LLukas22/scidocs huggingface dataset:
Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems

IoT in industry is a rapidly developing area. Numerous IoT research and application projects have been done by universities or in joint industryuniversity consortia in recent years. However an important question to be further addressed is on value creation by IoT industry applications. IoT applications in the sense of this paper are solutions using IoT technologies to improve industrial manufacturing processes, enable new and efficient ways to operate production plants, create new service or supervision means for industrial installations, offer an optimized infrastructure, reduce operational cost or improve human safety in industrial areas. The present paper brings together Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems, 153–206. © 2013 River Publishers. All rights reserved. 154 IoT Applications — Value Creation for Industry experts from academia, research and industry offering a view on the IoT application in industrial environment, the challenges, expected evolution of IoT technology and use in future factories, on connected and holistic processes. The paper is intended to contribute to an IoT supported paradigm change in manufacturing, industrial service and over life sustainable industrial activities.
Wavelet packet transfer function modelling of nonstationary time series

This article shows how a non-decimated wavelet packet transform (NWPT) can be used to model a response time series, Yt , in terms of an explanatory time series, Xt . The proposed computational technique transforms the explanatory time series into a NWPT representation and then uses standard statistical modelling methods to identify which wavelet packets are useful for modelling the response time series. We exhibit S-Plus functions from the freeware WaveThresh package that implement our methodology. The proposed modelling methodology is applied to an important problem from the wind energy industry: how to model wind speed at a target location using wind speed and direction from a reference location. Our method improves on existing target site wind speed predictions produced by widely used industry standard techniques. However, of more importance, our NWPT representation produces models to which we can attach physical and scientific interpretations and in the wind example enable us to understand more about the transfer of wind energy from site to site.
Motivational incentives and methylphenidate enhance electrophysiological correlates of error monitoring in children with attention deficit/hyperactivity disorder

BACKGROUND
Children with attention deficit hyperactivity disorder (ADHD) are characterised by developmentally inappropriate levels of hyperactivity, impulsivity and/or inattention and are particularly impaired when performing tasks that require a high level of cognitive control. Methylphenidate (MPH) and motivational incentives may help improve cognitive control by enhancing the ability to monitor response accuracy and regulate performance accordingly.


METHODS
Twenty-eight children with DSM-IV ADHD (combined type) aged 9-15 years and pairwise-matched typically developing children (CTRL) performed a go/no-go task in which the incentives attached to performance on no-go trials were manipulated. The ADHD group performed the task off and on their usual dose of MPH. CTRL children performed the task twice but were never medicated. EEG data were recorded simultaneously and two electrophysiological indices of error monitoring, the error-related negativity (ERN) and error positivity (Pe) were measured. Amplitudes of each ERP were compared between diagnostic groups (CTRL, ADHD), medication days (Off MPH, On MPH) and motivational conditions (baseline - low incentive, reward, response cost).


RESULTS
Error rates were lower in the reward and response cost conditions compared with baseline across diagnostic groups and medication days. ERN and Pe amplitudes were significantly reduced in ADHD compared with CTRL, and were significantly enhanced by MPH. Incentives significantly increased ERN and Pe amplitudes in the ADHD group but had no effect in CTRL. The effects of incentives did not interact with the effects of MPH on either ERP. Effect sizes were computed and revealed larger effects of MPH than incentives on ERN and Pe amplitudes.


CONCLUSIONS
The findings reveal independent effects of motivational incentives and MPH on two electrophysiological markers of error monitoring in children with ADHD, suggesting that each may be important tools for enhancing or restoring cognitive control in these children.
Emotionally meaningful targets enhance orienting triggered by a fearful gazing face.

Studies investigating the effect of emotional expression on spatial orienting to a gazed-at location have produced mixed results. The present study investigated the role of affective context in the integration of emotion processing and gaze-triggered orienting. In three experiments, a face gazed nonpredictively to the left or right, and then its expression became fearful or happy. Participants identified (Experiments 1 and 2) or detected (Experiment 3) a peripheral target presented 225 or 525 ms after the gaze cue onset. In Experiments 1 and 3 the targets were either threatening (a snarling dog) or nonthreatening (a smiling baby); in Experiment 2 the targets were neutral. With emotionally-valenced targets, the gaze-cuing effect was larger when the face was fearful compared to happy--but only with the longer cue-target interval. With neutral targets, there was no interaction between gaze and expression. Our results indicate that a meaningful context optimizes attentional integration of gaze and expression information.
Efficient sanitization of informative association rules

