Miracle-dz/UniFAR-FTUs huggingface dataset:
MADS-box protein PpDAM6 regulates chilling requirement-mediated dormancy and bud break in peach

Abstract Bud dormancy is crucial for winter survival and is characterized by the inability of the bud meristem to respond to growth-promotive signals before the chilling requirement (CR) is met. However, our understanding of the genetic mechanism regulating CR and bud dormancy remains limited. This study identified PpDAM6 (DORMANCY-ASSOCIATED MADS-box) as a key gene for CR using a genome-wide association study analysis based on structural variations in 345 peach (Prunus persica (L.) Batsch) accessions. The function of PpDAM6 in CR regulation was demonstrated by transiently silencing the gene in peach buds and stably overexpressing the gene in transgenic apple (Malus × domestica) plants. The results showed an evolutionarily conserved function of PpDAM6 in regulating bud dormancy release, followed by vegetative growth and flowering, in peach and apple. The 30-bp deletion in the PpDAM6 promoter was substantially associated with reducing PpDAM6 expression in low-CR accessions. A PCR marker based on the 30-bp indel was developed to distinguish peach plants with non-low and low CR. Modification of the H3K27me3 marker at the PpDAM6 locus showed no apparent change across the dormancy process in low- and non-low- CR cultivars. Additionally, H3K27me3 modification occurred earlier in low-CR cultivars on a genome-wide scale. PpDAM6 could mediate cell–cell communication by inducing the expression of the downstream genes PpNCED1 (9-cis-epoxycarotenoid dioxygenase 1), encoding a key enzyme for ABA biosynthesis, and CALS (CALLOSE SYNTHASE), encoding callose synthase. We shed light on a gene regulatory network formed by PpDAM6-containing complexes that mediate CR underlying dormancy and bud break in peach. A better understanding of the genetic basis for natural variations of CR can help breeders develop cultivars with different CR for growing in different geographical regions.
Human papillomavirus vaccination at the first opportunity: An overview

ABSTRACT The Advisory Committee on Immunization Practices (ACIP) has recommended human papillomavirus (HPV) vaccination for adolescents in the United States since 2006. Though recommended at a similar time to the routine recommendations for adolescent tetanus, diphtheria, and acellular pertussis vaccination (Tdap) and quadrivalent meningococcal vaccination (MCV4), HPV vaccine uptake has consistently lagged behind these other adolescent vaccines. The ACIP recommends HPV vaccination at 11–12 y, with vaccination starting at 9 y of age included as an option that is routinely encouraged by the American Academy of Pediatrics and American Cancer Society. To support efforts to increase HPV vaccination at the first opportunity, this commentary summarizes the current HPV vaccination recommendations and available evidence regarding HPV vaccination starting at 9 y – including recent studies and trials documenting the effectiveness of HPV vaccination at 9 in supporting vaccine series completion, while providing future directions for research and implementation to improve HPV vaccination.
State space modeling of multiple time series

Time series methods offer the possibility of making accurate forecasts even when the underlying structural model is unknown, by replacing the structural restrictions needed to reduce sampling error and improve forecasts with restrictions determined from the data. While there has been considerable success with relatively simple univariate time series modeling procedures, the complex interrela- tionships possible with multiple series requite more powerful techniques.Based on the insights of linear systems theory, a multivariate state space methos for both stationary and nonstationary problems is described and related to ARMA models. The states or dynamic factors of the procedure are chosen to be robust in the presence of model misspecification, in constrast to ARMA models which lack this property. In addition, by treating th emidel choice as a formal approximation problem certain new optimal properties of the procedure with respect to specification are established; in particular, it is shown that no other m.
Digital Gender Gap in the Second Half of Life Is Declining: Changes in Gendered Internet Use Between 2014 and 2021 in Germany

Abstract Objectives The main purpose of the study has been to examine changes in Internet use among men and women in 3 age groups (midlife, early old age, and advanced old age) between 2014 and 2021. We tested 2 hypotheses: The complementary hypothesis posits that online activities reproduce gender differences in offline activities. The compensatory hypothesis posits that women are catching up over time in male-typed activities as Internet access approaches saturation for both genders. Methods We used representative, longitudinal data from the German Ageing Survey collected in 2014, 2017, 2020, and 2021 (n = 21,505, age range 46–90 years). We ran logistic regressions on Internet access and Internet use for 4 different gender-typed activities: social contact (female-typed), shopping (gender-neutral), entertainment (male-typed), and banking (male-typed). Results Between 2014 and 2021, women drew level with men in Internet access. Gender differences in all 4 forms of Internet use declined considerably between 2014 and 2021. Women overtook men in using the Internet for social contact. In older age groups, men held the lead regarding online banking. During the coronavirus disease 2019 (COVID-19) crisis, women caught up to men in Internet use, especially for entertainment. Discussion Overall time trends support the complementary hypothesis. By contrast, the finding that women have been catching up in some male-typed online activities during the COVID-19 pandemic supports the compensatory hypothesis.
From Habitual Problems to a Systematic Approach for Problem Solving

