bluuebunny/crossref_metadata_2025 huggingface dataset:
Public misperception that very low nicotine cigarettes are less carcinogenic
Authors: Byron M Justin , Jeong Michelle , Abrams David B , Brewer Noel T
Published: January 2018

Objective

The USA is considering a very low nicotine content (VLNC) cigarette standard. We sought to characterise the prevalence and correlates of the incorrect belief that VLNC cigarettes are less carcinogenic than current cigarettes, as this could reduce motivation to quit.

Methods

Participants were a nationally representative sample of 650 adult smokers in the USA. In 2015–2016, before the VLNC proposal became public, these smokers took part in an online survey. We used multivariate weighted analyses to calculate ORs and percentages and a χ2 test to examine the association between variables.

Results

Overall, 47.1% of smokers believed that smoking VLNC cigarettes for 30 years would be less likely to cause cancer than smoking current cigarettes. This misperception was more common among smokers who were aged above 55 (56.6%) and black (57.4%). Additionally, 23.9% of smokers reported they would be less likely to quit if the USA adopted a VLNC standard. Thinking that VLNC cigarettes would be less carcinogenic was associated with smokers reporting they would be less likely to quit (P<0.01).

Conclusions

Many smokers had the misperception that smoking VLNC cigarettes is less likely to cause cancer, and some stated that they would be less likely to quit. A VLNC standard may be more effective if accompanied by a communication campaign that emphasises the continued dangers of smoking VLNC cigarettes due to the many toxic chemicals in smoke.
Model Reference Adaptive Control Scheme for Retuning Method-Based Fractional-Order PID Control with Disturbance Rejection Applied to Closed-Loop Control of a Magnetic Levitation System
Authors: Tepljakov Aleksei , Alagoz Baris Baykant , Gonzalez Emmanuel , Petlenkov Eduard , Yeroglu Celaleddin
Published: January 2018

This study demonstrates the utilization of model reference adaptive control (MRAC) for closed-loop fractional-order PID (FOPID) control of a magnetic levitation (ML) system. Design specifications of ML transportation systems require robust performance in the presence of environmental disturbances. Numerical and experimental results demonstrate that incorporation of MRAC and FOPID control can improve the disturbance rejection control performance of ML systems. The proposed multiloop MRAC–FOPID control structure is composed of two hierarchical loops which are working in conjunction to improve robust control performance of the system in case of disturbances and faults. In this multiloop approach, an inner loop performs a regular closed-loop FOPID control, and the outer loop performs MRAC based on Massachusetts Institute of Technology (MIT) rule. These loops are integrated by means of the input-shaping technique and therefore no modification of any parameter of the existing closed-loop control system is necessary. This property provides a straightforward design solution that allows for independent design of each loop. To implement FOPID control of the ML system, a retuning technique is used which allows transforming an existing PID control loop into an FOPID control loop. This paper presents the simulation and experimental results and discusses possible contributions of multiloop MRAC–FOPID structure to disturbance rejection control of the ML system.
On Non-standard Hilbert Functions
Authors: Bagheri Amir , Rahmati-Asghar Rahim
Published: January 2018

Let [Formula: see text] be a non-standard polynomial ring over a field k and let M be a finitely generated graded S-module. In this paper, we investigate the behaviour of Hilbert function of M and its relations with lattice point counting. More precisely, by using combinatorial tools, we prove that there exists a polytope such that the image of Hilbert function in some degree is equal to the number of lattice points of this polytope.
Improving Verification Accuracy of CPS by Modeling and Calibrating Interaction Uncertainty
Authors: Yang Wenhua , Xu Chang , Pan Minxue , Ma Xiaoxing , Lu Jian
Published: January 2018

Cyber-Physical Systems (CPS) intrinsically combine hardware and physical systems with software and network, which are together creating complex and correlated interactions. CPS applications often experience uncertainty in interacting with environment through unreliable sensors. They can be faulty and exhibit runtime errors if developers have not considered environmental interaction uncertainty adequately. Existing work in verifying CPS applications ignores interaction uncertainty and thus may overlook uncertainty-related faults. To improve verification accuracy, in this article we propose a novel approach to verifying CPS applications with explicit modeling of uncertainty arisen in the interaction between them and the environment. Our approach builds an Interactive State Machine network for a CPS application and models interaction uncertainty by error ranges and distributions. Then it encodes both the application and uncertainty models to Satisfiability Modulo Theories (SMT) formula to leverage SMT solvers searching for counterexamples that represent application failures. The precision of uncertainty model can affect the verification results. However, it may be difficult to model interaction uncertainty precisely enough at the beginning, because of the uncontrollable noise of sensors and insufficient data sample size. To further improve the accuracy of the verification results, we propose an approach to identifying and calibrating imprecise uncertainty models. We exploit the inconsistency between the counterexamples’ estimate and actual occurrence probabilities to identify possible imprecision in uncertainty models, and the calibration of imprecise models is to minimize the inconsistency, which is reduced to a Search-Based Software Engineering problem. We experimentally evaluated our verification and calibration approaches with real-world CPS applications, and the experimental results confirmed their effectiveness and efficiency.
Data Stream Evolution Diagnosis Using Recursive Wavelet Density Estimators
Authors: Treviño Edgar S. García , Hameed Muhammad Zaid , Barria Javier A
Published: January 2018

