Miracle-dz/UniFAR-FTUs huggingface dataset:
A Joint Optimization of Incrementality and Revenue to Satisfy both the Advertiser and the Publisher / Ad Network

It has been a long-standing goal in advertising to reduce wasted advertising costs due to advertising to people who are unlikely to buy, as well as to those who would make a purchase whether they saw an advertisement or not. The ideal audience for the advertiser are those incremental individuals who would buy if shown an ad, and would not buy, if not shown the ad. On the other hand, for publishers and ad networks who are paid when the user clicks or buys, revenue may be maximized by showing ads to those users who most likely to click or purchase. To satisfy both advertisers’ and publishers’ goals we need to optimize both the number of incremental purchases and the publisher’s revenue. We show analytically and empirically that optimizing only one of these objectives may result in the inferior performance in the other one. We examine several novel and previously known machine learning algorithms and training schemes that try to satisfy both advertisers’ and publishers’ goals. Based on the results of experiments with a publicly available e-mail marketing dataset and in-house display advertising datasets, we identify combinations of algorithms and training examples that have the best performance both in terms of the number of incremental purchases and in terms of the publisher’s revenue. Our additional technical contributions include: i) a novel theoretically-justified training scheme for optimizing both the number of incremental purchases and the overall number of purchases; ii) a performance guarantee for incrementality modeling.
An Empirical Study on the Affecting Factors of White-Collar Consumer Online Buying in High-Tech Industry Cluster of China

We develop a theoretical framework describing affecting factors of white-collar consumer online buying, and test the proposed model using a SEM technique on Internet white-collar consumer purchasing behavior data collected via a survey. The objective of this study is to assess the impact of third-party-provided electronic commerce assurance on consumerspsila likelihood to purchase products and services online and their concerns about perceived risk, cost for the source of information, e-service quality and customer involvement. Through an investigation to the white-collar consumer in high-tech industry cluster of China, the study found that online consumer perceived risk would negatively relate to the customer satisfaction and customer loyalty, and online consumer satisfaction and loyalty are positively influenced by the cost for the source of information, online consumer satisfaction is positively influenced by the e-service quality, online consumer satisfaction and loyalty is positively associated with involvement, online consumer satisfaction and loyalty have positive correlation, online consumer loyalty is positively influenced by the e-service quality. However, the e-service quality had no prominent influence on the online consumer loyalty. Research findings offer some theoretical insight into the decision making of online consumers and suggest management implications for online vendors and third-party EC assurance providers such as accountants or consumer unions.
Countering Walter Block's "Heroic" Private Counterfeiter

IN HIS PROVOCATIVE BOOK, Defending the Undefendable, Walter Block (1976) presents a cast of seemingly nefarious characters, such as the slumlord, the prostitute, and the moneylender, whose actions, he shows, are harmless and even beneficial when looked at from a free-market and natural law perspective. There is, however, one case where his defense is more than a little controversial: that of the private counterfeiter. According to Block, an individual counterfeiter who creates his own notes commits no real crime because money issued by the government is itself counterfeit, and counterfeiting counterfeit money is analogous to seizing stolen goods from thieves. Block points out that under the natural law, if B steals property from A, and C takes the stolen property away from B, C is not guilty of theft if the property in question cannot be returned to A; for example, if A no longer exists or cannot be found. Block contends that a similar proposition can be applied to counterfeiting, where B are the government and banking institutions, who throughout history have fraudulently misrepresented their notes as being equivalent to genuine money such as gold and silver, A are the past depositors of these precious metals who were the original victims of B’s counterfeiting fraud prior to the establishment of a universal fiat currency,
Using domain knowledge in knowledge discovery