The current presentation- the systematic approach for problem solving. Starting from identifying the habitual problems in an organization, this leads to the awareness to the areas of concern. Then, performance measure is assigned to monitor the habitual problems. It aims to be a tool to highlight when there is a sign or an occurrence of the problem. In other words, this is an approach to call for an attention when the problem occurs. The system also combines some supporting functions to accomplish the problem solving (e.g. functionalities of process map, problem solving guideline, tools and techniques, relevant project records). Those functions intend to be combined and proposed as the systematic approach for problem solving. In addition, the system requires to run as real-time since it aims to provide an auto-monitoring system and the indicator for problem occurrence. However, the process of problem solving still requires human-interact. Nevertheless, even the system can combine all supporting and relevant functions in problem solving, but human is still necessary to generate the solutions and decision making.
Gender bias in video game dialogue

Gender biases in fictional dialogue are well documented in many media. In film, television and books, female characters tend to talk less than male characters, talk to each other less than male characters talk to each other, and have a more limited range of things to say. Identifying these biases is an important step towards addressing them. However, there is a lack of solid data for video games, now one of the major mass media which has the ability to shape conceptions of gender and gender roles. We present the Video Game Dialogue Corpus, the first large-scale, consistently coded corpus of video game dialogue, which makes it possible for the first time to measure and monitor gender representation in video game dialogue. It demonstrates that there is half as much dialogue from female characters as from male characters. Some of this is due to a lack of female characters, but there are also biases in who female characters speak to, and what they say. We make suggestions for how game developers can avoid these biases to make more inclusive games.
Elastic wave dispersion in layered media with suture joints: influence of structural hierarchy and viscoelasticity

Suture joints contribute to the exceptional combination of stiffness, strength, toughness and efficient load bearing and transmission of many biological structures like the cranium or ammonite fossil shells. However, their role in the attenuation of vibrations and effect on dynamic loads is less clear. Moreover, the self-similar hierarchical geometry often associated with suture joints renders its treatment with standard numerical approaches computationally prohibitive. To address this problem, this paper investigates the dynamic response of periodic layered media with suture joints using an analytical approach based on material homogenization. A general trapezoidal suture geometry is considered together with the fundamental ingredients of hierarchy and viscoelasticity. The Spectral Element Method and Bloch theorem are used to derive the dispersion relation and band diagram of the system, including propagating and evanescent dispersion modes. A strong influence of the suture morphology and material properties emerges, and the analysis reveals an important advantage of adding hierarchy, i.e. the possibility of simultaneously obtaining wider bandgaps and their shift to higher frequencies. A synergy between hierarchy and structure is also observed, providing superior levels of wave attenuation. These findings suggest a possible design concept for bioinspired devices with efficient and tailorable wave attenuation properties.
An extended shoving model for dynamic fluctuation of glass transition in amorphous polymer towards cooperative shape-memory effect

Phase transition theory is a powerful approach to study shape-memory effect (SME) and dynamic relaxation behaviour in amorphous shape-memory polymers (SMPs) undergoing glass transition processes. However, previous studies are mostly limited to building-up of experimental models, mainly due to poor understanding of dynamic fluctuation of glass transition. In this study, the dynamic fluctuation of glass transition in the amorphous SMPs, whose thermodynamic SME is governed by the phase transition theory, was investigated using a shoving model. A constitutive relationship between potential energy and cooperatively rearranging region (CRR) volume is firstly developed to explore the working principle of phase transition in the thermodynamic SME of amorphous SMPs, based on the shoving model and Adam–Gibbs domain size model. The effect of CRR volume on the phase transition is further formulated using the strain function, and then employed to develop a constitutive stress–strain equation based on the extended Maxwell model. The working principles of cooperative SME and dynamic relaxation behaviours have been explored and discussed. Finally, the effectiveness of the analytical results obtained using the proposed model has been verified using the experimental results of amorphous SMPs reported in literature.
Forward Induction Works! An Experimental Study to Test the Robustness and the Power *

Cooper et al. (1993) found support for forward i nduction but its true predictive power was less than the apparent level due to a confounding focal point; an outside - option asymmetry generated the focal point . We test for the robustness and the true and independent predictive power of forward induction b y changing the asymmetry type and constructing a symmetric game (i.e. no focal point). Our results, for the first time, confirm that forward induction functions (1) in games with different types of asymmetry, and (2) as an independent selection criterion i n the absence of a confounding factor. We also find that controlling for social preferences provides some additional support to forward induction.
Arterial spin labeling versus BOLD in pharmacological fMRI

