Context Of Adaptation Research Articles

Resilience of Family Caregivers of People With Dementia in South Korea: A Scoping Review.

Due to rapid increases in the number of Korean people with dementia, dementia has become a priority health issue in South Korea. Likewise, the well-being of family caregivers of people with dementia has also become an issue of concern. However, little is known about the resilience of Korean family caregivers because there is a lack of review studies from a Korean cultural perspective about the resilience of family caregivers of people with dementia. The purpose of this scoping review was to investigate quantitative studies related to resilience theories, measurement instruments, correlates and resilience interventions for family caregivers of people with dementia. This review was conducted according to the Joanna Briggs Institute based on Arksey and O'Malley. Nine databases were searched to retrieve evidence published in English or Korean between January 2000 and September 2022. Studies with a quantitative research design reporting the resilience of family caregivers of people with dementia based on a resilience theory framework were included. A total of 13 studies were included in this review. All studies used either a modified McCubbin and McCubbin's family stress, adjustment and adaptation model or Walsh's family resilience model. All resilience instruments were used without cross-cultural adaptation. Family adaptation, social support, life satisfaction, family (di)stress and caregiver burden were associated with resilience among family caregivers. A few family resilience-enhancing programmes showed a positive effect on caregiver resilience. This review noted that all the resilience measures documented in this study need to test for cultural adaptation in a Korean context. Further research is required to develop and implement family-based, culturally tailored interventions to effectively enhance Korean resilience for family caregivers of people with dementia. Gerontological nurses should include Korean family caregivers in their nursing care and assess whether family caregivers have depression or suicidal thoughts to promote better health outcomes for caregivers and their family members.

Targeted isolation of Methanobrevibacter strains from fecal samples expands the cultivated human archaeome

Archaea are vital components of the human microbiome, yet their study within the gastrointestinal tract (GIT) is limited by the scarcity of cultured representatives. Our study presents a method for the targeted enrichment and isolation of methanogenic archaea from human fecal samples. The procedure combines methane breath testing, in silico metabolic modeling, media optimization, FACS, dilution series, and genomic sequencing through Nanopore technology. Additional analyzes include the co-cultured bacteriome, comparative genomics of archaeal genomes, functional comparisons, and structure-based protein function prediction of unknown differential traits. Successful establishment of stable archaeal cultures from 14 out of 16 fecal samples yielded nine previously uncultivated strains, eight of which are absent from a recent archaeome genome catalog. Comparative genomic and functional assessments of Methanobrevibacter smithii and Candidatus Methanobrevibacter intestini strains from individual donors revealed features potentially associated with gastrointestinal diseases. Our work broadens available archaeal representatives for GIT studies, and offers insights into Candidatus Methanobrevibacter intestini genomes’ adaptability in critical microbiome contexts.

Application and investigation of knowledge graph in biomedical field

A large amount of drug and disease research knowledge is scattered in unstructured literature data, presenting significant challenges in text mining within the field of biomedicine. These challenges include handling professional knowledge, integrating related knowledge, and disambiguating different meanings of the same words. Therefore, constructing a biomedical knowledge graph can significantly save expert human resources and make efficient use of medical literature resources. This review paper aims to summarize the construction methods used during the development of Biomedical Knowledge Graphs. It also outlines the latest models and frameworks, such as BioBERT and LSTM+CRF, highlighting their contributions and applications. In addition, this paper points out the limitations of current biomedical knowledge graphs, such as scalability issues and the need for large annotated datasets. To address these limitations, it proposes the use of Apache Spark for improved processing capabilities and transfer learning to enhance model performance and adaptability in diverse biomedical contexts.

Context-embedded hypergraph attention network and self-attention for session recommendation

Modeling user intention with limited evidence in short-term historical sequences is a major challenge in session recommendation. In this domain, research exploration extends from traditional methods to deep learning. However, most of them solely concentrate on the sequential dependence or pairwise relations within the session, disregarding the inherent consistency among items. Additionally, there is a lack of research on context adaptation in session intention learning. To this end, we propose a novel session-based model named C-HAN, which consists of two parallel modules: the context-embedded hypergraph attention network and self-attention. These modules are designed to capture the inherent consistency and sequential dependencies between items. In the hypergraph attention network module, the different types of interaction contexts are introduced to enhance the model’s contextual awareness. Finally, the soft-attention mechanism efficiently integrates the two types of information, collaboratively constructing the representation of the session. Experimental validation on three real-world datasets demonstrates the superior performance of C-HAN compared to state-of-the-art methods. The results show that C-HAN achieves an average improvement of 6.55%, 5.91%, and 6.17% over the runner-up baseline method on Precision@K, Recall@K, and MRR evaluation metrics, respectively.

