Natural Context Research Articles

Cortical alpha rhythms interpolate occluded motion from natural scene context.

Tracking objects as they dynamically move in and out of sight is critical for parsing our everchanging real-world surroundings. Here, we explored how the interpolation of occluded object motion in natural scenes is mediated by top-down information flows expressed in cortical alpha rhythms. We recorded EEG while participants viewed videos of a person walking across a scene. We then used multivariate decoding on alpha-band responses to decode the direction of movement across the scene. In trials where the person was temporarily occluded, alpha dynamics interpolated the person's predicted movement. Critically, they did so in a context-dependent manner: When the scene context required the person to stop in front of an obstacle, alpha dynamics tracked the termination of motion during occlusion. As these effects were obtained with an orthogonal task at fixation, we conclude that alpha rhythms automatically interpolate occluded motion based on the contextual cues from the surrounding environment.

Understanding in-situ complexities: a scoping review on the trends of qualitative method design and practice in coach–athlete dialogue studies

ABSTRACT Sport pedagogue–learner interactions encompass complex dynamics of (who, what, when, where, why, and how) speaking and listening acts. As discursive practice normatively frames embodied, pedagogic, and socio-cultural values/biases beyond information transmission, coach–athlete dialogues (CADs) mediate their way of being-in-the-world across multi-dimensions. Recognising this significance, a growing body of qualitative coaching research has applied methodological creativity to seize the in-situ moments of CADs and grasp their emergent, contextual, and nuanced nature, instead of repeating the prominent tendency to manufacture CAD into half-stories of coaches’ behaviours as speakers or athletes’ perceptions as listeners. Nonetheless, the methodological trajectories of such qualitative research (i.e. extant progress, potential limitations, and possible future directions) have seldom been scrutinised. Therefore, this article presents a scoping review on the design and practice of qualitative methods used in 41 CAD studies published from 2000 to 2024. The analysis reveals four major themes: (i) instructor-centred perspective; (ii) space before place; (iii) insufficient attention to non-verbal language-use-in-interaction; and (iv) imbalance of emic–etic approaches. The findings are expected to provide qualitative coaching researchers with reflexive sources for their own and participants’ CAD-related reality (ontology) and knowledge (epistemology), especially when crafting methods to better uncover the in-situ complexities of sport coaching.

Diversity, structure-function relationships and evolution of cell wall-binding domains of staphylococcal phage endolysins.

Diversity, structure-function relationships and evolution of cell wall-binding domains of staphylococcal phage endolysins.

The social media footprint of endoscopic spine surgery: a cross-sectional analysis of content on Twitter/X.

Cross-sectional social media content analysis. Patients increasingly rely on social media for education and perspectives regarding surgical care. Given the growing interest in endoscopic spine surgery, there is a need to critically evaluate related content available on social media. While patient and surgeon engagement with spine surgery topics on social media has been explored, no previous study has specifically examined endoscopic spine surgery content on Twitter/X. The Twitter/X website's user-facing search functionality was used to compile tweets containing hashtags related to endoscopic spine surgery. The search spanned from the website's inception to December 31, 2024. Tweets were categorized by authorship and location. Each tweet was independently analyzed by two reviewers to identify themes and contextual nature (educational vs. promotional). A total of 890 tweets from 199 accounts were analyzed. The majority of content (76.0%) originated from outside the United States. Medical doctors, doctors of osteopathy, and other healthcare providers authored 44.4% of the content. Patient-facing advertisements accounted for 24.5% of tweets. Approximately 22.1% of tweets contained content intended for healthcare professionals already familiar with endoscopic spine surgery, primarily highlighting conference/educational activities, research projects, or noteworthy cases. A growing body of information related to endoscopic spine surgery is available on Twitter/X, though a large portion of this content consists of healthcare providers advertising to potential patients. Future research should prioritize identifying and analyzing patient perspectives on endoscopic spine surgery portrayed on social media platforms.

Vocal communication and perception of pain in childbirth vocalizations.

