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CoFe-based catalysts are efficient electrocatalysts for the oxygen evolution reaction (OER) in alkaline media. Here, we present a simple one-pot hydrothermal method for synthesizing a series of CoFe glycerates with controllable surface morphologies and investigate their potential as highly efficient catalysts for the OER in alkaline media. These CoFe glycerates exhibit a unique yolk-shell microsphere structure assembled from ultrathin nanosheets. The adjustment of the surface nanosheet size is achieved by varying the CoFe ratio, ensuring a more efficient electrocatalytic system for the OER process. Due to the abundant active sites provided by the yolk-shell structure and interleaved ultrathin nanosheets, Co3Fe1 glycerate (Co3Fe1 gly) demonstrates a low overpotential (283 mV) and a small Tafel slope (44.61 mV dec-1) at 10 mA cm-2. Additionally, Co3Fe1 gly exhibits excellent durability in alkaline electrolytes. Moreover, a series of characterizations demonstrate that the active sites of Co3Fe1 gly are the high-valence Co species generated during the OER process. This study opens a promising avenue for utilizing efficient and low-cost electrocatalysts to enhance OER performance.
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This article focuses on the issue of novel dynamic event-triggered consensus control of multiagent systems (MASs) with denial-of-service (DoS) attacks. Different from the conventional Markovian switching topologies, the generally uncertain semi-Markovian (GUSM) switching topologies with partially unknown elements and time-dependent uncertainties are constructed for the leader-following MASs by considering the equipment performance and external uncertain environment influence. To save communication resources, the novel dynamic memory event-triggered strategy (DMETS) is presented to decrease the frequency of communication between agents. Some secure consensus control criteria are established for the MASs with GUSM switching topologies and DoS attacks due to the potential system communication disruption caused by attackers. Finally, two physical system examples are designed to prove the effectiveness of the presented method.
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The study examines the digital finance (DF) and regional sustainable development (RSD) across 90 cities within six major city clusters in China over the period from 2011 to 2020. By constructing an evaluation index system for DF and RSD, we employed the entropy value method to assess their levels, and the coupling coordination degree (CCD) model to evaluate their interplay. Our analysis extended to temporal and spatial disparities, distribution dynamics, and the convergence of CCD through kernel density estimation, Markov chain analysis, σ -convergence, and ß -convergence techniques. The results indicate a consistent upward trend in CCD, yet it remains at a low level with pronounced regional disparities and temporal characteristics. The kernel density distribution's central tendency has shifted rightward progressively, albeit with a decelerating pace annually. The Markov transition probability matrix suggests a stable CCD across various levels, hinting at "club convergence". Furthermore, both σ -convergence and ß -convergence analyses reveal significant convergence trends in CCD, enhanced by economic growth factors. Using the Quadratic Assignment Procedure (QAP) method, we found that regional economic growth disparities significantly influence the CCD's regional variances.
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Somatic cell nuclear transfer (SCNT) is one of the primary methods for production of genetically engineered sheep, which allows for gene editing or transgene introduction in somatic cells. The use of SCNT eliminates the risk of genetic mosaicism in embryos and animals that is commonly observed after zygote micromanipulations. This retrospective analysis of SCNT in sheep performed at Utah State University, spanning from 2016 to 2021, examined parameters that may impact pregnancy and full-term development, including donor oocytes (donor age), donor cell lines, SCNT parameters (time of oocyte activation following SCNT, number of transferred embryos, in vitro maturation and culture conditions), and recipients (surgical number and ovulatory status), as well as factors that may correlate with large offspring syndrome or abnormal offspring syndrome (LOS/AOS) in the fetuses and lambs. Our findings indicated that compared to prepubertal oocytes, the SCNT embryos produced from adult sheep oocytes had comparable in vitro maturation rates, pregnancy and full-term development rates, as well as SCNT efficiency. In addition, earlier activation time of SCNT embryos (e.g. 24-26 h post maturation) was correlated to the early pregnancy loss rate, full-term rate, and SCNT efficiency. Compared to our standard serum-containing medium, commercial serum-free culture medium showed a positive correlation with the full-term development of sheep SCNT embryos. Transferring 15-30 embryos per recipient resulted in consistently good pregnancy rates. Surgical numbers and ovulatory status (having at least one follicle between 6 and 12 mm in size or a corpus hemorrhagicum (CH)) of recipients did not affect pregnancy and full-term development rates. In summary, this retrospective analysis identified parameters for improving pregnancy and full-term development of SCNT embryos in sheep.