With the explosive growth of the size of databases, many knowledge discovery applications deal with large quantities of data. There is an urgent need to develop methodologies which will allow the applications to focus search to a potentially interesting and relevant portion of the data, which can reduce the computational complexity of the knowledge discovery process and improve the interestingness of discovered knowledge. Previous work on semantic query optimization, which is an approach to take advantage of domain knowledge for query optimization, has demonstrated that significant cost reduction can be achieved by reformulating a query into a less expensive yet equivalent query which produces the same answer as the original one. In this paper, we introduce a method to utilize three types of domain knowledge in reducing the cost of finding a potentially interesting and relevant portion of the data while improving the quality of discovered knowledge. In addition, we propose a method to select relevant domain knowledge without an exhaustive search of all domain knowledge. The contribution of this paper is that we lay out a general framework for using domain knowledge in the knowledge discovery process effectively by providing guidelines.
A Perceptually Motivated Method to Control Reconstruction Errors in Gradient-based Image Compositing

We propose a simple algorithm to control the spatial location of reconstruction errors inherent in gradient-based image compositing. We build upon the classical Poisson equation and add a weighting term that controls where reconstruction errors can occur. We define this term in such a way that residuals are mainly located in textured regions where they are less visible. Our approach is independent of howthecompositedgradientfieldhasbeenbuiltandiscomplementary to the methods that focus on this aspect. Our approach retains the simplicity of the traditional Poisson equation while producing more pleasing composites.
Cosmological consequences of scalar mesons from gauge/gravity correspondence

We consider the spectrum of mesons for the gauge theory dual to a supergravity configuration of intersecting D3/D7 branes, and use the expression for the Lagrangian of the scalar mesons to compute explicitly the Lagrangian for the lightest states in the infrared limit. Assuming that the matter content of this gauge theory is part of a hidden sector, which interacts with the standard model only via gravity, we explore the cosmological consequences of these lightest scalar mesons for a FRW universe. We show that phantom fields may appear naturally in this kind of scenarios.
A numerical investigation of head waves and leaky modes in fluid- filled boreholes.

Although synthetic borehole seismograms can be computed for a wide range of borehole conditions, the physical nature of shear and compressional head waves in fluid‐filled boreholes is poorly understood. This paper presents a series of numerical experiments designed to explain the physical mechanisms controlling head‐wave propagation in boreholes. These calculations demonstrate the existence of compressional normal modes equivalent to shear normal modes, or pseudo‐Rayleigh waves, with sequential cutoff frequencies spaced between the cutoff frequencies for the shear normal modes. Major contributions to head‐wave spectra occur in discrete peaks at frequencies just below mode cutoff for both compressional and shear modes. This result is confirmed by calculations with synthetic waveforms at frequencies corresponding to mode cutoff, and by branch‐cut integrals designed to yield independent spectra for the compressional mode. For soft formations where shear velocity falls below acoustic velocity in the borehole .
Hypermedia research at C&C research labs, NEC USA

In this organization overview, we explain our approach to next generation hypermedia environment. We discuss the importance of Computer-Human Interaction and ways to provide high level authoring and augmentation capabilities as key components for the environment. CHI will contribute to integrating hypermedia functions with media contents for improving information accessibility. Implemented systems such as multimedia stroryboarding tools demonstrate their advanced hypermedia capabilities.
A New Modified Approach to Rough Set Feature Selection

Extracting useful information from a huge data collection is an important and challenging issue. Feature selection (FS) refers to the problem of selecting minimal relevant features which produce the most predictive outcome and retaining the original meaning of the features after reduction. One of the successful techniques for feature selection from datasets is the rough set theory (RST). This paper starts with an outline of the fundamental concepts behind Rough set related to FS methods. Feature selection algorithms like Quickreduct (QR), Relative Reduct (RR), presented here. One new modified method based on Lower approximation base feature selection i.e. Improved Quickreduct algorithm is proposed which selects minimal subset of features and execution time is better than the original methods. This is performed using a stopping criterion with a threshold and with the concept of significance of features. A comparative study of the algorithms and the experiments are carried out on eight public domain datasets available in UCI machine learning repository to analyze the performance study.
Quantum dot-based immunofluorescent imaging and quantitative detection of TOP2A and prognostic value in triple-negative breast cancer

