A Deep Learning-Based Multimodal Architecture to predict Signs of Dementia

This paper proposes a multimodal deep learning architecture combining text and audio information to predict dementia, a disease which affects around 55 million people all over the world and makes them in some cases dependent people. The system was evaluated on the DementiaBank Pitt Corpus dataset, which includes audio recordings as well as their transcriptions for healthy people and people with dementia. Different models have been used and tested, including Convolutional Neural Networks (CNN) for audio classification, Transformers for text classification, and a combination of both in a multimodal ensemble. These models have been evaluated on a test set, obtaining the best results by using the text modality, achieving 90.36% accuracy on the task of detecting dementia. Additionally, an analysis of the corpus has been conducted for the sake of explainability, aiming to obtain more information about how the models generate their predictions and identify patterns in the data.We would like to thank “A way of making Europe” European Regional Development Fund (ERDF) and MCIN/AEI/10.13039/501100011033 for supporting this work under the MoDeaAS project (grant PID2019-104818RB-I00) and AICARE project (grant SPID202200X139779IV0). Furthermore, we would like to thank Nvidia for their generous hardware donation that made these experiments possible

Prácticas alimentarias en madres y estado nutricional de preescolares del AA.HH. Horacio Zeballos Arequipa 2022

La investigación tuvo como objetivo determinar las prácticas alimentarias en madres y estado nutricional de preescolares en el AA.HH. Horacio Zeballos - Arequipa 2022. Estudio cuantitativo, de tipo básico, descriptivo, no experimental y transversal. La muestra fue de 50 madres con niños en edad preescolar. Se aplicó un cuestionario validado y confiable sobre prácticas alimentarias en preescolares y una ficha de observación que se utilizó para evaluar el estado nutricional. Como resultados que el 56% de madres presentan una práctica alimentaria regular, el 24% buena y el 20% mala. En cuanto al estado nutricional según peso para la talla un 54% de preescolares presenta un peso normal para su talla, mientras que el 24% presenta desnutrición aguda, el 14% presenta desnutrición severa y el 8% mantiene sobrepeso. Conclusión: El estado nutricional de preescolares de acuerdo a la talla para la edad, peso para la edad y peso para la talla es normal

Diffusion in disordered systems under iterative measurement

We consider a sequence of idealized measurements of time-separation $\Delta t$ onto a discrete one-dimensional disordered system. A connection with Markov chains is found. For a rapid sequence of measurements, a diffusive regime occurs and the diffusion coefficient $D$ is analytically calculated. In a general point of view, this result suggests the possibility to break the Anderson localization due to decoherence effects. Quantum Zeno effect emerges because the diffusion coefficient $D$ vanishes at the limit $\Delta t \to 0$.Comment: 8 pages, 0 figures, LATEX. accepted in Phys.Rev.

Unravelling anomalous mass transport in antisolvent crystallisation

Antisolvent crystallisation is a process widely applied within the pharmaceutical industry. It relies on the difference in solubility of a solute in two miscible liquids—the solvent and the antisolvent—to create the supersaturation required for crystallisation to occur [1]. Since local supersaturation values affect the properties of the final product [2], mixing plays a major role in this process. However, mass transfer in this context is not well understood, leading to the formation of unwanted crystal phases or to undesired phenomena such as oiling out (i.e. separation of the solute via the formation of a second liquid phase). Traditionally, mixing in the microscale has been described through Fick’s second law. However, this model considers composition gradients as the driving force for mass transfer, instead of the more physically accurate gradient in chemical potential. Thus, it fails to explain non-idealities such as uphill diffusion [3], which is the diffusion of a species against its concentration gradient. Additionally, this model assumes ideal behaviour, but unwanted phenomena, such as oiling out, can occur when non-idealities lead to unexpected regions of the phase diagram. Thus, developing a model that accurately predicts and describes micromixing is essential for understanding and preventing these undesired events. In this work, we propose the modeling of an antisolvent crystallisation system through the Cahn-Hilliard phase-field model [4], coupled with either the Fickian or the Maxwell-Stefan diffusion coefficient. The system, in which the appearance of undesired phenomena has been reported, is formed by water, ethanol, and glycine. Since the Cahn-Hilliard model considers the driving force for mass transfer to be the minimization of the free energy, a better description of the mixing process is expected than through Fickian diffusion. Regarding its comparison with the Maxwell-Stefan model [3], a similar outcome is expected except when close to the spinodal region, in which the Cahn-Hilliard model will prove to be superior. Since this model considers the interphase free energy, it is suitable for the description of phase changes such as spinodal decomposition. Thus, it is also potentially capable of simulating oiling-out. The simulation results will be compared to experimental diffusion measurements obtained through Raman spectroscopy, with the expectation that the Cahn-Hilliard model will adjust better to the experimental results. This framework can greatly enhance our understanding of diffusive mixing processes and liquid-liquid separation phenomena in any chemical process in which diffusion of non-ideal solutions takes place. Ultimately, this will lead to safer, more robust manufacturing of chemical and pharmaceutical products

