title: Mobile application testing matrix and challenges

text: The adoption of smart phones and the usages of mobile applications are increasing rapidly. Consequently, within limited time-range, mobile Internet usages have managed to take over the desktop usages particularly since the first smart phone-touched application released by iPhone in 2007. This paper is proposed to provide solution and answer the most demandable questions related to mobile application automated and manual testing limitations. Moreover, Mobile application testing requires agility and physically testing. Agile testing is to detect bugs through automated tools, whereas the compatibility testing is more to ensure that the apps operates on mobile OS (Operation Systems) as well as on the different real devices. Moreover, we have managed to answer automated or manual questions through two mobile application case studies MES (Mobile Exam System) and MLM (Mobile Lab Mate) by creating test scripts for both case studies and our experiment results have been discussed and evaluated on whether to adopt test on real devices or on emulators? In addition to this, we have introduced new mobile application testing matrix for the testers and some enterprises to obtain knowledge from.


title: X-ray: Automating Root-Cause Diagnosis of Performance Anomalies in Production Software

text: Troubleshooting the performance of production software is challenging. Most existing tools, such as profiling, tracing, and logging systems, reveal what events occurred during performance anomalies. However, users of such tools must infer why these events occurred; e.g., that their execution was due to a root cause such as a specific input request or configuration setting. Such inference often requires source code and detailed application knowledge that is beyond system administrators and end users. This paper introduces performance summarization, a technique for automatically diagnosing the root causes of performance problems. Performance summarization instruments binaries as applications execute. It first attributes performance costs to each basic block. It then uses dynamic information flow tracking to estimate the likelihood that a block was executed due to each potential root cause. Finally, it summarizes the overall cost of each potential root cause by summing the per-block cost multiplied by the cause-specific likelihood over all basic blocks. Performance summarization can also be performed differentially to explain performance differences between two similar activities. X-ray is a tool that implements performance summarization. Our results show that X-ray accurately diagnoses 17 performance issues in Apache, lighttpd, Postfix, and PostgreSQL, while adding 2.3% average runtime overhead.


title: An Improving Deception Detection Method in Computer-Mediated Communication

text: Online deception is disrupting our daily life, organizational process, and even national security. Existing deception detection approaches followed a traditional paradigm by using a set of cues as antecedents, and used a variety of data sets and common classification models to detect deception, which were demonstrated to be an accurate technique, but the previous results also showed the necessity to expand the deception feature set in order to improve the accuracy. In our study, we propose a novel feature selection method of the combination of CHI statistics and hypothesis testing, and achieve the accuracy level of 86% and F-measure of 0.84 by using the novel feature sets and SVM classification models, which exceeds the previous experiment results.


title: When learning about the real world is better done virtually : A study of substituting computer simulations for laboratory equipment

text: This paper examines the effects of substituting a computer simulation for real laboratory equipment in the second semester of a large-scale introductory physics course. The direct current circuit laboratory was modified to compare the effects of using computer simulations with the effects of using real light bulbs, meters, and wires. Two groups of students, those who used real equipment and those who used a computer simulation that explicitly modeled electron flow, were compared in terms of their mastery of physics concepts and skills with real equipment. Students who used the simulated equipment outperformed their counterparts both on a conceptual survey of the domain and in the coordinated tasks of assembling a real circuit and describing how it worked.


title: Progressive Gaussian filtering using explicit likelihoods

text: In this paper, we introduce a new sample-based Gaussian filter. In contrast to the popular Nonlinear Kalman Filters, e.g., the UKF, we do not rely on linearizing the measurement model. Instead, we take up the Gaussian progressive filtering approach introduced by the PGF 42 but explicitly rely on likelihood functions. Progression means, we incorporate the information of a new measurement gradually into the state estimate. The advantages of this filtering method are on the one hand the avoidance of sample degeneration and on the other hand an adaptive determination of the number of likelihood evaluations required for each measurement update. By this means, less informative measurements can be processed quickly, whereas measurements containing much information automatically receive more emphasis by the filter. These properties allow the new filter to cope with the demanding problem of very narrow likelihood functions in an efficient way.


title: Distributed Edge Cloud R-CNN for Real Time Object Detection

text: Cloud computing infrastructures have become the de-facto platform for data driven machine learning applications. However, these centralized models of computing are unqualified for dispersed high-volume real-time edge data intensive applications such as real time object detection, where video streams may be captured at multiple geographical locations. While many recent advancements in object detection have been made using Convolutional Neural Networks, these performance improvements only focus on a single, contiguous object detection model. In this paper, we propose a distributed Edge-Cloud R-CNN pipeline. By splitting the object detection pipeline into components and dynamically distributing these components in the cloud, we can achieve optimal performance to enable real time object detection. As a proof of concept, we evaluate the performance of the proposed system on a distributed computing platform including cloud servers and edge-embedded devices for real-time object detection on live video streams.


title: A Novel Multi-Stack Device Structure and its Analysis for High Power CMOS Switch Design

text: A novel multi-stack CMOS device structure is proposed, the operation of the structure is fully analyzed for high power CMOS switch design. The structure is also implemented in a standard 0.18-um triple-well CMOS process, and its performance is fully characterized. The proposed switch device incorporates multi-stack NMOS switches, one of which has a switch at the bulk and the others of which have a connection between the bulk and the source in order to provide high power handling capability to the transmit switch side. In order to demonstrate the improvement of power handling capability, performance of the conventional structure and the proposed structure are fully analyzed, compared from various simulation results, and verified with measurement results in detail. Experimental data show that the isolation of the proposed test structure is 25 dB higher at 30 dBm input power level than that of conventional structures, which was caused by the significant reduction of leakage current of the switch device in OFF state. In addition, insertion loss of the Rx switch can be maintained as 1.5 dB by applying body switching technique in 900 MHz.


title: A Dual-Band Dual-Polarized Nested Vivaldi Slot Array With Multilevel Ground Plane

text: In this paper, we present a systematic approach to the design, optimization and characterization of a broadband 5:1 bandwidth (0.8 to 4.0 GHz) antenna subarray. The array element is an optimized-taper antipodal Vivaldi slot with a bandwidth of 2.5:1. Two such elements of different sizes and with 0.4 GHz (10% of the highest frequency) overlapping bandwidths are arrayed in a nested lattice above a multilevel ground plane that shields the feeds and electronics. Return loss, radiation patterns, cross-polarization and mutual coupling are measured from 0.5–5.0 GHz. This array demonstrates E plane patterns with 50 and 45 3-dB beamwidths in the lower and upper frequency bands, respectively. The coupling between the elements is characterized for different relative antenna positions in all three dimensions.


title: Online and Linear-Time Attention by Enforcing Monotonic Alignments

text: Recurrent neural network models with an attention mechanism have proven to be extremely effective on a wide variety of sequence-tosequence problems. However, the fact that soft attention mechanisms perform a pass over the entire input sequence when producing each element in the output sequence precludes their use in online settings and results in a quadratic time complexity. Based on the insight that the alignment between input and output sequence elements is monotonic in many problems of interest, we propose an end-to-end differentiable method for learning monotonic alignments which, at test time, enables computing attention online and in linear time. We validate our approach on sentence summarization, machine translation, and online speech recognition problems and achieve results competitive with existing sequence-tosequence models.


title: User involvement: a review of the benefits and challenges

text: Users can be involved in the design process in several ways. The author focuses on user-centred design, participatory design, ethnography, and contextual design. She briefly describes each approach and cites the corresponding literature. The expected benefits of these approaches highly overlap. Methods based on early user involvement promise to avoid the implementation of costly features that users do not want or cannot use. Participatory methods promise to improve the user satisfaction and the acceptance of a system. Nearly all approaches intend to improve the overall usability of the system and by this means increase the productivity and decrease the training costs and the need of user support.


title: BabyTalk: Understanding and Generating Simple Image Descriptions

text: We present a system to automatically generate natural language descriptions from images. This system consists of two parts. The first part, content planning, smooths the output of computer vision-based detection and recognition algorithms with statistics mined from large pools of visually descriptive text to determine the best content words to use to describe an image. The second step, surface realization, chooses words to construct natural language sentences based on the predicted content and general statistics from natural language. We present multiple approaches for the surface realization step and evaluate each using automatic measures of similarity to human generated reference descriptions. We also collect forced choice human evaluations between descriptions from the proposed generation system and descriptions from competing approaches. The proposed system is very effective at producing relevant sentences for images. It also generates descriptions that are notably more true to the specific image content than previous work.


title: Urogenital tract disorders in children suspected of being sexually abused.

text:
INTRODUCTION
Child sexual abuse (CSA) is generally defined as child exploitation that leads to achievement of sexual satisfaction. According to data from European countries, sexual abuse of children affects 10-40% of girls and 5-20% of boys.

MATERIAL AND METHODS
The Medline, and Web of Science databases were searched with no date limitation on May 2015 using the terms 'child abuse' in conjunction with 'urinary tract', 'urologist', 'urological dysfunction', 'urologic symptoms', 'LUTS' or 'urinary infection'.

RESULTS
Awareness of the CSA problem among paediatricians and urologists is very important, because they are often the only physicians who are able to recognize the problem. CSA diagnosis is possible only through the proper collection of a medical history and a thorough physical examination. Urologists have to remember that children exposed to sexual abuse rarely exhibit abnormal genital findings. In fact, absence of genital findings is the rule rather than the exception. In most cases, the final diagnosis of sexual abuse is based on the child's history and behavior, along with the onset and exacerbation of urologic symptoms.