Background Topoisomerase 2 alpha (TOP2A) is a key enzyme in DNA replication and a target of various cytotoxic agents including anthracyclines. Previous studies evaluating the predictive and prognostic values of TOP2A in breast cancer are contradictory, likely secondary to the use of both different detection methods and different cutoff thresholds for positive status. Our own studies have previously confirmed the advantages of quantum dot-based nanotechnology for quantitative analysis of biomarkers relative to conventional immunohistochemistry (IHC). This study was designed to 1) assess the expression of TOP2A, 2) investigate the relationship between TOP2A expression and major clinical pathological parameters, and 3) evaluate the prognostic value of TOP2A by quantum dot-based immunofluorescent imaging and quantitative analytical system (QD-IIQAS) in triple-negative breast cancer (TNBC). Patients and methods TOP2A expression in 145 TNBC specimens was detected using IHC and QD-IIQAS, and a comparative analysis of the two methods was conducted, including an exploration of the relationship between TOP2A expression and major clinical pathological parameters in TNBC. The prognostic value of TOP2A in TNBC was assessed. Results A similar antigen localization, a high correlation of staining rates (r=0.79), and a high agreement of measurements (κ=0.763) of TOP2A expression in TNBC were found by QD-IIQAS and conventional IHC (cutoff: 45.0 and 0.45, respectively). TOP2A was significantly higher in larger tumors (P=0.002), higher grade tumors (P=0.005), and lymph node positive patients (P<0.001). The 5-year disease-free survival (5-DFS) of the high and low TOP2A subgroups was significantly different for both QD-IIQAS and IHC (P<0.001, log-rank test for both). TOP2A expression was an independent predictor of survival in TNBC (P=0.001). Conclusion QD-IIQAS was an easy and accurate method for detecting and assessing TOP2A. The TOP2A expression was an independent prognostic indicator of 5-DFS in TNBC. Our study provides a good foundation for future studies exploring the relationship between TOP2A expression and response to anthracyclines.
Just Keep Swimming: Accounting for Uncertainty in Self-Modeling Aquatic Robots

A robust robotic system should be able to overcome unforeseen conditions, including physical damage and component failure occurring after deployment. A self-modeling system maintains an internal image of itself, which can be updated to reﬂect incurred damage. The robot can use this model to derive (or evolve) new behaviors such as gaits that account for the damage. In this paper we describe an approach to self-modeling for aquatic robots. The aquatic environment presents unique challenges to the self-modeling process, including the inherent uncertainty in the robot’s orientation and conﬁguration. We propose and evaluate two approaches to automatically infer missing contextual information, which otherwise complicates the task of developing an accurate model. We demonstrate the effectiveness of these methods on a particular aquatic robot intended for remote sensing.
Optimizing Cloud MapReduce for Processing Stream Data Using Pipelining

Cloud MapReduce (CMR) is a framework for processing large data sets of batch data in cloud. The Map and Reduce phases run sequentially, one after another. This leads to: 1. Compulsory batch processing 2. No parallelization of the map and reduce phases 3. Increased delays. The current implementation is not suited for processing streaming data. We propose a novel architecture to support streaming data as input using pipelining between the Map and Reduce phases in CMR, ensuring that the output of the Map phase is made available to the Reduce phase as soon as it is produced. This 'Pipelined MapReduce' approach leads to increased parallelism between the Map and Reduce phases, thereby 1. Supporting streaming data as input 2. Reducing delays 3. Enabling the user to take 'snapshots' of the approximate output generated in a stipulated time frame. 4. Supporting cascaded MapReduce jobs. This cloud implementation is light-weight and inherently scalable.
On Handoff Minimization in Wireless Networks: From a Navigation Perspective

