Complex training

Transcription factors (TFs) are proteins essential for regulating genetic transcriptions by binding to transcription factor binding sites (TFBSs) in DNA sequences. Accurate predictions of TFBSs can contribute to the design and construction of metabolic regulatory systems based on TFs. Although various deep-learning algorithms have been developed for predicting TFBSs, the prediction performance needs to be improved. This paper proposes a bidirectional encoder representations from transformers (BERT)-based model, called BERT-TFBS, to predict TFBSs solely based on DNA sequences...

Neuromodulators have been shown to alter the temporal profile of short-term synaptic plasticity (STP); however, the computational function of this neuromodulation remains unexplored. Here, we propose that the neuromodulation of STP provides a general mechanism to scale neural dynamics and motor outputs in time and space. We trained recurrent neural networks that incorporated STP to produce complex motor trajectories-handwritten digits-with different temporal (speed) and spatial (size) scales. Neuromodulation of STP produced temporal and spatial scaling of the learned dynamics and enhanced temporal or spatial generalization compared to standard training of the synaptic weights in the absence of STP...

Approximation biases of value functions are considered a key problem in reinforcement learning (RL). In particular, existing RL algorithms are hindered by overestimation and underestimation biases, i.e., value mismatching between RL's actual returns and action-value approximations limits the performance of RL algorithms. In this article, we first develop a new synthesis loss function for RL's action-value estimation integrating a regularization term and a modified "clipped double Q -learning" structure for solving overestimation and underestimation biases...

BACKGROUND: Magnetic particle imaging (MPI) is a recently developed, non-invasive in vivo imaging technique to map the spatial distribution of superparamagnetic iron oxide nanoparticles (SPIONs) in animal tissues with high sensitivity and speed. It is a challenge to reconstruct images directly from the received signals of MPI device due to the complex physical behavior of the nanoparticles. System matrix and X-space are two commonly used MPI reconstruction methods, where the former is extremely time-consuming and the latter usually produces blurry images...

Spiking neural networks (SNN), also often referred to as the third generation of neural networks, carry the potential for a massive reduction in memory and energy consumption over traditional, second-generation neural networks. Inspired by the undisputed efficiency of the human brain, they introduce temporal and neuronal sparsity, which can be exploited by next-generation neuromorphic hardware. Energy efficiency plays a crucial role in many engineering applications, for instance, in structural health monitoring...

In order to improve results, this work investigates how the Freelance Model (FM), Fractional Derivative (FD), and Artificial Neural Network (ANN) may all function together. We suggest a new method that combines the varied skills of freelancers with the precision of fractional derivatives and the adaptability of neural networks to maximize the benefits of each. This proposed strategy provides a new perspective to the computational methodologies and holds a promising impact on diverse industries. Future developments and applications can be made possible by this promising path toward enhanced performance in complex systems and data-driven areas...

Globally, chilli (Capsicum annuum L.) is one of the most economically important and widely cultivated crop which elicits ethnomedicinal and nutritional potential as well as enhancing the taste and aroma of foods (Ayob et al., 2022; Kiran et al., 2020). Anthracnose disease is regarded as a prime constraint in chilli production, leading to enormous losses in tropical and subtropical countries. In September 2022, chilli fruit displaying sunken, shriveled and dark bown to black lesion with abundant acervuli on the surface was obtained from Flacq, Mauritius...

BACKGROUND: Despite decades of evidence demonstrating the efficacy of hypertension care delivery in reducing morbidity and mortality, a majority of hypertension cases remain uncontrolled. There is an urgent need to elucidate and address multilevel facilitators and barriers clinical staff face in delivering evidence-based hypertension care, patients face in accessing it, and clinical systems face in sustaining it. Through a rigorous pre-implementation evaluation, we aimed to identify facilitators and barriers bearing the potential to affect the planned implementation of a multilevel technology-facilitated hypertension management trial across six primary care sites in a large federally qualified health center (FQHC) in New York City...

Since their inception more than 50 years ago, Brain-Computer Interfaces (BCIs) have held promise to compensate for functions lost by people with disabilities through allowing direct communication between the brain and external devices. While research throughout the past decades has demonstrated the feasibility of BCI to act as a successful assistive technology, the widespread use of BCI outside the lab is still beyond reach. This can be attributed to a number of challenges that need to be addressed for BCI to be of practical use including limited data availability, limited temporal and spatial resolutions of brain signals recorded non-invasively and inter-subject variability...

BACKGROUND: Seafarers' diets are often high in fat, sugar and calories, thus contributing to an increased risk of obesity, metabolic syndrome and cardiovascular disease. The multitude of obstacles to healthy eating in the on-board environment on merchant ships makes it essential to find new approaches for health promotion. This study explored seafarers' attitudes, the status quo of support measures and chances to improve nutrition on merchant ships from the perspective of crews and cooks...

