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[enter Abstract Body]This study examines how longevity risk, in conjunction with other postretirement risks, impacts retirement consumption decisions and retirement wealth needs. We develop a theoretical model that directly examines the relationship between longevity risk and consumption/savings, and empirically test these theoretical implications by simulating retirement outcomes for representative households, including longevity, inflation, investment, health, and long‐term care risks. Our study shows that the top third of households by longevity need approximately 20% more retirement wealth than those households who live only an average life span. Investigations of various risk mitigation strategies suggest that combination strategies, particularly those that include delayed retirement, can significantly reduce the retirement wealth target. This research provides valuable new insights on household financial planning strategies for managing longevity risk. Full Text Available Here: https://doi.org/10.1002/cfp2.1007

IntroductionCirculating tumour DNA (ctDNA) has potential applications in cancer management. Most previous studies about ctDNA focused on advanced stage cancer patients. We have completed a clinical prospective study (NCT02645318) and showed the feasibility and clinical application of ctDNA detection in early stage non-small cell lung cancer (NSCLC) patients. The aim of this study is to investigate the elimination rate of ctDNA level after surgery. This is the first prospective study to evaluate the perioperative dynamic changes of ctDNA in surgical lung cancer patients.Methods and analysisThis is a prospective observational study to determine the elimination rate of circulating tumour DNA after surgery. Consecutive patients with suspected lung cancer who undergo curative-intent lung resection will be enrolled. 10 mL blood samples are taken by intravenous puncture. Plasma samples are obtained before surgery (time A) and at a series of scheduled time-points (2 min to 72 hours, time B to F) after tumour resection. DNA is prepared from 4 mL of purified plasma. A multiplex assay based on circulating single-molecule amplification and resequencing technology (cSMART) is used to simultaneously detect and quantitate hot spot EGFR, KRAS, BRAF, ERBB2, PIK3CA, TP53, ALK, RET and MET plasma DNA variants. Positive plasma mutations are validated in tumour tissue and normal lung tissue by targeted sequencing.Ethics and disseminationEthical approval has been obtained from the Peking University People’s Hospital Medical Ethics Committee (2016PHB156-01). Results will be disseminated through presentations at scientific meetings and publications in peer-reviewed journals.Trial registration numberNCT02965391; Pre-results.

Many studies were proposed to discuss acoustic correlates of stress in recent years. Considering some inconsistent experiment results, we supposed that stress should be categorized into long-term and short-term stress in this topic, and the trend of short-term stress induced by workload may be affected by long-term stress. This study contains three parts: first, we proposed an acoustic feature set chosen by feature selection, which can be considered as a measurement of the level of long-term stress; second, we showed that this set is immune to short-term stress in stress classification tests; finally, we observed some particular voice features mentioned in previous researches in our experiment and the results may imply that short-term stress trend is in connection with the level of long-term stress. In short, long-term and shot-term stress should be discussed separately in future researches for clear and explicit conclusions.

Personnel security information collection system is based on wireless ad hoc networks, electronic devices, wireless communications and GPS positioning technology. The system employs smart wristbands terminal to gather security information periodically via wireless communication base station. The collected information is transmitted to portable terminal with a self-designed embedded application. With mapping coordinates, application in the terminal can display all available safety information and within-reach smart bracelet. Thus the system is more convenient for managers and users. In addition, the system is speedy and smart which is suitable for a multitude of life scenes. The smart hand ring terminals and radio base station are connected through self ZigBee networking, while the information between wireless communication base station and portable applications are transmitted by Bluetooth terminal. The system employs Bluetooth and ZigBee module, where the two parts complement each other. Also, the system takes advantage of ZigBee protocol by flexible networking and relatively low power consumption and Bluetooth transmission by high bandwidth.

Depression is a common mental disorder and one of the main causes of disability worldwide. Lacking objective depressive disorder assessment methods is the key reason that many depressive patients can't be treated properly. Developments in affective sensing technology with a focus on acoustic features will potentially bring a change due to depressed patient's slow, hesitating, monotonous voice as remarkable characteristics. Our motivation is to find out a speech feature set to detect, evaluate and even predict depression. For these goals, we investigate a large sample of 300 subjects (100 depressed patients, 100 healthy controls and 100 high-risk people) through comparative analysis and follow-up study. For examining the correlation between depression and speech, we extract features as many as possible according to previous research to create a large voice feature set. Then we employ some feature selection methods to eliminate irrelevant, redundant and noisy features to form a compact subset. To measure effectiveness of this new subset, we test it on our dataset with 300 subjects using several common classifiers and 10-fold cross-validation. Since we are collecting data currently, we have no result to report yet.

