bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Control of PEVs with a Charging Aggregator Considering Regulation Service Provisioning
Authors: Cui Tiansong , Chen Shuang , Wang Yanzhi , Nazarian Shahin , Pedram Massoud
Published: August 2017

Plug-in electric vehicles (PEVs) are considered the key to reducing fossil fuel consumption and an important part of the smart grid. The plug-in electric vehicle-to-grid (V2G) technology in the smart grid infrastructure enables energy flow from PEV batteries to the power grid so that the grid stability is enhanced and the peak power demand is shaped. PEV owners will also benefit from V2G technology, as they will be able to reduce energy cost through proper PEV charging and discharging scheduling. Moreover, power regulation service (RS) reserves have been playing an increasingly important role in modern power markets. It has been shown that by providing RS reserves, the power grid achieves a better match between energy supply and demand in presence of volatile and intermittent renewable energy generation. This article starts with the problem of PEV charging under dynamic energy pricing, properly taking into account the degradation of battery state-of-health (SoH) during V2G operations as well as RS provisioning. An overall optimization throughout the whole parking period is proposed for the PEV and an adaptive control framework is presented to dynamically update the optimal charging/discharging decision at each hour to mitigate the effect of RS tracking error.

As more and more PEVs are being plugged into the power grid, the control or management issue of PEV charging arises, since mass unregulated charging processes of PEVs may result in degradation of power quality and damage utility equipments and customer appliances. To solve this problem, this article also presents an SoH-aware charging aggregator design, which decides the control sequences of a group of PEVs. An energy storage system is used in the charging aggregator to do a peak power shaving, and future parking PEVs are properly taken care of. Experimental results show that the proposed optimal charging algorithm minimizes the combination of electricity cost and battery aging cost in the RS provisioning power market. Experimental results also show that the introduction of charging aggregator can significantly reduce the peak power consumption caused by simultaneous PEV charging.
The Economics of the Cloud
Authors: Anselmi Jonatha , Ardagna Danilo , Lui John C. S. , Wierman Adam , Xu Yunjian , Yang Zichao
Published: August 2017

This article proposes a model to study the interaction of price competition and congestion in the cloud computing marketplace. Specifically, we propose a three-tier market model that captures a marketplace with users purchasing services from Software-as-a-Service (SaaS) providers, which in turn purchase computing resources from either Provider-as-a-Service (PaaS) or Infrastructure-as-a-Service (IaaS) providers. Within each level, we define and characterize market equilibria. Further, we use these characterizations to understand the relative profitability of SaaSs and PaaSs/IaaSs and to understand the impact of price competition on the user experienced performance, that is, the “price of anarchy” of the cloud marketplace. Our results highlight that both of these depend fundamentally on the degree to which congestion results from shared or dedicated resources in the cloud.
Robust Spammer Detection in Microblogs
Authors: Fu Hao , Xie Xing , Rui Yong , Gong Neil Zhenqiang , Sun Guangzhong , Chen Enhong
Published: August 2017

Microblogging Web sites, such as Twitter and Sina Weibo, have become popular platforms for socializing and sharing information in recent years. Spammers have also discovered this new opportunity to unfairly overpower normal users with unsolicited content, namely social spams. Although it is intuitive for everyone to follow legitimate users, recent studies show that both legitimate users and spammers follow spammers for different reasons. Evidence of users seeking spammers on purpose is also observed. We regard this behavior as useful information for spammer detection. In this article, we approach the problem of spammer detection by leveraging the “carefulness” of users, which indicates how careful a user is when she is about to follow a potential spammer. We propose a framework to measure the carefulness and develop a supervised learning algorithm to estimate it based on known spammers and legitimate users. We illustrate how the robustness of the detection algorithms can be improved with aid of the proposed measure. Evaluation on two real datasets from Sina Weibo and Twitter with millions of users are performed, as well as an online test on Sina Weibo. The results show that our approach indeed captures the carefulness, and it is effective for detecting spammers. In addition, we find that our measure is also beneficial for other applications, such as link prediction.
Fast and Flexible Top-
k
Similarity Search on Large Networks
Authors: Zhang Jing , Tang Jie , Ma Cong , Tong Hanghang , Jing Yu , Li Juanzi , Luyten Walter , Moens Marie-Francine
Published: August 2017

Similarity search is a fundamental problem in network analysis and can be applied in many applications, such as collaborator recommendation in coauthor networks, friend recommendation in social networks, and relation prediction in medical information networks. In this article, we propose a sampling-based method using random paths to estimate the similarities based on both common neighbors and structural contexts efficiently in very large homogeneous or heterogeneous information networks. We give a theoretical guarantee that the sampling size depends on the error-bound ε, the confidence level (1-δ), and the path length
T
of each random walk. We perform an extensive empirical study on a Tencent microblogging network of 1,000,000,000 edges. We show that our algorithm can return top-
k
similar vertices for any vertex in a network 300× faster than the state-of-the-art methods. We develop a prototype system of recommending similar authors to demonstrate the effectiveness of our method.
Algorithm 981
Authors: Rizzardi Mariarosaria
Published: August 2017

In order to solve a differential problem, the
Laplace Transform method
, when applicable, replaces the problem with a simpler one; the solution is obtained by solving the new problem and then by computing the inverse Laplace Transform of this function. In a numerical context, since the solution of the transformed problem consists of a sequence of Laplace Transform samples, most of the software for the numerical inversion cannot be used since the transform, among parameters, must be passed as a function.

