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Boyle, T.C.
(2022)
T.C. Boyle, or Thomas Coraghessan Boyle, is probably best known for his 1995 novel Tortilla Curtain , which quickly became a staple of high school and college syllabi. Tortilla Curtain deftly illustrates what Boyle does best: acerbically tracing the irrationality that governs human thought and the resulting contradictory and often unethical behavior (mostly in relation to xenophobia, environmentalism, and the intersections of gender). Despite often casting a critical eye over US American society, Boyle's works are accessible reads with fast-paced and eventful plots. This combination has produced a number of international bestsellers. In fact, Boyle is so popular in Germany that translations of his works have been published before the original versions came out in English. However, his talent for depicting the impotence of reason in the face of base desires, selfishness, group dynamics, and indoctrinated ideologies is also a weakness: at times, Boyle's satire reproduces what it means to criticize, coming close to naturalizing the hedonistic, prejudiced, and emotionally charged behavior of his characters.
Accurately predicting total electron content (TEC) during geomagnetic storms is still a challenging task for ionospheric models. In this work, a neural-network (NN)-based model is proposed which predicts relative TEC with respect to the preceding 27-day median TEC, during storm time for the European region (with longitudes 30 degrees W-50 degrees E and latitudes 32.5 degrees N-70 degrees N). The 27-day median TEC (referred to as median TEC), latitude, longitude, universal time, storm time, solar radio flux index F10.7, global storm index SYM-H and geomagnetic activity index Hp30 are used as inputs and the output of the network is the relative TEC. The relative TEC can be converted to the actual TEC knowing the median TEC. The median TEC is calculated at each grid point over the European region considering data from the last 27 days before the storm using global ionosphere maps (GIMs) from international GNSS service (IGS) sources. A storm event is defined when the storm time disturbance index Dst drops below 50 nanotesla. The model was trained with storm-time relative TEC data from the time period of 1998 until 2019 (2015 is excluded) and contains 365 storms. Unseen storm data from 33 storm events during 2015 and 2020 were used to test the model. The UQRG GIMs were used because of their high temporal resolution (15 min) compared to other products from different analysis centers. The NN-based model predictions show the seasonal behavior of the storms including positive and negative storm phases during winter and summer, respectively, and show a mixture of both phases during equinoxes. The model's performance was also compared with the Neustrelitz TEC model (NTCM) and the NN-based quiet-time TEC model, both developed at the German Aerospace Agency (DLR). The storm model has a root mean squared error (RMSE) of 3.38 TEC units (TECU), which is an improvement by 1.87 TECU compared to the NTCM, where an RMSE of 5.25 TECU was found. This improvement corresponds to a performance increase by 35.6%. The storm-time model outperforms the quiet-time model by 1.34 TECU, which corresponds to a performance increase by 28.4% from 4.72 to 3.38 TECU. The quiet-time model was trained with Carrington averaged TEC and, therefore, is ideal to be used as an input instead of the GIM derived 27-day median. We found an improvement by 0.8 TECU which corresponds to a performance increase by 17% from 4.72 to 3.92 TECU for the storm-time model using the quiet-time-model predicted TEC as an input compared to solely using the quiet-time model.
Pancreatic steatosis associates with beta-cell failure and may participate in the development of type-2-diabetes. Our previous studies have shown that diabetes-susceptible mice accumulate more adipocytes in the pancreas than diabetes-resistant mice. In addition, we have demonstrated that the co-culture of pancreatic islets and adipocytes affect insulin secretion. The aim of this current study was to elucidate if and to what extent pancreas-resident mesenchymal stromal cells (MSCs) with adipogenic progenitor potential differ from the corresponding stromal-type cells of the inguinal white adipose tissue (iWAT). miRNA (miRNome) and mRNA expression (transcriptome) analyses of MSCs isolated by flow cytometry of both tissues revealed 121 differentially expressed miRNAs and 1227 differentially expressed genes (DEGs). Target prediction analysis estimated 510 DEGs to be regulated by 58 differentially expressed miRNAs. Pathway analyses of DEGs and miRNA target genes showed unique transcriptional and miRNA signatures in pancreas (pMSCs) and iWAT MSCs (iwatMSCs), for instance fibrogenic and adipogenic differentiation, respectively. Accordingly, iwatMSCs revealed a higher adipogenic lineage commitment, whereas pMSCs showed an elevated fibrogenesis. As a low degree of adipogenesis was also observed in pMSCs of diabetes-susceptible mice, we conclude that the development of pancreatic steatosis has to be induced by other factors not related to cell-autonomous transcriptomic changes and miRNA-based signals.
The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.
The degree of detrimental effects inflicted on mankind by the COVID-19 pandemic increased the need to develop ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable) POCT (point of care testing) to overcome the current and any future pandemics. Much effort in research and development is currently advancing the progress to overcome the diagnostic pressure built up by emerging new pathogens. LAMP (loop-mediated isothermal amplification) is a well-researched isothermal technique for specific nucleic acid amplification which can be combined with a highly sensitive immunochromatographic readout via lateral flow assays (LFA). Here we discuss LAMP-LFA robustness, sensitivity, and specificity for SARS-CoV-2 N-gene detection in cDNA and clinical swab-extracted RNA samples. The LFA readout is designed to produce highly specific results by incorporation of biotin and FITC labels to 11-dUTP and LF (loop forming forward) primer, respectively. The LAMP-LFA assay was established using cDNA for N-gene with an accuracy of 95.65%. To validate the study, 82 SARS-CoV-2-positive RNA samples were tested. Reverse transcriptase (RT)-LAMP-LFA was positive for the RNA samples with an accuracy of 81.66%; SARS-CoV-2 viral RNA was detected by RT-LAMP-LFA for as low as CT-33. Our method reduced the detection time to 15 min and indicates therefore that RT-LAMP in combination with LFA represents a promising nucleic acid biosensing POCT platform that combines with smartphone based semi-quantitative data analysis.