Interactive wireless applications, like VoIP over wireless networks, desire high-quality links and smooth con- nectivity during user movement. In order to support seamless roaming in wireless networks, handoff optimization has attracted a lot of attention recently. Most existing approaches aim at reducing handoff latency in communication protocols. While these methods provide signi&#64257;cant savings in handoff latency, frequent handoffs could still be crucial and problematic for interactive applications. In this paper, we propose a new perspec- tive for handoff optimization by introducing navigation guidance to minimize the handoff frequency. We &#64257;rst formulate the navigation- driven handoff minimization problem, then propose an optimal algorithm and a localized algorithm to solve it. The optimal algorithm assumes global knowledge of AP locations and uses a navigation graph to &#64257;nd a minimal handoff frequency path. The localized algorithm, however, only uses neighbor AP locations for route selection, which is more practical in real applications. Implementation issues of the proposed algorithms are discussed and simulations based on real world AP deployment are used to evaluate their performance. Experiment results show that our algorithms reduce handoff frequency by at most 42% compared to existing strategies.
Association of polymorphisms in the klotho gene with severity of non-diabetic ESRD in African Americans.

BACKGROUND Non-diabetic forms of nephropathy commonly lead to end-stage renal disease (non-DM ESRD). Previous studies have demonstrated that African Americans are more susceptible to non-DM ESRD compared to other ethnic groups, and this risk has a strong genetic component. A genome-wide scan for ESRD in African American families enriched for non-DM ESRD showed evidence for linkage in chromosome 13q33.3, and a candidate gene in this region, klotho, was selected for a detailed analysis in a follow-up case-control association study. METHODS Thirty-four single-nucleotide polymorphisms (SNPs) in the klotho gene were genotyped in 317 unrelated African American non-DM ESRD cases and 354 non-nephropathy controls, including 12 SNPs identified by re-sequencing a region around exon 4. RESULTS Two SNPs demonstrated modest admixture-adjusted evidence of association with non-DM ESRD, rs650439 (P = 0.013, recessive model) and rs643780 (P = 0.017, recessive model), while rs17643698 approached significance (P = 0.0953, two degrees of freedom test). Eight of the most significant SNPs were tested for replication in a second case-control collection (557 African American non-DM ESRD cases and 187 controls), and there was no evidence of association in replicate cases and controls; nor when the samples were combined for a total of 874 non-DM cases and 541 controls. Cox proportional hazards models were computed to test for association between polymorphisms in klotho and age at onset of ESRD. A three-SNP haplotype, rs526906, rs525014 and rs571118 (T/T/A), was associated with age of onset of ESRD [P = 0.007, recessive model; hazard ratio (HR) = 0.70]. Subjects homozygous for this haplotype had a mean 4 years later onset of ESRD, suggesting a slower disease progression. HapMap subjects homozygous for this haplotype had increased expression of klotho, further supporting a protective role of this variant in ESRD. CONCLUSION We conclude that three SNPs in intron 1 of the klotho gene are associated with delayed age at onset of non-DM ESRD in African Americans.
Prophylactic Effect of Probiotics on the Development of Experimental Autoimmune Myasthenia Gravis

Probiotics are live bacteria that confer health benefits to the host physiology. Although protective role of probiotics have been reported in diverse diseases, no information is available whether probiotics can modulate neuromuscular immune disorders. We have recently demonstrated that IRT5 probiotics, a mixture of 5 probiotics, could suppress diverse experimental disorders in mice model. In this study we further investigated whether IRT5 probiotics could modulate the progression of experimental autoimmune myasthenia gravis (EAMG). Myasthenia gravis (MG) is a T cell dependent antibody mediated autoimmune disorder in which acetylcholine receptor (AChR) at the neuromuscular junction is the major auto-antigen. Oral administration of IRT5 probiotics significantly reduced clinical symptoms of EAMG such as weight loss, body trembling and grip strength. Prophylactic effect of IRT5 probiotics on EMAG is mediated by down-regulation of effector function of AChR-reactive T cells and B cells. Administration of IRT5 probiotics decreased AChR-reactive lymphocyte proliferation, anti-AChR reactive IgG levels and inflammatory cytokine levels such as IFN-γ, TNF-α, IL-6 and IL-17. Down-regulation of inflammatory mediators in AChR-reactive lymphocytes by IRT5 probiotics is mediated by the generation of regulatory dendritic cells (rDCs) that express increased levels of IL-10, TGF-β, arginase 1 and aldh1a2. Furthermore, DCs isolated from IRT5 probiotics-fed group effectively converted CD4+ T cells into CD4+Foxp3+ regulatory T cells compared with control DCs. Our data suggest that IRT5 probiotics could be applicable to modulate antibody mediated autoimmune diseases including myasthenia gravis.
A COMPARISON OF KRIGING AND COKRIGING FOR MAPPING FOREST VOLUME IN CONNECTICUT

