Showing papers by "University of Oregon published in 2022"
TL;DR: In this paper , the authors used a 2DH ocean numerical model to simulate the phenomenon and compared the outputs of the numerical simulation with in-situ atmospheric pressure records and with remote satellite observations, revealing an excellent agreement in the wave arrival time between model and observations at hundreds of locations at different distances from the origin.
Abstract: On 15 January 2022, around 4:30 UTC the eruption of the Hunga-Tonga volcano, in the South Pacific Ocean, generated a violent underwater explosion. In addition to tsunami waves that affected the Pacific coasts, the eruption created atmospheric pressure disturbances that spread out in the form of Lamb waves. The associated atmospheric pressure oscillations were detected in high-frequency in-situ observations all over the globe. Here we take advantage of the similarities in the propagation and characteristics between atmospheric Lamb waves and long ocean waves and we use a 2DH ocean numerical model to simulate the phenomenon. We compare the outputs of the numerical simulation with in-situ atmospheric pressure records and with remote satellite observations. The signal in the model matches the observed atmospheric pressure perturbations and reveals an excellent agreement in the wave arrival time between model and observations at hundreds of locations at different distances from the origin.
70 citations
TL;DR: The Zebrafish Information Network (zfin.org) as mentioned in this paper is the central repository for Danio rerio genetic and genomic data, including genes, alleles, human disease models, gene expression, phenotype, and gene function.
Abstract: Abstract The Zebrafish Information Network (zfin.org) is the central repository for Danio rerio genetic and genomic data. The Zebrafish Information Network has served the zebrafish research community since 1994, expertly curating, integrating, and displaying zebrafish data. Key data types available at the Zebrafish Information Network include, but are not limited to, genes, alleles, human disease models, gene expression, phenotype, and gene function. The Zebrafish Information Network makes zebrafish research data Findable, Accessible, Interoperable, and Reusable through nomenclature, curatorial and annotation activities, web interfaces, and data downloads. Recently, the Zebrafish Information Network and 6 other model organism knowledgebases have collaborated to form the Alliance of Genome Resources, aiming to develop sustainable genome information resources that enable the use of model organisms to understand the genetic and genomic basis of human biology and disease. Here, we provide an overview of the data available at the Zebrafish Information Network including recent updates to the gene page to provide access to single-cell RNA sequencing data, links to Alliance web pages, ribbon diagrams to summarize the biological systems and Gene Ontology terms that have annotations, and data integration with the Alliance of Genome Resources.
41 citations
TL;DR: This article examined changes in depression and anxiety symptoms from before to during the first 6 months of the COVID-19 pandemic in a sample of 1,339 adolescents (9-18 years old, 59% female) from three countries.
Abstract: This study aimed to examine changes in depression and anxiety symptoms from before to during the first 6 months of the COVID-19 pandemic in a sample of 1,339 adolescents (9-18 years old, 59% female) from three countries. We also examined if age, race/ethnicity, disease burden, or strictness of government restrictions moderated change in symptoms. Data from 12 longitudinal studies (10 U.S., 1 Netherlands, 1 Peru) were combined. Linear mixed effect models showed that depression, but not anxiety, symptoms increased significantly (median increase = 28%). The most negative mental health impacts were reported by multiracial adolescents and those under 'lockdown' restrictions. Policy makers need to consider these impacts by investing in ways to support adolescents' mental health during the pandemic.
35 citations
TL;DR: A comprehensive survey of federated learning can be found in this paper , where the authors propose a functional architecture and a taxonomy of related techniques and present the distributed training, data communication, and security of FL systems.
Abstract: In recent years, data and computing resources are typically distributed in the devices of end users, various regions or organizations. Because of laws or regulations, the distributed data and computing resources cannot be directly shared among different regions or organizations for machine learning tasks. Federated learning emerges as an efficient approach to exploit distributed data and computing resources, so as to collaboratively train machine learning models, while obeying the laws and regulations and ensuring data security and data privacy. In this paper, we provide a comprehensive survey of existing works for federated learning. We propose a functional architecture of federated learning systems and a taxonomy of related techniques. Furthermore, we present the distributed training, data communication, and security of FL systems. Finally, we analyze their limitations and propose future research directions.
