The Magic of Slow-to-Fast and Constant: Evaluating Time Perception of Progress Bars by Bayesian Model

Objective: We aimed to use adaptive psychophysics methods, which is a Bayesian Model, to measure users' time perception of various progress bar quantitatively. Background: Progress bar informs users about the status of ongoing processes. Progress bars frequently display nonuniform speed patterns, such as acceleration and deceleration. However, which progress bar is perceived faster remain unclear. Methods: We measured the point of subject equality (PSE) of the constant progress bar toward four different 5-second progress bars with a non-constant speed. To measure PSE, in each trial, a constant progress bar and a non-constant progress bar were presented to participants. Participants needed to judge which one is shorter. Based on their choice, the model generated the time duration of constant progress bar in next trial. After 40 trials for each non-constant progress bar, the PSE was calculated by the model. Eye tracking was recorded during the experiment.Results: Our results show that the constant progress bar and speed-up progress bar are perceived to be faster. The anchoring effect fits the results of our study, indicating that the final part of the progress bar is more important for time perception. Moreover, the eye-tracking results indicate that the progress bar is perceived to be slower is related to the overload of cognitive resources.Conclusion: The constant progress bar and speed-up progress bar are perceived as the quickest. Application: The results suggest that UX design can use constant or speed-up progress bar, in order to improve user experience in waiting

Quantum control via a genetic algorithm of the field ionization pathway of a Rydberg electron

Quantum control of the pathway along which a Rydberg electron field ionizes is experimentally and computationally demonstrated. Selective field ionization is typically done with a slowly rising electric field pulse. The $(1/n^*)^4$ scaling of the classical ionization threshold leads to a rough mapping between arrival time of the electron signal and principal quantum number of the Rydberg electron. This is complicated by the many avoided level crossings that the electron must traverse on the way to ionization, which in general leads to broadening of the time-resolved field ionization signal. In order to control the ionization pathway, thus directing the signal to the desired arrival time, a perturbing electric field produced by an arbitrary waveform generator is added to a slowly rising electric field. A genetic algorithm evolves the perturbing field in an effort to achieve the target time-resolved field ionization signal.Comment: Corrected minor typographic errors and changed the titl

Understanding Public Online Donations on Social Media during the Pandemic: A Social Presence Theory Perspective

The COVID-19 pandemic has had a huge impact on the global economy and health care, but online donations from the public on social media have increased significantly. However, the role of social presence in motivating people to donate online during the pandemic has been largely unexplored. This study examines the relationship between social presence on social media and online donation behavior during the pandemic using social presence theory. We explore the interplay between social presence, perceived threat, social properties of social media, and donation intentions. The results showed that social presence based on social media, perception of others and social interaction significantly affected social media online donation participation, and the perceived threat of COVID-19 significantly moderated online donation participation. Our research contributes to the understanding of online donation behavior during a pandemic crisis and provides insights into how social media can be leveraged for effective donation campaigns

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Plants are exposed to increasingly severe drought events and roots play vital roles in maintaining plant survival, growth, and reproduction. A large body of literature has investigated the adaptive responses of root traits in various plants to water stress and these studies have been reviewed in certain groups of plant species at a certain scale. Nevertheless, these responses have not been synthesized at multiple levels. This paper screened over 2000 literatures for studies of typical root traits including root growth angle, root depth, root length, root diameter, root dry weight, root-to-shoot ratio, root hair length and density and integrates their drought responses at genetic and morphological scales. The genes, quantitative trait loci (QTLs) and hormones that are involved in the regulation of drought response of the root traits were summarized. We then statistically analyzed the drought responses of root traits and discussed the underlying mechanisms. Moreover, we highlighted the drought response of 1-D and 2-D root length density (RLD) distribution in the soil profile. This paper will provide a framework for an integrated understanding of root adaptive responses to water deficit at multiple scales and such insights may provide a basis for selection and breeding of drought tolerant crop lines

