scholarly journals Phylogenomics unravels the early diversification of fungi

2021 ◽  
Author(s):  
Jürgen F. H. Strassert ◽  
Michael T. Monaghan
Keyword(s):  
Life History Strategies ◽  
Evolutionary Models ◽  
Heterogeneous Mixture ◽  
Data Set ◽  
Transcriptomic Data ◽  
Evolutionary Origins ◽  
Early Diversification ◽  
Wide Range ◽  
Phylogenomic Analyses ◽  
Shed Light

Our understanding of the eukaryote tree of life is continually improving, although the branching events at some of the deepest nodes remain elusive. The fungi are an ancient group of eukaryotes with a wide range of morphologies, life-history strategies, and ecological roles. While several recent phylogenomic analyses have been shown to be a powerful tool for uncovering even earliest diversifications, no study has yet examined the entire tree of fungi using a taxonomically comprehensive data set and suitable models of evolution. Here, we assembled a data set of 299 proteins from all recognised fungal groups for which genomic/transcriptomic data were available and subjected this to a battery of analyses, including tree inferences using site-heterogeneous mixture models and the Multi-Species Coalescent model. Tree topology was highly congruent and well supported, and any incongruence was found to result from an inability of some frequently used evolutionary models to model fast-evolving and heterogeneous sites. Our results provide higher resolution among early-branching lineages than previous studies, and shed light on hitherto highly contested evolutionary origins of the major fungal groups.

scholarly journals När barnet blir expert: Förklaringar av ord och procedurer i det digitala spelet Growtopia

2019 ◽  
Vol NF 28 (2018) ◽  
pp. 48-77
Author(s):  
Åsa Palviainen ◽  
Arja Piirainen-Marsh
Keyword(s):  
Academic Language ◽  
Semantic Features ◽  
Data Set ◽  
Word Meanings ◽  
Context Sensitive ◽  
Video Recordings ◽  
Wide Range ◽  
Multimodal Features ◽  
The Family ◽  
Shed Light

The ability to explain word meanings is central to a child’s language development and socialisation into different domains of language use. In previous research explanations have been shown to be linked to cognitive and linguistic development as well as academic language and discursive skills. This paper analyses what kinds of linguistic and discursive competences are put to use in explanation activities in interactions between an 8-year-old bilingual child (Albin) and his mother around a digital game. The data comes from a larger data set of video-recordings and field observation of children’s interactions around games. The analysis focuses on explanation sequences in which the child explicates the meaning of objects and procedures in the game world. The analysis shows how explanations are initiated, how they unfold in interaction and how they make relevant asymmetrical roles for the participants, allowing the child to construct a position of knowledge with regard to the game, an important part of his life world. More specifically, the analysis elucidates how Albin’s explanations highlight semantic features and relations that are meaningful for him and how he employs a wide range of linguistic and other semiotic resources in constructing his explanations in a context-sensitive way. The findings shed light on linguistic, interactional and multimodal features of explanations as a discourse activity and provide a window into practices of two-way language socialization in the family.

Sentence-Based Experience Logging in New Hearing Aid Users

2020 ◽  
Vol 29 (3S) ◽  
pp. 631-637
Author(s):  
Katja Lund ◽  
Rodrigo Ordoñez ◽  
Jens Bo Nielsen ◽  
Dorte Hammershøi
Keyword(s):  
Hearing Aid ◽  
Patient Experiences ◽  
Online Tool ◽  
Rehabilitation Process ◽  
Hearing Rehabilitation ◽  
Clinical Observations ◽  
Hearing Aid Use ◽  
Wide Range ◽  
Insight Into ◽  
Shed Light

Purpose The aim of this study was to develop a tool to gain insight into the daily experiences of new hearing aid users and to shed light on aspects of aided performance that may not be unveiled through standard questionnaires. Method The tool is developed based on clinical observations, patient experiences, expert involvement, and existing validated hearing rehabilitation questionnaires. Results An online tool for collecting data related to hearing aid use was developed. The tool is based on 453 prefabricated sentences representing experiences within 13 categories related to hearing aid use. Conclusions The tool has the potential to reflect a wide range of individual experiences with hearing aid use, including auditory and nonauditory aspects. These experiences may hold important knowledge for both the patient and the professional in the hearing rehabilitation process.