CONCLUSIONS
In this article, we present a review of studies and literature concerning urinary symptoms in sexually abused children to clarify the problem for a broad group of urologists. We present common symptoms and premises that can point to the right diagnosis and basic guidelines of proceeding after suspicion of abuse.


title: The Three Layers Evaluation Model for Computer-Generated Plots

text: This paper describes a model for evaluating a computer-generated plot. The main motivation of this project is to provide MEXICA, our plot generator, with the capacity of evaluating its own outputs as well as assessing narratives generated by other agents that can be employed to enrich its knowledge base. We present a description of our computer model as well as an explanation of our first prototype. Then, we show the results of assessing three computergenerated narratives. The outcome suggests that we are in the right direction, although much more work


title: THE EFFECTS OF MYOFASCIAL RELEASE VS STATIC STRETCHING ON HAMSTRINGS RANGE OF MOTION

text: The purpose of this study was to investigate the effects of three days of foam rolling on the hamstrings range of motion in comparison with static stretching. Lower extremity injuries are prevalent in strength training and sports today. Poor flexibility has been found to increase the risk of overuse injuries and significantly affect the individual's level of function and performance. Self myofascial release (SMR), foam rolling, is a recent modality clinically used to increase flexibility. On the other hand, there are few research studies on the technique. Twenty college students participated in this study. Ten participants were in the static stretching group, while ten participants were in the SMR group. Participants received the treatment three times in one week with at least 48 hours between treatments. The treatments were static stretching and SMR for three minutes of stretching the hamstrings muscles. The wall sit-and-reach test was used to measure hamstrings range of motion. Measurements were made at the beginning of the study and after each treatment. iv The acute stretching programs increased hamstrings range of motion in the self myofascial release group (28.9%) and static group (33.2%) respectively. The Group by Time ANOVA for flexibility revealed that there was no main effect of Group (F(1,18) = 3.629, p = 0.0729), but that there was a main effect of Time (F(3,54) = 32.130, p =.0001). At the same time there was no Group by Time interaction (F(3,54) = 1.152, p =.3366). These data suggest that self myofascial release compared to static stretching did not have a greater effect on hamstrings range of motion, but both groups increased range of motion from pretest to posttest.


title: Cultural Congruent Care : A Reflection on Patient Outcome

text: The growing diverse multicultural population in the United States requires that healthcare workers develop cultural knowledge, awareness, and sensitivity to help diverse patient population receive quality health care. Personal belief has been identified as a significant contributor to professional care delivery and may influence the provision of culturally competent care. However, the relationship between cultural competence and the individual cognitive perception has been an uneasy one. This article explores the moral foundations of cultural competence and ultimately its impact on patient care outcome.


title: Global supply chain design : A literature review and critique

text: In this paper, we review decision support models for the design of global supply chains, and assess the fit between the research literature in this area and the practical issues of global supply chain design. The classification scheme for this review is based on ongoing and emerging issues in global supply chain management and includes review dimensions for (1) decisions addressed in the model, (2) performance metrics, (3) the degree to which the model supports integrated decision processes, and (4) globalization considerations. We conclude that although most models resolve a difficult feature associated with globalization, few models address the practical global supply chain design problem in its entirety. We close the paper with recommendations for future research in global supply chain modeling that is both forward-looking and practically oriented. 2005 Elsevier Ltd. All rights reserved.


Approximation capabilities of multilayer feedforward networks


title: The HiBench benchmark suite: Characterization of the MapReduce-based data analysis

text: The MapReduce model is becoming prominent for the large-scale data analysis in the cloud. In this paper, we present the benchmarking, evaluation and characterization of Hadoop, an open-source implementation of MapReduce. We first introduce HiBench, a new benchmark suite for Hadoop. It consists of a set of Hadoop programs, including both synthetic micro-benchmarks and real-world Hadoop applications. We then evaluate and characterize the Hadoop framework using HiBench, in terms of speed (i.e., job running time), throughput (i.e., the number of tasks completed per minute), HDFS bandwidth, system resource (e.g., CPU, memory and I/O) utilizations, and data access patterns.


title: The Google file system

text: We have designed and implemented the Google File System, a scalable distributed file system for large distributed data-intensive applications. It provides fault tolerance while running on inexpensive commodity hardware, and it delivers high aggregate performance to a large number of clients. While sharing many of the same goals as previous distributed file systems, our design has been driven by observations of our application workloads and technological environment, both current and anticipated, that reflect a marked departure from some earlier file system assumptions. This has led us to reexamine traditional choices and explore radically different design points. The file system has successfully met our storage needs. It is widely deployed within Google as the storage platform for the generation and processing of data used by our service as well as research and development efforts that require large data sets. The largest cluster to date provides hundreds of terabytes of storage across thousands of disks on over a thousand machines, and it is concurrently accessed by hundreds of clients. In this paper, we present file system interface extensions designed to support distributed applications, discuss many aspects of our design, and report measurements from both micro-benchmarks and real world use.


title: A Constrained, Weighted-L1 Minimization Approach for Joint Discovery of Heterogeneous Neural Connectivity Graphs

text: Determining functional brain connectivity is crucial to understanding the brain and neural differences underlying disorders such as autism. Recent studies have used Gaussian graphical models to learn brain connectivity via statistical dependencies across brain regions from neuroimaging. However, previous studies often fail to properly incorporate priors tailored to neuroscience, such as preferring shorter connections. To remedy this problem, the paper here introduces a novel, weighted-`1, multi-task graphical model (W-SIMULE). This model elegantly incorporates a flexible prior, along with a parallelizable formulation. Additionally, W-SIMULE extends the often-used Gaussian assumption, leading to considerable performance increases. Here, applications to fMRI data show that W-SIMULE succeeds in determining functional connectivity in terms of (1) log-likelihood, (2) finding edges that differentiate groups, and (3) classifying different groups based on their connectivity, achieving 58.6% accuracy on the ABIDE dataset. Having established W-SIMULE’s effectiveness, it links four key areas to autism, all of which are consistent with the literature. Due to its elegant domain adaptivity, W-SIMULE can be readily applied to various data types to effectively estimate connectivity.


title: Taming Subgraph Isomorphism for RDF Query Processing

text: RDF data are used to model knowledge in various areas such as l ife sciences, Semantic Web, bioinformatics, and social graphs . The size of real RDF data reaches billions of triples. This calls for a framework for efficiently processing RDF data. The core func tion of processing RDF data is subgraph pattern matching. There h av been two completely different directions for supporting ef ficient subgraph pattern matching. One direction is to develop spec ialized RDF query processing engines exploiting the properties of R DF data for the last decade, while the other direction is to deve lop fficient subgraph isomorphism algorithms for general, labele d graphs for over 30 years. Although both directions have a similar go al (i.e., finding subgraphs in data graphs for a given query grap h), they have been independently researched without clear reas on. We argue that a subgraph isomorphism algorithm can be easily mo dified to handle the graph homomorphism, which is the RDF patter n matching semantics, by just removing the injectivity const raint. In this paper, based on the state-of-the-art subgraph isomorp hism algorithm, we propose an in-memory solution, TurboHOM++, which is tamed for the RDF processing, and we compare it with the rep resentative RDF processing engines for several RDF benchmark s in a server machine where billions of triples can be loaded in mem ory. In order to speed upTurboHOM++, we also provide a simple yet effective transformation and a series of optimization tech niques. Extensive experiments using several RDF benchmarks show th at TurboHOM++ consistently and significantly outperforms the representative RDF engines. Specifically, TurboHOM++ outperforms its competitors by up tofiveorders of magnitude.


title: Identifying and Accounting for Task-Dependent Bias in Crowdsourcing

text: Models for aggregating contributions by crowd workers have been shown to be challenged by the rise of taskspecific biases or errors. Task-dependent errors in assessment may shift the majority opinion of even large numbers of workers to an incorrect answer. We introduce and evaluate probabilistic models that can detect and correct task-dependent bias automatically. First, we show how to build and use probabilistic graphical models for jointly modeling task features, workers’ biases, worker contributions and ground truth answers of tasks so that task-dependent bias can be corrected. Second, we show how the approach can perform a type of transfer learning among workers to address the issue of annotation sparsity. We evaluate the models with varying complexity on a large data set collected from a citizen science project and show that the models are effective at correcting the task-dependent worker bias. Finally, we investigate the use of active learning to guide the acquisition of expert assessments to enable automatic detection and correction of worker bias.


title: A soft robotic approach to robust and dexterous grasping

text: In this paper, we present a compliant robotic gripper, Edgy-2, with 4-DOF dexterity, enabling four grasping modes: parallel grasping, power grasping, finger-tip pinch and fully-actuated grasping. The roboticfinger is based on soft-rigid-hybrid structures, combining fiber-reinforced soft pneumatic actuators with rigid joints, which exhibit reliable structural rigidity and grasping robustness while maintaining excellent adaptability and inherent compliance. With both grasping dexterity and grasping robustness, the Edgy-2 achieves excellent grasping reliability with various daily objects, from a fragile cherry to a 2 kg water bottled water. The relationship of design parameters and grasping strength is presented with analytical models. The performance of a prototype Edgy-2 is verified by dedicated experiments. The proposed hybrid dexterous grasping approach can be easily extended into different end-effector designs according to application requirements. The proposed mechanism for grasping provides excellent human-robot interaction safety and reliability.


