RawHDR: High Dynamic Range Image Reconstruction from a Single Raw Image

High dynamic range (HDR) images capture much more intensity levels than standard ones. Current methods predominantly generate HDR images from 8-bit low dynamic range (LDR) sRGB images that have been degraded by the camera processing pipeline. However, it becomes a formidable task to retrieve extremely high dynamic range scenes from such limited bit-depth data. Unlike existing methods, the core idea of this work is to incorporate more informative Raw sensor data to generate HDR images, aiming to recover scene information in hard regions (the darkest and brightest areas of an HDR scene). To this end, we propose a model tailor-made for Raw images, harnessing the unique features of Raw data to facilitate the Raw-to-HDR mapping. Specifically, we learn exposure masks to separate the hard and easy regions of a high dynamic scene. Then, we introduce two important guidances, dual intensity guidance, which guides less informative channels with more informative ones, and global spatial guidance, which extrapolates scene specifics over an extended spatial domain. To verify our Raw-to-HDR approach, we collect a large Raw/HDR paired dataset for both training and testing. Our empirical evaluations validate the superiority of the proposed Raw-to-HDR reconstruction model, as well as our newly captured dataset in the experiments.Comment: ICCV 202

Soft Actuators and Robotic Devices for Rehabilitation and Assistance

Soft actuators and robotic devices have been increasingly applied to the field of rehabilitation and assistance, where safe human and machine interaction is of particular importance. Compared with their widely used rigid counterparts, soft actuators and robotic devices can provide a range of significant advantages; these include safe interaction, a range of complex motions, ease of fabrication and resilience to a variety of environments. In recent decades, significant effort has been invested in the development of soft rehabilitation and assistive devices for improving a range of medical treatments and quality of life. This review provides an overview of the current state-of-the-art in soft actuators and robotic devices for rehabilitation and assistance, in particular systems that achieve actuation by pneumatic and hydraulic fluid-power, electrical motors, chemical reactions and soft active materials such as dielectric elastomers, shape memory alloys, magnetoactive elastomers, liquid crystal elastomers and piezoelectric materials. Current research on soft rehabilitation and assistive devices is in its infancy, and new device designs and control strategies for improved performance and safe human-machine interaction are identified as particularly untapped areas of research. Finally, insights into future research directions are outlined

Clinical characteristics and risk factors associated with ICU-acquired infections in sepsis: A retrospective cohort study

Intensive care unit (ICU)-acquired infection is a common cause of poor prognosis of sepsis in the ICU. However, sepsis-associated ICU-acquired infections have not been fully characterized. The study aims to assess the risk factors and develop a model that predicts the risk of ICU-acquired infections in patients with sepsis.MethodsWe retrieved data from the Medical Information Mart for Intensive Care (MIMIC) IV database. Patients were randomly divided into training and validation cohorts at a 7:3 ratio. A multivariable logistic regression model was used to identify independent risk factors that could predict ICU-acquired infection. We also assessed its discrimination and calibration abilities and compared them with classical score systems.ResultsOf 16,808 included septic patients, 2,871 (17.1%) developed ICU-acquired infection. These patients with ICU-acquired infection had a 17.7% ICU mortality and 31.8% in-hospital mortality and showed a continued rise in mortality from 28 to 100 days after ICU admission. The classical Systemic Inflammatory Response Syndrome Score (SIRS), Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS), Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction Score (LODS), Charlson Comorbidity Index (CCI), and Acute Physiology Score III (APS III) scores were associated with ICU-acquired infection, and cerebrovascular insufficiency, Gram-negative bacteria, surgical ICU, tracheostomy, central venous catheter, urinary catheter, mechanical ventilation, red blood cell (RBC) transfusion, LODS score and anticoagulant therapy were independent predictors of developing ICU-acquired infection in septic patients. The nomogram on the basis of these independent predictors showed good calibration and discrimination in both the derivation (AUROC = 0.737; 95% CI, 0.725–0.749) and validation (AUROC = 0.751; 95% CI, 0.734–0.769) populations and was superior to that of SIRS, SOFA, OASIS, SAPS II, LODS, CCI, and APS III models.ConclusionsICU-acquired infections increase the likelihood of septic mortality. The individualized prognostic model on the basis of the nomogram could accurately predict ICU-acquired infection and optimize management or tailored therapy

Genomic and Proteomic Analyses of the Fungus Arthrobotrys oligospora Provide Insights into Nematode-Trap Formation

Nematode-trapping fungi are “carnivorous” and attack their hosts using specialized trapping devices. The morphological development of these traps is the key indicator of their switch from saprophytic to predacious lifestyles. Here, the genome of the nematode-trapping fungus Arthrobotrys oligospora Fres. (ATCC24927) was reported. The genome contains 40.07 Mb assembled sequence with 11,479 predicted genes. Comparative analysis showed that A. oligospora shared many more genes with pathogenic fungi than with non-pathogenic fungi. Specifically, compared to several sequenced ascomycete fungi, the A. oligospora genome has a larger number of pathogenicity-related genes in the subtilisin, cellulase, cellobiohydrolase, and pectinesterase gene families. Searching against the pathogen-host interaction gene database identified 398 homologous genes involved in pathogenicity in other fungi. The analysis of repetitive sequences provided evidence for repeat-induced point mutations in A. oligospora. Proteomic and quantitative PCR (qPCR) analyses revealed that 90 genes were significantly up-regulated at the early stage of trap-formation by nematode extracts and most of these genes were involved in translation, amino acid metabolism, carbohydrate metabolism, cell wall and membrane biogenesis. Based on the combined genomic, proteomic and qPCR data, a model for the formation of nematode trapping device in this fungus was proposed. In this model, multiple fungal signal transduction pathways are activated by its nematode prey to further regulate downstream genes associated with diverse cellular processes such as energy metabolism, biosynthesis of the cell wall and adhesive proteins, cell division, glycerol accumulation and peroxisome biogenesis. This study will facilitate the identification of pathogenicity-related genes and provide a broad foundation for understanding the molecular and evolutionary mechanisms underlying fungi-nematodes interactions