Data streams are a new class of data that is becoming pervasively important in a wide range of applications, ranging from sensor networks, environmental monitoring to finance. In this article, we propose a novel framework for the online diagnosis of evolution of multidimensional streaming data that incorporates Recursive Wavelet Density Estimators into the context of Velocity Density Estimation. In the proposed framework changes in streaming data are characterized by the use of
local
and
global evolution coefficients
. In addition, we propose for the analysis of changes in the correlation structure of the data a recursive implementation of the Pearson correlation coefficient using exponential discounting. Two visualization tools, namely temporal and spatial velocity profiles, are extended in the context of the proposed framework. These are the three main advantages of the proposed method over previous approaches: (1) the memory storage required is minimal and independent of any window size; (2) it has a significantly lower computational complexity; and (3) it makes possible the fast diagnosis of data evolution at all dimensions and at relevant combinations of dimensions with only one pass of the data. With the help of the four examples, we show the framework’s relevance in a change detection context and its potential capability for real world applications.
Joint Representation Learning for Location-Based Social Networks with Multi-Grained Sequential Contexts
Authors: Zhao Wayne Xin , Fan Feifan , Wen Ji-Rong , Chang Edward Y.
Published: January 2018

This article studies the problem of learning effective representations for Location-Based Social Networks (LBSN), which is useful in many tasks such as location recommendation and link prediction. Existing network embedding methods mainly focus on capturing topology patterns reflected in social connections, while check-in sequences, the most important data type in LBSNs, are not directly modeled by these models. In this article, we propose a representation learning method for LBSNs called as JRLM++, which models check-in sequences together with social connections. To capture sequential relatedness, JRLM++ characterizes two levels of sequential contexts, namely fine-grained and coarse-grained contexts. We present a learning algorithm tailored to the hierarchical architecture of the proposed model. We conduct extensive experiments on two important applications using real-world datasets. The experimental results demonstrate the superiority of our model. The proposed model can generate effective representations for both users and locations in the same embedding space, which can be further utilized to improve multiple LBSN tasks.
GOOWE
Authors: Bonab Hamed R. , Can Fazli
Published: January 2018

Designing adaptive classifiers for an evolving data stream is a challenging task due to the data size and its dynamically changing nature. Combining individual classifiers in an online setting, the ensemble approach, is a well-known solution. It is possible that a subset of classifiers in the ensemble outperforms others in a time-varying fashion. However, optimum weight assignment for component classifiers is a problem, which is not yet fully addressed in online evolving environments. We propose a novel data stream ensemble classifier, called Geometrically Optimum and Online-Weighted Ensemble (GOOWE), which assigns optimum weights to the component classifiers using a sliding window containing the most recent data instances. We map vote scores of individual classifiers and true class labels into a spatial environment. Based on the Euclidean distance between vote scores and ideal-points, and using the linear least squares (LSQ) solution, we present a novel, dynamic, and online weighting approach. While LSQ is used for batch mode ensemble classifiers, it is the first time that we adapt and use it for online environments by providing a spatial modeling of online ensembles. In order to show the robustness of the proposed algorithm, we use real-world datasets and synthetic data generators using the Massive Online Analysis (MOA) libraries. First, we analyze the impact of our weighting system on prediction accuracy through two scenarios. Second, we compare GOOWE with eight state-of-the-art ensemble classifiers in a comprehensive experimental environment. Our experiments show that GOOWE provides improved reactions to different types of concept drift compared to our baselines. The statistical tests indicate a significant improvement in accuracy, with conservative time and memory requirements.
Titus
Authors: Leung Andrew , Spyker Andrew , Bozarth Tim
Published: January 2018

Approaching container adoption in an already cloud-native infrastructure.
Fast, Accurate, and Flexible Algorithms for Dense Subtensor Mining
Authors: Shin Kijung , Hooi Bryan , Faloutsos Christos
Published: January 2018

Given a large-scale and high-order tensor, how can we detect dense subtensors in it? Can we spot them in near-linear time but with quality guarantees? Extensive previous work has shown that dense subtensors, as well as dense subgraphs, indicate anomalous or fraudulent behavior (e.g., lockstep behavior in social networks). However, available algorithms for detecting dense subtensors are not satisfactory in terms of speed, accuracy, and flexibility. In this work, we propose two algorithms, called M-Z
oom
and M-B
iz
, for fast and accurate dense-subtensor detection with various density measures. M-Z
oom
gives a lower bound on the density of detected subtensors, while M-B
iz
guarantees the local optimality of detected subtensors. M-Z
oom
and M-B
iz
can be combined, giving the following advantages: (1)
Scalable:
scale near-linearly with all aspects of tensors and are up to
114× faster
than state-of-the-art methods with similar accuracy, (2)
Provably accurate
: provide a guarantee on the lowest density and local optimality of the subtensors they find, (3)
Flexible:
support multi-subtensor detection and size bounds as well as diverse density measures, and (4)
Effective:
successfully detected edit wars and bot activities in Wikipedia, and spotted network attacks from a TCP dump with near-perfect accuracy (AUC = 0.98).
Objectives and State-of-the-Art of Location-Based Social Network Recommender Systems
Authors: Ding Zhijun , Li Xiaolun , Jiang Changjun , Zhou Mengchu
Published: January 2018