title: Which NoSQL Database? A Performance Overview

text: NoSQL data stores are widely used to store and retrieve possibly large amounts of data, typically in a key-value format. There are many NoSQL types with different performances, and thus it is important to compare them in terms of performance and verify how the performance is related to the database type. In this paper, we evaluate five most popular NoSQL databases: Cassandra, HBase, MongoDB, OrientDB and Redis. We compare those databases in terms of query performance, based on reads and updates, taking into consideration the typical workloads, as represented by the Yahoo! Cloud Serving Benchmark. This comparison allows users to choose the most appropriate database according to the specific mechanisms and application needs. TYPE OF PAPER AND


title: Pattern Recognition

text: In this paper a novel reconstruction method is presented that uses the topological relationship of detected image features to create a highly abstract but semantically rich 3D model of the reconstructed scenes. In the first step, a combined image-based reconstruction of points and lines is performed based on the current state of art structure from motion methods. Subsequently, connected planar threedimensional structures are reconstructed by a novel method that uses the topological relationships between the detected image features. The reconstructed 3D models enable a simple extraction of geometric shapes, such as rectangles, in the scene.


title: SD-Map - A Fast Algorithm for Exhaustive Subgroup Discovery

text: In this paper we present the novel SD-Map algorithm for exhaustive but efficient subgroup discovery. SD-Map guarantees to identify all interesting subgroup patterns contained in a data set, in contrast to heuristic or samplingbased methods. The SD-Map algorithm utilizes the well-known FP-growth method for mining association rules with adaptations for the subgroup discovery task. We show how SD-Map can handle missing values, and provide an experimental evaluation of the performance of the algorithm using synthetic data.


title: Demystifying Learning Analytics in Personalised Learning

text: This paper presents learning analytics as a mean to improve students’ learning. Most learning analytics tools are developed by in-house individual educational institutions to meet the specific needs of their students. Learning analytics is defined as a way to measure, collect, analyse and report data about learners and their context, for the purpose of understanding and optimizing learning. The paper concludes by highlighting framework of learning analytics in order to improve personalised learning. In addition, it is an endeavour to define the characterising features that represents the relationship between learning analytics and personalised learning environment. The paper proposes that learning analytics is dependent on personalised approach for both educators and students. From a learning perspective, students can be supported with specific learning process and reflection visualisation that compares their respective performances to the overall performance of a course. Furthermore, the learners may be provided with personalised recommendations for suitable learning resources, learning paths, or peer students through recommending system. The paper’s contribution to knowledge is in considering personalised learning within the context framework of learning analytics.


title: Credit card incidents and control systems

text: Credit and debit cards have spread and skyrocketed all around the world to become the most popular means of payments in many countries. Despite their enormous popularity, cards are not free of risk. Technology development and e-commerce have exponentially increased internal credit card incidents. This paper identifies and quantifies the different types of credit card fraud and puts into question the effectiveness of the role assigned to cardholders in its detection. © 2012 Elsevier Ltd. All rights reserved.


title: A unified view of gradient-based attribution methods for Deep Neural Networks

text: Understanding the flow of information in Deep Neural Networks (DNNs) is a challenging problem that has gain increasing attention over the last few years. While several methods have been proposed to explain network predictions, only few attempts to analyze them from a theoretical perspective have been made in the past. In this work we analyze various state-of-the-art attribution methods and prove unexplored connections between them. We also show how some methods can be reformulated and more conveniently implemented. Finally, we perform an empirical evaluation with six attribution methods on a variety of tasks and architectures and discuss their strengths and limitations.


title: Cyclic deadlock prediction and avoidance for zone-controlled AGV system

text: Automated guided vehicles (AGVs) are now becoming popular in automated materials handling systems, flexible manufacturing systems and even containers handling applications at seaports. Its performance affects the efficiency of the entire system. Deadlock formation is a serious problem as it stalls the AGVS. The objective of this paper is to develop an efficient AGV deadlock prediction and avoidance algorithm for container port operations. Deadlock in a broad sense is a situation in which at least a part of the system stalls. There are a lot of situations in which the system may stall and most of these situations can be avoided through the control and navigation system. This paper discusses the development of an efficient strategy for predicting and avoiding the deadlocks in a large scale AGVS A variety of deadlock-detecting algorithms are available, but these methods work mainly for manufacturing system where the network layout is simple and uses only a small number of AGVs. The AGVS under study has complex layout and involves close to 80 AGVs. The proposed solution is implemented using the Automod simulation software, and the performance of the technique is presented. Simulation shows that all the potential deadlock situations can be detected and avoided via this methodology. Also, the proposed strategy is computationally efficient and is able to provide the movement decision to the vehicles within the 1.5-s sampling time. r 2002 Published by Elsevier Science B.V.


title: The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems

text: We propose a deep learning based method, the Deep Ritz Method, for numerically solving variational problems, particularly the ones that arise from partial differential equations. The Deep Ritz method is naturally nonlinear, naturally adaptive and has the potential to work in rather high dimensions. The framework is quite simple and fits well with the stochastic gradient descent method used in deep learning. We illustrate the method on several problems including some eigenvalue problems.


title: The effect of music background on the emotional appraisal of film sequences

text: In this study the effects of musical background on the emotional appraisal of film sequences was investigated. Four pairs of polar emotions defined in Plutchik’s model were used as basic emotional qualities: joy-sadness, anticipation-surprise, fear-anger, and trustdisgust. In the preliminary study eight film sequences and eight music themes were selected as the best representatives of all eight Plutchik’s emotions. In the main experiment the participant judged the emotional qualities of film-music combinations on eight seven-point scales. Half of the combinations were congruent (e.g. joyful film joyful music), and half were incongruent (e.g. joyful film sad music). Results have shown that visual information (film) had greater effects on the emotion appraisal than auditory information (music). The modulation effects of music background depend on emotional qualities. In some incongruent combinations (joysadness) the modulations in the expected directions were obtained (e.g. joyful music reduces the sadness of a sad film), in some cases (anger-fear) no modulation effects were obtained, and in some cases (trust-disgust, anticipation-surprise) the modulation effects were in an unexpected direction (e.g. trustful music increased the appraisal of disgust of a disgusting film). These results suggest that the appraisals of conjoint effects of emotions depend on the medium (film masks the music) and emotional quality (three types of modulation effects).


title: Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting.

text: The growing need to store increasing amounts of renewable energy has recently triggered substantial R&D efforts towards efficient and stable water electrolysis technologies. The oxygen evolution reaction (OER) occurring at the electrolyser anode is central to the development of a clean, reliable and emission-free hydrogen economy. The development of robust and highly active anode materials for OER is therefore a great challenge and has been the main focus of research. Among potential candidates, perovskites have emerged as promising OER electrocatalysts. In this study, by combining a scalable cutting-edge synthesis method with time-resolved X-ray absorption spectroscopy measurements, we were able to capture the dynamic local electronic and geometric structure during realistic operando conditions for highly active OER perovskite nanocatalysts. Ba0.5Sr0.5Co0.8Fe0.2O3-δ as nano-powder displays unique features that allow a dynamic self-reconstruction of the material's surface during OER, that is, the growth of a self-assembled metal oxy(hydroxide) active layer. Therefore, besides showing outstanding performance at both the laboratory and industrial scale, we provide a fundamental understanding of the operando OER mechanism for highly active perovskite catalysts. This understanding significantly differs from design principles based on ex situ characterization techniques.


title: Applying multi-agent technique in multi-section flexible manufacturing system

text: In the highly competitive market, cooperative multi-agent transaction and negotiation mechanism have become an important research topic. This paper uses multi-agent technology to construct a multi-section flexible manufacturing system (FMS) model, and utilizes simulation to build a manufacturing environment based on JADE framework for multi-agent to combine with dispatching rules, such as shortest imminent processing time (SIPT), first come first serve (FCFS) earliest due date (EDD), and Buffer Sequence. This paper finds that using multi-agent technique for multi-section FMS model can enhance the production efficiency in practice. Meanwhile, in this study, multi-agent systems combined with dynamic dispatching can be used to identify the best dispatching rules combination for achieving largest throughput, and thus it can provide the reference for production scheduling in advance. 2010 Elsevier Ltd. All rights reserved.


title: Providing Research Graph Data in JSON-LD Using Schema.org

text: In this position paper, we describe a pilot project that provides Research Graph records to external web services using JSON-LD. The Research Graph database contains a largescale graph that links research datasets (i.e., data used to support research) to funding records (i.e. grants), publications and researcher records such as ORCID profiles. This database was derived from the work of the Research Data Alliance Working Group on Data Description Registry Interoperability (DDRI), and curated using the Research Data Switchboard open source software. By being available in Linked Data format, the Research Graph database is more accessible to third-party web services over the Internet, which thus opens the opportunity to connect to the rest of the world in the semantic format. The primary purpose of this pilot project is to evaluate the feasibility of converting registry objects in Research Graph to JSON-LD by accessing widely used vocabularies published at Schema.org. In this paper, we provide examples of publications, datasets and grants from international research institutions such as CERN INSPIREHEP, National Computational Infrastructure (NCI) in Australia, and Australian Research Council (ARC). Furthermore, we show how these Research Graph records are made semantically available as Linked Data through using Schema.org. The mapping between Research Graph schema and Schema.org is available on GitHub repository. We also discuss the po©c 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. WWW 2017 Companion, April 3–7, 2017, Perth, Australia. ACM 978-1-4503-4914-7/17/04. http://dx.doi.org/10.1145/3038912.3038914 . tential need for an extension to Schema.org vocabulary for scholarly communication.