BACKGROUND: There is a growing interest in employing community wellness worker models in Indigenous populations to address inequities in healthcare access and outcomes, concerns about shortage in health and mental health human resources, and escalating burden of chronic and complex diseases driving significant increase in health services demand and costs. A thorough review of Indigenous community wellness worker models has yet to be conducted. This rapid review sought to outline the characteristics of a community wellness worker model in Indigenous contexts across the globe, detailing factors shaping implementation challenges and success...

BACKGROUND: Antimicrobial resistance (AMR) is a pressing global health concern driven by inappropriate antibiotic use, which is in turn influenced by various social, systemic, and individual factors. This study, nested within FIND's AMR Diagnostic Use Accelerator clinical trial in Nepal, aimed to (i) explore the perspectives of patients, caregivers, and healthcare workers (HCWs) on antibiotic prescription adherence and (ii) assess the impact of a training and communication (T&C) intervention on adherence to antibiotic prescriptions...

Mohs Micrographic Surgery (MMS) is effective for treating common cutaneous malignancies, but complex repairs may often present challenges for reconstruction. This paper explores the potential of three-dimensional (3D) bioprinting in MMS, offering superior outcomes compared to traditional methods. 3D printing technologies show promise in advancing skin regeneration and refining surgical techniques in dermatologic surgery. A PubMed search was conducted using the following keywords: "Three-dimensional bioprinting" OR "3-D printing" AND "Mohs" OR "Mohs surgery" OR "Surgery...

In recent years, there has been a growing prevalence of deep learning in various domains, owing to advancements in information technology and computing power. Graph neural network methods within deep learning have shown remarkable capabilities in processing graph-structured data, such as social networks and traffic networks. As a result, they have garnered significant attention from researchers.However, real-world data often face challenges like data sparsity and missing labels, which can hinder the performance and generalization ability of graph convolutional neural networks...

After stroke rehabilitation, patients need to reintegrate back into their daily life, workplace and society. Reintegration involves complex processes depending on age, sex, stroke severity, cognitive, physical, as well as socioeconomic factors that impact long-term outcomes post-stroke. Moreover, post-stroke quality of life can be impacted by social risks of inadequate family, social, economic, housing and other supports needed by the patients. Social risks and barriers to successful reintegration are poorly understood yet critical for informing clinical or social interventions...

Cholangiocarcinoma (CCA) is a highly malignant biliary tract cancer with currently suboptimal diagnostic and prognostic approaches. We present a novel system to monitor CCA using exosomal circular RNA (circRNA) via serum and biliary liquid biopsies. A pilot cohort consisting of patients with CCA-induced biliary obstruction (CCA-BO, n = 5) and benign biliary obstruction (BBO, n = 5) was used to identify CCA-derived exosomal circRNAs through microarray analysis. This was followed by a discovery cohort (n = 20) to further reveal a CCA-specific circRNA complex (hsa-circ-0000367, hsa-circ-0021647, and hsa-circ-0000288) in both bile and serum exosomes...

Plasma medicine is gaining attraction in the medical field, particularly the use of cold atmospheric plasma (CAP) in biomedicine. The chemistry of the plasma is complex, and the reactive oxygen species (ROS) within it are the basis for the biological effect of CAP on the target. Understanding how the oxidative power of ROS responds to diverse plasma parameters is vital for standardizing the effective application of CAP. The proven applicability of machine learning (ML) in the field of medicine is encouraging, as it can also be applied in the field of plasma medicine to correlate the oxidative strength of plasma-treated water (PTW) according to different parameters...

OBJECTIVES: The surgical training of gynecologic oncology (GO) fellows is critical to providing excellent care to women with gynecologic cancers. We sought to evaluate changes in techniques and surgical volumes over an 18-year period among established GO fellowships across the US. METHODS: We emailed surveys to 30 GO programs that had trained fellows for at least 18 years. Surveys requested the number of surgical cases performed by a fellow for seventeen surgical procedures over each of five-time intervals...

MOTIVATION: Single cell profiling has become a common practice to investigate the complexity of tissues, organs and organisms. Recent technological advances are expanding our capabilities to profile various molecular layers beyond the transcriptome such as, but not limited to, the genome, the epigenome and the proteome. Depending on the experimental procedure, these data can be obtained from separate assays or from the very same cells. Despite development of computational methods for data integration is an active research field, most of the available strategies have been devised for the joint analysis of two modalities and cannot accommodate a high number of them...

Nearly one quarter (600,000) of all neonatal deaths worldwide per year occur in India. To reduce neonatal mortality, the Indian Ministry of Health and Family Welfare established neonatal care units, including neonatal intensive care units and specialized neonatal care units to provide immediate care at birth, resuscitation for asphyxiation, postnatal care, follow up for high-risk newborns, immunization, and referral for additional or complex healthcare services. Despite these efforts, neonatal mortality remains high, and measures taken to reduce mortality have been severely challenged by multiple problems caused by the Covid-19 pandemic...