Optical properties of apple skin and flesh in the wavelength range from 350 to 2200 nm

Optical measurement of fruit quality is challenging due to the presence of a skin around the fruit flesh and the multiple scattering by the structured tissues. To gain insight in the light-tissue interaction, the optical properties of apple skin and flesh tissue are estimated in the 350-2200nm range for three cultivars. For this purpose, single integrating sphere measurements are combined with inverse adding- doubling. The observed absorption coefficient spectra are dominated by water in the near infrared and by pigments and chlorophyll in the visible region, whose concentrations are much higher in skin tissue. The scattering coefficient spectra show the monotonic decrease with increasing wavelength typical for biological tissues with skin tissue being approximately three times more scattering than flesh tissue. Comparison to the values from time-resolved spectroscopy reported in literature showed comparable profiles for the optical properties, but overestimation of the absorption coefficient values, due to light losses

Catalyst structure and C-O activation during Fischer-Tropsch Synthesis

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Prediction of ‘Nules Clementine’ mandarin susceptibility to rind breakdown disorder using Vis/NIR spectroscopy

The use of diffuse reflectance visible and near infrared (Vis/NIR) spectroscopy was explored as a non-destructive technique to predict ‘Nules Clementine’ mandarin fruit susceptibility to rind breakdown (RBD) disorder by detecting rind physico-chemical properties of 80 intact fruit harvested from different canopy positions. Vis/NIR spectra were obtained using a LabSpec® spectrophotometer. Reference physico-chemical data of the fruit were obtained after 8 weeks of storage at 8 °C using conventional methods and included RBD, hue angle, colour index, mass loss, rind dry matter, as well as carbohydrates (sucrose, glucose, fructose, total carbohydrates), and total phenolic acid concentrations. Principal component analysis (PCA) was applied to analyse spectral data to identify clusters in the PCA score plots and outliers. Partial least squares (PLS) regression was applied to spectral data after PCA to develop prediction models for each quality attribute. The spectra were subjected to a test set validation by dividing the data into calibration (n = 48) and test validation (n = 32) sets. An extra set of 40 fruit harvested from a different part of the orchard was used for external validation. PLS-discriminant analysis (PLS-DA) models were developed to sort fruit based on canopy position and RBD susceptibility. Fruit position within the canopy had a significant influence on rind biochemical properties. Outside fruit had higher rind carbohydrates, phenolic acids and dry matter content and lower RBD index than inside fruit. The data distribution in the PCA and PLS-DA models displayed four clusters that could easily be identified. These clusters allowed distinction between fruit from different preharvest treatments. NIR calibration and validation results demonstrated that colour index, dry matter, total carbohydrates and mass loss were predicted with significant accuracy, with residual predictive deviation (RPD) for prediction of 3.83, 3.58, 3.15 and 2.61, respectively. The good correlation between spectral information and carbohydrate content demonstrated the potential of Vis/NIR as a non-destructive tool to predict fruit susceptibility to RBD

Autocatalytic role of molecular hydrogen in copper-catalyzed transfer hydrogenation of ketones

Catalytic transfer hydrogenation of ketones and aldehydes is generally accepted to follow a dehydrogenation-hydrogenation mechanism on copper, which makes the increased hydrogenation rate and selectivity rather puzzling. Using first-principles microkinetics on a Cu(111) surface, we show that, rather than a dehydrogenation-hydrogenation mechanism, there is also direct proton transfer between the sacrificial alcohol and the reacting ketone. The ketone is hydrogenated to a stable alkoxy intermediate using surface hydrogen. This alkoxy intermediate is subsequently hydrogenated to the alcohol product via direct proton transfer from the sacrificial alcohol, also forming a sacrificial alkoxy intermediate. To close the catalytic cycle, the sacrificial alkoxy species dehydrogenates, forming its corresponding ketone. We also observed a surprising catalytic effect of molecular hydrogen, which can be explained by the rate-controlling step in transfer hydrogenation: the direct hydrogenation of the ketone to its alkoxy intermediate by surface hydrogen. Under all realistic reaction conditions, this step has the highest degree of rate control

The intramolecular dynamics of a rigid yet twisty 'Ferrocenyl' TetraPhosphine : served with some 31P-NMR delicacy