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Técnicas de Transferencia Nuclear , Animales , Técnicas de Transferencia Nuclear/veterinaria , Ovinos/embriología , Estudios Retrospectivos , Femenino , Embarazo , Oocitos/fisiología , Transferencia de Embrión/veterinaria , Transferencia de Embrión/métodos , Clonación de Organismos/veterinaria , Clonación de Organismos/métodos , Técnicas de Cultivo de Embriones/veterinariaRESUMEN
Background: This qualitative study, part of a prospective mixed-methods research, aimed to gain insights into the medical experiences and disease perceptions of Chinese patients living with rheumatoid arthritis (RA). Specifically, the study examined how RA patients' perceptions of their disease were influenced by the diagnosis and treatment they receive. Methods: RA patients undergoing treatment were invited to participate in this qualitative study. Face-to-face semi-structured interviews were conducted among 18 patients, and the collected data were analyzed using thematic analysis. Results: The 18 participants in this study had a mean (SD) age of 58, a median disease duration of 6.5 years, and a predominance of female subjects (17 out of 18). The qualitative analysis identified two themes with six sub-themes: 1. Patients' experiences of treatment: discovery of the disease, misdiagnosis and mistreatment, and patients' treatment choices; 2. Feelings about the disease: psychological impact, reflections on the disease, and expectations of treatment. Conclusion: This study provides valuable perspectives and data to enhance the understanding of the relationship between patients' illness perceptions and their healthcare choices.
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OBJECTIVE: To assess and compare the composition of tongue coating microbiota among patients at different stages of rheumatoid arthritis (RA). METHODS: A total of 47 patients diagnosed with RA, as per the American College of Rheumatology criteria, and 10 healthy individuals were enrolled in this study. The RA patients were stratified considering their Disease Activity Score 28 (DAS28), a composite measure based on the 28 tender and swollen joint count and erythrocyte sedimentation rate (ESR). The study population was further categorized into active phase group (LMH group) and inactive phase group (RE group) according to their DAS28 values. DNA extraction was extracted from tongue coating samples. Subsequently, the V3-V4 16S rDNA region was selectively amplified and sequenced through high-throughput 16S rDNA analysis. The resulting data were then utilized to ascertain the microbial contents. RESULTS: Significant variations were observed in the tongue coating microbiota of patients with RA during active and inactive phases, in comparison to healthy individuals (p < 0.05). At the genus level, the presence of Prevotellan, Veillonella, Rothia, and Neisseria in RA patients was notably more evident than in the healthy control (HC) group. These disparities find support in existing research on gut and oral microbiota. During the active phase of RA, the relative abundance of Veillonella, Rothia, and Neisseria in the tongue coating microbiota of patients was significantly higher than in those with inactive RA. These findings underscore the need for further and in-depth research on the potential impact of these microorganisms on the progression of RA disease. CONCLUSION: The results substantiate the hypothesis that tongue coating microbes actively contribute to the progression of RA.
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Artritis Reumatoide , Bacterias , Progresión de la Enfermedad , Microbiota , ARN Ribosómico 16S , Lengua , Humanos , Artritis Reumatoide/microbiología , Lengua/microbiología , Lengua/patología , Femenino , Masculino , Persona de Mediana Edad , ARN Ribosómico 16S/genética , Adulto , Microbiota/genética , Bacterias/clasificación , Bacterias/genética , Bacterias/aislamiento & purificación , ADN Bacteriano/genética , Anciano , Índice de Severidad de la EnfermedadRESUMEN
In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, ß-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute ß-convergence, and conditional ß-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.