34 citations
TL;DR: This work proposes a novel online market mechanism, EdgeDR, to achieve cost efficiency in edge demand response programs and presents a dynamic payment mechanism for the operator to balance the tradeoff between short-term profit and long-term benefit in more practical scenarios.
Abstract: The computing frontier is moving from centralized mega datacenters towards distributed cloudlets at the network edge. We argue that cloudlets are well-suited for handling power demand response to help the grid maintain stability due to more flexible workload management attributed to their distributed nature. However, they also require computing demand response to avoid overload and maintain reliability. To this end, we propose a novel online market mechanism, EdgeDR, to achieve cost efficiency in edge demand response programs. At a high level, we observe that the cloudlet operator can dynamically switch on/off entire cloudlets to compensate for the energy reduction required by the power grid or provide enough computing resources to the edge service. We formulate a long-term social cost minimization problem and decompose it into a series of one-round procurement auctions. In each auction instance, we propose to let the cloudlet tenants bid with cost functions of their two-dimension service quality degradation tolerance, and let the cloudlet operator choose the service quality, manage the workload, and schedule the cloudlet activation status. In addition, we present a dynamic payment mechanism for the operator to balance the tradeoff between short-term profit and long-term benefit in more practical scenarios. Via rigorous analysis, we exhibit that our bidding policy is individually rational and truthful; our workload management algorithm has near-optimal performance in each auction; and our overall online algorithm achieves a provable competitive ratio. We further confirm the performance of our mechanism through extensive trace-driven simulations.
28 citations
TL;DR: In this article , the authors make a comprehensive survey of interpretability of deep neural networks and propose a taxonomy of interpretation algorithms. And they discuss the connections between deep models' interpretations and other factors, such as adversarial robustness and learning from interpretations, and introduce several open-source libraries for interpretation algorithms and evaluation approaches.
Abstract: Deep neural networks have been well-known for their superb handling of various machine learning and artificial intelligence tasks. However, due to their over-parameterized black-box nature, it is often difficult to understand the prediction results of deep models. In recent years, many interpretation tools have been proposed to explain or reveal how deep models make decisions. In this paper, we review this line of research and try to make a comprehensive survey. Specifically, we first introduce and clarify two basic concepts—interpretations and interpretability—that people usually get confused about. To address the research efforts in interpretations, we elaborate the designs of a number of interpretation algorithms, from different perspectives, by proposing a new taxonomy. Then, to understand the interpretation results, we also survey the performance metrics for evaluating interpretation algorithms. Further, we summarize the current works in evaluating models’ interpretability using “trustworthy” interpretation algorithms. Finally, we review and discuss the connections between deep models’ interpretations and other factors, such as adversarial robustness and learning from interpretations, and we introduce several open-source libraries for interpretation algorithms and evaluation approaches.
26 citations
TL;DR: In this article , a carbon-hosted sulfur cathode was designed to provide fully accessible channels for sodium ions with unobstructed channels during cycling, particularly for high sulfur content in Li-S and Na-S batteries.
Abstract: Porous carbon has been widely used as an efficient host to encapsulate highly active molecular sulfur (S) in Li–S and Na–S batteries. However, for these sub-nanosized pores, it is a challenge to provide fully accessible sodium ions with unobstructed channels during cycling, particularly for high sulfur content. It is well recognized that solid interphase with full coverage over the designed architectures plays critical roles in promoting rapid charge transfer and stable conversion reactions in batteries, whereas constructing a high-ionic-conductivity solid interphase in the pores is very difficult. Herein, unique continuous carbonaceous pores are tailored, which can serve as multifunctional channels to encapsulate highly active S and provide fully accessible pathways for sodium ions. Solid sodium sulfide interphase layers are also realized in the channels, showing high Na-ion conductivity toward stabilizing the redox kinetics of the S cathode during charge/discharge processes. This systematically designed carbon-hosted sulfur cathode delivers superior cycling performance (420 mAh g−1 at 2 A g−1 after 2000 cycles), high capacity retention of ≈90% over 500 cycles at current density of 0.5 A g−1, and outstanding rate capability (470 mAh g−1 at 5 A g−1) for room-temperature sodium–sulfur batteries.