To fill this gap, we present Talbot Suite DE, a C software collection for Laplace Transform inversions, specifically designed for these problems and based on
Talbot’s method
. It contains both sequential and parallel implementations; the latter is accomplished by means of OpenMP. We also report some performance results.

Aimed at non-expert users, the software is equipped with several examples and a User Guide that includes the external documentation, explains how to use all the sample code, and reports its results about accuracy and efficiency. Some examples are entirely in C and others combine different programming languages (C/MATLAB, C/FORTRAN). The User Guide also contains useful hints to avoid possible errors issued during the compilation or execution of mixed-language code.
Refined-Graph Regularization-Based Nonnegative Matrix Factorization
Authors: Li Xuelong , Cui Guosheng , Dong Yongsheng
Published: August 2017

Nonnegative matrix factorization (NMF) is one of the most popular data representation methods in the field of computer vision and pattern recognition. High-dimension data are usually assumed to be sampled from the submanifold embedded in the original high-dimension space. To preserve the locality geometric structure of the data,k-nearest neighbor (k-NN) graph is often constructed to encode the near-neighbor layout structure. However,k-NN graph is based on Euclidean distance, which is sensitive to noise and outliers. In this article, we propose a refined-graph regularized nonnegative matrix factorization by employing a manifold regularized least-squares regression (MRLSR) method to compute the refined graph. In particular, each sample is represented by the whole dataset regularized with ℓ2-norm and Laplacian regularizer. Then a MRLSR graph is constructed based on the representative coefficients of each sample. Moreover, we present two optimization schemes to generate refined-graphs by employing a hard-thresholding technique. We further propose two refined-graph regularized nonnegative matrix factorization methods and use them to perform image clustering. Experimental results on several image datasets reveal that they outperform 11 representative methods.
Facilitating Adoption of Internet Technologies and Services with Externalities via Cost Subsidization
Authors: Weber Steven
Published: August 2017

This article models the temporal adoption dynamics of an abstracted Internet technology or service, where the instantaneous net value of the service perceived by each (current or potential) user/customer incorporates three key features: (i) user service affinity heterogeneity, (ii) a network externality, and (iii) a subscription cost. Internet technologies and services with network externalities face a “chicken-and-egg” adoption problem in that the service
requires
an established customer base to
attract
new customers. In this article, we study cost subsidization as a means to “reach the knee,” at which point the externality drives rapid service adoption, and thereby change the equilibrium service fractional adoption level from an initial near-zero level to a final near-one level (full adoption). We present three simple subsidy models and evaluate them under two natural performance metrics: (i) the duration required for the subsidized service to reach a given target adoption level and (ii) the aggregate cost of the subsidy born by the service provide. First, we present a “two-target adoption subsidy” that subsidizes the cost to keep the fraction of users with positive net utility at a (constant) target level until the actual adoption target is reached. Second, we study a special case of the above where the target ensures all users have positive net utility, corresponding to a “quickest adoption” subsidy (QAS). Third, we introduce an approximation of QAS that only requires the service provider adjust the subsidy level a prescribed number of times. Fourth, we study equilibria and their stability under uniformly and normally distributed user service affinities, highlighting the unstable equilibrium in each case as the natural target adoption level for the provider. Finally, we provide a fictional case study to illustrate the application of the results in a (hopefully) realistic scenario, along with a brief discussion of the limitations of the model and analysis.
Animation of Fingerspelled Words and Number Signs of the Sinhala Sign Language
Authors: Punchimudiyanse Malinda , Meegama Ravinda Gayan Narendra
Published: August 2017

Sign language is the primary communication medium of the aurally handicapped community. Often, a sign gesture is mapped to a word or a phrase in a spoken language and named as a conversational sign. A fingerspelling sign is a special sign derived to show a single character that matches a character in the alphabet of a given language. This enables the deaf community to express words that do not have a conversational sign, such as a name, using a letter-by-letter technique. Sinhala Sign Language (SSL) uses a phonetic pronunciation mechanism to decode such words due to the presence of one or more modifiers after a consonant. Expressing numbers also have a similar notation, and it is broken down into parts before interpretation in sign gestures.