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Desarrollo Económico , Ríos , China , Ciudades , CabezaRESUMEN
Landslides refer to occurrences of massive ground movements due to geological (and meteorological) factors, and can have disastrous impacts on property, economy, and even lead to the loss of life. The advances in remote sensing provide accurate and continuous terrain monitoring, enabling the study and analysis of land deformation which, in turn, can be used for land deformation prediction. Prior studies either rely on predefined factors and patterns or model static land observations without considering the subtle interactions between different point locations and the dynamic changes of the surface conditions, causing the prediction model to be less generalized and unable to capture the temporal deformation characteristics. To address these issues, we present DyLand, a dynamic manifold learning framework that models the dynamic structures of the terrain surface. We contribute to the land deformation prediction literature in four directions. First, DyLand learns the spatial connections of interferometric synthetic aperture radar (InSAR) measurements and estimates the conditional distributions on a dynamic terrain manifold with a novel normalizing flow-based method. Second, instead of modeling the stable terrains, we incorporate surface permutations and capture the innate dynamics of the land surface while allowing for tractable likelihood estimations on the manifold. Third, we formulate the spatiotemporal learning of land deformations as a dynamic system and unify the learning of spatial embeddings and surface deformation. Finally, extensive experiments on curated real-world InSAR datasets (land slopes prone to landslides) show that DyLand outperforms existing benchmark models.
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As one of the key components of clinical trials, blinding, if successfully implemented, can help to mitigate the risks of implementation bias and measurement bias, consequently improving the validity and reliability of the trial results. However, successful blinding in clinical trials of traditional Chinese medicine (TCM) is hard to achieve, and the evaluation of blinding success through blinding assessment lacks established guidelines. Taking into account the challenges associated with blinding in the TCM field, here we present a framework for assessing blinding. Further, this study proposes a blinding assessment protocol for TCM clinical trials, building upon the framework and the existing methods. An assessment report checklist and an approach for evaluating the assessment results are presented based on the proposed protocol. It is anticipated that these improvements to blinding assessment will generate greater awareness among researchers, facilitate the standardization of blinding, and augment the blinding effectiveness. The use of this blinding assessment may further advance the quality and precision of TCM clinical trials and improve the accuracy of the trial results. The blinding assessment protocol will undergo continued optimization and refinement, drawing upon expert consensus and experience derived from clinical trials. Please cite this article as: Wang XC, Liu XY, Shi KL, Meng QG, Yu YF, Wang SY, Wang J, Qu C, Lei C, Yu XP. Blinding assessment in clinical trials of traditional Chinese medicine: Exploratory principles and protocol. J Integr Med. 2023; 21(6): 528-536.
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Medicamentos Herbarios Chinos , Medicina Tradicional China , Medicamentos Herbarios Chinos/uso terapéutico , Medicina Tradicional China/métodos , Evaluación de Resultado en la Atención de Salud , Estándares de Referencia , Reproducibilidad de los Resultados , Proyectos de Investigación , Ensayos Clínicos como AsuntoRESUMEN
In this paper, a novel simulation-based evolutionary method is presented for designing parameter-free MEMS structures with maximum degrees of freedom. This novel design method enabled semiautomatic structure evolution by weighing the attributes of each segment of the structure and yielded an optimal design after multiple iterations. The proposed method was utilized to optimize the pressure-sensitive diaphragm of a piezoresistive pressure sensor (PPS). Finite element method (FEM) simulations revealed that, in comparison to conventional diaphragms without islands and with square islands, the optimized diaphragm increased the stress by 10% and 16% and reduced the nonlinearity by 57% and 77%, respectively. These improvements demonstrate the value of this method. Characterization of the fabricated PPS revealed a high sensitivity of 8.8 mV V-1 MPa-1 and a low nonlinearity of 0.058% FS at 20 °C, indicating excellent sensor performance.