26 citations
TL;DR: This article constructed a sample of over 200,000 supply chains between 2003 and 2018 to conduct a chain-based analysis of trade credit and found that firms in more central or more profitable chains provide more net trade credit.
19 citations
01 Aug 2022
TL;DR: In this paper , a novel neural network sandwich structure with an improved attention mechanism is inserted into the double-layer bidirectional long short-term memory network shortened as A-DBLSTM.
Abstract: For power generation management and power system dispatching, it is of big significance to predict the consumption of electric energy accurately. For the sake of improving the prediction accuracy of power consumption, taking the complex features of time series data into consideration, a novel neural network sandwich structure with an improved attention mechanism is inserted into the double-layer bidirectional long short-term memory network shortened as A-DBLSTM is put forward in this article. In A-DBLSTM, compared with traditional attention mechanism, the presented attention mechanism focuses on different features in each time unit and the A-DBLLSTM network extracts time information in sequence. The parameter optimization of A-DBLSTM is based on the method of particle swarm optimization (PSO). For confirming the effectiveness and feasibility of A-DBLSTM, case studies using two datasets of the hourly temperature values and power loads between 2012 and 2014 and the electric energy consumption are carried out. The experimental results indicate that the presented A-DBLSTM with the novel sandwich network structure achieves superior performance in the aspects of the mean square error, root mean square, the average absolute error and the mean absolute percentage error to other advanced methods. What is more, the factors that have the greatest impact on the prediction performance can be found through analyzing the heatmap of the attention layer.
16 citations
TL;DR: In this article , the authors describe spectroscopic studies of model ss-dsDNA fork constructs that contain dimers of "internally labeled" cyanine (iCy3) chromophore probes that have been rigidly inserted within the sugar-phosphate backbones of the DNA strands.
Abstract: DNA replication and the related processes of genome expression require binding, assembly, and function of protein complexes at and near single-stranded (ss)-double-stranded (ds) DNA junctions. These central protein-DNA interactions are likely influenced by thermally induced conformational fluctuations of the DNA scaffold across an unknown distribution of functionally relevant states to provide regulatory proteins access to properly conformed DNA binding sites. Thus, characterizing the nature of conformational fluctuations and the associated structural disorder at ss-dsDNA junctions is critical for understanding the molecular mechanisms of these central biological processes. Here, we describe spectroscopic studies of model ss-dsDNA fork constructs that contain dimers of "internally labeled" cyanine (iCy3) chromophore probes that have been rigidly inserted within the sugar-phosphate backbones of the DNA strands. Our combined analyses of absorbance, circular dichroism, and two-dimensional fluorescence spectroscopy permit us to characterize the local conformational parameters and conformational distributions. We find that the DNA sugar-phosphate backbones undergo abrupt successive changes in their local conformations-initially from a right-handed and ordered DNA state to a disordered splayed-open structure and then to a disordered left-handed conformation-as the dimer probes are moved across the ss-dsDNA junction. Our results suggest that the sugar-phosphate backbones at and near ss-dsDNA junctions adopt specific position-dependent local conformations and exhibit varying extents of conformational disorder that deviate widely from the Watson-Crick structure. We suggest that some of these conformations can function as secondary-structure motifs for interaction with protein complexes that bind to and assemble at these sites.
14 citations
TL;DR: In this article, a model for surface deformation linked to the evolution of a subvolcanic chamber was presented, showing that the magnitude of surface velocities associated with crystallization and second boiling should not exceed ∼1 mm/yr unless the cooling rate is substantially elevated above normal conductive cooling rates.
TL;DR: In this article , the authors argue for the value of locally relevant measures, such as poverty, mental health, food insecurity, and type 2 diabetes, to assess the assessment of a potential syndemic from a locally grounded perspective.
Abstract: Syndemics theory has provided insight into the ways that disease states and social adversity interact in marginalized populations to further disempower these groups. Yet, until recently, scholars have not identified how we might actually recognize and measure a syndemic, as opposed to a situation where there are multiple but non-interacting diseases present in a population. As researchers like those included in this special issue develop new methods for assessing syndemic interactions in diverse global populations, this short communication argues for the value of locally relevant measures. Poverty, mental health, food insecurity, and type 2 diabetes are used to illustrate the assessment of a potential syndemic from a locally grounded perspective. The discussion emphasizes the insights locally adapted measures can add and what information would be lost without their use.