Evaluating combination models of solar irradiance on inclined surfaces and forecasting photovoltaic power generation

The traditional photovoltaic (PV) forecasting method depends on sufficient historical data (PV power station historical power generation data and numerical weather prediction meteorological data), which is not suitable for a newly built PV power plant. In order to calculate the PV array irradiance and to predict the PV power, a physical prediction approach based on solar irradiance on inclined surfaces is proposed. This method selects three decomposition models and four transposition models to be combined into 12 combination forecasting models. Furthermore, solar spectral response, incidence angle, and soiling factor are taken into account in the modified model. The results show that the methods combining the Liu–Jordan transposition model have higher forecasting accuracy under the different weather types. Among them, the Erbs + Liu–Jordan model predictions are the most accurate

The p38 MAPK/PMK-1 Pathway Is Required for Resistance to Nocardia farcinica Infection in Caenorhabditis elegance

Nocardia farcinica is an opportunistic pathogen that causes nocardiosis primarily in patients with compromised immune systems. In this study, we used the genetically tractable organism Caenorhabditis elegans as a model to study the innate immune responses to N. farcinica infection. We found that unlike other pathogenic bacteria such as Pseudomonas aeruginosa and Staphylococcus aureus, N. farcinica failed to kill adult worms. In another words, adult worms exposed to N. farcinica exhibited a normal lifespan, compared with those fed the standard laboratory food bacterium Escherichia coli OP50. Interestingly, deletion of three core genes (pmk-1, nsy-1 and sek-1) in the p38 MAPK/PMK-1 pathway reduced the survival of worm exposure to N. farcinica, highlighting a crucial role of this pathway for C. elegans in resistance to N. farcinica. Furthermore, our results revealed that N. farcinica exposure up-regulated the level of PMK-1 phosphorylation. The activation of PMK-1 promoted nuclear translocation of a transcription factor SKN-1/Nrf2, which in turn mediated N. farcinica infection resistance in C. elegans. Our results provide an excellent example that the integrity of immune system is key aspect for counteract with pathogenesis of N. farcinica

Function analysis of 5′-UTR of the cellulosomal xyl-doc cluster in Clostridium papyrosolvens

Abstract Background Anaerobic, mesophilic, and cellulolytic Clostridium papyrosolvens produces an efficient cellulolytic extracellular complex named cellulosome that hydrolyzes plant cell wall polysaccharides into simple sugars. Its genome harbors two long cellulosomal clusters: cip-cel operon encoding major cellulosome components (including scaffolding) and xyl-doc gene cluster encoding hemicellulases. Compared with works on cip-cel operon, there are much fewer studies on xyl-doc mainly due to its rare location in cellulolytic clostridia. Sequence analysis of xyl-doc revealed that it harbors a 5′ untranslated region (5′-UTR) which potentially plays a role in the regulation of downstream gene expression. Here, we analyzed the function of 5′-UTR of xyl-doc cluster in C. papyrosolvens in vivo via transformation technology developed in this study. Results In this study, we firstly developed an electrotransformation method for C. papyrosolvens DSM 2782 before the analysis of 5′-UTR of xyl-doc cluster. In the optimized condition, a field with an intensity of 7.5–9.0 kV/cm was applied to a cuvette (0.2 cm gap) containing a mixture of plasmid and late cell suspended in exponential phase to form a 5 ms pulse in a sucrose-containing buffer. Afterwards, the putative promoter and the 5′-UTR of xyl-doc cluster were determined by sequence alignment. It is indicated that xyl-doc possesses a long conservative 5′-UTR with a complex secondary structure encompassing at least two perfect stem-loops which are potential candidates for controlling the transcriptional termination. In the last step, we employed an oxygen-independent flavin-based fluorescent protein (FbFP) as a quantitative reporter to analyze promoter activity and 5′-UTR function in vivo. It revealed that 5′-UTR significantly blocked transcription of downstream genes, but corn stover can relieve its suppression. Conclusions In the present study, our results demonstrated that 5′-UTR of the cellulosomal xyl-doc cluster blocks the transcriptional activity of promoter. However, some substrates, such as corn stover, can relieve the effect of depression of 5′-UTR. Thus, it is speculated that 5′-UTR of xyl-doc was a putative riboswitch to regulate the expression of downstream cellulosomal genes, which is helpful to understand the complex regulation of cellulosome

Soft Controllable Carbon Fibre-based Piezoresistive Self-Sensing Actuators

Soft robots and devices exploit deformable materials that are capable of changes in shape to allow conformable physical contact for controlled manipulation. While the use of embedded sensors in soft actuation systems is gaining increasing interest, there are limited examples where the body of the actuator or robot is able to act as the sensing element. In addition, the conventional feedforward control method is widely used for the design of a controller, resulting in imprecise position control from a sensory input. In this work, we fabricate a soft self-sensing finger actuator using flexible carbon fibre-based piezoresistive composites to achieve an inherent sensing functionality and design a dual-closed-loop control system for precise actuator position control. The resistance change of the actuator body was used to monitor deformation and fed back to the motion controller. The experimental and simulated results demonstrated the effectiveness, robustness and good controllability of the soft finger actuator. Our work explores the emerging influence of inherently piezoresistive soft actuators to address the challenges of self-sensing, actuation and control, which can benefit the design of next-generation soft robots