title: An Improved Speech Enhancement Method based on Teager Energy Operator and Perceptual Wavelet Packet Decomposition

text: According to the distribution characteristic of noise and clean speech signal in the frequency domain, a new speech enhancement method based on teager energy operator (TEO) and perceptual wavelet packet decomposition (PWPD) is proposed. Firstly, a modified Mask construction method is made to protect the acoustic cues at the low frequencies. Then a level-dependent parameter is introduced to further adjust the thresholds in light of the noise distribution feature. At last the sub-bands which have very little influence are set directly 0 to improve the signal-to-noise ratio (SNR) and reduce the computation load. Simulation results show that, under different kinds of noise environments, this new method not only enhances the signal-to-noise ratio (SNR) and perceptual evaluation of speech quality (PESQ), but also reduces the computation load, which is very advantageous for real-time realizing.


title: Unikernels: library operating systems for the cloud

text: We present unikernels, a new approach to deploying cloud services via applications written in high-level source code. Unikernels are single-purpose appliances that are compile-time specialised into standalone kernels, and sealed against modification when deployed to a cloud platform. In return they offer significant reduction in image sizes, improved efficiency and security, and should reduce operational costs. Our Mirage prototype compiles OCaml code into unikernels that run on commodity clouds and offer an order of magnitude reduction in code size without significant performance penalty. The architecture combines static type-safety with a single address-space layout that can be made immutable via a hypervisor extension. Mirage contributes a suite of type-safe protocol libraries, and our results demonstrate that the hypervisor is a platform that overcomes the hardware compatibility issues that have made past library operating systems impractical to deploy in the real-world.


title: A Taxonomy of Attacks in RPL-based Internet of Things

text: The growing interest for the Internet of Things is contributing to the large-scale deployment of Low power and Lossy Networks (LLN). These networks support communications amongst objects from the real world, such as home automation devices and embedded sensors, and their interconnection to the Internet. An open standard routing protocol, called RPL, has been specified by the IETF in order to address the specific properties and constraints of these networks. However, this protocol is exposed to a large variety of attacks. Their consequences can be quite significant in terms of network performance and resources. In this paper, we propose to establish a taxonomy of the attacks against this protocol, considering three main categories including attacks targeting network resources, attacks modifying the network topology and attacks related to network traffic. We describe these attacks, analyze and compare their properties, discuss existing counter-measures and their usage from a risk management perspective.


Geostatistical Space-Time Models , Stationarity , Separability , and Full Symmetry


title: Who Invented the Reverse Mode of Differentiation ?

text: Nick Trefethen [13] listed automatic differentiation as one of the 30 great numerical algorithms of the last century. He kindly credited the present author with facilitating the rebirth of the key idea, namely the reverse mode. In fact, there have been many incarnations of this reversal technique, which has been suggested by several people from various fields since the late 1960s, if not earlier. Seppo Linnainmaa (Lin76) of Helsinki says the idea came to him on a sunny afternoon in a Copenhagen park in 1970. He used it as a tool for estimating the effects of arithmetic rounding errors on the results of complex expressions. Gerardi Ostrowski (OVB71) discovered and used it some five years earlier in the context of certain process models in chemical engineering. Here and throughout references that are not listed in the present bibliography are noted in parentheses and can be found in the book [7]. Also in the sixties Hachtel et al. [6] considered the optimization of electronic circuits using the costate equation of initial value problems and its discretizations to compute gradients in the reverse mode for explicitly time-dependent problems. Here we see, possibly for the first time, the close connection between the reverse mode of discrete evaluation procedures and continuous adjoints of differential equations. In the 1970s Iri analyzed the properties of dual and adjoint networks. In the 1980s he became one of the key researchers on the reverse mode. From a memory and numerical stability point of view the most difficult aspect of the reverse mode is the reversal of a program. This problem was discussed in the context of Turing Machines by Benett (Ben73), who foreshadowed the use of checkpointing as a tradeoff between numerical computational effort and memory requirement.


title: Erasure coded storage systems for cloud storage — challenges and opportunities

text: Erasure coded storage schemes offer a promising future for cloud storage. Highlights of erasure coded storage systems are that these offer the same level of fault tolerance as that of replication, at lower storage footprints. In the big data era, cloud storage systems based on data replication are of dubious usability due to 200% storage overhead in data replication systems. This has prompted storage service providers to use erasure coded storage as an alternative to replication. Refinements are required in various aspects of erasure coded storage systems to make it a real contender against data replication based storage systems. Streamlining huge bandwidth requirements during the recovery of failed nodes, inefficient update operations, effect of topology in recovery and consistency requirements of erasure coded storage systems, are some areas which need attention. This paper presents an in-depth study on the challenges faced, and research pursued in some of these areas. The survey shows that more research is required to improve erasure coded storage system from being bandwidth crunchers to efficient storage systems. Another challenge that has emerged from the study is the requirement of elaborate research for upgrading the erasure coded storage systems from being mere archival storage systems by providing better update methods. Provision of multiple level consistency in erasure coded storage is yet another research opportunity identified in this work. A brief introduction to open source libraries available for erasure coded storage is also presented in the paper.


title: Big data and cloud computing: current state and future opportunities

text: Scalable database management systems (DBMS)---both for update intensive application workloads as well as decision support systems for descriptive and deep analytics---are a critical part of the cloud infrastructure and play an important role in ensuring the smooth transition of applications from the traditional enterprise infrastructures to next generation cloud infrastructures. Though scalable data management has been a vision for more than three decades and much research has focussed on large scale data management in traditional enterprise setting, cloud computing brings its own set of novel challenges that must be addressed to ensure the success of data management solutions in the cloud environment. This tutorial presents an organized picture of the challenges faced by application developers and DBMS designers in developing and deploying internet scale applications. Our background study encompasses both classes of systems: (i) for supporting update heavy applications, and (ii) for ad-hoc analytics and decision support. We then focus on providing an in-depth analysis of systems for supporting update intensive web-applications and provide a survey of the state-of-the-art in this domain. We crystallize the design choices made by some successful systems large scale database management systems, analyze the application demands and access patterns, and enumerate the desiderata for a cloud-bound DBMS.


title: Partial-parallel-repair (PPR): a distributed technique for repairing erasure coded storage

text: With the explosion of data in applications all around us, erasure coded storage has emerged as an attractive alternative to replication because even with significantly lower storage overhead, they provide better reliability against data loss. Reed-Solomon code is the most widely used erasure code because it provides maximum reliability for a given storage overhead and is flexible in the choice of coding parameters that determine the achievable reliability. However, reconstruction time for unavailable data becomes prohibitively long mainly because of network bottlenecks. Some proposed solutions either use additional storage or limit the coding parameters that can be used. In this paper, we propose a novel distributed reconstruction technique, called Partial Parallel Repair (PPR), which divides the reconstruction operation to small partial operations and schedules them on multiple nodes already involved in the data reconstruction. Then a distributed protocol progressively combines these partial results to reconstruct the unavailable data blocks and this technique reduces the network pressure. Theoretically, our technique can complete the network transfer in ⌈(log2(k + 1))⌉ time, compared to k time needed for a (k, m) Reed-Solomon code. Our experiments show that PPR reduces repair time and degraded read time significantly. Moreover, our technique is compatible with existing erasure codes and does not require any additional storage overhead. We demonstrate this by overlaying PPR on top of two prior schemes, Local Reconstruction Code and Rotated Reed-Solomon code, to gain additional savings in reconstruction time.


title: Proliferation, cell cycle and apoptosis in cancer

text: Beneath the complexity and idiopathy of every cancer lies a limited number of 'mission critical' events that have propelled the tumour cell and its progeny into uncontrolled expansion and invasion. One of these is deregulated cell proliferation, which, together with the obligate compensatory suppression of apoptosis needed to support it, provides a minimal 'platform' necessary to support further neoplastic progression. Adroit targeting of these critical events should have potent and specific therapeutic consequences.


title: Performance Analysis of Engineering Students for Recruitment Using Classification Data Mining Techniques

text: -Data Mining is a powerful tool for academic intervention. Mining in education environment is called Educational Data Mining. Educational Data Mining is concerned with developing new methods to discover knowledge from educational database and can used for decision making in educational system. In our work, we collected the student’s data from engineering institute that have different information about their previous and current academics records like students S.No., Name, Branch, 10, 12 , B.Tech passing percentage and final grade & then apply different classification algorithm using Data Mining tools (WEKA) for analysis the students academics performance for Training & placement department or company executives. This paper deals with a comparative study of various classification data mining algorithms for the performance analysis of the student’s academic records and check which algorithm is optimal for classifying students’ based on their final grade. This analysis also classifies the performance of Students into Excellent, Good and Average categories. Keywords– Data Mining, Discover knowledge, Technical Education, Educational Data, Mining, Classification, WEKA, Classifiers.


title: A novel integrated dielectric-and-conductive ink 3D printing technique for fabrication of microwave devices

text: In this work a novel combination of printed electronics using conductive nanoparticle ink together with 3D printing of dielectric material is presented as one integrated process. This allows fabrication of complicated 3D electromagnetic (EM) structures such as wide range of different antennas and microwave devices to simultaneously include printing of conductive nanoparticle ink within 3D dielectric configurations. Characterization of conductive ink and polymer based substrate has been done to ensure proper RF, electric, thermal and mechanical performance of both substrate and the ink. A meander line dipole antenna on a V-shaped substrate is printed and tested to demonstrate the efficiency and accuracy of proposed technique. The goal in this paper is to provide a low cost, environmentally friendly integrated process for the fabrication of geometrically complicated 3D electromagnetic structures.


