nils-herrmann/clean_scirepeval huggingface dataset:
Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
Venue: SIGIR

Sponsored search represents a major source of revenue for web search engines. The advertising model brings a unique possibility for advertisers to target direct user intent communicated through a search query, usually done by displaying their ads alongside organic search results for queries deemed relevant to their products or services. However, due to a large number of unique queries, it is particularly challenging for advertisers to identify all relevant queries. For this reason search engines often provide a service of advanced matching, which automatically finds additional relevant queries for advertisers to bid on. We present a novel advance match approach based on the idea of semantic embeddings of queries and ads. The embeddings were learned using a large data set of user search sessions, consisting of search queries, clicked ads and search links, while utilizing contextual information such as dwell time and skipped ads. To address the large scale nature of our problem, both in terms of data and vocabulary size, we propose a novel distributed algorithm for training of the embeddings. Finally, we present an approach for overcoming a cold start problem associated with new ads and queries. We report results of editorial evaluation and online tests on actual search traffic. The results show that our approach significantly outperforms baselines in terms of relevance, coverage and incremental revenue. Lastly, as part of this study, we open sourced query embeddings that can be used to advance the field.
Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
Venue: ArXiv

Sponsored search represents a major source of revenue for web search engines. This popular advertising model brings a unique possibility for advertisers to target users' immediate intent communicated through a search query, usually by displaying their ads alongside organic search results for queries deemed relevant to their products or services. However, due to a large number of unique queries it is challenging for advertisers to identify all such relevant queries. For this reason search engines often provide a service of advanced matching, which automatically finds additional relevant queries for advertisers to bid on. We present a novel advanced matching approach based on the idea of semantic embeddings of queries and ads. The embeddings were learned using a large data set of user search sessions, consisting of search queries, clicked ads and search links, while utilizing contextual information such as dwell time and skipped ads. To address the large scale nature of our problem, both in terms of data and vocabulary size, we propose a novel distributed algorithm for training of the embeddings. Finally, we present an approach for overcoming a cold start problem associated with new ads and queries. We report results of editorial evaluation and online tests on actual search traffic. The results show that our approach significantly outperforms baselines in terms of relevance, coverage, and incremental revenue. Lastly, we opensource learned query embeddings to be used by researchers in computational advertising and related fields.
Chirped photonic crystal with different symmetries for asymmetric light propagation

In the present paper, we have carried out analysis of asymmetric light propagation in a chirped photonic crystal waveguide. The designed structures have hexagonal arrangement and square arrangement of silicon rods in air substrate. Dimensions of the defect rods are tailored, so that the proposed design structure works as an optical isolator. The transmission analysis of the structure reveals that it can act as an optical diode. We have plotted the extinction ratio and transmission analysis graphs for the structure, and it has been observed that the maximum output is obtained for telecom wavelength of 1.55 mm. Dispersion curves are obtained using the plane wave expansion method, and the transmission is simulated using finite element method. The proposed structures are applicable for photonic integrated circuits due to their simple and clear operating principle.
Deep multi context Network for FINE GRAINED VISUAL RECOGNITION
Venue: 2016 IEEE International Conference on Multimedia Expo Workshops (ICMEW)

In this paper, we tackle the FINE GRAINED VISUAL RECOGNITION problem by proposing a deep multi context framework. We employ deep Convolutional Neural Networks to model features of objects in images. Global context and local context are both taken into consideration, and are jointly modeled in a unified multi context deep learning framework. To cleanse the relatively dirty data for training, a regional proposal method is designed to make the multi context modeling suited for fine grained visual recognition in the real world. Furthermore, recently proposed contemporary deep models are used, and their combination is investigated. Our approaches are evaluated on MSR IRC 2016 and further assessed on the more complex validation set. The results show significant and consistent improvements over the baseline.
Sensor programming and concept implementation of a temperature monitoring system, using Arduino as prototyping platform
Venue: 2016 20th International Conference on System Theory, Control and Computing (ICSTCC)

The present work reports the programming paradigms that have been developed for a temperature monitoring system able to provide accurate data regarding food temperatures inside refrigerated vehicles and alert the driver accordingly, in relation to which temperature states are encountered. The mentioned solution is designed to be cost efficient and versatile, so that it can compete with available solutions. This paper also contributes with explanations of ideas behind our coding approach and solutions to encountered problems, along with a detailed insight into the flow of execution of our program.
Online wastewater monitoring system using solid state sensor
Venue: 2016 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS)