Recent development in Privacy-Preserving Data Mining has proposed many efficient and practical techniques for hiding sensitive patterns or information from been discovered by data mining algorithms. In hiding association rules, current approaches require hidden rules or patterns to be given in advance. In addition, for Apriori algorithm based techniques [26], multiple scanning of the entire database is required. For direct sanitization of itemsets from transaction techniques [21], one scanning of each window in the database is processed independently. However, the accumulated information among windows is not considered. In this work, we propose an efficient one database scanning sanitization algorithm to sanitize informative association rules. For a given predicting item, an informative association rule set [16] is the smallest association rule set that makes the same prediction as the entire association rule set by confidence priority. A new data structure called pattern-inversion tree is proposed to store related information so that only one scan of database is required. The pre-process of finding these informative association rules can be integrated into the sanitization process. Numerical experiments show that the performance of the proposed algorithm is more efficient than previous algorithms with similar side effects. Running time complexity of the algorithm is presented and compared to similar algorithm with better complexity.
The potentiality of computer-assisted instruction towards ameliorating Iranian EFL learners' reading level

The fundamental objective behind the present study is to demonstrate the visible effect of ComputerAssisted Instruction upon Iranian EFL learners' reading performance, and to see if it has any impact upon this skill in the Iranian EFLeducational settings. To this end, a sample of 50 male and female EFL learners was drawn from an English language institute in Iran. After participating in a proficiency pretest, these participants were assigned into two experimental and control groups, 25 and 25, respectively. An independent sample t-test was administered to find out if there were salient differences between the findings of the two selected groups in their reading test. The key research question was to see providing learners with computer-assisted instruction during the processes of learning and instruction for learners would have an affirmative influence upon the improvement and development of their reading skill. The results pinpointed computer-assisted instruction users' performance was meaningfully higher than that of nonusers (DF 1⁄4 48, P < 05). The consequences revealed that computer-assisted language learning and computer technology application have resulted in a greater promotion of students' reading improvement. In other words, computer-assisted instruction users outperformed the nonusers. The research, therefore, highlights the conclusion that EFL learners' use of computer-assisted instruction has the potential to promote more effective reading ability. © 2016 Elsevier Ltd. All rights reserved.
Fast and reliable detection of power islands using transient signals

A new technique for fast detection of power islands in a distribution network, which uses transient signals generated during the islanding event is investigated. Performance comparison of several pattern recognition techniques in classifying the transient generating events as islanding or non-islanding is presented. Features for the classifiers are extracted using the Discrete Wavelet Transform of current signal transients. Using a set of extracted features from simulated current signals, (i) a decision tree classifier, (ii) a probabilistic neural network classifier, and (iii) a support vector machine classifier were trained for recognizing the transient patterns originating from the islanding events. The trained classifiers were then tested with unseen test current waveforms. The test results demonstrated that the investigated technique can potentially provide a new way for identification of islanding in distribution systems. The approach was then extended changing the feature set and sampling frequency. Proposed method is finally compared with an existing islanding detection technique.
Child development and emergent literacy.

Emergent literacy consists of the skills, knowledge, and attitudes that are developmental precursors to reading and writing. This article offers a preliminary typology of children's emergent literacy skills, a review of the evidence that relates emergent literacy to reading, and a review of the evidence for linkage between children's emergent literacy environments and the development of emergent literacy skills. We propose that emergent literacy consists of at least two distinct domains: inside-out skills (e.g., phonological awareness, letter knowledge) and outside-in skills (e.g., language, conceptual knowledge). These different domains are not the product of the same experiences and appear to be influential at different points in time during reading acquisition. Whereas outside-in skills are associated with those aspects of children's literacy environments typically measured, little is known about the origins of inside-out skills. Evidence from interventions to enhance emergent literacy suggests that relatively intensive and multifaceted interventions are needed to improve reading achievement maximally. A number of successful preschool interventions for outside-in skills exist, and computer-based tasks designed to teach children inside-out skills seem promising. Future research directions include more sophisticated multidimensional examination of emergent literacy skills and environments, better integration with reading research, and longer-term evaluation of preschool interventions. Policy implications for emergent literacy intervention and reading education are discussed.
Planning and Learning in Environments with Delayed Feedback

Case II: Deterministic transitions, continuous state Case III: “Mildly” stochastic trans., finite state: P(s,a,s’) ≥ 1 δ Case IV: Bounded-noise stochastic transitions, continuous state: st+1 = T(st, at) + wt , ||wt|| ≤ ∆ Planning and Learning in Environments with Delayed Feedback Thomas J. Walsh, Ali Nouri, Lihong Li, Michael L. Littman Rutgers Laboratory for Real Life Reinforcement Learning Computer Science Department, Rutgers University, Piscataway NJ
Best-Laid Schemes: A Psychology of Emotions.