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Introduction: The retina is the "window" of the central nervous system. Previous studies discovered that retinal thickness degenerates through the pathological process of the Alzheimer's disease (AD) continuum. Hippocampal atrophy is one of the typical clinical features and diagnostic criteria of AD. Former studies have described retinal thinning in normal aging subjects and AD patients, yet the association between retinal thickness and hippocampal atrophy in AD is unclear. The optical coherence tomography (OCT) technique has access the non-invasive to retinal images and magnetic resonance imaging can outline the volume of the hippocampus. Thus, we aim to quantify the correlation between these two parameters to identify whether the retina can be a new biomarker for early AD detection. Methods: We systematically searched the PubMed, Embase, and Web of Science databases from inception to May 2023 for studies investigating the correlation between retinal thickness and hippocampal volume. The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the study quality. Pooled correlation coefficient r values were combined after Fisher's Z transformation. Moderator effects were detected through subgroup analysis and the meta-regression method. Results: Of the 1,596 citations initially identified, we excluded 1,062 studies after screening the titles and abstract (animal models, n = 99; irrelevant literature, n = 963). Twelve studies met the inclusion criteria, among which three studies were excluded due to unextractable data. Nine studies were eligible for this meta-analysis. A positive moderate correlation between the retinal thickness was discovered in all participants of with AD, mild cognitive impairment (MCI), and normal controls (NC) (r = 0.3469, 95% CI: 0.2490-0.4377, I2 = 5.0%), which was significantly higher than that of the AD group (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%) (p < 0.05). Among different layers, the peripapillary retinal nerve fiber layer (pRNFL) indicated a moderate positive correlation with hippocampal volume (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%). The retinal pigmented epithelium (RPE) was also positively correlated [r = 0.1421, 95% CI:(-0.0447-0.3192), I2 = 84.1%]. The retinal layers and participants were the main overall heterogeneity sources. Correlation in the bilateral hemisphere did not show a significant difference. Conclusion: The correlation between RNFL thickness and hippocampal volume is more predominant in both NC and AD groups than other layers. Whole retinal thickness is positively correlated to hippocampal volume not only in AD continuum, especially in MCI, but also in NC. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, CRD42022328088.
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We explored changes in pregnancy-specific glycoprotein 9 (PSG9) levels in the serum of patients with preeclampsia and the effects and underlying mechanisms of PSG9 effects on calcium (Ca2+) homeostasis and nitric oxide (NO) release in human umbilical vein endothelial cells (HUVECs). Western blotting was used to detect protein expression levels, and an NO fluorescence probe was used to examine NO production. Intracellular Ca2+ concentrations were measured using a Ca2+-sensitive fluorescent dye under a fluorescence microscope. Compared with those in healthy pregnant women, serum PSG9 levels were significantly decreased in patients with preeclampsia. PSG9 (0.1 µg/mL) treatment of HUVECs significantly enhanced the expression levels of store-operated calcium entry (SOCE) channel proteins Orai1 and Orai2, but not Orai3, and of endothelial nitric oxide synthase (eNOS) and NO production. Pretreatment with an inhibitor of SOCE (BTP2) abolished PSG9-enhanced Orai1, Orai2, and eNOS expression levels and NO production in HUVECs. The mechanisms underlying SOCE that were PSG9 enhanced in HUVECs appear to involve the Ca2+/eNOS/NO signaling pathway. These findings suggest that serum PSG9 levels may be a potential biomarker for monitoring the occurrence or development of preeclampsia in pregnancy and that PSG9 may be a potential therapeutic target for the treatment of preeclampsia.
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This article focuses on the synchronization problem of delayed inertial neural networks (INNs) with generally uncertain Markovian jumping and their applications in image encryption. The random connection weight strengths and generally uncertain Markovian are discussed in the INNs model. Compared with most existing INNs models that have constant connection weight strengths, our model is more practical because connection weight strengths of INNs may randomly vary due to the external and internal environment and human factor. The delay-range-dependent synchronization conditions (DRDSCs) could be obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial-based relaxed inequality (HOPRII). In addition, the desired controllers are obtained by solving a set of linear matrix inequalities. Finally, two examples are shown to demonstrate the effectiveness of the proposed results.