TL;DR: In this paper , a high performance catalyst for removing VOCs is presented using an efficient confinement effect coupled with an electron modifier approach, where the Pt nanoparticles are confined in TiO2 nanotubes (TNT) by surface oxygen vacancy towards the catalytic combustion of ethylene.
TL;DR: The authors of the PHREEQC program clearly stated that the choice of thermodynamic data files (TDFs) is the responsibility of the user as mentioned in this paper , and the TDFs are distributed along with the software release without detailed documentation or critical evaluation.
TL;DR: In this article, Wang et al. reported laboratory measurements of the size distribution of lofted dust particles in the range of 1 to 40 µm in diameter, which is in agreement with the theoretical expectation derived from the patched charge model (Wang et al., 2016a).
TL;DR: The authors reviewed the available evidence on DoS from the inception of the construct until July 31, 2020 and found that there is ample support for DoS as a predictor of psychological health and marital quality, and that there are positive associations between DoS and better physical health and intergenerational relationships.
TL;DR: In this article , a single-unit electrophysiology in V1 of freely moving mice while simultaneously measuring the mouse's eye position, head orientation, and the visual scene from the view of a fixed camera was performed.
TL;DR: In this paper , the authors investigated how the enteric nervous system shapes the intestinal environment in the absence of microbiota and associated inflammatory responses, and concluded that a primary function of the ENS is to regulate luminal pH which plays a critical role in shaping the resident microbial community and regulating intestinal inflammation.
Abstract: The enteric nervous system (ENS) controls many aspects of intestinal homeostasis, including parameters that shape the habitat of microbial residents. Previously we showed that zebrafish lacking an ENS, due to deficiency of the sox10 gene, develop intestinal inflammation and bacterial dysbiosis, with an expansion of proinflammatory Vibrio strains. To understand the primary defects resulting in dysbiosis in sox10 mutants, we investigated how the ENS shapes the intestinal environment in the absence of microbiota and associated inflammatory responses. We found that intestinal transit, intestinal permeability, and luminal pH regulation are all aberrant in sox10 mutants, independent of microbially induced inflammation. Treatment with the proton pump inhibitor, omeprazole, corrected the more acidic luminal pH of sox10 mutants to wild type levels. Omeprazole treatment also prevented overabundance of Vibrio and ameliorated inflammation in sox10 mutant intestines. Treatment with the carbonic anhydrase inhibitor, acetazolamide, caused wild type luminal pH to become more acidic, and increased both Vibrio abundance and intestinal inflammation. We conclude that a primary function of the ENS is to regulate luminal pH, which plays a critical role in shaping the resident microbial community and regulating intestinal inflammation.
TL;DR: In this article , the molecular profiles of pediatric thyroid cancer, both primary and RT-induced, remains poorly defined compared with adults and data on pediatric follicular thyroid carcinoma (FTC) are virtually nonexistent.
Abstract: Background: Childhood cancer survivors and bone marrow transplant recipients treated with radiation therapy (RT) are at increased risk for subsequent thyroid cancer. However, the genetic landscape of pediatric thyroid cancer, both primary and RT-induced, remains poorly defined, as pediatric papillary thyroid carcinoma (PTC) has been understudied compared with adults and data on pediatric follicular thyroid carcinoma (FTC) are virtually nonexistent. The objective of this study was to characterize and compare the molecular profiles of pediatric RT-induced PTC and FTC cases with primary pediatric thyroid cancers. Methods: A total of 41 differentiated thyroid carcinomas (11 RT cases and 30 primary cases) from 37 patients seen at Phoenix Children's Hospital between January 1, 2010 and December 31, 2019 were evaluated by targeted next-generation sequencing and/or BRAF immunohistochemistry. Results: Eighty-six percent (6/7) of RT-PTC harbored a gene fusion (GF) compared with 56% (14/25) of primary PTC; 14% (1/7) of RT-PTC had a single-nucleotide variant (SNV; specifically, a point mutation in the DICER1 gene) compared with 44% (11/25) of primary PTC (all of the latter had the BRAFV600E mutation). An exceedingly rare ROS1 fusion was identified in a child with RT-PTC. With respect to FTC, copy number alterations (CNAs) were seen in 75% (3/4) of RT cases compared with 40% (2/5) of primary cases. None of the RT-FTC had SNVs compared with 100% (5/5) of primary FTC. Conclusions: In children, the molecular profile of subsequent RT-induced thyroid cancers appears to differ from primary (sporadic and syndromic) cases, with a high prevalence of GFs in RT-PTC (similar to PTC occurring after the Chernobyl nuclear reactor accident) and CNAs in RT-FTC. A better understanding of the molecular mechanisms underlying these cancers may lead to more accurate diagnosis, prognosis, and treatment, as some of the genomic alterations are potentially targetable.
