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Background It is well known that circadian rhythms and sleep homeostasis contribute to a pronounced trough in sleepiness and behavioral performance at night. However, the underlying neuroimaging mechanisms remain unclear. How brain-function connectivity is modulated during sleep deprivation (SD) has been rarely examined. Methods By increasing the number of scanning sessions during SD, the current study used voxel-mirrored homotopic connectivity (VMHC) to investigate dynamic changes in interhemispheric communication during one night of SD. Every 2 hours from 10 pm to 06 am (session 1, 10 pm; session 2, 12 am; session 3, 2 am; session 4, 4 am; session 5, 6 am), functional magnetic resonance-imaging data and Stanford Sleepiness Scale (SSS) scores were collected from 36 healthy participants with intermediate chronotype. Dynamic changes in SSS scores and VMHC were determined using one-way repeated-measure ANOVA with the false discovery-rate method to correct for multiple comparisons. Results Significant time effects for VMHC were found mainly in the bilateral thalamus, bilateral superior temporal gyrus, and bilateral precentral gyrus. SSS scores and VMHC in these areas were both found to be monotonously increased during SD. Furthermore, significant positive associations were found between SSS valu and VMHC values in the left superior temporal and right superior gyri. Conclusion These findings might represent the dynamic modulation of circadian rhythm merely or the interaction effects of both circadian rhythm and sleep homeostasis on interhemispheric connectivity within the thalamus, default-mode network, and sensorimotor network. Our study provides more comprehensive information on how SD regulates brain connectivity between hemispheres and adds new evidence of neuroimaging correlates of increased sleepiness after SD.

Despite evidence of structural brain abnormalities in schizophrenia, the current study aimed to explore the effects of antipsychotic treatment on gray matter (GM) volume using structural magnetic resonance imaging (MRI) and investigate the relationship between brain structure and treatment response. The GM volumes of 33 patients with first-episode schizophrenia were calculated with voxel-based morphometry (VBM), with 33 matched healthy controls. Longitudinal volume changes within subjects after 4-month antipsychotic treatment were also evaluated. Correlation between volumetric changes and clinical symptoms derived from the Positive and Negative Syndrome Scale (PANSS) were further investigated. Compared with healthy controls, decreased GM volumes in the frontal gyrus were observed in schizophrenia patients. After 4-month treatment, patients showed significantly decreased GM volume primarily in the bilateral frontal, temporal and left parietal brain regions. In addition, the GM volume changes of the left postcentral gyrus was positively correlated with negative symptoms improvement, and the correlation analysis revealed the total PANSS scores changes were associated with GM volume changes in the right inferior frontal gyrus and the right superior temporal gyrus. Besides, non-responders had reduced GM volume in the bilateral middle frontal gyrus and the right superior frontal gyrus compared with responders and healthy controls. Our results suggest that the abnormality in the right frontal gyrus exists in the early stage of schizophrenia. Moreover, the relationship between antipsychotics and structural changes was identified. The GM volume might have the potential to reflect the symptom improvement in schizophrenia patients. And MRI may assist in predicting the antipsychotic treatment response in first-episode schizophrenia patients.

Objective We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs. Methods Resting-state functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female). Results Compared with healthy controls, SZ at baseline showed lower clustering coefficient (Cp) and local network efficiency (Eloc), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of Cp was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes. Conclusion The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, Cp, the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ.

Nowadays, the design of tourism cultural and creative products based on regional cultural characteristics has gradually occupied the market. On the basis of ordinary cultural and creative product design, shoe mountain cultural creation can also cover certain cultural value, artistic value, commercial value and inheritance value. This paper is based on Hukou shoe mountain as a tourist resort, combined with the local historical background, customs, cultural heritage, geographical features and other elements to start, the unique characteristics of shoe mountain, Design and research of electronic cultural and creative products through computer aided means.