List of figures and tables Acknowledgments Prologue Part I. Theory and Function: 1. The structure of emotions 2. Intuitive and empirical approaches to understanding 3. Rationality and emotions 4. Mutual plans and social emotions Part II. Conflict and Unpredictability: 5. Plans and emotions in fictional narrative 6. Stress and distress 7. Freud's cognitive psychology of intention: the case of Dora Part III. Enjoyment and Creativity: 8. Happiness 9. Putting emotions into words Epilogue Notes References Author index Subject index.
Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks

Scalability properties of deep neural networks raise key re search questions, particularly as the problems considered become larger and more challenging. This paper expands on the idea of conditional computation introd uce in [2], where the nodes of a deep network are augmented by a set of gating uni ts that determine when a node should be calculated. By factorizing the wei ght matrix into a low-rank approximation, an estimation of the sign of the pr -nonlinearity activation can be efficiently obtained. For networks using rec tifi d-linear hidden units, this implies that the computation of a hidden unit wit h an estimated negative pre-nonlinearity can be omitted altogether, as its val ue will become zero when nonlinearity is applied. For sparse neural networks, this c an result in considerable speed gains. Experimental results using the MNIST and SVHN d ata sets with a fully-connected deep neural network demonstrate the perf ormance robustness of the proposed scheme with respect to the error introduced b y the conditional computation process.
Rationale and design of the participant, investigator, observer, and data-analyst-blinded randomized AGENDA trial on associations between gene-polymorphisms, endophenotypes for depression and antidepressive intervention: the effect of escitalopram versus placebo on the combined dexamethasone-cortico

BACKGROUND
Endophenotypes are heritable markers, which are more prevalent in patients and their healthy relatives than in the general population. Recent studies point at disturbed regulation of the hypothalamic-pituitary-adrenocortical axis as a possible endophenotype for depression. We hypothesize that potential endophenotypes for depression may be affected by selective serotonin re-uptake inhibitor antidepressants in healthy first-degree relatives of depressed patients. The primary outcome measure is the change in plasma cortisol in the dexamethasone-corticotrophin releasing hormone test from baseline to the end of intervention.


METHODS
The AGENDA trial is designed as a participant, investigator, observer, and data-analyst-blinded randomized trial. Participants are 80 healthy first-degree relatives of patients with depression. Participants are randomized to escitalopram 10 mg per day versus placebo for four weeks. Randomization is stratified by gender and age. The primary outcome measure is the change in plasma cortisol in the dexamethasone-corticotrophin releasing hormone test at entry before intervention to after four weeks of intervention. With the inclusion of 80 participants, a 60% power is obtained to detect a clinically relevant difference in the primary outcome between the intervention and the placebo group. Secondary outcome measures are changes from baseline to four weeks in scores of: 1) cognition and 2) neuroticism. Tertiary outcomes measures are changes from baseline to four weeks in scores of: 1) depression and anxiety symptoms; 2) subjective evaluations of depressive symptoms, perceived stress, quality of life, aggression, sleep, and pain; and 3) salivary cortisol at eight different timepoints during an ordinary day. Assessments are undertaken by assessors blinded to the randomization group.
Predictors of quitting behaviour with special reference to nicotine dependence among adult tobacco-users in a slum of Burdwan district, West Bengal, India

BACKGROUND & OBJECTIVES
Information on predictors of quitting behaviour in adult tobacco users is scarce in Indian context. Hence, this study was undertaken to assess the intention of tobacco-users towards quitting and its predictors with reference to nicotine dependence.


METHODS
A community-based observational, cross-sectional study was conducted on 128 adult tobacco-users (89.8% male) with mean age of 41.1 ± 15.7 yr selected by complete enumeration method. Data were collected by interview using pre-designed, pre-tested schedule. Nicotine dependence was assessed by Fagerstrφm Test for Nicotine Dependence (FTND) questionnaire.


RESULT
Of the 128 users, 63.3 per cent had intention to quit. Majority of the tobacco users who did not intend to quit belonged to the age group of > 40 yr (66.0%), were illiterate (55.3%), started tobacco use at 11 - 15 yr of age (57.4%), had been using tobacco for 20 yr or more (70.2%), were daily tobacco users (91.5%), and highly dependent on nicotine (80.9%). Tobacco users having high FTND score and who started tobacco use early in life were 1.83 and 3.30 times more unintended to quit, respectively.


