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The unidentified very-high-energy (VHE; E > 0.1 TeV) gamma -ray source, HESS J1826-130, was discovered with the High Energy Stereoscopic System (HESS) in the Galactic plane. The analysis of 215 h of HESS data has revealed a steady gamma -ray flux from HESS J1826-130, which appears extended with a half-width of 0.21 degrees +/- 0.02 <br /> (stat)degrees <br /> stat degrees +/- 0.05 <br /> (sys)degrees sys degrees . The source spectrum is best fit with either a power-law function with a spectral index Gamma = 1.78 +/- 0.10(stat) +/- 0.20(sys) and an exponential cut-off at 15.2 <br /> (+5.5)(-3.2) -3.2+5.5 TeV, or a broken power-law with Gamma (1) = 1.96 +/- 0.06(stat) +/- 0.20(sys), Gamma (2) = 3.59 +/- 0.69(stat) +/- 0.20(sys) for energies below and above E-br = 11.2 +/- 2.7 TeV, respectively. The VHE flux from HESS J1826-130 is contaminated by the extended emission of the bright, nearby pulsar wind nebula, HESS J1825-137, particularly at the low end of the energy spectrum. Leptonic scenarios for the origin of HESS J1826-130 VHE emission related to PSR J1826-1256 are confronted by our spectral and morphological analysis. In a hadronic framework, taking into account the properties of dense gas regions surrounding HESS J1826-130, the source spectrum would imply an astrophysical object capable of accelerating the parent particle population up to greater than or similar to 200 TeV. Our results are also discussed in a multiwavelength context, accounting for both the presence of nearby supernova remnants, molecular clouds, and counterparts detected in radio, X-rays, and TeV energies.
We report on the detection of very high energy (VHE; E > 100 GeV) gamma-ray emission from the BL Lac objects KUV 00311-1938 and PKS 1440-389 with the High Energy Stereoscopic System (H.E.S.S.). H.E.S.S. observations were accompanied or preceded by multiwavelength observations with Fermi/LAT, XRT and UVOT onboard the Swift satellite, and ATOM. Based on an extrapolation of the Fermi/LAT spectrum towards the VHE gamma-ray regime, we deduce a 95 per cent confidence level upper limit on the unknown redshift of KUV 00311-1938 of z < 0.98 and of PKS 1440-389 of z < 0.53. When combined with previous spectroscopy results, the redshift of KUV 00311-1938 is constrained to 0.51 <= z < 0.98 and of PKS 1440-389 to 0.14 (sic) z < 0.53.
Say it with double flowers
(2020)
Every year, lovers world-wide rely on mutants to show their feelings on Valentine's Day. This is because many of the most popular ornamental flowering plants have been selected to form extra petals at the expense of reproductive organs to enhance their attractiveness and aesthetic value to humans. This so-called 'double flower' (DF) phenotype, first described more than 2000 years ago (Meyerowitz et al., 1989) is present, for example, in many modern roses, carnations, peonies, and camellias. Gattolin et al. (2020) now identify a unifying explanation for the molecular basis of many of these DF cultivars.
Increasingly, research attention is being afforded to various forms of problematic media use. Despite ongoing conceptual, theoretical, and empirical debates, a large number of retrospective self-report scales have been produced to ostensibly measure various classes of such behaviour. These scales are typically based on a variety of theoretical and diagnostic frameworks. Given current conceptual ambiguities, building on previous studies, we evaluated the dimensional structure of 50 scales targeting the assessment of supposedly problematic behaviours in relation to four technologies: Internet, smartphones, video games, and social network sites. We find that two dimensions (‘compulsive use’ and ‘negative outcomes’) account for over 50% of all scale-items analysed. With a median of five dimensions, on average, scales have considered fewer dimensions than various proposed diagnostic criteria and models. No relationships were found between the number of items in a scale and the number of dimensions, or the technology category and the dimensional structure. The findings indicate, firstly, that a majority of scales place an inordinate emphasis on some dimensions over others and, secondly, that despite differences in the items presented, at a dimensional level, there exists a high degree of similarity between scales. These findings highlight shortcomings in existing scales and underscore the need to develop more sophisticated conceptions and empirical tools to understand possible problematic interactions with various digital technologies.
Does a smile open all doors?
(2020)
Online photographs govern an individual’s choices across a variety of contexts. In sharing arrangements, facial appearance has been shown to affect the desire to collaborate, interest to explore a listing, and even willingness to pay for a stay. Because of the ubiquity of online images and their influence on social attitudes, it seems crucial to be able to control these aspects. The present study examines the effect of different photographic self-disclosures on the provider’s perceptions and willingness to accept a potential co-sharer. The findings from our experiment in the accommodation-sharing context suggest social attraction mediates the effect of photographic self-disclosures on willingness to host. Implications of the results for IS research and practitioners are discussed.