TL;DR: The power of numeric self-efficacy (confidence) has been little considered in MDM, but many medical decisions and behaviors require persistence to be successful over time (e.g., comprehension, medical-recommendation adherence) as discussed by the authors .
Abstract: Objective numeracy appears to support better medical decisions and health outcomes. The more numerate generally understand and use numbers more and make better medical decisions, including more informed medical choices. Numeric self-efficacy-an aspect of subjective numeracy that is also known as numeric confidence-also relates to decision making via emotional reactions to and inferences from experienced difficulty with numbers and via persistence linked with numeric comprehension and healthier behaviors over time. Furthermore, it moderates the effects of objective numeracy on medical outcomes.We briefly review the numeracy and decision-making literature and then summarize more recent literature on 3 separable effects of numeric self-efficacy. Although dual-process theories can account for the generally superior decision making of the highly numerate, they have neglected effects of numeric self-efficacy. We discuss implications for medical decision-making (MDM) research and practice. Finally, we propose a modification to dual-process theories, adding a "motivational mind" to integrate the effects of numeric self-efficacy on decision-making processes (i.e., inferences from experienced difficulty with numbers, greater persistence, and greater use of objective-numeracy skills) important to high-quality MDM.The power of numeric self-efficacy (confidence) has been little considered in MDM, but many medical decisions and behaviors require persistence to be successful over time (e.g., comprehension, medical-recommendation adherence). Including numeric self-efficacy in research and theorizing will increase understanding of MDM and promote development of better decision interventions.Research demonstrates that objective numeracy supports better medical decisions and health outcomes.The power of numeric self-efficacy (aka numeric confidence) has been little considered but appears critical to emotional reactions and inferences that patients and others make when encountering numeric information (e.g., in decision aids) and to greater persistence in medical decision-making tasks involving numbers.The present article proposes a novel modification to dual-process theory to account for newer findings and to describe how numeracy mechanisms can be better understood.Because being able to adapt interventions to improve medical decisions depends in part on having a good theory, future research should incorporate numeric self-efficacy into medical decision-making theories and interventions.
TL;DR: In this paper, the authors consider how prosocial processes potentially stimulated by perspective-taking can be derailed in such contexts and identify methodological limitations in current psychological evidence for a causal link between perspective taking and prosocial outcomes.
Abstract: The path from perspective-taking to prosocial behavior is not as straightforward or robust as it is often assumed to be. In some contexts, imagining the viewpoint of other person leads the perspective taker to thoughts about how that person might have negative thoughts or intentions toward them. It can also prompt other kinds of counter-productive egocentric projection. In this review, we consider how prosocial processes potentially stimulated by perspective-taking can be derailed in such contexts. We also identify methodological limitations in current (social-) psychological evidence for a causal link between perspective-taking and prosocial outcomes. Increased appreciation of factors moderating the path from perspective-taking to prosocial behavior can enhance the explanatory power of perspective-taking as social cognitive process.
TL;DR: In this paper , the authors present new archaeobotanical and radiocarbon data from combustion features within stratified cultural components at Connley Caves, Oregon, that reaffirm the inclusion of plants in the diet of Paleoindian groups.
Abstract: Paleoethnobotanical perspectives are essential for understanding past lifeways yet continue to be underrepresented in Paleoindian research. We present new archaeobotanical and radiocarbon data from combustion features within stratified cultural components at Connley Caves, Oregon, that reaffirm the inclusion of plants in the diet of Paleoindian groups. Botanical remains from three features in Connley Cave 5 show that people foraged for diverse dryland taxa and a narrow range of wetland plants during the summer and fall months. These data add new taxa to the known Pleistocene food economy and support the idea that groups equipped with Western Stemmed Tradition toolkits had broad, flexible diets. When viewed continentally, this work contributes to a growing body of research indicating that regionally adapted subsistence strategies were in place by at least the Younger Dryas and that some foragers in the Far West may have incorporated a wider range of plants including small seeds, leafy greens, fruits, cacti, and geophytes into their diet earlier than did Paleoindian groups elsewhere in North America. The increasing appearance of diverse and seemingly low-ranked resources in the emerging Paleoindian plant-food economy suggests the need to explore a variety of nutritional variables to explain certain aspects of early foraging behavior.
TL;DR: In this paper , a workflow to analyze (±)-Verapamil and its metabolites using differential mobility spectrometry (DMS) was developed, where the ionogram of protonated Verapamils consisted of two peaks.
Abstract: Upon development of a workflow to analyze (±)-Verapamil and its metabolites using differential mobility spectrometry (DMS), we noticed that the ionogram of protonated Verapamil consisted of two peaks. This was inconsistent with its metabolites, as each exhibited only a single peak in the respective ionograms. The unique behaviour of Verapamil was attributed to protonation at its tertiary amino moiety, which generated a stereogenic quaternary amine. The introduction of additional chirality upon N-protonation of Verapamil renders four possible stereochemical configurations for the protonated ion: (R,R), (S,S), (R,S), or (S,R). The (R,R)/(S,S) and (R,S)/(S,R) enantiomeric pairs are diastereomeric and thus exhibit unique conformations that are resolvable by linear and differential ion mobility techniques. Protonation-induced chirality appears to be a general phenomenon, as N-protonation of 12 additional chiral amines generated diastereomers that were readily resolved by DMS.
01 Feb 2022
TL;DR: In this paper , the mechanism of micro-fragmented adipose tissue (MF) on Osteoarthritis (OA) patients was investigated by co-culturing with miR-92a-3p and TNF-α.
Abstract: Apart from the treatment potential of micro-fragmented adipose tissue (MF) in joint diseases, what's less clear is the mechanism of MF on Osteoarthritis (OA). Synoviocytes isolated from synovium tissues of 11 knee joint OA patients were identified and co-cultured with MF collected by Lipogems®. Cytokines and mRNA levels in synoviocytes were detected by enzyme-linked immunosorbent assay (ELISA) and quantitative reverse transcription polymerase chain reaction (qRT-PCR). Cell viability, apoptosis and apoptosis-related protein expression of Tumor Necrosis Factor-α (TNF-α)-activated synoviocytes were detected by cell counting kit-8, flow cytometry and western blot, respectively. The rescue experiments were conducted to verify the causal relationship of MF and miR-92a-3p. The relationship between miR-92a-3p and KLHL29 was verified by bioinformatics analysis, qRT-PCR, dual-luciferase reporter assay and western blot. OA synoviocytes were composed of synovial fibroblasts and synovial macrophages. After co-cultivation of synoviocytes and TNF-α, the levels of Interleukin (IL)-8 and hyaluronic acid (HA) appeared a few changes, and those of chemotactic cytokine ligand (CCL) 2, CCL3, CCL5 and matrix metalloproteinases (MMP)-9 were downregulated, while the levels of Tissue Inhibitor of Metalloproteinases (TIMP)-1, IL-10 and Prostaglandin E2 (PGE2) were up-regulated. Co-culture of MF and activated synoviocytes reversed the above-mentioned effects regulated by TNF-α and reduced the mRNA levels of inflammatory factors. However, miR-92a-3p inhibitor overturned the reversal. KLHL29 was the target gene of miR-92a-3p and its expression was suppressed in activated synoviocytes co-cultured with MF, which was reversed by down-regulated miR-92a-3p. Collectively, MF regulated the biological functions of OA synoviocytes by upregulating miR-92a-3p expression.
TL;DR: In this paper , a review of the existing behavioral and neurophysiological evidence for these sources of temporal variability in naturalistic behavior is provided, highlighting the crucial role played by structural heterogeneities as well as noise from mesoscopic feedback loops in regulating flexible behavior.
Abstract: Naturalistic animal behavior exhibits a strikingly complex organization in the temporal domain, with variability arising from at least three sources: hierarchical, contextual, and stochastic. What neural mechanisms and computational principles underlie such intricate temporal features? In this review, we provide a critical assessment of the existing behavioral and neurophysiological evidence for these sources of temporal variability in naturalistic behavior. Recent research converges on an emergent mechanistic theory of temporal variability based on attractor neural networks and metastable dynamics, arising via coordinated interactions between mesoscopic neural circuits. We highlight the crucial role played by structural heterogeneities as well as noise from mesoscopic feedback loops in regulating flexible behavior. We assess the shortcomings and missing links in the current theoretical and experimental literature and propose new directions of investigation to fill these gaps.
TL;DR: In this paper , the authors evaluated the extent of this challenge for plastic surgery trainees and identified potential solutions to improve the research productivity of female and ethnically underrepresented medical trainees.
Abstract: Background: Lack of female and ethnically underrepresented in medicine (UIM) surgeons remains concerning in academic plastic surgery. One barrier to inclusion may be unequal opportunity to publish research. This study evaluates the extent of this challenge for plastic surgery trainees and identifies potential solutions. Methods: Data were collected on academic plastic surgeons' research productivity during training. Bivariate analysis compared publication measures between genders and race/ethnicities at different training stages (pre-residency/residency/clinical fellowship). Multivariate analysis determined training experiences independently associated with increased research productivity. Results: Overall, women had fewer total publications than men during training (8.89 versus 12.46, P = 0.0394). Total publications were similar between genders before and during residency (P > 0.05 for both) but lower for women during fellowship (1.32 versus 2.48, P = 0.0042). Women had a similar number of first-author publications during training (3.97 versus 5.24, P = 0.1030) but fewer middle-author publications (4.70 versus 6.81, P = 0.0405). UIM and non-UIM individuals had similar productivity at all training stages and authorship positions (P > 0.05 for all). Research fellowship completion was associated with increased total, first-, and middle-author training publications (P < 0.001 for all). Conclusions: Less research productivity for female plastic surgery trainees may reflect a disparity in opportunity to publish. Fewer middle-author publications could indicate challenges with network-building in a predominately male field. Despite comparable research productivity during training relative to non- UIM individuals, UIM individuals remain underrepresented in academic plastic surgery. Creating research fellowships for targeting underrepresented groups could help overcome these challenges.
TL;DR: This work presents a novel parallel algorithmic framework for updating the Single Source Shortest Path in large-scale dynamic networks and implements it on the shared-memory and GPU platforms.
Abstract: The Single Source Shortest Path (SSSP) problem is a classic graph theory problem that arises frequently in various practical scenarios; hence, many parallel algorithms have been developed to solve it. However, these algorithms operate on static graphs, whereas many real-world problems are best modeled as dynamic networks, where the structure of the network changes with time. This gap between the dynamic graph modeling and the assumed static graph model in the conventional SSSP algorithms motivates this work. We present a novel parallel algorithmic framework for updating the SSSP in large-scale dynamic networks and implement it on the shared-memory and GPU platforms. The basic idea is to identify the portion of the network affected by the changes and update the information in a rooted tree data structure that stores the edges of the network that are most relevant to the analysis. Extensive experimental evaluations on real-world and synthetic networks demonstrate that our proposed parallel updating algorithm is scalable and, in most cases, requires significantly less execution time than the state-of-the-art recomputing-from-scratch algorithms.
TL;DR: In this paper , the authors investigated the effect of 10-wt% Acetyl triethyl citrate (ATEC) on the glass transition temperature of poly(lactic-co-glycolic acid) (PLGA) and showed that the initial changes to the PLGA direct-writing outcomes seen in the first 3.5 h are temporary and that longer times result in a more stable MEW process.
