Miracle-dz/UniFAR-FTUs huggingface dataset:
Time Spent on Instagram and Body Image, Self-esteem, and Physical Comparison Among Young Adults in Spain: Observational Study

Background Instagram is a social media platform based on photos and videos that encourages interaction and comparison between users. Its growing popularity, especially among young people, has generated interest in the impact its use can have on users´ mental health, specifically on their self-esteem and degree of satisfaction with their own body image. Objective We aimed to analyze the relationships between the use of Instagram, both the hours of daily use and the type of content viewed, and self-esteem, tendency to make physical comparisons, and satisfaction with body image. Methods In this cross-sectional study, we recruited 585 participants aged between 18 years and 40 years. Individuals who were interested in participating but had a personal history of eating disorders or had previously been diagnosed with a psychiatric disorder were excluded. The assessment tools consisted of (1) a questionnaire that collected sociodemographic data and Instagram use variables and was created by the research team specifically for this study; (2) the self-esteem scale by Rosenberg; (3) Physical Appearance Comparison Scale-Revised (PACS-R); and (4) Body Shape Questionnaire (BSQ). The recruitment and evaluation processes were carried out in January 2021. Results Of the participants, 234 (234/585, 40%) used Instagram less than 1 hour a day, 303 (303/585, 51.8%) used Instagram between 1 hour and 3 hours a day, and 48 participants (48/585, 8.2%) used it more than 3 hours per day. We found statistically significant differences (P<.05) between the 3 groups in the scores obtained on the self-esteem test by Rosenberg, PACS-R, and BSQ. Participants who spent more time on Instagram had higher levels of body dissatisfaction, greater comparisons of physical appearance, and lower self-esteem. Moreover, we analyzed the relationship between the score obtained on the different scales and the types of content viewed, with no differences between those who mainly viewed professional content and those who primarily consumed fashion and beauty or sport and nutrition content. Conclusions The results of this study indicate that the use of Instagram is associated with poorer body image satisfaction and self-esteem, mediated by the tendency to compare physical appearance in relation to the daily duration of Instagram use.
Varieties of socialization goals: a qualitative study of Palestinian mothers from different socio-economic backgrounds

ABSTRACT This study examined diversity in the socialization goals of Palestinian mothers from different educational and socioeconomic backgrounds from the perspective of (Kagitçibasi, C. (1996). The autonomous-relational self. European Psychologist, 1(3), 180–186. Kagitçibasi, C. (2005). Autonomy and relatedness in cultural context: Implications for self and family. Journal of Cross-Cultural Psychology, 36(4), 403–422 Kagitçibasi, C. (2012). Sociocultural change and integrative syntheses in human development: Autonomous-related self and social–cognitive competence. Child Development Perspectives, 6(1), 5–11) Family Change model, which proposes that societal changes due to globalization can promote the development of autonomous-relational selves. Purposeful-convenience sampling was used to recruit twelve urban Arab mothers of first grade children enrolled in public and private schools to capture a variety of parent education levels. The first author interviewed each mother about her socialization goals and analyzed interviews thematically. One main finding was that mothers who had at least a Bachelor’s degree focused more on goals related to self-maximization, particularly in relation to choosing a career, thriving, and being highly successful. Mothers with less formal education themselves had education as a goal in itself and valued employment for their children with an emphasis on stability of income and comfort. Both groups of mothers reported goals related to decency, including ‘avoiding illicit behaviors,’ having morals, and treating others well. Collectivism and individualism were both present in the socialization goals of Palestinian mothers, which supported the development of autonomous-relational selves.
How State Ownership Affects Firm Innovation Performance: Evidence from China

ABSTRACT Innovation plays a vital role in economic development. This paper examined the effect of state ownership on firm innovation as well as the moderating roles of R&D capability and marketization by Chinese firm-level data from Chinese Industrial Enterprises (2008–2011) and listed companies (2007–2016). The theoretical and empirical study verified that state ownership positively influences firm innovation, and firm’s R&D capability and the degree of marketization have significant positive moderate effect. The result was robust in a series of checks such as using lagged data, adopting alternative identification methods and variables, and using independent replication. The conclusion provided implications for the management of Chinese firms. The unique innovation pattern of Chinese firms also provided enlightening experience to other emerging economies.
Inter-relationships among neutrophilic inflammation, air trapping and future exacerbation in COPD: an analysis of ECOPD study