When infants observe a human grasping action, experience-based accounts predict that all infants familiar with grasping actions should be able to predict the goal regardless of additional agency cues such as an action effect. Cue-based accounts, however, suggest that infants use agency cues to identify and predict action goals when the action or the agent is not familiar. From these accounts, we hypothesized that younger infants would need additional agency cues such as a salient action effect to predict the goal of a human grasping action, whereas older infants should be able to predict the goal regardless of agency cues. In three experiments, we presented 6-, 7-, and 11-month-olds with videos of a manual grasping action presented either with or without an additional salient action effect (Exp. 1 and 2), or we presented 7-month-olds with videos of a mechanical claw performing a grasping action presented with a salient action effect (Exp. 3). The 6-month-olds showed tracking gaze behavior, and the 11-month-olds showed predictive gaze behavior, regardless of the action effect. However, the 7-month-olds showed predictive gaze behavior in the action-effect condition, but tracking gaze behavior in the no-action-effect condition and in the action-effect condition with a mechanical claw. The results therefore support the idea that salient action effects are especially important for infants' goal predictions from 7 months on, and that this facilitating influence of action effects is selective for the observation of human hands.
This book endeavours to understand the seemingly direct link between utopianism and the USA, discussing novels that have never been brought together in this combination before, even though they all revolve around intentional communities: Imlay’s The Emigrants (1793), Hawthorne’s The Blithedale Romance (1852), Howland’s Papas Own Girl (1874), Griggs’s Imperium in Imperio (1899), and Du Bois’s The Quest of the Silver Fleece (1911). They relate nation and utopia not by describing perfect societies, but by writing about attempts to immediately live radically different lives. Signposting the respective communal history, the readings provide a literary perspective to communal studies, and add to a deeply necessary historicization for strictly literary approaches to US utopianism, and for studies that focus on Pilgrims/Puritans/Founding Fathers as utopian practitioners. This book therefore highlights how the authors evaluated the USA’s utopian potential and traces the nineteenth-century development of the utopian imagination from various perspectives.
In clinical settings, significant resources are spent on data collection and monitoring patients' health parameters to improve decision-making and provide better care. With increased digitization, the healthcare sector is shifting towards implementing digital technologies for data management and in administration. New technologies offer better treatment opportunities and streamline clinical workflow, but the complexity can cause ineffectiveness, frustration, and errors. To address this, we believe digital solutions alone are not sufficient. Therefore, we take a human-centred design approach for AI development, and apply systems engineering methods to identify system leverage points. We demonstrate how automation enables monitoring clinical parameters, using existing non-intrusive sensor technology, resulting in more resources toward patient care. Furthermore, we provide a framework on digitization of clinical data for integration with data management.
Background:
Childhood and adolescence are critical stages of life for mental health and well-being. Schools are a key setting for mental health promotion and illness prevention. One in five children and adolescents have a mental disorder, about half of mental disorders beginning before the age of 14. Beneficial and explainable artificial intelligence can replace current paper- based and online approaches to school mental health surveys. This can enhance data acquisition, interoperability, data driven analysis, trust and compliance. This paper presents a model for using chatbots for non-obtrusive data collection and supervised machine learning models for data analysis; and discusses ethical considerations pertaining to the use of these models.
Methods:
For data acquisition, the proposed model uses chatbots which interact with students. The conversation log acts as the source of raw data for the machine learning. Pre-processing of the data is automated by filtering for keywords and phrases.
Existing survey results, obtained through current paper-based data collection methods, are evaluated by domain experts (health professionals). These can be used to create a test dataset to validate the machine learning models. Supervised learning
can then be deployed to classify specific behaviour and mental health patterns.
Results:
We present a model that can be used to improve upon current paper-based data collection and manual data analysis methods. An open-source GitHub repository contains necessary tools and components of this model. Privacy is respected through
rigorous observance of confidentiality and data protection requirements. Critical reflection on these ethics and law aspects is included in the project.
Conclusions:
This model strengthens mental health surveillance in schools. The same tools and components could be applied to other public health data. Future extensions of this model could also incorporate unsupervised learning to find clusters and patterns
of unknown effects.