Abstract: Polymers sensitive to thermal degradation include poly(lactic-co-glycolic acid) (PLGA), which is not yet processed via melt electrowriting (MEW). After an initial period of instability where mean fiber diameters increase from 20.56 to 27.37 µm in 3.5 h, processing stabilizes through to 24 h. The jet speed, determined using critical translation speed measurements, also reduces slightly in this 3.5 h period from 500 to 433 mm min−1 but generally remains constant. Acetyl triethyl citrate (ATEC) as an additive decreases the glass transition temperature of PLGA from 49 to 4 °C, and the printed ATEC/PLGA fibers exhibits elastomeric behavior upon handling. Fiber bundles tested in cyclic mechanical testing display increased elasticity with increasing ATEC concentration. The processing temperature of PLGA also reduces from 165 to 143 °C with increase in ATEC concentration. This initial window of unstable direct writing seen with neat PLGA can also be impacted through the addition of 10-wt% ATEC, producing fiber diameters of 14.13 ± 1.69 µm for the first 3.5 h of heating. The investigation shows that the initial changes to the PLGA direct-writing outcomes seen in the first 3.5 h are temporary and that longer times result in a more stable MEW process.
TL;DR: In this article , the authors identify Local Group (LG) analogs in the IllustrisTNG cosmological simulation, and use these to study two mass estimators for the LG: one based on the timing argument (TA) and another based on virial theorem (VT).
Abstract: We identify Local Group (LG) analogs in the IllustrisTNG cosmological simulation, and use these to study two mass estimators for the LG: one based on the timing argument (TA) and one based on the virial theorem (VT). Including updated measurements of the Milky Way-M31 tangential velocity and the cosmological constant, we show that the TA mass estimator slightly overestimates the true median LG-mass, though the ratio of the TA to the true mass is consistent at the approximate 90\% c.l. These are in broad agreement with previous results using dark matter-only simulations. We show that the VT estimator better estimates the true LG-mass, though there is a larger scatter in the virial mass to true mass ratio relative to the corresponding ratio for the TA. We attribute the broader scatter in the VT estimator to several factors, including the predominantly radial orbits for LG satellite galaxies, which differs from the VT assumption of isotropic orbits. With the systematic uncertainties we derive, the updated measurements of the LG mass at 90\% c.l. are $4.75_{-2.41}^{+2.22} \times 10^{12}$ M$_\odot$ from the TA and $2.0_{-1.5}^{+2.1} \times 10^{12}$ M$_\odot$ from the VT. We consider the LMC's effect on the TA and VT LG mass estimates, and do not find exact LMC-MW-M31 analogues in the Illustris simulations. However, in LG simulations with satellite companions as massive as the LMC we find that the effect on the TA and VT estimators is small, though we need further studies on a larger sample of LMC-MW-M31 systems to confirm these results.
TL;DR: Men with patent foramen ovale (PFO) have a greater tendency to develop symptoms of acute mountain sickness and high-altitude pulmonary oedema upon ascent to high altitude, and PFO presence is associated with worse cardiopulmonary function in chronic mountain sickness as discussed by the authors .
Abstract: The foramen ovale is an essential component of the fetal circulation contributing to oxygenation and carbon dioxide elimination that remains patent under certain circumstances in ∼30% of the healthy adult population, without major negative sequelae in most. Adults with a patent foramen ovale (PFO) have a greater tendency to develop symptoms of acute mountain sickness and high-altitude pulmonary oedema upon ascent to high altitude, and PFO presence is associated with worse cardiopulmonary function in chronic mountain sickness. This increase in altitude illness prevalence may be related to dysregulated cerebral blood flow associated with altered respiratory chemoreflex sensitivity; however, the mechanisms remain to be elucidated. Interestingly, men with a PFO appear to have a shift in thermoregulatory control to higher internal temperatures, both at rest and during exercise, and they have blunted thermal hyperpnoea. The teleological 'reason' for this thermoregulatory shift is unclear, but the shift of ∼0.5°C in core body temperature does not appear to be sufficient to have any significant negative consequences in terms of risk of heat illness. Further work in this area is needed, particularly in women, to evaluate mechanisms of heat storage and dissipation in these individuals compared to people without a PFO. Consequences of a PFO in SCUBA divers include a greater incidence of unprovoked decompression sickness, but whether PFO is beneficial or detrimental to breath hold diving remains unexplored. Whether PFO presence will explain interindividual variability in responses to, and consequences from, other environmental stressors such as spaceflight remain entirely unknown.