Continuous-time block-oriented nonlinear modeling with complex input noise structure

The continuous-time closed-form algorithms to sinusoidal input changes are proposed and presented for single-input, single-output (SISO) Hammerstein and Wiener systems with the first-order, second-order, and second-order plus lead dynamics. By simulation on theoretical Hammerstein and Wiener systems, the predicted responses agree exactly with the true process values. They depend on only the most recent input change. The algorithms to SISO Hammerstein and Wiener systems can be conveniently extended to the multiple-input, multiple-output (MIMO) systems as shown by the two-input, two-output examples and demonstrated by the simulated seven-input, five-output continuous stirred tank reactor (CSTR). The predictions and the simulated theoretical responses agree exactly and the predicted multiple CSTR outputs are close to the true process outputs. The proposed algorithms can predict the responses closer to the true values when comparing with the piece-wise step input approximation of the sinusoidal input changes on a simulated MIMO CSTR. In addition, as the noisy process input could be decomposed as summation of sinusoidal signals imposed on a step input change; the proposed algorithms can be employed to predict outputs for the noisy process inputs once the decomposition is done and the predicted noisy process outputs are shown to be close to the true ones, and are much better than the predictions based on the perfect filtering of the input signals.;The estimating equations based on the moment method are proposed for the Wiener dynamic process with stochastically correlated process input disturbances or noises and they work well for the parameter estimation. No one has ever proposed such method before. This approach has led to stable and robust estimators that have reasonable estimation errors and there is no need to measure the input disturbances or noises, or to calculate the time derivative of the observed output variable. Only the original process output observations over time are needed. The original model can be shifted to an approximate model under some conditions. This approximation is acceptable based on some analysis and derivation. The estimating equation methodology was shown to work well for the approximate model, while other existing methods do not work at all

The lung function profile of once-daily tiotropium and olodaterol via Respimat® is superior to that of twice-daily salmeterol and fluticasone propionate via Accuhaler® (ENERGITO® study)

Background: Tiotropium + olodaterol has demonstrated improvements beyond lung function benefits in a large Phase III clinical program as a once-daily maintenance treatment for COPD and may be a potential option for the initiation of maintenance treatment in COPD. Despite guideline recommendations that combined long-acting beta(2)-agonists and inhaled corticosteroids should only be used in individuals at high risk of exacerbation, there is substantial use in individuals at lower risk. This raises the question of the comparative effectiveness of this combination as maintenance treatment in this group compared to other combination regimens. Objective: The study aimed to assess the effect on lung function of once-daily tiotropium + olodaterol versus twice-daily salmeterol + fluticasone propionate in all participants with Global initiative for chronic Obstructive Lung Disease 2 or 3 (moderate to severe) COPD. Methods: This was a randomized, double-blind, double-dummy, four-treatment, complete crossover study in which participants received once-daily tiotropium + olodaterol (5/5 mu g and 2.5/5 mu g) via Respimat (R) and twice-daily salmeterol + fluticasone propionate (50/500 mu g and 50/250 mu g) via Accuhaler (R) for 6 weeks. The primary end point was change in forced expiratory volume in 1 second (FEV1) area under the curve from 0 hour to 12 hours (AUC(0-12)) relative to the baseline after 6 weeks. Results: Tiotropium + olodaterol 5/5 mu g and 2.5/5 mu g demonstrated statistically significant improvements in FEV1 AUC(0-12) compared to salmeterol + fluticasone propionate (improvements from baseline were 317 mL and 295 mL with tiotropium + olodaterol 5/5 mu g and 2.5/5 mu g, and 188 mL and 192 mL with salmeterol + fluticasone propionate 50/500 mu g and 50/250 mu g, respectively). Tiotropium + olodaterol was superior to salmeterol + fluticasone propionate in lung function secondary end points, including FEV1 area under the curve from 0 hour to 24 hours (AUC(0-24)). Conclusion: Once-daily tiotropium + olodaterol in participants with moderate-to-severe COPD provided superior lung function improvements to twice-daily salmeterol + fluticasone propionate. Dual bronchodilation can be considered to optimize lung function in individuals requiring maintenance treatment for COPD

