Do not Waste Money on Advertising Spend: Bid Recommendation via Concavity Changes

In computational advertising, a challenging problem is how to recommend the bid for advertisers to achieve the best return on investment (ROI) given budget constraint. This paper presents a bid recommendation scenario that discovers the concavity changes in click prediction curves. The recommended bid is derived based on the turning point from significant increase (i.e. concave downward) to slow increase (convex upward). Parametric learning based method is applied by solving the corresponding constraint optimization problem. Empirical studies on real-world advertising scenarios clearly demonstrate the performance gains for business metrics (including revenue increase, click increase and advertiser ROI increase).Comment: 10 page

Demystifying Advertising Campaign Bid Recommendation: A Constraint target CPA Goal Optimization

In cost-per-click (CPC) or cost-per-impression (CPM) advertising campaigns, advertisers always run the risk of spending the budget without getting enough conversions. Moreover, the bidding on advertising inventory has few connections with propensity one that can reach to target cost-per-acquisition (tCPA) goals. To address this problem, this paper presents a bid optimization scenario to achieve the desired tCPA goals for advertisers. In particular, we build the optimization engine to make a decision by solving the rigorously formalized constrained optimization problem, which leverages the bid landscape model learned from rich historical auction data using non-parametric learning. The proposed model can naturally recommend the bid that meets the advertisers' expectations by making inference over advertisers' historical auction behaviors, which essentially deals with the data challenges commonly faced by bid landscape modeling: incomplete logs in auctions, and uncertainty due to the variation and fluctuations in advertising bidding behaviors. The bid optimization model outperforms the baseline methods on real-world campaigns, and has been applied into a wide range of scenarios for performance improvement and revenue liftup

Bid Optimization for Offsite Display Ad Campaigns on eCommerce

Online retailers often use third-party demand-side-platforms (DSPs) to conduct offsite advertising and reach shoppers across the Internet on behalf of their advertisers. The process involves the retailer participating in instant auctions with real-time bidding for each ad slot of their interest. In this paper, we introduce a bid optimization system that leverages the dimensional bidding function provided by most well-known DSPs for Walmart offsite display ad campaigns. The system starts by automatically searching for the optimal segmentation of the ad requests space based on their characteristics such as geo location, time, ad format, serving website, device type, etc. Then, it assesses the quality of impressions observed from each dimension based on revenue signals driven by the campaign effect. During the campaign, the system iteratively approximates the bid landscape based on the data observed and calculates the bid adjustments for each dimension. Finally, a higher bid adjustment factor is applied to dimensions with potentially higher revenue over ad spend (ROAS), and vice versa. The initial A/B test results of the proposed optimization system has shown its effectiveness of increasing the ROAS and conversion rate while reducing the effective cost per mille for ad serving

Discovery and Functional Characterization of Diverse Class 2 CRISPR-Cas Systems

Microbial CRISPR-Cas systems are divided into Class 1, with multisubunit effector complexes, and Class 2, with single protein effectors. Currently, only two Class 2 effectors, Cas9 and Cpf1, are known. We describe here three distinct Class 2 CRISPR-Cas systems. The effectors of two of the identified systems, C2c1 and C2c3, contain RuvC-like endonuclease domains distantly related to Cpf1. The third system, C2c2, contains an effector with two predicted HEPN RNase domains. Whereas production of mature CRISPR RNA (crRNA) by C2c1 depends on tracrRNA, C2c2 crRNA maturation is tracrRNA independent. We found that C2c1 systems can mediate DNA interference in a 5'-PAM-dependent fashion analogous to Cpf1. However, unlike Cpf1, which is a single-RNA-guided nuclease, C2c1 depends on both crRNA and tracrRNA for DNA cleavage. Finally, comparative analysis indicates that Class 2 CRISPR-Cas systems evolved on multiple occasions through recombination of Class 1 adaptation modules with effector proteins acquired from distinct mobile elements.National Institute of Mental Health (U.S.) (Grant 5DP1-MH100706)National Institute of Mental Health (U.S.) (Grant 1R01-MH110049)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Grant 5R01DK097768-03)National Institutes of Health (U.S.) (Grant GM10407

Influence of Quenching and Subsequent Artificial Aging on Tensile Strength of Laser-Welded Joints of Al–Cu–Li Alloy