The purpose of writing this paper. Through the in-depth understanding and value analysis of Mo Gao Grottoe at Dunhuang culture, as well as the analysis of the design of daily furniture — —according to hangers, the comparison of product types and the current situation of development, this paper tries to do a good job in the study of integrating Dunhuang cultural symbols with furniture design. How to write this paper. The first is to study the development of Dunhuang culture and the types of murals represented by Mogao Grottoes culture through historical literature exploration and research, and the second is to investigate and analyze the clothes hangers and compare the existing clothes hangers. Through these two methods, the shortcomings of existing hangers are found and the necessity of innovative design of hangers is put forward. The third is to integrate Dunhuang culture with clothes hanger through semiotics in order to better spread Dunhuang culture and let more people understand the depth of Chinese traditional culture. Fourth, through the method of computer-aided design, the product modeling, the determination of the scale, color collocation, design deliberation, refining and finally according to the semiotics and formal beauty law to come up with a computer-aided scheme. Write the conclusion of this paper. According to the interpretation and analysis of Dunhuang Mogao Grottoes culture combined with the current situation of social shortcomings of clothes hangers, the two are combined by semiotics research method to help people understand the connotation of Chinese traditional culture in their daily life.

This paper describes the status and attention of artificial intelligence technology in the international academic and industrial circles, as well as the classification and appearance characteristics of wearable products. This paper analyzes the correlation between artificial intelligence technology and product applicability, and discusses the combination method of wearable products and artificial intelligence technology. Through the research on the appearance design of wearable products and the aesthetic analysis of wearable backpacks, an intelligent assisted wearable backpack with product aesthetic characteristics was designed by using design practice. The design not only meets the functional requirements of the product, but also meets the visual aesthetic requirements, which makes the design not only integrates artificial intelligence technology, but also conforms to formal aesthetics.

Schizophrenia (SCZ) is an inherited disease, with the familial risk being among the most important factors when evaluating an individual’s risk for SCZ. However, robust imaging biomarkers for the disease that can be used for diagnosis and determination of the prognosis are lacking. Here, we explore the potential of functional connectivity (FC) for use as a biomarker for the early detection of high-risk first-degree relatives (FDRs). Thirty-eight first-episode SCZ patients, 38 healthy controls (HCs), and 33 FDRs were scanned using resting-state functional magnetic resonance imaging. The subjects’ brains were parcellated into 200 regions using the Craddock atlas, and the FC between each pair of regions was used as a classification feature. Multivariate pattern analysis using leave-one-out cross-validation achieved a correct classification rate of 88.15% [sensitivity 84.06%, specificity 92.18%, and area under the receiver operating characteristic curve (AUC) 0.93] for differentiating SCZ patients from HCs. FC located within the default mode, frontal-parietal, auditory, and sensorimotor networks contributed mostly to the accurate classification. The FC patterns of each FDR were input into each classification model as test data to obtain a corresponding prediction label (a total of 76 individual classification scores), and the averaged individual classification score was then used as a robust measure to characterize whether each FDR showed an SCZ-type or HC-type FC pattern. A significant negative correlation was found between the average classification scores of the FDRs and their semantic fluency scores. These findings suggest that FC combined with a machine learning algorithm could help to predict whether FDRs are likely to show an SCZ-specific or HC-specific FC pattern.

Zhu Y, Ren F, Zhu Y, et al. Nat Sci Sleep. 2020;12:1067–1074. The authors have advised that the name of last author on page1067 is incorrect. Mingwen Zheng should be Minwen Zheng. The authors apologize for this error. Read the original article

The smart grid frequently collects consumers’ fine-grained power usage data through smart meters to facilitate various applications, such as billing, load monitoring, regional statistics, and demand response. However, the smart meter reading streams may also pose severe privacy threats to the consumers by leaking their appliances’ ON/OFF status. In this paper, we first quantitatively measure the information leakage with respect to specific appliances’ status from any reading stream, and define a novel privacy notion to bound such information leakage. In addition, we propose a privacy preserving streaming algorithm with different options to effectively convert readings and promptly stream safe readings in different fashions. The output time series readings satisfy our privacy notion while guaranteeing excellent utility, such as extremely low aggregation errors and billing errors. Finally, we experimentally validate the effectiveness and efficiency of our approach using real data sets.