Type 2 diabetes (T2D) is a complex metabolic disease regulated by an interaction of genetic predisposition and environmental factors. To understand the genetic contribution in the development of diabetes, mice varying in their disease susceptibility were crossed with the obese and diabetes-prone New Zealand obese (NZO) mouse. Subsequent whole-genome sequence scans revealed one major quantitative trait loci (QTL),Nidd/DBAon chromosome 4, linked to elevated blood glucose and reduced plasma insulin and low levels of pancreatic insulin. Phenotypical characterization of congenic mice carrying 13.6 Mbp of the critical fragment of DBA mice displayed severe hyperglycemia and impaired glucose clearance at week 10, decreased glucose response in week 13, and loss of beta-cells and pancreatic insulin in week 16. To identify the responsible gene variant(s), further congenic mice were generated and phenotyped, which resulted in a fragment of 3.3 Mbp that was sufficient to induce hyperglycemia. By combining transcriptome analysis and haplotype mapping, the number of putative responsible variant(s) was narrowed from initial 284 to 18 genes, including gene models and non-coding RNAs. Consideration of haplotype blocks reduced the number of candidate genes to four (Kti12,Osbpl9,Ttc39a, andCalr4) as potential T2D candidates as they display a differential expression in pancreatic islets and/or sequence variation. In conclusion, the integration of comparative analysis of multiple inbred populations such as haplotype mapping, transcriptomics, and sequence data substantially improved the mapping resolution of the diabetes QTLNidd/DBA. Future studies are necessary to understand the exact role of the different candidates in beta-cell function and their contribution in maintaining glycemic control.
Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure – the weighted degree–betweenness (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.
This opinion article describes recent approaches to use the "biorefinery" concept to lower the carbon footprint of typical mass polymers, by replacing parts of the fossil monomers with similar or even the same monomer made from regrowing dendritic biomass. Herein, the new and green catalytic synthetic routes are for lactic acid (LA), isosorbide (IS), 2,5-furandicarboxylic acid (FDCA), and p-xylene (pXL). Furthermore, the synthesis of two unconventional lignocellulosic biomass derivable monomers, i.e., alpha-methylene-gamma-valerolactone (MeGVL) and levoglucosenol (LG), are presented. All those have the potential to enter in a cost-effective way, also the mass market and thereby recover lost areas for polymer materials. The differences of catalytic unit operations of the biorefinery are also discussed and the challenges that must be addressed along the synthesis path of each monomers.
This opinion article describes recent approaches to use the "biorefinery" concept to lower the carbon footprint of typical mass polymers, by replacing parts of the fossil monomers with similar or even the same monomer made from regrowing dendritic biomass. Herein, the new and green catalytic synthetic routes are for lactic acid (LA), isosorbide (IS), 2,5-furandicarboxylic acid (FDCA), and p-xylene (pXL). Furthermore, the synthesis of two unconventional lignocellulosic biomass derivable monomers, i.e., alpha-methylene-gamma-valerolactone (MeGVL) and levoglucosenol (LG), are presented. All those have the potential to enter in a cost-effective way, also the mass market and thereby recover lost areas for polymer materials. The differences of catalytic unit operations of the biorefinery are also discussed and the challenges that must be addressed along the synthesis path of each monomers.
We study those nonlinear partial differential equations which appear as Euler-Lagrange equations of variational problems. On defining weak boundary values of solutions to such equations we initiate the theory of Lagrangian boundary value problems in spaces of appropriate smoothness. We also analyse if the concept of mapping degree of current importance applies to Lagrangian problems.
Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.
Das Recht auf ein faires Verfahren gemäß Art. 6 der Europäischen Menschenrechtskonvention (EMRK) gewährleistet nach der ständigen Rechtsprechung des Europäischen Gerichtshofs für Menschenrechte die Fairness des Verfahrens insgesamt (»overall fairness«). Verkürzungen einzelner Verteidigungsrechte des Angeklagten können danach unter bestimmten Voraussetzungen innerhalb des Verfahrens ausgeglichen werden. Anna H. Albrecht leitet aus diesem Maßstab der Gesamtfairness ab, dass sich das nationale Strafverfahrensrecht und die Anforderungen des Art. 6 Abs. 1 und 3 EMRK an ebendieses wechselseitig beeinflussen. Sie analysiert, inwieweit der Gerichtshof solche Wechselwirkungen anzuerkennen bereit ist, und arbeitet sie am Beispiel des Rechts des Angeklagten auf Anwesenheit in der erstinstanzlichen Hauptverhandlung heraus, indem sie das einschlägige englische und deutsche Recht vergleicht und in Beziehung zu der entsprechenden Gewährleistung in Art. 6 Abs. 1, 3 EMRK setzt.
Editorial
(2020)