High throughput Single-cell Cultivation on Microfluidic Streak Plates

This paper describes the microfluidic streak plate (MSP), a facile method for high-throughput microbial cell separation and cultivation in nanoliter sessile droplets. The MSP method builds upon the conventional streak plate technique by using microfluidic devices to generate nanoliter droplets that can be streaked manually or robotically onto petri dishes prefilled with carrier oil for cultivation of single cells. In addition, chemical gradients could be encoded in the droplet array for comprehensive dose-response analysis. The MSP method was validated by using single-cell isolation of Escherichia coli and antimicrobial susceptibility testing of Pseudomonas aeruginosa PAO1. The robustness of the MSP work flow was demonstrated by cultivating a soil community that degrades polycyclic aromatic hydrocarbons. Cultivation in droplets enabled detection of the richest species diversity with better coverage of rare species. Moreover, isolation and cultivation of bacterial strains by MSP led to the discovery of several species with high degradation efficiency, including four Mycobacterium isolates and a previously unknown fluoranthene-degrading Blastococcus species

Global study of anti-NMDA encephalitis: a bibliometric analysis from 2005 to 2023

BackgroundAutoimmune diseases have always been one of the difficult diseases of clinical concern. Because of the diversity and complexity of its causative factors, unclear occurrence and development process and difficult treatment, it has become a key disease for researchers to study. And the disease explored in this paper, anti-NMDA encephalitis, belongs to a common type of autoimmune encephalitis. However, the quality of articles and research hotspots in this field are not yet known. Therefore, in this field, we completed a bibliometric and visualization analysis from 2005 to 2023 in order to understand the research hotspots and directions of development in this field.Materials and methodsWe searched the SCI-expanded databases using Web of Science’s core databases on January 22, 2024 and used tools such as VOS viewer, Cite Space, and R software to visualize and analyze the authors, countries, journals, institutions, and keywords of the articles.ResultsA total of 1,161 literatures were retrieved and analyzed in this study. China was the country with the most total publications, and USA and Spain were the most influential countries in the field of anti-NMDA encephalitis. University of Pennsylvania from USA was the institution with the highest number of publications. While Dalmau Josep is the most prolific, influential and contributing author who published one of the most cited articles in Lancet Neurology, which laid the foundation for anti-NMDA encephalitis research, the top three appearances of keyword analysis were: “antibodies”, “diagnosis”, and “autoimmune encephalitis.”ConclusionBibliometric analysis shows that the number of studies on anti-NMDA encephalitis is generally increasing year by year, and it is a hot disease pursued by researchers. USA and Spain are leading in the field of anti-NMDA encephalitis, while China should continue to improve the quality of its own research. The suspected causes of anti-NMDA encephalitis other than ovarian teratoma and herpes simplex, the specific clinical manifestations that are not masked by psychiatric symptoms, the diagnostic modalities that are faster and more accurate than antibody tests, and the improvement of treatment modalities by evaluating prognosis of various types of patients are the hotspots for future research

Individual-based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder

Individual-based morphological brain networks built from T1-weighted magnetic resonance imaging (MRI) reflect synchronous maturation intensities between anatomical regions at the individual level. Autism spectrum disorder (ASD) is a socio-cognitive and neurodevelopmental disorder with high neuroanatomical heterogeneity, but the specific patterns of morphological networks in ASD remain largely unexplored at the individual level. In this study, individual-based morphological networks were constructed by using high-resolution structural MRI data from 40 young children with ASD (age range: 2-8 years) and 38 age-, gender-, and handedness-matched typically developing children (TDC). Measurements were recorded as threefold. Results showed that compared with TDC, young children with ASD exhibited lower values of small-worldness (i.e., sigma) of individual-level morphological brain networks, increased morphological connectivity in cortico-striatum-thalamic-cortical (CSTC) circuitry, and decreased morphological connectivity in the cortico-cortical network. In addition, morphological connectivity abnormalities can predict the severity of social communication deficits in young children with ASD, thus confirming an associational impact at the behavioral level. These findings suggest that the morphological brain network in the autistic developmental brain is inefficient in segregating and distributing information. The results also highlight the crucial role of abnormal morphological connectivity patterns in the socio-cognitive deficits of ASD and support the possible use of the aberrant developmental patterns of morphological brain networks in revealing new clinically-relevant biomarkers for ASD.China Postdoctoral Science Foundation, Grant/Award Number: 2019M660236; National Natural Science Foundation of China, Grant/Award Numbers: 61901129, 62036003, 81871432, U1808204; The Basque Foundation for Science and from Ministerio de Economia, Industria y Competitividad (Spain) and FEDER, Grant/Award Number: DPI2016-79874-R; the Fundamental Research Funds for the Central Universities, Grant/Award Numbers: 2672018ZYGX2018J079, ZYGX2019Z017; the Sichuan Science and Technology Program, Grant/Award Number: 2019YJ018