Water and wastewater monitoring management is a task of paramount importance for the environmental control operations in the framework of the Adaptive Water Management policies enforced by the current EU legislation. Water resources management, on one side, and efficient water/wastewater treatment and control operations, on the other, must be carried out timely and synergistically for best results. It is well known that conventional field sampling operations condition significantly data reliability from both qualitative and quantitative aspects. To overcome this problem, speditive field analysis, carried out by the use of low cost devices with solid state gas sensors (e nose) may offer a solution to the sampling, transport and deferred laboratory operations. The proposed devices do not require consumable and may be easily connected to data acquisition network.
An asymmetrically dimethylarginated nuclear 90 kDa protein (p90aDMA) induced by interleukin (IL) 2, IL 4 or IL 6 in the tumor microenvironment is selectively degraded by autophagy.
Venue: International journal of oncology

Protein arginine methylation is a common posttranslational modification resulting in the generation of asymmetric dimethylarginine (aDMA) and symmetric dimethylarginine (sDMA) Currently, the regulation of aDMA or sDMA by hypoxia, nutrient stavation or cytokines in the tumor microenvironment remains largely unknown. Here we show that p90aDMA, p70aDMA and p90sDMA, endogenous proteins containing aDMA or sDMA with mass 70 or 90 kDa, were widely and dominantly expressed in breast cancer cell lines. Notably, it was p90aDMA rather than p90sDMA that accumulated in the nucleus upon stimulation of cancer cells with interleukin (IL) 2, IL 4, IL 6 but not IL 8. In addition, the p90aDMA accumulation could be inhibited after treatment with a global methyltrasferase inhibitor, adenosine 2',3' dialdehyde (AdOx) It seemed that some endogenous proteins in cancer cells were asymmetrically arginine methylated upon exposure to some cytokines. Furthermore, endogenous proteins of aDMA, such as p90aDMA and p70aDMA, were degraded in response to hypoxia, nutrient starvation and rapamycin treatment in breast and cervical cancer cells. IL 2/4/6 slightly increased basal autophagy but slightly decreased the rapamycin induced autophagy in cancer cells, suggesting that IL 2/4/6 and autophagy inducers play distinct roles in the regulation of aDMA of proteins. Conversely, rapamycin accumulated p90sDMA in MDA MB 231 and MCF 7 cells. Taken together, our results add a new dimension to the complexity of arginine methylated regulation in response to various stimuli and provide the first evidence that aDMA serves as one specific degradation signal of selective autophagy.
Proactive interference and concurrent inhibitory processes do not differentially affect item and associative recognition: Implication for the age related associative memory deficit
Venue: Memory

Previous studies have suggested an associative deficit hypothesis [Naveh Benjamin, M. (2000) Adult age differences in memory performance: Tests of an associative deficit hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 1170 1187] to explain age related episodic memory declines. The hypothesis attributes part of the deficient episodic memory performance in older adults to a difficulty in creating and retrieving cohesive episodes. In this article, we further evaluate this hypothesis by testing two alternative processes that potentially mediate associative memory deficits in older adults. Four experiments are presented that assess whether failure of inhibitory processes (proactive interference in Experiments 1 and 2) and concurrent inhibition (in Experiments 3 and 4) are mediating factors in age related associative deficits. The results suggest that creating conditions that require the operation of inhibitory processes, or that interfere with such processes, cannot simulate associative memory deficit in older adults. Instead, such results support the idea that associative memory deficits reflect a unique binding failure in older adults. This failure seems to be independent of other cognitive processes, including inhibitory and other resource demanding processes.
Random forest in remote sensing: A review of applications and future directions

A random forest (RF) classifier is an ensemble classifier that produces multiple decision trees, using a randomly selected subset of training samples and variables. This classifier has become popular within the remote sensing community due to the accuracy of its classifications. The overall objective of this work was to review the utilization of RF classifier in remote sensing. This review has revealed that RF classifier can successfully handle high data dimensionality and multicolinearity, being both fast and insensitive to overfitting. It is, however, sensitive to the sampling design. The variable importance (VI) measurement provided by the RF classifier has been extensively exploited in different scenarios, for example to reduce the number of dimensions of hyperspectral data, to identify the most relevant multisource remote sensing and geographic data, and to select the most suitable season to classify particular target classes. Further investigations are required into less commonly exploited uses of this classifier, such as for sample proximity analysis to detect and remove outliers in the training samples.
Des mots, des couleurs et des octaedres

