The migration of additives from food packaging to food stuffs is kinetically governed by the diffusion coefficient (D) of the additive within the polymer. Food safety authorities have recently allowed the use of mathematical models to predict D, with the additive molecular weight as a single entry parameter. Such models require experimental values to feed the databases, but these values are often scattered. To deal with this issue, a fluorescent chemically homologous series of model additives was synthesized with molecular weights (MW) ranging from 236 g.mol (-1) to 1120 g.mol (-1). This set was then used to collect diffusion coefficients D through confocal fluorescence recovery after photobleaching (FRAP). This microscopic technique allows in situ packaging micro migration tests. The FRAP method was tested against results from the literature before being applied to two different model polystyrenes in a preliminary study to investigate the relationship D = f(MW). Our intermediate objective was to compare various experimental D = f(MW) from our method with predictions from other mathematical or semiempirical models.
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http://dx.doi.org/10.1021/jf802166e | DOI Listing |
PLoS One
January 2025
College of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China.
In speech signal processing, time-frequency analysis is commonly employed to extract the spectrogram of speech signals. While many algorithms exist to achieve this with high-quality results, they often lack the flexibility to adjust the resolution of the extracted spectrograms. However, applications such as speech recognition and speech separation frequently require spectrograms of varying resolutions.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Knight Foundation of Computing & Information Sciences, Florida International University, Miami, FL, United States.
Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.
View Article and Find Full Text PDFJ Mol Model
January 2025
College of Electronics and Information, Xi'an Polytechnic University, Xian, People's Republic of China.
Context: The two-dimensional graphene/MoTe heterostructure holds extensive potential applications in optoelectronic devices, sensors, and catalysts. To expand its optical applications, this study systematically investigates the adsorption stability of metal atoms (Au, Pt, Pd, and Fe) on the graphene/MoTe and their influence on its optoelectronic properties employing first-principles methods. The findings indicate that after the adsorption of Au and Pd, the structure retains its direct bandgap properties, while the adsorption of Pt and Fe exhibits indirect bandgap characteristics.
View Article and Find Full Text PDFTraffic Inj Prev
January 2025
School of Traffic & Transportation Engineering, Changsha University of Science & Technology, Changsha, Hunan, China.
Objective: This study aims to investigate the causes of 2-vehicle collisions involving an autonomous vehicle (AV) and a conventional vehicle (CV). Prior research has primarily focused on the causes of crashes from the perspective of AVs, often neglecting the interactions with CVs.
Method: To address this limitation, the study proposes a classification framework for crash causation patterns in 2-vehicle collisions involving an AV and a CV, considering their interactions.
Neurourol Urodyn
January 2025
Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China.
Objectives: To automatically identify and diagnose bladder outflow obstruction (BOO) and detrusor underactivity (DUA) in male patients with lower urinary tract symptoms through urodynamics exam.
Patients And Methods: We performed a retrospective review of 1949 male patients who underwent a urodynamic study at two institutions. Deep Convolutional Neural Networks scheme combined with a short-time Fourier transform algorithm was trained to perform an accurate diagnosis of BOO and DUA, utilizing five-channel urodynamic data (consisting of uroflowmetry, urine volume, intravesical pressure, abdominal pressure, and detrusor pressure).
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