Nonlinear acoustic phenomena (NLP) likely facilitate the expression of distress in animal vocalizations, making calls perceptually rough and hard to ignore. Yet, their function in adult human vocal communication remains poorly understood. Here, to examine the production and perception of acoustic correlates of pain in spontaneous human nonverbal vocalizations, we take advantage of childbirth-a natural context in which labouring women typically produce a range of highly evocative loud vocalizations, including moans and screams-as they experience excruciating pain. We combine acoustic analyses of these real-life pain vocalizations with psychoacoustic experiments involving the playback of natural and synthetic calls to both naïve and expert listeners. We show that vocalizations become acoustically rougher, higher in fundamental frequency (pitch), less stable, louder and longer as child labour progresses, paralleling a rise in women's self-assessed pain. In perception experiments, we show that both naïve listeners and obstetric professionals assign the highest pain ratings to vocalizations produced in the final expulsion phase of labour. Experiments with synthetic vocal stimuli confirm that listeners rely largely on nonlinear phenomena to assess pain. Our study confirms that nonlinear phenomena communicate intense, pain-induced distress in humans, consistent with their widespread function to signal distress and arousal in vertebrate vocal signals.This article is part of the theme issue 'Nonlinear phenomena in vertebrate vocalizations: mechanisms and communicative functions'.

Moral Sensitivity among Engineering Students in a Natural Disaster Context

Moral Sensitivity among Engineering Students in a Natural Disaster Context

Wine Fermentation as a Model System for Microbial Ecology and Evolution.

In vitro microbial communities have proven to be invaluable model systems for studying ecological and evolutionary processes experimentally. However, it remains unclear whether quantitative insights obtained from these laboratory systems can be applied to complex communities assembling and evolving in their natural ecological context. To bridge the gap between the lab and the 'real-world', there is a need for laboratory model systems that better approximate natural and semi-natural ecosystems. Wine fermentation presents an ideal system for this purpose, balancing experimental tractability with rich ecological and evolutionary dynamics. In this perspective piece we outline the key features that make wine fermentation a fruitful model system for ecologists and evolutionary biologists. We highlight the diversity of environmentally mediated interactions that shape community dynamics during fermentation, the complex evolutionary history of wine microbial populations, and the opportunity to study the impact of complex ecologies on evolutionary dynamics. By integrating knowledge from both wine research and microbial ecology and evolution we aim to enhance understanding and foster collaboration between these fields.

Ethical and Methodological Considerations in Research with Asylum-Seeking and Refugee Youth in European Cities

Research about the lived experiences of asylum-seeking and refugee youth can evoke powerful emotions for those involved. Young people who escaped perilous situations often bear strong emotions linked to their experiences of migration and displacement, as well as their encounters with disorientation, insecurity, isolation, discrimination and racism in unfamiliar contexts in the host society. Such emotions and emotionally charged places can be challenging to work with as researchers and require reflexive and situated methodological and ethical judgements. This paper investigates the emotional complexities of fieldwork with vulnerable young people by reflecting on (dis)comfort and discusses how to negotiate these issues with care and consideration. It draws from qualitative participatory and creative fieldwork experiences using story mapping, photovoice, walk-along and community theatre approaches in Amsterdam, Brussels, Leipzig and Newcastle-Upon-Tyne. It reports on a range of critical ethical and methodological issues that arose in our work that address meaningful relationships, reciprocity and trust, understanding the field, positionality and reflexivity, and challenges around the co-production of knowledge and leaving the field. Throughout, the paper flags various complex and, at times, ambiguous ethical and methodological issues that emerged throughout the research process and argues for research approaches that are sensitive to the contextual and multi-faceted nature of investigating young refugees and asylum seekers in European cities.

High Performance of LSTM on Dengue Shock Syndrome Detection Using DNA Sequence Encoding Methods

Dengue fever (DF) is a significant global health challenge, affecting approximately 390 million people annually and imposing substantial public health and economic burdens. Accurate DNA sequence classification is crucial for identifying genetic factors in diseases such as DF. However, many machine learning (ML) models for disease detection rely on basic encoding methods such as one-hot encoding, which fail to fully exploit the sequential and contextual nature of DNA data. To address this limitation, this study applies long short-term memory (LSTM) networks, a neural architecture adept at handling sequential data, to classify DNA sequences for detecting dengue and dengue shock syndrome (DSS). The study evaluates three encoding techniques— one-hot encoding, term frequency-inverse document frequency (TF-IDF), and Word2Vec— using datasets of 3,458 DNA sequences sourced from genomics repositories. Preprocessing included the removal of non-ACGT sequences and duplicates to ensure data integrity, followed by under-sampling to address class imbalance. Experimental results demonstrate that the LSTM model with Word2Vec encoding achieved the highest accuracy (0.98), significantly outperforming other encoding techniques. Word2Vec captures contextual and semantic relationships within DNA sequences, enabling superior classification performance. These findings highlight the potential of combining advanced encoding techniques with LSTM networks to improve the accuracy of disease detection models. The study’s approach offers promising implications for genomic diagnostics, particularly in resource-limited settings, and lays the foundation for future research into applying similar methodologies to other diseases or datasets.