The research aim was to optimize post-weld heat-treatment (PWHT) modes for a laser-welded joint of the Al–Cu–Li alloy and improve their respective strength properties. As a result, the ultimate tensile strength, yield point, and elongation of the joint were enhanced up to 95%, 94%, and 38%, respectively, of those inherent in the base metal. Before and after PWHT, both microstructures and phase compositions have been examined by optical and scanning electron microscopy, as well as synchrotron X-ray diffractometry. In the as-welded metal, the α-Al and T1(Al2CuLi) phases were found, along with the θ′(Al2Cu) and S′(Al2CuMg) phases localized at the grain boundaries, significantly reducing the mechanical properties of the joint. Upon quenching, the agglomerates dissolved at the grain boundaries, the solid solution was homogenized, and both Guinier–Preston zones and precipitates of the intermediate metastable θ″ phase were formed. After subsequent optimal artificial aging, the (predominant) hardening θ′ and (partial) T1(Al2CuLi) phases were observed in the weld metal, which contributed to the improvement of the strength properties of the joint

Properties of TiAlN Coatings Obtained by Dual-HiPIMS with Short Pulses

The paper focuses on the dual high-power impulse magnetron sputtering of TiAlN coatings using short pulses of high power delivered to the target. The surface morphology, elemental composition, phase composition, hardness, wear resistance, and adhesive strength of TiAlN coatings with different Al contents were investigated on WC–Co substrates. The heat resistance of the TiAlN coating was determined with synchrotron X-ray diffraction. The hardness of the TiAlN coating with a low Al content ranged from 17 to 30 GPa, and its wear rate varied between 1.8∙10−6 and 4.9∙10−6 mm3·N−1·m−1 depending on the substrate bias voltage. The HF1–HF2 adhesion strength of the TiAlN coatings was evaluated with the Daimler–Benz Rockwell C test. The hardness and wear rate of the Ti0.61Al0.39N coating were 26.5 GPa and 5.2∙10−6 mm3·N−1·m−1, respectively. The annealing process at 700 °C considerably worsened the mechanical properties of the Ti0.94Al0.06N coating, in contrast to the Ti0.61Al0.39N coating, which manifested a high oxidation resistance at annealing temperatures of 940–950 °C

Properties of TiAlN Coatings Obtained by Dual-HiPIMS with Short Pulses

The paper focuses on the dual high-power impulse magnetron sputtering of TiAlN coatings using short pulses of high power delivered to the target. The surface morphology, elemental composition, phase composition, hardness, wear resistance, and adhesive strength of TiAlN coatings with different Al contents were investigated on WC–Co substrates. The heat resistance of the TiAlN coating was determined with synchrotron X-ray diffraction. The hardness of the TiAlN coating with a low Al content ranged from 17 to 30 GPa, and its wear rate varied between 1.8∙10−6 and 4.9∙10−6 mm3·N−1·m−1 depending on the substrate bias voltage. The HF1–HF2 adhesion strength of the TiAlN coatings was evaluated with the Daimler–Benz Rockwell C test. The hardness and wear rate of the Ti0.61Al0.39N coating were 26.5 GPa and 5.2∙10−6 mm3·N−1·m−1, respectively. The annealing process at 700 °C considerably worsened the mechanical properties of the Ti0.94Al0.06N coating, in contrast to the Ti0.61Al0.39N coating, which manifested a high oxidation resistance at annealing temperatures of 940–950 °C

The CRISPR Spacer Space Is Dominated by Sequences from Species-Specific Mobilomes

Clustered regularly interspaced short palindromic repeats and CRISPR-associated protein (CRISPR-Cas) systems store the memory of past encounters with foreign DNA in unique spacers that are inserted between direct repeats in CRISPR arrays. For only a small fraction of the spacers, homologous sequences, called protospacers, are detectable in viral, plasmid, and microbial genomes. The rest of the spacers remain the CRISPR “dark matter.” We performed a comprehensive analysis of the spacers from all CRISPR-cas loci identified in bacterial and archaeal genomes, and we found that, depending on the CRISPR-Cas subtype and the prokaryotic phylum, protospacers were detectable for 1% to about 19% of the spacers (~7% global average). Among the detected protospacers, the majority, typically 80 to 90%, originated from viral genomes, including proviruses, and among the rest, the most common source was genes that are integrated into microbial chromosomes but are involved in plasmid conjugation or replication. Thus, almost all spacers with identifiable protospacers target mobile genetic elements (MGE). The GC content, as well as dinucleotide and tetranucleotide compositions, of microbial genomes, their spacer complements, and the cognate viral genomes showed a nearly perfect correlation and were almost identical. Given the near absence of self-targeting spacers, these findings are most compatible with the possibility that the spacers, including the dark matter, are derived almost completely from the species-specific microbial mobilomes