knowledge network

Crime remains a crucial concern regarding ensuring a safe and secure environment for the public. Numerous efforts have been made to predict crime, emphasizing the importance of employing deep learning approaches for precise predictions. However, sufficient crime data and resources for training state-of-the-art deep learning-based crime prediction systems pose a challenge. To address this issue, this study adopts the transfer learning paradigm. Moreover, this study fine-tunes state-of-the-art statistical and deep learning methods, including Simple Moving Averages (SMA), Weighted Moving Averages (WMA), Exponential Moving Averages (EMA), Long Short Term Memory (LSTM), Bi-directional Long Short Term Memory (BiLSTMs), and Convolutional Neural Networks and Long Short Term Memory (CNN-LSTM) for crime prediction...

Caricature generation aims to translate portrait photos into caricatures with exaggerated and hand-drawn artistic styles. Previous methods faced challenges in creating diverse and meaningful exaggeration effects, yielding unsatisfactory and uncontrollable results. To overcome this, we proposed ETCari, a novel weakly supervised exaggeration transfer network. ETCari enables the learning of diverse exaggeration caricature styles from various artists, better meeting individual customization requirements and achieving diversified exaggeration while retaining identity features...

BACKGROUND: The COVID-19 pandemic has had a significant global impact, with millions of cases and deaths. Research highlights the persistence of symptoms over time (post-COVID-19 condition), a situation of particular concern in children and young people with symptoms. Social media such as Twitter (subsequently rebranded as X) could provide valuable information on the impact of the post-COVID-19 condition on this demographic. OBJECTIVE: With a social media analysis of the discourse surrounding the prevalence of post-COVID-19 condition in children and young people, we aimed to explore the perceptions of health care workers (HCWs) concerning post-COVID-19 condition in children and young people in the United Kingdom between January 2021 and January 2022...

Respiratory syncytial virus (RSV) is the most common pathogen causing acute lower respiratory tract infection in infants and children. Due to limited knowledge of the pathological and molecular mechanisms of immunodeficiency underlying RSV disease, there is currently a lack of an approved and effective RSV vaccine to combat RSV infections. This study aimed to identify genes associated with immune dysfunction using bioinformatics methods to gain insights into the role of dysregulated immune genes in RSV disease progression, and to predict potential therapeutic drugs by targeting dysregulated immune-related genes...

PURPOSE: Knowledge of neurovascular anatomy is vital for neurosurgeons, neurologists, neuro-radiologists and anatomy students, amongst others, to fully comprehend the brain's anatomy with utmost depth. This paper aims to enhance the foundational knowledge of novice physicians in this area. METHOD: A comprehensive literature review was carried out by searching the PubMed and Google Scholar databases using primary keywords related to brain vasculature, without date restrictions...

OBJECTIVE: To analyze knowledge about priority topics in mental health care of strategic actors who work in regions where the Health Care Planning (PAS) methodology is used. METHODS: This is a quantitative, descriptive, cross-sectional, and observational study carried out with professionals from six health regions, distributed in three Brazilian states (Goiás, Rondônia and Maranhão) and linked to the project "Saúde mental na APS" (Mental health in PHC) of the Programa de Apoio ao Desenvolvimento Institucional do Sistema Único de Saúde (Proadi-SUS - Institutional Development Support Program of the Brazilian Unified Health System)...

OBJECTIVES: This research study aimed to discover how dementia affecting older people was perceived, experienced, and managed by stakeholders in the Pacific Island country of Fiji. METHOD: A transformational grounded theory approach was used. Semi-structured interviews and focus groups with key stakeholders in the major towns of Suva, Lautoka, and Nadi were carried out. Transcripts were analysed in line with transformational grounded theory methods. RESULTS: A total of 50 participants (40 service providers, eight family caregivers, one person with dementia, and one village elder) shared their views and experiences about dementia...

Plants engage in a variety of interactions, including sharing nutrients through common mycorrhizal networks (CMNs), which are facilitated by arbuscular mycorrhizal fungi (AMF). These networks can promote the establishment, growth, and distribution of limited nutrients that are important for plant growth, which in turn benefits the entire network of plants. Interactions between plants and microbes in the rhizosphere are complex and can either be socialist or capitalist in nature, and the knowledge of these interactions is equally important for the progress of sustainable agricultural practice...

INTRODUCTION: We aimed to investigate the overlapping epidemiologies of human immunodeficiency virus (HIV), herpes simplex virus type 2 (HSV-2), chlamydia, gonorrhea, and syphilis in sexual networks of men who have sex with men (MSM), and to explore to what extent the epidemiology of one sexually transmitted infection (STI) relates to or differs from that of another STI. METHODS: An individual-based Monte Carlo simulation model was employed to simulate the concurrent transmission of STIs within diverse sexual networks of MSM...