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This article focuses on the dissipativity-based consensus tracking control (DBCTC) problems of time-varying delayed leader-following nonlinear multiagent systems (LFNMASs) with the event-triggered transmission strategy. The switching topologies of the LFNMASs are subject to the uncertain and partially unknown generally Markovian jumping process. The control inputs of the following agents are updated according to the proposed event-triggered transmission strategy, which could reduce the communication burden. Based on the event-triggered transmission condition and distributed consensus protocol, some dissipativity-based criteria obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial-based relaxed inequality (HOPRII) are proposed to guarantee the LFNMAS consensus. The validity of the main results is verified by two simulation examples.
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Type I interferons (IFNs) initiate immune responses to viral infections. Their effects are mediated by the type I IFN receptor, IFNAR, comprised of two subunits: IFNAR1 and IFNAR2. One or both chains of the sheep IFNAR were disrupted in fetal fibroblast lines using CRISPR/Cas9 and 12 lambs were produced by somatic cell nuclear transfer (SCNT). Quantitative reverse transcription-polymerase chain reaction for IFN-stimulated gene expression showed that IFNAR deficient sheep fail to respond to IFN-alpha. Furthermore, fibroblast cells from an IFNAR2 -/- fetus supported significantly higher levels of Zika virus (ZIKV) replication than wild-type fetal fibroblast cells. Although many lambs have died from SCNT related problems or infections, one fertile IFNAR2 -/- ram lived to over 4 years of age, remained healthy, and produced more than 80 offspring. Interestingly, ZIKV infection studies failed to demonstrate a high level of susceptibility. Presumably, these sheep compensated for a lack of type I IFN signaling using the type II, IFN-gamma and type III, IFN-lambda pathways. These sheep constitute a unique model for studying the pathogenesis of viral infection. Historical data supports the concept that ruminants utilize a novel type I IFN, IFN-tau, for pregnancy recognition. Consequently, IFNAR deficient ewes are likely to be infertile, making IFNAR knockout sheep a valuable model for studying pregnancy recognition. A breeding herd of 32 IFNAR2 +/- ewes, which are fertile, has been developed for production of IFNAR2 -/- sheep for both infection and reproduction studies.
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Aim: We evaluated the developmental process, research status, and existing challenges of network pharmacology. Moreover, we elucidated the corresponding solutions to improve and develop network pharmacology. Methods: Research data for the current study were retrieved from the Web of Science. The developmental process of network pharmacology was analyzed using HisCite, whereas cooccurrence analysis of countries, institutions, keywords, and references in literature was conducted using CiteSpace. Results: In literature, there was a trend of annual increase of studies on network pharmacology and China was found to be the country with the most published literature on network pharmacology. The main publishing research institutions were universities of traditional Chinese medicine (TCM). The keywords with more research frequency were TCM, mechanisms, molecular docking, and quercetin, among others. Conclusion: Currently, studies on network pharmacology are mainly associated with the exploration of action mechanisms of TCM. The main active ingredient in many Chinese medicines is quercetin. This ingredient may lead to deviation of research results, inability to truly analyze active ingredients, and even mislead the research direction of TCM. Such deviation may be because the database fails to reflect the content and composition changes of Chinese medicinal components. The database does not account for interactions among components, targets, and diseases, and it ignores the different pathological states of the disease. Therefore, network pharmacology should be improved from the databases and research methods.