Investigations of brain structure in schizophrenia using magnetic resonance imaging (MRI) have identified variations in regional grey matter (GM) volume throughout the brain but the results are mixed. This study aims to investigate whether the inconsistent voxel-based morphometry (VBM) findings in schizophrenia are due to the use of different software packages. T1 MRI images were obtained from 86 first-episode schizophrenia (FESZ) patients and 86 age- and gender-matched Healthy controls (HCs). VBM analysis was carried out using FMRIB software library (FSL) 5.0 and statistical parametric mapping 8 (SPM8). All images were processed using the default parameter settings as provided by these software packages. FSL-VBM revealed widespread GM volume reductions in FESZ patients compared with HCs, however, for SPM-VBM, only increased and circumscribed GM volume changes were found, both software revealed increased GM volume within cerebellum. Significant correlations between Positive and Negative Syndrome Scale (PANSS) and GM volume were mainly found in frontal regions. Algorithms of GM tissue segmentation, image registration and statistical strategies might contribute to these disparate results.

Nutrition therapy is considered an important treatment of burn patients. The aim of the study was to delineate the nutritional support in severe burn patients and to investigate association between nutritional practice and clinical outcomes. Severe burn patients were enrolled (n 100). In 90 % of the cases, the burn injury covered above 70 % of the total body surface area. Mean interval from injury to nutrition start was 2·4 (sd 1·1) d. Sixty-seven patients were initiated with enteral nutrition (EN) with a median time of 1 d from injury to first feed. Twenty-two patients began with parenteral nutrition (PN). During the study, thirty-two patients developed EN intolerance. Patients received an average of about 70 % of prescribed energy and protein. Patients with EN providing

With the development of the times and the promotion of technology, people’s living standards and aesthetic requirements have also been continuously improved. Intelligent design enables jewelry to break through its position in the traditional sense It is no longer limited to the handmade production of precious metals. Intelligent design can also be applied to jewelry design. The unlimited choice of materials allows designers to have greater design space and imagination. With the development of fashion trends, jewelry as a kind of decoration, in another way shows the personal quality of life and life attitude. Therefore, the more diversified forms of jewelry design are eclectic, and the pursuit of higher levels and more comprehensive forms to create fashionable and personalized products.

Abnormal expression of Retinoid X Receptor α (RXRα) seems to be a frequent incident in a variety of cancers. However, the expression pattern and the mechanisms in gastric carcinoma (GC) remain unclear.In GC tissues and cell lines, the expression levels of RXRα mRNA and protein were detected by Q-PCR and Western blot, respectively; the localization of RXRα was evaluated by immunohistochemistry (IHC) or immunocytochemistry (ICC). The effect of IL-1β on RXRα expression and localization was detected by Western blot and ICC. Nuclear factor-κB (NF-κB) pathway was assessed via Western blot.RXRα expression was markedly elevated at both mRNA and protein levels in GC tissues and cell lines (all P0.05). The abnormal overexpression of RXRα was predominantly visualized in cytoplasm. IL-1β significantly induced cytoplasmic expression of RXRα in a time-dependent manner. Co-incubation with IL-1β enhanced phospho-IKKα (p-IKKα) expression and this effect could be inhibited by the specific inhibitor for NF-κB (all P0.01).IL-1β upregulated RXRα through activation of NF-κB signaling and these suggested a possible clinic significance of retinoid receptor expression in the diagnosis and treatment of GC.