Warum rot rot, und blau blau ist, weis kein Mensch.  Nos experiences visuelles sont faites de couleurs. Le monde que nous voyons est un monde colore, et il y a meme un sens a dire qu'il est colore avant toute autre chose. Pour m'apparaitre, la lune doit dessiner une petite forme ronde dans le ciel nocturne pour m'apparaitre, la petite forme ronde doit avoir une certaine couleur, qui contraste avec celle du ciel nocturne. Des couleurs, pourtant, il semble a premiere vue n'y avoir pas grand chose a dire. Peut etre Margot voit elle rouge ce que Manon voit vert et vert ce que Manon voit rouge. Peut etre son spectre chromatique est il exactement l'inverse de celui de Manon quelle definition pourra alors lui donner tort ou raison Y a t il meme un sens a dire qu'elle a tort ou raison d'appeler rouge ce que Manon appelle vert A premiere vue, les couleurs semblent des qualites trop simples et primitives pour qu'il soit possible d'en dire quelque chose et, a plus forte raison, d'avoir des connaissances a leur sujet. Pourtant, nous savons avec evidence que tel n'est pas le cas. Si je dis a Margot que la couleur de la lune est moins claire que celle du ciel environnant, elle me repondra que j'ai tort. Sa reponse semblera tres naturelle et la plupart l'approuveront. Ce qui suggere que, quelque simples et primitives que soient les couleurs, il y a neanmoins quelque chose a en dire. Comment est ce possible Cela a manifestement quelque chose
Mastering AutoCAD 2017 and AutoCAD LT 2017

The bestselling guide to AutoCAD, updated and expanded with new video instruction Mastering AutoCAD 2017 and AutoCAD LT 2017 is the premier guide to the world's leading CAD program. With clear explanation, focused examples, and step by step instruction, this guide walks you through everything you need to know to use AutoCAD 2017 and AutoCAD LT 2017 effectively. From basic drafting tools to 3D modeling, this book leaves no stone unturned in exploring the full repertoire of AutoCAD capabilities. Hands on instruction allows for more productive learning, and over an hour's worth of video provides clarification of crucial techniques. Effective as both a complete tutorial and a dip in reference, the broadly applicable concepts and instructions will appeal to AutoCAD users across industries and abilities. This new edition has been thoroughly updated to align with the software's latest features and capabilities, giving you a one stop resource for getting up to speed. AutoCAD is the leading software for 2D and 3D technical drawings, and AutoCAD LT makes the software's tremendous functionality more accessible for smaller businesses and individuals. This guide shows you how to take full advantage of this powerful design platform, with expert guidance every step of the way. Get acquainted with the interface and master basic tools Utilize hatches, fields, cures, solid fills, dynamic blocks, and more Explore 3D modeling and imaging for more holistic design Customize the AutoCAD workflow to suit your needs Whether you're learning AutoCAD for the first time, upgrading from a previous version, or preparing for a certification exam, you need a thorough reference designed for the way professionals work.  2017 and AutoCAD LT 2017 is your ideal guide, with complete tutorials, video instruction, and expert advice.
Safety and efficacy of aneurysm treatment with WEB: results of the WEBCAST study.
Venue: Journal of neurosurgery

OBJECT WEB is an innovative intrasaccular treatment for intracranial aneurysms. Preliminary series have shown good safety and efficacy. The WEB Clinical Assessment of Intrasaccular Aneurysm Therapy (WEBCAST) trial is a prospective European trial evaluating the safety and efficacy of WEB in wide neck bifurcation aneurysms.  Patients with wide neck bifurcation aneurysms for which WEB treatment was indicated were included in this multicentergood clinical practices study. Clinical data including adverse events and clinical status at 1 and 6 months were collected and independently analyzed by a medical monitor. Six month follow up digital subtraction angiography was also performed and independently analyzed by a core laboratory. Success was defined at 6 months as complete occlusion or stable neck remnant, no worsening in angiographic appearance from postprocedure, and no retreatment performed or planned.  Ten European neurointerventional centers enrolled 51 patients with 51 aneurysms. Treatment with WEB was achieved in 48 of 51 aneurysms (94.1% Adjunctive implants (coils/stents) were used in 4 of 48 aneurysms (8.3% Thromboembolic events were observed in 9 of 51 patients (17.6% resulting in a permanent deficit (modified Rankin Scale [mRS] Score 1) in 1 patient (2.0% Intraoperative rupture was not observed. Morbidity (mRS score 2) and mortality were 2.0% (1 of 51 patients, related to rupture status on entry to study) and 0.0% at 1 month, respectively. Success was achieved at 6 months in 85.4% of patients treated with WEB: 23 of 41 patients (56.1% had complete occlusion, 12 of 41 (29.3% had a neck remnant, and 6 of 41 (14.6% had an aneurysm remnant.  The WEBCAST study showed good procedural and short term safety of aneurysm treatment with WEB and good 6 month anatomical results.
Frequent Pattern Mining
Venue: Encyclopedia of Algorithms