Because of the widespread adoption of GPS-enabled devices, such as smartphones and GPS navigation devices, more and more location information is being collected and available. Compared with traditional ones (e.g., Amazon, Taobao, and Dangdang), recommender systems built on location-based social networks (LBSNs) have received much attention. The former mine users’ preferences through the relationship between users and items, e.g., online commodity, movies and music. The latter add location information as a new dimension to the former, hence resulting in a three-dimensional relationship among users, locations, and activities. In this article, we summarize LBSN recommender systems from the perspective of such a relationship. User, activity, and location are called objects, and recommender objectives are formed and achieved by mining and using such 3D relationships. From the perspective of the 3D relationship among these objects, we summarize the state-of-the-art of LBSN recommender systems to fulfill the related objectives. We finally indicate some future research directions in this area.
Elements of the theory of dynamic networks
Authors: Michail Othon , Spirakis Paul G.
Published: January 2018

The challenge of computing in a highly dynamic environment.
Quantum technology forgoes unconditional security to extend its reach
Authors: Edwards Chris
Published: January 2018

Two projects in China demonstrate the possibility of global quantum key distribution networks.
The war over the value of personal data
Authors: Kugler Logan
Published: January 2018

In a world increasingly dependent on turning personal data into profits, it is unclear how much that data is actually worth.
The inclusive and accessible workplace
Authors: Wille Sarah , Sajous-Brady Daphne
Published: January 2018

Maximizing the performance of neurodiverse talent.
Reducing the attack surface
Authors: Neville-Neil George V.
Published: January 2018

Sometimes you can give the monkey a less-dangerous club.
Parking Management Efficiency Analysis through Various Charge Schemes for Day-Long Commuting considering Elastic Travel Demand
Authors: Wang Jing , Tan Chaowu , Liu Zhigang
Published: January 2018

In this paper, we investigate the travel pattern of the day-long commuting in a bisection bottleneck network and the efficiency of pricing schemes with elastic travel demand. We extend the Vickrey model to morning and evening commutes and allow commuters to arrive at workplace late and depart from workplace early. The parking searching time is considered in the morning commute. Next, we derive the independent morning and evening commuting travel patterns without road toll and parking fee. Then, we propose three pricing regimes: duration dependent parking fees; optimal time-varying road tolls; optimal time-varying road tolls with duration dependent parking fees. We compare the efficiency of the four schemes with elastic demand. Theoretical analysis and the numerical examples show that optimal time-varying road toll is the most efficient pricing scheme. Charging a duration dependent fee neither improves nor deteriorates the scheme of time-varying road toll, if the toll rates are appropriately set. The regime of duration dependent parking fee only is less efficient than the regime of independent morning and evening commuting travel patterns without road toll and parking fee. In the regime of duration dependent parking fee, the social surplus decreases with the increase of duration dependent parking fee rate.
A Deep Alteration and Oxidation Profile in a Shallow Clay Aquitard: Example of the Tégulines Clay, East Paris Basin, France
Authors: Lerouge Catherine , Robinet Jean-Charles , Debure Mathieu , Tournassat Christophe , Bouchet Alain , Fernández Ana María , Flehoc Christine , Guerrot Catherine , Kars Myriam , Lagroix France , Landrein Philippe , Madé Benoit , Negrel Philippe , Wille Guillaume , Claret Francis
Published: January 2018

The oxidation profile of a surficial clay aquitard was studied on a 35-meter borecore from the Albian Tégulines Clay near Brienne-le-Château (Paris Basin, France). Mineralogical, geochemical, and petrophysical data showed evidences of gradual oxidation taking place down to a depth of 20 m. Below 20 m, the clay material was nonplastic and nonfractured, and it inherited reduced redox conditions from bacterial sulfate reduction that occurred after sediment deposition. Above 20 m, the clay material was plastic. Up to a depth of 10-11 m, only rare yellowish aggregates of glauconite attested to limited oxidation, and pore water chemistry was unmodified. The 5–11 m depth interval was characterized by intensive pyrite oxidation, calcite dissolution, and formation of sulfate and iron hydroxide minerals. The upper 2-3 m was ochrous and entirely oxidized. These mineralogical changes were mirrored with pore water chemistry modifications such as an increase of alkalinity and sulfate concentration in the upper part of the profile. The presence of siderite at ~11 m evinced the reactivity of Fe(II) in the structure of clay minerals with dioxygen from meteoric waters that infiltrated into the Tégulines Clay through vertical fractures.
Analysis of Control Rod Drop Accidents for the Canadian SCWR Using Coupled 3-Dimensional Neutron Kinetics and Thermal Hydraulics
Authors: Salaun Frederic , Novog David R.
Published: January 2018