BACKGROUND: The aim of the study was to identify the clinical features and the factors associated with burn induced mortality among young adults after exposure to indoor explosion and fire. METHODS: This is an observational study which included burn patients who were admitted to eighteen ICUs after a fire disaster. Epidemiologic and clinical characteristics, as well as therapy were recorded. The primary outcome was 90-day mortality. The mortality-related factors were also analyzed. RESULTS: There were 167 burn patients enrolled in the study, the median age was 38 years, 62 (37.1%) patients died within 90 days. Seventy-one percent of patients had a burn size ≥90% TBSA, and 73.7% of patients had a full-thickness burn area above 50% TBSA. The survivors had lower Baux scores, and received earlier escharectomy and autologous skin grafts. The 50% mortality rates (LA50s) for burn size and full-thickness burn area were 95.8% and 88.6% TBSA, respectively. The multivariate analysis showed that full-thickness burn area over 50% TBSA and residual burned surface area (RBSA)/TBSA at 28 days were strong predictors of mortality among burn patients (odds ratio 2.55; 95% CI, 1.01 to 6.44, P=0.047; odds ratio 1.07; 95% CI, 1.04 to 1.09, P

Summary To date, increasing number of entities on the smart grid begin to establish their local energy generator for ensuring reliability and resilience of power supply. These ‘microgrids’ can either connect to the power grid or isolate themselves from the grid by consuming their locally generated or stored energy. In reality, some microgrids may have excessive energy while the others may have to request extra energy from the main grid. To better balance the demand and supply of the distributed smart microgrids, it is desired to develop peer-to-peer (P2P) energy exchange models that enable microgrids to interactively exchange their local energy instead of consuming energy delivered from the main grid. However, in this scenario, all the microgrids have to disclose their private information (e.g., demand load and energy storage amount) to each other in the exchange. To tackle these issues, in this paper, we first formulate several novel energy exchange optimization problems that minimize the global energy loss during the exchange in different scenarios, and then develop an efficient and privacy-preserving scheme to solve the energy exchange optimization problems without private information disclosure. We also extend the privacy-preserving scheme to a collusion-resistant scheme in which all the microgrids cannot learn any additional information through colluding with each other. The performance of our proposed approaches is experimentally validated on real microgrid data. Copyright © 2015 John Wiley & Sons, Ltd.

Web-based applications are gaining popularity as they require less client-side resources, and are easier to deliver and maintain. On the other hand, web applications also pose new security and privacy challenges. In particular, recent research revealed that many high profile web applications might cause sensitive user inputs to be leaked from encrypted traffic due to side-channel attacks exploiting unique patterns in packet sizes and timing. Moreover, existing solutions, such as random padding and packet-size rounding, were shown to incur prohibitive overhead while still failing to guarantee sufficient privacy protection. In this paper, we first observe an interesting similarity between this privacy-preserving traffic padding (PPTP) issue and another well studied problem, privacy-preserving data publishing (PPDP). Based on such a similarity, we present a formal PPTP model encompassing the privacy requirements, padding costs, and padding methods. We then formulate PPTP problems under different application scenarios, analyze their complexity, and design efficient heuristic algorithms. Finally, we confirm the effectiveness and efficiency of our algorithms by comparing them to existing solutions through experiments using real-world web applications.

The small structures can directly affect the admissibility of the coal seam, the mining schedule, cost and safety. Seismic attributes extracted from seismic data can be used to identify small structures; However, geophysical methods often have multiple solutions, this will make the results of interpretation become unreliable. In this paper we will use image fusion technology to fuse a variety of seismic attributes, and then make full use of the complementarity of different attributes to reduce the multiple solutions, and make the seismic attributes more accurately in predicting small structures in coalmine.