Discover Use Linen Back Baby Carriers in Ancient Egypt

Egyptological Research of the hieroglyphics of Linen back baby carriers specifically used in ancient Egypt, there is a depiction from a tomb dating back to 1500 B.C. that shows women carrying children in what appears to be white fabric carriers on their backs. Objectives of This article present a thought-provoking perspective on a possible link between ancient Egyptian design and ergonomics. Remember that this is an ongoing field of research, and new discoveries or interpretations may challenge or refine the presented ideas. Always strive to critically evaluate sources and consider alternative perspectives when exploring historical topics. Egyptians were resourceful people and linen was one of their most common textiles. And It's highly they used linen for a variety of purposes, including carrying children. However, since most Egyptians were farmers and laborers, they used simpler methods for carrying their children, such as slings made from scraps of fabrics. The Pharaohs of Egypt innovate the science of ergonomics and the design of infant carriers the value of our pictures for the earliest history of art. Definitive proof of photos ancient Egypt, the explicit evidence does of back baby carriers being used in ancient Egypt, even within the royal household. Considering the cultural context, practical advantages, and potential adaptations for royalty, further research holds promise in unlocking this fascinating aspect of childcare in a bygone era. This article is intended for research informational purposes and should be depended of research professional ergonomics medical advice. And this research paper is a starting point and can be further expanded upon by including specific citations, additional research findings, and personalized discussions based on your specific interests and areas of focus.

Navigating Turbulence: The Impact of COVID-19 Stress on Flight Attendants’ Pro-Social Service Behavior and Job Dynamics

ABSTRACT The aggravated COVID-19 pandemic has induced stress and impacted employees’ job insecurity and service behaviors across the airline industry. This study examines whether COVID-19-induced stress influences flight attendants’ pro-social service behavior through job insecurity and job stress. Initially, a COVID-19-induced stress measurement was developed. This was followed by a quantitative survey of 322 flight attendants, selected through purposive and snowball sampling. Subsequently, in-depth interviews were conducted with 11 flight attendants to explore the identified factors further. This study utilized partial least squares (PLS) path modeling with the SmartPLS software to test the hypotheses in the proposed theoretical model. The study findings suggest that stress induced by COVID-19 amplifies feelings of job insecurity and job-related stress among flight attendants. Consequently, this heightened stress adversely affects pro-social service behaviors, leading to a decrease in their manifestation. The direct and indirect effects of COVID-induced stress differ according to job position. Unexpectedly, job insecurity has no impact on the pro-social service behaviors, highlighting the complexity of employee responses to stress and the potential for adaptation in crisis contexts.

MFPIDet: improved YOLOV7 architecture based on multi-scale feature fusion for prohibited item detection in complex environment

Prohibited item detection is crucial for the safety of public places. Deep learning, one of the mainstream methods in prohibited item detection tasks, has shown superior performance far beyond traditional prohibited item detection methods. However, most neural network architectures in deep learning still lack sufficient local feature representation ability for overlapping and small targets, and ignore the problem of semantic conflicts caused by direct feature fusion. In this paper, we propose MFPIDet, a novel prohibited item detection neural network architecture based on improved YOLOV7 to achieve reliable prohibited item detection in complex environments. Specifically, a multi-scale attention module (MAM) backbone is proposed to filter the redundant information of target regions and further applied to enhance the local feature representation ability of overlapping objects. Here, to reduce the redundant information of target regions, a squeeze-excitation (SE) block is used to filter the background. Then, aiming at enhancing the feature expression ability of overlapping objects, a multi-scale feature extraction module (MFEM) is designed for local feature representation. In addition, to obtain richer context information, We design an adaptive fusion feature pyramid network (AF-FPN) to combine the adaptive context information fusion module (ACIFM) with the feature fusion module (FFM) to improve the neck structure of YOLOV7. The proposed method is validated on the PIDray dataset, and the tested results showed that our method obtained the highest mAP (68.7%), which is improved by 3.5% than YOLOV7 methods. Our approach provides a new design pattern for prohibited item detection in complex environments and shows the development potential of deep learning in related fields.

An activity theory perspective on interprofessional teamwork in long-term care.

Teamwork in healthcare is shaped by reciprocal interactions among individual team members and their clinical context. Cultural Historical Activity Theory (CHAT) provides a framework to study teamwork from a developmental perspective. We observed interactions between members of an Interprofessional Healthcare Team (IHT) to identify practical guidelines for educators. Three Health Care Providers (HCPs) with more than 22-years' experience in a semi-urban LTC facility participated. We video-recorded two regular IHT meetings and selected excerpts for subsequent video-recall interviews. The excerpts were shown and discussed first with each team member, then with members in pairs and finally with all members reunited. We prompted participants to explain what was happening on the videos. All interviews were recorded, transcribed, and analyzed using CHAT's unit of analysis based on Activity Systems. We observed contradictions within the Activity Systems involving diverging views on outcomes of enhancing or maintaining quality of life; using non-traditional tools and spaces to sustain resident mobility; safeguarding community and patient safety despite time constraints and job titles, and unease for being paid to perform unconventional interventions. The contradictions have been grouped into three themes reflecting the Activity Systems: 1) enhancing versus maintaining quality of life; 2) improvising to achieve care goals; and 3) role fluidity. Our findings show that practical goal-oriented and contextual adaptations rely heavily on improvisation and dialogue. Educating HCPs for interprofessional teamwork should focus on developing situational awareness to foster continuous adaptation of disciplinary interventions.

CoWPE: Adaptive Context Window Adjustment in LLMs for Complex Input Queries

CoWPE: Adaptive Context Window Adjustment in LLMs for Complex Input Queries

Unveiling Digital Leadership: Exploring Models and Theories

Digital leadership has emerged as an essential strategy in addressing the demands of the digital era. This study reviews academic research on digital leadership models and theories, drawing from published articles in the field. This study has synthesized existing research to create a robust framework that integrates transformational and distributed leadership principles. The framework clarifies the essential components of effective digital leadership and provides practical guidance for organizations navigating the digital landscape. By combining insights from various leadership theories with current digital practices, this research improves our understanding of leveraging technology for organizational success. Moving ahead, it is crucial to empirically validate and apply this framework to verify its effectiveness and adaptability in diverse contexts. The research findings lay the foundation for further exploration of digital leadership strategies, enabling sustainable digital transformation in organizations. The proposed model presents opportunities for future research to explore the broader impact of digital leadership on digital transformation.

A spherical fuzzy objective weighting framework for factors affecting bidding decisions for construction projects: A case study of Taiwan

In response to the intensely competitive bidding environment in Taiwan's construction industry, this study innovates with a spherical fuzzy extension of the modified CRITIC method (SFmCRITIC), a pioneering approach crafted to refine the decision-making process. The research centers on the pivotal role of accurately weighting various significant factors, such as financial stability, market insight, and specialized expertise, to optimize bid success rates. The SFmCRITIC method stands out by quantitatively incorporating the uncertainty and subjectivity typically encountered in bid evaluation. The findings from this methodological application demonstrate a clear hierarchy of influencing factors, offering a nuanced view of strategic priorities for construction firms. This hierarchical understanding not only aids firms in targeted resource distribution and strategic development but also holds promise for adaptation in diverse industry contexts beyond Taiwan, potentially revolutionizing bidding strategies at a global scale.

NeighborNet: Learning Intra- and Inter-Image Pixel Neighbor Representation for Breast Lesion Segmentation.

Breast lesion segmentation from ultrasound images is essential in computer-aided breast cancer diagnosis. To alleviate the problems of blurry lesion boundaries and irregular morphologies, common practices combine CNN and attention to integrate global and local information. However, previous methods use two independent modules to extract global and local features separately, such feature-wise inflexible integration ignores the semantic gap between them, resulting in representation redundancy/insufficiency and undesirable restrictions in clinic practices. Moreover, medical images are highly similar to each other due to the imaging methods and human tissues, but the captured global information by transformer-based methods in the medical domain is limited within images, the semantic relations and common knowledge across images are largely ignored. To alleviate the above problems, in the neighbor view, this paper develops a pixel neighbor representation learning method (NeighborNet) to flexibly integrate global and local context within and across images for lesion morphology and boundary modeling. Concretely, we design two neighbor layers to investigate two properties (i.e., number and distribution) of neighbors. The neighbor number for each pixel is not fixed but determined by itself. The neighbor distribution is extended from one image to all images in the datasets. With the two properties, for each pixel at each feature level, the proposed NeighborNet can evolve into the transformer or degenerate into the CNN for adaptive context representation learning to cope with the irregular lesion morphologies and blurry boundaries. The state-of-the-art performances on three ultrasound datasets prove the effectiveness of the proposed NeighborNet.

Exploring Malay Parenting Patterns and Cultural Identity in Medan City: Traditions, Values, Adaptation in an Urban Context

This research explores early childhood parenting patterns and Malay culture in Medan City, Indonesia. With a focus on traditions, values, and adaption in urban context, this research explores how Malay culture remains relevant in child-rearing patterns amidts dynamic changes in the urban environment. The research method involved in-depth interviews with parents and Malay community leaders living in Medan City, as well as observations of child-rearing practices in everyday life. The research results show that despite adaption to urban development, Malay cultural traditions and values remain the main basis for parenting patterns. However, there are also challenges faced in maintaining Malay cultural identity in globalization and modernization. The implication of this research is the importance of understanding the dynamic of local culture in a urban context to strengthen cultural identity and enrich the study of child-rearing patterns in Indonesia.

The struggle to overcome traffic congestion: A study of social interaction and effects on deviant behavior of motorcycle riders

Background: Motorcycle riding as a means of daily transportation in Southeast Asia, especially Jakarta, Indonesia, manifests the struggle to use the road. This struggle - associated with congestion, irregularity, and lack of control - can lead to physical harm or material loss. Studies on deviant behavior related to motorcycle use mainly discuss motorcycle gangs and traffic violations. This paper intends to explicate how the context of this struggle informs the different meanings of the deviant behavior of motorcyclists in daily traffic life. It employs concepts of innovation and ritualism, learning, harm, visuality, and secret deviance to shatter the prevailing understanding of motorcyclist traffic behavior. Methods: This study chooses T.B. Simatupang Street, one of the busiest roads in Jakarta, as a research location. A mixed method is used to examine the context of the struggle, first qualitatively by utilizing visual data collected through (a) direct video recordings on the road and (b) aerial drone video recordings. Both recordings captured images of motorcyclist behavior considered deviant and can cause harm, such as stopping illegally, clamoring while cutting lanes and other vehicles, and slipping between two automobiles. Then quantitatively, it conducts a survey to collect data on motorcyclists' experiences. Included in the survey were questions with images captured from the direct video recording footage to collect responses toward motorcyclist riding behavior. Findings: The survey findings show that responses toward images of motorcyclist behavior - concerning harm - show a lack of understanding of driving safety and traffic rules, and some consider it as just the daily routine of motorcyclists. Conclusion: Therefore, the visuality of motorcyclist traffic violation is learned through innovation (driving recklessly) or ritualism (daily habit) as a struggle that is ironically visibly secretly upheld by fellow motorcyclists. Novelty/Originality of this Study: This study offers a novel perspective by framing motorcyclists' behavior in Jakarta's traffic as a form of adaptive struggle rather than mere deviance or rule-breaking. It uniquely utilizes visual criminology to argue that what is often seen as traffic violations may be better understood as contextual adaptations to urban congestion, thereby challenging prevailing interpretations of motorcyclist behavior.

The impact of alternative recycled and synthetic phosphorus sources on plant growth and responses, soil interactions and sustainable agriculture - lettuce (Lactuca sativa) as a case model

This research assesses the efficacy of two phosphorus (P) adsorbents as alternative fertilizers in promoting lettuce growth. A synthetic Mg/Al-layered double hydroxide (LDH) and an iron-based recycled water treatment residual (Fe-WTR), both enriched with P from dairy wastewater and added at three dosage levels. We hypothesized that the adsorbents' physicochemical nature will overshadow the biological efforts in the plant ecosystem to increase P solubility, impacting plant growth, nutritional composition, and metabolite profiles.Fe-WTR significantly enhanced lettuce biomass compared to LDH. Yet, elemental analysis revealed higher or equal P concentrations in the low-biomass LDH plants relative to other treatments. Phosphorus uptake appears to influence the assimilation of other nutrients that divided into two groups: calcium, magnesium, zinc, and copper with notable correlations to P and nitrogen, iron, aluminum, vanadium and manganese with low correlations to P. Conversely, P retained poor correlation with most metabolites whereas iron showed a higher correlation with numerous metabolites. Analysis of metabolites, encompassing carbohydrates, the Krebs cycle, amino acids, nucleic acids, and stress and regulatory pathways, revealed diminished levels in the LDH treatments. Overall, carbon assimilation (plant growth) was more effectively predicted by soil P availability (adsorbent type and dose) rather than by cellular P concentration, suggesting root signaling was at play, influencing carbohydrate translocation to the roots. Diminished levels of cellular sugars further affect metabolic pathways and iron uptake, thus restricting photosynthesis. The results illustrate the substantial influence of the P source on the plant's metabolic processes and soil biogeochemistry. The synthetic LDH adsorbent with high sorption capacity, tightly binds its substantial P pool, rendering it inaccessible and potentially disrupting rhizosphere biogeochemical interactions. In contrast, the chemical nature of Fe-WTR enabled efficient nutrients acquisition bioactivity. The study highlights Fe-WTR as a promising sustainable alternative to conventional fertilizers, emphasizing its potential scalability and adaptability in agricultural contexts.

Primary amino acid sequences of decapod (Na+, K+)-ATPase provide evolutionary insights into osmoregulatory mechanisms

Decapod Crustacea exhibit a marine origin, but many taxa have occupied environments ranging from brackish to fresh water and terrestrial habitats, overcoming their inherent osmotic challenges. Osmotic and ionic regulation is achieved by the gill epithelia, driven by two active ATP-hydrolyzing ion transporters, the basal (Na+, K+)-ATPase and the apical V(H+)-ATPase. The kinetic characteristic of gill (Na+, K+)-ATPase and the mRNA expression of its α subunit have been widely studied in various decapod species under different salinity challenges. However, the evolution of the primary structure has not been explored, especially considering the functional modifications associated with decapod phylogeny. Here, we proposed a model for the topology of the decapod α subunit, identifying the sites and motifs involved in its function and regulation, as well as the patterns of its evolution assuming a decapod phylogeny. We also examined both the amino acid substitutions and their functional implications within the context of biochemical and physiological adaptation. The α-subunit of decapod crustaceans shows greater conservation (∼94% identity) compared to the β-subunit (∼40%). While the binding sites for ATP and modulators are conserved in the decapod enzyme, the residues involved in the α-β interaction are only partially conserved. In the phylogenetic context of the complete sequence of (Na+, K+)-ATPase α-subunit, most substitutions appear to be characteristic of the entire group, with specific changes for different subgroups, especially among brachyuran crabs. Interestingly, there was no consistent separation of α-subunit partial sequences related to habitat, suggesting that the convergent evolution for freshwater or terrestrial modes of life is not correlated with similar changes in the enzyme's primary amino acid sequence.

Facilitating climate adaptation: The resilience adaptation feasibility tool (RAFT) framework

ABSTRACT There is a disconnect between the urgency of responding to the threats posed by climate change and the existing resources, technical capacity, and political will necessary to engage in resilience planning and climate action. A variety of frameworks for bridging these gaps exist, but few have emerged through an iterative process of piloting and refining strategies to bridge these gaps on the ground. The Resilience Adaptation Feasibility Tool (RAFT) framework builds upon decades of experience designing and implementing community engagement processes and offers an alternate model for advancing resilience and climate adaptation planning that leverages social learning to build consensus around shared values and community priorities. This paper documents the RAFT process, situates it within the context of climate adaptation planning research, and articulates its specific strengths as a flexible and portable model for engaging the public in preparing for climate change impacts.

Transformasi Tradisi Mangalehen Tuor dalam Upacara Perkawinan Mandailing Pasca Migrasi ke Kota Medan

This research examines the transformation of the Mangalehen Tuor tradition in Mandailing ethnic wedding ceremonies after migration to Medan City. This tradition has undergone significant adaptation in the context of rapid urbanization and intercultural interactions in urban environments. Changes in the implementation of traditions, such as adjustments to the time and place of implementation, as well as changes in participation and delivery of advice, are the main focus of this research. Factors influencing these changes, such as urbanization, intercultural interactions, the influence of the younger generation, economics, and technology, are analyzed to understand the dynamics of cultural adaptation in a broader context. Despite undergoing transformation, efforts to preserve Mandailing cultural values ??remain a priority, reflected in cultural education efforts, community activities and technology integration. This research provides insight into how ethnic communities manage and maintain their cultural identity amidst the ever-growing challenges of globalization and modernization.

BFT‐Net: A transformer‐based boundary feedback network for kidney tumour segmentation

AbstractKidney tumours are among the top ten most common tumours, the automatic segmentation of medical images can help locate tumour locations. However, the segmentation of kidney tumour images still faces several challenges: firstly, there is a lack of renal tumour endoscopic datasets and no segmentation techniques for renal tumour endoscopic images; secondly, the intra‐class inconsistency of tumours caused by variations in size, location, and shape of renal tumours; thirdly, difficulty in semantic fusion during decoding; and finally, the issue of boundary blurring in the localization of lesions. To address the aforementioned issues, a new dataset called Re‐TMRS is proposed, and for this dataset, the transformer‐based boundary feedback network for kidney tumour segmentation (BFT‐Net) is proposed. This network incorporates an adaptive context extract module (ACE) to emphasize local contextual information, reduces the semantic gap through the mixed feature capture module (MFC), and ultimately improves boundary extraction capability through end‐to‐end optimization learning in the boundary assist module (BA). Through numerous experiments, it is demonstrated that the proposed model exhibits excellent segmentation ability and generalization performance. The mDice and mIoU on the Re‐TMRS dataset reach 91.1% and 91.8%, respectively.

A NSC-34 cell line-derived spheroid model: Potential and challenges for in vitro evaluation of neurodegeneration.

Three-dimensional (3D) spheroid models aim to bridge the gap between traditional two-dimensional (2D) cultures and the complex in vivo tissue environment. These models, created by self-clustering cells to mimic a 3D environment with surrounding extracellular framework, provide a valuable research tool. The NSC-34 cell line, generated by fusing mouse spinal cord motor neurons and neuroblastoma cells, is essential for studying neurodegenerative diseases like amyotrophic lateral sclerosis (ALS), where abnormal protein accumulation, such as TAR-DNA-binding protein 43 (TDP-43), occurs in affected nerve cells. However, NSC-34 behavior in a 3D context remains underexplored, and this study represents the first attempt to create a 3D model to determine its suitability for studying pathology. We generated NSC-34 spheroids using a nonadhesive hydrogel-based template and characterized them for 6 days. Light microscopy revealed that NSC-34 cells in 3D maintained high viability, a distinct round shape, and forming stable membrane connections. Scanning electron microscopy identified multiple tunnel-like structures, while ultrastructural analysis highlighted nuclear bending and mitochondria alterations. Using inducible GFP-TDP-43-expressing NSC-34 spheroids, we explored whether 3D structure affected TDP-43 expression, localization, and aggregation. Spheroids displayed nuclear GFP-TDP-43 expression, albeit at a reduced level compared with 2D cultures and generated both TDP-35 fragments and TDP-43 aggregates. This study sheds light on the distinctive behavior of NSC-34 in 3D culture, suggesting caution in the use of the 3D model for ALS or TDP-43 pathologies. Yet, it underscores the spheroids' potential for investigating fundamental cellular mechanisms, cell adaptation in a 3D context, future bioreactor applications, and drug penetration studies. RESEARCH HIGHLIGHTS: 3D spheroid generation: NSC-34 spheroids, developed using a hydrogel-based template, showed high viability and distinct shapes for 6 days. Structural features: advanced microscopy identified tunnel-like structures and nuclear and mitochondrial changes in the spheroids. Protein dynamics: the study observed how 3D structures impact TDP-43 behavior, with altered expression but similar aggregation patterns to 2D cultures. Research implications: this study reveals the unique behavior of NSC-34 in 3D culture, suggests a careful approach to use this model for ALS or TDP-43 pathologies, and highlights its potential in cellular mechanism research and drug testing applications.