E learning

Spectrum-structure correlation is playing an increasingly crucial role in spectral analysis and has undergone significant development in recent decades. With the advancement of spectrometers, the high-throughput detection triggers the explosive growth of spectral data, and the research extension from small molecules to biomolecules accompanies massive chemical space. Facing the evolving landscape of spectrum-structure correlation, conventional chemometrics becomes ill-equipped, and deep learning assisted chemometrics rapidly emerges as a flourishing approach with superior ability of extracting latent features and making precise predictions...

Chemical modulation of proteins enables a mechanistic understanding of biology and represents the foundation of most therapeutics. However, despite decades of research, 80% of the human proteome lacks functional ligands. Chemical proteomics has advanced fragment-based ligand discovery toward cellular systems, but throughput limitations have stymied the scalable identification of fragment-protein interactions. We report proteome-wide maps of protein-binding propensity for 407 structurally diverse small-molecule fragments...

BACKGROUND: High reliability in health care requires a balance between intentionally designed systems and individual professional accountability. One element of accountability includes a process for addressing clinicians whose practices are associated with a disproportionate share of patient complaints. This study aimed to evaluate the impact of the Patient Advocacy Reporting System (PARS), a tiered intervention model to reduce patient complaints about clinicians. METHODS: A retrospective cohort study was conducted involving a southeastern U...

BACKGROUND: Leptospirosis is a neglected zoonosis which remains poorly known despite its epidemic potential, especially in tropical islands where outdoor lifestyle, vulnerability to invasive reservoir species and hot and rainy climate constitute higher risks for infections. Burden remains poorly documented while outbreaks can easily overflow health systems of these isolated and poorly populated areas. Identification of generic patterns driving leptospirosis dynamics across tropical islands would help understand its epidemiology for better preparedness of communities...

INTRODUCTION: Septic shock is a severe form of sepsis that has a high mortality rate, and a substantial proportion of these patients will develop cardiac dysfunction, often termed septic cardiomyopathy (SCM). Some SCM patients may develop frank cardiac failure, termed sepsis-related cardiogenic shock (SeRCS). Little is known of SeRCS. This study describes baseline characteristics of patients with SCM and SeRCS compared to patients with septic shock without cardiac dysfunction. We compare clinical outcomes among SCM, SeRCS, and septic shock, and identify risk factors for the development of SCM and SeRCS...

While pre-training large-scale video-language models (VLMs) has shown remarkable potential for various downstream video-language tasks, existing VLMs can still suffer from certain commonly seen limitations, e.g., coarse-grained cross-modal aligning, under-modeling of temporal dynamics, detached video-language view. In this work, we target enhancing VLMs with a fine-grained structural spatio-temporal alignment learning method (namely Finsta). First of all, we represent the input texts and videos with fine-grained scene graph (SG) structures, both of which are further unified into a holistic SG (HSG) for bridging two modalities...

Fine-grained image recognition is a longstanding computer vision challenge that focuses on differentiating objects belonging to multiple subordinate categories within the same meta-category. Since images belonging to the same meta-category usually share similar visual appearances, mining discriminative visual cues is the key to distinguishing fine-grained categories. Although commonly used image-level data augmentation techniques have achieved great success in generic image classification problems, they are rarely applied in fine-grained scenarios, because their random editing-region behavior is prone to destroy the discriminative visual cues residing in the subtle regions...

The simultaneous quantification of multiple proteins is crucial for accurate medical diagnostics. A promising technology, the multiplex colorimetric immunoassay using encoded hydrogel microparticles, has garnered attention, due to its simplicity and multiplex capabilities. However, it encounters challenges related to its dynamic range, as it relies solely on the colorimetric signal analysis of encoded hydrogel microparticles at the specific time point (i.e., end-point analysis). This necessitates the precise determination of the optimal time point for the termination of the colorimetric reaction...

The Supreme Court decision that race conscious admissions policies in universities are unconstitutional has created questions and concerns about the sustainability of diversity, equity and inclusion programs in many organizations and across sectors. This editorial provides hopeful examples of how belongingness is being embraced as a core value in many organizations. In an interview with education expert, Dr Pauline Dow, we discuss ways that the education sector creates trust and belongingness and explore best practices and leadership development methods that allow teachers to thrive...