title: Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIP

text: RNA transcripts are subject to posttranscriptional gene regulation involving hundreds of RNA-binding proteins (RBPs) and microRNA-containing ribonucleoprotein complexes (miRNPs) expressed in a cell-type dependent fashion. We developed a cell-based crosslinking approach to determine at high resolution and transcriptome-wide the binding sites of cellular RBPs and miRNPs. The crosslinked sites are revealed by thymidine to cytidine transitions in the cDNAs prepared from immunopurified RNPs of 4-thiouridine-treated cells. We determined the binding sites and regulatory consequences for several intensely studied RBPs and miRNPs, including PUM2, QKI, IGF2BP1-3, AGO/EIF2C1-4 and TNRC6A-C. Our study revealed that these factors bind thousands of sites containing defined sequence motifs and have distinct preferences for exonic versus intronic or coding versus untranslated transcript regions. The precise mapping of binding sites across the transcriptome will be critical to the interpretation of the rapidly emerging data on genetic variation between individuals and how these variations contribute to complex genetic diseases.


title: Revised Estimates for the Number of Human and Bacteria Cells in the Body

text: Reported values in the literature on the number of cells in the body differ by orders of magnitude and are very seldom supported by any measurements or calculations. Here, we integrate the most up-to-date information on the number of human and bacterial cells in the body. We estimate the total number of bacteria in the 70 kg "reference man" to be 3.8·1013. For human cells, we identify the dominant role of the hematopoietic lineage to the total count (≈90%) and revise past estimates to 3.0·1013 human cells. Our analysis also updates the widely-cited 10:1 ratio, showing that the number of bacteria in the body is actually of the same order as the number of human cells, and their total mass is about 0.2 kg.


title: A New Technique to Design Circularly Polarized Microstrip Antenna by Fractal Defected Ground Structure

text: A new technique to design single-feed circularly polarized (CP) microstrip antenna is proposed. The CP radiation is obtained by adjusting the dimension of the etched fractal defected ground structure (FDGS) in the ground plane. Parameter studies of the FDGS are given to illustrate the way to achieve CP radiation. The CP microstrip antennas with the second and third iterative FDGS are fabricated and measured. The measured 10-dB return-loss bandwidth of the CP microstrip antenna is about 30 MHz (1.558 to 1.588 GHz), while its 3-dB axial-ratio bandwidth is 6 MHz (1.572 to 1.578 GHz). The gain across the CP band is between 1.7 and 2.2 dBic.


title: The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid Clouds

text: Cloud computing alters the way traditional software systems are built and run by introducing a utilitybased model for delivering IT infrastructure, platforms, applications, and services. The consolidation of this new paradigm in both enterprises and academia demanded reconsideration in the way IT resources are used, so Cloud computing can be used together with available resources. A case for the utilization of Clouds for increasing the capacity of computing infrastructures is Desktop Grids: these infrastructures typically provide best effort execution of high throughput jobs and other workloads that fit the model of the platform. By enhancing Desktop Grid infrastructures with Cloud resources, it is possible to offer QoS to users, motivating the adoption of Desktop Grids as a viable platform for application execution. In this paper,we describe howAneka, a platform for developing scalable applications on the Cloud, supports such a vision by provisioning resources fromdifferent sources and supporting different applicationmodels.We highlight the key concepts and features of Aneka that support the integration between Desktop Grids and Clouds and present an experiment showing the performance of this integration. © 2011 Elsevier B.V. All rights reserved.


title: Model predictive path-following control of an A.R. drone quadrotor

text: This paper addresses the design and implementation of the Extended Prediction Self-Adaptive Control (EPSAC) approach to Model Predictive Control (MPC) for path-following. Special attention is paid to the closed-loop performance in order to achieve a fast response without overshoot, which are the necessary conditions to ensure the desired tracking performance in confined or indoor environments. The performance of the proposed MPC strategy is compared to the one achieved using PD controllers. Experimental results using the low-cost quadrotor AR.Drone 2.0 validate the reliability of the proposed strategy for 2D and 3D movements.


title: Mutual Information, Fisher Information, and Population Coding

text: In the context of parameter estimation and model selection, it is only quite recently that a direct link between the Fisher information and information-theoretic quantities has been exhibited. We give an interpretation of this link within the standard framework of information theory. We show that in the context of population coding, the mutual information between the activity of a large array of neurons and a stimulus to which the neurons are tuned is naturally related to the Fisher information. In the light of this result, we consider the optimization of the tuning curves parameters in the case of neurons responding to a stimulus represented by an angular variable.


title: Novel Concept of the Three-Dimensional Vertical FG nand Flash Memory Using the Separated-Sidewall Control Gate

text: Recently, we proposed a novel 3-D vertical floating gate (FG)-type nand Flash memory cell array using the separated-sidewall control gate (CG) (S-SCG). This novel cell consists of one cylindrical FG with line-type CG and S-SCG structures. For simplifying the process flow, we realized the common S-SCG lines by using the prestacked polysilicon layer, through which variable medium voltages are applied not only to control the electrically inverted S/D region but also to assist the program and erase operations. In this paper, we successfully demonstrate the normal Flash cell operation and show its superior performances in comparison with the recent 3-D FG nand cells by using the cylindrical device simulation. It is shown that the proposed cell can realize the highest CG coupling ratio, low-voltage cell operations of program with 15 V at Vth = 4V and erase with 14 V at Vth = -3V , good retention-mode electric field, and sufficient read-mode on-current margin. Moreover, the proposed S-SCG cell array can fully suppress both the interference effects and the disturbance problems at the same time by removing the direct coupling effects in the same cell string, which are the most critical problems of the recent 3-D vertical stacked cell structures. Above all, the proposed cell array has good potential for terabit 3-D vertical nand Flash cell array with highly reliable multilevel cell operation.


title: "Preventative" vs. "Reactive": How Parental Mediation Influences Teens' Social Media Privacy Behaviors

text: Through an empirical, secondary analysis of 588 teens (ages 12 - 17) and one of their parents living in the USA, we present useful insights into how parental privacy concerns for their teens and different parental mediation strategies (direct intervention versus active mediation) influence teen privacy concerns and privacy risk-taking and risk-coping privacy behaviors in social media. Our results suggest that the use of direct intervention by itself may have a suppressive effect on teens, reducing their exposure to online risks but also their ability to engage with others online and to learn how to effectively cope with online risks. Therefore, it may be beneficial for parents to combine active mediation with direct intervention so that they can protect their teens from severe online risks while empowering teens to engage with others online and learn to make good online privacy choices.


title: The Adult Sensory Profile: measuring patterns of sensory processing.

text:
OBJECTIVE
This article describes a series of studies designed to evaluate the reliability and validity of the Adult Sensory Profile.

METHOD
Expert judges evaluated the construct validity of the items. Coefficient alpha, factor analysis, and correlations of items with subscales determined item reliability, using data from 615 adult sensory profiles. A subsample of 20 adults furnished skin conductance data. A heterogeneous group of 93 adults completed the revised Adult Sensory Profile, and item reliability was reexamined.

RESULTS
Expert judgment indicated that items could be categorized according to Dunn's Model of Sensory Processing. Results suggested reasonable item reliability for all subscales except for the Sensation Avoiding subscale. Skin conductance measures detected distinct patterns of physiological responses consistent with the four-quadrant model. Revision of the Adult Sensory Profile resulted in improved reliability of the Sensation Avoiding subscale.

CONCLUSION
The series of studies provides evidence to support the four subscales of the Adult Sensory Profile as distinct constructs of sensory processing preferences.


title: The core role of the nurse practitioner: practice, professionalism and clinical leadership.

text:
AIM
To draw on empirical evidence to illustrate the core role of nurse practitioners in Australia and New Zealand.

BACKGROUND
Enacted legislation provides for mutual recognition of qualifications, including nursing, between New Zealand and Australia. As the nurse practitioner role is relatively new in both countries, there is no consistency in role expectation and hence mutual recognition has not yet been applied to nurse practitioners. A study jointly commissioned by both countries' Regulatory Boards developed information on the core role of the nurse practitioner, to develop shared competency and educational standards. Reporting on this study's process and outcomes provides insights that are relevant both locally and internationally.

METHOD
This interpretive study used multiple data sources, including published and grey literature, policy documents, nurse practitioner program curricula and interviews with 15 nurse practitioners from the two countries. Data were analysed according to the appropriate standard for each data type and included both deductive and inductive methods. The data were aggregated thematically according to patterns within and across the interview and material data.

FINDINGS
The core role of the nurse practitioner was identified as having three components: dynamic practice, professional efficacy and clinical leadership. Nurse practitioner practice is dynamic and involves the application of high level clinical knowledge and skills in a wide range of contexts. The nurse practitioner demonstrates professional efficacy, enhanced by an extended range of autonomy that includes legislated privileges. The nurse practitioner is a clinical leader with a readiness and an obligation to advocate for their client base and their profession at the systems level of health care.

CONCLUSION
A clearly articulated and research informed description of the core role of the nurse practitioner provides the basis for development of educational and practice competency standards. These research findings provide new perspectives to inform the international debate about this extended level of nursing practice.