This article presents the variations implemented to make the 3D avatar-based interpreter system look similar to an actual fingerspelled SSL by a human interpreter. To accomplish the task, a phonetic English-based 3D avatar animation system is developed with Blender animation software. The conversion of Sinhala Unicode text to phonetic English and numbers written in digits to sign gestures is done with a Visual Basic.NET (VB.NET) application. The presented application has 61 SSL fingerspelling signs and 40 SSL number signs. It is capable of interpreting any word written using the modern Sinhala alphabet without conversational signs and interprets the numbers that go up to the billions. This is a helpful tool in teaching SSL fingerspelling and number signs of SSL to deaf children.
Sound Non-Statistical Clustering of Static Analysis Alarms
Authors: Lee Woosuk , Lee Wonchan , Kang Dongok , Heo Kihong , Oh Hakjoo , Yi Kwangkeun
Published: August 2017

We present a sound method for clustering alarms from static analyzers. Our method clusters alarms by discovering sound dependencies between them such that if the dominant alarms of a cluster turns out to be false, all the other alarms in the same cluster are guaranteed to be false. We have implemented our clustering algorithm on top of a realistic buffer-overflow analyzer and proved that our method reduces 45% of alarm reports. Our framework is applicable to any abstract interpretation-based static analysis and orthogonal to abstraction refinements and statistical ranking schemes.
Energy-Efficient Mobile Video Streaming
Authors: Zhang Wei , Fan Rui , Wen Yonggang , Liu Fang
Published: August 2017

Video streaming is one of the most widely used mobile applications today, and it also accounts for a large fraction of mobile battery usage. Much of the energy consumption is for wireless data transmission and is highly correlated to network bandwidth conditions. In periods of poor connectivity, up to 90% of mobile energy can be used for wireless data transfer. In this article, we study the problem of energy-efficient mobile video streaming. We make use of the observed correlation between bandwidth and user
location
, and also observe that a user’s location is
predictable
in many situations, such as when commuting to a known destination. Based on the user’s predicted locations and bandwidth conditions, we optimize wireless transmission times to achieve high quality video playback while minimizing energy use. We propose an optimal offline algorithm for this problem, which runs in
O
(
Tk
) time, where
T
is the duration of the video and
k
is the size of the video buffer. We also propose LAWS, a Location AWare Streaming algorithm. LAWS learns from historical location-aware bandwidth conditions and predicts future bandwidths along a planned route to make online wireless download decisions. We evaluate LAWS using real bandwidth traces, and show that LAWS closely approximates the performance of the optimal offline algorithm, achieving 90.6% of the optimal performance on average, and 97% in certain cases. LAWS also outperforms three popular strategies used in practice by, on average, 69%, 63%, and 38%, respectively. Lastly, we show that LAWS is able to deal with noisy data and can attain the stated performance after sampling bandwidth conditions only five times.
TTC
Authors: Springer Paul , Hammond Jeff R. , Bientinesi Paolo
Published: August 2017

We present Tensor Transpose Compiler (TTC), an open-source parallel compiler for multidimensional tensor transpositions. To generate high-performance C++ code, TTC explores a number of optimizations, including software prefetching, blocking, loop-reordering, and explicit vectorization. To evaluate the performance of multidimensional transpositions across a range of possible use-cases, we also release a benchmark covering arbitrary transpositions of up to six dimensions. Performance results show that the routines generated by TTC achieve close to peak memory bandwidth on both the Intel Haswell and the AMD Steamroller architectures and yield significant performance gains over modern compilers. By implementing a set of pruning heuristics, TTC allows users to limit the number of potential solutions; this option is especially useful when dealing with high-dimensional tensors, as the search space might become prohibitively large. Experiments indicate that when only 100 potential solutions are considered, the resulting performance is about 99% of that achieved with exhaustive search.
Scaling Reliably
Authors: Trinder Phil , Chechina Natalia , Papaspyrou Nikolaos , Sagonas Konstantinos , Thompson Simon , Adams Stephen , Aronis Stavros , Baker Robert , Bihari Eva , Boudeville Olivier , Cesarini Francesco , Stefano Maurizio Di , Eriksson Sverker , fördős Viktória , Ghaffari Amir , Giantsios Aggelos , Green Rickard , Hoch Csaba , Klaftenegger David , Li Huiqing , Lundin Kenneth , Mackenzie Kenneth , Roukounaki Katerina , Tsiouris Yiannis , Winblad Kjell
Published: August 2017

Distributed actor languages are an effective means of constructing scalable reliable systems, and the Erlang programming language has a well-established and influential model. While the Erlang model conceptually provides reliable scalability, it has some inherent scalability limits and these force developers to depart from the model at scale. This article establishes the scalability limits of Erlang systems and reports the work of the EU RELEASE project to improve the scalability and understandability of the Erlang reliable distributed actor model.

We systematically study the scalability limits of Erlang and then address the issues at the virtual machine, language, and tool levels. More specifically: (1) We have evolved the Erlang virtual machine so that it can work effectively in large-scale single-host multicore and NUMA architectures. We have made important changes and architectural improvements to the widely used Erlang/OTP release. (2) We have designed and implemented Scalable Distributed (SD) Erlang libraries to address language-level scalability issues and provided and validated a set of semantics for the new language constructs. (3) To make large Erlang systems easier to deploy, monitor, and debug, we have developed and made open source releases of five complementary tools, some specific to SD Erlang.