Response of seasonal soil freeze depth to climate change across China

Abstract. The response of seasonal soil freeze depth to climate change has repercussions for the surface energy and water balance, ecosystems, the carbon cycle, and soil nutrient exchange. Despite its importance, the response of soil freeze depth to climate change is largely unknown. This study employs the Stefan solution and observations from 845 meteorological stations to investigate the response of variations in soil freeze depth to climate change across China. Observations include daily air temperatures, daily soil temperatures at various depths, mean monthly gridded air temperatures, and the normalized difference vegetation index. Results show that soil freeze depth decreased significantly at a rate of −0.18 ± 0.03 cm yr−1, resulting in a net decrease of 8.05 ± 1.5 cm over 1967–2012 across China. On the regional scale, soil freeze depth decreases varied between 0.0 and 0.4 cm yr−1 in most parts of China during 1950–2009. By investigating potential climatic and environmental driving factors of soil freeze depth variability, we find that mean annual air temperature and ground surface temperature, air thawing index, ground surface thawing index, and vegetation growth are all negatively associated with soil freeze depth. Changes in snow depth are not correlated with soil freeze depth. Air and ground surface freezing indices are positively correlated with soil freeze depth. Comparing these potential driving factors of soil freeze depth, we find that freezing index and vegetation growth are more strongly correlated with soil freeze depth, while snow depth is not significant. We conclude that air temperature increases are responsible for the decrease in seasonal freeze depth. These results are important for understanding the soil freeze–thaw dynamics and the impacts of soil freeze depth on ecosystem and hydrological process. </jats:p

REG1A and RUNX3 Are Potential Biomarkers for Predicting the Risk of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Clinical features are traditionally used to predict DKD, yet with low diagnostic efficacy. Most of the recent biomarkers used to predict DKD are based on transcriptomics and metabolomics; however, they also should be used in combination with many other predictive indicators. The purpose of this study was thus to identify a simplified class of blood biomarkers capable of predicting the risk of developing DKD. The Gene Expression Omnibus database was screened for DKD biomarkers, and differentially expressed genes (DEGs) in human blood and kidney were identified via gene expression analysis and the Least Absolute Shrinkage and Selection Operator regression. A comparison of the area under the curve (AUC) profiles on multiple receiver operating characteristic curves of the DEGs in DKD and other renal diseases revealed that REG1A and RUNX3 had the highest specificity for DKD diagnosis. The AUCs of the combined expression of REG1A and RUNX3 in kidney (AUC = 0.929) and blood samples (AUC = 0.917) of DKD patients were similar to each other. The AUC of blood samples from DKD patients and healthy individuals obtained for external validation further demonstrated that REG1A combined with RUNX3 had significant diagnostic efficacy (AUC=0.948). REG1A and RUNX3 expression levels were found to be positively and negatively correlated with urinary albumin creatinine ratio and estimated glomerular filtration rate, respectively. Kaplan-Meier curves also revealed the potential of REG1A and RUNX3 for predicting the risk of DKD. In conclusion, REG1A and RUNX3 may serve as biomarkers for predicting the risk of developing DKD