Exploration of transfer learning techniques for the prediction of PM.

Modelling of pollutants provides valuable insights into air quality dynamics, aiding exposure assessment where direct measurements are not viable. Machine learning (ML) models can be employed to explore such dynamics, including the prediction of air pollution concentrations, yet demanding extensive training data. To address this, techniques like transfer learning (TL) leverage knowledge from a model trained on a rich dataset to enhance one trained on a sparse dataset, provided there are similarities in data distribution.

Mechanisms of aortic dissection: From pathological changes to experimental and models.

Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants.

Comparison of plastisphere microbiomes during the degradation of conventional and biodegradable mulching films.

Biodegradable mulch films (BDMs) are becoming increasingly popular in agriculture and are emerging as an alternative to conventional polyethylene (PE) films. However, the intricate details surrounding the establishment and growth of microorganisms on BDMs and PE during their degradation in agricultural fields remain unclear. In this study, the succession of bacterial communities in farmland soil and the plastispheres of PE and BDMs were compared through 16S rRNA gene high-throughput sequencing and real-time PCR.

Exploring 1-alkene biosynthesis in bacterial antagonists and jeotgalicoccus sp. ATCC 8456.

Terminal olefins are important platform chemicals, drop-in compatible hydrocarbons and also play an important role as biocontrol agents of plant pathogens. Currently, 1-alkenes are derived from petroleum, although microbial biosynthetic routes are known. Jeotgalicoccus sp.

Rapid, High-resolution and Distortion-free Mapping of Fetal Brain using Multi-echo Radial FLASH and Model-based Reconstruction.

Purpose: To develop a rapid, high-resolution and distortion-free quantitative mapping technique for fetal brain at 3 T.

Methods: A 2D multi-echo radial FLASH sequence with blip gradients is adapted for fetal brain data acquisition during maternal free breathing at 3 T. A calibrationless model-based reconstruction with sparsity constraints is developed to jointly estimate water, fat, and field maps directly from the acquired k-space data.

Effects of spectral manipulations of music mixes on musical scene analysis abilities of hearing-impaired listeners.

Music pre-processing methods are currently becoming a recognized area of research with the goal of making music more accessible to listeners with a hearing impairment. Our previous study showed that hearing-impaired listeners preferred spectrally manipulated multi-track mixes. Nevertheless, the acoustical basis of mixing for hearing-impaired listeners remains poorly understood.

A cellulosic fibre foam as a bicycle helmet impact liner for brain injury mitigation in oblique impacts.

Bulky cellulosic network structures (BRC) with densities between 60 and 130 g/l were investigated as a sustainable alternative to fossil-based foams for impact liners in bicycle helmets. The mechanical properties of BRC foams were characterized across a wide range of strain rates and incorporated into a validated finite element model of a hardshell helmet. Virtual impact tests simulating both consumer information and certification scenarios were conducted to compare BRC-lined helmets against conventional expanded polystyrene (EPS) designs.

Paired nerve stimulation with selective compensation effect.

Background: In this study we investigate the selective compensation of paired peripheral nerves in healthy humans, focusing on distinct axonal conduction velocities in different fibre types. Using paired associative stimulation (PAS) with adjustable parameters, we aimed to modulate and compensate for neuronal activity along the median nerve.

Methods: Six healthy volunteers (3 male, 3 female, aged: 22-49) participated in the current study.

Water-soluble platinum and palladium porphyrins with peripheral ethyl phosphonic acid substituents: synthesis, aggregation in solution, and photocatalytic properties.

Water-soluble porphyrins have garnered significant attention due to their broad range of applications in biomedicine, catalysis, and material chemistry. In this work, water-soluble platinum(II) and palladium(II) complexes with porphyrins bearing ethyl phosphonate substituents, namely, Pt/Pd 10-(ethoxyhydroxyphosphoryl)-5,15-di(-carboxyphenyl)porphyrins (M3m, M = Pt(II), Pd(II)) and Pt/Pd 5,10-bis(ethoxyhydroxyphosphoryl)-10,20-diarylporphyrins (M1d-M3d; aryl = -tolyl (1), mesityl (2), -carboxyphenyl (3)), were synthesized by alkaline hydrolysis of the corresponding diethyl phosphonates M6m and M4d-M6d. NMR, UV-vis, and fluorescence spectroscopy revealed that the mono-phosphonates M3m tend to form aggregates in aqueous media, while the bis-phosphonates M3d exist predominantly as monomeric species across a wide range of concentrations (10-10 M), ionic strengths (0-0.

arterioscope.sim: Enabling Simulations of Blood Flow and Its Impact on Bioimpedance Signals.

Objectives: Early detection of cardiovascular diseases and their pre-existing conditions, arteriosclerosis and atherosclerosis, is crucial to increasing a patient's chance of survival. While imaging technologies and invasive procedures provide a reliable diagnosis, they carry high costs and risks for patients. This study aims to explore impedance plethysmography (IPG) as a non-invasive and affordable alternative for diagnosis.