Overexpression of SIRT1 in Mouse Forebrain Impairs Lipid/Glucose Metabolism and Motor Function

SIRT1 plays crucial roles in glucose and lipid metabolism, and has various functions in different tissues including brain. The brain-specific SIRT1 knockout mice display defects in somatotropic signaling, memory and synaptic plasticity. And the female mice without SIRT1 in POMC neuron are more sensitive to diet-induced obesity. Here we created transgenic mice overexpressing SIRT1 in striatum and hippocampus under the control of CaMKIIα promoter. These mice, especially females, exhibited increased fat accumulation accompanied by significant upregulation of adipogenic genes in white adipose tissue. Glucose tolerance of the mice was also impaired with decreased Glut4 mRNA levels in muscle. Moreover, the SIRT1 overexpressing mice showed decreased energy expenditure, and concomitantly mitochondria-related genes were decreased in muscle. In addition, these mice showed unusual spontaneous physical activity pattern, decreased activity in open field and rotarod performance. Further studies demonstrated that SIRT1 deacetylated IRS-2, and upregulated phosphorylation level of IRS-2 and ERK1/2 in striatum. Meanwhile, the neurotransmitter signaling in striatum and the expression of endocrine hormones in hypothalamus and serum T3, T4 levels were altered. Taken together, our findings demonstrate that SIRT1 in forebrain regulates lipid/glucose metabolism and motor function

A novel data mining method to identify assay-specific signatures in functional genomic studies

BACKGROUND: The highly dimensional data produced by functional genomic (FG) studies makes it difficult to visualize relationships between gene products and experimental conditions (i.e., assays). Although dimensionality reduction methods such as principal component analysis (PCA) have been very useful, their application to identify assay-specific signatures has been limited by the lack of appropriate methodologies. This article proposes a new and powerful PCA-based method for the identification of assay-specific gene signatures in FG studies. RESULTS: The proposed method (PM) is unique for several reasons. First, it is the only one, to our knowledge, that uses gene contribution, a product of the loading and expression level, to obtain assay signatures. The PM develops and exploits two types of assay-specific contribution plots, which are new to the application of PCA in the FG area. The first type plots the assay-specific gene contribution against the given order of the genes and reveals variations in distribution between assay-specific gene signatures as well as outliers within assay groups indicating the degree of importance of the most dominant genes. The second type plots the contribution of each gene in ascending or descending order against a constantly increasing index. This type of plots reveals assay-specific gene signatures defined by the inflection points in the curve. In addition, sharp regions within the signature define the genes that contribute the most to the signature. We proposed and used the curvature as an appropriate metric to characterize these sharp regions, thus identifying the subset of genes contributing the most to the signature. Finally, the PM uses the full dataset to determine the final gene signature, thus eliminating the chance of gene exclusion by poor screening in earlier steps. The strengths of the PM are demonstrated using a simulation study, and two studies of real DNA microarray data – a study of classification of human tissue samples and a study of E. coli cultures with different medium formulations. CONCLUSION: We have developed a PCA-based method that effectively identifies assay-specific signatures in ranked groups of genes from the full data set in a more efficient and simplistic procedure than current approaches. Although this work demonstrates the ability of the PM to identify assay-specific signatures in DNA microarray experiments, this approach could be useful in areas such as proteomics and metabolomics

Guiding the PLMs with Semantic Anchors as Intermediate Supervision: Towards Interpretable Semantic Parsing

