Counterfactual Estimation and Optimization of Click Metrics for Search Engines

Optimizing an interactive system against a predefined online metric is particularly challenging, when the metric is computed from user feedback such as clicks and payments. The key challenge is the counterfactual nature: in the case of Web search, any change to a component of the search engine may result in a different search result page for the same query, but we normally cannot infer reliably from search log how users would react to the new result page. Consequently, it appears impossible to accurately estimate online metrics that depend on user feedback, unless the new engine is run to serve users and compared with a baseline in an A/B test. This approach, while valid and successful, is unfortunately expensive and time-consuming. In this paper, we propose to address this problem using causal inference techniques, under the contextual-bandit framework. This approach effectively allows one to run (potentially infinitely) many A/B tests offline from search log, making it possible to estimate and optimize online metrics quickly and inexpensively. Focusing on an important component in a commercial search engine, we show how these ideas can be instantiated and applied, and obtain very promising results that suggest the wide applicability of these techniques

A posture similarity calculation method using self-adaptive joint weight

A novel posture similarity calculation method using self-adaptive joint weight was proposed in this paper.Kinect was selected to collect posture information,using which the human skeleton joint data was acquired.In order to accommodate various body shapes,the data of joints was modified according to the length of skeletons.In addition,the definition of self-adaptive joint weight was proposed in terms of various human postures.The experimental results showed that the proposed posture similarity calculation method achieved high accuracy and stable results

Assessment of Economic Recovery in Hebei Province, China, under the COVID-19 Pandemic Using Nighttime Light Data

The COVID-19 pandemic has presented unprecedented disruptions to human society worldwide since late 2019, and lockdown policies in response to the pandemic have directly and drastically decreased human socioeconomic activities. To quantify and assess the extent of the pandemic’s impact on the economy of Hebei Province, China, nighttime light (NTL) data, vegetation information, and provincial quarterly gross domestic product (GDP) data were jointly utilized to estimate the quarterly GDP for prefecture-level cities and county-level cities. Next, an autoregressive integrated moving average model (ARIMA) model was applied to predict the quarterly GDP for 2020 and 2021. Finally, economic recovery intensity (ERI) was used to assess the extent of economic recovery in Hebei Province during the pandemic. The results show that, at the provincial level, the economy of Hebei Province had not yet recovered; at the prefectural and county levels, three prefectures and forty counties were still struggling to restore their economies by the end of 2021, even though these economies, as a whole, were gradually recovering. In addition, the number of new infected cases correlated positively with the urban NTL during the pandemic period, but not during the post-pandemic period. The study results are informative for local government’s strategies and policies for allocating financial resources for urban economic recovery in the short- and long-term

Petrogenesis and tectonic setting of Early Cretaceous magmatism in the Jiwa area, central Lhasa Terrane, Tibet

<p>New zircon LA-ICP-MS U–Pb ages, Sr-Nd isotopic data, and whole-rock major and trace element data from Early Cretaceous volcanic rocks are reported for the Jiwa area in the southern central Lhasa Terrane of Tibet. These mainly silicic volcanic rocks and subordinate intermediate-basic volcanic rocks have long been considered to be Pliocene (Wuyu Group) or Eocene (Pana Formation) in age. However, our new zircon U–Pb ages constrain the timing of eruption to the Early Cretaceous (124.6 ± 1.6–126.1 ± 1.1 Ma); thus, we have redefined these volcanic rocks as the Lower Cretaceous Zenong Group. The silicic volcanic rocks feature high-K calc-alkaline to shoshonitic compositions and are mostly strongly peraluminous, rich in Rb, Th, and light rare earth elements (LREEs), and depleted in Nb, Ta, P, and Ti. They are also characterized by negative whole-rock <i>ε</i>Nd(t) values (–9.1 to –13.1) and variable ⁸⁷Sr/⁸⁶Sr ratios. Thus, the geochemical and zircon U–Pb age data of the Jiwa volcanic rocks suggest that these rocks are associated with a continental arc and are mostly likely derived from anatexis of ancient continental crustal material and minor basalt-derived melts. The discovery of Early Cretaceous volcanic rocks in the southern central Lhasa Terrane extends the duration of magmatism triggered by southward subduction of the Bangong-Nujiang oceanic lithosphere from the Late Jurassic to the Early Cretaceous. The spatial distribution of magmatism is also extended 70–80 km to the south. The Lower Cretaceous volcanic rocks in the Jiwa area are proposed to be a result of bi-directional subduction, with southward subduction of the Bangong-Nujiang oceanic crust and northward subduction of the Yarlung Zangbo oceanic crust. The bi-directional subduction of the oceanic lithosphere and gravitational sinking led to slab retreat at ca. 125 Ma. The roll-back of the slab would have then led to back-arc extension and asthenospheric upwelling. The subduction-induced decompression melting of the mantle led to the generation of widespread rhyolitic volcanism with continental arc geochemical signatures.</p