Background The inter-relationships among neutrophilic airway inflammation, air trapping and future exacerbation in chronic obstructive pulmonary disease (COPD) remain unclear. Objective To evaluate the associations between sputum neutrophil proportions and future exacerbation in COPD and to determine whether these associations are modified by significant air trapping. Methods Participants with completed data were included and followed up to the first year in the Early Chronic Obstructive Pulmonary Disease study (n=582). Sputum neutrophil proportions and high-resolution CT-related markers were measured at baseline. Sputum neutrophil proportions were dichotomised based on their median (86.2%) to low and high levels. In addition, subjects were divided into the air trapping or non-air trapping group. Outcomes of interest included COPD exacerbation (separately any, severe and frequent exacerbation, occurring in the first year of follow-up). Multivariable logistic regressions were performed to examine the risk of severe exacerbation and frequent exacerbation with either neutrophilic airway inflammation groups or air trapping groups. Results There was no significant difference between high and low levels of sputum neutrophil proportions in the exacerbation in the preceding year. After the first year of follow-up, subjects with high sputum neutrophil proportions had increased risks of severe exacerbation (OR=1.68, 95% CI: 1.09 to 2.62, p=0.020). Subjects with high sputum neutrophil proportions and significant air trapping had increased odds of having frequent exacerbation (OR=3.29, 95% CI: 1.30 to 9.37, p=0.017) and having severe exacerbation (OR=2.72, 95% CI: 1.42 to 5.43, p=0.003) when compared with those who had low sputum neutrophil proportions and non-air trapping. Conclusions We found that subjects with high sputum neutrophil proportions and significant air trapping are prone to future exacerbation of COPD. It may be a helpful predictor of future exacerbation.
Types and effects of feedback for emergency ambulance staff: a systematic mixed studies review and meta-analysis

Background Extensive research has been conducted into the effects of feedback interventions within many areas of healthcare, but prehospital emergency care has been relatively neglected. Exploratory work suggests that enhancing feedback and follow-up to emergency medical service (EMS) staff might provide staff with closure and improve clinical performance. Our aim was to summarise the literature on the types of feedback received by EMS professionals and its effects on the quality and safety of patient care, staff well-being and professional development. Methods A systematic review and meta-analysis, including primary research studies of any method published in peer-reviewed journals. Studies were included if they contained information on systematic feedback to emergency ambulance staff regarding their performance. Databases searched from inception were MEDLINE, Embase, AMED, PsycINFO, HMIC, CINAHL and Web of Science, with searches last updated on 2 August 2022. Study quality was appraised using the Mixed Methods Appraisal Tool. Data analysis followed a convergent integrated design involving simultaneous narrative synthesis and random effects multilevel meta-analyses. Results The search strategy yielded 3183 articles, with 48 studies meeting inclusion criteria after title/abstract screening and full-text review. Interventions were categorised as audit and feedback (n=31), peer-to-peer feedback (n=3), postevent debriefing (n=2), incident-prompted feedback (n=1), patient outcome feedback (n=1) or a combination thereof (n=4). Feedback was found to have a moderate positive effect on quality of care and professional development with a pooled effect of d=0.50 (95% CI 0.34, 0.67). Feedback to EMS professionals had large effects in improving documentation (d=0.73 (0.00, 1.45)) and protocol adherence (d=0.68 (0.12, 1.24)), as well as small effects in enhancing cardiac arrest performance (d=0.46 (0.06, 0.86)), clinical decision-making (d=0.47 (0.23, 0.72)), ambulance times (d=0.43 (0.12, 0.74)) and survival rates (d=0.22 (0.11, 0.33)). The between-study heterogeneity variance was estimated at σ2=0.32 (95% CI 0.22, 0.50), with an I2 value of 99% (95% CI 98%, 99%), indicating substantial statistical heterogeneity. Conclusion This review demonstrated that the evidence base currently does not support a clear single point estimate of the pooled effect of feedback to EMS staff as a single intervention type due to study heterogeneity. Further research is needed to provide guidance and frameworks supporting better design and evaluation of feedback interventions within EMS. PROSPERO registration number CRD42020162600.
Characterization of separability for $LF$-spaces

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Covariance, Subspace, and Intrinsic CramrRao Bounds