Structure Guided Molecular Docking Assisted Alignment Dependent 3DQSAR Study on Steroidal Aromatase Inhibitors (SAIs) as Anti-breast Cancer Agents

2019 ◽  
Vol 16 (7) ◽  
pp. 808-817 ◽  
Author(s):  
Laxmi Banjare ◽  
Sant Kumar Verma ◽  
Akhlesh Kumar Jain ◽  
Suresh Thareja
Keyword(s):  
Breast Cancer ◽  
Molecular Docking ◽  
Aromatase Inhibitors ◽  
Direct Synthesis ◽  
3D Qsar ◽  
Chemotherapeutic Agents ◽  
Modeling Tools ◽  
Data Set ◽  
Wide Range ◽  
Steroidal Aromatase Inhibitors

Background: In spite of the availability of various treatment approaches including surgery, radiotherapy, and hormonal therapy, the steroidal aromatase inhibitors (SAIs) play a significant role as chemotherapeutic agents for the treatment of estrogen-dependent breast cancer with the benefit of reduced risk of recurrence. However, due to greater toxicity and side effects associated with currently available anti-breast cancer agents, there is emergent requirement to develop target-specific AIs with safer anti-breast cancer profile. Methods: It is challenging task to design target-specific and less toxic SAIs, though the molecular modeling tools viz. molecular docking simulations and QSAR have been continuing for more than two decades for the fast and efficient designing of novel, selective, potent and safe molecules against various biological targets to fight the number of dreaded diseases/disorders. In order to design novel and selective SAIs, structure guided molecular docking assisted alignment dependent 3D-QSAR studies was performed on a data set comprises of 22 molecules bearing steroidal scaffold with wide range of aromatase inhibitory activity. Results: 3D-QSAR model developed using molecular weighted (MW) extent alignment approach showed good statistical quality and predictive ability when compared to model developed using moments of inertia (MI) alignment approach. Conclusion: The explored binding interactions and generated pharmacophoric features (steric and electrostatic) of steroidal molecules could be exploited for further design, direct synthesis and development of new potential safer SAIs, that can be effective to reduce the mortality and morbidity associated with breast cancer.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

scholarly journals A Self-Spatial Adaptive Weighting Based U-Net for Image Segmentation

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 348
Author(s):  
Choongsang Cho ◽  
Young Han Lee ◽  
Jongyoul Park ◽  
Sangkeun Lee
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Feature Maps ◽  
Data Set ◽  
Feature Map ◽  
Adaptive Weighting ◽  
Spatially Adaptive ◽  
Wide Range ◽  
Decoder Architecture

Semantic image segmentation has a wide range of applications. When it comes to medical image segmentation, its accuracy is even more important than those of other areas because the performance gives useful information directly applicable to disease diagnosis, surgical planning, and history monitoring. The state-of-the-art models in medical image segmentation are variants of encoder-decoder architecture, which is called U-Net. To effectively reflect the spatial features in feature maps in encoder-decoder architecture, we propose a spatially adaptive weighting scheme for medical image segmentation. Specifically, the spatial feature is estimated from the feature maps, and the learned weighting parameters are obtained from the computed map, since segmentation results are predicted from the feature map through a convolutional layer. Especially in the proposed networks, the convolutional block for extracting the feature map is replaced with the widely used convolutional frameworks: VGG, ResNet, and Bottleneck Resent structures. In addition, a bilinear up-sampling method replaces the up-convolutional layer to increase the resolution of the feature map. For the performance evaluation of the proposed architecture, we used three data sets covering different medical imaging modalities. Experimental results show that the network with the proposed self-spatial adaptive weighting block based on the ResNet framework gave the highest IoU and DICE scores in the three tasks compared to other methods. In particular, the segmentation network combining the proposed self-spatially adaptive block and ResNet framework recorded the highest 3.01% and 2.89% improvements in IoU and DICE scores, respectively, in the Nerve data set. Therefore, we believe that the proposed scheme can be a useful tool for image segmentation tasks based on the encoder-decoder architecture.

EXPRESS: How Does Bonus Payment Affect the Demand for Auto Loans and Their Delinquency?

