Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising

Significant progress has been made in self-supervised image denoising (SSID) in the recent few years. However, most methods focus on dealing with spatially independent noise, and they have little practicality on real-world sRGB images with spatially correlated noise. Although pixel-shuffle downsampling has been suggested for breaking the noise correlation, it breaks the original information of images, which limits the denoising performance. In this paper, we propose a novel perspective to solve this problem, i.e., seeking for spatially adaptive supervision for real-world sRGB image denoising. Specifically, we take into account the respective characteristics of flat and textured regions in noisy images, and construct supervisions for them separately. For flat areas, the supervision can be safely derived from non-adjacent pixels, which are much far from the current pixel for excluding the influence of the noise-correlated ones. And we extend the blind-spot network to a blind-neighborhood network (BNN) for providing supervision on flat areas. For textured regions, the supervision has to be closely related to the content of adjacent pixels. And we present a locally aware network (LAN) to meet the requirement, while LAN itself is selectively supervised with the output of BNN. Combining these two supervisions, a denoising network (e.g., U-Net) can be well-trained. Extensive experiments show that our method performs favorably against state-of-the-art SSID methods on real-world sRGB photographs. The code is available at https://github.com/nagejacob/SpatiallyAdaptiveSSID.Comment: CVPR 2023 Camera Read

A Novel Evolution-Based Method for Detecting Gene-Gene Interactions

BACKGROUND: The rapid advance in large-scale SNP-chip technologies offers us great opportunities in elucidating the genetic basis of complex diseases. Methods for large-scale interactions analysis have been under development from several sources. Due to several difficult issues (e.g., sparseness of data in high dimensions and low replication or validation rate), development of fast, powerful and robust methods for detecting various forms of gene-gene interactions continues to be a challenging task. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we have developed an evolution-based method to search for genome-wide epistasis in a case-control design. From an evolutionary perspective, we view that human diseases originate from ancient mutations and consider that the underlying genetic variants play a role in differentiating human population into the healthy and the diseased. Based on this concept, traditional evolutionary measure, fixation index (Fst) for two unlinked loci, which measures the genetic distance between populations, should be able to reveal the responsible genetic interplays for disease traits. To validate our proposal, we first investigated the theoretical distribution of Fst by using extensive simulations. Then, we explored its power for detecting gene-gene interactions via SNP markers, and compared it with the conventional Pearson Chi-square test, mutual information based test and linkage disequilibrium based test under several disease models. The proposed evolution-based method outperformed these compared methods in dominant and additive models, no matter what the disease allele frequencies were. However, its performance was relatively poor in a recessive model. Finally, we applied the proposed evolution-based method to analysis of a published dataset. Our results showed that the P value of the Fst -based statistic is smaller than those obtained by the LD-based statistic or Poisson regression models. CONCLUSIONS/SIGNIFICANCE: With rapidly growing large-scale genetic association studies, the proposed evolution-based method can be a promising tool in the identification of epistatic effects

Konsep Proses Pemesinan Berkelanjutan

Metal industrial machining usually strongth pressure from all sectors, ether raw material industries or user metal industries. Manufacturint process which offered to all sectors industries or companies that sustainable manufakturing consist of three main factor are efective cost, enviroment and social performance

Sleeping More Hours Per Day Than Working Can Prevent New-Onset Diabetes

Objectives: We expressed the combined effect by the ratio of daily sleep time to daily work time. The aim of this study was to discussed the predictive ability of daily sleep hours/work hours (SH/WH) ratio for diabetes risk.Methods: Cox proportional hazards regression was used to calculate the hazard ratios (HRs) of new-onset diabetes. Restricted cubic spline analyses were performed to visualize the influence trend of SH/WH ratio and diabetes risk.Results: The RCS model revealed a non-linear and L-shaped correlation between SH/WH ratio and diabetes risk. Compared with the participates with SH/WH ratio <1, those with a ratio ≥1 had a lower risk of developing diabetes. The multivariable adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) of new-onset diabetes in Q2, Q3, Q4 and Q5 groups compared with Q1 group were 0.82 (0.57, 1.19), 1.05 (0.69, 1.59), 0.57 (0.36, 0.91), 0.66 (0.42, 1.06). The Kaplan-Meier curve showed that Q4 group had lower cumulative incidence.Conclusion: Sleeping longer than working (SH/WH ratio ≥1) can reduce risk for developing diabetes. A minimal risk observed at 1.10–<1.37 (the fourth quintile) of SH/WH ratio