Crami? r-Rao bounds on estimation accuracy are established for estimation problems on arbitrary manifolds in which no set of intrinsic coordinates exists. The frequently encountered examples of estimating either an unknown subspace or a covariance matrix are examined in detail. The set of subspaces, called the Grassmann manifold, and the set of covariance (positive-definite Hermitian) matrices have no fixed coordinate system associated with them and do not possess a vector space structure, both of which are required for deriving classical Crami? r-Rao bounds. Intrinsic versions of the Crami? r-Rao bound on manifolds utilizing an arbitrary affine connection with arbitrary geodesics are derived for both biased and unbiased estimators. In the example of covariance matrix estimation, closed-form expressions for both the intrinsic and flat bounds are derived and compared with the root-mean-square error (RMSE) of the sample covariance matrix (SCM) estimator for varying sample support K. The accuracy bound on unbiased covariance matrix estimators is shown to be about (10/log 10)n/K 1/2 dB, where n is the matrix order. Remarkably, it is shown that from an intrinsic perspective, the SCM is a biased and inefficient estimator and that the bias term reveals the dependency of estimation accuracy on sample support observed in theory and practice. The RMSE of the standard method of estimating subspaces using the singular value decomposition (SVD)is compared with the intrinsic subspace Crami? r-Rao bound derived in closed form by varying both the signal-to-noise ratio (SNR) of the unknown p-dimensional subspace and the sample support. In the simplest case, the Crami? r-Rao bound on subspace estimation accuracy is shown to be about (p(n - p)1/2 K-1/2SN-1/2 rad for p-dimensional subspaces. It is seen that the SVD-based method yields accuracies very close to the Crami? r-Rao bound, esta blishing that the principal invariant subspace of a random sample provides an excellent estimator of an unknown subspace. The analysis approach developed is directly applicable to many other estimation problems on manifolds encountered in signal processing and elsewhere, such as estimating rotation matrices in computer vision and estimating subspace basis vectors in blind source separation.
N-cadherin dynamically regulates pediatric glioma cell migration in complex environments

Pediatric high-grade gliomas are highly invasive and essentially incurable. Glioma cells migrate between neurons and glia, along axon tracts, and through extracellular matrix surrounding blood vessels and underlying the pia. Mechanisms that allow adaptation to such complex environments are poorly understood. N-cadherin is highly expressed in pediatric gliomas and associated with shorter survival. We found that inter-cellular homotypic N-cadherin interactions differentially regulate glioma migration according to the microenvironment, stimulating migration on cultured neurons or astrocytes but inhibiting invasion into reconstituted or astrocyte-deposited extracellular matrix. N-cadherin localizes to filamentous connections between migrating leader cells but to epithelial-like junctions between followers. Leader cells have more surface and recycling N-cadherin, increased YAP1/TAZ signaling, and increased proliferation relative to followers. YAP1/TAZ signaling is dynamically regulated as leaders and followers change position, leading to altered N-cadherin levels and organization. Together, the results suggest that pediatric glioma cells adapt to different microenvironments by regulating N-cadherin dynamics and cell-cell contacts. Summary Pediatric gliomas invade the brain by migrating between nerve cells or exploiting extracellular matrix along blood vessels. This research reveals cross-talk between YAP1/TAZ signaling and N-cadherin that regulates leader-follower cell phenotypes and migration efficiency in neural and extracellular matrix environments.
Topological benchmarking of algorithms to infer Gene Regulatory Networks from Single-Cell RNA-seq Data

In recent years, many algorithms for inferring gene regulatory networks from single-cell transcriptomic data have been published. Several studies have evaluated their accuracy in estimating the presence of an interaction between pairs of genes. However, these benchmarking analyses do not quantify the algorithms’ ability to capture structural properties of networks, which are fundamental, for example, for studying the robustness of a gene network to external perturbations. Here, we devise a three-step benchmarking pipeline called STREAMLINE that quantifies the ability of algorithms to capture topological properties of networks and identify hubs. To this aim, we use data simulated from different types of networks as well as experimental data from three different organisms. We apply our benchmarking pipeline to four algorithms and provide guidance on which algorithm should be used depending on the global network property of interest.
Functional genomics identifies extension of complex N-glycans as a mechanism to evade lysis by natural killer cells

Somatic mutations can lead to the transformation of healthy cells into malignant cells and allow their evasion from immune surveillance. To uncover genes that play a role in the detection and lysis of tumor cells by natural killer (NK) cells, a B lymphoblastoid cell line was subjected to a genome-wide CRISPR screen. Among the top hits that facilitated NK evasion was SPPL3, which encodes an intramembrane protease that cleaves transmembrane glycosyltransferases in the Golgi apparatus. SPPL3-deficient cells accumulated glycosyltransferases, such as acetylglucosaminyltransferase 5 (MGAT5), and displayed increased N-glycosylation. Binding of NK receptors NKG2D and CD2 to their corresponding ligands MICB and CD58, and binding of rituximab to CD20, was disrupted by SPPL3-deletion. Inhibition of N-glycan maturation restored receptor binding and sensitivity to NK cells. To elucidate the mechanism of this resistant phenotype, a secondary CRISPR screen was performed in SPPL3-deficient cells. This screen identified glycosyltransferases that catalyze the formation of highly branched N-glycans and N-acetyl-lactosamine (LacNAc) extensions as key regulators that prevent killing. A significant enrichment of poly-LacNAc-containing tetra-antennary species was confirmed by glycoproteomic analysis. These findings provide mechanistic insight into how SPPL3 deletions have been linked to cancer.
Title: Identification of a novel MCR-1 variant displaying low level of co-resistance to β-lactam