INTERPRETATION & CONCLUSIONS
Suitable plan for quitting should be developed depending on the FTND score of an individual, the most important determinant of quitting that would be beneficial for categorization of the treatment leading to successful quitting.
Seabed properties analysis from multibeam backscatter data

Acoustic classification of seabed using multibeam echosounder data has a range of applications and processing methodologies to create seabed models. The main focus on this paper is to achieve a reliable model of seabed grain size distribution. Multibeam backscatter data from Kongsberg EM3000 was analyzed on CARIS HIPS and SIPS software with Geocoder engine. This algorithm uses angular analysis to generate seabed model. Each patch defined by software user is analyzed for port and starboard side and as final results it gives not only the seabed grain size distribution but also properties such as velocity, loss, density, roughness, volume and impedance. Data was acquired on a glaciomarine environment, which represents a major challenge on defining seabed grain size distribution. As a final result, all final data given by Geocoder algorithm were correlated on Matlab to evaluate reliability of properties distribution on seabed.
High-Dose Intravenous Vitamin C Combined with Cytotoxic Chemotherapy in Patients with Advanced Cancer: A Phase I-II Clinical Trial

BACKGROUND
Biological and some clinical evidence suggest that high-dose intravenous vitamin C (IVC) could increase the effectiveness of cancer chemotherapy. IVC is widely used by integrative and complementary cancer therapists, but rigorous data are lacking as to its safety and which cancers and chemotherapy regimens would be the most promising to investigate in detail.


METHODS AND FINDINGS
We carried out a phase I-II safety, tolerability, pharmacokinetic and efficacy trial of IVC combined with chemotherapy in patients whose treating oncologist judged that standard-of-care or off-label chemotherapy offered less than a 33% likelihood of a meaningful response. We documented adverse events and toxicity associated with IVC infusions, determined pre- and post-chemotherapy vitamin C and oxalic acid pharmacokinetic profiles, and monitored objective clinical responses, mood and quality of life. Fourteen patients were enrolled. IVC was safe and generally well tolerated, although some patients experienced transient adverse events during or after IVC infusions. The pre- and post-chemotherapy pharmacokinetic profiles suggested that tissue uptake of vitamin C increases after chemotherapy, with no increase in urinary oxalic acid excretion. Three patients with different types of cancer experienced unexpected transient stable disease, increased energy and functional improvement.


CONCLUSIONS
Despite IVC's biological and clinical plausibility, career cancer investigators currently ignore it while integrative cancer therapists use it widely but without reporting the kind of clinical data that is normally gathered in cancer drug development. The present study neither proves nor disproves IVC's value in cancer therapy, but it provides practical information, and indicates a feasible way to evaluate this plausible but unproven therapy in an academic environment that is currently uninterested in it. If carried out in sufficient numbers, simple studies like this one could identify specific clusters of cancer type, chemotherapy regimen and IVC in which exceptional responses occur frequently enough to justify appropriately focused clinical trials.


TRIAL REGISTRATION
ClinicalTrials.gov NCT01050621.
Farrow-Structure-Based Reconfigurable Bandpass Linear-Phase FIR Filters for Integer Sampling Rate Conversion

A class of Farrow-structure-based reconfigurable bandpass FIR filters for integer sampling rate conversion is introduced. The converters are realized in terms of a number of fixed linear-phase FIR subfilters and two sets of reconfigurable multipliers that determine the passband location and the conversion factor, respectively. Both Mth-band and general FIR filters can be realized, and the filters work equally well for any integer factor and passband location. Design examples are included, demonstrating their efficiency compared with modulated regular filters. In addition, in contrast to regular filters, the proposed ones have considerably fewer filter coefficients that need to be determined in the filter design process.
Credibility and trust of information in online environments : The use of cognitive heuristics

Networked digital media present new challenges for people to locate information that they can trust. At the same time, societal reliance on information that is available solely or primarily via the Internet is increasing. This article discusses how and why digitally networked communication environments alter traditional notions of trust, and presents research that examines how information consumers make judgments about the credibility and accuracy of information they encounter online. Based on this research, the article focuses on the use of cognitive heuristics in credibility evaluation. Findings from recent studies are used to illustrate the types of cognitive heuristics that information consumers employ when determining what sources and information to trust online. The article concludes with an agenda for future research that is needed to better understand the role and influence of cognitive heuristics in credibility evaluation in computer-mediated communication contexts. © 2013 Elsevier B.V. All rights reserved.