The recent prevalence of pretrained language models (PLMs) has dramatically shifted the paradigm of semantic parsing, where the mapping from natural language utterances to structured logical forms is now formulated as a Seq2Seq task. Despite the promising performance, previous PLM-based approaches often suffer from hallucination problems due to their negligence of the structural information contained in the sentence, which essentially constitutes the key semantics of the logical forms. Furthermore, most works treat PLM as a black box in which the generation process of the target logical form is hidden beneath the decoder modules, which greatly hinders the model's intrinsic interpretability. To address these two issues, we propose to incorporate the current PLMs with a hierarchical decoder network. By taking the first-principle structures as the semantic anchors, we propose two novel intermediate supervision tasks, namely Semantic Anchor Extraction and Semantic Anchor Alignment, for training the hierarchical decoders and probing the model intermediate representations in a self-adaptive manner alongside the fine-tuning process. We conduct intensive experiments on several semantic parsing benchmarks and demonstrate that our approach can consistently outperform the baselines. More importantly, by analyzing the intermediate representations of the hierarchical decoders, our approach also makes a huge step toward the intrinsic interpretability of PLMs in the domain of semantic parsing

Object Detection for Caries or Pit and Fissure Sealing Requirement in Children's First Permanent Molars

Dental caries is one of the most common oral diseases that, if left untreated, can lead to a variety of oral problems. It mainly occurs inside the pits and fissures on the occlusal/buccal/palatal surfaces of molars and children are a high-risk group for pit and fissure caries in permanent molars. Pit and fissure sealing is one of the most effective methods that is widely used in prevention of pit and fissure caries. However, current detection of pits and fissures or caries depends primarily on the experienced dentists, which ordinary parents do not have, and children may miss the remedial treatment without timely detection. To address this issue, we present a method to autodetect caries and pit and fissure sealing requirements using oral photos taken by smartphones. We use the YOLOv5 and YOLOX models and adopt a tiling strategy to reduce information loss during image pre-processing. The best result for YOLOXs model with tiling strategy is 72.3 mAP.5, while the best result without tiling strategy is 71.2. YOLOv5s6 model with/without tiling attains 70.9/67.9 mAP.5, respectively. We deploy the pre-trained network to mobile devices as a WeChat applet, allowing in-home detection by parents or children guardian

Pathogenic Pseudorabies Virus, China, 2012

In 2012, an unprecedented large-scale outbreak of disease in pigs in China caused great economic losses to the swine industry. Isolates from pseudorabies virus epidemics in swine herds were characterized. Evidence confirmed that the pathogenic pseudorabies virus was the etiologic agent of this epidemic

WldS Reduces Paraquat-Induced Cytotoxicity via SIRT1 in Non-Neuronal Cells by Attenuating the Depletion of NAD

WldS is a fusion protein with NAD synthesis activity, and has been reported to protect axonal and synaptic compartments of neurons from various mechanical, genetic and chemical insults. However, whether WldS can protect non-neuronal cells against toxic chemicals is largely unknown. Here we found that WldS significantly reduced the cytotoxicity of bipyridylium herbicides paraquat and diquat in mouse embryonic fibroblasts, but had no effect on the cytotoxicity induced by chromium (VI), hydrogen peroxide, etoposide, tunicamycin or brefeldin A. WldS also slowed down the death of mice induced by intraperitoneal injection of paraquat. Further studies demonstrated that WldS markedly attenuated mitochondrial injury including disruption of mitochondrial membrane potential, structural damage and decline of ATP induced by paraquat. Disruption of the NAD synthesis activity of WldS by an H112A or F116S point mutation resulted in loss of its protective function against paraquat-induced cell death. Furthermore, WldS delayed the decrease of intracellular NAD levels induced by paraquat. Similarly, treatment with NAD or its precursor nicotinamide mononucleotide attenuated paraquat-induced cytotoxicity and decline of ATP and NAD levels. In addition, we showed that SIRT1 was required for both exogenous NAD and WldS-mediated cellular protection against paraquat. These findings suggest that NAD and SIRT1 mediate the protective function of WldS against the cytotoxicity induced by paraquat, which provides new clues for the mechanisms underlying the protective function of WldS in both neuronal and non-neuronal cells, and implies that attenuation of NAD depletion may be effective to alleviate paraquat poisoning