The Canadian Supercritical Water-cooled Reactor (SCWR), a GEN IV reactor design, is a hybrid design of the well-established CANDU™ and Boiling Water Reactor with water above its thermodynamic critical point. Given the batch fueled design, control rods are used to manage the reactivity throughout the fuel cycle. This paper examines the consequences of a control rod drop accident (CRDA) for the Canadian SCWR. The asymmetry generated by the dropped rod requires an accurate 3-dimensional neutron kinetics calculation coupled to a detailed thermal-hydraulic model. Before simulating the CRDAs, the proper implementation of the 3D reactivity feedback was verified and various sensitivity studies were performed. This work demonstrates that the proposed safety systems for the SCWR core are capable of terminating the CRDA sequence prior to exceeding maximum sheath and centerline temperatures. In one instance involving a rod on the periphery of the core, the proposed trip setpoint (115% FP) was not exceeded and a new steady state was reached. Therefore it is recommended that the design also include provisions for a high-log rate and/or local Neutron Overpower Protection (NOP) trips, similar to existing CANDU designs such that reactor shutdown can be assured for such spatial anomalies.
The Application of Macroprudential Capital Requirements in Managing Systemic Risk
Authors: Fan Hong , Keregero Chirongo Moses , Gao Qianqian
Published: January 2018

When setting banks regulatory capital requirement based on their contribution to the overall risk of the banking system we need to consider that the risk of the banking system as well as each banks risk contribution changes once bank equity capital gets redistributed. Therefore the present paper provides a theoretical framework to manage the systemic risk of the banking system in Nigeria based on macroprudential capital requirements, which requires banks to hold capital that is proportional to their contribution to systemic risk. Using a sample of 10 Nigerian banks, we reallocate capital in the system based on two scenarios; firstly in the situation where the system shocks do not exist in the system, we find that almost all banks appear to hold more capital; secondly, we also consider the situation where the system shocks exist in the system; we find that almost all banks tend to hold little capital on four risk allocation mechanisms. We further find that despite the heterogeneity in macroprudential capital requirements, all risk allocation mechanisms bring a substantial decrease in the systemic risk. The risk allocation mechanism based on ΔCoVaR decreases the average default probability the most. Our results suggest that financial stability can be substantially improved by implementing macroprudential regulations for the banking system.
Security Analysis of Dynamic SDN Architectures Based on Game Theory
Authors: Qi Chao , Wu Jiangxing , Cheng Guozhen , Ai Jianjian , Zhao Shuo
Published: January 2018

Security evaluation of SDN architectures is of critical importance to develop robust systems and address attacks. Focused on a novel-proposed dynamic SDN framework, a game-theoretic model is presented to analyze its security performance. This model can represent several kinds of players’ information, simulate approximate attack scenarios, and quantitatively estimate systems’ reliability. And we explore several typical game instances defined by system’s capability, players’ objects, and strategies. Experimental results illustrate that the system’s detection capability is not a decisive element to security enhancement as introduction of dynamism and redundancy into SDN can significantly improve security gain and compensate for its detection weakness. Moreover, we observe a range of common strategic actions across environmental conditions. And analysis reveals diverse defense mechanisms adopted in dynamic systems have different effect on security improvement. Besides, the existence of equilibrium in particular situations further proves the novel structure’s feasibility, flexibility, and its persistent ability against long-term attacks.
Classifying Imbalanced Data Sets by a Novel RE-Sample and Cost-Sensitive Stacked Generalization Method
Authors: Yan Jianhong , Han Suqing
Published: January 2018

Learning with imbalanced data sets is considered as one of the key topics in machine learning community. Stacking ensemble is an efficient algorithm for normal balance data sets. However, stacking ensemble was seldom applied in imbalance data. In this paper, we proposed a novel RE-sample and Cost-Sensitive Stacked Generalization (RECSG) method based on 2-layer learning models. The first step is Level 0 model generalization including data preprocessing and base model training. The second step is Level 1 model generalization involving cost-sensitive classifier and logistic regression algorithm. In the learning phase, preprocessing techniques can be embedded in imbalance data learning methods. In the cost-sensitive algorithm, cost matrix is combined with both data characters and algorithms. In the RECSG method, ensemble algorithm is combined with imbalance data techniques. According to the experiment results obtained with 17 public imbalanced data sets, as indicated by various evaluation metrics (AUC, GeoMean, and AGeoMean), the proposed method showed the better classification performances than other ensemble and single algorithms. The proposed method is especially more efficient when the performance of base classifier is low. All these demonstrated that the proposed method could be applied in the class imbalance problem.
Indian Classical Dance Action Identification and Classification with Convolutional Neural Networks
Authors: Kishore P. V. V. , Kumar K. V. V. , Kiran Kumar E. , Sastry A. S. C. S. , Teja Kiran M. , Anil Kumar D. , Prasad M. V. D.
Published: January 2018