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Clinical expertise, patient preference, and the best evidence are the three elements of evidence-based medicine. Based on high-level and high-quality evidence, qualitative and quantitative analysis of the prescribing decisions of physicians is beneficial to improving clinical efficacy. A mature methodological system is available for the retrieval, analysis, summary, evaluation, and recommendation of the evidence, but there are still few studies on physicians' prescribing decisions. How to analyze the trend of physicians' prescribing decisions based on the priority ranking in addition and subtraction of prescriptions? Analytic hierarchy process(AHP) is a method for decision making, which arranges the elements of the decision problem into overall goal, criteria, and operational sub-criteria, and uses the matrix eigenvector method to solve the problem. This study aims to analyze the priority of physicians' prescribing decisions for diabetes mellitus with deficiency of both Qi and Yin based on AHP. To be specific, a database of diabetes mellitus cases with deficiency of both Qi and Yin was established and AHP was used to yield the priority ranking of Chinese patent medicine prescriptions in specific clinical scenarios. In the selected cases of diabetes mellitus with deficiency of both Qi and Yin, Xiaoke Pills was the best prescription for the treatment of type 2 diabetes mellitus(deficiency of both Qi and Yin)(normalized=0.388), followed by Liuwei Dihuang Pills(normalized=0.269), Qishen Capsules(normalized=0.230), and Shengmai Injection(normalized=0.113). According to the analysis the available data, for type 2 diabetes mellitus(deficiency of both Qi and Yin), Xiaoke Pills was the most effective prescription in specific scenarios. When the physicians' prescribing decisions are consistent with the evidence, quantitative analysis of physicians' cognition will boost the evidence-based medical decision-making. However, the research results are also affected by the quality of literature, evidence level and priority, which are thus have some limitations. It is recommended that further small data research based on individual cases be carried out to lay a evidence-based basis for the clinical decision-making of type 2 diabetes mellitus.
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Diabetes Mellitus Tipo 2 , Medicina Tradicional China , Proceso de Jerarquía Analítica , China , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Prescripciones de Medicamentos , Humanos , Medicamentos sin Prescripción/uso terapéutico , Qi , Síndrome , Deficiencia Yin/tratamiento farmacológicoRESUMEN
Recently, the visual quality evaluation of screen content images (SCIs) has become an important and timely emerging research theme. This article presents an effective and novel blind quality evaluation metric for SCIs by using stacked autoencoders (SAE) based on pictorial and textual regions. Since the SCI consists of not only the pictorial area but also the textual area, the human visual system (HVS) is not equally sensitive to their different distortion types. First, the textual and pictorial regions can be obtained by dividing an input SCI via an SCI segmentation metric. Next, we extract quality-aware features from the textual region and pictorial region, respectively. Then, two different SAEs are trained via an unsupervised approach for quality-aware features that are extracted from these two regions. After the training procedure of the SAEs, the quality-aware features can evolve into more discriminative and meaningful features. Subsequently, the evolved features and their corresponding subjective scores are input into two regressors for training. Each regressor can obtain one output predictive score. Finally, the final perceptual quality score of a test SCI is computed by these two predicted scores via a weighted model. Experimental results on two public SCI-oriented databases have revealed that the proposed scheme can compare favorably with the existing blind image quality assessment metrics.
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Bases de Datos Factuales , HumanosRESUMEN
Production of embryos with high developmental competence by somatic cell nuclear transfer (scNT) is far less efficient than for in vitro fertilized (IVF) embryos, likely due to an accumulation of errors in genome reprogramming that results in aberrant expression of RNA transcripts, including messenger RNAs (mRNA) and, possibly, microRNAs (miRNA). Thus, our objectives were to use RNAseq to determine the dynamics of mRNA expression in early developing scNT and IVF embryos in the context of the maternal-to-embryonic transition (MET) and to correlate apparent transcriptional dysregulation in cloned embryos with miRNA expression profiles. Comparisons between scNT and IVF embryos indicated large scale transcriptome differences, which were most evident at the 8-cell and morula stages for genes associated with biological functions critical for the MET. For two miRNAs previously identified as differentially expressed in scNT morulae, miR-34a and miR-345, negative correlations with some predicted mRNA targets were apparent, though not widespread among the majority of predicted targets. Moreover, although large-scale aberrations in expression of mRNAs were evident during the MET in cattle scNT embryos, these changes were not consistently correlated with aberrations in miRNA expression at the same developmental stage, suggesting that other mechanisms controlling gene expression may be involved.