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2022 ◽  
Vol 0 (0) ◽  
Jian Cao ◽  
Seo-young Silvia Kim ◽  
R. Michael Alvarez

Abstract How do we ensure a statewide voter registration database’s accuracy and integrity, especially when the database depends on aggregating decentralized, sub-state data with different list maintenance practices? We develop a Bayesian multivariate multilevel model to account for correlated patterns of change over time in multiple response variables, and label statewide anomalies using deviations from model predictions. We apply our model to California’s 22 million registered voters, using 25 snapshots from the 2020 presidential election. We estimate countywide change rates for multiple response variables such as changes in voter’s partisan affiliation and jointly model these changes. The model outperforms a simple interquartile range (IQR) detection when tested with synthetic data. This is a proof-of-concept that demonstrates the utility of the Bayesian methodology, as despite the heterogeneity in list maintenance practices, a principled, statistical approach is useful. At the county level, the total numbers of anomalies are positively correlated with the average election cost per registered voter between 2017 and 2019. Given the recent efforts to modernize and secure voter list maintenance procedures in the For the People Act of 2021, we argue that checking whether counties or municipalities are behaving similarly at the state level is also an essential step in ensuring electoral integrity.

2022 ◽  
Zhengjun Zhang

Genes functionally associated with SARS-CoV-2 and genes functionally related to COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in transcriptional response to SARS-CoV-2 with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with one another gene in predicting disease status to achieve better-indicating power than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. With their exceptional predicting power, these two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in the literature, genes and their transcriptional response and functional effects to SARS-CoV-2 and genes and their functional signature patterns to COVID-19 antibody are significantly different, which can be interpreted as the former is the point of a phenomenon, and the latter is the essence of the disease. Such significant findings can help explore the causal and pathological clue between SARS-CoV-2 and COVID-19 disease and fight against the disease with more targeted vaccines, antiviral drugs, and therapies.

Matthias Busch ◽  
Tino Hausotte

AbstractSurface determination is an essential step of the measurement process in industrial X-ray computed tomography (XCT). The starting point of the surface determination process step is a single grey value threshold within a voxel volume in conventional surface determination methods. However, this value is not always found in the reconstructed volume in the local environment of the surface of the measurement object due to various artefacts, so that none or incorrect surfaces are determined. In order to find surfaces independently of a single grey value, a three-dimensional approach of the initial contour determination based on a Prewitt edge detection algorithm is presented in this work. This method is applied to different test specimens and specimen compositions which, due to their material or material constellation, their geometric properties with regard to surfaces and interfaces as well as their calibrated size and length dimensions, embody relevant properties in the examination of joining connections. It is shown that by using the surface determination method in the measurement process, both a higher metrological structure resolution and interface structure resolution can be achieved. Surface artefacts can be reduced by the application and it is also an approach to improved surface finding for the multi-material components that are challenging for XCT.

RNA ◽  
2022 ◽  
pp. rna.078814.121
Anna Ender ◽  
Nadine Grafl ◽  
Tim Kolberg ◽  
Sven Findeiss ◽  
Peter F. Stadler ◽  

Removal of the 5' leader region is an essential step in the maturation of tRNA molecules in all domains of life. This reaction is catalyzed by various RNase P activities, ranging from ribonucleoproteins with ribozyme activity to protein-only forms. In Escherichia coli, the efficiency of RNase P mediated cleavage can be controlled by computationally designed riboswitch elements in a ligand-dependent way, where the 5' leader sequence of a tRNA precursor is either sequestered in a hairpin structure or presented as a single-stranded region accessible for maturation. In the presented work, the regulatory potential of such artificial constructs is tested on different forms of eukaryotic RNase P enzymes – two protein-only RNase P enzymes (PRORP1 and PRORP2) from Arabidopsis thaliana and the ribonucleoprotein of Homo sapiens. The PRORP enzymes were analyzed in vitro as well as in vivo in a bacterial RNase P complementation system. We also tested in HEK293T cells whether the riboswitches remain functional with human nuclear RNase P. While the regulatory principle of the synthetic riboswitches applies for all tested RNase P enzymes, the results also show differences in the substrate requirements of the individual enzyme versions. Hence, such designed RNase P riboswitches represent a novel tool to investigate the impact of the structural composition of the 5'-leader on substrate recognition by different types of RNase P enzymes.

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 107
Santosh Manicka ◽  
Michael Levin

What information-processing strategies and general principles are sufficient to enable self-organized morphogenesis in embryogenesis and regeneration? We designed and analyzed a minimal model of self-scaling axial patterning consisting of a cellular network that develops activity patterns within implicitly set bounds. The properties of the cells are determined by internal ‘genetic’ networks with an architecture shared across all cells. We used machine-learning to identify models that enable this virtual mini-embryo to pattern a typical axial gradient while simultaneously sensing the set boundaries within which to develop it from homogeneous conditions—a setting that captures the essence of early embryogenesis. Interestingly, the model revealed several features (such as planar polarity and regenerative re-scaling capacity) for which it was not directly selected, showing how these common biological design principles can emerge as a consequence of simple patterning modes. A novel “causal network” analysis of the best model furthermore revealed that the originally symmetric model dynamically integrates into intercellular causal networks characterized by broken-symmetry, long-range influence and modularity, offering an interpretable macroscale-circuit-based explanation for phenotypic patterning. This work shows how computation could occur in biological development and how machine learning approaches can generate hypotheses and deepen our understanding of how featureless tissues might develop sophisticated patterns—an essential step towards predictive control of morphogenesis in regenerative medicine or synthetic bioengineering contexts. The tools developed here also have the potential to benefit machine learning via new forms of backpropagation and by leveraging the novel distributed self-representation mechanisms to improve robustness and generalization.

