AN OVERVIEW OF EFFICIENT NONLINEAR FILTERING - FROM KALMAN FILTER TO PARTICLE FILTERS TO EIS

Generally, in most applied fields, the dynamic state space models are of nonlinearity with non-Gaussian noise. However, as a famous and simple algorithmic filter, Kalman filter can only estimate linear system with Gaussian noise state space models. The Extend Kalman filter and the Unscented Kalman filter still have limitations and therefore are not accurate enough for nonlinear estimation. The Bayesian filtering approach which is based on sequential Monte Carlo sampling is called particle filters. Particle filters were developed and widely applied in various areas because of the ability to process observations represented by nonlinear state-space models where the noise of the models can be non-Gaussian. However, particle filters suffer from two long-standing problems that are referred as sample degeneracy and impoverishment. To fight these problems, resampling step is necessary. In this review work, a variety of resampling of particle filter methods as well as their characteristics and algorithms are introduced and discussed, such as Sampling-Importance resampling, Auxiliary particle filter, Optimal resampling and so on to combat against the sample degeneracy and impoverishment. Finally, efficient importance sampling, as a more accurate method, capable of estimating high-dimensional integration and carrying out global optimization, will be introduced and compared to particle filters

APP, PSEN1, and PSEN2 Variants in Alzheimer’s Disease: Systematic Re-evaluation According to ACMG Guidelines

The strategies of classifying APP, PSEN1, and PSEN2 variants varied substantially in the previous studies. We aimed to re-evaluate these variants systematically according to the American college of medical genetics and genomics and the association for molecular pathology (ACMG-AMP) guidelines. In our study, APP, PSEN1, and PSEN2 variants were collected by searching Alzforum and PubMed database with keywords “PSEN1,” “PSEN2,” and “APP.” These variants were re-evaluated based on the ACMG-AMP guidelines. We compared the number of pathogenic/likely pathogenic variants of APP, PSEN1, and PSEN2. In total, 66 APP variants, 323 PSEN1 variants, and 63 PSEN2 variants were re-evaluated in our study. 94.91% of previously reported pathogenic variants were re-classified as pathogenic/likely pathogenic variants, while 5.09% of them were variants of uncertain significance (VUS). PSEN1 carried the most prevalent pathogenic/likely pathogenic variants, followed by APP and PSEN2. Significant statistically difference was identified among these three genes when comparing the number of pathogenic/likely pathogenic variants (P < 2.2 × 10–16). Most of the previously reported pathogenic variants were re-classified as pathogenic/likely pathogenic variants while the others were re-evaluated as VUS, highlighting the importance of interpreting APP, PSEN1, and PSEN2 variants with caution according to ACMG-AMP guidelines

Design Methodology for Six-Port Equal/Unequal Quadrature and Rat-Race Couplers With Balanced and Unbalanced Ports Terminated by Arbitrary Resistances

For the first time, the 6-port quadrature and rat-race couplers with balanced-unbalanced-hybrid ports are proposed. The corresponding design methodology is presented, which is capable of designing the proposed couplers with arbitrary power divisions and terminated resistances. In this paper, four types including quadrature and rat-race couplers are fully analyzed, covering all the application configurations of the balanced/unbalanced ports. Besides, the design equations are rigorously derived, with the final design procedures presented. Eventually, prototypes of the four coupler types are fabricated and experimentally measured. The final results sufficiently validate the proposed methodology

Modeling Alzheimer's Disease with Induced Pluripotent Stem Cells: Current Challenges and Future Concerns

Alzheimer's disease (AD) is the most prevalent type of dementia and its pathology is characterized by deposition of extracellular -amyloid plaques, intracellular neurofibrillary tangles, and extensive neuron loss. While only a few familial AD cases are due to mutations in three causative genes (APP, PSEN1, and PSEN2), the ultimate cause behind the rest of the cases, called sporadic AD, remains unknown. Current animal and cellular models of human AD, which are based on the A and tau hypotheses only, partially resemble the familial AD. As a result, there is a pressing need for the development of new models providing insights into the pathological mechanisms of AD and for the discovery of ways to treat or delay the onset of the disease. Recent preclinical research suggests that stem cells can be used to model AD. Indeed, human induced pluripotent stem cells can be differentiated into disease-relevant cell types that recapitulate the unique genome of a sporadic AD patient or family member. In this review, we will first summarize the current research findings on the genetic and pathological mechanisms of AD. We will then highlight the existing induced pluripotent stem cell models of AD and, lastly, discuss the potential clinical applications in this field

Screening and Identification of APOC1 as a Novel Potential Biomarker for Differentiate of Mycoplasma pneumoniae in Children

Background: Although mycoplasma pneumoniae (MP) is a common cause of community-acquired pneumonia in children, the currently used diagnostic methods are not optimal. Proteomics is increasingly being used to study the biomarkers of infectious diseases. Methods: Label-free quantitative proteomics and liquid chromatography-mass/mass spectrometry were used to analyze the fold change of protein expression in plasma of children with MP pneumonia (MPP), infectious disease control (IDC), and healthy control (HC) groups. Selected proteins that can distinguish MPP from HC and IDC were further validated by enzyme-linked immunosorbent assay (ELISA).Results: After multivariate analyses, 27 potential plasma biomarkers were identified to be expressed differently among child MPP, HC, and IDC groups. Among these proteins, SERPINA3, APOC1, ANXA6, KNTC1, and CFLAR were selected for ELISA verification. SERPINA3, APOC1, and CFLAR levels were significantly different among the three groups and the ratios were consistent with the trends of proteomics results. A comparison of MPP patients and HC showed APOC1 had the largest area under the curve (AUC) of 0.853, with 77.6% sensitivity and 81.1% specificity. When APOC1 levels were compared between MPP and IDC patients, it also showed a relatively high AUC of 0.882, with 77.6% sensitivity and 88.3% specificity. Conclusion: APOC1 is a potential biomarker for the rapid and noninvasive diagnosis of MPP in children. The present finding may offer new insights into the pathogenesis and biomarker selection of MPP in children