RELEVANCE TO CLINICAL PRACTICE
The findings from this research have the potential to achieve a standardised approach and internationally consistent nomenclature for the nurse practitioner role.


title: Event-based Camera Pose Tracking using a Generative Event Model

text: Event-based vision sensors mimic the operation of biological retina and they represent a major paradigm shift from traditional cameras. Instead of providing frames of intensity measurements synchronously, at artificially chosen rates, event-based cameras provide information on brightness changes asynchronously, when they occur. Such non-redundant pieces of information are called “events”. These sensors overcome some of the limitations of traditional cameras (response time, bandwidth and dynamic range) but require new methods to deal with the data they output. We tackle the problem of event-based camera localization in a known environment, without additional sensing, using a probabilistic generative event model in a Bayesian filtering framework. Our main contribution is the design of the likelihood function used in the filter to process the observed events. Based on the physical characteristics of the sensor and on empirical evidence of the Gaussian-like distribution of spiked events with respect to the brightness change, we propose to use the contrast residual as a measure of how well the estimated pose of the event-based camera and the environment explain the observed events. The filter allows for localization in the general case of six degrees-of-freedom motions.


title: Zero quiescent current, delay adjustable, power-on-reset circuit

text: A power-on-reset (POR) circuit is extremely important in digital and mixed-signal ICs. It is used to initialize critical nodes of digital circuitry inside the chip during power-on. A novel POR circuit having zero quiescent current and an adjustable delay is proposed and demonstrated. The circuit has been designed in 0.5μm CMOS process to work for a supply voltage ranging from 1.8V to 5.5V. The circuit generates a POR signal after a predetermined delay, after the supply voltage crosses a predefined threshold voltage. This delay can be increased or decreased via programmable fuses. The POR threshold does not depend upon the supply ramp rate. The Brown-Out (BO) voltage for the proposed circuit matches the minimum supply voltage required by the digital circuitry inside the IC. The circuit consumes zero steady state current, making it ideal for low power applications.


title: Spatial Partitioning Techniques in Spatial Hadoop

text: SpatialHadoop is an extended MapReduce framework that supp orts global indexing that spatial partitions the data across machines providing orders of magnitude speedup, compared to traditi onal Hadoop. In this paper, we describe seven alternative partit ioning techniques and experimentally study their effect on the qua lity of the generated index and the performance of range and spatial join queries. We found that using a 1% sample is enough to produce high quality partitions. Also, we found that the total area o f partitions is a reasonable measure of the quality of indexes when r unning spatial join. This study will assist researchers in cho osing a good spatial partitioning technique in distributed enviro nments. 1. INDEXING IN SPATIALHADOOP SpatialHadoop [2, 3] provides a generic indexing algorithm which was used to implement grid, R-tree, and R+-tree based p artitioning. This paper extends our previous study by introduci ng four new partitioning techniques, Z-curve, Hilbert curve, Quad tree, and K-d tree, and experimentally evaluate all of the seven techn iques. The partitioning phase of the indexing algorithm runs in thr ee steps, where the first step is fixed and the last two steps are customiz ed for each partitioning technique. The first step computes number of desired partitionsn based on file size and HDFS block capacity which are both fixed for all partitioning techniques. The second st ep reads a random sample, with a sampling ratio ρ, from the input file and uses this sample to partition the space into cells such that number of sample points in each cell is at most ⌊k/n⌋, wherek is the sample size. The third step actually partitions the file by as signing each record to one or more cells. Boundary objects are handle d using either thedistribution or replication methods. Thedistribution method assigns an object to exactly one overlapping cell and the cell has to be expanded to enclose all contained records. The replication method avoids expanding cells by replicating each record to all overlapping cells but the query processor has to employ a duplicate avoidance technique to account for replicated records . ∗This work is supported in part by the National Science Founda tion, USA, under Grants IIS-0952977 and IIS-1218168 and the University of Minnesota Doctoral Disseration Fellowship. This work is licensed under the Creative Commons Attributio nNonCommercial-NoDerivs 3.0 Unported License. To view a cop y f this license, visit http://creativecommons.org/licenses/by-n c-nd/3.0/. Obtain permission prior to any use beyond those covered by the license. Contact copyright holder by emailing info@vldb.org. Articles fromthis volume were invited to present their results at the 41st Internatio l Conference on Very Large Data Bases, August 31st September 4th 2015, Koha la Coast, Hawaii. Proceedings of the VLDB Endowment, Vol. 8, No. 12 Copyright 2015 VLDB Endowment 2150-8097/15/08. 2. EXPERIMENTAL SETUP All experiments run on Amazon EC2 ‘m1.large’ instances which have a dual core processor, 7.5 GB RAM and 840 GB disk storage. We use Hadoop 1.2.1 running on Java 1.6 and CentOS 6. Each machine is configured to run three mappers and two reduce rs. Tables 1 and 2 summarize the datasets and configuration param eters used in our experiments, respectively. Default parame ters (in parentheses) are used unless otherwise mentioned. In the fo llowing part, we describe the partitioning techniques, the quer ies we run, and the performance metrics measured in this paper. 2.1 Partitioning Techniques This paper employsgrid and Quad tree as space partitioning techniques;STR, STR+, and K-d tree as data partitioning techniques; andZ-curve andHilbert curve as space filling curve (SFC) partitioning techniques. These techniques can also be grou ped, according to boundary object handling, into replication-based techniques (i.e., Grid, Quad, STR+, and K-d tree) and distributionbased techniques (i.e., STR, Z-Cruve, and Hilbert). Figure 1 illustrates these techniques, where sample points and partition bou daries are shown as dots and rectangles, respectively. 1. Uniform Grid: This technique does not require a random sample as it divides the input MBR using a uniform grid of ⌈√n⌉ × ⌈√n⌉ grid cells and employs the replication method to handle boundary objects. 2. Quad tree: This technique inserts all sample points into a quad tree [6] with node capacity of ⌊k/n⌋, wherek is the sample size. The boundaries of all leaf nodes are used as cell boundaries. W use the replication method to assign records to cells. 3. STR: This technique bulk loads the random sample into an Rtree using the STR algorithm [8] and the capacity of each node is set to⌊k/n⌋. The MBRs of leaf nodes are used as cell boundaries. Boundary objects are handled using the distribution method where it assigns a record r to the cell with maximal overlap. 4. STR+: This technique is similar to the STR technique but it uses the replication method to handle boundary objects. 5. K-d tree: This technique uses the K-d tree [1] partitioning method to partition the space into n cells. It starts with the input MBR as one cell and partitions it n − 1 times to producen cells. Records are assigned to cells using the replication method. 6. Z-curve: This technique sorts the sample points by their order on the Z-curve and partitions the curve into n splits, each containing roughly⌊k/n⌋ points. It uses the distribution method to assign a recordr to one cell by mapping the center point of its MBR to one of then splits. 7. Hilbert curve: This technique is exactly the same as the Zcurve technique but it uses Hilbert space filling curve which has better spatial properties. (a) Grid (b) Quad Tree (c) STR and STR+ (d) K-d Tree (e) Z-curve (f) Hilbert Curve Figure 1: Partitioning Techniques. Examples of nearly-empty partitions are starred. Name Size Records Average Record Size All Objects 88GB 250M 378 bytes Buildings 25GB 109M 234 bytes Roads 23GB 70M 337 bytes Lakes 8.6GB 9M 1KB Cities 1.4GB 170K 8.4KB


title: Mobile application for guiding tourist activities: tourist assistant - TAIS

text: The paper presents category classification of mobile travel applications accessible at the moment for tourists in application stores for most popular mobile operation systems (Android and iOS). The most interesting category is "Travel Guides" that combines "Information Resources" and "Location-Based Services" category. Authors propose application "Tourist assistant - TAIS" that is related to "Travel Guides" category and recommends the tourist attractions around. Information about attractions is extracted from different internet sources.


title: A novel isolated electrolytic capacitor-less single-switch AC-DC offline LED driver with power factor correction

text: Conventional AC-DC driver circuits for Light-Emitting Diode (LED) lamps require large output capacitance across the LED load to minimize the low frequency current ripple. This large capacitance is usually achieved by using an electrolytic capacitor, which has a lifetime that is at least two times less than that of a LED device. To match the potential lifetime of the LEDs, a new isolated single switch AC-DC high power factor LED driver without any electrolytic capacitors is proposed in this paper. In the proposed circuit, the energy storage capacitor is moved to the rectifier side, with a three-winding transformer used to provide isolation; power factor correction as well as to store and provide the required energy to the output. As a result, the energy storage capacitance is significantly reduced, which allows film capacitor to replace the unreliable electrolytic capacitors. The circuit's operating principles and its characteristics are described in this paper. Simulation and experimental results confirm that a power factor of 0.96 is achieved on a 120Vrms, 12W prototype.


title: Lightweight Cryptography for FPGAs

text: The advent of new low-power Field Programmable Gate Arrays (FPGA) for battery powered devices opens a host of new applications to FPGAs. In order to provide security on resource constrained devices lightweight cryptographic algorithms have been developed. However, there has not been much research on porting these algorithms to FPGAs. In this paper we propose lightweight cryptography for FPGAs by introducing block cipher independent optimization techniques for Xilinx Spartan3 FPGAs and applying them to the lightweight cryptographic algorithms HIGHT and Present. Our implementations are the first reported of these block ciphers on FPGAs. Furthermore, they are the smallest block cipher implementations on FPGAs using only 117 and 91 slices respectively, which makes them comparable in size to stream cipher implementations. Both are less than half the size of the AES implementation by Chodowiec and Gaj without using block RAMs. Present’s throughput over area ratio of 240 Kbps/slice is similar to that of AES, however, HIGHT outperforms them by far with 720 Kbps/slice.


title: Pixel Recurrent Neural Networks

text: Modeling the distribution of natural images is a landmark problem in unsupervised learning. This task requires an image model that is at once expressive, tractable and scalable. We present a deep neural network that sequentially predicts the pixels in an image along the two spatial dimensions. Our method models the discrete probability of the raw pixel values and encodes the complete set of dependencies in the image. Architectural novelties include fast twodimensional recurrent layers and an effective use of residual connections in deep recurrent networks. We achieve log-likelihood scores on natural images that are considerably better than the previous state of the art. Our main results also provide benchmarks on the diverse ImageNet dataset. Samples generated from the model appear crisp, varied and globally coherent.


title: Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields

text: We present an approach to efficiently detect the 2D pose of multiple people in an image. The approach uses a nonparametric representation, which we refer to as Part Affinity Fields (PAFs), to learn to associate body parts with individuals in the image. The architecture encodes global context, allowing a greedy bottom-up parsing step that maintains high accuracy while achieving realtime performance, irrespective of the number of people in the image. The architecture is designed to jointly learn part locations and their association via two branches of the same sequential prediction process. Our method placed first in the inaugural COCO 2016 keypoints challenge, and significantly exceeds the previous state-of-the-art result on the MPII Multi-Person benchmark, both in performance and efficiency.


Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks


title: Conditional Generative Adversarial Nets

text: Generative Adversarial Nets [8] were recently introduced as a novel way to train generative models. In this work we introduce the conditional version of generative adversarial nets, which can be constructed by simply feeding the data, y, we wish to condition on to both the generator and discriminator. We show that this model can generate MNIST digits conditioned on class labels. We also illustrate how this model could be used to learn a multi-modal model, and provide preliminary examples of an application to image tagging in which we demonstrate how this approach can generate descriptive tags which are not part of training labels.


title: Efficiency of low power audio amplifiers and loudspeakers

text: In this paper we look at the load presented to audio amplifiers by real transducers. We consider the power losses in Class-AB and Class-D amplifier topologies, and determine that in order to predict efficiency it is necessary to consider the amplifier/transducer combination. The ability of the class-D amplifier to recycle quadrature load current offers new ways to improve efficiency. INTRODUCTION Class-D amplifiers are beginning to become viable alternatives to the Class-AB amplifier because of the reducing cost of suitable devices. There is particular interest in developing them for low power applications where their intrinsic efficiency advantages are important. The operation of Class-D amplifiers is very different to Class-AB amplifiers and this has implications for other components in the audio chain. Conventionally the performance of audio amplifiers is considered using a pure resistive load of four or eight ohms. The origin of this lies in the nominal impedance given to electro-magnetic loudspeakers. The true impedance of an electro-magnetic loudspeaker will vary over the operating frequency range, but the variability between individual real transducers makes the definition of a more realistic ‘bench-mark’ load impractical. Other audio transducers also have a complex impedance. Transducers which utilise piezo electric elements have a input impedance that is highly reactive. The load presented to the amplifier is almost entirely capacitive. The power output and efficiency of an amplifier are dependent load impedance and so the resistive load performance may not resemble to the operation of the amplifier in real situations. In this paper we will look at the true load presented to amplifiers by the transducer and derive a more accurate measure of overall efficiency. GENERAL AMPLIFIER EFFICIENCY The electrical efficiency of an amplifier is defined as the ratio of the power developed in the load to the power drawn from the DC supply. Using simple linear analysis we can determine the efficiency of amplifier output stages and the dependence of the efficiency on load parameters. In this section the following symbols are used; Vo Output voltage Vs Supply rail voltage RL Load resistance Ibias Class AB quiescent bias current φ Load phase angle Zload Load impedance L Class D filter inductance Rin Resistance of filter inductor RDson ‘On’ state resistance of switching devices fs Class D Switching frequency Class-AB resistive case A simple Class-AB output stage is shown in figure 1. A complementary pair of output devices operate over their linear region to amplify the signal. When the devices are operated in the linear region there will be current flowing through them whilst there is a voltage across them, this will give rise to power dissipation, and hence reduce efficiency. The devices also need a quiescent bias to reduce crossover distortion as one device takes over from the other. Load


title: Impact of a contemplative end-of-life training program: being with dying.

text:
OBJECTIVE
Health care professionals report a lack of skills in the psychosocial and spiritual aspects of caring for dying people and high levels of moral distress, grief, and burnout. To address these concerns, the "Being with Dying: Professional Training Program in Contemplative End-of-Life Care" (BWD) was created. The premise of BWD, which is based on the development of mindfulness and receptive attention through contemplative practice, is that cultivating stability of mind and emotions enables clinicians to respond to others and themselves with compassion. This article describes the impact of BWD on the participants.

METHODS
Ninety-five BWD participants completed an anonymous online survey; 40 completed a confidential open-ended telephone interview.

RESULTS
Four main themes-the power of presence, cultivating balanced compassion, recognizing grief, and the importance of self-care-emerged in the interviews and were supported in the survey data. The interviewees considered BWD's contemplative and reflective practices meaningful, useful, and valuable and reported that BWD provided skills, attitudes, behaviors, and tools to change how they worked with the dying and bereaved.

SIGNIFICANCE OF RESULTS
The quality of presence has the potential to transform the care of dying people and the caregivers themselves. Cultivating this quality within themselves and others allows clinicians to explore alternatives to exclusively intellectual, procedural, and task-oriented approaches when caring for dying people. BWD provides a rare opportunity to engage in practices and methods that cultivate the stability of mind and emotions that may facilitate compassionate care of dying patients, families, and caregivers.


title: The influence of geometrical deviations of electrical machine systems on the signal quality of the variable reluctance resolver

text: Variable reluctance resolvers are needed to regulate electrical machines with inverter control. Due to several issues, e.g. discrete windings in the stator and geometric tolerances in the assembly of the electrical machine, the rotors angular position cannot be acquired properly. The subject of this paper is a variable reluctance resolver model to investigate manufacturing induced geometrical tolerances of the electrical machine in means of rotor position. For this purpose, a block diagram of a stator segment is built, connecting 24 segments to one stator core using PLECS. The rotor can be set freely in shape and position. By varying a permeance block the rotation, i.e. the position dependent airgap, is mirrored. The proposed model allows a sensitivity analysis of the sensor signal according to geometrical changes and the absolute position in the electrical machine system. To evaluate the investigations, the results are verified by measurements on a sensor test bench. The simulation results show a similar behavior as the measurement. Although the values differ by a factor of five, this absolute difference is discussed by means of neglected boundary conditions.


title: Clinical practice guidelines for diagnosis of autism spectrum disorder in adults and children in the UK: a narrative review

text:
BACKGROUND
Research suggests that diagnostic procedures for Autism Spectrum Disorder are not consistent across practice and that diagnostic rates can be affected by contextual and social drivers. The purpose of this review was to consider how the content of clinical practice guidelines shapes diagnoses of Autism Spectrum Disorder in the UK; and investigate where, within those guidelines, social factors and influences are considered.

METHODS
We electronically searched multiple databases (NICE Evidence Base; TRIP; Social Policy and Practice; US National Guidelines Clearinghouse; HMIC; The Cochrane Library; Embase; Global health; Ovid; PsychARTICLES; PsychINFO) and relevant web sources (government, professional and regional NHS websites) for clinical practice guidelines. We extracted details of key diagnostic elements such as assessment process and diagnostic tools. A qualitative narrative analysis was conducted to identify social factors and influences.

RESULTS
Twenty-one documents were found and analysed. Guidelines varied in recommendations for use of diagnostic tools and assessment procedures. Although multidisciplinary assessment was identified as the 'ideal' assessment, some guidelines suggested in practice one experienced healthcare professional was sufficient. Social factors in operational, interactional and contextual areas added complexity to guidelines but there were few concrete recommendations as to how these factors should be operationalized for best diagnostic outcomes.

CONCLUSION
Although individual guidelines appeared to present a coherent and systematic assessment process, they varied enough in their recommendations to make the choices available to healthcare professionals particularly complex and confusing. We recommend a more explicit acknowledgement of social factors in clinical practice guidelines with advice about how they should be managed and operationalised to enable more consistency of practice and transparency for those coming for diagnosis.


title: Navigation of an omni-directional mobile robot with active caster wheels

text: This work deals with navigation of an omni-directional mobile robot with active caster wheels. Initially, the posture of the omni-directional mobile robot is calculated by using the odometry information. Next, the position accuracy of the mobile robot is measured through comparison of the odometry information and the external sensor measurement. Finally, for successful navigation of the mobile robot, a motion planning algorithm that employs kinematic redundancy resolution method is proposed. Through experiments for multiple obstacles and multiple moving obstacles, the feasibility of the proposed navigation algorithm was verified.


title: Examining a hate speech corpus for hate speech detection and popularity prediction

text: As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other facets of research, such as popularity of hate tweets.


title: Process integration of a 27nm, 16Gb Cu ReRAM

text: A 27nm 16Gb Cu based NV Re-RAM chip has been demonstrated. Novel process introduction to enable this technology include a Damascene Cell, Line-SAC Digit Lines filled with Cu, exhumed-silicided array contacts, raised epitaxial arrays, and high-drive buried access devices.


title: A Comparison of 10 Sampling Algorithms for Configurable Systems

text: Almost every software system provides configuration options to tailor the system to the target platform and application scenario. Often, this configurability renders the analysis of every individual system configuration infeasible. To address this problem, researchers have proposed a diverse set of sampling algorithms. We present a comparative study of 10 state-of-the-art sampling algorithms regarding their fault-detection capability and size of sample sets. The former is important to improve software quality and the latter to reduce the time of analysis. In a nutshell, we found that sampling algorithms with larger sample sets are able to detect higher numbers of faults, but simple algorithms with small sample sets, such as most-enabled-disabled, are the most efficient in most contexts. Furthermore, we observed that the limiting assumptions made in previous work influence the number of detected faults, the size of sample sets, and the ranking of algorithms. Finally, we have identified a number of technical challenges when trying to avoid the limiting assumptions, which questions the practicality of certain sampling algorithms.