Soil enzyme profile analysis for indicating decomposer micro‐food web

Abstract Highly diverse exoenzymes mediate the energy flow from substrates to the multitrophic microbiota within the soil decomposer micro‐food web. Here, we used a “soil enzyme profile analysis” approach to establish a series of enzyme profile indices; those indices were hypothesized to reflect micro‐food web features. We systematically evaluated the shifts in enzyme profile indices in relation to the micro‐food web features in the restoration of an abandoned cropland to a natural area. We found that enzymatic C:N stoichiometry and decomposability index were significantly associated with substrate availability. Furthermore, the higher Shannon diversity index in the exoenzyme profile, especially for the C‐degrading hydrolase, corresponded to a greater microbiota community diversity. The increased complexity and stability of the exoenzyme network reflected similar changes with the micro‐food web networks. In addition, the gross activity of the enzyme profile as a parameter for soil multifunctionality, effectively predicted the substrate content, microbiota community size, diversity, and network complexity. Ultimately, the proposed enzymic channel index was closely associated with the traditional decomposition channel indices derived from microorganisms and nematodes. Our results showed that soil enzyme profile analysis reflected very well the decomposer food web features. Our study has important implications for projecting future climate change or anthropogenic disturbance impacts on soil decomposer micro‐food web features by using soil enzyme profile analysis

Stoichiometric theory shapes enzyme kinetics in paddy bulk soil but not in rhizosphere soil

The available carbon (C) to phosphorus (P) ratio in soil is regulated by extracellular hydrolases for C and P acquisition by microbes and plants. However, the stoichiometric relationship between acquiring C and P in paddy rhizosphere and bulk soils remains unclear. The objective was to explore the underlying mechanisms of C and P acquisition stoichiometry in rhizosphere and bulk soils in response to P fertilization and cellulose addition. Amendment with either cellulose or P separately caused a significant increase in the maximal velocity (Vmax) of C acquisition enzymes (β-1,4-glucosidase and β-cellobiohydrolase) but decreased that of P acquisition enzymes (acid and alkaline phosphomonoesterases) in bulk soil. In contrast, lower Vmax values of C and P acquisition enzymes were observed in rhizosphere soil than in bulk soil. The co-application of cellulose and P increased the Vmax of P acquisition enzymes in rhizosphere soil but decreased that of only alkaline phosphomonoesterase in bulk soil. Results show that P availability and labile-C content co-regulated the P/C acquisition ratio, and two inverse linear relationships were observed. Specifically, the P/C acquisition ratio was negatively related to both the dissolved organic C/Olsen-P ratio and the microbial biomass C/P ratio in rhizosphere soil. However, the P/C acquisition ratio was positively related to both the dissolved organic C/Olsen-P ratio and the microbial biomass C/P ratio in bulk soil. Overall, microbes mineralized less organic P to acquire P in paddy soil rhizosphere (i.e. containing higher labile-C) than in bulk soil (i.e. having lower labile-C contents)