A carefully controlled study allowed us to compare the sensitivity of ASL (arterial spin labeling) and BOLD (blood oxygen level dependent) fMRI for detecting the effects of the adenosine A2a antagonist tozadenant in Parkinson disease. Only ASL detected the direct effect of tozadenant. BOLD was more sensitive to a cognitive task, which (unlike most drugs) allows onoff comparisons over short periods of time. Neither ASL nor BOLD could detect a cognitive-pharmacological interaction. These results are consistent with the known relative advantages of each fMRI method, and suggest that for drug development, directly imaging pharmacodynamic effects with ASL may have advantages over cognitive-pharmacological interaction BOLD, which has hitherto been the more common approach to pharmacological fMRI.
Mutiple exp-function Method for Two Kinds of (3+1)-dimensional Generalized BKP Equations

By using the mutiple exp-function method and the homogeneous balance method,two kinds of(3 + 1)-dimensional generalized Boussinesq-Kadomtsev-Petviashvili(BKP) equations have been solved and the wave solutions of exponential function have been obtained.Because of the arbitrariness of parameters,we can get two kinds of solutions by choosing different values for parameters.It has a certain reference value for some related engineering fields.As examples,two kinds of images with specific values of involved parameters have been given by Maple.According to the images of solutions,we can see more clearly the characteristics of solutions of the generalized BKP equations,which is bene? cial to related research in the future.
The effect of intersemiotic relations on L2 learners’ multimodal reading

The paper adopts a mixed-method approach (online and eye-tracking experiments) to investigate which image-text relation in multimodal texts, namely image-subordinate-to-text (IST) and text-subordinate-to-image (TSI), creates a strong visual or verbal mental representation in the case of second language (L2) learners. Thirty-eight Hungarian L2 learners with B1 English language proficiency attended the online experiment to read and respond to the multimodal texts with IST and TSI relations. Furthermore, during the eye-tracking experiment, second language learners’ (N=9) gaze patterns were examined while reading IST and TSI multimodal texts. The initial study results reveal that while the semantic gap between the image and text encourages more intermodal interactions and longer eye fixations, redundancy, involving the duplication of information via image and text, also develops a strong mental model of the meaning. The present research may contribute to the development of a more comprehensive model of L2 multimodal and multimedia learning.
Synthetic predictabilities from large language models explain reading eye movements

A long tradition in eye movement research has focused on three linguistic variables explaining fixation durations during sentence reading: word length, frequency, and predictability. Lengths and frequencies are easily obtainable but predictabilities are tedious to collect, requiring the incremental cloze procedure. Modern large language models are trained using the objective of predicting the next word given previous context, hence they readily provide predictability information. This capability has largely been overlooked in eye movement research. Here we investigate the suitability of a synthetic predictability measure, extracted from pretrained GPT-2 models, as a surrogate for cloze predictability. Using several published eye movement corpora, we find that synthetic and cloze predictabilities are highly correlated, and that their influence on eye movements is qualitatively similar. Similar patterns are obtained when including synthetic predictabilities in data sets lacking cloze predictabilities. In conclusion, synthetic predictabilities can serve as a substitute for empirical cloze predictabilities.
Leveraging Eye Tracking in Digital Classrooms: A Step Towards Multimodal Model for Learning Assistance

Instructors who teach digital literacy skills are increasingly faced with the challenges that come with larger student populations and online courses. We asked an educator how we could support student learning and better assist instructors both online and in the classroom. To address these challenges, we discuss how behavioral signals collected from eye tracking and mouse tracking can be combined to offer predictions of student performance. In our preliminary study, participants completed two image masking tasks in Adobe Photoshop based on real college-level course content. We then trained a machine learning model to predict student performance in each task based on data from other students, as a step towards offering automated student assistance and feedback to instructors. We reflect on the challenges and scalability issues to deploying such a system in-the-wild, and present some guidelines for future work.
A Deep Learning Architecture for Egocentric Time-to-Saccade Prediction using Weibull Mixture-Models and Historic Priors

Real-time detection of saccades is of major interest for many applications in human-computer interaction and mixed reality. However, due to relatively low update rates and high latencies of current commercially available eye trackers, gaze events are typically detected after they occur with some delay. This limits interaction scenarios such as intent-based gaze interaction, redirected walking, or gaze forecasting. In this paper, we propose a deep learning framework for time-to-event prediction of saccades. In contrast to previous approaches, we utilize past multimodal data captured from head-mounted displays. We combine the well-established transformer architecture with a Weibull Mixture Model. This also allows estimating the uncertainty of the prediction. Additionally, we propose a sampling strategy that differs from conventional approaches to better account for the temporal properties of gaze sequences. We demonstrate that our model achieves state-of-the-art performance by evaluating it on three datasets and performing multiple ablation studies.
Foveated Noise Reduction: Visual Search Tasks under Spatio-Temporal Control Synchronized with Eye Movements