Selenium is an essential trace element that is delivered to the brain by the selenium transport protein selenoprotein P (SEPP1), primarily by binding to its receptor low-density lipoprotein receptor-related protein 8 (LRP8), also known as apolipoprotein E receptor 2 (ApoER2), at the blood-brain barrier. Selenium transport is required for several important brain functions, with transgenic deletion of either Sepp1 or Lrp8 resulting in severe neurological dysfunction and death in mice fed a selenium-deficient diet...

OBJECTIVE: While social networks influence individuals with substance use disorders (SUDs), the mechanisms for such influence are under-explored among women who use drugs. This study triangulates the perspectives of criminal justice professionals, SUD treatment professionals, and women with past and current experiences with substance use to explore these dynamics. METHOD: We conducted semistructured interviews ( N = 42) in 2022 with women with current or past opioid use disorder ( n = 20), SUD treatment professionals ( n = 12), and criminal justice professionals ( n = 10) who work with women with opioid use disorder...

Primates can recognize objects despite 3D geometric variations such as in-depth rotations. The computational mechanisms that give rise to such invariances are yet to be fully understood. A curious case of partial invariance occurs in the macaque face-patch AL and in fully connected layers of deep convolutional networks in which neurons respond similarly to mirror-symmetric view (e.g., left and right profiles). Why does this tuning develop? Here, we propose a simple learning-driven explanation for mirror-symmetric viewpoint tuning...

Target 3 in the Kunming-Montreal Global Biodiversity Framework (GBF) calls for protecting at least 30% of the world's lands and waters in area-based conservation approaches by 2030. This ambitious 30×30 target has spurred great interest among policy makers, practitioners, and researchers in defining and measuring the effectiveness of these types of approaches. But along with this broad interest, there has also been a proliferation of terms and their accompanying abbreviations used to describe different types of conservation areas and their governance, planning, management, and monitoring...

Are children and adults sensitive to gaps in their knowledge, and do they actively elicit information to resolve such knowledge gaps? In a cross-situational word learning task, we asked 5-year-olds, 6- to 9-year-olds and adults to estimate their knowledge of newly learned word-object associations. We then examined whether participants preferentially sampled objects they reported not knowing the label in order to hear their labels again. We also examined whether such uncertainty-driven sampling behaviour led to improved learning...

This current study examines the extent to which children's interests and caregivers' sensitivity to their children's interests are associated with the quality of caregiver-child interaction, and subsequent learning. Eighty-one caregiver-child dyads (24-30-month old children) completed an online shared book-reading task where caregivers and children read two e-books with pictures and descriptions of objects from different categories-one previously determined to be of low and one of high interest to the child (with one novel word-object mapping introduced in each book)...

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i...

A core feature of behavior analysis is the single-subject design, in which each subject serves as its own control. This approach is powerful for identifying manipulations that are causal to behavioral changes but often fails to account for individual differences, particularly when coupled with a small sample size. It is more common for other subfields of psychology to use larger-N approaches; however, these designs also often fail to account for the individual by focusing on aggregate-level data only. Moving forward, it is important to study individual differences to identify subgroups of the population that may respond differently to interventions and to improve the generalizability and reproducibility of behavioral science...

The behavioral repertoire grows and develops through a lifetime in a manner intricately dependent on bidirectional connections between its current form and the shaping environment. Behavior analysis has discovered many of the key relationships that occur between repertoire elements that govern this constant metamorphosis, including the behavioral cusp: an event that triggers contact with new behavioral contingencies. The current literature already suggests possible integration of the behavioral cusp and related concepts into a wider understanding of behavioural development and cumulative learning...

INTRODUCTION: Applying new technologies in teaching has led to the phenomenon of blended learning (BL), which is currently flourishing as a specific requirement for higher self-efficacy and success in increasingly complex healthcare environments. Although various forms of novel education are on the rise worldwide, the effects of electronic learning (EL), combined with collaborative learning (CL) and lecture-based teaching (LBT) approaches, have not yet been validated on academic self-efficacy among undergraduate nursing students...

INTRODUCTION: The potential for secondary use of health data to improve healthcare is currently not fully exploited. Health data is largely kept in isolated data silos and key infrastructure to aggregate these silos into standardized bodies of knowledge is underdeveloped. We describe the development, implementation, and evaluation of a federated infrastructure to facilitate versatile secondary use of health data based on Health Data Space nodes. MATERIALS AND METHODS: Our proposed nodes are self-contained units that digest data through an extract-transform-load framework that pseudonymizes and links data with privacy-preserving record linkage and harmonizes into a common data model (OMOP CDM)...