approximate results. We then combine the two proposed schemes into a hybrid approach, which is adaptive to the data changing speed. We evaluate this design through extensive simulations. The results show that our approach significantly reduces the traffic cost compared with previous works while maintaining the same accuracy. © 1990-2012 IEEE.

Backscatter communication networks receive much attention recently due to the small size and low power of backscatter nodes. As backscatter communication is often influenced by the dynamic wireless channel quality, rate adaptation becomes necessary. Most existing approaches share a common drawback: they do not distinguish channel qualities from different nodes or sub-channels. Consequently, the transmission rate may be improperly selected, resulting in low network throughput. Through extensive experimental studies, we observe that channel diversity plays a significant role in rate selection. Therefore, there are opportunities of exploiting channel diversity for better rate adaptation, improving network throughput. In this paper, we propose a Channel-Aware Rate Adaptation framework (CARA) for backscatter communication networks. By employing a lightweight channel probing scheme, we are able to obtain fine-grained channel information that enables accurate channel estimation. We further design a novel channel selection algorithm, benefiting as many backscatter nodes as possible. On each selected channel, CARA chooses data rate with respect to the node that has the best channel condition. We implement CARA on commercial readers and the experiment results show that CARA achieves up to 4× goodput gain compared with state-of-the-art rate adaptation scheme. © 2016 IEEE.

Many algorithms have been introduced to deterministically authenticate Radio Frequency Identification (RFID) tags, while little work has been done to address scalability issue in batch authentications. Deterministic approaches verify tags one by one, and the communication overhead and time cost grow linearly with increasing size of tags. We design a fast and scalable counterfeits estimation scheme, INformative Counting (INC), which achieves sublinear authentication time and communication cost in batch verifications. The key novelty of INC builds on an FM-Sketch variant authentication synopsis that can capture key counting information using only sublinear space. With the help of this well-designed data structure, INC is able to provide authentication results with accurate estimates of the number of counterfeiting tags and genuine tags, while previous batch authentication methods merely provide 0/1 results indicating the existence of counterfeits. We conduct detailed theoretical analysis and extensive experiments to examine this design and the results show that INC significantly outperforms previous work in terms of effectiveness and efficiency.

Counting the number of tags is a fundamental issue and has a wide range of applications in RFID systems. Most existing protocols, however, only apply to the scenario where a single reader counts the number of tags covered by its radio, or at most the union of tags covered by multiple readers. They are unable to achieve more complex counting objectives, i.e., counting the number of tags in a composite set expression such as(S1∪ S2)-(S3cap;S4)This type of counting has realistic significance as it provides more diversity than existing counting scenario, and can be applied in various applications. We formally introduce the RFID composite counting problem, which aims at counting the tags in an arbitrary set expression and obtain its strong lower bounds on the communication cost. We then propose a generic Composite Counting Framework (CCF) that provides estimates for any set expression with desired accuracy. The communication cost of CCF is proved to be within a small factor from the optimal. We build a prototype system for CCF using USRP software defined radio and Intel WISP computational tags. Also, extensive simulations are conducted to evaluate the performance of CCF. The experimental results show that CCF is generic, accurate and time-efficient. © 2015 IEEE.

In low-duty-cycle networks, sensors stay dormant most of time to save their energy and wake up based on their needs. Such a technique, while prolonging the network lifetime, sets excessive challenges for efficien floodin within the network. Tailored for obtaining short delay in low-duty-cycle networks, recently proposed floodin protocols have achieved some initial success. Many fundamental problems of floodin in low-duty-cycle networks, however, are still not well understood. In this paper, we thoroughly investigate how the floodin behaviors are fundamentally affected from theory to practice in a low-duty-cycle sensor network. We study how practical factors like duty cycle length, topology and link loss affect the floodin delay. We mathematically quantify the performance deterioration caused by those factors and present initial learning in achieving efficien floodin against them. Our theoretical analysis brings us not only an in-depth understanding of several fundamental trade-offs in low-duty-cycle sensor networks, but also insights on the design of floodin protocols that can approach excellent performance.