The authors propose a spatiotemporal noise reduction system called Foveated Noise Reduction. This system reduces ambient motion noise synchronized with eye movements and spatiotemporal blurring in peripheral vision. Preliminary experiments were conducted with the visual search task in ambient motion noise. The authors evaluated task performance when varying spatiotemporal blurring parameters. The results suggest that the spatial reduction affected the task performance, and the blur size would be suitable under the visual search task with ambient noise.
Comparison of interferon-gamma production between TB1 and TB2 tubes of QuantiFERON-TB Gold Plus: a meta-analysis

Abstract Objectives CD8 T-cells play an important role in interferon-gamma (IFN-γ) production as a host defense against tuberculosis (TB) infection. Therefore, QuantiFERON-TB Gold Plus (QFT-Plus) was developed by adding a TB2 tube beside the TB1 tube. This study aimed to compare and analyze the difference in IFN-γ production between the two tubes in general and specific populations. Content PubMed, Web of Science, and EBSCO were searched for studies reporting IFN-γ production levels in the TB1 and TB2 tubes. Statistical analysis was performed using RevMan 5.3. Summary A total of 17 studies met the inclusion criteria. The IFN-γ production in the TB2 tube was statistically higher than that in the TB1 tube (mean difference (MD)=0.02, 95 % confidence interval (95 % CI): 0.01–0.03). Further subgroup analysis in specific populations revealed that the MD of IFN-γ production between the TB2 and TB1 tubes was significantly higher in active TB subjects than in latent TB infection (LTBI) subjects (MD=1.13, 95 % CI: 0.49–1.77, and MD=0.30, 95 % CI: 0.00–0.60, respectively). A similar finding was found in immune-mediated inflammatory disease subjects, but not statistically significant. Interestingly, IFN-γ production capacity was lower in active TB subjects than in LTBI subjects in each of the TB1 and TB2 tubes. Outlook This study is the first to systematically compare IFN-γ production between the TB1 and TB2 tubes. The IFN-γ production was higher in the TB2 tube than in the TB1 tube, representing the host’s CD8 T-cell response magnitude to TB infection.
Changes in Cortical Directional Connectivity during Difficult Listening in Younger and Older Adults

One way to investigate the mechanisms that underlie speech comprehension under difficult listening conditions is via cortical connectivity. The innovative Network Localized Granger Causality (NLGC) framework was applied to magnetoencephalography (MEG) data, obtained from older and younger subjects performing a speech listening task in noisy conditions, in delta and theta frequency bands. Directional connectivity between frontal, temporal, and parietal lobes was analyzed. Both aging- and condition-related changes were found, particularly in theta. In younger adults, as background noise increased, there was a transition from predominantly temporal-to-frontal (bottom-up) connections, to predominantly frontal-to-temporal (top-down). In contrast, older adults showed bidirectional information flow between frontal and temporal cortices even for speech in quiet, not changing substantially with increased noise. Additionally, younger listeners did not show changes in the nature of their cortical links for different listening conditions, whereas older listeners exhibited a switch from predominantly facilitative links to predominantly sharpening, when noise increased. Graphical Abstract Highlights Different bands show strong differences in directional functional connectivity patterns Directional functional connectivity patterns altered by listening task difficulty Aging dramatically alters directional functional connectivity patterns in during listening Nature of functional connectivity, additive vs subtractive, depends on age and task
Utilizing tumor microenvironment microbial profiles and host gene expressions for survival subtyping in diverse types of cancers

The tumor microbiome, a complex community of microbes found in tumors, has been found to be linked to cancer development, progression, and treatment outcome. However, it remains a bottleneck in distangling the relationship between the tumor microbiome and patient survival. In this study, we aimed to decode this complex relationship by developing ASD-cancer (autoencoder-based subtypes detector for cancer), a semi-supervised deep learning framework that could extract survival-related features from tumor microbiome and transcriptome data, and identify patients’ survival subtypes. By using samples from The Cancer Genome Atlas database, we identified two statistically distinct survival subtypes across all 20 types of cancer. Our framework provided improved risk-stratification (e.g., for Liver hepatocellular carcinoma, LIHC, log-rank test, P = 8.12E-6) compared to PCA (e.g., for LIHC, log-rank test, P = 0.87), predicted survival subtypes accurately, and identified biomarkers for survival subtypes. Additionally, we identified potential interactions between microbes and genes that may play roles in survival. For instance, in LIHC, Arcobacter, Methylocella, and Isoptericola may regulate host survival through interactions with host genes enriched in the HIF-1 signaling pathway, indicating these species as potential therapy targets. Further experiments on validation dataset have also supported these patterns. Collectively, ASD-cancer has enabled accurate survival subtyping and biomarker discovery, which could facilitate personalized treatment for a broad-spectrum types of cancers.