Notes

Hippocampal disturbances of synaptic and astrocyte fat burning capacity tend to be principal events of earlier amyloid pathology in the 5xFAD computer mouse type of Alzheimer's.
Finding the roots of nonlinear equations has many applications in various sciences, especially engineering, and various methods have been proposed for this purpose. However, almost all these methods have some shortcoming. This paper presents a new method, where we consider the desired function to find the root(s) of the absolute value, so the root(s) (if any) is the absolute minimum. Using Monte Carlo method, we divide the desired distance into smaller parts. In each section where the slope of the function changes, we use the Bisection method to find the root. It largely covers the limitations of previous methods. The most important advantage of this method over the Bisection method is that it finds all the roots of the equation.•Solve the problem of the bisection method in roots tangent to the x-axis.•Separation of Root(s) that crossed and Root(s) that are tangent to the x-axis.Inflation and inflation uncertainty are instrumental in the determination of financial stability, and ultimately, economic growth. We investigated the impact of inflation and inflation uncertainty on growth in South Africa by applying the autoregressive distributed lag (ARDL) estimation techniques on quarterly data covering the period 1961Q1 to 2019Q4. Unlike previous studies on South Africa, we investigated the joint impact of inflation and inflation uncertainty in South Africa, and also, pioneered in comparing the impact of both variables on growth before, and after, inflation targeting. This provided an opportunity to assess the effectiveness of inflation targeting while also investigating any changes in the behavior of the variables. We found that inflation negatively harms growth in both the short and long run, while inflation uncertainty is a short-run phenomenon in South Africa with no bearing in the long run. To promote growth, policymakers should continue to pursue policies that ensure price stability. • The paper investigated the impact of inflation and inflation uncertainty on economic growth in South Africa covering the period 1961Q1 to 2019Q4. • Using the autoregressive distributed lag estimation techniques, the paper found that inflation harms economic growth in both the short- and long-run in South Africa while inflation uncertainty is a short-run phenomenon as it affects economic growth only in the short run, • Interestingly, after adoption of inflation targeting, inflation uncertainty lost it relevance as a factor determining economic growth in South Africa.[This corrects the article DOI 10.1016/j.mex.2021.101453.].In this article, an abstract framework for annual averaged wind power output generation prediction of wind turbines is presented which is heavily based on large wind speed data sets and power curve data of wind turbines due to the rising interest in wind energy as one main future renewable energy source. As combinations of arbitrary power curve modeling techniques and arbitrary wind speed distributions based on wind speed data are seldom combined, the abstract combination of these two aspects in wind power output generation prediction in one pipeline is thoroughly described here. Conclusively, one detailed example wind speed data set from a weather station situation in Bremen, Germany illustrates applicability of the presented framework.Electrical contacts are pervasively found on countless modern devices and systems. Akt inhibitor It is imperative that connecting components present adequate electrical, mechanical, and chemical characteristics to fulfill the crucial role that they play in the system. To develop an electrical contact material that is tailored for a specific application, different approaches are pursued (e.g., coatings, reinforced composites, alloyed metals, duplex systems, etc.). The manufacturing of electrical contact materials demand a thorough characterization of their electrical properties, mechanical properties, and their resistance to wear, as well as their resistance to atmospheric conditions. Accordingly, commissioning of a novel setup enables a more comprehensive study of the materials that are developed. Therefore, a complete understanding of the material's electrical and tribological characteristics are attained, allowing the production of a material that is compliant with the particular demands of the application for which it is intended. This multipurpose setup was built with higher precision stages and higher accuracy 3-axis force sensor, thus providing the following improvement over the preceding setup•Elevated load-bearing capacity (double), higher precision and stability.•Tribo-electrical characterization (implementation of scratch and fretting tests).•Environmental control (climate and external vibration).The current standard approach for analyzing cortical bone structure and trabecular bone microarchitecture from micro-computed tomography (microCT) is through classic parametric (e.g., ANOVA, Student's T-test) and nonparametric (e.g., Mann-Whitney U test) statistical tests and the reporting of p-values to indicate significance. However, on their own, these univariate assessments of significance fall prey to a number of weaknesses, including an increased chance of Type 1 error from multiple comparisons. Machine learning classification methods (e.g., unsupervised, k-means cluster analysis and supervised Support Vector Machine classification, SVM) simultaneously utilize an entire dataset comprised of many cortical structure or trabecular microarchitecture measures, thus minimizing bias and Type 1 error that are generated through multiple testing. Through simultaneous evaluation of an entire dataset, k-means and SVM thus provide a complementary approach to classic statistical analysis and enable a more robust assessment of microCT measures.Our group works on the detection and characterization of cassava viruses, supporting projects that involve large scale pathogen surveillance activities and resistance screening assays in multiple and remote locations. In order to comply with these applications, nucleic acid isolation protocols need to be cost effective, adjusted for samples that will stand long distance transport and harsh storage conditions, while maximizing the yield and quality of the nucleic acid extracts obtained. The method we describe here has been widely used and validated using different downstream tests (including, but not limited to, Rolling Circle Amplification and Illumina and Nanopore sequencing), but is currently unpublished. The protocol begins with milligram amounts of dry leaf samples stored in silica gel, does not require liquid Nitrogen nor phenol extraction and produces an average of 2.11 µg of nucleic acids per mg of dry tissue.