Modeling the dependence between uncertainties in decision and risk analyses is an important part of the problem structuring process. We focus on situations where correlated uncertainties are discrete, and extend the concept of the copula-based approach for modeling correlated continuous uncertainties to the representation of correlated discrete uncertainties. This approach reduces the required number of probability assessments significantly compared to approaches requiring direct estimates of conditional probabilities. It also allows the use of multiple dependence measures, including product moment correlation, rank order correlation and tail dependence, and parametric families of copulas such as normal copulas, t-copulas, and Archimedean copulas. This approach can be extended to model the dependence between discrete and continuous uncertainties in the same event tree.

Intracellular pH plays an important role in the response to cancer invasion. We have designed and synthesized a series of new fluorescent probes (Superior LysoProbes) with the capacity to label acidic organelles and monitor lysosomal pH. Unlike commercially available fluorescent dyes, Superior LysoProbes are lysosome-specific and are highly stable. The use of Superior LysoProbes facilitates the direct visualization of the lysosomal response to lobaplatin elicited in human chloangiocarcinoma (CCA) RBE cells, using confocal laser scanning microscopy. Additionally, we have characterized the role of lysosomes in autophagy, the correlation between lysosome function and microtubule strength and the alteration of lysosomal morphology during apoptosis. Our findings indicate that Superior LysoProbes offer numerous advantages over previous reagents to examine the intracellular activities of lysosomes.

Many important decision and risk analysis problems are complicated by dependencies between input variables. In such cases, standard one-variable-at-a-time sensitivity analysis methods are typically eschewed in favor of fully probabilistic, or n-way, analysis techniques which simultaneously model all n input variables and their interdependencies. Unfortunately, much of the intuition provided by one-way sensitivity analysis and its associated graphical output displays such as Tornado diagrams may not be available in fully probabilistic methods. It is also difficult or impossible to isolate the marginal effects of variables in an n-way analysis. In this paper, we present a dependence-adjusted approach for identifying and analyzing the impact of the input variables in a model through the use of probabilistic sensitivity analysis based on copulas. This approach provides insights about the influence of both the input variables and the dependence relationships between the input variables. A key contribution of this approach is that it facilitates assessment of the relative marginal influence of variables for the purpose of determining which variables should be modeled in applications where computational efficiency is a concern, such as in decision tree analysis of large scale problems. In addition, we also investigate the sensitivity to the magnitude of correlation in the inputs.

This paper examines the information content of risk-neutral moments to explain crude oil futures returns. Implied volatility and higher moments are extracted from observed crude oil option prices using a model-free implied volatility framework and the Black-Scholes model. We find a tenuous and time-varying association between returns and implied volatility and its innovations. Specifically, changes in implied volatility are found to be meaningfully associated with crude returns only over the period spanning the recent financial crisis. Overall, results are consistent with prior evidence that crude oil prices are determined primarily in a flow demand/supply environment. Finally, we document that oil risk is priced into the cross-section of stock returns in the oil and transportation sectors.

Objective: Most previous studies about circulating tumor DNA focused on advanced stage cancer patients. We have completed a clinical prospective study (NCT02645318) and showed the feasibility of ctDNA detection in early stage (I-IIA) non-small cell lung cancer (NSCLC) patients, which have been published (Sci. Rep.6,31985,2016). We also investigated its clinical application on early diagnosis and showed our data by oral presentation in American Association of Thoracic Surgery Annual meeting 2016 in Baltimore. Based on our previous study, we further evaluated the clinical value of ctDNA. Few study revealed dynamic changes of circulating tumor DNA in surgical lung cancer patients that no criterion has been established of how to use it for surveillance. The aim of this study is to investigate the elimination rate of circulating tumor DNA level after surgery. This is the first prospective study to evaluate the dynamic changes of ctDNA in surgical lung cancer patients. Method: Consecutive patients with suspected lung cancer who underwent curative-intent lung resection were enrolled prospectively in this study from 11/2016. 10 mL blood samples were taken by intravenous puncture. Plasma samples were obtained before surgery (time A) and at a series of scheduled time-points (2 min to 72 hours, time B to F) after tumor resection. DNA was prepared from 4mL of purified plasma. We designed a multiplex assay based on circulating single-molecule amplification and resequencing technology (cSMART) to simultaneously detect and quantitate hot spot EGFR, KRAS, BRAF, ERBB2, PIK3CA, TP53, ALK, RET and MET plasma DNA variants, with matched white blood cell DNA as controls. Positive plasma mutations were validated in tumor tissue by targeted sequencing. Study protocol (ClinicalTrials.gov identifier NCT02965391) was approved by the Peking University People’s Hospital Medical Ethics Committee (2016PHB156-01). Results: A hundred and seven patients were enrolled, in which 18(16.8%)patients showed detectable driver mutations in the preoperative plasma sample (time A), 9 patients were excluded due to non-radical surgery(3); no plasma of other time-points(2); non-somatic driver mutations (2); no surgery performed(2). Therefore, 9 patients (4 stage I, 3 stage II and 2 stage III) with 11 mutations met the inclusion criteria, which included four EGFR, three TP53, two PIK3CA, one KRAS and one ALK mutations. All of the patients had a decrease of mutation ratio as time went on and dropped to 0 after 72 hours of tumor resection. The average mutation ratio was 2.99%, 1.64%, 0.82%, 0.03%, 0.015% and 0 at the time-points A to F, respectively. The evaluated half-life of ctDNA was about 10 min. The total DNA template appeared higher post-operation than pre-operation (3082±2234 vs.1787±1181, p=0.12).One patient had concurrent driver mutations of PIK3CA E545K and EGFR L858R. PIK3CA was detected in time A and decreased gradually from time B to C. EGFR was not detected in time A but in plasma time B and decreased in time C. Conclusion: The elimination of ctDNA in lung cancer patients is very rapid after surgical resection. The intraoperative manipulation may not only push forward releasing of cell free DNA, but also lead heterogeneous tumor mutation discharging to plasma. Detection of ctDNA 72h after surgery could be the reference value for postoperative surveillance. Note: This abstract was not presented at the meeting. Citation Format: Kezhong Chen, Fan Yang, Heng Zhao, Tianyang Wang, Lien Tu Wang, Jun Wang. A prospective study of dynamic changes of circulating tumor DNA in surgical lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr CT125. doi:10.1158/1538-7445.AM2017-CT125

This paper proposes a variant application of the Merton distance-to-default model by employing implied volatility and implied cost of capital to forecast defaults. The proposed model's results are compared with predictions obtained from the three popular models in different setups. We find that our "best" model, which contains both forward-looking proxies, outperforms all other models with a default prediction accuracy rate of 89%. Additional analysis using a discrete-time hazard model indicates that the psuedo-R² values from regression models that include the two implied measures are as high as 51%. Overall, our results establish the informational relevance of implied volatility and implied cost of capital in predicting defaults.

In a well-designed enterprise risk management (ERM) program, the firm integrates risk management into the strategic planning process, addressing strategic risk, financial risk, operational risk, and hazard risk under a single overarching process. This is particularly important to large financial firms, such as property and casualty (P&C) insurers, which face a diverse set of risks. We find that ERM quality, as measured by S&P ERM ratings from 2006-2012, has a strong positive affect on ROA and Tobin’s Q for P&C insurers. In contrast to previous studies that have found that diversified firms suffer a value discount relative to their more focused peers, the results of this study suggest that, after controlling for ERM quality, business line diversification is associated with a performance premium whereas geographic diversification is not a significant factor.

The selection of fewer or more representative features from multidimensional features is important when the artificial neural network (ANN) algorithm is used as a classifier. In this paper, a new feature selection method called the mean impact variance (MIVAR) method is proposed to determine the feature that is more suitable for classification. Moreover, this method is constructed on the basis of the training process of the ANN algorithm. To verify the effectiveness of the proposed method, the MIVAR value is used to rank the multidimensional features of the bearing fault diagnosis. In detail, (1) 70-dimensional all waveform features are extracted from a rolling bearing vibration signal with four different operating states, (2) the corresponding MIVAR values of all 70-dimensional features are calculated to rank all features, (3) 14 groups of 10-dimensional features are separately generated according to the ranking results and the principal component analysis (PCA) algorithm and a back propagation (BP) network is constructed, and (4) the validity of the ranking result is proven by training this BP network with these seven groups of 10-dimensional features and by comparing the corresponding recognition rates. The results prove that the features with larger MIVAR value can lead to higher recognition rates.