Throughout the article we use two case studies to investigate the capabilities of our new technologies and tools: a distributed hash table based Orbit calculation and Ant Colony Optimisation (ACO). Chaos Monkey experiments show that two versions of ACO survive random process failure and hence that SD Erlang preserves the Erlang reliability model. While we report measurements on a range of NUMA and cluster architectures, the key scalability experiments are conducted on the Athos cluster with 256 hosts (6,144 cores). Even for programs with no global recovery data to maintain, SD Erlang partitions the network to reduce network traffic and hence improves performance of the Orbit and ACO benchmarks above 80 hosts. ACO measurements show that maintaining global recovery data dramatically limits scalability; however, scalability is recovered by partitioning the recovery data. We exceed the established scalability limits of distributed Erlang, and do not reach the limits of SD Erlang for these benchmarks at this scale (256 hosts, 6,144 cores).
Investigating the Post-Training Persistence of Expert Interaction Techniques
Authors: Lafreniere Benjamin , Gutwin Carl , Cockburn Andy
Published: August 2017

Expert interaction techniques enable users to greatly improve their performance; however, to realize these advantages, the user must first acquire the skill necessary to use a technique, then choose to use it over competing novice techniques. This article investigates several factors that may influence whether use of an expert technique persists when the context of use changes. Two studies examine the effect of changing performance requirements, and find that a high performance requirement imposed in a training context can effectively push users to adopt an expert technique, and that use of the technique is maintained when the requirement is subsequently reduced or removed. In a final study, performance requirement, high-level task, and environment of use are changed—participants played a training game to learn the menu for a drawing application, which they then used to complete a series of drawings over the following week. Participants exhibited a somewhat surprising “all-or-nothing” effect, using the expert technique nearly exclusively or not at all, and maintaining this behavior over a range of qualitatively different tasks. This suggests that switching to an expert technique involves a global change by the user, rather than an incremental change as suggested by previous work.
Using Worker Self-Assessments for Competence-Based Pre-Selection in Crowdsourcing Microtasks
Authors: Gadiraju Ujwal , Fetahu Besnik , Kawase Ricardo , Siehndel Patrick , Dietze Stefan
Published: August 2017

Paid crowdsourcing platforms have evolved into remarkable marketplaces where requesters can tap into human intelligence to serve a multitude of purposes, and the workforce can benefit through monetary returns for investing their efforts. In this work, we focus on individual crowd worker competencies. By drawing from self-assessment theories in psychology, we show that crowd workers often lack awareness about their true level of competence. Due to this, although workers intend to maintain a high reputation, they tend to participate in tasks that are beyond their competence. We reveal the diversity of individual worker competencies, and make a case for competence-based pre-selection in crowdsourcing marketplaces. We show the implications of flawed self-assessments on real-world microtasks, and propose a novel worker pre-selection method that considers accuracy of worker self-assessments. We evaluated our method in a sentiment analysis task and observed an improvement in the accuracy by over 15%, when compared to traditional performance-based worker pre-selection. Similarly, our proposed method resulted in an improvement in accuracy of nearly 6% in an image validation task. Our results show that requesters in crowdsourcing platforms can benefit by considering worker self-assessments in addition to their performance for pre-selection.
Broadband to Mars
Authors: Mone Gregory
Published: August 2017

Scientists are demonstrating that lasers could be the future of space communication.
Why agile teams fail without UX research
Authors: Convertino Gregorio , Frishberg Nancy
Published: August 2017

Failures to involve end users or to collect comprehensive data representing user needs are described and solutions to avoid such failures are proposed.
Stretch activation properties of Drosophila and Lethocerus indirect flight muscle suggest similar calcium-dependent mechanisms
Authors: Glasheen Bernadette M. , Eldred Catherine C. , Sullivan Leah C. , Zhao Cuiping , Reedy Michael K. , Edwards Robert J. , Swank Douglas M.
Published: August 2017

Muscle stretch activation (SA) is critical for optimal cardiac and insect indirect flight muscle (IFM) power generation. The SA mechanism has been investigated for decades with many theories proposed, but none proven. One reason for the slow progress could be that multiple SA mechanisms may have evolved in multiple species or muscle types. Laboratories studying IFM SA in the same or different species have reported differing SA functional properties which would, if true, suggest divergent mechanisms. However, these conflicting results might be due to different experimental methodologies. Thus, we directly compared SA characteristics of IFMs from two SA model systems, Drosophila and Lethocerus, using two different fiber bathing solutions. Compared with Drosophila IFM, Lethocerus IFM isometric tension is 10- or 17-fold higher and SA tension was 5- or 10-fold higher, depending on the bathing solution. However, the rate of SA tension generation was 9-fold faster for Drosophila IFM. The inverse differences between rate and tension in the two species causes maximum power output to be similar, where Drosophila power is optimized in the bathing solution that favors faster muscle kinetics and Lethocerus in the solution that favors greater tension generation. We found that isometric tension and SA tension increased with calcium concentration for both species in both solutions, reaching a maximum plateau around pCa 5.0. Our results favor a similar mechanism for both species, perhaps involving a troponin complex that does not fully calcium activate the thin filament thus leaving room for further tension generation by SA.
miR-15b negatively correlates with lipid metabolism in mammary epithelial cells
Authors: Chu Meiqiang , Zhao Yong , Yu Shuai , Hao Yanan , Zhang Pengfei , Feng Yanni , Zhang Hongfu , Ma Dongxue , Liu Jing , Cheng Ming , Li Lan , Shen Wei , Cao Hongfang , Li Qiang , Min Lingjiang
Published: August 2017