Extracting and recognizing complex human movements from unconstrained online/offline video sequence is a challenging task in computer vision. This paper proposes the classification of Indian classical dance actions using a powerful artificial intelligence tool: convolutional neural networks (CNN). In this work, human action recognition on Indian classical dance videos is performed on recordings from both offline (controlled recording) and online (live performances, YouTube) data. The offline data is created with ten different subjects performing 200 familiar dance mudras/poses from different Indian classical dance forms under various background environments. The online dance data is collected from YouTube for ten different subjects. Each dance pose is occupied for 60 frames or images in a video in both the cases. CNN training is performed with 8 different sample sizes, each consisting of multiple sets of subjects. The remaining 2 samples are used for testing the trained CNN. Different CNN architectures were designed and tested with our data to obtain a better accuracy in recognition. We achieved a 93.33% recognition rate compared to other classifier models reported on the same dataset.
Influence of Altitude on the Spatiotemporal Variations of Meteorological Droughts in Mountain Regions of the Free State Province, South Africa (1960–2013)
Authors: Mbiriri M. , Mukwada G. , Manatsa D.
Published: January 2018

The Standardized Precipitation Index (SPI) was computed for October to December (OND) and January to March (JFM) summer subseasons for Free State Province, South Africa, to assess the influence of altitude on drought severity and frequency. The observed spatiotemporal heterogeneity in the SPI variability revealed that factors governing drought interannual variability varied markedly within the region for the two subseasons. Strong correlations between r=0.76 and 0.93 across the clusters in both subseasons were observed. Significant shift in average SPI, towards the high during the OND subseason, was detected for the far western low-lying and central regions of the province around the 1990s. An ANOVA test revealed a significant relationship between drought severity and altitude during the OND subseason only. The impact of altitude is partly manifested in the strong relationship between meridional winds and SPI extremes. When the winds are largely northerly, Free State lies predominantly in the windward side of the Drakensberg Mountains but lies in the rain shadow when the winds are mostly southerly. The relationship between ENSO and SPI indicates stronger correlations for the early summer subseason than for the late summer subseason while overall presenting a diminishing intensity with height over the province.
A Toxicological Evaluation of a Standardized Hydrogenated Extract of Curcumin (CuroWhite™)
Authors: Ravikumar Alastimmanahalli Narasimhiah , Jacob Joby , Gopi Sreeraj , Jagannath Tumkur Subbarao
Published: January 2018

A series of toxicological investigations were conducted in order to evaluate the genotoxic potential and repeated-dose oral toxicity of CuroWhite, a proprietary extract of curcumin that has been hydrogenated and standardized to not less than 25% hydrogenated curcuminoid content. All tests were conducted in general accordance with internationally accepted standards. The test item was not mutagenic in the bacterial reverse mutation test or in vitro mammalian chromosomal aberration test, and no in vivo genotoxic activity was observed in rat bone marrow in the micronucleus test. A 90-day repeated-dose study was conducted in male and female Sprague-Dawley rats. Two mortalities occurred in the main and satellite high-dose groups and were determined due to gavage error. No organ specific or other toxic effects of the test item were observed up to the maximum dose of 800 mg/kg bw/day, administered by gavage. NOAEL was, therefore, estimated as 800 mg/kg bw/day.
A Study of Mechanical Property of Artificial Frozen Clay under Dynamic Load
Authors: Li Dongwei , Fan Juhong
Published: January 2018

To determine the mechanical properties of artificial frozen clay under dynamic load, 81 triaxial shear tests were carried out for artificial frozen clay at different temperatures, amplitudes, frequencies, and precompressions and three kinds of testing conditions. The change laws of the dynamic modulus of elasticity, maximum dynamic shear modulus, dynamic damping ratio, and strain rate were determined. These results can guide future research on the mechanical mechanisms of frozen soil, providing both theoretical and practical significance.
Development and Evaluation of a Powered Artificial Gastrocnemius for Transtibial Amputee Gait
Authors: Eilenberg Michael F. , Kuan Jiun-Yih , Herr Hugh
Published: January 2018

Existing robotic transtibial prostheses provide only ankle joint actuation and do not restore biarticular function of the gastrocnemius muscle. This paper presents the first powered biarticular transtibial prosthesis, which is a combination of a commercial powered ankle-foot prosthesis and a motorized robotic knee orthosis. The orthosis is controlled to emulate the human gastrocnemius based on neuromuscular models of matched nonamputees. Together with the ankle-foot prosthesis, the devices provide biarticular actuation. We evaluate differences between this biarticular condition and a monoarticular condition with the orthosis behaving as a free-joint. Six participants with transtibial amputation walk with the prosthesis on a treadmill while motion, force, and metabolic data are collected and analyzed for differences between conditions. The biarticular prosthesis reduces affected-side biological knee flexion moment impulse and hip positive work during late-stance knee flexion, compared to the monoarticular condition. The data do not support our hypothesis that metabolism decreases for all participants, but some participants demonstrate large metabolic reductions with the biarticular condition. These preliminary results suggest that a powered artificial gastrocnemius may be capable of providing large metabolic reductions compared to a monoarticular prosthesis, but further study is warranted to determine an appropriate controller for achieving more consistent metabolic benefits.
Anisotropic Cosmological Models with Two Fluids
Authors: Mishra B. , Ray Pratik P. , Pacif S. K. J.
Published: January 2018

