Multi-modal knowledge graph inference via media convergence and logic rule

Media convergence works by processing information from different modalities and applying them to different domains. It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective. To address the issue, an inference method based on Media Convergence and Rule-guided Joint Inference model (MCRJI) has been proposed. The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction. First, a multi-headed self-attention approach is used to obtain the attention of different media features of entities during semantic synthesis. Second, logic rules of different lengths are mined from knowledge graph to learn new entity representations. Finally, knowledge graph inference is performed based on representing entities that converge multi-media features. Numerous experimental results show that MCRJI outperforms other advanced baselines in using multi-media features and knowledge graph inference, demonstrating that MCRJI provides an excellent approach for knowledge graph inference with converged multi-media features

Different water and nitrogen level effects on soil microbial properties of spinach

Understanding the interactions of plant soil environment and rhizosphere microbial changes are necessary to develop new strategies for the sustainable agriculture. A field experiment with combination of three water levels and three nitrogen rates was conducted to investigate the effect of water and nitrogen management on the changes of soil microbial properties in non-rhizosphere and rhizosphere soils of spinach. Non-Rhizosphere and rhizosphere microbial diversities were affected by water and nitrogen applications. Evenness index in the no-nitrogen treatment was more than that of 85 and 170 kg ha–1 nitrogen treatments in the non-rhizosphere or rhizosphere soil. Microbial biomass carbon in non-rhizosphere soil or rhizosphere soil decreased with the increase of nitrogen application, but showed the highest value in 16.5% of soil water content, followed by 12.5% and 20.5% of soil water content. Soil microbial biomass phosphorus content of 85 kg ha–1 nitrogen treatment in the non-rhizosphere soil or rhizosphere soil was significantly different for 0 and 170 kg ha–1 nitrogen treatments. Nitrification rate increased with the increase of soil water content in 0 and 170 kg ha–1 treatments. Our results demonstrated that water and nitrogen could impact the soil fertility and microbial activity of spinach

Gradient bandgap enables >13% efficiency sulfide Kesterite solar cells with open-circuit voltage over 800 mV

Sulfide Kesterite Cu2ZnSnS4 (CZTS), a nontoxic and low-cost photovoltaic material, has always being facing severe charge recombination and poor carrier transport, resulting in the cell efficiency record stagnating around 11% for years. Gradient bandgap is a promising approach to relieve these issues, however, has not been effectively realized in Kesterite solar cells due to the challenges in controlling the gradient distribution of alloying elements at high temperatures. Herein, targeting at the Cd alloyed CZTS, we propose a pre-crystallization strategy to reduce the intense vertical mass transport and Cd rapid diffusion in the film growth process, thereby realizing front Cd-gradient CZTS absorber. The Cd-gradient CZTS absorber, exhibiting downward bending conduction band structure, has significantly enhanced the minority carrier transport and additionally improved band alignment and interface property of CZTS/CdS heterojunction. Ultimately, we have achieved a champion total-area efficiency of 13.5% (active-area efficiency: 14.1%) in the cell and in particular a high open-circuit voltage of >800 mV. We have also achieved a certified total-area cell efficiency of 13.16%, realizing a substantial step forward for the pure sulfide Kesterite solar cell

Multi-interface engineering to realize all-solution processed highly efficient Kesterite solar cells

With the rapid development of Kesterite Cu2ZnSn(S, Se)4 solar cells in the past few years, how to achieve higher cost-performance ratio has become an important topic in the future development and industrialization of this technology. Herein, we demonstrate an all-solution route for the cell fabrication, in particular targeting at the solution processed window layer comprised of ZnO nanoparticles/Ag nanowires. A multi-interface engineering strategy assisted by organic polymers and molecules is explored to synergistically improve the film deposition, passivate the surface defects and facilitate the charge transfer. These efforts help us achieve high-performance and robust Kesterite solar cells at extremely low time and energy costs, with efficiency records of 14.37% and 13.12% being realized in rigid and flexible Kesterite solar cells, respectively. Our strategy here is also promising to be transplanted into other solar cells with similar geometric and energy band structures, helping reduce production costs and shorten the production cycle (i.e. increasing production capacity) of these photovoltaic industries

Development and validation of risk prediction model for identifying 30-day frailty in older inpatients with undernutrition: A multicenter cohort study