Unraveling Controversies Over Civic Honesty Measurement: An Extended Field Replication in China

Cohn et al. (2019) conducted a wallet drop experiment in 40 countries to measure civic honesty around the globe, which has received worldwide attention but also sparked controversies over using the email response rate as the sole metric of civic honesty. Relying on the lone measurement may overlook cultural differences in behaviors that demonstrate civic honesty. To investigate this issue, we conducted an extended replication study in China, utilizing email response and wallet recovery to assess civic honesty. We found a significantly higher level of civic honesty in China, as measured by the wallet recovery rate, than reported in the original study, while email response rates remained similar. To resolve the divergent results, we introduce a cultural dimension, individualism versus collectivism, to study civic honesty across diverse cultures. We hypothesize that cultural differences in individualism and collectivism could influence how individuals prioritize actions when handling a lost wallet, such as contacting the wallet owner or safeguarding the wallet. In reanalyzing Cohn et al.\u27s data, we found that email response rates were inversely related to collectivism indices at the country level. However, our replication study in China demonstrated that the likelihood of wallet recovery was positively correlated with collectivism indicators at the provincial level. Consequently, relying solely on email response rates to gauge civic honesty in cross-country comparisons may neglect the vital individualism versus collectivism dimension. Our study not only helps reconcile the controversy surrounding Cohn et al.\u27s influential field experiment but also furnishes a fresh cultural perspective to evaluate civic honesty

Multiple Visual Rating Scales Based on Structural MRI and a Novel Prediction Model Combining Visual Rating Scales and Age Stratification in the Diagnosis of Alzheimer's Disease in the Chinese Population

Objective: To explore the value of multiple visual rating scales based on structural MRI in the diagnosis of Alzheimer's disease (AD) in the Chinese population.Materials and Methods: One hundred patients with AD and 100 age- and gender- matched cognitively normal controls were enrolled in this study. All the participants underwent neuropsychological tests and a structural MRI scan of the brain, among them, 42 AD cases and 47 cognitively normal controls also underwent 3D-T1 weighted sequence used for the analysis of voxel-based morphometry (VBM). The AD cases were divided into mild and moderate–severe groups according to the mini-mental state examination. Each participant was evaluated by two trained radiologists who were blind to the clinical information, according to the six visual rating scales, including for medial temporal lobe atrophy (MTA), posterior atrophy (PA), anterior temporal (AT), orbitofrontal (OF) cortex, anterior cingulate (AC), and fronto-insula (FI). Finally, we estimated the relationship between the visual rating scales and the volume of corresponding brain regions, using correlation analysis, and evaluated the specificity and sensitivity of every single scale and combination of multiple scales in the diagnosis of AD, using a receiver operating characteristic (ROC) curve and establishing a logistic regression model.Results: The optimal cutoff of all six visual rating scales for distinguishing AD cases from normal controls was 1.5. Using automated classification based on all six rating scales, the accuracy for distinguishing AD cases from healthy controls ranged from 0.68 to 0.80 (for mild AD) and 0.77–0.90 (for moderate–severe AD), respectively. A diagnostic prediction model with a combination of MTA and OF results was made as follows: Score = BMTA(score) + BOF(score) −1.58 (age < 65 years); Score = BMTA(score) + BOF(score) −4.09 (age ≥65 years). The model was superior to any single visual rating scale in the diagnosis of mild AD (P < 0.05).Conclusion: Each of the six visual rating scales could be applied to the diagnosis of moderate-severe AD alone in the Chinese population. A prediction model of the combined usage of MTA, OF, and age stratification for the early diagnosis of AD was preliminarily established

Intrachromosomal Looping Is Required for Activation of Endogenous Pluripotency Genes during Reprogramming

SummaryGeneration of induced pluripotent stem cells (iPSCs) by defined factors is an extremely inefficient process, because there is a strong epigenetic block preventing cells from achieving pluripotency. Here we report that virally expressed factors bound to the promoters of their target genes to the same extent in both iPSCs and unreprogrammed cells (URCs). However, expression of endogenous pluripotentcy genes was observed only in iPSCs. Comparison of local chromatin structure of the OCT4 locus revealed that there was a cohesin-complex-mediated intrachromosomal loop that juxtaposes a downstream enhancer to the gene’s promoter, enabling activation of endogenous stemness genes. None of these long-range interactions were observed in URCs. Knockdown of the cohesin-complex gene SMC1 by RNAi abolished the intrachromosomal interaction and affected pluripotency. These findings highlight the importance of the SMC1-orchestrated intrachromosomal loop as a critical epigenetic barrier to the induction of pluripotency

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state‐of‐the‐art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing‐based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water and natural hazard management are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined