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© 2019 Elsevier B.V. Rewards allocation in one of the key issues for ensuring a high task acceptance rate in spatial crowdsourcing applications. Generally, workers who participate in a crowdsourcing project are required to disclose their locations, which may lead to serious privacy threats. Unfortunately, providing a rigid privacy guarantee is incompatible with ensuring a high task acceptance rate in most existing crowdsourcing solutions. Hence, this paper proposes a crowdsourcing framework based on optimized reward allocation strategies. The key idea is to tune the reward for performing each task to the workers’ preferences to attain a high acceptance rate. The first step in the framework is to interrogate the workers’ preferences using a cryptographic protocol that fully preserves the location privacy of the workers. Based on those preferences, two different approaches to reward assignments have been proposed to ensure the rewards are distributed optimally. A theoretical analysis of the privacy protection inherent in the framework demonstrates that the proposed framework guarantee the worker's location privacy from adversaries including the requester and crowdsourcing server. Further, experiments based on real-world datasets show that the proposed strategies outperform existing solutions in terms of task acceptance rates.

© 2018 Elsevier B.V. Research on molecularly thin two-dimensional (2D)nanosheets has experienced significant progress since the discovery of graphene. Due to the high tunability of the structure, composition, and functionality, a great number of recent studies have focused on 2D ultrathin metal oxides, which have shown promising perspectives in many fields, including electrochemical energy storage. In this review, we focus on recent advances in 2D genuine unilamellar metal oxide nanosheets delaminated from their layered parent precursors and overview nanostructured materials based on these nanosheets for electrochemical energy storage applications. In particular, new, molecular-scale integrated superlattice structures fabricated by facile solution-based strategies using 2D unilamellar metal oxide nanosheets as building blocks are highlighted as emerging electrode materials to provide ultimately enhanced performance. Finally, current opportunities and future challenges for research into 2D unilamellar metal oxide nanosheets are proposed and outlined.

© 2019 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Sodium-based batteries have attracted considerable attention and are recognized as ideal candidates for large-scale and low-cost energy storage. Sodium (Na) metal anodes are considered as one of the most promising anodes for next-generation, high-energy, Na-based batteries owing to their high theoretical specific capacity (1166 mA h g−1) and low standard electrode potential. Herein, an overview of the recent developments in Na metal anodes for high-energy batteries is provided. The high reactivity and large volume expansion of Na metal anodes during charge and discharge make the electrode/electrolyte interphase unstable, leading to the formation of Na dendrites, short cycle life, and safety issues. Design strategies to enable the efficient use of Na metal anodes are elucidated, including liquid electrolyte engineering, electrode/electrolyte interface optimization, sophisticated electrode construction, and solid electrolyte engineering. Finally, the remaining challenges and future research directions are identified. It is hoped that this progress report will shape a consistent view of this field and provide inspiration for future research to improve Na metal anodes and enable the development of high-energy sodium batteries.

© 2018 Elsevier Ltd Developing low-cost and efficient catalysts for oxygen evolution reactions (OER) with both excellent activity and robust stability remains a great challenge. Herein, we report a facile spontaneous redox reaction to grow cobalt-doped MnO2 ultrathin nanosheets in situ with abundant oxygen vacancies vertically aligned on cobalt/nitrogen co-functionalized carbon nanofibers (Co-MnO2|OV) as an efficient OER catalyst. It is confirmed that metallic cobalt plays a critical role in the formation of long and ultrathin MnO2 nanosheets during the redox reaction. Furthermore, the cobalt ions doped into MnO2 significantly enhance the catalytic activity of MnO2 nanosheets. Benefiting from the collaborative advantages of doping strategy, fast charge transfer kinetics and strong synergistic coupling effects, Co-MnO2|OV composites exhibit an excellent catalytic activity and a good durability for electrochemical water oxidation, reaching 10 mA cm−2 at an overpotential of 279 mV. According to the density functional theory (DFT) calculations, the enhanced catalytic activity mainly originates from a better conductivity and the decreased adsorption energy barrier of OH- on the O sites neighboring the doped Co and oxygen vacancies. Our findings suggest that the control over the structure and composition of the materials can achieve highly efficient oxygen evolution electrocatalysts.

© 2017 Elsevier B.V. Privacy preserving data release is a hot topic that attracts a lot of attentions in data mining, machine learning, and social network communities. Most studies on privacy preserving focus on static data releases; however, data are usually updated periodically. As a potential solution, differential privacy addresses continual data release by simplifying it into an event stream release problem. This approach overlooks the relationship between events, which is defined as coupled information in this paper. We argue that datasets cannot be simplified as an event stream due to the coupled information. In addition, the coupled information may reveal more private information than expected. This work proposes a privacy-preserving mechanism that explicitly identify the coupled information in continually released datasets. In stead of simplifying datasets to event streams, this mechanism considers the continual released datasets as coupled datasets based on the relationship between the same individual in different datasets, and the relationship between different individuals in the same dataset. We also propose the notion of coupled sensitivity for answering differentially private queries and develop an iterative based coupled continual release algorithm, called CCR, that answers these queries with a large set of differentially private results. Theoretical analysis proves the privacy of this method, and an extensive performance study shows that CCR outperforms traditional differential privacy mechanisms when answering a large set of queries.

© 2018 Elsevier B.V. With the development of Cyber Physical Systems, privacy issues become an important topics in the past few years. It is worthwhile to apply differential privacy, one of the most influential privacy definitions, in cyber physical system. However, as the essential idea of differential privacy is to release query results rather than entire datasets, a large volume of noise has to be introduced. To provide high quality services we need to decrease the correlation between large sets of queries, while to predict on newly entered queries. This paper transfers the data publishing problem in cyber physical systems to a machine learning problem, in which a prediction model will be shared with clients. The predict model is used to answer current submitted queries and predict results for newly entered queries from the public.