Polydentate ferrocenyl phosphines equipped with bulky functional groups are regarded as rigid ligands capable of stabilizing and/or activating a broad range of chemical compounds such as smaller complexes (being formed e.g. in transition metal-catalyzed cross coupling reactions), nanoparticles, or even larger surfaces. The fruitful rigidity of these fascinating molecular species originates from the internal steric constraints imposed by the substituents; hence, the rotational reorientation of the Cp rings around the vertical 5-fold symmetry axis is hampered, and a permanent polydentate phosphine ‘cage’ is created (see figure). Latter construction then provides a large variety of coordination modes for the actual substrate what is the core structural feature being responsible for the diverse applicability spectrum. If such ferrocenyl phosphine is investigated on a sufficiently long i.e. ‘NMR time scale’ however, its decelerated intramolecular motions might be discovered and quantitatively characterized. Indeed, selective 1D 31P-{1H} EXSY {Exchange Spectroscopy} pointed out the exchange of the chemically distinct phosphoruses (green and red spheres below) in the scrutinized Fc(P)4tBu ligand and thus successfully demonstrated the previously unknown rotation (i.e. antiparallel twisting) of the Cp rings around the Fe centre. Series of measurements performed at different temperatures enabled the evaluation of the respective thermodynamic parameters (ΔS#, ΔH#, ΔG#) for which the influence of the solvent was also studied – while the confrontation of the experimental and theoretical values computed by DFT methods completed the analysis of the motion. In fact, the four 31P-s of Fc(P)4tBu composes an AA’BB’ spin system giving rise to a puzzling second order 31P NMR spectrum. Although the respective J-couplings had already been presented reclining upon the output of in silico simulations, a side track of the current work covered the full deduction of the results by the means of a quantum mechanical approach. Besides, the internal ring rotations shed new light on the ’through space’ nature of the JAA’ coupling affecting the inner phosphoruses (red spheres). That is, the interaction showed unquenchable and endured higher ring rotation rates than its actual frequency value what highlighted the intricacy of the magnetization transfer phenomena between the two nuclei. Finally, exchange phenomena were revealed for the complexed state of the ligand as well. According to 2D 1H–1H EXSY spectra, in case of [Pd(II)Br2-Fc(P)4tBu] the familiar twisting of the cyclopentadienyl rings was complemented with the periodic transconnection of the [Pd(II)Br2-] moiety between the bidentate (-PPH2)2 sites – perfectly illustrating the possibility for multiple coordination ways offered by polydentate phosphines

A transfer-learning approach to feature extraction from cancer transcriptomes with deep autoencoders

Publicado en Lecture Notes in Computer Science.The diagnosis and prognosis of cancer are among the more challenging tasks that oncology medicine deals with. With the main aim of fitting the more appropriate treatments, current personalized medicine focuses on using data from heterogeneous sources to estimate the evolu- tion of a given disease for the particular case of a certain patient. In recent years, next-generation sequencing data have boosted cancer prediction by supplying gene-expression information that has allowed diverse machine learning algorithms to supply valuable solutions to the problem of cancer subtype classification, which has surely contributed to better estimation of patient’s response to diverse treatments. However, the efficacy of these models is seriously affected by the existing imbalance between the high dimensionality of the gene expression feature sets and the number of sam- ples available for a particular cancer type. To counteract what is known as the curse of dimensionality, feature selection and extraction methods have been traditionally applied to reduce the number of input variables present in gene expression datasets. Although these techniques work by scaling down the input feature space, the prediction performance of tradi- tional machine learning pipelines using these feature reduction strategies remains moderate. In this work, we propose the use of the Pan-Cancer dataset to pre-train deep autoencoder architectures on a subset com- posed of thousands of gene expression samples of very diverse tumor types. The resulting architectures are subsequently fine-tuned on a col- lection of specific breast cancer samples. This transfer-learning approach aims at combining supervised and unsupervised deep learning models with traditional machine learning classification algorithms to tackle the problem of breast tumor intrinsic-subtype classification.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A full-body motion capture gait dataset of 138 able-bodied adults across the life span and 50 stroke survivors

\ua9 2023, The Author(s).This reference dataset contains biomechanical data of 138 able-bodied adults (21–86 years) and 50 stroke survivors walking bare-footed at their preferred speed. It is unique due to its size, and population, including adults across the life-span and over 70 years, as well as stroke survivors. Full-body kinematics (PiG-model), kinetics and muscle activity of 14 back and lower limbs muscles was collected with a Vicon motion capture system, ground-embedded force plates, and a synchronized surface EMG system. The data is reliable to compare within and between groups as the same methodology and infrastructure were used to gather all data. Both source files (C3D) and post-processed ready-to-use stride-normalized kinematics, kinetics and EMG data (MAT-file, Excel file) are available, allowing high flexibility and accessibility of analysis for both researchers and clinicians. These records are valuable to examine ageing, typical and hemiplegic gait, while also offering a wide range of reference data which can be utilized for age-matched controls during normal walking