Ordinary kriging and cokriging are two geostatistical techniques used to create continuous maps of spatially autocorrelated attributes. Both procedures use the same primary variable, but cokriging, like multivariate statistics, incorporates additional independent variables. In this study, the primary variable is cubic foot volume and the secondary variable, mean normalized difference vegetation index, is calculated from an August 1996 Landsat Thematic Mapper satellite image. Two methods of evaluating the results include comparing the residuals and breaking both the estimated and sampled data into five volume classes and then examining the resulting confusion matrix. The comparison statistics: root mean square error, overall accuracy, and kappa statistic indicate that cokriging is superior when all of the sample data points are included. The cross-validation results show that cokriging is superior for correctly classifying the observed data by volume classes as indicated by the overall accuracy and kappa statistic. However, the cross-validation root mean square error is larger for cokriging indicating the superiority of kriging. Both procedures capture the same trends in Connecticut. Low volume areas are located around New York City and along the I-91 corridor and the high volume areas are in the NW part of the state. Kriging smoothes the map missing the fine scale heterogeneity of the landscape that cokriging detects.
Automatic text classification and focused crawling

A focused crawler is a web crawler that traverse the web to explore information that is related to a particular topic of interest only. On the other hand, generic web crawlers try to search the entire web, which is impossible due to the size and the complexity of WWW. In this paper we make a survey of some of the latest focused web crawling approaches discussing each with their experimental results. We categorize them as focused crawling based on content analysis, focused crawling based on link analysis and focused crawling based on both the content and link analysis. We also give an insight to the future research and draw the overall conclusions.
Forging links with the self to combat implicit bias

Two experiments examined whether Whites’ implicit biases toward Blacks could be reduced by conditioning links between Blacks and the self. Via a computer-mediated experience, White participants were assigned to the same (minimal) group as several Black individuals and practiced classifying photographs as “MY GROUP” or “OTHER GROUP. ” Subsequent performance on implicit prejudice and stereotyping measures was compared to a control condition and another condition involving extensive counterstereotype conditioning. Across experiments, the link to self strategy significantly reduced implicit prejudice, relative to the control condition, and to the same extent as the counterstereotype conditioning condition. Process dissociation analyses revealed that these effects corresponded with a reduction in the automatic activation of biased associations. Counterstereotype conditioning also reduced implicit stereotyping, but the link-to-self strategy did not. These findings extend prior work on the reduction of implicit biases and highlight the importance of comparing implicit bias strategies across different types of bias measures.
Resource fit in digital transformation

Purpose – The implementation of e‐banking projects highlights the importance of digital transformation for contemporary organizations in order to survive and achieve competitive advantage in a digital economy. This paper aims to explore the development process of digital transformation through an e‐banking project based on the resource fit concept.Design/methodology/approach – The qualitative method of case study is applied. In total, 17 in‐depth interviews and secondary data were collected and analyzed.Findings – Numerous researches related to e‐banking have focused on either the resource‐based theory or strategic fit perspective, but not on both. This paper makes a unique contribution by constructing a resource fit framework that integrates these two theories. This framework offers a theoretical advancement in the resource fit literature. It includes four dimensions: external resource fit, internal resource fit, external capability fit, and internal capability fit. Through an actual empirical case exami.