Anisotropic dark energy cosmological models have been constructed in a Bianchi V space-time, with the energy momentum tensor consisting of two noninteracting fluids, namely, bulk viscous fluid and dark energy fluid. Two different models are constructed based on the power law cosmology and de Sitter universe. The constructed model was also embedded with different pressure gradients along different spatial directions. The variable equation of state (EoS) parameter and skewness parameters for both models are obtained and analysed. The physical properties of the models obtained with the use of scale factors of power law and de Sitter law are also presented.
Severe Drug-Induced Agranulocytosis Successfully Treated with Recombinant Human Granulocyte Colony-Stimulating Factor
Authors: Kubota Yohei , Ezekiel Wong Toh Yoon
Published: January 2018

When elderly patients are prescribed many different medications, the risk for developing serious adverse events should be kept in mind. One of these adverse events is agranulocytosis, which, although rare, can be life-threatening if left untreated. The majority of agranulocytosis cases are caused by drugs, including antibiotics. Here, we report a case of severe agranulocytosis in a 96-year-old woman following antibiotic therapy which was successfully managed using recombinant human granulocyte colony-stimulating factor (rhG-CSF) and the appropriate choice of antibiotics to treat her concomitant infection.
Ellis-van Creveld Syndrome: A Rare Clinical Report of Oral Rehabilitation by Interdisciplinary Approach
Authors: Naqash Talib Amin , Alshahrani Ibrahim , Simasetha Siripan
Published: January 2018

Ellis-van Creveld syndrome (EVC) is a very rare genetic disorder that affects various tissues of ectodermal and mesodermal origin; patients with EVC present with typical oral deficiencies. The affected individuals are quite young at the time of oral evaluation. It is, therefore, important that these individuals are diagnosed and receive dental treatment at an early age for their physiologic and psychosocial well-being. Albeit there are numerous articles penned on the EVC, the treatise from an oral perspective is inadequate, covering only oral exhibitions and the preventive treatments. This article reviews the literature and serves as the first disquisition for oral rehabilitation of an EVC patient utilizing surgical, orthodontic, restorative, and prosthodontic management.
Observer Design for Delayed Markovian Jump Systems with Output State Saturation
Authors: Wang Guoliang , Feng Bo
Published: January 2018

This paper considers the observer design problem of continuous-time delayed Markovian jump systems with output state saturation. Different from the traditionally observer-based saturation control methods, a kind of system output state saturation with a partially delay-dependent property is proposed, where both nondelay and delay states exist at the same time but happen asynchronously. By exploiting the Bernoulli variable, the probability distributions of such two states are described and considered in the observer design. Based on an improved equality applied to deal with saturation terms, sufficient conditions for the designed observer with three kinds of output saturations are all provided with LMI forms. Finally, a numerical example is given to indicate the effectiveness of the obtained results.
Low IL-6, IL-10, and TNF-αand High IL-13 Cytokine Levels Are Associated with Severe Hepatic Fibrosis inSchistosoma mansoniChronically Exposed Individuals
Authors: Mutengo Mable M. , Mduluza Takafira , Kelly Paul , Mwansa James C. L. , Kwenda Geoffrey , Musonda Patrick , Chipeta James
Published: January 2018

Several studies have attributed the etiopathogenesis of chronicSchistosoma mansonirelated hepatic fibrosis to unregulated immune responses against trapped parasite ova in the host. However, there is limited data on immune profiles associated with varying degrees of the disease in a population under chronic exposure to the parasite. We therefore investigated the role of selected T-helper (Th)1, Th2, and Th17 cytokines in relation to hepatic fibrosis severity among individuals resident in a hyper-Schistosoma mansoniendemic region of Western Zambia. Two hundred and forty-fourS. mansoniinfected individuals with and without fibrosis were analysed for cytokine profiles. Based on hepatic fibrosis stage as determined by ultrasound, participants were categorized into Group 0, Group I, Group II, and Group III. Cytokines were measured inS. mansoniegg stimulated whole blood culture supernatants using the BD Cytometric Bead Array kits. Compared to the nonfibrotic group, participants in the severe hepatic fibrotic group produced less interleukin- (IL-) 6, IL-10, and tumour necrosis factor-alpha (TNF-α). On the other hand, IL-13 was significantly elevated in this group compared to the nonfibrotic group (p<0.001). Our results suggest that low IL-6, IL-10, and TNF-αand high IL-13 levels may influenceS. mansonidisease progression.
A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification
Authors: Gursel Ozmen Nurhan , Gumusel Levent , Yang Yuan
Published: January 2018

Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-computer interfaces (BCI). We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on different mental tasks using single-channel EEG. This biologically inspired method extracts the most discriminative spectral features from power spectral densities (PSDs) of the EEG signals. We applied our method on a dataset of six subjects who performed five different imagination tasks: (i) resting state, (ii) mental arithmetic, (iii) imagination of left hand movement, (iv) imagination of right hand movement, and (v) imagination of letter “A.” Pairwise and multiclass classifications were performed in single EEG channel using Linear Discriminant Analysis and Support Vector Machines. Our method produced results (mean classification accuracy of 83.06% for binary classification and 91.85% for multiclassification) that are on par with the state-of-the-art methods, using single-channel EEG with low computational cost. Among all task pairs, mental arithmetic versus letter imagination yielded the best result (mean classification accuracy of 90.29%), indicating that this task pair could be the most suitable pair for a binary class BCI. This study contributes to the development of single-channel BCI, as well as finding the best task pair for user defined applications.
Tumor–Stroma IL1β-IRAK4 Feedforward Circuitry Drives Tumor Fibrosis, Chemoresistance, and Poor Prognosis in Pancreatic Cancer
Authors: Zhang Daoxiang , Li Lin , Jiang Hongmei , Li Qiong , Wang-Gillam Andrea , Yu Jinsheng , Head Richard , Liu Jingxia , Ruzinova Marianna B. , Lim Kian-Huat
Published: January 2018