The conventional inversion can only get P-impedance data, but neural network inversion can obtain various kinds of well-log attributes data by getting the nonlinear relationship through training the data of seismic attributes and well-log attributes, and then apply the nonlinear relationship to the whole seismic data volume. In this paper, we use multilayer feed forward neural network, probability neural network and radial basis function neural network to carry out the log-density inversion research, and obtain three pseudo density data volumes. We compare the effect of the inversion results and analysis the density distribution in spatial domain through section and slice data, at last we predict the stability of the coal seam’s floor in more reasonable way.

// Hong-Yue Ren 1, * , Fan Liu 2, * , Gui-Li Huang 3 , Yu Liu 4 , Jin-Xing Shen 4 , Pan Zhou 3 , Wen-Ming Liu 5 , Dong-Yan Shen 4 1 Department of Pathology, The Affiliated Southeast Hospital of Xiamen University, Zhangzhou 363000, Fujian Province, China 2 Department of Medical College, Xiamen University, Xiamen 361005, Fujian Province, China 3 State Key Laboratory of Cellular Stress Biology, Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, Department of Life Sciences, Xiamen University, Xiamen 361005, Fujian Province, China 4 Department of Biobank, The First Affiliated Hospital of Xiamen University, Xiamen 361003, Fujian Province, China 5 Department of Gastroenterology, Zhongshan Hospital, Gastroenterology Institute of Xiamen University, Gastroenterology Center of Xiamen, Xiamen 361003, Fujian Province, China * These authors have contributed equally to this work Correspondence to: Dong-Yan Shen, email: shendongyan@163.com Wen-Ming Liu, email: 846928419@qq.com Keywords: RARα, gastric carcinoma, Akt, IL-1β Received: July 02, 2016 Accepted: December 01, 2016 Published: December 27, 2016 ABSTRACT Abnormal expression and function of retinoic acid receptor α (RARα) have been reported to be associated with various cancers including acute promyelocytic leukemia and hepatocellular carcinoma. However, the role and the mechanism of RARα in gastric carcinoma (GC) were unknown. Here, the expression of RARα was frequently elevated in human GC tissues and cell lines, and its overexpression was closely correlated with tumor size, lymph node metastasis and clinical stages in GC patients. Moreover, RARα overexpression was related with pathological differentiation. Functionally, RARα knockdown inhibited the proliferation and metastasis of GC cells, as well as enhanced drug susceptibility both in vitro and in vivo . Additionally, RARα knockdown suppressed GC progression through regulating the expression of cell proliferation, cell cycle, invasion and drug resistance associated proteins, such as PCNA, CyclinB1, CyclinD2, CyclinE, p21, MMP9 and MDR1. Mechanistically, the above oncogenic properties of RARα in GC were closely associated with Akt signaling activation. Moreover, overexpression of RARα was induced by IL-1β/Akt signaling activation, which suggested a positive feedback loop of IL-1β/Akt/RARα/Akt signaling in GC. Taken together, we demonstrated that RARα was frequently elevated in GC and exerted oncogenic properties. It might be a potential molecular target for GC treatment.

In this chapter, we study the side channel leak of sensitive micro-data in which adversaries combine the published data with their knowledge about the generalization algorithms used to produce such data, in order to refine their mental image about the sensitive data. Today, data owners are usually expected to disclose micro-data for research, analysis, and various other purposes. In disclosing micro-data with sensitive attributes, the goal is usually twofold. First, the data utility of disclosed data should be preserved to a certain level for analysis purposes. Second, the private information contained in such data must be sufficiently hidden. Typically, a disclosure algorithm would first sort potential generalization functions into a predetermined order (e.g., with decreasing utility), and then discloses data using the first generalization function that satisfies the desired privacy property. Knowledge about how such disclosure algorithms work can usually render the algorithm unsafe, because adversaries may refine their guesses of the sensitive data by “simulating” the algorithms and comparing with the disclosed data. In this chapter, we show that an existing unsafe algorithm can be transformed into a large family of safe algorithms, namely, k-jump algorithms. We then prove that the data utility of different k-jump algorithms is generally incomparable, which is independent of utility measures and privacy models. Finally, we analyze the computational complexity of k-jump algorithms, and confirm the necessity of safe algorithms even when a secret choice is made among algorithms.

In this chapter, we present a formal Privacy-Preserving Traffic Padding (PPTP) model encompassing the privacy requirements, padding costs, and padding methods to prevent side-channel leaks due to unique patterns in packet sizes and directions of the encrypted traffic among components of the Web application. Web-based applications are gaining popularity as they require less client-side resources, and are easier to deliver and maintain. On the other hand, Web applications also pose new security and privacy challenges. In particular, recent research revealed that many high profile Web applications might cause sensitive user inputs to be leaked from encrypted traffic due to side-channel attacks exploiting unique patterns in packet sizes and timing. Moreover, existing solutions, such as random padding and packet-size rounding, were shown to incur prohibitive overhead while still failing to guarantee sufficient privacy protection. In this chapter, we first observe an interesting similarity between this privacy-preserving traffic padding (PPTP) issue and another well studied problem, privacy-preserving data publishing (PPDP). Based on such a similarity, we present a formal PPTP model encompassing the privacy requirements, padding costs, and padding methods. We then formulate PPTP problems under different application scenarios, analyze their complexity, and design efficient heuristic algorithms. Finally, we confirm the effectiveness and efficiency of our algorithms by comparing them to existing solutions through experiments using real-world Web applications.

The solutions in the previous chapter rely on the assumption that adversaries do not possess prior background knowledge about possible user inputs, which is a common limitation shared by most existing solutions. In this chapter, we discuss a random ceiling padding approach whose results are resistant to such adversarial knowledge. Recent studies show that a Web-based application may be inherently vulnerable to side-channel attacks which exploit unique packet sizes to identify sensitive user inputs from encrypted traffic. Existing solutions based on packet padding or packet-size rounding generally rely on the assumption that adversaries do not possess prior background knowledge about possible user inputs. In this chapter, we propose a novel random ceiling padding approach whose results are resistant to such adversarial knowledge. Specifically, the approach injects randomness into the process of forming padding groups, such that an adversary armed with background knowledge would still face sufficient uncertainty in estimating user inputs. We formally present a generic scheme and discuss two concrete instantiations. We then confirm the correctness and performance of our approach through both theoretic analysis and experiments with two real world applications.

The previous chapters have described in-depth studies of side channel leaks in different applications. Although those side channel leaks and their corresponding countermeasures all look very different, there in fact exists some commonality in terms of both challenges and solutions. For example, in previous chapters, we usually apply a similar idea for tacking side channel leaks, i.e., we divide objects into groups and then break the linkage inside each group by obfuscating any observable information about the objects, where objects are either published micro-data records, encrypted packets (sizes) in web applications, or readings reported by a smart meter. In this chapter, we design a general framework for preserving privacy against side-channel leaks. We show how different problems may fit into this framework by revisiting the three side channel leaks covered in previous chapters.

The privacy preserving issues have received significant attentions in various domains. Various models and techniques have been proposed to achieve optimal privacy with minimal costs. However, side-channel leakages (such as, publicly-known algorithms of data publishing, observable traffic information in web application, fine-grained readings in smart metering) further complicate the process of privacy preservation. In this thesis, we make the first effort on investigating a general framework to model side-channel attacks across different domains and applying the framework to various categories of applications. In privacy-preserving data publishing with publicly-known algorithms, we first theoretically study a generic strategy independent of data utility measures and syntactic privacy properties. We then propose an efficient approach to preserving diversity. In privacy-preserving traffic padding in Web applications, we first propose a formal PPTP model to quantify the privacies and costs based on the key observation about the similarity between data publishing and traffic padding. We then introduce randomness into the previous solutions to provide background knowledge-resistant privacy guarantee. In privacy-preserving smart metering, we propose a light-weight approach to simultaneously preserving privacy on both billing and consumption aggregation based on the key observation about the privacy issue beyond the fine-grained readings.