ObjectiveTo develop and externally validate a frailty prediction model integrating physical factors, psychological variables and routine laboratory test parameters to predict the 30-day frailty risk in older adults with undernutrition.MethodsBased on an ongoing survey of geriatrics syndrome in elder adults across China (SGSE), this prognostic study identified the putative prognostic indicators for predicting the 30-day frailty risk of older adults with undernutrition. Using multivariable logistic regression analysis with backward elimination, the predictive model was subjected to internal (bootstrap) and external validation, and its calibration was evaluated by the calibration slope and its C statistic discriminative ability. The model derivation and model validation cohorts were collected between October 2018 and February 2019 from a prospective, large-scale cohort study of hospitalized older adults in tertiary hospitals in China. The modeling derivation cohort data (n = 2,194) were based on the SGSE data comprising southwest Sichuan Province, northern Beijing municipality, northwest Qinghai Province, northeast Heilongjiang Province, and eastern Zhejiang Province, with SGSE data from Hubei Province used to externally validate the model (validation cohort, n = 648).ResultsThe incidence of frailty in the older undernutrition derivation cohort was 13.54% and 13.43% in the validation cohort. The final model developed to estimate the individual predicted risk of 30-day frailty was presented as a regression formula: predicted risk of 30-day frailty = [1/(1+e-riskscore )], where riskscore = -0.106 + 0.034 × age + 0.796 × sex -0.361 × vision dysfunction + 0.373 × hearing dysfunction + 0.408 × urination dysfunction - 0.012 × ADL + 0.064 × depression - 0.139 × nutritional status - 0.007 × hemoglobin - 0.034 × serum albumin - 0.012 × (male: ADL). Area under the curve (AUC) of 0.71 in the derivation cohort, and discrimination of the model were similar in both cohorts, with a C statistic of nearly 0.7, with excellent calibration of observed and predicted risks.ConclusionA new prediction model that quantifies the absolute risk of frailty of older patients suffering from undernutrition was developed and externally validated. Based on physical, psychological, and biological variables, the model provides an important assessment tool to provide different healthcare needs at different times for undernutrition frailty patients.Clinical trial registrationChinese Clinical Trial Registry [ChiCTR1800017682]

HFR1 Is Crucial for Transcriptome Regulation in the Cryptochrome 1-Mediated Early Response to Blue Light in Arabidopsis thaliana

Cryptochromes are blue light photoreceptors involved in development and circadian clock regulation. They are found in both eukaryotes and prokaryotes as light sensors. Long Hypocotyl in Far-Red 1 (HFR1) has been identified as a positive regulator and a possible transcription factor in both blue and far-red light signaling in plants. However, the gene targets that are regulated by HFR1 in cryptochrome 1 (cry1)-mediated blue light signaling have not been globally addressed. We examined the transcriptome profiles in a cry1- and HFR1-dependent manner in response to 1 hour of blue light. Strikingly, more than 70% of the genes induced by blue light in an HFR1-dependent manner were dependent on cry1, and vice versa. High overrepresentation of W-boxes and OCS elements were found in these genes, indicating that this strong cry1 and HFR1 co-regulation on gene expression is possibly through these two cis-elements. We also found that cry1 was required for maintaining the HFR1 protein level in blue light, and that the HFR1 protein level is strongly correlated with the global gene expression pattern. In summary, HFR1, which is fine-tuned by cry1, is crucial for regulating global gene expression in cry1-mediated early blue light signaling, especially for the function of genes containing W-boxes and OCS elements

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

Tire Speckle Interference Bubble Defect Detection Based on Improved Faster RCNN-FPN

With the development of neural networks, object detection based on deep learning is developing rapidly, and its applications are gradually increasing. In the tire industry, detecting speckle interference bubble defects of tire crown has difficulties such as low image contrast, small object scale, and large internal differences of defects, which affect the detection precision. To solve these problems, we propose a new feature pyramid network based on Faster RCNN-FPN. It can fuse features across levels and directions to improve small object detection and localization, and increase object detection precision. The method has proven its effectiveness through cross-validation experiments. On a tire crown bubble defect dataset, the mAP [0.5:0.95] increased by 2.08% and the AP0.5 increased by 2.4% over the original network. The results show that the improved network significantly improves detecting tire crown bubble defects