Bias driven coherent carrier dynamics in a two-dimensional aperiodic potential

We study the dynamics of an electron wave-packet in a two-dimensional square lattice with an aperiodic site potential in the presence of an external uniform electric field. The aperiodicity is described by $\epsilon_{\bf m} = V\cos{(\pi\alpha m_x^{\nu_x})}\cos{(\pi\alpha m_y^{\nu_y})}$ at lattice sites $(m_x, m_y)$, with $\pi \alpha$ being a rational number, and $\nu_x$ and $\nu_y$ tunable parameters, controlling the aperiodicity. Using an exact diagonalization procedure and a finite-size scaling analysis, we show that in the weakly aperiodic regime ($\nu_x,\nu_y < 1$), a phase of extended states emerges in the center of the band at zero field giving support to a macroscopic conductivity in the thermodynamic limit. Turning on the field gives rise to Bloch oscillations of the electron wave-packet. The spectral density of these oscillations may display a double peak structure signaling the spatial anisotropy of the potential landscape. The frequency of the oscillations can be understood using a semi-classical approach.Comment: 16 pages, to appear in Phys. Lett.

In Vivo 6-([18F]Fluoroacetamido)-1-hexanoicanilide PET Imaging of Altered Histone Deacetylase Activity in Chemotherapy-Induced Neurotoxicity

Background. Histone deacetylases (HDACs) regulate gene expression by changing histone deacetylation status. Neurotoxicity is one of the major side effects of cisplatin, which reacts with deoxyribonucleic acid (DNA) and has excellent antitumor effects. Suberoylanilide hydroxamic acid (SAHA) is an HDAC inhibitor with neuroprotective effects against cisplatin-induced neurotoxicity. Purpose. We investigated how cisplatin with and without SAHA pretreatment affects HDAC expression/activity in the brain by using 6-([18F]fluoroacetamido)-1-hexanoicanilide ([18F]FAHA) as a positron emission tomography (PET) imaging agent for HDAC IIa. Materials and Methods. [18F]FAHA and [18F]fluoro-2-deoxy-2-D-glucose ([18F]FDG) PET studies were done in 24 mice on 2 consecutive days and again 1 week later. The mice were divided into three groups according to drug administration between the first and second imaging sessions (Group A: cisplatin 2 mg/kg, twice; Group B: cisplatin 4 mg/kg, twice; Group C: cisplatin 4 mg/kg, twice, and SAHA 300 mg/kg pretreatment, 4 times). Results. The value of [18F]FAHA was increased and the percentage of injected dose/tissue g (% ID/g) of [18F]FDG was decreased in the brains of animals in Groups A and B. The value of [18F]FAHA and % ID/g of [18F]FDG were not significantly different in Group C. Conclusions. [18F]FAHA PET clearly showed increased HDAC activity suggestive of cisplatin neurotoxicity in vivo, which was blocked by SAHA pretreatment

Effect of Ni on MCM-41 in the Adsorption of Nitrogen and Sulfur Compounds to Obtain Ultra-Low-Sulfur Diesel

Adsorption of heterocyclic sulfur and nitrogen compounds like dibenzothiophene (DBT) and quinoline (Q), respectively, was carried out using mesostructured adsorbent MCM-41 and Ni/MCM-41 in calcined (C) and reduced (R) form. These materials were proved in a batch adsorption system using a model fuel diesel: a mixture of dodecane, DBT and Q with the same concentrations of ppmw of sulfur and nitrogen at 313 K and atmospheric pressure. When MCM-41 was impregnated with Ni, an important modification of the adsorption properties was observed, for example, the uptake of DBT was increased and this adsorption was twice in Ni/MCM-41 in reduce form than in the calcined form. On the other hand, for the nitrogen adsorption of Q diminished by 62 and 58%, considering Ni/MCM-41 in reduce form and in calcined form as adsorbent, respectively. This is a significant achievement regarding the desulfurization and denitrogenation, especially for commercial diesel without pretreatment. Moreover, the kinetic results were adjusted with second order considering Q as nitrogen and DBT as sulfur molecule. Data fitting for Q was achieved better by the Langmuir model for all materials than the Freundlich model, meanwhile the experimental adsorption data of DBT was fitted to the Freundlich model for Ni/MCM-41 calcinated and reduced form

Effects of Photoacoustic Imaging and Photothermal Ablation Therapy Mediated by Targeted Hollow Gold Nanospheres in an Orthotopic Mouse Xenograft Model of Glioma

Advancements in nanotechnology have made it possible to create multifunctional nanostructures that can be used simultaneously to image and treat cancers. For example, hollow gold nanospheres (HAuNS) have been shown to generate intense photoacoustic signals and induce efficient photothermal ablation (PTA) therapy. In this study, we used photoacoustic tomography, a hybrid imaging modality, to assess the intravenous delivery of HAuNS targeted to integrins that are overexpressed in both glioma and angiogenic blood vessels in a mouse model of glioma. Mice were then treated with near-infrared laser, which elevated tumor temperature by 20.7°C. We found that PTA treatment significantly prolonged the survival of tumor-bearing mice. Taken together, these results show the feasibility of using a single nanostructure for image-guided local tumor PTA therapy with photoacoustic molecular imaging