Transforming precision medicine: The potential of the clinical artificial intelligent single-cell framework.

The editorial, "Clinical and translational mode of single-cell measurements: An artificial intelligent single-cell," introduces the innovative clinical artificial intelligence single-cell (caiSC) system, which merges AI with single-cell informatics to advance real-time diagnostics, disease monitoring, and treatment prediction. By combining clinical data and multimodal molecular inputs, caiSC facilitates personalized medicine, promising enhanced diagnostic precision and tailored therapeutic approaches. Despite its potential, caiSC lacks comprehensive data coverage across cell types and diseases, presenting challenges in data quality and model robustness.

The Effect of Accessibility of Insoluble Substrate on the Overall Kinetics of Enzymatic Degradation.

The enzymatic reaction kinetics on cellulose and other solid substrates is limited by the access of the enzyme to the reactive substrate sites. We introduce a general model in which the reaction rate is determined by the active surface area, and the resulting kinetics consequently reflects the evolving relationship between the exposed substrate surface and the remaining substrate volume. Two factors influencing the overall surface-to-volume ratio are considered: the shape of the substrate particles, characterized by a single numerical parameter related to its dimensionality, and the distribution of the particle sizes.

Phase Characterization and Bioactivity Evaluation of Nucleic Acid-Encapsulated Biomimetically Mineralized ZIF-8.

Metal-organic frameworks (MOFs) provide diverse applications across a wide range of scientific disciplines, including drug/nucleic acid (NA) delivery. In the subclass of MOFs, zeolitic imidazolate framework-8 (ZIF-8) is well regarded due to its exceptional physicochemical properties. Biomolecules can be encapsulated and released under precise conditions within ZIF, making it an important material for materials science and biomedical applications.

Synthesis and characterization of dextran palmitate for extrusion 3D printing.

The fabrication of objects with complex shape and geometry has been greatly facilitated with the advancements in additive manufacturing. While synthetic polymers like ABS and PLA have found widespread use in extrusion 3D printing, other biobased thermoplastics that are both biodegradable and biocompatible could offer strategic advantages over traditional synthetic materials. In this work dextran of low (20 kDa) and medium (40 kDa) molecular weight (MW) was modified with palmitic acid to obtain meltable polymers for extrusion 3D printing/fused deposition modeling additive manufacturing.

Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features.

Purpose: Heart failure (HF) is a clinical syndrome in which structural or functional abnormalities of the heart result in impaired ventricular filling or ejection capacity. In order to improve the adaptability of models to different patient populations and data situations. This study aims to develop predictive models for HF risk using six machine learning algorithms, providing valuable insights into the early assessment and recognition of HF by clinical features.

A simple model for Behavioral Time Scale Synaptic Plasticity (BTSP) provides content addressable memory with binary synapses and one-shot learning.

Recent experimental studies in the awake brain have identified a rule for synaptic plasticity that is instrumental for the instantaneous creation of memory traces in area CA1 of the mammalian brain: Behavioral Time scale Synaptic Plasticity. This one-shot learning rule differs in five essential aspects from previously considered plasticity mechanisms. We introduce a transparent model for the core function of this learning rule and establish a theory that enables a principled understanding of the system of memory traces that it creates.

- a large-scale dataset of 3D medical shapes for computer vision.

Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models).

Expanded Perlite-Reinforced Alginate Xerogels: A Chemical Approach to Sustainable Building and Packaging Materials.

In sustainable construction and packaging, the development of novel bio-based materials is crucial, driving a re-evaluation of traditional components. Lightweight, biodegradable materials, including xerogels, have great potential in architectural and packaging applications. However, reinforcing these materials to improve their mechanical strength remains a challenge.

ESG assessment methodology for emerging technologies: plasma conventional technology for ammonia production.

Environmental, social and governance (ESG) criteria demand that enterprises should not be assessed solely on their financial performance, but also on their environmental, social, and governance performance. This numerical assessment of ESG criteria enables them to be evaluated with the consideration of other financial issues of enterprises' performance and thereby guides financial investments into environmentally and socially responsible firms. ESG, however, solidifies the continuance of conventional technologies but can potentially disadvantage emerging technologies.

Implications of compressive loading of the stomach wall: Interplay between mechanical deformation and microstructure.

During gastric surgery, the stomach wall is compressed with clamps and sutures or staple lines. These short- and long-term deformations can severely compromise the integrity of the tissue and make it difficult for the stomach wall to respond and remodel to the new loading conditions. Consequently, serious intra- and postoperative complications such as the formation of leaks during bariatric surgeries, can be associated with these immense tissue deformations.

Simultaneous encoding of speed, distance, and direction in discrete reaching: an EEG study.

The complicated processes of carrying out a hand reach are still far from fully understood. In order to further the understanding of the kinematics of hand movement, the simultaneous representation of speed, distance, and direction in the brain is explored.We utilized electroencephalography (EEG) signals and hand position recorded during a four-direction center-out reaching task with either quick or slow speed, near and far distance.