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Purpose: Coarticulatory effects in speech vary across development, but the sources of this variation remain unclear. This study investigated whether developmental differences in intrasyllabic coarticulation degree could be explained by differences in children's articulatory patterns compared to adults.
Method: To address this question, we first compared the tongue configurations of 3-to 7-year-old German children to those of adults. The observed developmental differences were then examined through simulations with Task Dynamics Application, a Task Dynamics simulation system, to establish which articulatory modifications could best reproduce the empirical results. To generate syllables simulating the lack of tongue gesture differentiation, we tested three simulation scenarios.
Results: We found that younger speakers use less differentiated articulatory patterns to achieve alveolar constrictions than adults. The simulations corresponding to undifferentiated control of tongue tip and tongue body resulted in (a) tongue shapes similar to those observed in natural speech and (b) higher degrees of intrasyllabic coarticulation in children when compared to adults.
Conclusions: Results provide evidence that differences in articulatory patterns contribute to developmental differences in coarticulation degree. This study further shows that empirically informed modeling can advance our understanding of changes in coarticulatory patterns across age.
Advances in characteristics improvement of polymeric membranes/separators for zinc-air batteries
(2022)
Zinc-air batteries (ZABs) are gaining popularity for a wide range of applications due to their high energy density, excellent safety, and environmental friendliness. A membrane/separator is a critical component of ZABs, with substantial implications for battery performance and stability, particularly in the case of a battery in solid state format, which has captured increased attention in recent years. In this review, recent advances as well as insight into the architecture of polymeric membrane/separators for ZABs including porous polymer separators (PPSs), gel polymer electrolytes (GPEs), solid polymer electrolytes (SPEs) and anion exchange membranes (AEMs) are discussed. The paper puts forward strategies to enhance stability, ionic conductivity, ionic selectivity, electrolyte storage capacity and mechanical properties for each type of polymeric membrane. In addition, the remaining major obstacles as well as the most potential avenues for future research are examined in detail.
Deep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions.
Ionic guest in ionic host
(2022)
Ionosilica ionogels, i.e. composites consisting of an ionic liquid (IL) guest confined in an ionosilica host matrix, were synthesized via a non-hydrolytic sol-gel procedure from a tris-trialcoxysilylated amine precursor using the IL [BMIM]NTf2 as solvent. Various ionosilica ionogels were prepared starting from variable volumes of IL in the presence of formic acid. The resulting brittle and nearly colourless monoliths are composed of different amounts of IL guests confined in an ionosilica host as evidenced via thermogravimetric analysis, FT-IR, and C-13 CP-MAS solid-state NMR spectroscopy. In the following, we focused on confinement effects between the ionic host and guest. Special host-guest interactions between the IL guest and the ionosilica host were evidenced by H-1 solid-state NMR, Raman spectroscopy, and broadband dielectric spectroscopy (BDS) measurements. The three techniques indicate a strongly reduced ion mobility in the ionosilica ionogel composites containing small volume fractions of confined IL, compared to conventional silica-based ionogels. We conclude that the ionic ionosilica host stabilizes an IL layer on the host surface; this then results in a strongly reduced ion mobility compared to conventional silica hosts. The ion mobility progressively increases for systems containing higher volume fractions of IL and finally reaches the values observed in conventional silica based ionogels. These results therefore point towards strong interactions and confinement effects between the ionic host and the ionic guest on the ionosilica surface. Furthermore, this approach allows confining high volume fractions of IL into self-standing monoliths while preserving high ionic conductivity. These effects may be of interest in domains where IL phases must be anchored on solid supports to avoid leaching or IL spilling, e.g., in catalysis, in gas separation/sequestration devices or for the elaboration of solid electrolytes for (lithium-ion) batteries and supercapacitors.
We characterize finite-time thermodynamic processes of multidimensional quadratic overdamped systems.
Analytic expressions are provided for heat, work, and dissipation for any evolution of the system covariance matrix.
The Bures-Wasserstein metric between covariance matrices naturally emerges as the local quantifier of dissipation.
General principles of how to apply these geometric tools to identify optimal protocols are discussed.
Focusing on the relevant slow-driving limit, we show how these results can be used to analyze cases in which the experimental control over the system is partial.
Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively.
Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively.
We used structural topic modeling to analyze over 800,000 German tweets about COVID-19 to answer the questions: What patterns emerge in tweets as a response to a health crisis? And how do topics discussed change over time? The study leans on the goals associated with the health information seeking (GAINS) model, discerning whether a post aims at tackling and eliminating the problem (i.e., problem-focused) or managing the emotions (i.e., emotion-focused); whether it strives to maximize positive outcomes (promotion focus) or to minimize negative outcomes (prevention focus). The findings indicate four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Public communication is volatile over time, and a shift is evidenced from self-centered to community-centered topics within 4.5 weeks. Our study illustrates social media text mining's potential to quickly and efficiently extract public opinions and reactions. Monitoring fears and trending topics enable policymakers to rapidly respond to deviant behavior, like resistive attitudes toward containment measures or deteriorating physical health. Healthcare workers can use the insights to provide mental health services for battling anxiety or extensive loneliness from staying home.
During a crisis event, social media enables two-way communication and many-to-many information broadcasting, browsing others’ posts, publishing own content, and public commenting. These records can deliver valuable insights to approach problematic situations effectively. Our study explores how social media communication can be analyzed to understand the responses to health crises better. Results based on nearly 800 K tweets indicate that the coping and regulation foci framework holds good explanatory power, with four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Second, the inter-temporal analysis shows high volatility of topic proportions and a shift from self-centered to community-centered topics during the course of the event. The insights are beneficial for research on crisis management and practicians who are interested in large-scale monitoring of their audience for well-informed decision-making.
One for all, all for one
(2022)
We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap.
One for all, all for one
(2022)
We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap.
Beyond humanitarianism
(2022)
Alien Horrors
(2022)
H. P. Lovecraft’s oeuvre abounds with stereotypes of the racialized poor. As scholars have noted, Lovecraft’s work turns those he viewed as ‘Others’ into ‘aliens.’ Poor people of color (as opposed to the orderly White rural population and White working class) in Lovecraft’s stories are foreign, diseased, and criminal, and they threaten social and cosmic orders as they are in league with a nebulous entity that waits to wreak indescribable havoc. This chapter analyzes three ‘Lovecraftian’ novels published in 2016 - Cassandra Khaw’s Hammers on Bone,Victor LaValle’s The Ballad of Black Tom, and Matt Ruff’s Lovecraft Country. These works elucidate the connection of Trump’s 2016 rhetoric in campaign and presidential speeches and the White supremacist imagery used by Lovecraft. In these novels, the racialized poor have a special connection to an astronomical, evil entity à la Lovecraft. As carriers of numinous genes or parasitic entities (literally having ‘an alien within’) they become empowered. They thus occupy a pivotal position in forestalling or bringing about the destruction of societal order; that is, of White supremacy. Exploring the alleged risk posed by this ‘underclass,’ these works seem to foretell current representations of protesters as ‘riotous mobs’ that threaten the body politic Trump sought to make great (and White) again.
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.