•DNA purity estimations reveal OD260/280 ratios above 2.0 and OD260/230 ratios above 1.7, even for samples stored in silica gel for several months.•The high quality of the extracts is suitable for detection of DNA and RNA viruses, with high efficiency.•We suggest this method could be used as part of a gold standard kit for virus detection in cassava.People usually prefer to appear with an inclusive and positive attitude to others' eyes. For this reason, the self-report scales assessing social exclusion intentions are often biased by social desirability. In this work, we present an innovative graphical tool, named Social Exclusion Bench Tool (SEBT), for assessing social exclusion not influenced by social desirability. The tool is based on the consistency between social distance and physical distance evaluation. The results showed that in two samples of adults from Italy (N = 252) and the UK (N = 254), the SEBT positively correlated with self-report measures of social exclusion, but not with the social desirability measure. The tool has been preliminarily evaluated in the context of social exclusion toward migrant people, but it appears a promising instrument for assessing social exclusion intentions toward different social groups.•The self-report scales assessing social exclusion intentions are often biased by social desirability.•The Social Exclusion Bench Tool (SEBT) is an innovative visual instrument for assessing social exclusion that seems not to be influenced by social desirability.•The tool appears a promising instrument for assessing social exclusion intentions toward different social groups.In California vineyards, spore dispersal of fungi that cause grapevine trunk diseases Botryosphaeria dieback and Eutypa dieback occurs with winter rains. Spores infect through pruning wounds made to the woody structure of the vine in winter. link2 Better timing of preventative practices that minimize infection may benefit from routine spore-trapping, which could pinpoint site-specific time frames of spore dispersal. To speed pathogen detection from environmental spore samples, we identified species-specific PCR primers and protocols. Then we compared the traditional culture-based method versus our new DNA-based method.•PCR primers for Botryosphaeria-dieback pathogen Neofusicoccum parvum and Eutypa-dieback pathogen Eutypa lata were confirmed species-specific, through extensive testing of related species (in families Botryosphaeriaceae and Diatrypaceae, respectively), other trunk-disease pathogens, and saprophytic fungi that sporulate in vineyards.•Consistent detection of N. parvum was achieved from spore suspensions used fresh or stored at -20°C, whereas consistent detection of E. lata was achieved only with a new spore-lysis method, using zirconia/silica beads in a FastPrep homogenizer (MP Biomedicals; Solon, Ohio, USA), and only from spore suspensions used fresh. Freezing E. lata spores at -20°C made detection inconsistent.•From environmental samples, spores of E. lata were detected only via PCR, whereas spores of N. parvum were detected both via PCR and in culture.Laser-diffraction analysis has been established as one of the standard methods for particle-size distribution (PSD) measurement. However, the uncertainty when analyzing naturally heterogeneous sediment is poorly constrained for the lack of control on one of its largest error sources simply originating from subsampling. Here, we introduce a novel subsampling method, binary pipette splitting (BPS), and verify its precision by using sediment samples from ten flood-layer deposits that have formed in the wake of Hurricane Florence (2018). The BPS approach avoids extracting from only a fixed part of the suspended fluid but considers all the suspended sediment, resulting in the generation of twin subsamples. The median coefficient of variation (COV) for D10, D50, and D90 of subsamples obtained using BPS is 4%, 3%, and 2%, respectively. These values are significantly smaller than the corresponding values of 18%, 15%, and 13% obtained using the conventional pipette subsampling method. Therefore, the new BPS method represents a significant improvement in producing statistically identical subsamples for laser-diffraction particle-size analysis. •The binary pipette splitting (BPS) subsampling method dramatically improves the reproducibility of subsampling wet sediment.Studies on clean energy transition amongst low-income urban households in the Global South use an array of qualitative and quantitative methods. link3 However, attempts to combine qualitative and quantitative methods are rare and there are a lack of systematic approaches to this. This paper demonstrates a two stage approach using clustering methods to analyse a mixed dataset containing quantitative household survey data and qualitative interview data. By clustering the quantitative and qualitative data separately, latent groups with common characteristics and narratives arising from each of the two analyses are identified. A second stage of clustering identifies links between these qualitative and quantitative clusters and enables inference of energy transition pathways followed by low-income urban households defined by both quantitative characteristics and qualitative narratives. This approach can support interdisciplinary collaboration in energy research, providing a systematic approach to comparing and identifying links between quantitative and qualitative findings.
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