Secure multi-party computation (SMC) allows multiple parties to jointly and securely compute a function while preserving the privacy of the involved parties. In this regard, homomorphic cryptosystems allow users to perform addition or multiplication operations on encrypted values without having to decrypt the input values. In this paper, we propose both a cryptographic and a non-cryptographic privacy-preserving protocols that allow one party to collaboratively compute a private polynomial function with at least two other parties using semantically secure cryptosystems. In this respect, the function to be evaluated is kept private to the party in question. In addition, we assume that there is no fully trusted party and that all parties are semi-honest. Moreover, we assume that there is no collusion between the different parties. We present the two protocols in question and report on the underlying performance through the presentation of our implementation results. The proposed protocols are relevant in many applications such as evidence sharing in multi-party forensic investigations, situation awareness through the secure sharing in distributed monitoring of plan execution, etc.

// San-Gang Wu 1, * , Zhao-Qiang Zhang 2, * , Wen-Ming Liu 3, * , Zhen-Yu He 4 , Feng-Yan Li 4 , Huan-Xin Lin 4 , Jia-Yuan Sun 4 , Hui Lin 5 , Qun Li 4 1 Department of Radiation Oncology, the First Affiliated Hospital of Xiamen University, Xiamen 361003, People’s Republic of China 2 Eye Institute of Xiamen University, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Medical College of Xiamen University, Xiamen 361003, People’s Republic of China 3 Department of Gastroenterology, Zhongshan Hospital of Xiamen University, Xiamen 361003, People’s Republic of China 4 Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Collaborative Innovation Center of Cancer Medicine, Guangzhou 510060, People’s Republic of China 5 Department of Cardiovascular and Thoracic Surgery, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, People’s Republic of China * These authors contributed equally to this work Correspondence to: Hui Lin, e-mail: linhui33622@sina.com Qun Li, e-mail: liqun0799@126.com Keywords: esophageal cancer, lymph nodes, preoperative radiotherapy, survival, SEER Received: October 29, 2015 Accepted: February 24, 2016 Published: March 16, 2016 ABSTRACT To assess the impact of the number of resected lymph nodes (RLNs) for survival in esophageal cancer (EC) patients treated with preoperative radiotherapy and cancer-directed surgery. The Surveillance Epidemiology and End Results (SEER) database was queried to identify EC patients treated from 1988 to 2012 who had complete data on the number of positive lymph nodes and number of RLNs. Kaplan–Meier survival analysis and Cox regression proportional hazard methods were used to determine factors that significantly impact cause-specific survival (CSS) and overall survival (OS). There were a total of 3,159 patients who received preoperative radiotherapy and cancer-directed surgery. The median number of RLNs was 10 in both patients who received and did not receive preoperative radiotherapy ( P = 0.332). Cox regression univariate and multivariate analysis showed that RLN count was a significant prognostic factor for CSS and OS. Patients with 11–71 RLNs had better CSS (hazard ratio [HR] = 0.694, 95% confidence interval [CI]: 0.603–0.799, P < 0.001) and OS (HR = 0.724, 95% CI: 0.636–0.824, P < 0.001) than patients with 1–10 RLNs. The 5-year CSS rates were 39.1% and 44.8% in patients with 1–10 RLNs and 11–71 RLNs, respectively ( P < 0.001). The 5-year OS rates were 33.7% and 39.9% in patients with 1–10 RLNs and 11–71 RLNs, respectively ( P < 0.001). A higher number of RLNs was associated with better survival by tumor stage and nodal stage (all P < 0.05). RLN count is an independent prognostic factor in EC patients who undergo preoperative radiotherapy and cancer-directed surgery.