Modeling the dependence between uncertainties in decision and risk analyses is an important part of the problem structuring process. We focus on situations where correlated uncertainties are discrete, and extend the concept of the copula-based approach for modeling correlated continuous uncertainties to the representation of correlated discrete uncertainties. This approach reduces the required number of probability assessments significantly compared to approaches requiring direct estimates of conditional probabilities. It also allows the use of multiple dependence measures, including product moment correlation, rank order correlation and tail dependence, and parametric families of copulas such as normal copulas, t-copulas and Archimedean copulas. This approach can be extended to model the dependence between discrete and continuous uncertainties in the same event tree.

We derive a robust multi-period portfolio model considering investors' behavioral factors.A PSO with an aging leader and multi-frequency vibration (ALMV-PSO) is proposed.The ALMV-PSO algorithm is effective to solve the constrained multi-period portfolio model.The proposed portfolio model provides an effective tool for a real multi-period investment. The studies of behavioral finance show that the cognitive bias plays an important role in investors' decision-making process. In this paper, based on the robust theory and prospect theory, a robust multi-period portfolio considering investors' behavioral factors is constructed, which features the reference dependence, loss aversion and diminishing sensitivity. To solve the proposed portfolio model, an improved particle swarm optimization (PSO) algorithm is developed, which incorporates the two-stage initialization strategy, the improved stochastic ranking approach, the aging leader and the multi-frequency vibrational mutation operator. We illustrate the robust model with real market data and show its effectiveness based on the performance of the proposed algorithm. The results show that the proposed algorithm is successful in solving the constrained multi-period portfolio model and the proposed portfolio model provides an effective tool for a real multi-period investment.

In this paper, we have studied the effect of air pressure damping on the vibration- based energy harvesting devices. The device we used is an electrostatic energy harvester with an out-of-the-plane gap closing scheme. A broadened bandwidth is observed at 4 Pa when the acceleration is increased from 0.5 m/s2. A power output of 2.2 μW is achieved at the air pressure of 4 Pa when a low acceleration of 0.5 m/s2 is applied, while the power output is only 0.02 μW at atmosphere with an acceleration of 1.2 m/s2. Detailed study is made to investigate the waveform of the displacement and the voltage output. Nonlinearity is observed at low air gas pressure about 239 Pa and it is more significant at 4 Pa.

In this paper, a new method named cross-correlation approximate entropy is proposed based on the correlation analysis and the approximate entropy theory. It can detect anomaly of running state in a quantitative manner without any priori knowledge. The method takes a section of signal with fixed-length of running state of equipment as a window. By sliding the window through the state signal, the paper calculates the cross-correlation function of the first window and latter ones, and then figure out their approximate entropy values. This paper sets the approximate entropy value of cross-correlation function of the first and second windows as the standard value. If there is an anomaly, the approximate entropy value of cross-correlation function of windows will be far larger than the standard value. Finally, a case is studied to test the validity and stability of this method by using the normal vibration signals of normal and faulty rolling bearing.

CDHL algorithm is a new hybrid range-free localization algorithm, which combines the Centroid and DV-Hop algorithms. The basic theory of the algorithm was introduced in this paper, and the average localization error rate of this hybrid algorithm is discussed and the algorithm energy consumption is analyzed. Simulation experiments show that the proposed algorithm is effective on different network situations, and the energy consumption is in low level. The localization accuracy of the proposed algorithm has been improved by 5%–7% compared with DV-Hop.