Pattern mining is a fundamental problem in data mining. The problem is to find all the patterns appearing in the given database frequently. For a set E D f1; ng of items, an itemset (also called a pattern) is a subset of E. Let D be a given database composed of transactions R1; Rm, Ri E. For an itemset P an occurrence of P is a transaction of D such that P R, and the occurrence set Occ.P is the set of occurrences of P The frequency of P also called support, is jOcc.P /j and denoted by frq.P For a given constant called minimum support, an itemset P is frequent if frq.P For given a database and a minimum support, frequent itemset mining is the problem of enumerating all frequent itemsets in D.
Distributed Variational Bayesian Algorithms Over Sensor Networks
Venue: IEEE Transactions on Signal Processing

Distributed inference/estimation in Bayesian framework in the context of sensor networks has recently received much attention due to its broad applicability. The variational Bayesian (VB) algorithm is a technique for approximating intractable integrals arising in Bayesian inference. In this paper, we propose two novel distributed VB algorithms for general Bayesian inference problem, which can be applied to a very general class of conjugate exponential models. In the first approach, the global natural parameters at each node are optimized using a stochastic natural gradient that utilizes the Riemannian geometry of the approximation space, followed by an information diffusion step for cooperation with the neighbors. In the second method, a constrained optimization formulation for distributed estimation is established in natural parameter space and solved by alternating direction method of multipliers (ADMM) An application of the distributed inference/estimation of a Bayesian Gaussian mixture model is then presented, to evaluate the effectiveness of the proposed algorithms. Simulations on both synthetic and real datasets demonstrate that the proposed algorithms have excellent performance, which are almost as good as the corresponding centralized VB algorithm relying on all data available in a fusion center.
A novel distributed variational approximation method for density estimation in sensor networks

In this paper, a consensus filter based distributed variational Bayesian (CFBDVB) algorithm is developed for distributed density estimation. Sensor measurements are assumed to be statistically modeled by a finite mixture model for which the CFBDVB algorithm is used to estimate the parameters, including means, covariances and weights of components. This algorithm is based on three steps: (1) calculating local sufficient statistics at every node, (2) estimating a global sufficient statistics vector using a consensus filter, (3) updating parameters of the finite mixture model based on the global sufficient statistics vector. Scalability and robustness are two advantages of the proposed algorithm. Convergence of the CFBDVB algorithm is also proved using Robbins Monro stochastic approximation method. Finally, to verify performance of CFBDVB algorithm, we perform several simulations of sensor networks. Simulation results are very promising.
Billboard Advertising and Customer Attention: A Pakistani Perspective

Billboard advertising plays an important role and it should be placed on right place at right moment. It is a best way for introducing or advertising your business products because it's an easiest marketing tool to communicate with different people, you don't need to find your customers, and customer will find your advertising. The objective of this study is to determine what features should be used to attract customer while making billboard ads. This study explain billboard advertising and their impact on consumer attention, whether the target audience gives importance to billboard or not, and to understand the element that are necessary to create an effective billboard to attract customers attention. Variables used in this study include Color size, Celebrity Images, Brand Image Logo and Texture Messages. A sample of 200 respondents has been taken. The primary data of the study is collected personally with the help of well structured and closed ended questionnaire and survey based on 200 respondents. Researcher conducted one tail T Test and used the frequencies too. The SPSS program was used in conducting the analysis. All these variables have positive impact on customer attention. Effective advertising through billboard should be based on variety, reality, quality and attractiveness. The results show that the chosen variables have an impact on billboard advertisement and hence the objective of this research met. This research is beneficial for all consumers as well as for companies that use to promote their products through this medium. Further research will be done by interviewing more consumers of all ages and advertising experts so that more accuracy in the results will be generated, moreover researchers may specify the industries or sectors to get the targeted results.
"Your Father Knows that You Need All of This" Divine Fatherhood as Socio Ethical Impetus in Q's Formative Stratum

The observation that the Q people understood themselves as a new symbolic family, with God as Father, is certainly not new in Q studies. Likewise, it is not uncommon for an interpreter to mention during her analysis of an individual Q text that the instruction in question is motivated by imitatio Dei rhetoric. However, the pervasiveness of this link between Q's theology of divine fatherhood and its socio ethical programme has not received enough attention in Q scholarship. In an attempt to address this deficiency, the current article argues that the idea of divine fatherhood is the primary paradigm that informs, determines and motivates the alternative socio ethical programme of Q's formative stratum. More than being just an interesting observation in relation to some Q texts, divine fatherhood and imitatio Dei rhetoric are central to the radical socio ethical programme of Q's formative stratum. After an overview of Q's self perception as God's symbolic family, the article turns to the analysis of specific texts in Q's formative stratum, first considering the theme of divine fatherhood, and then considering its socio ethical relevance. These discussions are finally related to the notion of "mutual mothering," with some implications for our understanding of women in the Q movement.