BACKGROUND AND OBJECTIVES: Prior research has highlighted the beneficial impact of social networks and social support on older adults' physical and psychosocial well-being. However, the impact of the relationship between chronic illness and social networks on the psychosocial well-being of older Nigerians remains understudied. This study explored how older Nigerians with chronic illnesses navigate the physical, mental, and emotional changes due to their chronic disease diagnosis within their social contexts...

The etiopathogenesis of type 1 diabetes mellitus (T1DM) is a complex multifactorial process that involves an intricate network of genetic, epigenetic, immunological, and environmental factors. Despite the advances in recent years, some aspects of the mechanisms involved in triggering the disease are still unclear. Infections with certain viruses have been suggested as possible environmental triggers for the autoimmune process that leads to selective and progressive destruction of pancreatic β-cells and insufficiency of insulin production, which is its hallmark...

Abrocitinib is a highly selective Janus kinase 1 (JAK1) inhibitor that can block a multitude of inflammatory signaling pathways that underlie atopic dermatitis (AD). In addition, abrocitinib inhibits JAK1 signaling in sensory neurons to alleviate acute and chronic pruritus during AD. However, substantial variations in efficacy and safety risks remain due to variations in doses applied in clinical use. Therefore for the present study, differences in the efficacy and tolerability of 100 and 200 mg abrocitinib for treating pruritus and eczema symptoms in patients with moderate-to-severe AD were evaluated compared with placebo...

Biological networks are often modular. Explanations for this peculiarity either assume an adaptive advantage of a modular design such as higher robustness, or attribute it to neutral factors such as constraints underlying network assembly. Interestingly, most insights on the origin of modularity stem from models in which interactions are either determined by highly simplistic mechanisms, or have no mechanistic basis at all. Yet, empirical knowledge suggests that biological interactions are often mediated by complex structural or behavioural traits...

The latest breakthroughs in spatially resolved transcriptomics technology offer comprehensive opportunities to delve into gene expression patterns within the tissue microenvironment. However, the precise identification of spatial domains within tissues remains challenging. In this study, we introduce AttentionVGAE (AVGN), which integrates slice images, spatial information and raw gene expression while calibrating low-quality gene expression. By combining the variational graph autoencoder with multi-head attention blocks (MHA blocks), AVGN captures spatial relationships in tissue gene expression, adaptively focusing on key features and alleviating the need for prior knowledge of cluster numbers, thereby achieving superior clustering performance...

BACKGROUND: Microbes play vital roles across coral reefs both in the environment and inside and upon macrobes (holobionts), where they support critical functions such as nutrition and immune system modulation. These roles highlight the potential ecosystem-level importance of microbes, yet most knowledge of microbial functions on reefs is derived from a small set of holobionts such as corals and sponges. Declining seawater pH - an important global coral reef stressor - can cause ecosystem-level change on coral reefs, providing an opportunity to study the role of microbes at this scale...

BACKGROUND: Although the importance of context in implementation science is not disputed, knowledge about the actual impact of external context variables on implementation processes remains rather fragmented. Current frameworks, models, and studies merely describe macro-level barriers and facilitators, without acknowledging their dynamic character and how they impact and steer implementation. Including organizational theories in implementation frameworks could be a way of tackling this problem...

The mechanism by which mammalian liver cell responses are coordinated during tissue homeostasis and perturbation is poorly understood, representing a major obstacle in our understanding of many diseases. This knowledge gap is caused by the difficulty involved with studying multiple cell types in different states and locations, particularly when these are transient. We have combined Stereo-seq (spatiotemporal enhanced resolution omics-sequencing) with single-cell transcriptomic profiling of 473,290 cells to generate a high-definition spatiotemporal atlas of mouse liver homeostasis and regeneration at the whole-lobe scale...

Accurate and efficient motion estimation is a crucial component of real-time ultrasound elastography (USE). However, obtaining radiofrequency ultrasound (RF) data in clinical practice can be challenging. In contrast, although B-mode (BM) data is readily available, elastographic data derived from BM data results in sub-optimal elastographic images. Furthermore, existing conventional ultrasound devices (e.g., portable devices) cannot provide elastography modes, which has become a significant obstacle to the widespread use of traditional ultrasound devices...

The current epoch in fisheries science has been driven by continual advances in laboratory techniques and  increasingly sophisticated approaches to analysing datasets. We now have the scientific knowledge and tools to proactively identify obstacles to the sustainable management of marine resources. However, in addition to technological advances, there are predicted global environmental changes, each with inherent implications for fisheries. The 2023 symposium of the Fisheries Society of the British Isles called for "open and constructive knowledge exchange between scientists, stakeholders, managers and policymakers" (https://fsbi...

The recent prevalence of deep neural networks has led semantic segmentation networks to achieve human-level performance in the medical field, provided they are given sufficient training data. However, these networks often fail to generalize when tasked with creating semantic maps for out-of-distribution images, necessitating re-training on new distributions. This labor-intensive process requires expert knowledge for generating training labels. In the medical field, distribution shifts can naturally occur due to the choice of imaging devices, such as MRI or CT scanners...