Renal ischemia/reperfusion is a common cause of acute renal failure. Glycine is an effective anti-inflammatory, cytoprotective agent and is reported to have a beneficial effect against ischemia/reperfusion injury in various organs. Previous research notes that free radicals and inflammatory leukocytes both play important roles in the pathogenesis of renal ischemia/reperfusion injury. To develop new therapeutic agents against renal ischemia/reperfusion injury, we sought to link an antioxidant moiety (nitronyl nitroxide) to glycine in the hope that the resulting glycine-nitronyl nitroxide conjugate (GNN) would provide a synergetic protection against renal ischemia/reperfusion injury. In this manuscript, we report the synthesis and biological evaluation of the GNN conjugate. The biological activity of the GNN conjugate was evaluated in an in vivo rat model of renal ischemia/reperfusion induced injury and oxidative change. Since the GNN conjugate markedly reduced elevated levels of tissue lipid peroxidation and attenuated renal dysfunction in rats subjected to renal ischemia/reperfusion, it might be possible to develop the GNN conjugate into a potential therapeutic agent against renal ischemia/reperfusion injury.

The Role-Based Access Control (RBAC) model is widely accepted as the model of access control of workflow management system (WFMS).However, the RBAC model exist a lot of limit when it describe the authorization constraint of access control. Especially , the RBAC model cannot express the transaction character and the phase authorization constraint when the role and the user perform the task. This paper proposed an improved role-Based access control model for WFMS. The new authorization concepts for WfMS are defined respectively. The access control rules of IRBAC model are build, which can express complex access control constraints for WfMS.

In this paper, we proposed a framework of multimedia retrieval system base on the MPEG-7 standard as information schema. It provides a content- based retrieval method which uses MPEG-7 Metadata Schema. Our framework is aim at the high-level semantic retrieval, which composed of three module and fully rely on the MPEG-7 standard. This framework provides a rich set of automatic feature extraction components and an independent retrieval interface.

The traditional workflow technology has many disadvantages when applied in the inter-enterprise supply chain management systems. To overcome these disadvantages we design a cooperative control framework based on both integrated-distributed agent and workflow technology, we implemented the cooperating process between the collaborative originating agent and collaborative participation agent taking advantage of the MSA collaborative model; based on the RAWF (roled-driven agent workflow, RAWF) distributed transaction processing model, we described the dependence between different tasks. Finally we implemented the supply chain management system on the JADE platform and J2EE development frameworks.

Order tracking is one of the most effective algorithms to eliminate the effect of time-varying rotational speed on the rotary machines. However, this algorithm is not suitable for the faulty rolling bearing unless the peak time of the fault-induced impulse is set as zero which cannot be met in the real engineering. The traditional resampling process will cause uneven intervals between the adjacent impulse peaks in the angular domain and then affect the envelope analysis-based diagnosis result. To solve this problem, a new resampling algorithm with three parts is proposed: (a) linearly fitting the instantaneous rotational speed measured by the tachometer, (b) resampling the vibration signal from the time domain to the angular domain using the traditional method, (c) calculating the envelope deformation amount and then compensating the resampled result. The effectiveness of the proposed method has been validated by both the simulated and experimental bearing vibration signals.

Chrysanthemum indicum Flower is usually consumed as functional food. This paper described an improved total quality assessment method for Chrysanthemum indicum Flower by simultaneous quantitation using a single standard to determine multi-components method combined with high performance liquid chromatography fingerprint analysis. Six main components of Chrysanthemum indicum Flower including two flavonoids and four phenolic acids were simultaneously quantified using linarin as the internal reference standard. The method was fully validated with respect to linearity, precision, accuracy, robustness and stability. The validated method was successfully applied to the analysis of thirty three batches of Chrysanthemum indicum Flower samples. Under the same chromatographic conditions, fingerprint analysis in combination with Similarity analysis and principal component analysis was performed to identify the samples from different regions. In general, an effective assessment using a single standard to determinate multi-components method combined with fingerprint analysis make the reliable qualitation and quantitation analysis of Chrysanthemum indicum Flower available.

MALTA is a full scale monolithic pixel detector implemented in TowerJazz 180 nm CMOS technology. The small pixel electrode allowed for the implementation of a fast, low noise and low power front-end, which is sensitive to the charge released by ionizing radiation in a 20–25 μ m deep depleted region. The novel asynchronous matrix architecture is designed to ensure low power consumption and high rate capability. Such features make MALTA a possible candidate for the outer layer of ATLAS Inner Tracker (ITk) upgrade. Unirradiated and irradiated MALTA sensors have been extensively tested in laboratory and with high energy particle beams. Results of this measurements campaign are shown, and the further improvements that are being implemented in the next versions of the chip are discussed.