title: Gaussian Process Regression Networks

text: We introduce a new regression framework, Gaussian process regression networks (GPRN), which combines the structural properties of Bayesian neural networks with the nonparametric flexibility of Gaussian processes. GPRN accommodates input (predictor) dependent signal and noise correlations between multiple output (response) variables, input dependent length-scales and amplitudes, and heavy-tailed predictive distributions. We derive both elliptical slice sampling and variational Bayes inference procedures for GPRN. We apply GPRN as a multiple output regression and multivariate volatility model, demonstrating substantially improved performance over eight popular multiple output (multi-task) Gaussian process models and three multivariate volatility models on real datasets, including a 1000 dimensional gene expression dataset.


title: Microplastics in the marine environment.

text: This review discusses the mechanisms of generation and potential impacts of microplastics in the ocean environment. Weathering degradation of plastics on the beaches results in their surface embrittlement and microcracking, yielding microparticles that are carried into water by wind or wave action. Unlike inorganic fines present in sea water, microplastics concentrate persistent organic pollutants (POPs) by partition. The relevant distribution coefficients for common POPs are several orders of magnitude in favour of the plastic medium. Consequently, the microparticles laden with high levels of POPs can be ingested by marine biota. Bioavailability and the efficiency of transfer of the ingested POPs across trophic levels are not known and the potential damage posed by these to the marine ecosystem has yet to be quantified and modelled. Given the increasing levels of plastic pollution of the oceans it is important to better understand the impact of microplastics in the ocean food web.


title: Machine Learning and Social Robotics for Detecting Early Signs of Dementia

text: This paper presents the EACare project, an ambitious multidisciplinary collaboration with the aim to develop an embodied system, capable of carrying out neuropsychological tests to detect early signs of dementia, e.g., due to Alzheimer’s disease. The system will use methods from Machine Learning and Social Robotics, and be trained with examples of recorded clinician-patient interactions. The interaction will be developed using a participatory design approach. We describe the scope and method of the project, and report on a first Wizard of Oz prototype.


title: The basic building blocks and evolution of CRISPR-CAS systems.

text: CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) is an adaptive immunity system in bacteria and archaea that functions via a distinct self/non-self recognition mechanism that involves unique spacers homologous with viral or plasmid DNA and integrated into the CRISPR loci. Most of the Cas proteins evolve under relaxed purifying selection and some underwent dramatic structural rearrangements during evolution. In many cases, CRISPR-Cas system components are replaced either by homologous or by analogous proteins or domains in some bacterial and archaeal lineages. However, recent advances in comparative sequence analysis, structural studies and experimental data suggest that, despite this remarkable evolutionary plasticity, all CRISPR-Cas systems employ the same architectural and functional principles, and given the conservation of the principal building blocks, share a common ancestry. We review recent advances in the understanding of the evolution and organization of CRISPR-Cas systems. Among other developments, we describe for the first time a group of archaeal cas1 gene homologues that are not associated with CRISPR-Cas loci and are predicted to be involved in functions other than adaptive immunity.


title: An algorithmic approach to multimodality midfacial rejuvenation using a new classification system for midfacial aging.

text: Midfacial aging is the result of the complex interplay between the osseous skeleton, facial retaining ligaments, soft tissues envelope, facial fat compartments, and the overlying skin elasticity. As a result of the many anatomic components involved in midfacial aging, the authors proposed a classification system based on distinct anatomic factors to direct surgical treatment. Evidence based data suggest that midface rejuvenation often requires a multimodality approach to obtain desired results, especially in patients with more advanced aging and poor tissue elasticity, or those with hypoplastic midfacial skeletal structure.


title: A Robust Mid-Level Representation for Harmonic Content in Music Signals

text: When considering the problem of audio-to-audio matching, determining musical similarity using low-level features such as Fourier transforms and MFCCs is an extremely difficult task, as there is little semantic information available. Full semantic transcription of audio is an unreliable and imperfect task in the best case, an unsolved problem in the worst. To this end we propose a robust mid-level representation that incorporates both harmonic and rhythmic information, without attempting full transcription. We describe a process for creating this representation automatically, directly from multi-timbral and polyphonic music signals, with an emphasis on popular music. We also offer various evaluations of our techniques. Moreso than most approaches working from raw audio, we incorporate musical knowledge into our assumptions, our models, and our processes. Our hope is that by utilizing this notion of a musically-motivated mid-level representation we may help bridge the gap between symbolic and audio research.


title: Roman-txt: forms and functions of roman urdu texting

text: In this paper, we present a user study conducted on students of a local university in Pakistan and collected a corpus of Roman Urdu text messages. We were interested in forms and functions of Roman Urdu text messages. To this end, we collected a mobile phone usage dataset. The data consists of 116 users and 346, 455 text messages. Roman Urdu text, is the most widely adopted style of writing text messages in Pakistan. Our user study leads to interesting results, for instance, we were able to quantitatively show that a number of words are written using more than one spelling; most participants of our study were not comfortable in English and hence they write their text messages in Roman Urdu; and the choice of language adopted by the participants sometimes varies according to who the message is being sent. Moreover we found that many young students send text messages(SMS) of intimate nature.


title: OCR and RFID enabled vehicle identification and parking allocation system

text: The available parking management systems require human efforts for recording entries of coming and leaving vehicles from parking in sheets. For huge parking it is difficult to keep track of the information. Use of Radio Frequency Identification known as RFID technology reduces human efforts and Optical Character Recognition known as OCR, enabled system will provide an automated system for parking management. And also it will provide the control over the access of parking space by the use of boom barriers. For huge parking it will be an effective system. Parking can be a commercial one or can be a Very Important Person (VIP) parking. Depending on the usage system can be used. Vehicle cannot be parked in parking if it is not registered. OCR acts as a solution for vehicles which are not registered. To keep track of the happenings in parking cameras are used. Places where automated systems are required, the proposed system is an answer. System combines the two strong technologies RFID and OCR.


title: The REVIVE (REal Women's VIews of Treatment Options for Menopausal Vaginal ChangEs) survey in Europe: Country-specific comparisons of postmenopausal women's perceptions, experiences and needs.

text:
OBJECTIVES
To achieve a better comprehension of the variability of perceptions, experiences and needs in terms of sexual and vaginal health in postmenopausal women (PMW) from four different European countries.

METHODS
An internet-based survey was conducted in Italy, Germany, Spain and the United Kingdom with a total surveyed population of 3768 PMW aged between 45 and 75 years.

RESULTS
The UK sample was significantly older, with almost a quarter of participants over 65 years of age, and had the highest proportion of women experiencing recent vulvar and vaginal atrophy (52.8%). The majority of Italian and Spanish participants were receiving VVA treatment, whereas in the UK only 28% of PMW were on medication. The most common menopausal symptom was vaginal/vulvar dryness, with almost 80% of participants reporting it in all the countries except the UK (48%). On the other hand, vaginal/vulvar irritation was more frequently reported in the UK (41%). The percentage of participants with a partner was lower in the UK (71%), as was the monthly rate of sexual activity (49%). In the UK, the proportion of participants who had seen a healthcare professional for gynaecological reasons in the last year was lower than in other countries (27% vs. ≥50%), as was the proportion who has discussed their VVA symptoms with them (45% vs. ∼67%). In this sense, UK PMW waited for a longer before asking for help (especially for pain with intercourse and dryness). The main issues relating to VVA treatment difficulties expressed by participants were administration route in the UK, efficacy in Germany, and side-effects in Italy.

CONCLUSIONS
Although all European women shared the same expectation of improving the quality of their sex lives, the opportunity for that varied among different countries in relation to the healthcare system and to the effective communication achieved with healthcare professionals when managing VVA.


title: Do burnout and work engagement predict depressive symptoms and life satisfaction? A three-wave seven-year prospective study.

text:
BACKGROUND
Burnout and work engagement have been viewed as opposite, yet distinct states of employee well-being. We investigated whether work-related indicators of well-being (i.e. burnout and work engagement) spill-over and generalize to context-free well-being (i.e. depressive symptoms and life satisfaction). More specifically, we examined the causal direction: does burnout/work engagement lead to depressive symptoms/life satisfaction, or the other way around?

METHODS
Three surveys were conducted. In 2003, 71% of all Finnish dentists were surveyed (n=3255), and the response rate of the 3-year follow-up was 84% (n=2555). The second follow-up was conducted four years later with a response rate of 86% (n=1964). Structural equation modeling was used to investigate the cross-lagged associations between the study variables across time.

RESULTS
Burnout predicted depressive symptoms and life dissatisfaction from T1 to T2 and from T2 to T3. Conversely, work engagement had a negative effect on depressive symptoms and a positive effect on life satisfaction, both from T1 to T2 and from T2 to T3, even after adjusting for the impact of burnout at every occasion.

LIMITATIONS
The study was conducted among one occupational group, which limits its generalizability.

CONCLUSIONS
Work-related well-being predicts general wellbeing in the long-term. For example, burnout predicts depressive symptoms and not vice versa. In addition, burnout and work engagement are not direct opposites. Instead, both have unique, incremental impacts on life satisfaction and depressive symptoms.