Targeting the desmoplastic stroma of pancreatic ductal adenocarcinoma (PDAC) holds promise to augment the effect of chemotherapy, but success in the clinic has thus far been limited. Preclinical mouse models suggest that near-depletion of cancer-associated fibroblasts (CAF) carries a risk of accelerating PDAC progression, underscoring the need to concurrently target key signaling mechanisms that drive the malignant attributes of both CAF and PDAC cells. We previously reported that inhibition of IL1 receptor–associated kinase 4 (IRAK4) suppresses NFκB activity and promotes response to chemotherapy in PDAC cells. In this study, we report that CAF in PDAC tumors robustly express activated IRAK4 and NFκB. IRAK4 expression in CAF promoted NFκB activity, drove tumor fibrosis, and supported PDAC cell proliferation, survival, and chemoresistance. Cytokine array analysis of CAF and microarray analysis of PDAC cells identified IL1β as a key cytokine that activated IRAK4 in CAF. Targeting IRAK4 or IL1β rendered PDAC tumors less fibrotic and more sensitive to gemcitabine. In clinical specimens of human PDAC, high stromal IL1β expression associated strongly with poor overall survival. Together, our studies establish a tumor–stroma IL1β-IRAK4 feedforward signal that can be therapeutically disrupted to increase chemotherapeutic efficacy in PDAC.

Significance: Targeting the IL1β-IRAK4 signaling pathway potentiates the effect of chemotherapy in pancreatic cancer. Cancer Res; 78(7); 1700–12. ©2018 AACR.
Myeloma Cells Are Activated in Bone Marrow Microenvironment by the CD180/MD-1 Complex, Which Senses Lipopolysaccharide
Authors: Kikuchi Jiro , Kuroda Yoshiaki , Koyama Daisuke , Osada Naoki , Izumi Tohru , Yasui Hiroshi , Kawase Takakazu , Ichinohe Tatsuo , Furukawa Yusuke
Published: January 2018

Multiple myeloma (MM) cells acquire dormancy and drug resistance via interaction with bone marrow stroma cells (BMSC) in a hypoxic microenvironment. Elucidating the mechanisms underlying the regrowth of dormant clones may contribute to further improvement of the prognosis of MM patients. In this study, we find that the CD180/MD-1 complex, a noncanonical lipopolysaccharide (LPS) receptor, is expressed on MM cells but not on normal counterparts, and its abundance is markedly upregulated under adherent and hypoxic conditions. Bacterial LPS and anti-CD180 antibody, but not other Toll-like receptor ligands, enhanced the growth of MM cells via activation of MAP kinases ERK and JNK in positive correlation with expression levels of CD180. Administration of LPS significantly increased the number of CD180/CD138 double-positive cells in a murine xenograft model when MM cells were inoculated with direct attachment to BMSC. Knockdown of CD180 canceled the LPS response in vitro and in vivo. Promoter analyses identified IKZF1 (Ikaros) as a pivotal transcriptional activator of the CD180 gene. Both cell adhesion and hypoxia activated transcription of the CD180 gene by increasing Ikaros expression and its binding to the promoter region. Pharmacological targeting of Ikaros by the immunomodulatory drug lenalidomide ameliorated the response of MM cells to LPS in a CD180-dependent manner in vitro and in vivo. Thus, the CD180/MD-1 pathway may represent a novel mechanism of growth regulation of MM cells in a BM milieu and may be a therapeutic target of preventing the regrowth of dormant MM cells.

Significance: This study describes a novel mechanism by which myeloma cells are regulated in the bone marrow, where drug resistance and dormancy can evolve after treatment, with potential therapeutic implications for treating this often untreatable blood cancer. Cancer Res; 78(7); 1766–78. ©2018 AACR.
Nitric Oxide Production by Myeloid-Derived Suppressor Cells Plays a Role in Impairing Fc Receptor–Mediated Natural Killer Cell Function
Authors: Stiff Andrew , Trikha Prashant , Mundy-Bosse Bethany , McMichael Elizabeth , Mace Thomas A. , Benner Brooke , Kendra Kari , Campbell Amanda , Gautam Shalini , Abood David , Landi Ian , Hsu Vincent , Duggan Megan , Wesolowski Robert , Old Matthew , Howard John Harrison , Yu Lianbo , Stasik Nancy , Olencki Thomas , Muthusamy Natarajan , Tridandapani Susheela , Byrd John C. , Caligiuri Michael , Carson William E.
Published: January 2018

Purpose: mAbs are used to treat solid and hematologic malignancies and work in part through Fc receptors (FcRs) on natural killer cells (NK). However, FcR-mediated functions of NK cells from patients with cancer are significantly impaired. Identifying the mechanisms of this dysfunction and impaired response to mAb therapy could lead to combination therapies and enhance mAb therapy.