OBJECTIVE It is difficult for clinicians to diagnose schizophrenia solely based on interviews. We explored the diagnostic efficiency and predictive capability of serum biomarkers for schizophrenia. METHOD Levels of β nerve growth factor (β-NGF), brain-derived neurotrophic factor (BDNF), interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), interferon γ (IFN-γ), calcium binding protein S100β, myelin basic protein (MBP), and glial fibrillary acidic protein (GFAP) were measured in the sera of 278 schizophrenia patients, 240 depression and bipolar disorder patients, and 260 healthy controls. DSM-IV-TR criteria were used as the diagnostic criteria for schizophrenia and depressive and bipolar disorders. The diagnostic efficiency was high in patients with schizophrenia compared with the healthy controls. Receiver operating characteristic (ROC) curve analysis was used to ascertain the diagnostic efficiency of the 8 proteins. Data were collected between July 2010 and December 2012. RESULTS One-way analysis of variance significantly demonstrated lower serum BDNF, MBP, and GFAP levels (F = 16.504, P < .001; F = 207.209, P < .001; F = 33.668, P < .001, respectively) but higher serum IL-6 and S100β concentrations (F = 15.250, P < .001; F = 12.751, P < .001, respectively) among patients with schizophrenia. ROC analysis of the discriminant scores of the serum β-NGF, BDNF, IL-6, S100β, MBP, and GFAP levels resulted in significant discrimination between the schizophrenia and control groups (AUC = 0.922) and the depressive/bipolar disorder and control groups (AUC = 0.762). CONCLUSIONS Serum levels of 6 proteins (but not TNF-α and IFN-γ) contribute most to the diagnosis of schizophrenia. These proteins may prove to be useful adjuncts for the clinical assessment of this disease.

Sentinel lymph node biopsy is an extensively explored diagnostic mean for reducing surgical risks while improving staging in different human malignancies. Several different techniques have been introduced to clinical use during last two decades. Methods as ink lymphography and lymphoscintigraphy have already established their position in sentinel nodes mapping. Novel approaches as CT-, MRI-lymphography, contrast enhanced ultrasound and near-infrared fluorescence imaging possesses prominent potential advantages and demand further experience gaining. A review of the clinically utilized techniques is presented a special attention is drawn to their usefulness in the head and neck carcinomas work-up.

Background The remodeling patterns in different types of chronic rhinosinusitis (CRS) have rarely been compared, particularly the difference between eosinophilic and noneosinophilic CRS with nasal polyps (CRSwNP). Moreover, whether there is a link between remodeling and inflammation remains controversial. Objective To directly compare the remodeling features of different CRS and to explore their relationship with inflammation in Chinese patients. Methods Histologic characteristics of surgical samples were analyzed in 33 controls, 72 eosinophilic and 76 noneosinophilic CRSwNP, and 72 CRS without nasal polyps (CRSsNP) patients. Tissue samples from 38 controls, 26 eosinophilic and 26 noneosinophilic CRSwNP, and 32 CRSsNP patients were measured for mRNA and/or protein expression of profibrotic growth factors, metalloproteinases (MMPs), tissue inhibitor of metalloproteinases (TIMPs), hypoxia-inducible factor (HIF)-1α, interleukin (IL)-8, eosinophil cationic protein (ECP), and myeloperoxidase (MPO). Results The amount of collagen decreased, whereas the edema scores increased, from CRSsNP to noneosinophilic CRSwNP and to eosinophilic CRSwNP. Transforming growth factor (TGF)-β2 protein levels were enhanced in CRSsNP compared with CRSwNP. TIMP-4 protein levels decreased in eosinophilic CRSwNP compared with noneosinophilic CRSwNP and CRSsNP. The number of neutrophils decreased from CRSsNP to noneosinophilic CRSwNP and to eosinophilic CRSwNP. ECP levels were only up-regulated in eosinophilic CRSwNP. ECP levels and neutrophil number correlated positively with the severity of edema and fibrosis, respectively. Neutrophils were the major sources of TGF-β2 in CRSsNP and noneosinophilic CRSwNP. Conclusion Distinct remodeling patterns are revealed for different types of CRS, particularly for eosinophilic and noneosinophilic CRSwNP. Tissue remodeling associates with inflammation in CRS.

Giant Random Telegraph Noise (RTN) in the resistance fluctuation of a macroscopic film of perovskite-type manganese oxide La2/3Ca1/3MnO3 has been observed at various temperatures ranging from 4K to 170K, well below the Curie temperature (TC = 210K). The amplitudes of the two-level-fluctuations (TLF) vary from 0.01% to 0.2%. We use a statistical analysis of the life-times of the TLF to gain insight into the microscopic electronic and magnetic state of this manganite. At low temperature (below 30K) The TLF is well described by a thermally activated two-level model. An estimate of the energy difference between the two states is inferred. At higher temperature (between 60K and 170K) we observed critical effects of the temperature on the life-times of the TLF. We discuss this peculiar temperature dependence in terms of a sharp change in the free energy functional of the fluctuators. We attribute the origin of the RTN to be a dynamic mixed-phase percolative conduction process, where manganese clusters switch back and forth between two phases that differ in their conductivity and magnetization., Comment: 15 pages, PDF only, Phys. Rev. Lett. (in press)