Mammary epithelial cells are regulated by steroid hormones, growth factors, and even microRNAs. miR-15b has been found to regulate lipid metabolism in adipocytes; however, its effects on lipid metabolism in mammary epithelial cells, the cells of lipid synthesis and secretion, are as yet unknown. The main purpose of this investigation was to explore the effect of miR-15b on lipid metabolism in mammary epithelial cells, along with the underlying mechanisms. miR-15b was overexpressed or inhibited by miRNA mimics or inhibitors; subsequently, lipid formation in mammary epithelial cells, and proteins related to lipid metabolism, were investigated. Through overexpression or inhibition of miR-15b expression, the current investigation found that miR-15b downregulates lipid metabolism in mammary epithelial cells and is expressed differentially at various stages of mouse and goat mammary gland development. Inhibition of miR-15b expression increased lipid content in mammary epithelial cells through elevation of the lipid synthesis enzyme fatty acid synthetase (FASN), and overexpression of miR-15b reduced lipid content in mammary epithelial cells with decreasing levels of FASN. Moreover, the steroid hormones estradiol and progesterone decreased miR-15b expression with a subsequent increase in lipid formation in mammary epithelial cells. The expression of miR-15b was lower during lactation and negatively correlated with lipid synthesis proteins, which suggests that it may be involved in lipid synthesis and milk production. miR-15b might be a useful target for altering lipid production and milk yield.
Cyclical blood flow restriction resistance exercise: a potential parallel to remote ischemic preconditioning?
Authors: Sprick Justin D. , Rickards Caroline A.
Published: August 2017

Remote ischemic preconditioning (RIPC) is characterized by the cyclical application of limb blood flow restriction and reperfusion and has been shown to protect vital organs during a subsequent ischemic insult. Blood flow restriction exercise (BFRE) similarly combines bouts of blood flow restriction with low-intensity exercise and thus could potentially emulate the protection demonstrated by RIPC. One concern with BFRE, however, is the potential for an augmented rise in sympathetic outflow due to greater activation of the exercise pressor reflex. Because of the use of lower workloads, however, we hypothesized that BFRE would elicit an attenuated increase in sympathetic outflow [assessed via plasma norepinephrine (NE) and mean arterial pressure (MAP)] and middle cerebral artery velocity (MCAv) when compared with conventional exercise (CE). Fifteen subjects underwent two leg press exercise interventions: 1) BFRE-220 mmHg bilateral thigh occlusion at 20% 1 rep-max (1RM), and 2) CE-65% 1RM without occlusion. Each condition consisted of 4 × 5-min cycles of exercise, with 3 × 10-reps in each cycle. Five minutes of rest and reperfusion (for BFRE) followed each cycle. MAP increased with exercise ( P < 0.001) and was 4–5 mmHg higher with CE versus BFRE ( P ≤ 0.09). Mean MCAv also increased with exercise ( P < 0.001) and was higher with CE compared with BFRE during the first bout of exercise only ( P = 0.07). Plasma NE concentration increased with CE only ( P < 0.001) and was higher than BFRE throughout exercise ( P ≤ 0.02). The attenuated sympathetic response, combined with similar cerebrovascular responses, suggest that cyclical BFRE could be explored as an alternative to CE in the clinical setting.
Glomerular mesangial cell recruitment and function require the co-receptor neuropilin-1
Authors: Bartlett Christina S. , Scott Rizaldy P. , Carota Isabel Anna , Wnuk Monika L. , Kanwar Yashpal S. , Miner Jeffrey H. , Quaggin Susan E.
Published: August 2017

Proteinuria has been reported in cancer patients receiving agents that target the transmembrane receptor neuropilin-1 (Nrp1) suggesting potential adverse effects on glomerular function. Here we show that Nrp1 is highly expressed by mesangial cells and that genetic deletion of the Nrp1 gene from PDGF receptor-β+mesangial cells results in proteinuric disease and glomerulosclerosis, leading to renal failure and death within 6 wk of age in mice. The major defect is a failure of mesangial cell migration that is required to establish the mature glomerular tuft. In vitro data show that the potent chemotactic effect of PDGFB is lost in Nrp1-deficient mesangial cells. Biochemical analyses reveal that Nrp1 is required for PDGFB-dependent phosphorylation of p130 Crk-associated substrate (p130Cas), a large-scaffold molecule that is involved in motility of other cell types. In stark contrast, matrix adhesion and activation of ERK and Akt, which mediate proliferation of mesangial cells in response to PDGFB, are unaffected by the absence of Nrp1. Taken together, these results identify a critical cell-autonomous role for Nrp1 in the migratory behavior of mesangial cells and may help explain the renal effects that occur in patients receiving Nrp1-inhibitory drugs.
The divisive normalization model of V1 neurons: a comprehensive comparison of physiological data and model predictions
Authors: Sawada Tadamasa , Petrov Alexander A.
Published: August 2017