2022 ◽  
pp. 000992282110703
Ellen Wagner ◽  
Omar Jamil ◽  
Bethany Hodges

While discussing obesity with pediatric patients and their families can be difficult, it is an essential step toward appropriate weight management. There is paucity of data regarding language preferences when discussing obesity in this population. In this pilot qualitative study, we interviewed 8 parents of patients diagnosed with obesity to identify language and communication preferences for discussing their child’s weight. Interviews were analyzed for emerging themes. Important trends appeared revealing that parents prefer neutral, medical terms discussed at well-child checks or obesity-specific visits. Providers should frame lifestyle changes as positive for all patients and set achievable goals with the help of visual aids. Our analysis uncovered several important communication strategies that can better equip providers to discuss obesity with their pediatric patients. This research may serve as a foundation for larger studies into the topic.

2022 ◽  
Vol 12 (1) ◽  
Tatsuya Sato ◽  
Nobutoshi Ichise ◽  
Takeshi Kobayashi ◽  
Hiroyori Fusagawa ◽  
Hiroya Yamazaki ◽  

AbstractThe initiation of heartbeat is an essential step in cardiogenesis in the heart primordium, but it remains unclear how intracellular metabolism responds to increased energy demands after heartbeat initiation. In this study, embryos in Wistar rats at embryonic day 10, at which heartbeat begins in rats, were divided into two groups by the heart primordium before and after heartbeat initiation and their metabolic characteristics were assessed. Metabolome analysis revealed that increased levels of ATP, a main product of glucose catabolism, and reduced glutathione, a by-product of the pentose phosphate pathway, were the major determinants in the heart primordium after heartbeat initiation. Glycolytic capacity and ATP synthesis-linked mitochondrial respiration were significantly increased, but subunits in complexes of mitochondrial oxidative phosphorylation were not upregulated in the heart primordium after heartbeat initiation. Hypoxia-inducible factor (HIF)-1α was activated and a glucose transporter and rate-limiting enzymes of the glycolytic and pentose phosphate pathways, which are HIF-1α-downstream targets, were upregulated in the heart primordium after heartbeat initiation. These results suggest that the HIF-1α-mediated enhancement of glycolysis with activation of the pentose phosphate pathway, potentially leading to antioxidant defense and nucleotide biosynthesis, covers the increased energy demand in the beating and developing heart primordium.

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262281
Virginia R. Shervette ◽  
Jesús M. Rivera Hernández

Ensuring the accuracy of age estimation in fisheries science through validation is an essential step in managing species for long-term sustainable harvest. The current study used Δ14 C in direct validation of age estimation for queen triggerfish Balistes vetula and conclusively documented that triggerfish sagittal otoliths provide more accurate and precise age estimates relative to dorsal spines. Caribbean fish samples (n = 2045) ranged in size from 67–473 mm fork length (FL); 23 fish from waters of the southeastern U.S. (SEUS) Atlantic coast ranged in size from 355–525 mm FL. Otolith-based age estimates from Caribbean fish range from 0–23 y, dorsal spine-based age estimates ranged from 1–14 y. Otolith-based age estimates for fish from the SEUS ranged from 8–40 y. Growth function estimates from otoliths in the current study (L∞ = 444, K = 0.13, t0 = -1.12) differed from spined-derived estimates in the literature. Our work indicates that previously reported maximum ages for Balistes species based on spine-derived age estimates may underestimate longevity of these species since queen triggerfish otolith-based ageing extended maximum known age for the species by nearly three-fold (14 y from spines versus 40 y from otoliths). Future research seeking to document age and growth population parameters of Balistes species should strongly consider incorporating otolith-based ageing in the research design.

Tatireddy Reddy ◽  
Jonnadula Harikiran

Hyperspectral imaging is used in a wide range of applications. When used in remote sensing, satellites and aircraft are employed to collect the images, which are used in agriculture, environmental monitoring, urban planning and defence. The exact classification of ground features in the images is a significant research issue and is currently receiving greater attention. Moreover, these images have a large spectral dimensionality, which adds computational complexity and affects classification precision. To handle these issues, dimensionality reduction is an essential step that improves the performance of classifiers. In the classification process, several strategies have produced good classification results. Of these, machine learning techniques are the most powerful approaches. As a result, this paper reviews three different types of hyperspectral image machine learning classification methods: cluster analysis, supervised and semi-supervised classification. Moreover, this paper shows the effectiveness of all these techniques for hyperspectral image classification and dimensionality reduction. Furthermore, this review will assist as a reference for future research to improve the classification and dimensionality reduction approaches.

2022 ◽  
Mimi Coultas ◽  
Mable Mideva Chanza ◽  
Ruhil Iyer ◽  
Lambert Karangwa ◽  
Jimmy Eric Kariuki ◽  

Abstract Government leadership at both the national and sub-national levels is an essential step towards ensuring safely managed sanitation services for all. Though the importance of sub-national government leadership for water, sanitation and hygiene is widely acknowledged, to date much of the focus has been on the delivery of water services. This article sets out to start to address this imbalance by focusing on practical ways to galvanise and foster sub-national government leadership for sanitation programming. By focusing on the experiences across three sub-national areas in East Africa where positive changes in the prioritisation of sanitation by local governments have been witnessed, we (a group of researchers, local government representatives and development partner staff) cross-examine and identify lessons learnt. The results presented in this paper and subsequent discussion provide practical recommendations for those wishing to trigger a change in political will at the local level and create the foundation to strengthen sanitation governance and the wider system needed to ensure service delivery for all.

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