Video quality assessment (VQA) is an important problem in computer vision. The videos in computer vision applications are usually captured in the wild. We focus on automatically assessing the quality ...of in-the-wild videos, which is a challenging problem due to the absence of reference videos, the complexity of distortions, and the diversity of video contents. Moreover, the video contents and distortions among existing datasets are quite different, which leads to poor performance of data-driven methods in the cross-dataset evaluation setting. To improve the performance of quality assessment models, we borrow intuitions from human perception, specifically, content dependency and temporal-memory effects of human visual system. To face the cross-dataset evaluation challenge, we explore a mixed datasets training strategy for training a single VQA model with multiple datasets. The proposed unified framework explicitly includes three stages: relative quality assessor, nonlinear mapping, and dataset-specific perceptual scale alignment, to jointly predict relative quality, perceptual quality, and subjective quality. Experiments are conducted on four publicly available datasets for VQA in the wild,
i.e.
, LIVE-VQC, LIVE-Qualcomm, KoNViD-1k, and CVD2014. The experimental results verify the effectiveness of the mixed datasets training strategy and prove the superior performance of the unified model in comparison with the state-of-the-art models. For reproducible research, we make the PyTorch implementation of our method available at
https://github.com/lidq92/MDTVSFA
.
Genomic insertions, duplications and insertion/deletions (indels), which account for ~14% of human pathogenic mutations, cannot be accurately or efficiently corrected by current gene-editing methods, ...especially those that involve larger alterations (>100 base pairs (bp)). Here, we optimize prime editing (PE) tools for creating precise genomic deletions and direct the replacement of a genomic fragment ranging from ~1 kilobases (kb) to ~10 kb with a desired sequence (up to 60 bp) in the absence of an exogenous DNA template. By conjugating Cas9 nuclease to reverse transcriptase (PE-Cas9) and combining it with two PE guide RNAs (pegRNAs) targeting complementary DNA strands, we achieve precise and specific deletion and repair of target sequences via using this PE-Cas9-based deletion and repair (PEDAR) method. PEDAR outperformed other genome-editing methods in a reporter system and at endogenous loci, efficiently creating large and precise genomic alterations. In a mouse model of tyrosinemia, PEDAR removed a 1.38-kb pathogenic insertion within the Fah gene and precisely repaired the deletion junction to restore FAH expression in liver.
Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment ...options. Standard survival models like the linear Cox proportional hazards model require extensive feature engineering or prior medical knowledge to model treatment interaction at an individual level. While nonlinear survival methods, such as neural networks and survival forests, can inherently model these high-level interaction terms, they have yet to be shown as effective treatment recommender systems.
We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations.
We perform a number of experiments training DeepSurv on simulated and real survival data. We demonstrate that DeepSurv performs as well as or better than other state-of-the-art survival models and validate that DeepSurv successfully models increasingly complex relationships between a patient's covariates and their risk of failure. We then show how DeepSurv models the relationship between a patient's features and effectiveness of different treatment options to show how DeepSurv can be used to provide individual treatment recommendations. Finally, we train DeepSurv on real clinical studies to demonstrate how it's personalized treatment recommendations would increase the survival time of a set of patients.
The predictive and modeling capabilities of DeepSurv will enable medical researchers to use deep neural networks as a tool in their exploration, understanding, and prediction of the effects of a patient's characteristics on their risk of failure.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Chinese listed companies play a vital role in national economy, which has contributed more than half of the gross domestic product. But the environmental pollution existed in the production and ...operation of companies has been ignored, so an objective and comprehensive efficiency assessment of Chinese listed companies were urgent. This paper constructed an index system based on green perspective, employed a super-efficiency slacks-based measure DEA (SBM-DEA) model considering undesirable outputs to assess the sustainability efficiency of Chinese listed companies. The results indicated that (1) the green sustainability efficiency of listed companies needed to be greatly improved. The average efficiency score of samples was 0.461 over 3 years, so the improvement potential was about 53.9%, only 23 companies were relatively effective. (2) The sustainability efficiency of companies has shown a slow upward trend in volatility since 2017, the non-daily consumer goods sector was the most efficient, while utilities were relatively inefficient. (3) When efficient and inefficient companies were compared, the latter were found to have significant input surplus, especially in water consumption. (4) The analysis of sensitivity on inputs and outputs showed that attention should be paid to water consumption and greenhouse gas emissions. (5) Spearman non-parametric test verified that company size and debt-paying ability were the implicit factors affecting company sustainability efficiency. The results of performance evaluation can not only provide a potential reference for the operation and management of listed companies in China, but also have guiding significance for local governments to strengthen the supervision of companies.
Graphical abstract
Chemoresistance remains the uppermost disincentive for cancer treatment on account of many genetic and epigenetic alterations. Long non-coding RNAs (lncRNAs) are emerging players in promoting cancer ...initiation and progression. However, the regulation and function in chemoresistance are largely unknown. Herein, we identified ARHGAP5-AS1 as a lncRNA upregulated in chemoresistant gastric cancer cells and its knockdown reversed chemoresistance. Meanwhile, high ARHGAP5-AS1 expression was associated with poor prognosis of gastric cancer patients. Intriguingly, its abundance is affected by autophagy and SQSTM1 is responsible for transporting ARHGAP5-AS1 to autophagosomes. Inhibition of autophagy in chemoresistant cells, thus, resulted in the upregulation of ARHGAP5-AS1. In turn, it activated the transcription of ARHGAP5 in the nucleus by directly interacting with ARHGAP5 promoter. Interestingly, ARHGAP5-AS1 also stabilized ARHGAP5 mRNA in the cytoplasm by recruiting METTL3 to stimulate m
A modification of ARHGAP5 mRNA. As a result, ARHGAP5 was upregulated to promote chemoresistance and its upregulation was also associated with poor prognosis in gastric cancer. In summary, impaired autophagic degradation of lncRNA ARHGAP5-AS1 in chemoresistant cancer cells promoted chemoresistance. It can activate the transcription of ARHGAP5 in the nucleus and stimulate m
A modification of ARHGAP5 mRNA to stabilize ARHGAP5 mRNA in the cytoplasm by recruiting METTL3. Therefore, targeting ARHGAP5-AS1/ARHGAP5 axis might be a promising strategy to overcome chemoresistance in gastric cancer.
Silicon is getting much attention as the promising next-generation negative electrode materials for lithium-ion batteries with the advantages of abundance, high theoretical specific capacity and ...environmentally friendliness. In this work, a series of phosphorus (P)-doped silicon negative electrode materials (P-Si-34, P-Si-60 and P-Si-120) were obtained by a simple heat treatment method, which can maintain the original nanoparticle morphology. The P-Si-60 material shows excellent discharge specific capacity, rate performance and cycling performance. The discharge specific capacity after 50 cycles remains > 2000 mAh g
−1
with a capacity retention rate of 74.3%. The excellent electrochemical properties of P-Si-60 material can be attributed to the phosphorus doping without destroying the original particle morphology and nanostructure and the higher intrinsic electric conductivity. It will bring new thoughts for the further application of silicon negative electrode materials.
There is no consensus on the prevalence of sarcopenia or its impact on mortality in end‐stage renal disease patients undergoing dialysis. This review aimed to summarize the diagnostic criteria of ...sarcopenia and its prevalence and impact on the mortality of end‐stage renal disease patients undergoing dialysis. Embase, MEDLINE, PubMed, and Cochrane Library were searched from inception to 8 May 2021 to retrieve eligible studies that assessed muscle mass by commonly used instruments, such as dual‐energy X‐ray absorptiometry, bioelectrical impedance analysis, magnetic resonance imaging, and body composition monitor. Two assessment tools matched to study designs were employed to evaluate study quality. Pooled sarcopenia prevalence was calculated with 95% confidence interval (CI), and heterogeneity was estimated using the I2 test. Associations of sarcopenia with mortality were expressed as hazard ratio (HR) and 95% CI. The search identified 3272 studies, and 30 studies (6162 participants, mean age from 47.5 to 77.5 years) were analysed in this review. The risk of bias in the included studies was low to moderate. Twenty‐two studies defined sarcopenia based on low muscle mass (LMM) plus low muscle strength and/or low physical performance, while eight studies used LMM alone. Muscle mass was assessed by different instruments, and a wide range of cut‐off points were used to define LMM. Overall, sarcopenia prevalence was 28.5% (95% CI 22.9–34.1%) and varied from 25.9% (I2 = 94.9%, 95% CI 20.4–31.3%; combined criteria) to 34.6% (I2 = 98.1%, 95% CI 20.9–48.2%; LMM alone) (P = 0.247 between subgroups). The statistically significant differences were not found in the subgroups of diagnostic criteria (P > 0.05) and dialysis modality (P > 0.05). Additionally, the sarcopenia prevalence could not be affected by average age regression coefficient 0.004 (95% CI: −0.005 to 0.012), P = 0.406 and dialysis duration regression coefficient 0.002 (95% CI −0.002 to 0.005), P = 0.327 in the meta‐regression. The pooled analyses showed that combined criteria of sarcopenia were related to a higher mortality risk HR 1.82 (I2 = 26.3%, 95% CI 1.38–2.39), as was LMM HR 1.61 (I2 = 26.0%, 95% CI 1.31–1.99) and low muscle strength HR 2.04 (I2 = 80.4%, 95% CI 1.19–3.5). Although there are substantial differences in diagnostic criteria, sarcopenia is highly prevalent in dialysis patients and is linked to increased mortality. The standardization of sarcopenia diagnostic criteria would be beneficial, and future longitudinal studies are needed to investigate the prevalence and prognostic value of sarcopenia in dialysis patients.
Shot peening is a widely used surface strengthening technique which can improve the fatigue life of metal components by introducing reasonably distributed compressive residual stress. The accurate ...prediction of residual stress distribution of parts is a tough challenge in the simulation of shot peening. In this paper, the numerical calculation of the residual stress of shot peening is investigated with 12Cr2Ni4A steel as the target. A two-dimensional Gaussian distribution model is proposed to calculate the number of impact shots. A method is proposed to calculate shot peening coverage using displacement and displacement gradient, which increases the identification accuracy of peened surface topography and provides a scientific method for coverage calculation. A random multi-shot finite element model for high strength steel is established considering the elastoplastic of shot. The effects of the process parameters, initial surface morphology and initial residual stress on the residual stress distribution after shot peening are investigated. The accuracy of the proposed method is verified by comparing the measured and simulated results.
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•A two-dimensional Gaussian distribution model is proposed to calculate the number of impact shots.•An improved model for predicting the residual stress distribution in shot peening is developed.•A method to calculate the shot peening coverage using displacement and displacement gradient is proposed.•The effects of treatment parameters and initial state on residual stress are studied.•The experiment is used to verify the proposed model.
CRISPR-Cas9-associated base editing is a promising tool to correct pathogenic single nucleotide mutations in research or therapeutic settings. Efficient base editing requires cellular exposure to ...levels of base editors that can be difficult to attain in hard-to-transfect cells or in vivo. Here we engineer a chemically modified mRNA-encoded adenine base editor that mediates robust editing at various cellular genomic sites together with moderately modified guide RNA, and show its therapeutic potential in correcting pathogenic single nucleotide mutations in cell and animal models of diseases. The optimized chemical modifications of adenine base editor mRNA and guide RNA expand the applicability of CRISPR-associated gene editing tools in vitro and in vivo.
A ratiometric surface-enhanced Raman scattering (SERS) aptasensor based on internal standard (IS) methods was proposed for the ultrasensitive and reproducible quantitative detection of silver ion ...(Ag+) with Au@Ag core-shell nanoparticle (Au@Ag NP) substrate. In principle, the thiolated 5′-Rox C-containing labeled aptamer probe (Rox-aptamer) is firstly immobilized on the SERS substrate surface and then hybridizes with the complementary DNA (cDNA) to form a rigid double-stranded DNA (dsDNA), in which the Rox Raman labels is used to produce the Raman signal. Furthermore, the pyridine is employed as an IS element to provide the ratiometric determination of target. In the presence of Ag+, the Rox-aptamer is turned into the cytosine (C)-Ag+-C mediated hairpin structure, which remarkably reduces the distance between the Rox labels and the Au@Ag NP surface responsible for a measurable ‘turn-on’ signal change of Rox. This IS-based ratiometric SERS aptasensor exhibits a limit of detection of 50 pM for Ag+ with a linear detection range from 0.1 to 100 nM and the shortcoming of irreproducibility of SERS signal could be overcome. The proposed method provides a simple, robust, and rapid approach for the sensitive and reproducible quantitative detection of Ag+, and it could also be used for the detection of other metal ions which exhibits specific interactions with natural or synthetic bases.
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•An internal standard-based ratiometric SERS aptasensor was developed for ultrasensitive quantitative Ag+ detection.•The ratiometric SERS aptasensor achieves a limit of detection (LOD) to 50 pM Ag+.•This strategy may offer a new direction for development of high performance SERS aptasensors for other metal ions detection.
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