The physiological responses of simple and complex cells in the primary visual cortex (V1) have been studied extensively and modeled at different levels. At the functional level, the divisive normalization model (DNM; Heeger DJ. Vis Neurosci 9: 181–197, 1992) has accounted for a wide range of single-cell recordings in terms of a combination of linear filtering, nonlinear rectification, and divisive normalization. We propose standardizing the formulation of the DNM and implementing it in software that takes static grayscale images as inputs and produces firing rate responses as outputs. We also review a comprehensive suite of 30 empirical phenomena and report a series of simulation experiments that qualitatively replicate dozens of key experiments with a standard parameter set consistent with physiological measurements. This systematic approach identifies novel falsifiable predictions of the DNM. We show how the model simultaneously satisfies the conflicting desiderata of flexibility and falsifiability. Our key idea is that, while adjustable parameters are needed to accommodate the diversity across neurons, they must be fixed for a given individual neuron. This requirement introduces falsifiable constraints when this single neuron is probed with multiple stimuli. We also present mathematical analyses and simulation experiments that explicate some of these constraints.
A Quasi‐Monte‐Carlo‐Based Feasible Sequential System of Linear Equations Method for Stochastic Programs with Recourse
Authors: Zhou Changyin , Su Rui , Jiang Zhihui
Published: August 2017

A two‐stage stochastic quadratic programming problem with inequality constraints is considered. By quasi‐Monte‐Carlo‐based approximations of the objective function and its first derivative, a feasible sequential system of linear equations method is proposed. A new technique to update the active constraint set is suggested. We show that the sequence generated by the proposed algorithm converges globally to a Karush‐Kuhn‐Tucker (KKT) point of the problem. In particular, the convergence rate is locally superlinear under some additional conditions.
Modeling the Variation in the Trajectory of Crosswalk Overflow Violation Pedestrians in China and Countermeasure
Authors: Cao Ning-Bo , Qu Zhao-Wei , Song Xian-Min , Zhao Li-Ying , Bai Qiao-Wen , Luo Rui-Qi
Published: August 2017

The phenomenon that pedestrians walk outside the crosswalk during green and flashing green is defined as overflow violation, and it is an illegal but common phenomenon in China. Few safety countermeasures can be applied to restrict it. At signalized intersections, one safety issue is the conflicts between turning vehicles and pedestrians. Large variations in overflow pedestrian trajectories lead to widely distributed conflict points. This paper puts forward a model to estimate spatial variations of overflow pedestrian trajectories. By video tracking, only trajectories of overflow violation pedestrians are collected. After analysis, crosswalk geometry, destination, previous passing position, and densities are determined as significant factors of trajectories variations. To simplify modeling process of trajectories variations, this paper assumes that individual trajectory is roughly represented by three feature points on the trajectory. Three feature points are defined as three crossing positions at three cross‐sections. Furthermore, Weibull distribution is applied to estimate the spatial distribution of violation pedestrian crossing positions at three cross‐sections; then, the spatial distributions of overflow violation pedestrians’ trajectories are gained by connecting crossing positions at three cross‐sections. Finally, the validation result suggests that the established models are capable of explaining well the spatial maneuver of overflow violation pedestrians’ trajectories variations.
Semantic Labeling of User Location Context Based on Phone Usage Features
Authors: Leppäkoski Helena , Rivero-Rodriguez Alejandro , Rautalin Sakari , Muñoz Martínez David , Käppi Jani , Ali-Löytty Simo , Piché Robert
Published: August 2017

In mobile phones, the awareness of the user’s context allows services better tailored to the user’s needs. We propose a machine learning based method for semantic labeling that utilizes phone usage features to detect the user’s home, work, and other visited places. For place detection, we compare seven different classification methods. We organize the phone usage data based on periods of uninterrupted time that the user has been in a certain place. We consider three approaches to represent this data: visits, places, and cumulative samples. Our main contribution is semantic place labeling using a small set of privacy-preserving features and novel data representations suitable for resource constrained mobile devices. The contributions include (1) introduction of novel data representations including accumulation and averaging of the usage, (2) analysis of the effect of the data accumulation time on the accuracy of the place classification, (3) analysis of the confidence on the classification outcome, and (4) identification of the most relevant features obtained through feature selection methods. With a small set of privacy-preserving features and our data representations, we detect the user’s home and work with probability of 90% or better, and in 3-class problem the overall classification accuracy was 89% or better.
Interactions of Desmethoxyyangonin, a Secondary Metabolite from Renealmia alpinia, with Human Monoamine Oxidase‐A and Oxidase‐B
Authors: Chaurasiya Narayan D. , León Francisco , Ding Yuanqing , Gómez-Betancur Isabel , Benjumea Dora , Walker Larry A. , Cutler Stephen J. , Tekwani Babu L.
Published: August 2017