54 The emerging and global spread of a novel plasmid-mediated colistin resistance gene, mcr-1, 55 threatens human health. It is accepted that MCR-1 affects bacterial fitness, and this fitness cost 56 correlates with bacterial membrane lipid A perturbation. However, the detailed molecular mechanism 57 remains unclear. Here, we screened out a novel MCR-1 variant, named M6, with a two-point mutation 58 that rendered a low level of co-resistance to β-lactam antibiotics. Compared to wild-type (WT) MCR-1, 59 this variant caused severe lipid A perturbation resulting in peptidoglycan layer remodelling and thus 60 resulted in phenotypic co-resistance to β-lactams. Moreover, we found that a lipid A loading cavity is 61 localized at the linker domain of MCR-1 and governs colistin resistance and bacterial membrane 62 permeability, and the mutated pocket of M6 facilitates the binding affinity of lipid A. More importantly, 63 synthetic peptides derived from M6 achieved broad-spectrum antimicrobial activity. These findings 64 provide insights into a potential vulnerability that could be exploited in future antimicrobial drug design. 65
Profile-matrix-based shapelet discovery for time series binary classification

Due to the characteristics of interpretability and high accuracy, shapelet-based time series classification (S-TSC) has attracted considerable attention on data mining community over the past decades. An effective way for the S-TSC is shapelet transformation which produces a transformed dataset by the best k shapelets, where each of the k features in the dataset represent the distance between a time series and a shapelet. It can not only optimize the shapelet selection process, but also the transformed dataset can be combined with any traditional classifiers. However, the method requires evaluating a large amount of shapelets that will consume huge time. In this paper, we propose a matrix profile based method for shapelet discovery to handle time series binary classification. Firstly, this method calculates the distance from time series in one class to time series in another class. Secondly, it selects the three pairs of time series with the farthest distance, and finds the critical region corresponding to each set by the Matrix Profile, and extracts the shapelets from them. By this way, the shapelet candidates for evaluation can be significantly reduced. Experiments show that the method can improve the discovery speed of shapelets to a certain extent while maintaining high accuracy.
Proposal Context Awareness and Personalization in Dialogue Planning

In this thesis proposal, we present techniques to improve the effectiveness of a conversational intelligent agent by incorporating rich, contextual information into the dialogue planning process. First, we propose the usage of linguistic features derived from semantic and discourse parsing to better understand the structure of a dialogue with a user. Discourse parsing gives us the relational structure of a dialogue and can be used to identify inter-sentential references and connections in a conversation. We have developed a novel, spectral algorithm for discourse parsing that is statistically consistent and computationally efficient. We also suggest the incorporation of non-linguistic contextual factors, such as a user’s physical engagement or the aural characteristics of the environment. Modeling the diverse array of social factors we wish to include requires a very expressive state space representation. To account for this, we propose dialogue planning using contextual information stored in a Contextual Knowledge Base (CKB) that can be combined with Predictive State Representations and imitation learning techniques. A conversational agent with access to a Contextual Knowledge Base will be able to respond to environmental and linguistic conditions in ways that a simple question answering agent is not capable of. Our work is motivated by the education domain, and we intend for our methods to be included in a conversational intelligent tutoring system. By incorporating information about the student, the environment, and the state of the dialogue into a planning system, we hope to reduce the collaborative effort required to teach new concepts and to improve the overall effectiveness of conversational tutoring systems.
The Convective Boundary Layer during Active and Break Conditions of Summer Monsoon

Abstract A case study of the convective boundary layer (CBL) during active and break conditions of Indian summer monsoon has been carried out. Conserved variable analysis of the observations showed differences in CBL thermodynamic structures during active and break monsoon periods. The monsoon boundary layer structures during the summer monsoon are comparable with the FGGE CBL structures over tropical oceanic regions of Pacific.
Cloud-resolving modeling of cloud systems during Phase III of GATE. Part II: Effects of resolution and the third spatial dimension

Abstract Two- and three-dimensional simulations of cloud systems for the period of 1–7 September 1974 in phase III of the Global Atmospheric Research Programme (GARP) Atlantic Tropical Experiment (GATE) are performed using the approach discussed in Part I of this paper. The aim is to reproduce cloud systems over the GATE B-scale sounding array. Comparison is presented between three experiments driven by the same large-scale conditions: (i) a fully three-dimensional experiment, (ii) a two-dimensional experiment that is an east–west section of the three-dimensional case, and (iii) a high-resolution version of the two-dimensional experiment. Differences between two- and three-dimensional frameworks and those related to spatial resolution are analyzed. The three-dimensional experiment produced a qualitatively realistic organization of convection: nonsquall clusters, a squall line, and scattered convection and transitions between regimes were simulated. The two-dimensional experiments produced convective organ.