Click-aware Structure Transfer with Sample Weight Assignment for Post-Click Conversion Rate Estimation

Post-click Conversion Rate (CVR) prediction task plays an essential role in industrial applications, such as recommendation and advertising. Conventional CVR methods typically suffer from the data sparsity problem as they rely only on samples where the user has clicked. To address this problem, researchers have introduced the method of multi-task learning, which utilizes non-clicked samples and shares feature representations of the Click-Through Rate (CTR) task with the CVR task. However, it should be noted that the CVR and CTR tasks are fundamentally different and may even be contradictory. Therefore, introducing a large amount of CTR information without distinction may drown out valuable information related to CVR. This phenomenon is called the curse of knowledge problem in this paper. To tackle this issue, we argue that a trade-off should be achieved between the introduction of large amounts of auxiliary information and the protection of valuable information related to CVR. Hence, we propose a Click-aware Structure Transfer model with sample Weight Assignment, abbreviated as CSTWA. It pays more attention to the latent structure information, which can filter the input information that is related to CVR, instead of directly sharing feature representations. Meanwhile, to capture the representation conflict between CTR and CVR, we calibrate the representation layer and reweight the discriminant layer to excavate the click bias information from the CTR tower. Moreover, it incorporates a sample weight assignment algorithm biased towards CVR modeling, to make the knowledge from CTR would not mislead the CVR. Extensive experiments on industrial and public datasets have demonstrated that CSTWA significantly outperforms widely used and competitive models

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Global Mixup: Eliminating Ambiguity with Clustering

Data augmentation with Mixup has been proven an effective method to regularize the current deep neural networks. Mixup generates virtual samples and corresponding labels simultaneously by linear interpolation. However, the one-stage generation paradigm and the use of linear interpolation have two defects: (1) The label of the generated sample is simply combined from the labels of the original sample pairs without reasonable judgment, resulting in ambiguous labels. (2) Linear combination significantly restricts the sampling space for generating samples. To address these issues, we propose a novel and effective augmentation method, Global Mixup, based on global clustering relationships. Specifically, we transform the previous one-stage augmentation process into two-stage by decoupling the process of generating virtual samples from the labeling. And for the labels of the generated samples, relabeling is performed based on clustering by calculating the global relationships of the generated samples. Furthermore, we are no longer restricted to linear relationships, which allows us to generate more reliable virtual samples in a larger sampling space. Extensive experiments for CNN, LSTM, and BERT on five tasks show that Global Mixup outperforms previous baselines. Further experiments also demonstrate the advantage of Global Mixup in low-resource scenarios

Identification of land-cover characteristics using MODIS time series data: an application in the Yangtze river estuary.

Land-cover characteristics have been considered in many ecological studies. Methods to identify these characteristics by using remotely sensed time series data have previously been proposed. However, these methods often have a mathematical basis, and more effort is required to better illustrate the ecological meanings of land-cover characteristics. In this study, a method for identifying these characteristics was proposed from the ecological perspective of sustained vegetation growth trend. Improvement was also made in parameter extraction, inspired by a method used for determining the hyperspectral red edge position. Five land-cover types were chosen to represent various ecosystem growth patterns and MODIS time series data were adopted for analysis. The results show that the extracted parameters can reflect ecosystem growth patterns and portray ecosystem traits such as vegetation growth strategy and ecosystem growth situations

Impact of Climate Change on Vegetation Growth in Arid Northwest of China from 1982 to 2011

Previous studies have concluded that the increase in vegetation in the arid northwest of China is related to precipitation rather than temperature. However, these studies neglected the effects of climate warming on water availability that arise through changes in the melting characteristics of this snowy and glaciated region. Here, we characterized vegetation changes using the newly improved third-generation Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS-3g NDVI) from 1982 to 2011. We analyzed the temperature and precipitation trends based on data from 51 meteorological stations across Northwest China and investigated changes in the glaciers using Gravity Recovery and Climate Experiment (GRACE) data. Our results indicated an increasing trend in vegetation greenness in Northwest China, and this increasing trend was mostly associated with increasing winter precipitation and summer temperature. We found that the mean annual temperature increased at a rate of 0.04 °C per year over the past 30 years, which induced rapid glacial melting. The total water storage measured by GRACE decreased by up to 8 mm yr−1 and primarily corresponded to the disappearance of glaciers. Considering the absence of any observed increase in precipitation in the growing season, the vegetation growth may have benefited from the melting of glaciers in high-elevation mountains (i.e., the Tianshan Mountains). Multiple regression analysis showed that temperature was positively correlated with NDVI and that gravity was negatively correlated with NDVI; together, these variables explained 84% of the NDVI variation. Our findings suggest that both winter precipitation and warming-induced glacial melting increased water availability to the arid vegetation in this region, resulting in enhanced greenness

Spectral Discrimination of the Invasive Plant <i>Spartina alterniflora</i> at Multiple Phenological Stages in a Saltmarsh Wetland

<div><p><i>Spartina alterniflora</i> has widely invaded the saltmarshes of the Yangtze River Estuary and brought negative effects to the ecosystem. Remote sensing technique has recently been used to monitor its distribution, but the similar morphology and canopy structure among <i>S. alterniflora</i> and its neighbor species make it difficult even with high-resolution images. Nevertheless, these species have divergence on phenological stages throughout the year, which cause distinguishing spectral characteristics among them and provide opportunities for discrimination. The field spectra of the <i>S. alterniflora</i> community as well as its major victims, native <i>Phragmites australis</i> and <i>Scirpus mariqueter</i>, were measured in 2009 and 2010 at multi-phenological stages in the Yangtze River Estuary, aiming to find the most appropriate periods for mapping <i>S. alterniflora</i>. Collected spectral data were analyzed separately for every stage firstly by re-sampling reflectance curves into continued 5-nm-wide hyper-spectral bands and then by re-sampling into broad multi-spectral bands – the same as the band ranges of the TM sensor, as well as calculating commonly used vegetation indices. The results showed that differences among saltmarsh communities’ spectral characteristics were affected by their phenological stages. The germination and early vegetative growth stage and the flowering stage were probably the best timings to identify <i>S. alterniflora</i>. Vegetation indices like NDVI, ANVI, VNVI, and RVI are likely to enhance spectral separability and also make it possible to discriminate <i>S. alterniflora</i> at its withering stage.</p></div

The spectral separability of hyper-spectral bands between <i>Scirpus</i> and <i>Phragmites</i> at various phenological stages.

<p>The blank symbol stands for significantly similar bands, while the other symbols stand for significantly different bands with different separability determined by JM distance.</p

Field reflectance spectra of <i>Spartina</i>, <i>Phragmites</i>, and <i>Scirpus</i> at various phenological stages.

<p>Field reflectance spectra of <i>Spartina</i>, <i>Phragmites</i>, and <i>Scirpus</i> at various phenological stages.</p