Studies comparing gray matter (GM) volume of schizophrenic patients with or without auditory verbal hallucinations (AVHs) to that of normal controls remain controversial. This project aims to investigate changes of GM volumes of drug-naïve schizophrenic patients with and without AVHs. Eighteen first episode schizophrenic (FES) patients with AVHs, 18 FES patients without AVHs and 18 healthy controls were scanned using structural MRI. Voxel-based morphometry (VBM) analysis was conducted to investigate changes of GM volume among the three groups. Patients with and without AVHs exhibited reduced GM volumes relative to normal controls in the left superior temporal gyrus, frontal regions, cerebellum and caudate. Further analysis of the GM of subcortical structures found that patients with AVHs had reduced thalamic volume than healthy controls. No significant difference was found between patients with and without AVHs. Significant correlation was found between the total scores of the Positive and Negative Syndrome Scale and bilateral thalamic volume. ROC analysis of thalamic volumes of the patients with AVHs and normal controls showed that the area under the curve was 0.698 (P = 0.043). The decreased thalamic volumes might serve as a biomarker for discriminating FES AVHs patients from normals.

While enjoying the convenience of Software as a Service (SaaS), users are also at an increased risk of privacy breaches. Recent studies show that a Web-based application may be inherently vulnerable to side-channel attacks which exploit unique packet sizes to identify sensitive user inputs from encrypted traffic. Existing solutions based on packet padding or packet-size rounding generally rely on the assumption that adversaries do not possess prior background knowledge about possible user inputs. In this paper, we propose a novel random ceiling padding approach whose results are resistant to such adversarial knowledge. Specifically, the approach injects randomness into the process of forming padding groups, such that an adversary armed with background knowledge would still face sufficient uncertainty in estimating user inputs. We formally present a generic scheme and discuss two concrete instantiations. We then confirm the correctness and performance of our approach through both theoretic analysis and experiments with two real world applications.

While web-based applications are becoming increasingly ubiquitous, they also present new security and privacy challenges. In particular, recent research revealed that many high profile Web applications might cause private user information to leak from encrypted traffic due to side-channel attacks exploiting packet sizes and timing. Moreover, existing solutions, such as random padding and packet-size rounding, are shown to incur prohibitive cost while still not ensuring sufficient privacy protection. In this paper, we propose a novel k-indistinguishable traffic padding technique to achieve the optimal tradeoff between privacy protection and communication and computational cost. Specifically, we first present a formal model of the privacy-preserving traffic padding (PPTP). We then formulate PPTP problems under different application scenarios, analyze their complexity, and design efficient heuristic algorithms. Finally, we confirm the effectiveness and efficiency of our algorithms by comparing them to existing solutions through experiments using real-world Web applications.

While web-based applications are gaining popularity, they also pose new security challenges. In particular, Chen et al. recently revealed that many popular Web applications actually leak out highly sensitive data from encrypted traffic due to side-channel attacks using packet sizes and timing [1]. They further demonstrated that existing solutions usually incur a high overhead while still not guaranteeing privacy protection. In this paper, we observe a striking similarity between this issue and another well studied problem, privacy-preserving data publishing (PPDP). Based on such a similarity, we propose a formal model for privacy-preserving traffic padding (PPTP) that encompasses privacy requirement, padding cost, and padding methods.

The general dispersion relation for polariton modes of a system described by a spatially periodic local dielectric function is derived. The dispersion relation is evaluated numerically for a number of different semiconductor superlattice systems.

The ground-state energy of a shallow impurity in a semiconductor quantum well of finite barrier height is calculated using a variational method. The binding energy U is obtained as a function of the well width L, the impurity position ${z}_{i}$, and the height of the potential barrier ${V}_{0}$. The behavior of the variational parameter \ensuremath{\lambda}, which determines the extension of the wave function around the impurity, is also studied. The maximum binding energy corresponds to the minimum value of \ensuremath{\lambda}. Larger values of ${V}_{0}$ result in faster variation of U with ${z}_{i}$. Our results agree very well with published experimental data.