Evaluation of pharmacist-led telemedicine medication management for hypertension established patients during COVID-19 pandemic: A pilot study

AimTo evaluate the impact of a telemedicine medication management service in patients with hypertension.MethodsParticipants were allocated to either a telemedicine service (N = 173) or usual care (UC) (N = 179). The primary outcome was blood pressure (BP) reduction from baseline to the 6-month follow-up visit, the proportion of the target BP achievement, overall adherence to prescribed medication as well as a composite of non-fatal stroke, non-fatal myocardial infarction and cardiovascular death.ResultsAt 6 months, BP was controlled in 89.6% (n = 155) of intervention patients and 78.8% (n = 141) of UC patients (OR = 1.14, 95% CI = 1.04–1.25, P = 0.006), giving a mean difference of −6.0 (−13.0 to −2.5 mmHg) and −2.0 mmHg (−4.0 to −0.1 mmHg) in SBP and DBP, respectively. 17.9% (n = 31) of the patients in the intervention group were non-adherent with medications, compared with 29.1% (n = 52) in the UC group (P = 0.014). The composite clinical endpoints were reached by 2.9% in the intervention group and 4.5% in the control group with no significant differences (OR = 1.566, 95% CI = 0.528–4.646).ConclusionTelemedicine medication management for hypertension management had led to better BP control and medication adherence improvement than UC during COVID-19 epidemic, resulting in a reduction of overall adverse cardiovascular events occurrence

Using field measurements across land cover types to evaluate albedo-based wind friction velocity and estimate sediment transport

The soil surface wind friction velocity (us*) is an essential parameter for predicting sediment transport on rough surfaces. However, this parameter is difficult and time-consuming to obtain over large areas due to its spatiotemporal heterogeneity. The albedo-based approach calibrates normalized shadow retrieved from any source of albedo data with laboratory measurements of aerodynamic properties. This enables direct and cross-scale us* retrieval but has not been evaluated against field measurements for different cover types. We evaluated the approach's performance using wind friction velocity (u*) measurements from ultrasonic anemometers. We retrieved coincident field pyranometer and satellite albedo at 48 sites that were spread over approximately 1,800 km on the Inner Mongolia Plateau, including grassland, artificial shrubland, open shrubland, and gobi land. For all cover types, u* estimates from ultrasonic anemometers were close to the albedo-based results approach. Our results confirm and extend the findings that the approach works across scales from lab to field measurements and permits large-area assessments using satellite albedo. We compared the seasonal sediment transport across the region calculated from albedo-based us* with results from an exemplar traditional transport model (QT) driven by u* with aerodynamic roughness length varying with land cover type and fixed over time. The traditional model could not account for spatiotemporal variation in roughness elements and considerably over-estimated sediment transport, particularly in partially vegetated and gravel-covered central and western parts of the Inner Mongolia Plateau. The albedo-based sediment transport (QA) estimates will enable dynamic monitoring of the interaction between wind and surface roughness to support Earth System models

Determining threshold values for root-soil water weighted plant water deficit index based smart irrigation