Offering and showing gestures in 12- to 15-month-old infants in natural contexts: a corpus-based study

ABSTRACT Developmental theories propose that the ontogeny of sharing behaviour builds on earlier emerging social routines of offering objects in caregiver–child interactions. The current study explored the occurrence of offering and showing behaviour in naturalistic contexts, and how caregivers react to these gestures. To this end, we relied on video recordings of spontaneous infant–caregiver interactions from two CHILDES corpora. We analysed data of six infants from 12 to 15 months comprising 222 tokes of gestures. Across ages, infants showed more offering behaviour than showing behaviour. Caregivers responded vocally to both types of gestures and showed more object-directed action in the context of the offering gesture. Showing behaviour was thus more likely to lead to a unimodal reaction, whereas offering behaviour more often led to a bimodal reaction from caregivers. Overall, the study provides evidence for how infant gestures, and the early precursors of sharing behaviour, develop in the context of naturalistic caregiver–child interactions.

Uncovering a Timescale Hierarchy by Studying the Brain in a Natural Context.

As we train multiple generations of students to narrowly design clever, carefully controlled experiments in our confined lab spaces, we may fail to notice, as a field, that we have overlooked fundamental aspects of human cognition. This is a first-person account of how our research and understanding of the neural code were forever transformed when we decided to open the lab's door to the natural world. This journey started with the decision to shift from controlled stimuli to natural dynamic and "messy" stimuli. This transition enabled us to focus on how information is accumulated and processed over time. As a result, we have discovered a new topographic mapping of the hierarchy of cortical processing timescales. I will conclude with a general observation of the paradigm shift occurring in the field as it increasingly emphasizes the study of the neural processes that underlie human behavior in natural, everyday contexts. I am excited to share this journey with you.

PEMAHAMAN DAN PERANAN PRINSIP-PRINSIP HAK ASASI MANUSIA DALAM PRAKTIK ADVOKAT

The main problem in this study is the Understanding and Role of Human Rights Principles in Advocate Practice. The main problem is then described in several sub-problems, namely: 1). How is the process of Human Rights Principles in Advocate Practice. 2) How is the legal analysis of the understanding of the role of Human Rights Principles in Advocate Practice. The type of research conducted in this study is a type of qualitative research, namely: research that intends to understand the phenomenon of what is experienced by the research subject, for example behavior, perception, motivation, actions and so on holistically, by means of description in the form of words and language, in a specific natural context and by utilizing various natural methods. The objectives of the study are as follows: 1). To find out how to understand the process of Human Rights Principles in Advocate Practice. 2) To find out how to analyze the legal role of Human Rights Principles in Advocate Practice.

Behavioral Skills Training and Self-Monitoring to Increase and Maintain the Rate and Quality of Parent-Delivered Praise

Supporting parents in foundational positive behavior support strategies for use with their child is a commonly employed method to improve child behavior in natural contexts, including the home. Parents have learned and implemented a variety of strategies with integrity; however, there is limited research regarding the maintenance of skills. Furthermore, although parents have been taught to implement behavior-specific praise (BSP), the quality of parent BSP has yet to be evaluated. Using a single-case design, three parents were taught to use targeted levels of BSP that contained quality elements, including contingency, immediacy, and variety. Results demonstrated that behavioral skills training resulted in parent mastery of BSP for both frequency and quality; however, skills diminished during maintenance. Self-monitoring was then introduced, resulting in increases to targeted levels. Child engagement and problem behavior were also assessed, with mixed results. Social validity for both BSP and self-monitoring indicated that parents found the practices to be acceptable and feasible.

Method for Using Functional Near-Infrared Spectroscopy (fNIRS) to Explore Music-Induced Brain Activation in Orchestral Musicians in Concert

The act of performing music may induce a specific state of mind, musicians potentially becoming immersed and detached from the rest of the world. May this be measured? Does this state of mind change based on repetition? In collaboration with Stavanger Symphony Orchestra (SSO), we developed protocols to investigate ongoing changes in the brain activation of a first violinist and a second violinist in real time during seven sequential, public concerts using functional near-infrared spectroscopy (fNIRS). Using wireless fNIRS systems (Brite MKII) from Artinis, we measured ongoing hemodynamic changes and projected the brain activation to the audience through the software OxySoft 3.5.15.2. We subsequently developed protocols for further analyses through the Matlab toolboxes Brainstorm and Homer2/Homer3. Our developed protocols demonstrate how one may use “functional dissection” to imply how the state of mind of musicians may alter while performing their art. We focused on a subset of cortical regions in the right hemisphere, but the current study demonstrates how fNIRS may be used to shed light on brain dynamics related to producing art in ecological and natural contexts on a general level, neither restricted to the use of musical instrument nor art form.

Environmental Context of Watermills in Medieval Sussex: Natural and Social Contexts

Environmental Context of Watermills in Medieval Sussex: Natural and Social Contexts

Families’ experiences and perspectives on the early use of powered mobility in children with spinal muscular atrophy type I in the natural context

Purpose To describe the experiences of parents who used powered mobility in children with Spinal Muscular Atrophy, SMA type I,at an early age in the natural context like a family-centered program, using inductive qualitative content analysis. Materials and methods This qualitative study was embedded within a single-blinded randomized waiting list controlled clinical trial, which involved 16 children with SMA type I. This study specifically explores the experiences of the 9 parents whose children participated in the intervention group and completed the training. The training lasted 12 weeks, 3 weekly sessions of half an hour each in a motorized mobility car. Subsequently, there were 4 weeks of free use, based on the child and family’s interest. The therapist evaluated the learning of powered mobility using the ALP assessment. Parent Interviews were conducted using an interview guide. Results The results revealed that parents’ learning was supported by powered mobility coaching, leading to acquired knowledge, skills, and competence. Several themes emerged for consideration in early age power mobility applications: motivation, playing, the importance of a family-centered program to enhance adherence to training and family satisfaction and to share decision making. Conclusion The study concludes that early powered mobility for children with SMA type I should educate, empower, and monitor families to increase the interaction and goal achievement and considering barriers in the child’s context is essential for accessible mobility.

A Participatory Survey to Investigate the Long-Term Effectiveness of Adult Psychiatric Services (PSILEAPS): Baseline Data and Recruitment Experiences.

In clinical psychology and psychiatry, traditional hypothesis testing is challenging due to the subjective and contextual nature of the studied phenomenon. To address this, more exploratory and participatory research is needed. This paper reports recruitment experiences and baseline data of a prospective exploratory cohort study with participatory elements, initiated in mental health services in one Finnish region. The primary aims, design, and survey for data collection were developed through community meetings involving local mental health workers, peer experts, and service users. Over 2 weeks, all mental health service users, their care teams, and social network members were asked to share their views on the reasons for needing services and what aspects of treatment have been or could be helpful or unhelpful. Descriptive statistics summarized baseline data, and simple thematic analysis examined field notes on supporting and hindering aspects of the study design. A total of 117 service users, 54 care team members, and 34 social network members participated, with a service user attrition rate of 40-50%. The study achieved 79% of the target sample size. Women and participants with mood disorder diagnoses and long-term service usage were overrepresented. Findings suggest that integrating participatory research into Finnish public mental health services would require additional resources. Despite its limitations, the collected data will facilitate exploratory research into real-life mental health treatment processes from various perspectives.

Mobile Phone Usage in Higher Education Among Pre-Service Teachers in Nigeria: A Qualitative Study

Technology integration has transformed education globally, making learning more accessible and seamless. Mobile education plays a crucial role in this transformation, relying heavily on mobile technology devices. Among these devices, mobile phones are particularly prevalent among students in higher education institutions worldwide. However, concerns have emerged regarding how students utilize these devices, prompting discussions among educational stakeholders. This study employed a qualitative research design, selecting 40 pre-service teachers through random sampling and conducting interviews to explore their experiences with mobile phone usage in natural contexts. Guided by the Uses and Gratifications Theory, the research addressed five key research questions. The findings indicate that students use mobile phones extensively, engaging actively on six social media platforms, with Facebook and WhatsApp being the most frequently used. Mobile phones are also widely utilized for academic purposes, with the majority of students using them for reading. Notably, the study identified gender differences in mobile phone usage patterns. Challenges associated with mobile phone usage were also highlighted, including a lack of teacher support and limited access to browsing data. The study concludes by offering recommendations to enhance the effective use of mobile phones for learning, including the implementation of policies to regulate and guide their use in educational settings.

Capacity building for youth with disabilities: principles and key ingredients identified through a scoping review.

This knowledge synthesis aimed to 1) Map the extent and nature of the literature on capacity building in the field of rehabilitation for transition-age youth with disabilities (12-30 years old) and 2) Describe how capacity building is conceptualized and identify principles and key ingredients underpinning this concept. A scoping review using JBI methodology was employed. A search of six databases resulted in 2169 English documents; 34 were retained. Two reviewers charted and analyzed the data, supported by the third reviewer. Inductive content analysis was used to identify principles and key ingredients. Seven documents provided explicit definitions of capacity or capacity building. Content analysis revealed four principles describing capacity building as: 1) individualized approach with real-world application 2) fostering a preferred future 3) youth taking ownership for change and 4) an ongoing process. Six key ingredients detail how to build capacity: 1) individualized and flexible approach in natural context 2) shared responsibility 3) use of accessible information and resources 4) cultivate strengths 5) opportunities for full participation and 6) facilitate reflection on experiences. Clinicians and researchers can draw upon identified capacity building principles and ingredients to support meaningful real-world outcomes for transition-age youth.

Evaluating the Effectiveness of CNN, LSTM, and Bi-LSTM Models in Classifying Twitter Sentiments

Introduction: Twitter sentiment analysis is an essential tool for understanding public opinions and extracting valuable insights from social media discussions. However, the informal, concise nature of tweets, along with their context-dependent language, poses significant challenges for accurate sentiment classification. Deep learning techniques have shown promise in addressing these challenges due to their ability to learn complex patterns and contextual relationships in data. This study explores the application of Convolutional Neural Networks (1D-CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (Bi-LSTM) models for classifying tweet sentiments into four categories: positive, negative, neutral, and irrelevant. Objectives: The primary objective of this study is to evaluate the effectiveness of deep learning models, including 1D-CNN, LSTM, and Bi-LSTM, in classifying tweet sentiments into categories such as positive, negative, neutral, and irrelevant. By analyzing the performance of these models, the study aims to compare their accuracy, precision, recall, and F1-score to determine their strengths and limitations. Additionally, the research seeks to identify the most suitable model capable of effectively capturing the sequential and contextual nature of tweets, addressing the unique challenges posed by the informal and context-dependent language of social media data. Methods: The study employs a publicly available Twitter sentiment dataset comprising 73,906 tweets related to general Twitter discussions. The dataset undergoes pre-processing steps, including tokenization, stopword removal, and handling emoticons and hashtags, to ensure clean input for training the models. Tweets are represented using pre-trained word embeddings, specifically GloVe and Word2Vec, which provide rich semantic information by capturing word meanings in context. Individual models—1D-CNN, LSTM, and Bi-LSTM—are trained and evaluated using this pre-processed data. Performance metrics, including accuracy, precision, recall, and F1-score, are calculated to compare the models' effectiveness. Results: The experimental analysis demonstrates that each model has unique strengths in sentiment classification. However, the 1D-CNN outperforms both LSTM and Bi-LSTM models, achieving superior results in capturing both the sequential and contextual information inherent in tweet data. This highlights its efficiency and suitability for Twitter sentiment analysis. Conclusions: This study underscores the potential of deep learning techniques for sentiment analysis in social media. Among the evaluated models, 1D-CNN proves to be the most effective, offering a robust approach to handling the complexities of tweet sentiment classification. Future work could explore hybrid models and further optimization techniques to enhance sentiment analysis performance.