Natural rubber latex (NRL) from Hevea brasiliensis was used as a matrix to synthesize gold nanoparticles (AuNPs), leading to an organic-inorganic hybrid latex of NRL-supported AuNPs (AuNPs@NRL). The in situ and environmentally friendly preparation of AuNPs in an NRL matrix was developed by thermal treatment without using any other reducing agents or stabilizers because natural rubber particles and non-rubber components present in serum can serve as supporters for the synthesized AuNPs. As a result, the nanosized and well-dispersed AuNPs not only are decorated on the surface of natural rubber particles, but also can be found in the serum of NRL. The size of the AuNPs presented in NRL matrix can be controlled by adjusting the concentration of NRL. Furthermore, the flexible surface-enhanced Raman scattering (SERS) substrates made from the AuNPs@NRL through vacuum filtration presented good enhancement of the Raman probe molecule of 4-mercaptopyridine and outstanding SERS reproducibility. The capability of synthesizing the bio-supported nanohybrid latex provides a novel green and simple approach for the fabrication of flexible and effective SERS substrates.

Fei Zhang,* Maolan Li,* Xiangsong Wu,* Yunping Hu, Yang Cao, Xu’an Wang, Shanshan Xiang, Huaifeng Li, Lin Jiang, Zhujun Tan, Wei Lu, Hao Weng, Yijun Shu, Wei Gong, Xuefeng Wang, Yong Zhang, Weibin Shi, Ping Dong,# Jun Gu,# Yingbin Liu#Department of General Surgery and Laboratory of General Surgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Institute of Biliary Tract Disease, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China *These authors contributed equally to this work #These authors jointly directed this work Abstract: Gallbladder cancer (GBC), the most frequent malignancy of the biliary tract, is associated with high mortality and extremely poor prognosis. 20(S)-ginsenoside Rg3 (20(S)-Rg3) is a steroidal saponin with high pharmacological activity. However, the anticancer effect of 20(S)-Rg3 in human GBC has not yet been determined. In this study, we primarily found that 20(S)-Rg3 exposure suppressed the survival of both NOZ and GBC-SD cell lines in a concentration-dependent manner. Moreover, induction of cellular senescence and G0/G1 arrest by 20(S)-Rg3 were accompanied by a large accumulation of p53 and p21 as a result of murine double minute 2 (MDM2) inhibition. 20(S)-Rg3 also caused a remarkable increase in apoptosis via the activation of the mitochondrial-mediated intrinsic caspase pathway. Furthermore, intraperitoneal injection of 20(S)-Rg3 (20 or 40 mg/kg) for 3 weeks markedly inhibited the growth of xenografts in nude mice. Our results demonstrated that 20(S)-Rg3 potently inhibited growth and survival of GBC cells both in vitro and in vivo. 20(S)-Rg3 attenuated GBC growth probably via activation of the p53 pathway, and subsequent induction of cellular senescence and mitochondrial-dependent apoptosis. Therefore, 20(S)-Rg3 may be a potential chemotherapeutic agent for GBC therapy.Keywords: gallbladder cancer, 20(S)-ginsenoside Rg3, sene

One important issue of RFID applications is to estimate the cardinality of large-scale RFID tags in the interested region. From a practical perspective, we require: (i) the estimate can be arbitrarily accurate, and (ii) its time cost should be scalable with the tags size, regardless of the tags distribution. Existing solutions, however, either assume the use of hash functions with ideal random properties, or impose unacceptable computation/storage overhead for tags. More importantly, those approaches only give asymptotic results and fail to provide rigorous bounds for the rate of convergence. In this paper, we propose a new scheme, Arbitrarily Accurate Approximation (A3), to reliably estimate the number of tags with any desired accuracy. In particular, for a given requirement of (ε,δ), we show that A3 achieves O((log log n+ε-2) log δ-1) time efficiency. Results show that A3 significantly outperforms previous designs under various distributions of tags. © 2014 IEEE.

Counting the number of RFID tags is a fundamental issue and has a wide range of applications in RFID systems. Most existing protocols, however, only apply to the scenario where a single reader counts the number of tags covered by its radio, or at most the union of tags covered by multiple readers. They are unable to achieve more complex counting objectives, i.e., counting the number of tags in a composite set expression such as (S-1 big cup S-2)-(S-3 big cap S-4). This type of counting has realistic significance since it provides more diversity than existing counting scenario, and can be applied in various applications. In this paper, we formally introduce the RFID composite counting problem, which aims at counting the tags in arbitrary set expression. We obtain strong lower bounds on the communication cost of composite counting. We then propose a generic Composite Counting Framework (CCF) that provides estimates for any set expression with desired accuracy. The communication cost of CCF is proved to be within a small factor from the optimal. We build a prototype system for CCF using USRP software defined radio and Intel WISP computational tags. Also, extensive simulations are conducted to evaluate the performance of CCF. The experimental results show that CCF is generic, accurate and time-efficient.