Experimental Design: Cocultures of autologous NK cells and MDSC from patients with cancer were used to study the effect of myeloid-derived suppressor cells (MDSCs) on NK-cell FcR-mediated functions including antibody-dependent cellular cytotoxicity, cytokine production, and signal transduction in vitro. Mouse breast cancer models were utilized to study the effect of MDSCs on antibody therapy in vivo and test the efficacy of combination therapies including a mAb and an MDSC-targeting agent.

Results: MDSCs from patients with cancer were found to significantly inhibit NK-cell FcR-mediated functions including antibody-dependent cellular cytotoxicity, cytokine production, and signal transduction in a contact-independent manner. In addition, adoptive transfer of MDSCs abolished the efficacy of mAb therapy in a mouse model of pancreatic cancer. Inhibition of iNOS restored NK-cell functions and signal transduction. Finally, nonspecific elimination of MDSCs or inhibition of iNOS in vivo significantly improved the efficacy of mAb therapy in a mouse model of breast cancer.

Conclusions: MDSCs antagonize NK-cell FcR-mediated function and signal transduction leading to impaired response to mAb therapy in part through nitric oxide production. Thus, elimination of MDSCs or inhibition of nitric oxide production offers a strategy to improve mAb therapy. Clin Cancer Res; 24(8); 1891–904. ©2018 AACR.
The Expanding World of N-MYC–Driven Tumors
Authors: Rickman David S. , Schulte Johannes H. , Eilers Martin
Published: January 2018

Enhanced and deregulated expression of N-MYC, a member of the MYC family of transcription factors, drives the development of multiple tumors, including tumors of the nervous and hematologic systems and neuroendocrine tumors in other organs. This review summarizes the cell-of-origin, biological features, associated signaling pathways, and current treatment strategies for N-MYC–driven tumors. We also highlight biological differences within specific tumor types that are driven by the different MYC proteins.

Significance: N-MYC is a driver of multiple tumor types that are derived through a mechanism that involves direct differentiation within the same lineage (e.g., in the case of neuroblastoma, medulloblastoma, and acute myeloid leukemia) and is often associated with a poor prognosis. Emerging data suggest that N-MYC also drives other tumor types through a mechanism that promotes a lineage switch and that this switch may be exploited for therapeutic purposes. Cancer Discov; 8(2); 150–63. ©2018 AACR.
Combination Gemcitabine and WT1 Peptide Vaccination Improves Progression-Free Survival in Advanced Pancreatic Ductal Adenocarcinoma: A Phase II Randomized Study
Authors: Nishida Sumiyuki , Ishikawa Takeshi , Egawa Shinichi , Koido Shigeo , Yanagimoto Hiroaki , Ishii Jun , Kanno Yoshihide , Kokura Satoshi , Yasuda Hiroaki , Oba Mari Saito , Sato Maho , Morimoto Soyoko , Fujiki Fumihiro , Eguchi Hidetoshi , Nagano Hiroaki , Kumanogoh Atsushi , Unno Michiaki , Kon Masanori , Shimada Hideaki , Ito Kei , Homma Sadamu , Oka Yoshihiro , Morita Satoshi , Sugiyama Haruo
Published: January 2018

We investigated the efficacy of a Wilms' tumor gene 1 (WT1) vaccine combined with gemcitabine (GEMWT1) and compared it with gemcitabine (GEM) monotherapy for advanced pancreatic ductal adenocarcinoma (PDAC) in a randomized phase II study. We randomly assigned HLA-A*02:01– or HLA-A*24:02–positive patients with advanced PDAC to receive GEMWT1 or GEM. We assessed WT1-specific immune responses via delayed-type hypersensitivity (DTH) to the WT1 peptide and a tetramer assay to detect WT1-specific cytotoxic T lymphocytes (WT1-CTL). Of 91 patients enrolled, 85 were evaluable (GEMWT1: n = 42; GEM: n = 43). GEMWT1 prolonged progression-free survival [PFS; hazard ratio (HR), 0.66; P = 0.084] and improved overall survival rate at 1 year (1-year OS%; GEMWT1: 35.7%; GEM: 20.9%). However, the difference in OS was not significant (HR: 0.82; P = 0.363). These effects were particularly evident in metastatic PDAC (PFS: HR 0.51, P = 0.0017; 1-year OS%: GEMWT1 27.3%; GEM 11.8%). The combination was well tolerated, with no unexpected serious adverse events. In patients with metastatic PDAC, PFS in the DTH-positive GEMWT1 group was significantly prolonged, with a better HR of 0.27 compared with the GEM group, whereas PFS in the DTH-negative GEMWT1 group was similar to that in the GEM group (HR 0.86; P = 0.001). DTH positivity was associated with an increase in WT1-CTLs induced by the WT1 vaccine. GEM plus the WT1 vaccine prolonged PFS and may improve 1-year OS% in advanced PDAC. These clinical effects were associated with the induction of WT1-specific immune responses. Cancer Immunol Res; 6(3); 320–31. ©2018 AACR.