Trabajo desarrollado bajo la financiación del proyecto “Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping Systems” (773903), coordinado por José Alfonso Gómez Calero, investigador del Instituto de Agricultura Sostenible (IAS).Plant water deficit index (PWDI) represents the extent of water stress by relating soil moisture to the ability of a plant to take up water including consideration of the relative distribution of soil water to roots. However, for a smart irrigation decision support system, we are challenged in determining reliable thresholds of PWDI to initiate irrigation events to achieve predetermined yield and/or water use efficiency (WUE) targets. Taking drip irrigated maize and sprinkler irrigated alfalfa as examples, field experiments were conducted to investigate the choice and effects of PWDI thresholds. The results indicated that, with increasing PWDI thresholds, irrigation times and quantity of water, as well as crop transpiration, growth, and yield, were all significantly limited while WUE was enhanced except under extremely stressed conditions. To disconnect the unpredictable effects of other factors, yield and WUE were normalized to their corresponding potential values. Within the experimentally determined range of PWDI, relative yield and WUE were described with linear functions for maize, and linear and quadratic functions for alfalfa, allowing identification of the most efficient threshold value according to the objective parameter of choice. The method described can be adopted in smart irrigation decision support systems with consideration of spatial variability and after further verification and improvement under more complicated situations with various crop types and varieties, environmental conditions, cultivation modes, and wider or dynamic PWDI thresholds allowing regulated deficit irrigation.This research was supported partly by National Key Research and Development Program of China (2017YFE0118100, 2016YFD0200303), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 research and innovation programme under Project SHui, grant agreement No 773903.Peer reviewe

Relationships between the Toxicities of Radix Aconiti Lateralis Preparata (Fuzi) and the Toxicokinetics of Its Main Diester-Diterpenoid Alkaloids

The processed lateral root of Aconitum carmichaelii Deb (Aconiti Radix lateralis praeparata or Fuzi) is a potent traditional herbal medicine extensively used in treatment of cardiovascular diseases, rheumatism arthritis, and bronchitis in many Asian countries. Although Fuzi has promising therapeutic effects, its toxicities are frequently observed. Three main C19-diester-diterpenoid alkaloids (DDAs) are believed to be the principal toxins of the herb. Although toxicokinetic profiles of the toxic DDAs have already been examined in several studies, they have seldom been correlated with the toxicities of Fuzi. The current article aimed to investigate the relationship between the up-to-date toxicokinetic data of the toxic DDAs and the existing evidence of the toxic effects of Fuzi. Relationships between the cardiac toxicity and the plasma and heart concentration of DDAs in mice and rats were established. Based on our findings, clinical monitoring of the plasma concentrations of DDAs of Fuzi is recommended to prevent potential cardiac toxicities. Additionally, caution with respect to potential hepatic and renal toxicity induced by Fuzi should be exercised. In addition, further analyses focusing on the preclinical tissue distribution profile of DDAs and on the long-term toxicokinetic-toxicity correlation of DDAs are warranted for a better understanding of the toxic mechanisms and safer use of Fuzi

The Potential for PE Microplastics to Affect the Removal of Carbamazepine Medical Pollutants from Aqueous Environments by Multiwalled Carbon Nanotubes

Microplastics are ubiquitous in aquatic environments and interact with other kinds of pollutants, which affects the migration, transformation, and fate of those other pollutants. In this study, we employ carbamazepine (CBZ) as the contaminant to study the influence of polyethylene (PE) microplastics on the adsorption of CBZ pollutants by multiwalled carbon nanotubes (MCNTs) in aqueous solution. The adsorption capacity of CBZ by MCNTs in the presence of PE microplastics was obviously lower than that by MCNTs alone. The influencing factors, including the dose of microplastics, pH, and CBZ solution concentration, on the adsorption of CBZ by MCNTs and MCNTs−PE were thoroughly investigated. The adsorption rate of CBZ by MCNTs decreased from 97.4% to 90.6% as the PE microplastics dose increased from 2 g/L to 20 g/L. This decrease occurred because the MCNTs were coated on the surface of the PE microplastics, which further decreased the effective adsorption area of the MCNTs. This research provides a framework for revealing the effect of microplastics on the adsorption of pollutants by carbon materials in aqueous environments