Renealmia alpinia (Zingiberaceae), a medicinal plant of tropical rainforests, is used to treat snakebites and other injuries and also as a febrifuge, analgesic, antiemetic, antiulcer, and anticonvulsant. The dichloromethane extract of R. alpinia leaves showed potent inhibition of human monoamine oxidases‐ (MAOs‐) A and B. Phytochemical studies yielded six known compounds, including pinostrobin 1, 4′‐methyl ether sakuranetin 2, sakuranetin 3, pinostrobin chalcone 4, yashabushidiol A 5, and desmethoxyyangonin 6. Compound 6 displayed about 30‐fold higher affinity for MAO‐B than MAO‐A, with Ki values of 31 and 922 nM, respectively. Kinetic analysis of inhibition and equilibrium‐dialysis dissociation assay of the enzyme‐inhibitor complex showed reversible binding of desmethoxyyangonin 6 with MAO‐A and MAO‐B. The binding interactions of compound 6 in the active site of the MAO‐A and MAO‐B isoenzymes, investigated through molecular modeling algorithms, confirmed preferential binding of desmethoxyyangonin 6 with MAO‐B compared to MAO‐A. Selective reversible inhibitors of MAO‐B, like desmethoxyyangonin 6, may have important therapeutic significance for the treatment of neurodegenerative disorders, such as Parkinson’s disease and Alzheimer’s disease.
Operator Inequalities of Morrey Spaces Associated with Karamata Regular Variation
Authors: Wang Jiajia , Fu Zunwei , Shi Shaoguang , Mi Ling
Published: August 2017

Karamata regular variation is a basic tool in stochastic process and the boundary blow-up problems for partial differential equations (PDEs). Morrey space is closely related to study of the regularity of solutions to elliptic PDEs. The aim of this paper is trying to bring together these two areas and this paper is intended as an attempt at motivating some further research on these areas. A version of Morrey space associated with Karamata regular variation is introduced. As application, some estimates of operators, especially one-sided operators, on these spaces are considered.
Compound Danshen Dripping Pill for Treating Nonproliferative Diabetic Retinopathy: A Meta‐Analysis of 13 Randomized Controlled Trials
Authors: Huang Wenjing , Bao Qi , Jin De , Lian Fengmei
Published: August 2017

Objective. We assess the clinical effect of compound Danshen dripping pill (CDDP) for treating diabetic retinopathy (DR). Methods. Electronic databases were searched from January 2001 to October 2016 to locate randomized controlled trials (RCTs). Efficacy was measured as main outcome and microaneurysms, hemorrhage, exudate, vision, and fundus fluorescein angiography (FFA) were measured as second outcomes. Methodological quality for each study was evaluated, RevMan 5 software was used to assess treatment effects, and GRADE was used to rate quality of evidence. Results. We located 13 RCTs and methodological quality was evaluated as high risk. Statistics indicated CDDP for treating DR was better than controls and DR risk was reduced 64% with CDDP (RR: 0.36, P = 0.68); retinal microaneurysms (MD = −4.32NO, P < 0.00001); retinal hemorrhages (MD = −0.70PD, P = 0.03); exudate improvements (MD = −0.09PD, P = 0.79); visual changes (MD = −0.12 letter, P = 0.006); FFA (RR: 0.40, P = 0.003). About GRADE, quality of evidence was “low.” Conclusion. CDDP may be safe and efficacious for treating or delaying DR and may improve vision or delay vision loss.
Research into the Effect of Supercapacitor Terminal Voltage on Regenerative Suspension Energy-Regeneration and Dynamic Performance
Authors: Wang Ruochen , Ding Yanshu , Ye Qing , Ding Renkai , Qian Jingang
Published: August 2017

To study the effect of supercapacitor initial terminal voltage on the regenerative and semiactive suspension energy-regeneration and dynamic performance, firstly, the relationship between supercapacitor terminal voltage and linear motor electromagnetic damping force and that between supercapacitor terminal voltage and recycled energy by the supercapacitor in one single switching period were both analyzed. The result shows that the linear motor electromagnetic damping force is irrelevant to the supercapacitor terminal voltage, and the recycled energy by the supercapacitor reaches the maximum when initial terminal voltage of the supercapacitor equals output terminal voltage of the linear motor. Then, performances of system dynamics and energy-regeneration were studied as the supercapacitor initial terminal voltage varied in situations of B level and C level road. The result showed that recycled energy by the supercapacitor increased at first and then decreased while the dynamic performance had no obvious change. On the basis of previous study, a mode-switching control strategy of supercapacitor for the regenerative and semiactive suspension system was proposed, and the mode-switching rule was built. According to simulation and experiment results, the system energy-regeneration efficiency can be increased by utilizing the control strategy without influencing suspension dynamic performance, which is highly valuable to practical engineering.
Febuxostat Modulates MAPK/NF‐κBp65/TNF‐α Signaling in Cardiac Ischemia‐Reperfusion Injury
Authors: Khan Sana Irfan , Malhotra Rajiv Kumar , Rani Neha , Sahu Anil Kumar , Tomar Ameesha , Garg Shanky , Nag Tapas Chandra , Ray Ruma , Ojha Shreesh , Arya Dharamvir Singh , Bhatia Jagriti
Published: August 2017