Etmopteridae (lantern sharks) is the most species-rich family of sharks, comprising more than 50 species.
Many species are described from few individuals, and re-collection of specimens is often hindered by the remoteness of their sampling sites.
For taxonomic studies, comparative morphological analysis of type specimens housed in natural history collections has been the main source of evidence.
In contrast, DNA sequence information has rarely been used.
Most lantern shark collection specimens, including the types, were formalin fixed before long-term storage in ethanol solutions.
The DNA damage caused by both fixation and preservation of specimens has excluded these specimens from DNA sequence-based phylogenetic analyses so far.
However, recent advances in the field of ancient DNA have allowed recovery of wet-collection specimen DNA sequence data.
Here we analyse archival mitochondrial DNA sequences, obtained using ancient DNA approaches, of two wet-collection lantern shark paratype specimens, namely Etmopterus litvinovi and E. pycnolepis, for which the type series represent the only known individuals.
Target capture of mitochondrial markers from single-stranded DNA libraries allows for phylogenetic placement of both species.
Our results suggest synonymy of E. benchleyi with E. litvinovi but support the species status of E. pycnolepis. This revised taxonomy is helpful for future conservation and management efforts, as our results indicate a larger distribution range of E. litvinovi. This study further demonstrates the importance of wet-collection type specimens as genetic resource for taxonomic research.
Simultaneous Barcode Sequencing of Diverse Museum Collection Specimens Using a Mixed RNA Bait Set
(2022)
A growing number of publications presenting results from sequencing natural history collection specimens reflect the importance of DNA sequence information from such samples. Ancient DNA extraction and library preparation methods in combination with target gene capture are a way of unlocking archival DNA, including from formalin-fixed wet-collection material. Here we report on an experiment, in which we used an RNA bait set containing baits from a wide taxonomic range of species for DNA hybridisation capture of nuclear and mitochondrial targets for analysing natural history collection specimens. The bait set used consists of 2,492 mitochondrial and 530 nuclear RNA baits and comprises specific barcode loci of diverse animal groups including both invertebrates and vertebrates. The baits allowed to capture DNA sequence information of target barcode loci from 84% of the 37 samples tested, with nuclear markers being captured more frequently and consensus sequences of these being more complete compared to mitochondrial markers. Samples from dry material had a higher rate of success than wet-collection specimens, although target sequence information could be captured from 50% of formalin-fixed samples. Our study illustrates how efforts to obtain barcode sequence information from natural history collection specimens may be combined and are a way of implementing barcoding inventories of scientific collection material.
Water stable isotopes (delta O-18 and delta H-2) were analyzed in samples collected in lakes, associated with riverine systems in northeastern Germany, throughout 2020. The dataset (Aichner et al., 2021; https://doi.org/10.1594/PANGAEA.935633) is derived from water samples collected at (a) lake shores (sampled in March and July 2020), (b) buoys which were temporarily installed in deep parts of the lake (sampled monthly from March to October 2020), (c) multiple spatially distributed spots in four selected lakes (in September 2020), and (d) the outflow of Muggelsee (sampled biweekly from March 2020 to January 2021). At shores, water was sampled with a pipette from 40-60 cm below the water surface and directly transferred into a measurement vial, while at buoys a Limnos water sampler was used to obtain samples from 1 m below the surface. Isotope analysis was conducted at IGB Berlin, using a Picarro L2130-i cavity ring-down spectrometer, with a measurement uncertainty of < 0.15 parts per thousand (delta O-18) and < 0.0 parts per thousand (delta H-2). The data give information about the vegetation period and the full seasonal isotope amplitude in the sampled lakes and about spatial isotope variability in different branches of the associated riverine systems.
The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies.
Suppression of the TeV Pair-beam-Plasma Instability by a Tangled Weak Intergalactic Magnetic Field
(2022)
We study the effect of a tangled sub-fG level intergalactic magnetic field (IGMF) on the electrostatic instability of a blazar-induced pair beam. Sufficiently strong IGMF may significantly deflect the TeV pair beams, which would reduce the flux of secondary cascade emission below the observational limits. A similar flux reduction may result from the electrostatic beam-plasma instability, which operates the best in the absence of IGMF. Considering IGMF with correlation lengths smaller than a kiloparsec, we find that weak magnetic fields increase the transverse momentum of the pair-beam particles, which dramatically reduces the linear growth rate of the electrostatic instability and hence the energy-loss rate of the pair beam. We show that the beam-plasma instability is eliminated as an effective energy-loss agent at a field strength three orders of magnitude below that needed to suppress the secondary cascade emission by magnetic deflection. For intermediate-strength IGMF, we do not know a viable process to explain the observed absence of GeV-scale cascade emission.