2021 ◽  
pp. 002224372110092
Author(s):  
Zhenling Jiang ◽  
Dennis J. Zhang ◽  
Tat Chan
Keyword(s):  
Consumer Products ◽  
Data Set ◽  
Financial Decisions ◽  
Consumer Panel ◽  
Loan Demand ◽  
Bonus Payments ◽  
Base Salary ◽  
Long Term Impact ◽  
Shed Light

This paper studies how receiving a bonus changes the consumers’ demand for auto loans and the risk of future delinquency. Unlike traditional consumer products, auto loans have a long-term impact on consumers’ financial state because of the monthly payment obligation. Using a large consumer panel data set of credit and employment information, the authors find that receiving a bonus increases auto loan demand by 21 percent. These loans, however, are associated with higher risk, as the delinquency rate increases by 18.5 −31.4 percent depending on different measures. In contrast, an increase in consumers’ base salary will increase the demand for auto loans but not the delinquency. By comparing consumers with bonuses with those without bonuses, the authors find that bonus payments lead to both demand expansion and demand shifting on auto loans. The empirical findings help shed light on how consumers make financial decisions and have important implications for financial institutions on when demand for auto loans and the associated risk arise.

scholarly journals Prediction of Wide Range Two-Dimensional Refractivity Using an IDW Interpolation Method from High-Altitude Refractivity Data of Multiple Meteorological Observatories

2021 ◽  
Vol 11 (4) ◽  
pp. 1431
Author(s):  
Sungsik Wang ◽  
Tae Heung Lim ◽  
Kyoungsoo Oh ◽  
Chulhun Seo ◽  
Hosung Choo
Keyword(s):  
High Altitude ◽  
Korean Peninsula ◽  
Interpolation Method ◽  
Atmospheric Condition ◽  
Propagation Path ◽  
Two Dimensional ◽  
Data Set ◽  
Wide Range ◽  
Atmospheric Data ◽  
Terrain Surface

This article proposes a method for the prediction of wide range two-dimensional refractivity for synthetic aperture radar (SAR) applications, using an inverse distance weighted (IDW) interpolation of high-altitude radio refractivity data from multiple meteorological observatories. The radio refractivity is extracted from an atmospheric data set of twenty meteorological observatories around the Korean Peninsula along a given altitude. Then, from the sparse refractive data, the two-dimensional regional radio refractivity of the entire Korean Peninsula is derived using the IDW interpolation, in consideration of the curvature of the Earth. The refractivities of the four seasons in 2019 are derived at the locations of seven meteorological observatories within the Korean Peninsula, using the refractivity data from the other nineteen observatories. The atmospheric refractivities on 15 February 2019 are then evaluated across the entire Korean Peninsula, using the atmospheric data collected from the twenty meteorological observatories. We found that the proposed IDW interpolation has the lowest average, the lowest average root-mean-square error (RMSE) of ∇M (gradient of M), and more continuous results than other methods. To compare the resulting IDW refractivity interpolation for airborne SAR applications, all the propagation path losses across Pohang and Heuksando are obtained using the standard atmospheric condition of ∇M = 118 and the observation-based interpolated atmospheric conditions on 15 February 2019. On the terrain surface ranging from 90 km to 190 km, the average path losses in the standard and derived conditions are 179.7 dB and 182.1 dB, respectively. Finally, based on the air-to-ground scenario in the SAR application, two-dimensional illuminated field intensities on the terrain surface are illustrated.

Prodromal Dementia With Lewy Bodies: Evolution of Symptoms and Predictors of Dementia Onset

2021 ◽  
pp. 089198872110235
Author(s):  
Kathryn A. Wyman-Chick ◽  
Lauren R. O’Keefe ◽  
Daniel Weintraub ◽  
Melissa J. Armstrong ◽  
Michael Rosenbloom ◽  
...  
Keyword(s):  
Clinical Features ◽  
Dementia With Lewy Bodies ◽  
Clinical Symptoms ◽  
Neuropsychiatric Symptoms ◽  
Lewy Bodies ◽  
Rem Sleep Behavior Disorder ◽  
Data Set ◽  
Wide Range ◽  
Prodromal Dementia ◽  
Dementia Onset

Background: Research criteria for prodromal dementia with Lewy bodies (DLB) were published in 2020, but little is known regarding prodromal DLB in clinical settings. Methods: We identified non-demented participants without neurodegenerative disease from the National Alzheimer’s Coordinating Center Uniform Data Set who converted to DLB at a subsequent visit. Prevalence of neuropsychiatric and motor symptoms were examined up to 5 years prior to DLB diagnosis. Results: The sample included 116 participants clinically diagnosed with DLB and 348 age and sex-matched (1:3) Healthy Controls. Motor slowing was present in approximately 70% of participants 3 years prior to DLB diagnosis. In the prodromal phase, 50% of DLB participants demonstrated gait disorder, 70% had rigidity, 20% endorsed visual hallucinations, and over 50% of participants endorsed REM sleep behavior disorder. Apathy, depression, and anxiety were common prodromal neuropsychiatric symptoms. The presence of 1+ core clinical features of DLB in combination with apathy, depression, or anxiety resulted in the greatest AUC (0.815; 95% CI: 0.767, 0.865) for distinguishing HC from prodromal DLB 1 year prior to diagnosis. The presence of 2+ core clinical features was also accurate in differentiating between groups (AUC = 0.806; 95% CI: 0.756, 0.855). Conclusion: A wide range of motor, neuropsychiatric and other core clinical symptoms are common in prodromal DLB. A combination of core clinical features, neuropsychiatric symptoms and cognitive impairment can accurately differentiate DLB from normal aging prior to dementia onset.

scholarly journals Beyond cultural and geographical proximity: delving into the factors that influence the dynamics of academic relationships between students in higher education

2021 ◽  
Author(s):  
José-Vicente Tomás-Miquel ◽  
Jordi Capó-Vicedo
Keyword(s):  
University Students ◽  
Academic Research ◽  
Past Research ◽  
Academic Networks ◽  
Level Data ◽  
Wide Range ◽  
Specific Stage ◽  
The University ◽  
Proximity Dimensions ◽  
Shed Light

AbstractScholars have widely recognised the importance of academic relationships between students at the university. While much of the past research has focused on studying their influence on different aspects such as the students’ academic performance or their emotional stability, less is known about their dynamics and the factors that influence the formation and dissolution of linkages between university students in academic networks. In this paper, we try to shed light on this issue by exploring through stochastic actor-oriented models and student-level data the influence that a set of proximity factors may have on formation of these relationships over the entire period in which students are enrolled at the university. Our findings confirm that the establishment of academic relationships is derived, in part, from a wide range of proximity dimensions of a social, personal, geographical, cultural and academic nature. Furthermore, and unlike previous studies, this research also empirically confirms that the specific stage in which the student is at the university determines the influence of these proximity factors on the dynamics of academic relationships. In this regard, beyond cultural and geographic proximities that only influence the first years at the university, students shape their relationships as they progress in their studies from similarities in more strategic aspects such as academic and personal closeness. These results may have significant implications for both academic research and university policies.

Relationship Between Gas Emissions and Dry Matter Intake in Mature Angus Cows

2021 ◽  
Vol 99 (Supplement_2) ◽  
pp. 32-33
Author(s):  
Amanda Holder ◽  
Megan A Gross ◽  
Alexi Moehlenpah ◽  
Paul Beck
Keyword(s):  
Dry Matter ◽  
Significant Positive Correlation ◽  
Crossover Design ◽  
Dry Matter Intake ◽  
Data Set ◽  
Gas Emissions ◽  
Positive Correlation ◽  
Wide Range ◽  
Carbon Dioxide Co2 ◽  
Second Period

Abstract The objective of this study was to examine the effects of diet quality on greenhouse gas emissions and dry matter intake (DMI). We used 42 mature, gestating Angus cows (600±69 kg; and BSC 5.3±1.1) with a wide range in DMI EPD (-1.36 to 2.29). Cows were randomly assigned to 2 diet sequences forage-concentrate (FC) or concentrate-forage(CF) determined by the diet they consumed in each period (forage or concentrate). The cows were adapted to the diet and the SmartFeed individual intake units for 14 d followed by 45 d of intake data collection for each period. Body weight was recorded on consecutive weigh days at the beginning and end of each period and then once every two wk for the duration of a period. Cows were exposed to the GreenFeed Emission Monitoring (GEM) system for no less than 9 d during each period. The GEM system was used to measure emissions of carbon dioxide (CO2) and methane (CH4). Only cows with a minimum of 20 total >3-m visits to the GEM were included in the data set. Data were analyzed in a crossover design using GLIMMIX in SASv.9.4. Within the CF sequence there was a significant, positive correlation between TMR DMI and CH4 (r=0.81) and TMR DMI and CO2 (r=0.69), however, gas emissions during the second period on the hay diet were not correlated with hay intake. There was a significant, positive correlation between hay DMI and CO2 (r=0.76) and hay DMI and CH4 (r=0.74) when cows first consumed forage (FC). In comparison to the CF sequence, cows on the FC sequence showed a positive correlation between CO2 and TMR DMI during the second period. There was also a significant positive correlation between hay and TMR DMI when assessed across (r=0.43) or within sequence (FC r=0.41, CF r=0.47).

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