Xanthine oxidase and xanthine dehydrogenase have been implicated in producing myocardial damage following reperfusion of an occluded coronary artery. We investigated and compared the effect of febuxostat and allopurinol in an experimental model of ischemia‐reperfusion (IR) injury with a focus on the signaling pathways involved. Male Wistar rats were orally administered vehicle (CMC) once daily (sham and IR + control), febuxostat (10 mg/kg/day; FEB10 + IR), or allopurinol (100 mg/kg/day; ALL100 + IR) for 14 days. On the 15th day, the IR‐control and treatment groups were subjected to one‐stage left anterior descending (LAD) coronary artery ligation for 45 minutes followed by a 60‐minute reperfusion. Febuxostat and allopurinol pretreatment significantly improved cardiac function and maintained morphological alterations. They also attenuated oxidative stress and apoptosis by suppressing the expression of proapoptotic proteins (Bax and caspase‐3), reducing TUNEL‐positive cells, and increasing the level of antiapoptotic proteins (Bcl‐2). The MAPK‐based molecular mechanism revealed suppression of active JNK and p38 proteins concomitant with the rise in ERK1/ERK2, a prosurvival kinase. Additionally, a reduction in the level of inflammatory markers (TNF‐α, IL‐6, and NF‐κB) was also observed. The changes observed with febuxostat were remarkable in comparison with those observed with allopurinol. Febuxostat protects relatively better against IR injury than allopurinol by suppressing inflammation and apoptosis mediating the MAPK/NF‐κBp65/TNF‐α pathway.
The Characteristics of TCM Clinical Trials: A Systematic Review of ClinicalTrials.gov
Authors: Chen Junchao , Huang Jihan , Li Jordan V. , Lv Yinghua , He Yingchun , Zheng Qingshan
Published: August 2017

Objective. The aim of this review is to characterize current status of global TCM clinical trials registered in ClinicalTrials.gov. Methods. We examined all the trials registered within ClinicalTrials.gov up to 25 September 2015, focusing on study interventions to identify TCM‐related trials, and extracted 1,270 TCM trials from the data set. Results. Overall, 691 (54.4%) trials were acupuncture, and 454 (35.8%) trials were herbal medicines. Differences in TCM trial intervention types were also evident among the specific therapeutic areas. Among all trials, 55.7% that were small studies enrolled <100 subjects, and only 8.7% of completed studies had reported results of trials. As for the location, the United States was second to China in conducting the most TCM trials. Conclusion. This review is the first snapshot of the landscape of TCM clinical trials registered in ClinicalTrials.gov, providing the basis for treatment and prevention of diseases within TCM and offering useful information that will guide future research on TCM.
Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
Authors: Zhang Cheng
Published: August 2017

This study focuses on the aircraft recovery problem (ARP). In real-life operations, disruptions always cause schedule failures and make airlines suffer from great loss. Therefore, the main objective of the aircraft recovery problem is to minimize the total recovery cost and solve the problem within reasonable runtimes. An aircraft recovery model (ARM) is proposed herein to formulate the ARP and use feasible line of flights as the basic variables in the model. We define the feasible line of flights (LOFs) as a sequence of flights flown by an aircraft within one day. The number of LOFs exponentially grows with the number of flights. Hence, a two-stage heuristic is proposed to reduce the problem scale. The algorithm integrates a heuristic scoring procedure with an aggregated aircraft recovery model (AARM) to preselect LOFs. The approach is tested on five real-life test scenarios. The computational results show that the proposed model provides a good formulation of the problem and can be solved within reasonable runtimes with the proposed methodology. The two-stage heuristic significantly reduces the number of LOFs after each stage and finally reduces the number of variables and constraints in the aircraft recovery model.
B-cell Receptor Signaling Regulates Metabolism in Chronic Lymphocytic Leukemia
Authors: Vangapandu Hima V. , Havranek Ondrej , Ayres Mary L. , Kaipparettu Benny Abraham , Balakrishnan Kumudha , Wierda William G. , Keating Michael J. , Davis R. Eric , Stellrecht Christine M. , Gandhi Varsha
Published: August 2017

Peripheral blood chronic lymphocytic leukemia (CLL) cells are quiescent but have active transcription and translation processes, suggesting that these lymphocytes are metabolically active. Based on this premise, the metabolic phenotype of CLL lymphocytes was investigated by evaluating the two intracellular ATP-generating pathways. Metabolic flux was assessed by measuring glycolysis as extracellular acidification rate (ECAR) and mitochondrial oxidative phosphorylation as oxygen consumption rate (OCR) and then correlated with prognostic factors. Further, the impact of B-cell receptor signaling (BCR) on metabolism was determined by genetic ablation and pharmacological inhibitors. Compared with proliferative B-cell lines, metabolic fluxes of oxygen and lactate were low in CLL cells. ECAR was consistently low, but OCR varied considerably in human patient samples (n = 45). Higher OCR was associated with poor prognostic factors such as ZAP 70 positivity, unmutated IGHV, high β2M levels, and higher Rai stage. Consistent with the association of ZAP 70 and IGHV unmutated status with active BCR signaling, genetic ablation of BCR mitigated OCR in malignant B cells. Similarly, knocking out PI3Kδ, a critical component of the BCR pathway, decreased OCR and ECAR. In concert, PI3K pathway inhibitors dramatically reduced OCR and ECAR. In harmony with a decline in metabolic activity, the ribonucleotide pools in CLL cells were reduced with duvelisib treatment. Collectively, these data demonstrate that CLL metabolism, especially OCR, is linked to prognostic factors and is curbed by BCR and PI3K pathway inhibition.

Implications: This study identifies a relationship between oxidative phosphorylation in CLL and prognostic factors providing a rationale to therapeutically target these processes. Mol Cancer Res; 15(12); 1692–703. ©2017 AACR.